Synovial sarcoma is among the most common non-rhabdomyosarcoma soft tissue sarcomas in adolescents and young adults, yet it remains a rare and formidable diagnosis. Tumors arising in the shoulder region account for approximately 6 percent of all synovial sarcomas, and the disease typically does not originate from inside the joint but from the surrounding soft tissues. The tumor often progresses slowly, taking months to years before patients present for evaluation, which can result in a significant delay in diagnosis. In this case, the girl’s symptoms had been present for several months and had gradually worsened, eventually prompting clinical evaluation when the pain began interfering with daily activities and sports participation. Physical examination revealed localized bulging of the right shoulder, reduced range of motion, and tenderness on palpation of the periarticular region.

The diagnostic journey began with plain radiography and ultrasound of the shoulder. The radiograph revealed a soft tissue mass of increased density adjacent to the joint, without significant calcification or osseous involvement. Subsequent ultrasound demonstrated a large heterogeneous soft tissue mass involving the periarticular region and extending into adjacent muscular compartments. The lesion appeared poorly defined, with marked internal heterogeneity—findings that immediately raised suspicion for an underlying malignant soft tissue tumor. These initial assessments, while not diagnostic on their own, served as the critical first step in a multimodal imaging strategy that would ultimately characterize the tumor from both anatomical and functional perspectives.

Magnetic resonance imaging, performed on a 1.5-T scanner with a standard musculoskeletal protocol including T1-weighted, T2-weighted, and STIR sequences without intravenous contrast medium, demonstrated a large soft tissue mass measuring approximately 18 centimeters in maximum diameter. The lesion showed a multilobulated configuration with marked internal heterogeneity and areas of variable signal intensity on T2-weighted sequences, characterized by both cystic and solid components, with no enhancement in the areas containing cysts. Fluid-fluid levels were noted together with the characteristic triple sign, consisting of the coexistence of low, intermediate, and high signal intensity regions. These features suggested the diagnosis of synovial sarcoma. The tumor involved several muscles of the shoulder girdle, including the deltoid, infraspinatus, and subscapularis muscles, and extended into the surrounding soft tissues. MRI is considered the reference modality for local staging due to its excellent soft tissue contrast and its ability to assess tumor extent and relationship with surrounding structures, information that is essential for surgical planning and for defining target volumes in radiotherapy.

However, MRI findings in synovial sarcoma are not pathognomonic, and additional imaging techniques are often required to fully characterize the disease. In this case, the evaluation of possible bone involvement was initially challenging due to periosteal reaction and inflammatory changes. For this reason, contrast-enhanced computed tomography was performed and confirmed the absence of direct invasion of the humeral head. Moreover, contrast-enhanced CT provided important information on the enhancement pattern of the lesion, contributing to the characterization of tumor heterogeneity. Most synovial sarcomas demonstrate heterogeneous enhancement with reduced or absent enhancement in areas of cystic necrosis or internal septations, and this case was no exception. The CT findings, combined with the MRI data, allowed clinicians to confidently exclude bone invasion while gaining a deeper understanding of the tumor’s complex internal architecture.

To complete staging, a whole-body 18F-FDG PET/CT was performed three weeks after the MRI, acquired 60 minutes after tracer injection according to the institutional pediatric oncology protocol. The examination revealed a highly heterogeneous pattern of metabolic activity within the primary tumor, with a maximum standardized uptake value (SUVmax) of 12.3, a mean activity (SUVmean) of 1.5, and a peak activity (SUVpeak) of 7.7. Areas of intense uptake corresponded to viable tumor tissue, while regions of absent uptake corresponded to necrosis or fluid components. A key diagnostic finding was the identification of metabolically active lymph nodes in the ipsilateral axilla—information that had direct implications for disease staging and therapeutic planning. PET/CT proved particularly valuable in identifying regional lymph node involvement that was not clearly detected on morphological imaging, confirming its well-recognized higher sensitivity in detecting nodal and distant disease in pediatric sarcomas.

Histopathological examination of the excisional biopsy confirmed the diagnosis of monophasic poorly differentiated synovial sarcoma. Molecular testing demonstrated the presence of the characteristic chromosomal translocation t(X;18)(p11;q11) involving the SS18 gene, the genetic hallmark of this tumor type. Following multidisciplinary discussion, the patient started multimodal therapy consisting of combination chemotherapy with ifosfamide and doxorubicin, according to the EpSSG NRSTS 2005 protocol. After completion of three cycles of chemotherapy, which were well tolerated with no relevant treatment-related complications, a follow-up imaging evaluation was performed to assess treatment response.

The follow-up imaging told a fascinating story about the biology of treatment response. Contrast-enhanced CT demonstrated persistent tumor volume without clear evidence of disease progression, but with changes in the enhancement pattern of the solid tumor component. Meanwhile, the whole-body 18F-FDG PET/CT demonstrated a clear reduction in metabolic activity of the primary tumor compared with baseline, consistent with an early metabolic response to therapy. SUVmax decreased from 12.3 at baseline to 6.7 at follow-up, and SUVpeak decreased from 7.7 to 2.6. These structural changes corresponded to the reduction in metabolic activity observed on follow-up PET/CT, suggesting an early biological response to therapy preceding measurable tumor shrinkage. This finding highlights the ability of functional imaging to detect early treatment response before morphological tumor shrinkage becomes evident, a phenomenon that has been reported in high-grade soft tissue sarcomas and supports the role of PET/CT in early response assessment and treatment monitoring. While tumor size remains a widely used parameter for response evaluation, changes in metabolic activity may represent earlier and more sensitive indicators of therapeutic effectiveness—information that would not have been captured by size-based criteria alone.

Semiquantitative metabolic parameters, including SUVmax, SUVmean, and SUVpeak, are commonly used to characterize tumor biology and monitor response to therapy. Among these, SUVpeak, which reflects metabolic activity within a small, standardized tumor volume, may provide a more robust and reproducible measure than single-voxel metrics in heterogeneous lesions. Although considerable variability exists in reported thresholds due to differences in scanners and acquisition protocols, in synovial sarcoma a baseline SUVmax above approximately 5 has been associated with higher histological grade and worse clinical outcomes, supporting its role as a clinically relevant imaging biomarker for risk stratification. In addition, metabolic imaging with 18F-FDG PET/CT can help identify metabolically active tumor regions within heterogeneous masses, which are more likely to correspond to areas of higher cellularity and biological aggressiveness. These regions may represent optimal targets for biopsy and may support biologically guided radiotherapy planning, including potential dose escalation to high-risk tumor subregions while sparing surrounding normal tissues, thereby improving local tumor control and reducing treatment-related toxicity.

Interestingly, the follow-up PET/CT also detected multiple areas of symmetrical intense FDG uptake bilaterally in the neck area, the posterior mediastinum, bilateral costovertebral margins, and bilateral suprarenal fossa, extending to perinephric fat, which anatomically correlated to fat at CT—consistent with functioning brown fat. Although typically considered a physiological finding, recent evidence suggests that brown fat activation on FDG PET/CT may reflect systemic metabolic status and has been associated with improved survival outcomes in oncologic patients. In the present case, this finding was interpreted as a physiological phenomenon; however, its potential prognostic implications deserve further investigation, particularly in pediatric and adolescent populations. The case underscores the importance of an integrated imaging strategy in the management of pediatric soft tissue sarcomas and highlights the clinical value of combining complementary imaging techniques in rare and complex presentations. The main limitation of this report is the relatively short duration of follow-up, which does not allow assessment of long-term outcomes. Nevertheless, individual case reports remain valuable in the context of rare pediatric malignancies, where clinical experience is limited and each well-documented case contributes to improving diagnostic awareness and management strategies. At the time of the most recent follow-up, the patient reported good tolerance of therapy and maintained a positive outlook regarding treatment.

Subject of Research: Multimodal imaging with MRI, CT, and 18F-FDG PET/CT for staging and response assessment of pediatric synovial sarcoma

Article Title: Case Report: Role of MRI, CT, and 18F-FDG PET/CT in staging and response assessment of pediatric synovial sarcoma

Article References: Picori, L., Maccio, L., Meneghello, L., Caldarella, C., Donner, D., & Feraco, P. (2026). Case Report: Role of MRI, CT, and 18F-FDG PET/CT in staging and response assessment of pediatric synovial sarcoma. Frontiers in Nuclear Medicine, 6, Article 1870009. https://doi.org/10.3389/fnume.2026.1870009

Image Credits: AI Generated

DOI: 10.3389/fnume.2026.1870009

Keywords: synovial sarcoma, pediatric oncology, MRI, CT, 18F-FDG PET/CT, SUVmax, tumor staging, treatment response, soft tissue sarcoma, ifosfamide, doxorubicin, triple sign

Apocrine gland anal sac adenocarcinoma, abbreviated AGASACA, is a malignant epithelial tumor arising from the anal sacs, the small scent glands tucked on either side of a dog’s anus. It is not common, accounting for roughly 2 percent of all skin tumors and about 17 percent of perianal malignancies in dogs, but it is notorious for two reasons. First, it frequently spreads to regional lymph nodes, sometimes even when the primary tumor is small. Second, it often triggers a paraneoplastic syndrome in which the tumor produces hormone-like signals that drive blood calcium to dangerously high levels, causing increased thirst, weakness, and strain on the kidneys. Dogs typically arrive at the clinic with constipation or straining to defecate, caused by the primary mass or by enlarged metastatic lymph nodes pressing on the rectum.

The patient in this report was a 10-year-old castrated male Maltese weighing just 3.88 kilograms, referred for evaluation of a right anal sac mass and enlarged intra-abdominal lymph nodes. Fine-needle aspiration performed at the referring clinic had already revealed cells with cytological features of malignancy, but a definitive diagnosis would have to wait for histopathology after surgery. The clinical picture was telling: the dog had mild leukocytosis, an elevated ionized calcium concentration of 1.66 mmol/L against a reference interval of 1.16 to 1.40 mmol/L, and metabolic acidosis marked by a raised anion gap, low bicarbonate, and negative base excess. Chest radiographs showed no evidence of pulmonary metastasis, but the abdominal picture remained uncertain.

That uncertainty is exactly where 18F-fluorodeoxyglucose positron emission tomography combined with computed tomography, or 18F-FDG PET/CT, enters the story. The technique exploits a fundamental quirk of cancer biology: malignant cells burn glucose at an accelerated rate. The radiopharmaceutical 18F-FDG is a glucose analog tagged with a positron-emitting isotope of fluorine. Once injected, it is taken up by metabolically hungry tissues, where it becomes trapped after phosphorylation, allowing the PET scanner to map glucose consumption across the entire body. Fused with the anatomical detail of CT, the result is an image that shows not just where structures are, but which of them are biologically active. Uptake is quantified with the standardized uptake value, calculated by dividing the tissue concentration of FDG in megabecquerels per milliliter by the injected activity per gram of body weight. The maximum value within a region of interest, SUVmax, serves as a compact summary of a lesion’s metabolic intensity.

In human oncology, FDG PET/CT is an established staging workhorse, outperforming CT alone for assessing disease extent across many tumor types. In veterinary medicine it has been explored in canine lymphoma, osteosarcoma, mammary carcinoma, cutaneous squamous cell carcinoma, and granulosa cell tumors, but its role in specific tumor entities remains poorly defined. For AGASACA, PET/CT had been mentioned as a staging option, yet no detailed imaging findings or SUV measurements had ever been published. The Korean team set out to fill that gap with a rigorously documented single case.

The imaging protocol was meticulous. The dog was fasted for at least 12 hours, anesthetized with medetomidine and propofol, intubated, and maintained on isoflurane in 100 percent oxygen with mechanical ventilation and intravenous fluids at twice the maintenance rate to support blood pressure. After anesthetic induction, 0.187 mCi/kg of 18F-FDG was injected intravenously. Whole-body CT was acquired on a multidetector scanner at 100 mAs and 120 kVp with 1.25 mm slice thickness, before and after contrast enhancement with iohexol. PET followed on the same scanner after a 60-minute uptake period, with the entire imaging session lasting about two hours. Regions of interest were manually delineated on the fused images, and SUVmax was measured for each suspicious lesion.

The results were striking. CT identified a mass measuring 3.8 by 2.6 by 3.8 centimeters within the right anal sac, an internal iliac lymph node of 3.5 by 2.2 by 1.6 centimeters, and a lumbar aortic lymph node of 1.3 by 1.0 by 1.3 centimeters. PET revealed focally intense FDG uptake in all three: SUVmax 7.3 in the primary tumor, 6.35 in the internal iliac node, and 4.3 in the lumbar aortic node. Crucially, no distant metastatic uptake appeared in the lungs, liver, spleen, or other visceral organs. The dog was classified as Stage IIIa, defined as locoregional nodal metastasis with a maximum metastatic node smaller than 4.5 centimeters and no distant spread. The nodal SUVmax values clearly exceeded the general threshold range of 2.5 to 3.5 used to flag metabolically active lymph nodes as suspicious for metastasis.

Guided by the metabolic map, the surgeons performed an intra-abdominal lymphadenectomy before the right anal sacculectomy, sequencing the procedure to minimize contamination of the abdominal field. The enlarged lumbar aortic node, found adjacent to the aorta at the level of the caudal pole of the right kidney, consisted of two distinct segments that were harvested separately. The enlarged internal iliac node was then excised. During removal of the anal sac, gross invasion of part of the rectal wall was discovered, and the involved portion was resected along with the primary mass. Histopathology confirmed AGASACA in the primary tumor, showing tubular to acinar differentiation, moderate anisocytosis and anisokaryosis, necrosis, and desmoplasia, with a mitotic count of 30 per 2.37 square millimeters and no vascular invasion. The resected lymph nodes contained morphologically similar metastatic adenocarcinoma, with mitotic counts of 35 and 30 in the two lumbar aortic segments and 16 in the internal iliac node, confirming the preoperative Stage IIIa classification.

The postoperative course offered both encouragement and a sobering lesson. The day after surgery, ionized calcium fell to 1.35 mmol/L, back within the reference interval, demonstrating that the paraneoplastic hypercalcemia resolved with removal of the tumor burden. A surgical site dehiscence required a secondary repair, and the dog was discharged 12 days after the initial operation, initially doing well with a good appetite and no fecal incontinence. But at approximately three months, thoracic radiography and abdominal ultrasonography revealed enlargement of multiple intra-abdominal lymph nodes, the rectum was displaced ventrally by a nodal mass, and hypercalcemia recurred at 2.31 mmol/L, signaling progressive nodal metastasis. The owner declined further tumor-directed treatment, and the dog was euthanized on postoperative day 104.

The discussion surrounding the case highlights why the findings matter. Conventional staging for AGASACA relies on abdominal ultrasonography and CT, which judge lymph nodes by size and morphology and say nothing about metabolic activity. Fine-needle aspiration can confirm cytology but is invasive and technically difficult for deep nodes. Lymphatic drainage in AGASACA is also unpredictable: in a prospective pilot study of eight dogs with unilateral tumors, preoperative and intraoperative sentinel lymph node mapping disagreed in four dogs, and contralateral sentinel nodes were identified in four of eight cases. Lumbar aortic involvement, seen here, is less commonly reported than disease in the iliosacral lymphocenter. The primary tumor’s SUVmax of 7.3 sits within the range reported for other canine carcinomas, including adenocarcinomas at 7.6 to 27.0 and malignant mammary carcinomas at 2.97 to 10.01, though cross-study comparisons remain hazardous because scanner hardware and reconstruction algorithms vary. Intriguingly, the internal iliac node showed higher uptake despite a lower mitotic count than the lumbar aortic node, a reminder that FDG uptake reflects cellular composition and glucose metabolism, not proliferation alone. As a single case, the values cannot be generalized, and no disease-specific reference range yet exists for canine AGASACA. But the authors argue the case demonstrates that PET/CT can complement morphology-based imaging by exposing metabolically active nodes at both typical and atypical sites, potentially sharpening preoperative staging and surgical planning. For a cancer that so often hides its true spread until the abdomen is open, that metabolic window may prove to be a genuinely valuable addition to the veterinary oncologist’s toolkit.

Subject of Research: First reported 18F-FDG PET/CT imaging findings and SUVmax values in a dog with apocrine gland anal sac adenocarcinoma and confirmed lymph node metastases

Article Title: Case Report: 18F-FDG PET/CT findings and SUVmax characterization in a dog with apocrine gland anal sac adenocarcinoma

Article References: Shim, B., Kim, Y., & Lee, S. (2026). Case Report: 18F-FDG PET/CT findings and SUVmax characterization in a dog with apocrine gland anal sac adenocarcinoma. Frontiers in Veterinary Science, 13, Article 1977879. https://doi.org/10.3389/fvets.2026.1977879

Image Credits: AI Generated

DOI: 10.3389/fvets.2026.1977879

Keywords: 18F-FDG PET/CT, apocrine gland anal sac adenocarcinoma, SUVmax, veterinary oncology, canine cancer, lymph node metastasis, staging, paraneoplastic hypercalcemia, nuclear medicine, case report, comparative oncology, anal sacculectomy

The study followed 175 patients with pathologically confirmed EGFR-mutant lung adenocarcinoma who received baseline 18F-FDG PET/CT imaging within 30 days of starting targeted therapy between January 2020 and December 2023. The cohort, composed of 77 men and 98 women with a mean age of 60.52 years, reflected the modern clinical landscape: nearly 89 percent of patients had stage IV disease at diagnosis, and roughly half received third-generation tyrosine kinase inhibitors such as osimertinib, almonertinib, or furmonertinib as their treatment. This is a crucial distinction, because much of the earlier literature on metabolic imaging in this disease was built on cohorts treated with older first- and second-generation drugs, limiting how well those results apply to patients being treated today.

The imaging technique at the heart of the study exploits a metabolic quirk of cancer cells known as the Warburg effect. Malignant cells consume glucose at a far higher rate than normal tissue, and 18F-FDG, a radioactive glucose analog, accumulates in proportion to that consumption. The PET scanner converts this signal into quantitative measures: SUVmax captures the highest metabolic intensity within any tumor, SUVpeak provides a more robust peak measure, while metabolic tumor volume (MTV) and total lesion glycolysis (TLG) quantify the overall burden of metabolically active disease. Two experienced nuclear medicine physicians independently traced regions of interest for every patient, with interobserver agreement ranging from good to excellent across all four parameters, meaning the measurements are reproducible rather than artifacts of who happened to read the scan.

When the researchers analyzed survival outcomes using Kaplan–Meier estimates and log-rank tests over a median follow-up of 48 months, all four metabolic parameters showed significant associations with shorter progression-free survival in univariate analysis. But the picture sharpened considerably under multivariate Cox proportional hazards regression, which adjusts for competing clinical variables. Only SUVmax retained its independent prognostic value, with a hazard ratio of 1.031 per unit increase (95 percent confidence interval, 1.001 to 1.059; P = .045). Volumetric measures such as MTV and TLG, despite their intuitive appeal as gauges of total tumor burden, lost statistical significance once SUVmax was accounted for.

That pattern carries a provocative biological implication. The authors suggest that SUVmax may capture the single most aggressive subclone within a tumor, the cellular population driving disease progression regardless of how large the overall tumor burden happens to be. This mirrors observations in multiple myeloma, where the lesion with the highest glucose avidity proved more prognostically relevant than total metabolic volume. Heightened glycolytic flux, in this framing, is not just a passive marker of tumor size but a window into activated PI3K/AKT/mTOR signaling, a downstream pathway that can bypass the blocked EGFR receptor and allow cancer cells to shrug off drug inhibition. In other words, a hot tumor on PET may be a tumor already wired for resistance.

The study also reinforced a molecular divide that has become increasingly hard to ignore. Patients whose tumors carried an exon 19 deletion, one of the two most common sensitizing EGFR mutations, experienced a median progression-free survival of 13.57 months, significantly longer than the 10.37 months observed in patients with the L858R point mutation (P = .02). Notably, the baseline PET parameters themselves did not differ significantly between the two mutation subgroups, meaning the survival gap cannot be explained by grossly different glucose avidity. The two mutations, the authors argue, likely arise from distinct cellular lineages with divergent downstream signaling networks, a divergence that proteomic studies support: L858R tumors preferentially activate networks involving PARPBP and HOXA1 that may confer a more aggressive phenotype, while exon 19 deletion tumors are dominated by different pathway architecture.

Perhaps the most clinically tantalizing, and most cautious, finding concerned drug generation. Within the exon 19 deletion subgroup, third-generation tyrosine kinase inhibitors were associated with a significant prolongation of progression-free survival, whereas no statistically significant benefit emerged in the L858R subgroup (P = .197). The authors are explicit that these subgroup results must be interpreted as preliminary exploratory observations: some strata contained as few as two patients, statistical power was insufficient, and treatment assignment in this single-center retrospective cohort was based on clinical availability and physician preference rather than randomization. Still, the trend aligns with structural biology, because the conformation of the exon 19 deletion mutant allows higher drug-binding affinity and more durable inhibition by osimertinib, while the L858R configuration may facilitate earlier acquisition of bypass resistance pathways.

The researchers also confronted an uncomfortable statistical reality with characteristic transparency. Receiver operating characteristic analysis showed that each metabolic parameter alone had only modest discriminatory power for survival, with area under the curve values hovering between 0.579 and 0.582. The authors attribute this to the genetically uniform nature of their cohort: because all patients shared EGFR-driven downstream metabolic reprogramming, the dynamic range of SUV values needed for clean binary classification is compressed. Rather than dichotomizing patients at a cutoff, the team treated SUVmax as a continuous variable in the Cox models, avoiding the information loss that binary thresholds impose and confirming that even incremental increases in glycolytic activity correspond to elevated risk.

The study is not without limitations, which the authors enumerate candidly. The retrospective, single-center design with 175 patients limits generalizability, the mixture of drug generations and treatment lines introduces residual confounding that multivariate adjustment cannot fully eliminate, and the fixed SUV threshold of 2.5 used to compute volumetric parameters may underestimate tumor burden in EGFR-mutant lesions that are inherently less glucose-avid. Overall survival was not chosen as the primary endpoint because treatment crossover and insufficient death events during follow-up would have made the analysis unreliable.

Even so, the take-home message is a step toward genuinely integrated risk assessment in precision oncology. Genotyping tells clinicians which mutation a tumor carries; a baseline PET scan, measured cheaply and reproducibly before the first pill is taken, appears to tell them something orthogonal and complementary: how metabolically aggressive that tumor actually is. The authors envision future prognostic models that combine SUVmax with molecular profiles, potentially identifying high-risk patients, such as those with L858R mutations and intense glucose uptake, who might benefit from intensified upfront strategies including combination therapy. Larger prospective, multi-center cohorts with standardized treatment protocols will be needed before such models reach the clinic, but the study adds weight to an emerging consensus: in EGFR-mutant lung cancer, the genotype sets the stage, while the metabolic phenotype may help predict how the play unfolds.

Subject of Research: Prognostic value of baseline 18F-FDG PET/CT metabolic parameters in EGFR-mutant lung adenocarcinoma treated with EGFR tyrosine kinase inhibitors

Article Title: Prognostic value of baseline 18F-FDG PET/CT metabolic parameters in EGFR-mutant lung adenocarcinoma patients treated with EGFR-TKIs

Article References: Wang, L., Wang, Z., & Wu, W. (2026). Prognostic value of baseline 18F-FDG PET/CT metabolic parameters in EGFR-mutant lung adenocarcinoma patients treated with EGFR-TKIs. Frontiers in Nuclear Medicine, 6, Article 1864776. https://doi.org/10.3389/fnume.2026.1864776

Image Credits: AI Generated

DOI: 10.3389/fnume.2026.1864776

Keywords: 18F-FDG PET/CT, EGFR mutation, lung adenocarcinoma, tyrosine kinase inhibitors, SUVmax, progression-free survival, exon 19 deletion, L858R, osimertinib, prognosis, precision oncology, tumor metabolism

The research team, led by Yang You, Weifeng Zhang, and colleagues in the hospital’s Department of Nuclear Medicine, set out to compare two statistical models for classifying indeterminate pulmonary nodules. The first, a conventional model, relied on seven predictors drawn from clinical data, CT features, and early-phase PET measurements. The second, an extended model, added a single extra variable: the retention index of maximum standardized uptake value, or RI-SUVmax, which captures how tracer concentration in the nodule changes between the early scan and a delayed scan performed roughly 120 to 180 minutes after injection of the radiopharmaceutical. The biological rationale is appealing. Inflammatory lesions and malignant tumors can both light up on early PET images, but the kinetics of glucose uptake differ; some investigators have argued that malignant tissue retains or accumulates FDG over time, while inflammatory activity tends to wash out. If true, delayed imaging could unmask cancers that the standard single-time-point scan misses.

To test this idea properly, the researchers assembled a cohort of 612 patients, each with a single index pulmonary nodule measuring between 8 and 30 millimeters. From an initial pool of 817 screened patients, 205 were excluded, leaving a study population in which every nodule eventually received a definitive reference diagnosis. Malignancy was confirmed in all cases by histopathology, obtained through surgical resection or image-guided biopsy. Benign status was established either by the same pathological route or, for solid nodules, by at least 24 months of serial chest CT follow-up showing stability or resolution. In total, 369 of the 612 patients—60.3 percent—turned out to have malignant nodules, a proportion that underscores just how high the stakes are in this diagnostic gray zone.

What distinguishes this study from much of the prior literature on dual-time-point PET imaging is its validation strategy. Rather than splitting patients randomly, the team assigned them chronologically: 312 patients scanned between 2018 and 2022 formed the training cohort, while 300 patients scanned between 2023 and 2025 formed a temporal validation cohort. This design matters because models that are tested on randomly shuffled data can quietly benefit from temporal leakage—subtle shifts in scanners, protocols, or patient demographics that make the test set resemble the training set. Temporal validation, by contrast, asks the harder question: does a model built on yesterday’s patients still work on tomorrow’s? The researchers also employed least absolute shrinkage and selection operator regression, or LASSO, to select predictors from a starting pool of 26 candidate variables, a technique that shrinks weak coefficients toward zero and helps prevent overfitting. Internal validation was performed with 1,000 bootstrap resamples, and the final locked models were then frozen and applied, unmodified, to the later cohort.

The headline result is a study in statistical nuance. In temporal validation, the conventional model achieved an area under the receiver operating characteristic curve of 0.891, with a 95 percent confidence interval of 0.854 to 0.928. The extended model, enriched with the delayed-phase retention index, reached 0.903, with an interval of 0.868 to 0.938. The paired difference between the two was just 0.0120, with a confidence interval stretching from −0.0003 to 0.0243 and a P value of 0.056—just shy of conventional statistical significance. In plain terms, adding the delayed scan produced a small improvement in the model’s ability to separate malignant from benign nodules, but the researchers could not confidently rule out that the difference was a fluke of this particular dataset. Brier scores, which combine discrimination and calibration into a single measure of predictive accuracy, were 0.134 for the conventional model and 0.127 for the extended one, again favoring the delayed approach modestly.

But the deeper story lies in the trade-offs and the calibration problem. At decision thresholds derived from the training data, the extended model pushed sensitivity up from 76.7 percent to 84.4 percent—meaning it caught more cancers—while specificity slipped from 86.7 percent to 81.7 percent, meaning more benign nodules were falsely flagged as suspicious. In a clinical setting, that shift translates into more patients with harmless lesions being funneled toward invasive biopsies or additional imaging, with all the anxiety, cost, and procedural risk those entail. Exploratory decision-curve analysis, which estimates the net benefit of acting on a model’s predictions across a range of risk thresholds, showed only threshold-dependent differences between the two approaches, leaving the clinical value of the extra scan contingent on how aggressively a given institution chooses to pursue nodules.

Perhaps the most sobering finding was the miscalibration. Calibration slopes in the temporal validation cohort were 0.557 for the conventional model and 0.482 for the extended model—far from the ideal value of 1.0. A perfectly calibrated model would assign a 70 percent malignancy probability to a group of nodules in which 70 percent are truly malignant; these models systematically overstated or understated risk when transplanted across time. The authors attribute this to the inherent difficulty of transporting prediction models across changing clinical eras and note that the miscalibration persisted regardless of whether delayed imaging was included. Their conclusion is unambiguous: recalibration and multicenter external validation are required before either model can be deployed in routine practice. This candor is refreshing in a field where promising discrimination statistics are sometimes oversold as clinical readiness.

The study also probed the robustness of its findings through a battery of exploratory analyses documented in supplementary materials. Subgroup analyses examined whether the benefit of delayed imaging varied by nodule characteristics, including a conventional definition of PET/CT-indeterminate status based on early SUVmax values between 1.5 and 4.0 or intermediate visual uptake scores. The team tested restrictions to a narrower 75-to-105-minute interval between early and delayed acquisitions, substituted delayed SUVmax for the retention index, and even refit the models using flexible restricted cubic splines to allow nonlinear relationships. Across these variations, the advantage of delayed imaging remained small and inconsistent, reinforcing the central message that the retention index is not a transformative addition to nodule characterization.

Why does this matter beyond the walls of one hospital in Zhengzhou? Dual-time-point PET imaging has been proposed, debated, and intermittently adopted for more than two decades, and the extra scan carries real costs: additional scanner time, higher radiation exposure from the second CT pass, greater patient burden, and scheduling complexity. If the incremental diagnostic yield is a statistically uncertain 0.012 in AUC, health systems may reasonably question whether the delayed phase earns its keep. At the same time, the study’s rigorous architecture—chronological validation, bootstrap internal checks, LASSO regularization, and transparent reporting of calibration failures—sets a template for how diagnostic prediction models should be evaluated before entering the clinic. As machine learning tools proliferate in medical imaging, studies like this one serve as a reminder that a model’s true test is not how impressively it fits the data it was trained on, but how faithfully it performs on patients it has never seen, months or years down the line.

For now, patients with indeterminate pulmonary nodules and their physicians are left with a nuanced picture. Early-phase ¹⁸F-FDG PET/CT, combined with clinical and CT features, remains a strong discriminator, achieving an AUC near 0.89 even without delayed imaging. The delayed scan may tip the balance in selected cases, particularly where sensitivity is paramount and a modest loss of specificity is acceptable, but the evidence does not yet justify routine adoption. The authors’ call for recalibration and multi-institutional validation is not a bureaucratic formality; it is the necessary next step before these models can safely inform decisions about who undergoes biopsy and who can be reassured with surveillance. In the ongoing effort to shrink the diagnostic gray zone of the solitary pulmonary nodule, this study measures the ground gained—and honestly reports how much of the fog remains.

Subject of Research: Diagnostic prediction modeling with early and delayed-phase ¹⁸F-FDG PET/CT for classifying indeterminate pulmonary nodules

Article Title: ¹⁸F-FDG PET/CT models with and without delayed-phase imaging for indeterminate pulmonary nodules: development and temporal validation

Article References: You, Y., Zhang, W., Zhen, Z., Xu, J., Hu, B., & Xuan, A. (2026). ¹⁸F-FDG PET/CT models with and without delayed-phase imaging for indeterminate pulmonary nodules: development and temporal validation. BMC Medical Imaging. https://doi.org/10.1186/s12880-026-02846-7

Image Credits: AI Generated

DOI: 10.1186/s12880-026-02846-7

Keywords: pulmonary nodules, ¹⁸F-FDG PET/CT, dual-time-point imaging, retention index, SUVmax, temporal validation, LASSO regression, lung cancer diagnosis, medical imaging, model calibration, nuclear medicine, diagnostic accuracy

The imaging technique at the heart of the study, positron emission tomography combined with computed tomography, has become a cornerstone of modern cancer care. Patients receive an injection of [18F]-fluorodeoxyglucose, a radioactive glucose analog that is avidly taken up by metabolically active cells. Because cancer cells typically consume glucose at a far higher rate than healthy tissue, they light up on the resulting images, allowing physicians to visualize both the primary tumor and any spread to lymph nodes or distant organs. The PET component reveals metabolic activity, while the CT component provides detailed anatomical context, and the fusion of the two gives clinicians a map of where active disease resides in the body.

In the standard workflow for locally advanced cervical cancer, PET-CT is used twice: once before treatment begins, to establish the stage of the disease, and again several weeks after chemoradiotherapy has concluded, to assess how well the cancer responded. The Swedish team set out to determine whether the information gathered at that second time point could do more than simply confirm whether the tumor had shrunk. They wanted to know whether the pattern of metabolic response could serve as a genuine prognostic instrument, capable of stratifying patients into distinct risk categories that would justify different follow-up strategies or, potentially, additional interventions.

To quantify treatment response, the researchers extracted three complementary parameters from every scan. The first and most widely used is SUVmax, the maximum standardized uptake value, which reflects the peak glucose metabolism within the most active region of a lesion. The second is metabolic tumour volume, or MTV, which measures the total physical volume of tissue exhibiting abnormally high FDG uptake. The third is total lesion glycolysis, or TLG, which combines volume and intensity into a single figure representing the overall metabolic burden carried by the disease. Each parameter captures a different dimension of tumor biology, and the team analyzed all three separately to see whether the more computationally demanding volume-based measures offered any advantage over the simple maximum uptake value.

Using these parameters, the investigators classified each patient’s post-treatment response into one of four categories adapted from established response criteria. A complete metabolic response, or CMR, meant the total resolution of abnormal FDG uptake in all lesions, essentially signaling that no metabolically active cancer could be detected anywhere in the scanned field. A partial metabolic response, or PMR, was defined as a reduction of more than 25 percent in SUVmax, MTV or TLG, indicating that disease remained but had been substantially weakened. Progressive metabolic disease, or PMD, was declared when uptake increased by more than 25 percent or when new FDG-avid lesions appeared, a clear sign that the treatment had failed to contain the cancer. Patients who fit none of these categories were classified as having stable disease. Because the number of events in the PMR and stable disease groups was limited, the researchers combined them into a single intermediate group for statistical analysis.

The results were striking. Taking patients with complete metabolic response as the reference group, those with partial response or stable disease faced roughly 1.2 times the odds of experiencing a recurrence, a modest but measurable elevation in risk. Far more dramatic was the picture for patients whose disease progressed: their odds of recurrence were 1.7 times higher when response was assessed by SUVmax, and 1.8 times higher when assessed by MTV or TLG. In other words, a scan showing growing or newly emerged metabolically active disease after treatment was a red flag that recurrence was substantially more likely, regardless of which of the three parameters was used to make the call.

The survival analysis carried an even starker message. Patients in the intermediate response group had a hazard ratio for death of 4.0 when response was measured by SUVmax, meaning their risk of dying during the follow-up period was four times that of patients who achieved a complete metabolic response. When MTV or TLG served as the response metric, the hazard ratio for this intermediate group was 2.9. For patients with progressive metabolic disease, the hazard ratio soared to 16.0 across all three parameters, a sixteen-fold increase in mortality risk compared with complete responders. The concordance index, a statistical measure of how well a model discriminates between patients with different outcomes, reached 0.84 for SUVmax-based models and 0.86 for models built on MTV or TLG, values that indicate strong predictive performance for any prognostic tool in oncology.

Perhaps the most consequential finding of the study is what it did not find: no meaningful superiority of the sophisticated volume-based parameters over the simple maximum uptake value. MTV and TLG require semi-automated segmentation of tumor volumes and considerably more computational processing, and some researchers have argued that their added information content should translate into better prognostic power. In this cohort, however, the three parameters performed in a nearly identical fashion, with concordance indices differing by only two hundredths. For clinical practice, this is genuinely good news, because it suggests that the prognostic value of post-treatment PET-CT can be unlocked using a parameter that is already routinely reported by nuclear medicine departments worldwide, without the need for new software, additional training or workflow changes.

The implications for patient management are considerable. Patients who achieve a complete metabolic response could potentially be spared intensive surveillance, receiving standard follow-up with the reassurance that their statistical outlook is excellent. Those with partial or stable metabolic response, whose risk is elevated but not extreme, might benefit from closer imaging intervals and a lower threshold for biopsy or salvage interventions. Patients showing progression on the post-treatment scan represent the group with the most urgent need for attention, and the sixteen-fold hazard ratio suggests that early escalation of care, whether through additional systemic therapy or enrollment in clinical trials of novel agents, could be life-extending for this small but high-risk population. The study also reinforces the value of performing a post-treatment PET-CT at all, since the metabolic information it provides clearly carries prognostic weight beyond anatomical assessment alone.

As with all retrospective single-center analyses, the findings come with caveats. The 133 patients were treated at a single Swedish institution, and the classification thresholds, including the 25 percent change criteria, were drawn from established response frameworks rather than derived de novo. Prospective validation in larger and more diverse cohorts will be needed before response category can be formally incorporated into treatment guidelines. Nevertheless, the strength and consistency of the associations, spanning recurrence risk, overall survival and three independent metabolic parameters, make a compelling case that the post-treatment FDG-PET/CT scan is far more than a formality. It is, in effect, a crystal ball of glucose metabolism, offering each patient and her medical team an early, individualized forecast of the road ahead, and pointing the way toward a future in which follow-up care for cervical cancer is tailored not to the average patient but to the biology revealed on a single scan.

Subject of Research: FDG-PET/CT-based treatment response assessment as a predictor of recurrence and survival in locally advanced cervical cancer

Article Title: FDG-PET/CT-based treatment response predicts recurrence and overall survival in locally advanced cervical cancer

Article References: Markus, M., Sartor, H., Bjurberg, M., Minarik, D., & Trägårdh, E. (2026). FDG-PET/CT-based treatment response predicts recurrence and overall survival in locally advanced cervical cancer. BMC Medical Imaging, 26(1), Article 458. https://doi.org/10.1186/s12880-026-02772-8

Image Credits: AI Generated

DOI: 10.1186/s12880-026-02772-8

Keywords: FDG-PET/CT, cervical cancer, treatment response, SUVmax, metabolic tumour volume, total lesion glycolysis, recurrence, overall survival, radiotherapy, nuclear medicine, predictive medicine, oncology

The clinical dilemma the study addresses is well known to urologists and nuclear medicine physicians alike. Multiparametric MRI has become the cornerstone of modern prostate cancer detection, allowing clinicians to localize suspicious lesions, direct biopsy needles toward the most concerning regions, and spare many men unnecessary sampling of slow-growing tumors that may never require treatment. Yet the technology is not infallible. According to the researchers, up to 20 to 30 percent of clinically significant prostate cancers may be missed in patients whose MRI scans are negative or equivocal. For these men, a reassuring scan does not actually rule out dangerous disease, and the standard response—repeated or extended systematic biopsies—carries its own burden of bleeding, infection, anxiety, and cost, all while aggressive tumors can still slip through the sampling grid.

“A negative or unclear MRI does not completely rule out clinically significant prostate cancer. As a result, some men may undergo repeated or extensive biopsies, while relevant tumors may still be missed,” said Andrea Farolfi, MD, a nuclear medicine physician at the Nuclear Medicine Unit of IRCCS Azienda Ospedaliero-Universitaria di Bologna and the study’s lead author. “Determining whether PSMA PET can refine risk stratification and guide targeted sampling for these men could have a direct impact on clinical decision-making.” The rationale behind the approach rests on the biology of the prostate-specific membrane antigen, or PSMA, a protein that is overexpressed on the surface of prostate cancer cells, and often to a far greater degree in aggressive, high-grade disease than in indolent tissue.

PSMA PET/CT exploits this molecular signature by pairing a radiolabeled ligand that binds to PSMA with the anatomic precision of computed tomography. When the radiotracer accumulates intensely within a prostatic region, it signals not merely anatomic distortion, as MRI might show, but active metabolic expression of a marker tightly linked to tumor aggressiveness. In the FUPERMAN study, the researchers enrolled 63 men with negative or inconclusive multiparametric MRI scans who nonetheless carried persistent clinical suspicion of prostate cancer. Each participant underwent gallium-68 PSMA-11 PET/CT followed by prostate biopsy performed with PET fusion guidance, meaning the targeting information from the molecular image was directly co-registered with the biopsy system in real time. A subset of 11 patients additionally underwent dynamic total-body PET, an emerging technique that captures the kinetic behavior of the tracer as it flows into and binds within tissue.

The results were striking in their consistency. PSMA PET/CT was positive in 25 of the 26 men who were ultimately diagnosed with clinically significant prostate cancer, indicating that the molecular image rarely overlooked disease that biopsy later confirmed. PSMA PET/CT-targeted biopsy alone detected clinically significant cancer in 37 percent of the entire study population, while systematic biopsy alone managed only 21 percent. Combining the two strategies raised the detection rate to 41 percent, demonstrating that the molecularly guided approach does not simply duplicate what systematic sampling finds—it uncovers cancers that the conventional grid-based method misses, particularly in prostatic zones where MRI provided no suspicious target to aim at.

Beyond simple detection, the study explored whether quantitative information from the PET scan itself could predict which patients harbored aggressive disease. The researchers found that SUVmax, the maximum standardized uptake value reflecting the peak concentration of radiotracer in a lesion, was independently associated with clinically significant prostate cancer. In other words, the intensity of the molecular signal carried prognostic weight, offering a semiquantitative bridge between imaging and pathology that could help clinicians decide which men truly need biopsy and which might be safely monitored. This kind of risk stratification is precisely what the field has been seeking for the MRI-negative population, where current guidelines offer limited guidance and clinical judgment often defaults to repeat invasive procedures.

The exploratory dynamic total-body PET component added a further layer of technical sophistication. By acquiring continuous imaging data immediately after tracer injection, dynamic total-body PET allows researchers to characterize the kinetics of radiotracer uptake and washout within prostatic lesions. In the 11 patients studied with this protocol, the investigators observed distinct kinetic patterns in aggressive lesions, particularly in cases where MRI findings were unclear. While the subset was small and the analysis explicitly exploratory, the finding hints at a future in which the temporal behavior of PSMA binding—how quickly tracer accumulates and how persistently it is retained—could complement static uptake measurements and further sharpen the distinction between indolent and clinically threatening disease.

“Our findings suggest that PSMA PET/CT could provide an additional tool for identifying men who remain at risk despite non-diagnostic MRI findings and for directing the biopsy toward the most suspicious area,” Farolfi said. “If confirmed in larger studies, this approach could make the diagnostic pathway more accurate and personalized.” The implications for patient care extend beyond the immediate detection statistics. For men caught in the diagnostic gray zone—elevated PSA, negative or equivocal MRI, and mounting pressure for repeat biopsy—a positive PSMA PET/CT could concentrate sampling where it matters most, potentially reducing the number of biopsy cores required, lowering complication rates, and sparing men with truly negative molecular imaging from yet another round of invasive sampling.

The study, titled “PSMA PET/CT–Targeted Biopsy in Men with Negative or Equivocal Multiparametric MRI and Exploratory Dynamic Total-Body PET: The FUPERMAN Study,” was conducted by a multidisciplinary team spanning nuclear medicine, urology, radiology, and internal medicine at the University of Bologna and its teaching hospital. The collaboration reflects the practical demands of the technique itself, which requires nuclear medicine physicians to interpret molecular images, radiologists to reconcile them with prior MRI data, and urologists to execute fusion-guided biopsies with millimeter-level precision. The research was published in The Journal of Nuclear Medicine, the flagship journal of the Society of Nuclear Medicine and Molecular Imaging, and carries the DOI 10.2967/jnumed.126.272108.

As with any single-center study of modest size, the findings will need validation in larger, multi-institutional cohorts before PSMA PET/CT-guided biopsy becomes a standard recommendation for the MRI-negative population. Questions remain about cost-effectiveness, radiation exposure, access to PSMA radiotracers, and whether the impressive detection rates hold across more diverse patient populations. Nevertheless, the FUPERMAN results mark an important proof of concept: a molecular imaging modality originally developed for staging advanced disease can, when fused with biopsy guidance, illuminate cancers that the anatomical gold standard cannot see. For the substantial minority of men whose MRI scans fail them, that could mean the difference between an aggressive tumor caught early and one discovered only after it has progressed beyond the gland.

Subject of Research: PSMA PET/CT-guided targeted biopsy for detecting clinically significant prostate cancer in men with negative or equivocal MRI

Article Title: PSMA PET/CT-targeted biopsy improves detection of clinically significant prostate cancer

Article References: PSMA PET/CT-targeted biopsy improves detection of clinically significant prostate cancer. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: PSMA PET/CT, prostate cancer, targeted biopsy, multiparametric MRI, clinically significant cancer, total-body PET, SUVmax, risk stratification, nuclear medicine, FUPERMAN study, fusion-guided biopsy, diagnostic imaging

The clinical benchmark for staging idiopathic pulmonary fibrosis is the GAP score, an acronym drawn from the variables it incorporates: gender, age, and physiology, the latter captured through lung function tests such as forced vital capacity and the transfer factor for carbon monoxide. The GAP score is a powerful and convenient tool, but it is fundamentally static. It describes the damage that has already accumulated; it says nothing about the biological activity of the disease at the level of the tissue itself. That distinction matters because fibrosis is not merely a passive scar. In active disease, fibroblasts proliferate, inflammatory cells infiltrate, and remodeling processes consume energy, and all of that cellular work demands fuel, principally glucose.

This metabolic hunger is precisely what fluorodeoxyglucose exploits. The radiotracer is a glucose analog labeled with fluorine-18, and once injected it is taken up by metabolically active cells, where it becomes trapped after phosphorylation and emits positrons that the PET scanner detects. In oncology, this principle underpins the familiar maximum standardised uptake value, or SUVmax, a number that quantifies the hottest spot of tracer accumulation within a lesion. The Gdańsk team asked a deceptively simple question: could the same measurement, applied not to tumors but to fibrotic lung parenchyma, serve as a window into the aggressiveness of pulmonary fibrosis?

To find out, the researchers turned to a cohort of thirty patients with idiopathic pulmonary fibrosis who had undergone fluorodeoxyglucose PET/CT for suspected comorbid disease, most often to rule out malignancy. This is a common clinical scenario, since patients with pulmonary fibrosis carry an elevated risk of lung cancer, and the retrospective design allowed the team to mine scans that had already been acquired for other reasons. The researchers measured raw SUVmax values within the fibrotic regions of the lung and compared those values against each patient’s GAP score calculated at the time of the scan. Because uptake values and severity scores are not normally distributed in a sample of this size, they used Spearman’s rank correlation coefficient, a non-parametric statistic that assesses whether two variables tend to increase together without assuming a linear relationship.

The answer was a qualified yes. The correlation between GAP score and fibrotic-lung SUVmax was positive and statistically significant, with a Spearman coefficient of 0.448 and a p-value of 0.013. In plain terms, patients whose lungs burned through more glucose on the scan tended to be the patients whose disease was already more advanced by conventional clinical criteria. A coefficient of 0.448 represents a moderate association, not a perfect one, and the authors are careful to frame the finding as exploratory. Yet the implication is striking: a molecular imaging measurement, taken from a single scan session, appears to carry information that overlaps with, and potentially extends beyond, the physiologic staging that clinicians currently rely upon.

The more provocative part of the study concerns outcomes. The researchers split their cohort into high and low metabolic activity groups using a median split of the SUVmax values, set at 2.53 for the full cohort of thirty patients and at 2.75 for the nineteen patients who were receiving antifibrotic therapy, the modern standard of care with drugs such as the tyrosine kinase inhibitor nintedanib. They then compared progression-free survival and overall survival between the groups using the Mantel-Cox log-rank test, the standard survival analysis method that compares the hazard of an event over time between two populations. In the antifibrotic-treated subgroup, patients with high uptake in their fibrotic lesions showed a median progression-free survival of twenty-five months, exactly half the fifty months observed in the low-uptake group, corresponding to a hazard ratio of 3.68.

Here the statistical caution becomes essential. The confidence interval for that hazard ratio stretched from 0.74 to 18.43, a range that crosses the value of 1.0, meaning the result cannot be distinguished from chance, and the log-rank p-value of 0.089 fell short of the conventional threshold of 0.05. The authors are transparent about this: the survival signal is a hypothesis-generating observation, not a proven predictor. But the pattern is biologically coherent and clinically tantalizing. A hazard ratio approaching four, even with wide uncertainty, suggests that with a larger sample the association could harden into something actionable. If metabolic activity in fibrotic lung truly doubles the pace of progression despite antifibrotic drugs, that information could reshape decisions about monitoring frequency, transplant referral timing, and enrollment into clinical trials of new therapies.

The study’s limitations are the natural consequences of its design. Thirty patients is a small sample, and the scans were acquired for indications unrelated to fibrosis staging, which introduces selection bias even as it offers a glimpse of real-world imaging. The retrospective framework, approved by the Bioethics Committee of the Medical University of Gdańsk with the consent requirement waived, means the researchers could not standardise when or why each scan was performed. SUV measurements are also sensitive to technical factors such as patient blood glucose levels, uptake time, and scanner calibration, all of which complicate comparisons across individuals. The authors themselves conclude that larger prospective studies are required before molecular imaging can be declared an additive prognostic tool in idiopathic pulmonary fibrosis.

Even so, the conceptual advance is worth savoring. For decades, the assessment of fibrotic lung disease has rested on structural and functional endpoints: how much the lung can hold, how well oxygen crosses the membrane, how the tissue looks on high-resolution CT. These measures capture the aftermath of disease. Metabolic imaging, by contrast, offers something closer to a live readout of the pathological process itself, the cellular furnace that drives scarring forward. Previous research has linked fluorodeoxyglucose uptake in the lung to inflammatory and proliferative activity in interstitial disease, and the Gdańsk findings now tie that signal to a validated severity index and to survival trajectories in a treated population.

The road from exploratory correlation to clinical utility is long, and most imaging biomarkers that show promise in small retrospective series never reach the clinic. But the logic of this study points toward a future in which a patient’s PET scan does more than exclude cancer. It could quantify how ferociously their fibrosis is burning, stratify them into risk groups that GAP scores alone cannot resolve, and identify the patients most likely to benefit from intensified therapy or novel antifibrotic agents. For a disease that kills most of those it afflicts within a few years of diagnosis, any tool that reveals the fire beneath the scar, before the lung has irreversibly stiffened, would represent a genuine leap forward. This study is an early, cautious step in that direction, and its authors have mapped the path that the next, larger studies must walk.

Subject of Research: Association between fibrotic-lung FDG-PET uptake and disease severity and outcomes in idiopathic pulmonary fibrosis

Article Title: Association of fibrotic-lung 18F-FDG uptake with GAP severity and clinical outcomes in idiopathic pulmonary fibrosis: an exploratory retrospective study

Article References: Ward, C., Oppmann-Ward, A., Wilczynski, S., Korneliussen, J., Żegleń, S., Rogoza, K., & Cytawa, W. (2026). Association of fibrotic-lung 18F-FDG uptake with GAP severity and clinical outcomes in idiopathic pulmonary fibrosis: an exploratory retrospective study. BMC Medical Imaging. https://doi.org/10.1186/s12880-026-02856-5

Image Credits: AI Generated

DOI: 10.1186/s12880-026-02856-5

Keywords: idiopathic pulmonary fibrosis, FDG-PET/CT, SUVmax, GAP score, pulmonary fibrosis, nuclear medicine, interstitial lung disease, progression-free survival, antifibrotic therapy, molecular imaging, lung fibrosis, prognosis

The research team, led by Yanmei Han and corresponding authors Zairong Gao and Xiao Zhang, set out to address a well-recognized gap in lymphoma prognostication. Existing risk stratification systems for MALT lymphoma, including the MALT lymphoma International Prognostic Index, rely on clinical parameters such as age, disease stage, and lactate dehydrogenase levels, but they do not incorporate information from metabolic imaging. That omission matters, because fluorodeoxyglucose positron emission tomography combined with computed tomography captures something that blood tests and pathology slides cannot: the glucose appetite of the tumor in living tissue. The maximum standardized uptake value, or SUVmax, quantifies how avidly the most active region of a lesion consumes the radiolabeled glucose analog, providing a whole-body metabolic fingerprint of the disease at baseline.

To build their model, the investigators retrospectively analyzed 98 patients with histologically confirmed MALT lymphoma who underwent baseline FDG PET/CT scanning between January 2020 and December 2024. From the pool of available clinical, laboratory, pathological, and imaging measurements, they assembled 17 candidate predictors. Rather than forcing all of them into a regression equation, the team applied least absolute shrinkage and selection operator regression, a statistical technique known as LASSO that penalizes model complexity and drives the coefficients of uninformative variables to zero. Ten-fold cross-validation was used to tune the procedure, meaning the data were repeatedly split so that the variable selection would not simply memorize the quirks of one particular sample.

Out of the 17 candidates, five variables survived the LASSO filter: patient age, the primary site of disease, SUVmax, the Ki-67 proliferation index, and Eastern Cooperative Oncology Group performance status. Each of these carries a plausible biological story. Age and performance status reflect the resilience of the patient and the aggressiveness of the clinical course. Ki-67 measures the fraction of tumor cells actively dividing, a direct readout of proliferative drive. The primary disease site has long been associated with differing behaviors across MALT lymphoma locations, with gastric and non-gastric presentations following distinct trajectories. SUVmax, the sole imaging variable to make the cut, adds the metabolic dimension that conventional indices have ignored.

These five predictors were then combined in a multivariable Cox regression, the standard framework for modeling time-to-event outcomes such as progression-free survival. The result was distilled into a nomogram, a graphical scoring instrument that allows a clinician to assign points to each patient characteristic and read off an estimated probability of remaining progression-free. On the data used to build the model, the five-variable score achieved a concordance index of 0.814, with a 95 percent confidence interval of 0.738 to 0.891. The concordance index, or C-index, expresses the probability that a patient who progresses earlier is correctly assigned a higher risk score than a patient who progresses later, with 0.5 representing random guessing and 1.0 representing perfect ranking.

The authors were careful not to stop at that flattering apparent figure. Apparent performance is notoriously optimistic, because the same data that build a model inevitably flatter it. To correct for this, the team ran a full-pipeline bootstrap procedure with 500 resamples, in which the entire modeling process, from variable selection onward, was repeated on each resampled dataset. This approach estimates how much the model’s measured accuracy is inflated by chance fitting, and the optimism-corrected C-index settled at 0.740, with a 95 percent uncertainty interval of 0.662 to 0.757. In practical terms, the model retains moderate discriminative ability after accounting for statistical overfitting, a level of honesty that many published prognostic models never report.

Time-dependent receiver operating characteristic analysis added a temporal dimension to the evaluation. The area under the time-ROC curve was 0.766 at one year, 0.872 at two years, and 0.883 at three years, indicating that the model’s ability to separate patients who progress from those who remain in remission actually strengthens over the first few years of follow-up. That pattern is clinically meaningful for an indolent lymphoma, where the most consequential question is often not whether relapse will ever occur but whether it will arrive early enough to justify intensified surveillance or alternative first-line strategies.

Perhaps the most intriguing result emerged from an exploratory re-stratification exercise. The team focused on patients classified as intermediate risk by the MALT-IPI, the current standard prognostic index, and asked whether the new integrated model could split this apparently homogeneous group into meaningful subgroups. It could. Within the intermediate-risk category, the nomogram separated patients into lower-risk and higher-risk groups that showed clearly different observed progression-free survival. If confirmed in larger and independent cohorts, this finding suggests that metabolic imaging can refine the coarse resolution of existing clinical indices, potentially sparing lower-risk intermediate patients unnecessary treatment intensity while flagging higher-risk ones for closer monitoring.

The study’s limitations are those inherent to its design. It was retrospective, single-center, and modest in size, with 28 progression events among 98 patients, and the validation was internal rather than external. The authors themselves describe the risk separation within the intermediate-risk subgroup as exploratory. External validation on independent cohorts from different institutions and populations will be essential before the nomogram can influence routine clinical decisions. Nevertheless, the methodological rigor, including the full-pipeline bootstrap and the transparent reporting of optimism-corrected performance, sets a standard that prognostic modeling studies in oncology imaging do not always meet.

Beyond its immediate findings, the work signals a broader shift in how nuclear medicine and hematology are converging. FDG PET/CT has already transformed staging and response assessment in aggressive lymphomas, and quantitative metabolic parameters are increasingly being treated as biomarkers in their own right rather than as pictures for the radiologist’s eye alone. By demonstrating that a single imaging metric can stand alongside age, proliferation index, and performance status in a validated survival model, the Wuhan team provides a template for integrating molecular imaging into prognostic algorithms across indolent cancers. For patients with MALT lymphoma, the hope is that a routine baseline scan, already performed in many centers, will one day do double duty: mapping the disease and forecasting its course, so that the small minority destined for early progression can be identified while their options are still widest.

Subject of Research: An integrated FDG PET/CT and clinicopathological nomogram for predicting progression-free survival in MALT lymphoma

Article Title: Development and internal evaluation of an integrated [18F]FDG PET/CT-clinicopathological nomogram for predicting progression-free survival in MALT lymphoma

Article References: Han, Y., Zhang, Y., Wu, R., Hu, F., Gao, Z., & Zhang, X. (2026). Development and internal evaluation of an integrated [18F]FDG PET/CT-clinicopathological nomogram for predicting progression-free survival in MALT lymphoma. BMC Medical Imaging. https://doi.org/10.1186/s12880-026-02847-6

Image Credits: AI Generated

DOI: 10.1186/s12880-026-02847-6

Keywords: MALT lymphoma, FDG PET/CT, nomogram, SUVmax, progression-free survival, prognosis, Ki-67 index, LASSO regression, Cox regression, bootstrap validation, MALT-IPI, nuclear medicine

Esophageal squamous cell carcinoma is one of the most common and lethal malignancies worldwide, and it is particularly prevalent in parts of East Asia. Treatment decisions increasingly hinge on PD-L1, a protein that tumor cells use to dampen the immune system’s attack. When PD-L1 is abundant on the tumor surface, immune checkpoint inhibitors, drugs that block the PD-1/PD-L1 interaction, tend to work well. The standard way to measure PD-L1 is immunohistochemistry, a laboratory technique in which a biopsy sample is stained with antibodies and scored using a combined positive score, or CPS, that reflects how many tumor and immune cells display the protein. Patients whose tumors score at or above a defined threshold are typically considered candidates for immunotherapy.

The problem is that this assessment requires tissue, and obtaining it is not always straightforward. Esophageal tumors sit deep in the chest, biopsies sample only a fragment of a heterogeneous tumor, and PD-L1 expression can vary across space and change over time. A noninvasive surrogate that could be read off a scan performed before treatment would be enormously valuable, allowing clinicians to stratify patients earlier and perhaps to repeat the assessment as the disease evolves. That is the premise behind the new study, led by Jiazhong Ren and Zheng Fu of the Department of Medical Imaging and Yongbin Cui and Yong Yin of the Department of Radiation Oncology Physics and Technology at Shandong Cancer Hospital and Institute, affiliated with Shandong First Medical University and the Shandong Academy of Medical Sciences.

The physics behind the approach is elegant. 18F-FDG is a radioactive analog of glucose that is taken up by metabolically active cells, and tumors, with their voracious appetite for energy, typically accumulate far more of the tracer than surrounding healthy tissue. The PET scanner converts this accumulation into standardized uptake values, or SUVs, which quantify how much tracer concentrates in a given region. The researchers measured a family of these parameters: the maximum standardized uptake value (SUVmax), which captures the single hottest pixel in the tumor; the mean (SUVmean) and peak (SUVpeak) values, which describe average and locally averaged intensity; the standard deviation (SUVsd), which reflects how heterogeneous the uptake is; and two volumetric measures, the metabolic tumor volume (MTV), the physical volume of metabolically active tumor, and total lesion glycolysis (TLG), which combines volume with intensity.

The team enrolled 89 patients with esophageal squamous cell carcinoma in this retrospective study. All patients underwent 18F-FDG PET/CT and had PD-L1 expression evaluated by immunohistochemistry on primary tumor tissue before receiving any anti-tumor treatment. The investigators also recorded a comprehensive set of clinicopathological characteristics, including age, gender, smoking status, drinking status, tumor location, vertical tumor length, TNM stage, and pathological grade. For the analysis, patients were divided into two groups: those with PD-L1-negative tumors, defined as a combined positive score below 10, and those with PD-L1-positive tumors, defined as a CPS of 10 or higher, a cutoff commonly used in clinical decision-making.

The results showed a clear statistical pattern. Four of the six metabolic parameters, SUVmax, SUVmean, SUVpeak, and SUVsd, were significantly higher in patients whose tumors expressed PD-L1 than in those whose tumors did not, with all comparisons reaching statistical significance at P values below 0.05. In other words, tumors that glowed more brightly and more unevenly on the PET scan were more likely to be PD-L1 positive. The volumetric measures, MTV and TLG, did not show the same association, suggesting that it is the intensity and heterogeneity of glucose metabolism, rather than the sheer bulk of metabolically active tissue, that tracks with this immune marker.

To quantify how well these imaging features could actually predict PD-L1 status, the researchers turned to receiver operating characteristic curve analysis, a standard statistical technique that plots true positive rates against false positive rates across all possible cutoff values. The area under the curve, or AUC, summarizes discriminative ability on a scale from 0.5, equivalent to a coin flip, to 1.0, perfect prediction. SUVmax achieved an AUC of 0.636 with a P value of 0.029, and SUVmean achieved an AUC of 0.628 with a P value of 0.044, both statistically significant but modest in magnitude. The optimal cutoff values were 19.74 for SUVmax and 10.01 for SUVmean, thresholds that could be applied to future patients, though with considerable uncertainty.

The team then used univariate logistic regression to examine each parameter’s independent association with PD-L1 positivity. SUVmax was the strongest predictor with a P value of 0.006, followed by SUVmean at 0.011, SUVpeak at 0.022, and SUVsd at 0.024. However, a technical complication emerged: these four SUV-derived parameters are all computed from the same underlying uptake distribution and are therefore severely multicollinear, meaning they carry heavily overlapping information and cannot be meaningfully combined in a single statistical model. Because of this severe multicollinearity, the researchers selected only SUVmax, the strongest individual predictor, for the final single-predictor logistic model, which retained its significance at P = 0.006.

The authors are explicit about what these numbers do and do not mean. An AUC of 0.636 represents discriminative performance that is only modestly better than chance, far below what would be needed for a reliable diagnostic test. Consequently, the study concludes that SUVmax should serve only as an auxiliary imaging reference rather than a dependable noninvasive substitute for pathological PD-L1 detection in patients with esophageal squamous cell carcinoma. This honest framing matters, because the temptation to overread an imaging-biomarker association is real, and premature clinical adoption of an imprecise surrogate could misdirect treatment decisions with serious consequences.

Nevertheless, the research adds to a growing body of work exploring how imaging phenotypes reflect molecular tumor characteristics, a field sometimes described as radiomics or imaging genomics. The biological plausibility is compelling: PD-L1 expression is often driven by inflammatory and oncogenic signaling pathways that also reprogram tumor metabolism, so a link between glucose avidity and immune checkpoint ligand expression is not surprising. The study was supported by the National Natural Science Foundation of China under grants 12275162 and 12575365, was approved by the Ethics Committee of the Cancer Hospital Affiliated to Shandong First Medical University in accordance with the Declaration of Helsinki, and was published open access on 29 September 2026. Future studies with larger cohorts, prospective designs, and possibly machine learning approaches that combine multiple imaging features may refine the predictive power enough to bring scan-based biomarker assessment closer to the clinic.

Subject of Research: The association between 18F-FDG PET/CT metabolic imaging parameters and PD-L1 expression in esophageal squamous cell carcinoma

Article Title: The predictive value of 18F-FDG PET/CT metabolic parameters for PD-L1 expression in esophageal squamous cell carcinoma

Article References: Ren, J., Cui, Y., Fu, Z., & Yin, Y. (2026). The predictive value of 18F-FDG PET/CT metabolic parameters for PD-L1 expression in esophageal squamous cell carcinoma. BMC Cancer. https://doi.org/10.1186/s12885-026-17026-7

Image Credits: AI Generated

DOI: 10.1186/s12885-026-17026-7

Keywords: 18F-FDG PET/CT, PD-L1, esophageal squamous cell carcinoma, SUVmax, metabolic parameters, immunotherapy biomarker, immunohistochemistry, combined positive score, cancer imaging, radiomics, tumor metabolism, BMC Cancer

The imaging technique at the heart of the study is ¹⁸F-fluorodeoxyglucose PET/CT, a hybrid technology that pairs the functional sensitivity of positron emission tomography with the anatomical detail of computed tomography. Fluorine-18 labelled fluorodeoxyglucose is a radioactive glucose analogue that cells import through the same transporters they use for ordinary sugar. Because most cancer cells run their metabolism on glycolysis even when oxygen is plentiful, the Warburg effect, malignant tissue accumulates the tracer far more avidly than surrounding healthy structures. A detector ring records the decay of the fluorine-18 isotope, and the resulting signal is converted into standardised uptake values, or SUVs, which quantify how intensely a given lesion traps glucose relative to the injected dose and body mass. The maximum standardised uptake value, SUVmax, captures the single hottest pixel within a lesion and has long served as a convenient, if imperfect, proxy for metabolic aggressiveness.

The Zhejiang team, led by Yunqi Zhu and corresponding author Xinhui Su, assembled thirty treatment-naïve patients with histologically confirmed testicular germ cell tumours who had undergone ¹⁸F-FDG PET/CT before any antitumour therapy. Twelve carried a diagnosis of seminoma and eighteen had non-seminomatous germ cell tumours, a group that encompasses embryonal carcinoma, yolk sac tumour, choriocarcinoma and other histologies, often in mixtures. Because the patients had not yet received chemotherapy, surgery or radiotherapy, the scans offered an unfiltered view of each tumour’s native metabolism, free from the confounding effects of treatment-induced inflammation or necrosis that plague post-therapy imaging.

The headline result is hard to overstate. Non-seminomatous tumours showed a median primary-tumour SUVmax of 16.66, compared with just 8.41 for seminomas, a difference that reached statistical significance at P equals 0.007. When the researchers looked instead at the hottest lesion anywhere in each patient, the gap widened further: 21.91 versus 8.41, with P below 0.001. In other words, the non-seminomatous tumours were burning through glucose at roughly twice the rate of their seminoma counterparts, a metabolic distinction that mirrors the known biological gulf between these entities. Non-seminomatous germ cell tumours tend to be more proliferative, more genetically chaotic and more prone to early haematogenous spread, and the PET data appear to capture that ferocity in a single number.

Disease extent itself was also strikingly different between the groups. Distant metastatic disease, classified as M1 under the American Joint Committee on Cancer staging system, was present in 55.6 percent of the non-seminomatous patients but only 8.3 percent of those with seminoma. This imbalance matters for interpretation, because a patient-level measurement such as the highest-lesion SUVmax can be inflated simply by the presence of a metabolically hot metastasis rather than by any intrinsic property of the primary tumour. The investigators were alert to this pitfall and designed their analyses accordingly, performing receiver operating characteristic analysis to compare diagnostic performance, restricting analyses to patients without distant metastases, and building exploratory multivariable models to adjust for tumour size and metastatic status.

Those sensitivity analyses proved revealing. When the analysis was confined to patients with M0 disease, meaning no distant metastases, the primary-tumour SUVmax remained significantly higher in non-seminomatous tumours, at 16.96 versus 8.00 with P equal to 0.001. However, the apparent advantage of the patient-level highest-lesion SUVmax over the primary-tumour measurement shrank dramatically: the difference in area under the receiver operating characteristic curve fell from 0.148 in the full cohort to just 0.023 in the metastasis-free subgroup. This tells an important story about what each metric actually measures. The highest-lesion SUVmax looked like a superb discriminator across all comers, achieving an apparent area under the curve of 0.944, but part of that performance was borrowed from the fact that metastatic spread is itself more common in non-seminomatous disease. The primary-tumour measurement, by contrast, appears to reflect genuine histology-linked biology.

The exploratory log-linear model drove the point home. After adjusting for primary-tumour size and M status, non-seminomatous tumours retained a higher primary-tumour SUVmax, with an adjusted geometric mean ratio of 1.67 relative to seminoma and a 95 percent confidence interval of 1.07 to 2.60, yielding P equal to 0.024. A geometric mean ratio of 1.67 implies that, on average, the non-seminomatous primary tumours took up roughly two-thirds more glucose than seminomas of comparable size and stage. For a single-centre study of thirty patients, this is an encouraging signal, though the authors are careful to label the modelling as exploratory and to emphasise that validation in larger independent cohorts is essential before any clinical application.

The study also placed PET-derived parameters alongside the traditional serum tumour markers that clinicians already use. Among individual biomarkers, the patient-level highest-lesion SUVmax showed the highest apparent discrimination with an area under the curve of 0.944, followed by alpha-fetoprotein at 0.910 and primary-tumour SUVmax at 0.796. Alpha-fetoprotein is a well-established hallmark of non-seminomatous histology, since seminomas do not produce it, so its strong showing is unsurprising. What is intriguing is that a purely metabolic imaging metric could rival a specific biochemical marker, suggesting that glucose avidity and embryonal differentiation are intertwined at a fundamental level. The researchers also computed a panel of volumetric parameters, including metabolic tumour volume, total lesion glycolysis and total metabolic tumour volume, which quantify not just how bright a lesion is but how much metabolically active tissue it contains, though the SUVmax comparisons dominated the significant findings.

Why should two tumours arising from the same primordial germ cell lineage differ so markedly in their sugar consumption? Seminomas are histologically homogeneous, composed of sheets of uniform cells resembling primitive spermatogonia, whereas non-seminomatous tumours can contain wildly divergent components, from gland-like yolk sac structures to syncytiotrophoblasts that secrete human chorionic gonadotropin. Embryonal carcinoma elements, in particular, are highly proliferative and express patterns of gene activity reminiscent of pluripotent stem cells, states that are metabolically expensive. Rapid proliferation demands nucleotide synthesis, lipid production and continuous ATP generation, all of which push cells toward intensified glycolysis and upregulated glucose transporters. The doubled SUVmax observed in non-seminomatous tumours is thus plausibly a readout of this underlying developmental chaos, though the study was not designed to identify the molecular mechanisms responsible.

The practical implications, if confirmed, could be meaningful. A pretreatment PET/CT that hints at histology could help clinicians anticipate the tumour type in settings where biopsy material is limited or ambiguous, flag patients at higher risk of harboring metastatic disease, and potentially refine surveillance strategies after orchiectomy. The authors themselves are appropriately measured, describing their work as a retrospective exploratory study of thirty patients from a single centre and calling for validation in larger, independent and ideally prospective cohorts. Such studies would need to address selection bias, scanner variability across institutions and the heterogeneity of non-seminomatous histologies. Still, the core observation stands out for its simplicity: before a single drop of chemotherapy, the two great families of testicular germ cell tumour already glow differently on a glucose scan, and that difference survives statistical scrutiny even when tumour size and spread are taken into account. It is a vivid reminder that cancer metabolism is not merely a byproduct of malignancy but a window into what a tumour truly is.

Subject of Research: Metabolic characteristics of testicular germ cell tumours on pretreatment ¹⁸F-FDG PET/CT imaging

Article Title: Pretreatment ¹⁸F-FDG PET/CT metabolic characteristics of seminoma and non-seminomatous testicular germ cell tumours: a retrospective exploratory study

Article References: Zhu, Y., Lu, X., Lin, L., Wang, H., Yu, Q., & Su, X. (2026). Pretreatment ¹⁸F-FDG PET/CT metabolic characteristics of seminoma and non-seminomatous testicular germ cell tumours: a retrospective exploratory study. BMC Medical Imaging. https://doi.org/10.1186/s12880-026-02855-6

Image Credits: AI Generated

DOI: 10.1186/s12880-026-02855-6

Keywords: testicular cancer, testicular germ cell tumour, seminoma, non-seminomatous germ cell tumour, ¹⁸F-FDG PET/CT, SUVmax, tumour metabolism, metabolic tumour volume, alpha-fetoprotein, cancer imaging, BMC Medical Imaging, diagnostic imaging