Fibrous dysplasia is a rare, mosaic skeletal disorder in which normal bone is replaced by fibro-osseous tissue. Disease activity typically peaks during childhood and diminishes by adulthood, and the extent and severity of skeletal involvement generally correlate with accelerated bone turnover. The patient had been diagnosed with mild polyostotic fibrous dysplasia 19 years before the new imaging findings.

Her history of precocious menarche at eight years of age later led clinicians to revise the diagnosis to fibrous dysplasia associated with McCune–Albright syndrome, abbreviated FD/MAS. Another defining feature of the patient’s medical history was permanent hypoparathyroidism. At age 31, she underwent total thyroidectomy for papillary thyroid cancer, and the operation was complicated by permanent hypoparathyroidism.

This condition became an important part of the case analysis because the measured bone-turnover markers did not follow the pattern generally associated with polyostotic fibrous dysplasia. During follow-up, 18F-sodium fluoride positron-emission tomography combined with computed tomography, or 18F-NaF PET/CT, identified rib lesions that had not been evident on an 18F-fluorodeoxyglucose PET/CT examination performed 19 years earlier when fibrous dysplasia was diagnosed. All of the newly detected skeletal foci showed morphological features consistent with fibrous dysplasia on the CT component of the NaF scan.

The report documents lesions recognized after a prolonged imaging interval; it does not establish when they arose or whether they represent renewed disease activity. Clinical and diagnostic checks did not offer an obvious alternative explanation for the rib findings. The patient had no clinical evidence of rib trauma and no biochemical or structural evidence of recurrent thyroid cancer.

The evidence therefore supports classifying the detected rib sites as additional skeletal manifestations consistent with fibrous dysplasia, while leaving open broader questions about their biological course in this adult case. Genetic testing supported the underlying diagnosis. Following target enrichment, next-generation sequencing of DNA extracted from the dysplastic right iliac bone identified the causal Arg201Cys variant in the GNAS gene.

The molecular result, combined with the earlier history of precocious puberty, established the revised classification as FD/MAS. Because the report concerns one person, however, the genetic finding characterizes this case rather than defining a general pattern for all adults with fibrous dysplasia. The most notable laboratory feature was the contrast among several bone-turnover indicators.

In polyostotic fibrous dysplasia, elevated markers would be expected in light of the association between skeletal involvement and accelerated bone turnover. In this patient, serum osteocalcin and alkaline phosphatase remained within their normal ranges. Procollagen type 1 N-terminal propeptide was the only marker reported as persistently elevated, staying three to four times above the upper limit of normal.

Authors suggested that this atypical profile could reflect the combined effects of FD/MAS and suppressed skeletal remodeling associated with hypoparathyroidism. That explanation remains a possibility rather than a demonstrated causal result. As a case report, the study offers a detailed clinical snapshot rather than a population-level estimate or controlled comparison.

Its scope is limited to one 42-year-old woman with mild polyostotic FD/MAS, permanent hypoparathyroidism, and additional rib foci detected on interval imaging. The authors’ principal conclusion is that skeletal lesions can become detectable in an adult case despite expected quiescence and that bone-turnover markers may display an unusual combination of normal and elevated results in the presence of FD/MAS and permanent hypoparathyroidism.

Subject of Research: Newly detected rib lesions and altered bone-turnover markers in adult fibrous dysplasia/McCune–Albright syndrome with hypoparathyroidism

Article Title: Adult fibrous dysplasia/McCune–Albright syndrome with hypoparathyroidism: additional skeletal lesions and an unusual bone turnover profile

Article References: Zajíčková, K., Včelák, J., Kuklíková, V., Černý, V., & Zogala, D. (2026). Adult fibrous dysplasia/McCune–Albright syndrome with hypoparathyroidism: additional skeletal lesions and an unusual bone turnover profile. BMC Endocrine Disorders. https://doi.org/10.1186/s12902-026-02687-z

Image Credits: AI Generated

DOI: 10.1186/s12902-026-02687-z

Keywords: fibrous dysplasia, McCune–Albright syndrome, hypoparathyroidism, rib lesions, bone turnover, PET/CT, GNAS variant, osteocalcin, procollagen type 1 N-terminal propeptide, Adult, fibrous, dysplasia

Several studies focused on transcriptomic risk models designed to estimate outcomes. In breast cancer, one investigation combined weighted gene co-expression network analysis, protein–protein interaction networks and LASSO-Cox regression to define a six-gene signature related to NETosis and inflammation. The genes were ZMYND10, IL12B, CXCL13, TFF1, LTB and SPIB, and the resulting risk score was reported to be independent of age and other clinical features. Five genes were confirmed by RT-qPCR; LTB was excluded because of limited tissue availability. A separate breast-cancer analysis derived and validated a seven-gene metastasis-associated signature in the TCGA-BRCA, AURORA US, SCAN-B and GEO cohorts. Tumors classified as low risk were described as immune-hot, with activated CD8+ T cells, whereas high-risk tumors showed T-cell exclusion and enrichment of kinase and metabolic pathways. RTN1 and TLR10 were proposed as candidate drivers, but their functional roles were not established.

In clear-cell renal cell carcinoma, investigators used single-cell and bulk transcriptomic data to construct a nucleotide-metabolism prognostic signature that was reported to outperform 122 previously published models. IFI30 was validated in laboratory experiments both in vitro and in vivo. That work did not establish that the signature can guide treatment decisions or improve outcomes in patients. Another breast-cancer study moved from prognosis toward prediction of response to neoadjuvant chemotherapy. A pretreatment 15-gene score achieved an area under the curve of 0.809 in one external cohort and 0.876 in another when predicting non-pathological complete response. The authors traced part of the signal to a pyruvate–CCND1–YAP1–HIF1A/ARNT–MET axis, found that serum pyruvate was elevated in tumors without a complete pathological response, and reported that capmatinib, a MET inhibitor, attenuated pyruvate-driven phenotypes. These findings nominate a pathway and compound for further testing, but they do not demonstrate clinical benefit from capmatinib in this setting.

In pancreatic ductal adenocarcinoma, investigators combined genes related to lactylation and programmed cell death to identify HMGA1 and KIF2C as core prognostic drivers. They supported the model with drug-sensitivity analyses and clinical specimens, connecting a molecular signature with candidate therapeutic compounds. The blood-cancer studies used complementary approaches spanning molecular prognosis, imaging prediction and routine clinical risk assessment. In DLBCL, SYTL4 was reported to be upregulated and independently associated with adverse outcome in a tissue-microarray subgroup, with a multivariable hazard ratio of 25.5, a 95% confidence interval of 1.8 to 367.3 and P = 0.017. The unusually wide confidence interval reflects the subgroup’s small size of 48 cases. SYTL4-high tumors were enriched for extracellular-matrix remodeling, whereas mitochondrial translation and oxidative phosphorylation were negatively enriched.

Another DLBCL study trained deep-learning models on features extracted from 18F-FDG PET/CT images to predict cancer-related cognitive impairment in patients without central nervous system involvement. This was a single-center study with a modest sample of 112 patients, making external validation a prerequisite before the approach could support clinical use. In chronic-phase CML, investigators compared three comorbidity indices—CCI, ACE-27 and CIRS-G—among 559 patients receiving flumatinib. CIRS-G contributed the largest incremental value for predicting 12-month major molecular response, with a change in area under the curve of 0.078. SHAP analysis exposed a nonlinear threshold at CIRS-G ≥ 8, above which predicted response declined, although the authors framed the finding as exploratory. The analysis therefore identifies a pattern in the model rather than demonstrating that comorbidity scoring can prospectively improve treatment selection.

Liquid biopsy contributed one candidate diagnostic panel to the collection. A study of publicly available microRNA-sequencing data identified a circulating three-miRNA panel—hsa-miR-29b-3p, hsa-miR-19b-3p and hsa-miR-30e-5p—for early-stage ovarian cancer. A random-forest classifier reached 91.7% accuracy and an area under the curve of 0.991, while pathway analysis implicated TP53 and VEGFA signaling. These retrospective performance figures do not establish accuracy in population screening or among symptomatic patients, both of which require confirmation. The editorial also notes that platelets and extracellular vesicles can carry tumor-derived material, including in cholangiocarcinoma. That observation raises the same unresolved question for these sample types: whether analytically detectable signals can be converted into reliable diagnostic measurements.

Two single-cell studies examined interactions among tumor, immune and stromal cell populations at a resolution that homogenized tissue samples can obscure. One profiled 70,760 cells from 11 melanoma samples, resolved nine subpopulations and used CellChat to infer signaling relationships. Prognostically favorable subpopulations engaged MIF–CD74/CD44/CXCR4 and MHC-I signaling, with CD8+ T cells as the predominant receivers. A derived 15-gene signature reached a mean concordance index of 0.675, and high EIF5A expression was associated with poor outcome. The other study combined single-cell transcriptomics with Mendelian randomization in lung adenocarcinoma, identifying seven prognostic genes related to endoplasmic-reticulum stress and butyrate metabolism: VDAC1, TXNRD1, GDF15, TRIB3, LPL, KCNQ1 and PKP2. The genes were validated by RT-qPCR, and the analysis placed macrophages centrally in progression. Both studies provide biological candidates that could be diluted when cells of different types and states are averaged together.

Across the collection, the most conspicuous limitation is the absence of prospective validation. Most analyses rely on public repositories, retrospective cohorts or data from a single institution, and the editorial states that none of the signatures is ready for inclusion in a clinical guideline. Prospective, multicenter validation with harmonized preprocessing will be needed to determine whether the reported associations persist in independent patients and translate into useful clinical decisions. Reporting standards also need to tighten as models become more complex. The authors recommend routine use of TRIPOD+AI for prediction-model studies and CLEAR for radiomics, with bias, calibration and failure modes assessed explicitly before deployment. Methods used to interpret model behavior, including SHAP attribution, attention weights and pathway mapping, should appear in the main report rather than only in supplementary material.

The authors identify spatial multi-omics as a natural next step for connecting single-cell inference with tissue architecture. Signatures that account for regional heterogeneity and distinguish immune-excluded from inflamed niches may generalize better than those derived from homogenized bulk tissue, while combining spatial context with liquid-biopsy dynamics could permit non-invasive tracking of spatial evolution. Spatial profiling was an explicit aim of the research call, however, and was absent from the collection. Multimodal frameworks that encode genomics, imaging, clinical text and longitudinal outcomes in one model are also attractive, but their bias, calibration and failure modes require explicit evaluation before clinical deployment. Eight of the 11 studies paired a computational hypothesis with orthogonal validation, providing useful examples of how bioinformatics findings can be checked experimentally. Taken together, the evidence supports a cautious conclusion: computational integration is generating cancer-biomarker candidates and illuminating biological pathways for investigation, while prospective testing, standardized reporting and clinical validation remain the decisive steps toward patient use.

Subject of Research: Computational cancer-biomarker discovery across solid tumors and blood malignancies

Article Title: Editorial: Bioinformatics and big data driving the discovery of clinical biomarkers for solid tumors and blood malignancies

Article References: Chen, M., Zhang, J., & Jiang, X. (2026). Editorial: Bioinformatics and big data driving the discovery of clinical biomarkers for solid tumors and blood malignancies. Frontiers in Genetics, 17, Article 1999998. https://doi.org/10.3389/fgene.2026.1999998

Image Credits: AI Generated

DOI: 10.3389/fgene.2026.1999998

Keywords: cancer biomarkers, bioinformatics, machine learning, single-cell analysis, liquid biopsy, multi-omics, PET/CT, prognostic signatures, prospective validation, solid tumors, hematologic malignancies, Editorial

Between-study heterogeneity in this bivariate assessment was low, with an I² of 9.8%. The findings position CXCR4-targeted PET/CT as a potential adjunct for selected patients, but the available evidence does not support replacing adrenal venous sampling or PET-guided surgery outside established protocols. The review was conducted in the context of reported high CXCR4 receptor expression in aldosterone-producing adenoma and growing attention to radiotracers such as ⁶⁸Ga-pentixafor.

Its clinical objective was to assess the diagnostic accuracy and utility of CXCR4-targeted PET/CT for identifying the side of aldosterone production in patients evaluated for this tumor type. Following PRISMA guidelines, the researchers searched three databases for studies that had used CXCR4-targeted PET/CT in patients with aldosterone-producing adenoma. The primary outcomes were sensitivity, specificity and diagnostic accuracy, assessed with both univariate and bivariate pooling methods for diagnostic-test-accuracy meta-analysis.

The univariate random-effects model produced a pooled sensitivity of 0.83 (95% CI, 0.776–0.874), specificity of 0.821 (0.700–0.901) and overall accuracy of 0.823 (0.774–0.862). The bivariate estimates were lower than the univariate estimates for both sensitivity and specificity, illustrating that the results varied with the statistical approach used to combine the studies. Predicted performance also differed between positive and negative test results.

In the univariate analysis, the positive predictive value was 0.918 (95% CI, 0.860–0.953), whereas the negative predictive value was 0.671 (0.564–0.763). These estimates showed moderate to substantial heterogeneity across the included studies, with I² values ranging from 43.8% to 67.2%. Published as an open-access systematic review and meta-analysis in BMC Medical Imaging on 20 October 2026, the article is based on 29 studies rather than a new prospective trial or direct comparison in one participant group.

The supplied version states that it was made available after peer-review acceptance, carries a permanent DOI and remains subject to further edits before the final version of record. Taken together, the pooled results support further evaluation of CXCR4-targeted PET/CT as an additional tool in selected patients, while the heterogeneity in predictive values and the limits of the current evidence prevent the imaging method from being presented as a replacement for established pathways.

Subject of Research: Diagnostic accuracy of CXCR4-targeted PET/CT for lateralizing primary aldosteronism in patients with aldosterone-producing adenoma

Article Title: Diagnostic accuracy of CXCR4-targeted PET/CT in primary aldosteronism: a systematic review and meta-analysis of 29 studies

Article References: Qattea, A., Aloraini, D. M., Altaweel, S., Alazmi, M. A. M., Alanazi, F. N., Alfallaj, M. A., Alshahrani, N. A., Aldaham, W., Balkair, Y. M., Alkhawaldeh, I. M., & Tulbah, R. (2026). Diagnostic accuracy of CXCR4-targeted PET/CT in primary aldosteronism: a systematic review and meta-analysis of 29 studies. BMC Medical Imaging. https://doi.org/10.1186/s12880-026-02952-6

Image Credits: AI Generated

DOI: 10.1186/s12880-026-02952-6

Keywords: CXCR4, PET/CT, primary aldosteronism, aldosterone-producing adenoma, diagnostic accuracy, meta-analysis, sensitivity, specificity, medical imaging, 68Ga-pentixafor, Diagnostic, accuracy

The research team assembled a retrospective cohort of 255 patients with histologically confirmed non-small cell lung cancer, every one of whom had undergone systematic lymph node dissection, meaning that the true pathological status of their lymph nodes was known with certainty. This gold-standard ground truth is critical, because many previous prediction studies relied on sampling rather than complete dissection, leaving room for missed metastases to distort the results. The patients were randomly divided, with stratification by their pathological lymph node status to preserve the balance of positive and negative cases, into a training cohort of 178 patients and an internal held-out test cohort of 77 patients.

Before any machine learning began, the investigators screened candidate predictors using univariable and multivariable logistic regression within the training cohort. This filtering step matters because feeding an algorithm hundreds of weakly informative variables invites overfitting, the statistical equivalent of memorizing noise. What survived the screen was strikingly parsimonious: central tumor location, elevated carcinoembryonic antigen, elevated squamous cell carcinoma antigen, and solid nodule status on imaging. Perhaps the most surprising finding was what did not survive. None of the quantitative PET metabolic parameters, such as standardized uptake values that measure how avidly a tumor consumes radioactive glucose, remained independently associated with lymph node metastasis.

That negative result challenges a widespread intuition. Positron emission tomography combined with computed tomography is a cornerstone of modern lung cancer staging, and many clinicians assume that the metabolic numbers extracted from these scans carry independent predictive power. In this dataset, once clinical location, serological tumor markers, and the morphological character of the nodule were accounted for, the quantitative metabolic measurements added nothing. The study’s title emphasizes morphological features for good reason: whether a nodule appears solid, as opposed to partly ground-glass in texture, turned out to be one of the four pillars of prediction, a visual quality that radiologists assess routinely.

With four predictors in hand, the team trained six different machine-learning algorithms, optimizing each through repeated nested five-fold cross-validation. Nested cross-validation is the rigorous way to tune hyperparameters while keeping an honest estimate of performance, since the inner loop selects settings and the outer loop evaluates them on data not used for that selection. Among the six candidates, XGBoost, a gradient-boosted decision tree method that builds an ensemble of weak learners sequentially, each correcting the errors of its predecessors, achieved the highest cross-validated area under the receiver operating characteristic curve in the training cohort: 0.735, with a 95 percent confidence interval of 0.653 to 0.813. It was therefore designated the primary model.

The decisive test came when all six models, frozen and unmodified, were applied to the held-out test cohort of 77 patients. XGBoost delivered an AUC of 0.747, with a 95 percent confidence interval of 0.631 to 0.846, confirming that its training performance was not an artifact of overfitting. An AUC in this range represents moderate discrimination, meaning the model separates patients with and without nodal spread considerably better than a coin flip but far short of diagnostic certainty. The authors also compared the test-set AUCs of all six algorithms using paired DeLong tests with Holm correction for multiple comparisons, and found no statistically significant differences among them, a humbling result for anyone hoping that a sophisticated algorithm would dramatically outperform its rivals.

To probe that point further, the researchers added a conventional multivariable logistic regression model using the same four predictors as a simple reference. On the test cohort, this old-fashioned statistical workhorse achieved an AUC of 0.733, with a confidence interval of 0.612 to 0.841, and a DeLong test found no significant difference from XGBoost, with a P value of 0.301. Even more telling, the logistic regression model posted a Brier score of 0.152, compared with 0.198 for XGBoost, indicating that the simpler model’s predicted probabilities were actually better calibrated to observed outcomes. In plain terms, a transparent equation with four terms matched the flagship machine-learning algorithm in discrimination and beat it in calibration.

The primary XGBoost model was additionally evaluated for calibration, clinical utility, and feature contribution using SHAP, or SHapley Additive exPlanations, a technique borrowed from cooperative game theory that assigns each feature a quantified contribution to every individual prediction. This interpretability layer is increasingly considered essential for clinical machine learning, because a black-box risk score that physicians cannot interrogate is unlikely to earn trust or survive regulatory scrutiny. The study also reported a high negative predictive value, meaning that when the model predicted an absence of lymph node metastasis, that reassurance was usually correct, a property with real surgical relevance for selecting patients who might safely avoid extended nodal dissection.

Yet the authors are admirably candid about the limits. The model’s positive predictive value was limited, so a positive prediction could not reliably confirm metastasis, and invasive pathological confirmation remains indispensable. The absence of significant differences among the six algorithms, combined with the near-identical performance of plain logistic regression, suggests that the predictive ceiling here is set by the information content of the four features themselves, not by the sophistication of the learner. Moderate discrimination, a modest sample of 255 patients from a single center, and an internal test cohort rather than a truly external one all argue for caution.

The study’s real contribution may be methodological discipline rather than algorithmic novelty. It demonstrates a standardized, transparent workflow, from predictor screening through nested cross-validation to held-out evaluation, calibration analysis, and SHAP-based explanation, using only parameters available before surgery. The authors conclude that external multicenter evaluation is required before any clinical implementation, and that the results support cautious interpretation. If future multi-institutional validation confirms these findings, the payoff could be meaningful: a simple, interpretable risk score, computable from a CT report and two blood tests, that helps surgeons stratify lymph node metastasis risk in non-small cell lung cancer and decide, with greater confidence, who needs the most aggressive nodal surgery and who does not.

Subject of Research: Predicting lymph node metastasis in non-small cell lung cancer using clinical, serological, and PET/CT-derived features with interpretable machine learning

Article Title: Predicting lymph node metastasis in non-small cell lung cancer using clinical and PET/CT-derived morphological features: An interpretable machine-learning study

Article References: Xu, Y., Hao, J., Dou, Y., & Zeng, B. (2026). Predicting lymph node metastasis in non-small cell lung cancer using clinical and PET/CT-derived morphological features: An interpretable machine-learning study. PLOS One, 21(10), e0361043. https://doi.org/10.1371/journal.pone.0361043

Image Credits: AI Generated

DOI: 10.1371/journal.pone.0361043

Keywords: non-small cell lung cancer, lymph node metastasis, machine learning, XGBoost, PET/CT, logistic regression, SHAP, tumor markers, carcinoembryonic antigen, cancer staging, predictive modeling, cross-validation

The patient’s journey began more than four months before her admission, when the low back pain first appeared without any identifiable trigger. By February 2026, dizziness and fatigue prompted her admission to the Department of Neurology at The First People’s Hospital of Yancheng. Cranial computed tomography revealed nothing abnormal, but the story changed dramatically when she underwent whole-body positron emission tomography combined with computed tomography, a technique that maps glucose metabolism throughout the body and lights up tissues consuming energy at malignant rates. The scan showed a hypermetabolic mass in the right lower uterine body near the cervix, with a maximum standardized uptake value of approximately 12.4, a figure firmly in the range of aggressive malignancy. Surrounding that finding were multiple diffuse nodules in both lungs, a nodule in liver segment five, enlarged iliac and para-aortic lymph nodes, and numerous osteoblastic bone lesions scattered across the skeleton, all showing elevated glucose metabolism.

Given the dominant uterine lesion and the pattern of spread, the imaging team’s initial interpretation was entirely reasonable: a primary uterine malignancy that had already metastasized widely. A diagnostic curettage performed in February 2026, however, returned only mucinous tissue from the endocervical canal and chronic inflammation of the cervix, with no malignant cells identified. That false negative, the authors explain, likely reflected the limited sampling area of curettage and the patchy, heterogeneous distribution of metastatic deposits within the uterus. Gastroscopy and colonoscopy were then used to exclude a gastrointestinal primary, yielding only a benign fundic gland polyp. Pelvic magnetic resonance imaging subsequently showed an abnormal signal at the uterine-cervical junction and metastatic signals in the right ilium and left acetabulum, prompting an ultrasound-guided percutaneous core-needle biopsy that would finally supply the tissue needed to solve the puzzle.

Under the microscope, the biopsy revealed poorly differentiated adenocarcinoma: tumor cells arranged in solid nests and sheets, lacking obvious glandular differentiation, with large irregular nuclei, coarse chromatin, prominent nuclear atypia, increased mitotic figures, and focal invasion of the supporting stroma. The problem was that this morphology overlapped almost completely with a poorly differentiated primary uterine adenocarcinoma. Morphology alone, the case demonstrates, simply cannot distinguish a metastasis from a primary tumor when the cancer has lost the architectural features that betray its origin. This diagnostic ambiguity is precisely why the case carries such educational weight, and why the authors argue that tissue-based diagnosis must extend far beyond routine staining when a patient presents with multiorgan disease of uncertain origin.

The decisive evidence came from immunohistochemistry, a technique that uses antibodies to detect specific proteins in tissue sections and thereby fingerprints a tumor’s cellular ancestry. The uterine lesion stained positive for TTF-1 and Napsin A, two markers highly characteristic of lung adenocarcinoma, and positive for CK7, a keratin consistent with pulmonary and other epithelial origins. Critically, the tumor was negative for PAX8, estrogen receptor, and progesterone receptor, the markers that typically define primary uterine adenocarcinomas. The authors are careful to note the nuance: TTF-1 positivity has occasionally been reported in a small number of endometrial adenocarcinomas, so no single marker is absolutely diagnostic. It is the combined signature, TTF-1, Napsin A, and CK7 positivity alongside PAX8, ER, and PR negativity, integrated with the clinical and imaging context, that pointed decisively to the lung.

Genomic testing then delivered both confirmation and a therapeutic roadmap. Using next-generation sequencing across a full exon panel on the biopsy tissue, the team detected an EGFR exon 21 p.L858R mutation, one of the commonest sensitizing alterations in lung adenocarcinoma and a well-established predictor of response to tyrosine kinase inhibitors. No other actionable gene alterations were found. A multidisciplinary team spanning gynecology, medical oncology, radiation oncology, pathology, radiology, and nuclear medicine therefore established the final diagnosis: stage IV lung adenocarcinoma with synchronous metastases to the uterus, lungs, liver, and bone, harboring a druggable EGFR mutation. The uterine mass, in other words, was never a uterine cancer at all; it was lung cancer wearing a disguise that only molecular analysis could strip away.

Treatment proceeded along two complementary tracks. The patient received palliative radiotherapy, 30 gray delivered in 10 fractions using 6 MV-X helical tomotherapy, targeting the osteoblastic bone lesions and the local uterine mass to relieve pain and reduce tumor burden. Simultaneously, she began oral osimertinib, a third-generation tyrosine kinase inhibitor that selectively inhibits mutant EGFR and has become first-line standard therapy for advanced EGFR-mutant lung adenocarcinoma. The combination demands vigilance, because radiotherapy and targeted therapy share potential overlapping toxicities, most notably radiation pneumonitis and myelosuppression. Throughout treatment, the team monitored blood counts and pulmonary function closely. Adverse events were limited to radiation-induced fatigue and mild myelosuppression, both of which improved with supportive care, demonstrating that the combined regimen is clinically feasible and well tolerated in this setting.

By the follow-up examination on July 30, 2026, contrast-enhanced CT of the chest and abdomen showed a marked reduction in the uterine tumor and pelvic lymph nodes, with pulmonary nodules essentially unchanged, a partial response by the RECIST 1.1 criteria. The authors emphasize that long-term follow-up will be needed to verify durability, but the early result underscores a broader principle of modern oncology: when genomic profiling identifies an actionable mutation, even a patient with widely metastatic, atypically presenting disease can achieve meaningful disease control and quality-of-life gains with targeted therapy rather than conventional chemotherapy.

The rarity of this presentation is what makes the case scientifically valuable. Among secondary tumors of the female genital tract, the ovaries account for roughly 76 percent of metastases and the vagina for about 13 percent, while the uterus represents only about 8 percent. A recent retrospective series of five patients, the largest to date, found that most presented with abnormal vaginal bleeding or abdominal pain and bloating. This patient differed on nearly every count: she was older, her symptoms were entirely non-gynecologic, imaging pointed toward a uterine primary, an initial curettage was negative, and her management combined palliative radiotherapy with osimertinib, a sequence rarely reported for uterine metastasis. Primary uterine malignancies typically announce themselves with abnormal bleeding or pelvic pain, whereas metastatic uterine tumors often lack these classic features, a contrast that directly contributed to the initial misdirection.

The clinical lesson the authors draw is unambiguous. Imaging, however sophisticated, can suggest but never confirm a tumor’s origin in patients with multiorgan lesions, and clinicians should resist anchoring on the most visually dominant lesion. The path to the correct diagnosis ran through targeted biopsy, a multi-index immunohistochemical panel, and molecular genetic testing, each layer correcting the assumptions of the last. For patients with cancer of unknown primary origin, this integrated approach is not optional but mandatory, because identifying the true primary site determines whether a patient receives chemotherapy, hormone therapy, or, as in this case, a mutation-targeted drug that can shrink disease across the body. As lung adenocarcinoma, which accounts for roughly 40 percent of all lung cancers, continues to lead global cancer mortality, awareness of its rarest metastatic patterns may be the difference between a delayed, misdirected workup and an early, precise, life-extending intervention.

Subject of Research: Uterine metastasis of lung adenocarcinoma mimicking a primary uterine malignancy

Article Title: Metastatic Lung Adenocarcinoma to the Uterus Mimicking a Primary Uterine Malignancy: A Case Report

Article References: Sun, P., & Wang, Y. (2026). Metastatic Lung Adenocarcinoma to the Uterus Mimicking a Primary Uterine Malignancy: A Case Report. Cancer Reports, 9(10), Article e70706. https://doi.org/10.1002/cnr2.70706

Image Credits: AI Generated

DOI: 10.1002/cnr2.70706

Keywords: lung adenocarcinoma, uterine metastasis, EGFR L858R, osimertinib, immunohistochemistry, TTF-1, Napsin A, PET-CT, misdiagnosis, targeted therapy, case report, palliative radiotherapy

The patient arrived at Hebei General Hospital complaining of nausea, vomiting, and pervasive fatigue. His blood pressure had climbed as high as 200/110 mmHg despite ten years of treatment, and laboratory tests told a consistent story: his serum potassium had fallen to 2.5 mmol/L, well below the normal range, while his plasma aldosterone concentration reached 771.100 pg/mL during upright renin-angiotensin-aldosterone system testing. The aldosterone-to-renin ratio exceeded 37, far above the screening threshold of 30 that strongly suggests primary aldosteronism, and a captopril suppression test failed to rein in his aldosterone levels, confirming that the hormone was being produced autonomously rather than under normal regulatory control.

Primary aldosteronism is an endocrine disorder in which the zona glomerulosa, the outermost layer of the adrenal cortex, secretes aldosterone without regard to the physiological signals that normally govern it. The resulting sodium retention expands plasma volume and suppresses renin activity, producing hypertension that is often resistant to conventional drugs, sometimes accompanied by dangerously low potassium. Aldosterone-producing adenomas, or APAs, are among the most common subtypes, and they typically appear as a single tumor on one adrenal gland. Bilateral involvement, in which multiple adenomas arise on both glands simultaneously, is rare and diagnostically treacherous, because it upends the standard assumption that removing one gland will cure the disease.

Contrast-enhanced computed tomography revealed multiple bilateral adrenal adenomas in this patient, each showing mild-to-moderate heterogeneous enhancement with a rapid wash-in and wash-out pattern characteristic of benign adrenal masses. But CT has a fundamental limitation: it can depict structure without revealing function. Small adenomas under one centimeter in diameter are frequently missed altogether, and even when lesions are seen, the scan cannot determine which of them are actually secreting aldosterone. The team turned to adrenal vein sampling, the invasive catheter-based procedure considered the diagnostic gold standard for lateralizing aldosterone excess, but the attempt failed to identify a dominant side, a failure that in itself hinted at bilateral disease.

That is where gallium-68 pentixafor entered the picture. The tracer is a high-affinity ligand for CXCR4, a G-protein-coupled receptor that sits on the cell membrane of APA cells and correlates strongly with the expression of aldosterone synthase, the enzyme encoded by the CYP11B2 gene that catalyzes the final step of aldosterone synthesis. Because the receptor is abundantly displayed on functional aldosterone-producing cells, a positron emission tomography scan with pentixafor can visualize not just where adrenal nodules are, but which ones are metabolically equipped to produce the hormone. Thirty minutes after an intravenous injection of 3.5 mCi, or 129.5 MBq, of the tracer, the PET/CT images revealed five distinct nodular lesions across both adrenal glands, every one of them taking up the radioactive signal to a measurable degree.

The quantitative details were remarkable. The nodule in the medial branch of the left adrenal gland showed the highest metabolic activity, with a maximum standardized uptake value, or SUVmax, of 31.3, against a mean SUV of 2.26 for normal liver parenchyma and 3.41 for normal adrenal cortex. The lesion-to-liver ratios for the five lesions ranged from 2.38 to 13.85, and the lesion-to-normal-adrenal ratios ranged from 1.58 to 9.18. Established diagnostic thresholds for APA on pentixafor PET/CT are a lesion-to-liver ratio of at least 2.5 and a lesion-to-normal-adrenal ratio of at least 2.4, and every one of the five nodules exceeded both cutoffs. Integrating these functional findings with the laboratory data and the CT morphology, the clinical team classified all five adenomas as functional aldosterone-producing lesions.

The therapeutic implication was decisive. Because the disease was bilateral and multifocal, with no single dominant gland to remove, surgery was unsuitable; excising one adrenal would leave the contralateral tumors free to keep secreting. Instead, the patient opted for conservative medical management, and his regimen was switched to a mineralocorticoid receptor antagonist, a drug class that blocks the action of aldosterone at its receptor. Within thirty days, his serum potassium had normalized to 4.3 mmol/L and his blood pressure remained within normal limits, a rapid and gratifying response that validated the diagnostic reasoning behind the treatment choice.

The case also carries a broader scientific signal. Prior research has shown that functional APAs take up gallium-68 pentixafor significantly more avidly than nonfunctional adrenal nodules on the opposite side, with more than 90 percent of functional nodules demonstrating tracer uptake, and that CXCR4 expression correlates significantly with CYP11B2. In this patient, the SUVmax of the left medial nodule was markedly higher than those of the other four, suggesting a potential positive correlation between tracer uptake and the intensity of aldosterone secretion. If confirmed in larger cohorts, SUVmax measurements could serve as an indirect, noninvasive readout of the hormone-producing capacity of individual adrenal lesions, allowing clinicians to rank nodules by function rather than merely by size.

For decades, the diagnostic pathway for primary aldosteronism has rested on an awkward pairing: CT, which finds anatomy but not function, and adrenal vein sampling, which probes function but requires catheterizing the tiny adrenal veins, a technically demanding procedure with complication risks that has limited its widespread adoption. Bilateral disease imposes further constraints on AVS, because excess aldosterone pouring from both sides can obscure the identification of any dominant source. A single pentixafor PET/CT scan, by contrast, delivers simultaneous morphological and functional assessment in one noninvasive session, compensating for the weaknesses of both conventional tools and proving especially valuable in multifocal or bilateral adrenal pathologies of exactly the kind seen here.

The authors of the report are careful to note that a single case cannot establish clinical practice, and that the diagnostic thresholds and the SUVmax-aldosterone correlation they observed require validation in larger sample sizes. They also caution that CXCR4 is not exclusive to APAs; it is detectable in other adrenal lesions, including cortisol-producing adenomas, so interpretation must always be anchored in the full clinical and laboratory context. Even with those caveats, the case stands as a compelling proof of concept: one scan, five glowing lesions, and a treatment decision that restored a long-suffering patient’s potassium and blood pressure to normal within a month. As molecular imaging of endocrine hypertension matures, scans like this one may become the decisive instrument for untangling which adrenal nodules matter, and what to do about them.

Subject of Research: Molecular PET/CT imaging of bilateral aldosterone-producing adrenal adenomas using the CXCR4-targeted tracer 68Ga-pentixafor

Article Title: Case Report: Five positive lesions on bilateral adrenal glands detected by a single 68Ga-pentixafor PET/CT

Article References: Mao, Z., Zheng, L., Hua, R., Wu, D., Shi, Y., Zhang, X., Hu, Y., & Bian, Y. (2026). Case Report: Five positive lesions on bilateral adrenal glands detected by a single 68Ga-pentixafor PET/CT. Frontiers in Nuclear Medicine, 6, Article 1676221. https://doi.org/10.3389/fnume.2026.1676221

Image Credits: AI Generated

DOI: 10.3389/fnume.2026.1676221

Keywords: primary aldosteronism, aldosterone-producing adenoma, 68Ga-pentixafor, PET/CT, CXCR4, adrenal glands, hypertension, hypokalemia, adrenal vein sampling, molecular imaging, mineralocorticoid receptor antagonist, case report

Perhaps the most striking preclinical result comes from a new radiohybrid ligand pair designed for prostate cancer, a platform that fuses imaging and targeted alpha therapy in a single chemical scaffold. In mouse models, the therapeutic agent achieved 2.2-fold to 3.5-fold higher tumor uptake than a reference agent, while producing similar effects on tumor growth and survival. That combination is significant because targeted alpha therapy delivers highly potent, short-range radiation directly to tumor cells, and improving delivery to the tumor while sparing healthy tissue is the central challenge of the approach. The radiohybrid chemistry allows the same targeting molecule to be labeled with either an imaging isotope or a therapeutic alpha emitter, meaning physicians could potentially visualize where a drug goes before committing a patient to treatment. The authors say the findings support further investigation of this strategy, a step toward the kind of paired diagnostic-and-therapy paradigm that defines modern theranostics.

Artificial intelligence is the second major theme of the new releases. In a multicenter study, researchers built a vision–language model that integrates PET or SPECT imaging with clinical data to predict 24-month survival in patients with metastatic castration-resistant prostate cancer who are receiving PSMA-targeted radiopharmaceutical therapy. The model achieved 81.8 percent accuracy, outperforming conventional machine-learning approaches and showing promise in external validation—an important test of whether an algorithm trained at one set of hospitals can generalize to patients it has never seen. Metastatic castration-resistant prostate cancer is the lethal, treatment-refractory stage of the disease, and PSMA-targeted radioligand therapy has rapidly become a mainstay for these patients. A tool that can forecast survival from combined imaging and clinical inputs could help clinicians decide who benefits most from therapy, intensify treatment for high-risk patients, or redirect those unlikely to respond toward alternatives earlier in the course of disease.

Radiopharmaceutical therapy itself is expanding beyond prostate cancer. A French multicenter study evaluated lutetium-177 DOTATATE—(177)Lu-DOTATATE—in 69 patients with meningiomas that had not responded to previous treatments. These tumors arise from the membranes surrounding the brain and spinal cord, and when they resist surgery and radiation, options become scarce. The results offer a genuine foothold: six-month progression-free survival was 70 percent, with a median progression-free survival of 14.6 months. Grade 3 adverse events, mainly lymphopenia—a depletion of infection-fighting white blood cells—occurred in 16 percent of patients. For a tumor type long managed with blunt instruments, a receptor-targeted radiopharmaceutical that exploits somatostatin receptors on meningioma cells represents a meaningful shift toward molecularly guided care.

Complementing the therapeutic study, a separate investigation showed that quantitative PET measurements can capture the biology that makes such therapy possible. In 44 patients with meningiomas, quantitative measurements from gallium-68 DOTATATE PET/CT strongly correlated with Krenning scores, the visual scale clinicians use to grade somatostatin receptor expression. Two measures stood out: SUVmax, the maximum standardized uptake value within a lesion, and a ratio normalized to the superior sagittal sinus, a major venous channel that serves as an internal reference. These metrics distinguished clinically relevant scoring categories with areas under the curve reaching 0.98—near-perfect discrimination on the standard 0-to-1 scale. The implication is that visual scoring, which depends on reader experience, could increasingly be supplemented or replaced by reproducible numbers, standardizing patient selection for receptor-targeted therapy and trials.

Breast cancer imaging also received a boost. In a study of 30 patients, a targeted tracer called gallium-68 B7H3-BCH—(68)Ga-B7H3-BCH—used with PET/CT detected 96.8 percent of lesions, compared with 92.4 percent for standard fluorine-18 FDG PET/CT, the workhorse scan used across oncology. The difference may sound incremental, but its consequences were not: findings from the targeted scan prompted a change in disease stage or treatment in eight patients. B7H3 is a molecule associated with aggressive tumor biology, and a tracer that homes in on it can reveal disease that glucose-based imaging misses. In breast cancer, where the presence and location of additional lesions can determine whether a patient receives surgery, systemic therapy or both, a scan that changes management in roughly a quarter of a small cohort is a result that demands larger trials.

Behind every quantitative advance in nuclear medicine lies a quieter question: can the numbers be trusted? A prospective, two-center study addressed exactly that by evaluating the repeatability of fluorine-18 FDG PET/MRI measurements across different cancers and scanner models. Within-subject variability for SUVmax ranged from 9.5 percent to 12.3 percent, while SUVpeak variability was tighter, at 8.8 percent to 9.6 percent. Notably, differences in attenuation-correction maps—the computational corrections that account for how tissue absorbs radiation—had minimal impact on measurement repeatability. This matters because PET/MRI is a hybrid technology whose attenuation correction can be implemented in several ways; if those choices destabilized measurements, quantitative comparisons across centers would be compromised. The study suggests SUVpeak may be the more robust metric and that the technology is ready for the kind of multicenter quantitative trials modern oncology requires.

The final study ventures into territory rarely mapped: the normal body. In 20 adults without active malignancy, researchers examined the distribution of fluorine-18 AraG, a PET tracer that accumulates in activated T cells, the immune system’s front-line soldiers. Uptake patterns varied across brown adipose tissue, bone marrow, breast implant regions and the lungs, with some findings associated with medications or prior respiratory conditions. The work establishes a baseline atlas of where immune activation appears in healthy people, which is essential before the tracer can be used to image immunotherapy response in cancer patients. Immune imaging has long been a goal of oncology—being able to see whether checkpoint inhibitors are igniting a T-cell response in a tumor would be transformative—but such efforts require knowing what normal looks like first. This study provides that reference point, while also flagging confounders, from common medications to prior respiratory illness, that could otherwise be mistaken for pathology.

Taken together, the seven studies sketch the trajectory of a field that is becoming simultaneously more powerful and more precise. Therapeutic molecules are being engineered for better tumor delivery; AI models are learning to read images and clinical records together to forecast survival; targeted tracers are finding lesions that standard scans miss and changing treatment decisions as a result; and quantitative methods are being validated for repeatability across scanners and centers. The Journal of Nuclear Medicine, accessed more than 90 million times each year by practitioners worldwide, functions as the central clearinghouse for this progress, and its ahead-of-print pipeline means these findings reach clinicians before the formal issue date. For patients with cancers that resist conventional treatment—from refractory meningiomas to metastatic prostate disease—the studies offer something increasingly rare in oncology: multiple independent lines of evidence that molecular imaging and targeted radiopharmaceutical therapy are converting previously untreatable disease into manageable, measurable targets.

The broader significance of the research extends beyond any single result. Theranostics, the discipline that pairs a diagnostic isotope with a therapeutic one using the same targeting molecule, is moving from concept to clinical routine, and each of these studies contributes a piece: the radiohybrid ligands demonstrate the chemistry, the vision–language model demonstrates the analytics, the meningioma and breast cancer studies demonstrate the clinical applications, and the repeatability and baseline studies demonstrate the metrology that makes it all trustworthy. As the Society of Nuclear Medicine and Molecular Imaging notes, the goal is precision medicine—diagnosis and treatment tailored to individual patients to achieve the best possible outcomes. The October 2026 ahead-of-print releases show that goal being pursued on every front at once, from the chemistry bench to the scanner to the algorithm, and for patients facing the hardest diagnoses, that convergence cannot come soon enough.

Subject of Research: Advances in nuclear medicine imaging and radiopharmaceutical therapy for cancer

Article Title: The Journal of Nuclear Medicine ahead-of-print tip sheet: October 16, 2026

Article References: The Journal of Nuclear Medicine ahead-of-print tip sheet: October 16, 2026. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: nuclear medicine, theranostics, prostate cancer, radiopharmaceutical therapy, PET/CT, PET/MRI, meningioma, breast cancer imaging, artificial intelligence, PSMA-targeted therapy, molecular imaging, DOTATATE

The review, authored by Aaditya Sinha and Arnie Purushotham of King’s College London, synthesizes evidence from five key clinical studies of intraoperative specimen imaging technologies. The unifying principle is elegant: patients receive an intravenous injection of 18F-fluorodeoxyglucose, or 18F-FDG, a radiolabelled glucose analogue that accumulates preferentially in malignant tissue. Because breast cancer cells, like many tumors, exhibit the Warburg effect and rely heavily on aerobic glycolysis, they import glucose at rates far exceeding those of healthy tissue. The tracer enters cells through glucose transporters, chiefly GLUT1, and is phosphorylated by hexokinase into 18F-FDG-6-phosphate, which cannot proceed through glycolysis and becomes metabolically trapped inside the cell. The result is a molecular beacon that marks tumor tissue with a brightness proportional to its metabolic activity.

Three distinct imaging modalities have emerged to read that signal from excised lumpectomy specimens. The first, Cerenkov luminescence imaging, or CLI, capitalizes on a phenomenon first documented by the Russian scientist Pavel Cerenkov in 1934. When positrons emitted by decaying 18F travel through tissue faster than light travels in that medium, they polarize surrounding molecules, which then relax and emit faint blue optical photons. Sensitive cameras can capture this intrinsic glow without any external light source, revealing where FDG-avid tumor cells sit relative to the cut edge of the specimen. In a first-in-human feasibility study, Grootendorst and colleagues injected patients with 150 to 230 MBq of 18F-FDG roughly 45 to 60 minutes before surgery and imaged 15 margins from 12 patients. CLI achieved 89 percent sensitivity and 95 percent specificity, correctly identified elevated tumor radiance in 10 of 12 patients, and showed strong agreement with histopathology, with a kappa statistic of 0.81 and an interrater reliability among surgeons of 0.912.

The second technique, flexible autoradiography, or FAR, takes a different physical approach. Instead of detecting Cerenkov photons, it places a thin scintillating film in direct contact with the excised tissue, capturing beta particles emitted by FDG-labelled cancer cells and converting them into scintillations that yield high-resolution surface maps of tracer activity. Because the detector sits millimeters from the tissue, FAR achieves millimetre to sub-millimetre spatial resolution, far exceeding standard gamma-based approaches. A multicentre first-in-human study by Jurrius and colleagues enrolled 66 patients who received about 3 MBq/kg of 18F-FDG preoperatively, with imaging completed within 10 minutes of excision. The technique delivered an overall diagnostic accuracy of 80.5 percent, with 46.2 percent sensitivity and 81.7 percent specificity. Notably, in a high-activity subgroup, sensitivity rose to 71.4 percent and the negative predictive value reached 98.4 percent, suggesting the method is most reliable when tracer uptake is strong.

The third and most technically ambitious approach combines both optical modalities. In the CLI-FAR technique, evaluated prospectively at Guy’s Hospital in the United Kingdom by Sinha and colleagues, patients received a standardized 250 MBq dose of 18F-FDG approximately 145 minutes before intraoperative imaging. Excised specimens were first imaged with three-dimensional intraoperative X-ray, then CLI-FAR was applied to margins suspected of involvement, or to the two closest margins when no suspicion existed. Seven trained consultant surgeons reviewed every intraoperative finding and acted on them immediately, excising additional tissue when imaging suggested residual disease. Histopathologists, blinded to the imaging results, then independently assessed margin status, tumor type and grade, receptor status, and lymphovascular invasion. The dual-modality approach achieved 76.9 percent sensitivity and a striking 97.8 percent specificity, and reduced re-excision rates by 69 percent, with an average image interpretation time of just six minutes.

All three optical techniques rely on the LightPath imaging system, an in vitro diagnostic device developed by Lightpoint Medical in the United Kingdom. The system centers on an ultrasensitive electron-multiplying charge-coupled device camera, paired with a white-light reference camera, housed in a fully light-tight specimen chamber. For CLI, the specimen is imaged uncovered, with the camera detecting Cerenkov photons in the 550 to 850 nanometre wavelength range. For FAR, a 12-micrometre scintillator is affixed to the specimen, separated by a 3-micrometre Mylar sheet to prevent contamination, and a band-pass filter isolates the scintillation signal. Each acquisition takes 300 seconds with 8-by-8 pixel binning, and each margin must be imaged individually because the camera captures only a two-dimensional field at any moment.

The fourth technology abandons optical detection altogether in favor of true three-dimensional tomography. The XEOS AURA 10 is the first and currently the only mobile PET/CT specimen imager designed for the operating room, combining a high-sensitivity PET detector with a built-in CT scanner. Its small field of view and dedicated design yield roughly five-fold higher spatial resolution than conventional whole-body PET, allowing sub-centimetre foci of residual FDG-avid tumor to be localized in three dimensions within minutes of excision. A proof-of-concept study by Göker and colleagues imaged 20 patients using the MOLECUBES micro-PET and micro-CT scanners, with a supervised automated algorithm segmenting regions of elevated uptake. Automated image analysis achieved 90 percent sensitivity but only 60 percent specificity, with an area under the curve of 0.86, while blinded surgeon interpretation reached 79 percent sensitivity and 72 percent specificity. The subsequent BIMAP study, conducted in Belgium by De Crem and colleagues with 41 patients, using the integrated AURA 10 device, achieved 91 percent sensitivity and 94 percent specificity, particularly in invasive ductal carcinoma, and enabled four patients to avoid additional surgery. The estimated number needed to treat to prevent one reoperation was just four.

Beyond diagnostic accuracy, the practical advantages of these techniques are considerable. Radiation exposure to surgical staff across all studies remained low, ranging from approximately 15 to 38 microsieverts per procedure, well within safe occupational limits, and imaging added minimal time to operative workflows. Unlike frozen section analysis or specimen radiography, which rely on anatomical landmarks or slow laboratory processing, radionuclide imaging detects metabolic activity directly, offering a molecular perspective that can reveal microscopic residual disease invisible to palpation or conventional imaging. The technologies are also portable: they have been deployed in general hospital settings without on-site PET/CT infrastructure, as Lambert and colleagues demonstrated in a feasibility study covering 32 surgical procedures across multiple malignancies, including breast, thyroid, renal, prostate, and skin cancers, all completed intraoperatively with a median staff dose of about 15 microsieverts.

Significant challenges remain, however. CLI is vulnerable to chemiluminescence artifacts that require substantial training to distinguish from true radioactivity, and the standardized scintillator used for FAR can only accommodate specimens up to 4 centimetres in diameter, a limitation that becomes acute as oncoplastic procedures increasingly produce larger specimens, though larger scintillators are becoming available. FDG-PET also performs poorly in tumors with low intrinsic glucose metabolism, such as invasive lobular carcinoma and in situ lesions, which can produce false negatives. Timing is another constraint: 18F-FDG has a physical half-life of about 109.7 minutes, and while acceptable imaging results can be achieved up to roughly 180 minutes post-injection, a target interval of 60 to 120 minutes is generally recommended, demanding careful coordination between radiopharmacy, surgery, and imaging teams. PET interpretation also carries a learning curve, and the review’s authors suggest that involving radiologists or nuclear medicine physicians in real-time image reading could further improve accuracy, at the cost of additional coordination.

Despite these hurdles, the accumulated evidence paints a compelling picture. Across CLI, FAR, CLI-FAR, and intraoperative PET/CT, imaging findings correlate robustly with histopathological gold standards, re-excision rates fall substantially when results are acted upon immediately, and the techniques integrate into existing surgical workflows without requiring operating theatres to be rebuilt around nuclear medicine infrastructure. The review’s authors conclude that radionuclide-based intraoperative specimen imaging represents a transformative opportunity for precision-guided oncologic surgery, one that could spare thousands of breast cancer patients the physical and psychological burden of a second operation. As larger scintillators, refined interpretive algorithms, and tailored imaging protocols mature, the prospect of a single, definitive cancer surgery, guided by the faint blue glow of a decaying isotope, moves steadily closer to routine clinical practice.

Subject of Research: Radionuclide imaging techniques for intraoperative margin assessment in breast-conserving surgery

Article Title: A review on the use of radionuclide imaging techniques to detect margin positivity in intraoperative specimens during breast-conserving surgery

Article References: Sinha, A., & Purushotham, A. (2025). A review on the use of radionuclide imaging techniques to detect margin positivity in intraoperative specimens during breast-conserving surgery. Frontiers in Medical Engineering, 3, Article 1628589. https://doi.org/10.3389/fmede.2025.1628589

Image Credits: AI Generated

DOI: 10.3389/fmede.2025.1628589

Keywords: breast cancer, breast-conserving surgery, surgical margins, Cerenkov luminescence imaging, flexible autoradiography, PET/CT, 18F-FDG, re-excision, intraoperative imaging, radiotracers, molecular imaging, oncological surgery

The diagnostic journey began conventionally enough. Blood tests showed neutrophilic leukocytosis, mild anemia, and elevated platelet counts, with a white blood cell count of 15.95 × 10⁹ per liter and an erythrocyte sedimentation rate of 92 millimeters per hour. Ultrasound of the head and neck disclosed multiple enlarged, hypoechoic lymph nodes measuring up to three centimeters, some with irregular vascularization. An excisional lymph node biopsy settled the question of what was wrong: classical Hodgkin lymphoma, nodular sclerosis subtype. A staging PET-CT scan then mapped the disease to stage IIB, showing hypermetabolic lymphadenopathy above the diaphragm, but it also flagged something unexpected, a focal area of increased FDG uptake in the right pericardiac region that raised the possibility of cardiac or pericardial involvement by the lymphoma itself.

Before chemotherapy could begin, clinicians placed a peripherally inserted central catheter, a PICC line, to secure reliable venous access for the months of treatment ahead. Thirteen days later, a transthoracic echocardiogram performed as part of the pre-treatment assessment delivered a jolt: a 3.5 by 2.4 centimeter mass, lobulated and isoechoic, adherent to the lateral wall of the right atrium and extending toward the tricuspid valve plane. Critically, the mass was not obstructing venous inflow through the vena cava and had not compromised the patient’s hemodynamics. She felt nothing from it. An asymptomatic mass the size of a small plum, sitting inside the heart of a young woman about to start curative chemotherapy, presented her physicians with an urgent two-part question: was it tumor or thrombus, and how should it be treated?

The answer came from cardiac magnetic resonance imaging, the workhorse of modern tissue characterization. The CMR showed a right atrial mass with isointense signal on cine, T1-weighted, and T2-weighted sequences, internal signal heterogeneity, and, most tellingly, an absence of both first-pass perfusion and late gadolinium enhancement. In plain terms, the lesion had no blood supply of its own. Tumors, by contrast, are vascular structures that light up when contrast agent courses through them. An avascular, non-enhancing mass is the signature of a thrombus, a stationary clot, and the imaging team concluded that this was not lymphomatous infiltration of the heart but a floating clot anchored to the atrial wall.

Anticoagulation was started immediately, first with low-molecular-weight heparin at 6,000 international units daily, then escalated to full therapeutic dosing of 8,000 international units twice daily. Once specialists weighed the competing demands of clot control and chemotherapy compatibility, the regimen was transitioned to apixaban, a direct oral anticoagulant, at 5 milligrams twice daily, which the patient continues to take. The choice was not arbitrary. Doxorubicin, a cornerstone drug of the ABVD regimen used in Hodgkin lymphoma, can reduce the area under the curve of apixaban, potentially lowering its systemic exposure and weakening its anticoagulant effect. Sequencing the therapies, heparin first during the most intensive phase, apixaban later, allowed the team to navigate this pharmacological interaction safely.

The patient then received the HD17 regimen, two cycles of escalated BEACOPP followed by two cycles of ABVD, and completed the planned course without significant treatment-related or thrombotic complications. End-of-treatment PET-CT demonstrated a complete metabolic response, scored as Deauville 2, meaning no residual metabolically active lymphoma. A follow-up echocardiogram performed one month after treatment completion showed the right atrial mass had shrunk from 3.5 by 2.4 centimeters to 1.7 by 1.2 centimeters, still without any obstruction to venous inflow. The patient remains under surveillance with no relapse or other significant clinical events recorded.

What makes this case scientifically interesting is the timing. Venous thromboembolism is a well-recognized complication of hematologic malignancies, with reported incidence in lymphoma patients ranging from 4 to 10 percent, and rates as high as 1.5 to 13 percent in studies of lymphoma-associated thrombosis more broadly. But the overwhelming majority of these events occur during active chemotherapy or after placement of a central venous catheter. Thrombosis detected before any systemic treatment has begun is genuinely uncommon, and intracardiac thrombosis is rarer still. A review of the published literature on Hodgkin lymphoma turned up only a handful of comparable cases, and every one of them occurred during or after treatment, never at diagnosis.

The Padua team is careful about attribution. The 13-day interval between PICC placement and echocardiographic detection of the mass strongly suggests a catheter-related or catheter-contributed mechanism. Central venous catheters promote clot formation through several pathways: local endothelial injury during insertion, disturbed blood flow around the catheter tip, and activation of the coagulation cascade on the foreign-body surface. In a patient whose lymphoma had already pushed her into a hypercoagulable state, with elevated white cells, platelets, and inflammatory markers, these catheter effects may have found fertile ground. Yet the authors acknowledge a fundamental limitation: no cardiac imaging was performed before the PICC was inserted, so it is impossible to determine whether the thrombus was already present, partially formed, or entirely catheter-induced. The honest answer is that both malignancy-related hypercoagulability and the catheter likely contributed.

The case also underscores how easily such a finding can be misread. The focal FDG uptake on the staging PET-CT initially raised concern that the lymphoma had reached the heart or pericardium, a scenario that would have altered both staging and treatment. But detailed reassessment showed the uptake was not anatomically concordant with the interatrial mass seen on echocardiography, and the CMR findings pointed decisively toward thrombus rather than tumor. This distinction mattered enormously: anticoagulation is the right treatment for a clot but would be useless against lymphomatous tissue, while chemotherapy addresses the cancer but leaves a thrombus in place. Multimodality imaging, echocardiography for rapid detection and hemodynamic assessment, CMR for tissue characterization, and PET-CT for metabolic mapping, was what allowed the team to thread this needle correctly.

Management of right atrial thrombosis remains a matter of debate, with evidence drawn largely from case reports and small series rather than controlled trials. Options include systemic anticoagulation, thrombolysis, and surgical thrombectomy, selected according to thrombus size, mobility, hemodynamic compromise, and embolization risk. For clinically stable patients with cancer-associated thrombosis, guidelines from the American Society of Hematology recommend low-molecular-weight heparin or direct oral anticoagulants as first-line therapy, which is precisely the path this patient followed. Her outcome, complete lymphoma remission, a shrinking clot, and no thromboembolic or hemorrhagic events, illustrates what early recognition and coordinated hematologic, cardiological, and oncologic care can achieve. The broader lesson for clinicians is uncomfortable but clear: in newly diagnosed lymphoma patients, an incidental right atrial mass may be a clot, not cancer, and distinguishing between the two before starting treatment can change everything that follows.

Subject of Research: Right atrial thrombosis detected before treatment in a patient with newly diagnosed classical Hodgkin lymphoma

Article Title: Right atrial thrombus in treatment-naive patient with an early-stage classical Hodgkin lymphoma: a case report and review of the literature

Article References: Giordano, A., Bodanza, V., Angotzi, F., Cellini, A., Bevilacqua, A., D’Antiga, M., De Ferrari, M., Pergola, V., Campello, E., Trentin, L., & Visentin, A. (2026). Right atrial thrombus in treatment-naive patient with an early-stage classical Hodgkin lymphoma: a case report and review of the literature. Frontiers in Hematology, 5, Article 1874214. https://doi.org/10.3389/frhem.2026.1874214

Image Credits: AI Generated

DOI: 10.3389/frhem.2026.1874214

Keywords: Hodgkin lymphoma, right atrial thrombus, cancer-associated thrombosis, cardiac MRI, PET-CT, anticoagulation, apixaban, PICC line, venous thromboembolism, echocardiography, hematology, case report

The article, published in Frontiers in Nuclear Medicine by Chuangyan Zhai of the Third Affiliated Hospital of Southern Medical University in Guangzhou and the Shanghai Key Laboratory of Molecular Imaging, proposes a conceptual administrative blueprint called the Management-Driven Integration Loop. Its central claim is provocative for a field dominated by physicists and physicians: the biggest barrier to molecular imaging is not technical but managerial. Molecular imaging often represents the largest capital expenditure in an institution, yet its findings are frequently treated as supplementary data rather than central drivers of treatment planning. Opportunities to guide personalized therapy, avoid unnecessary procedures, and optimize resource use are systematically overlooked.

Zhai is careful to note that this isolation rarely reflects the skills or dedication of nuclear medicine specialists. Instead, it reflects functional silos, inconsistent interdepartmental communication, and incentive structures that fail to reward collaborative clinical impact. Since informal collaboration alone has proven insufficient, the framework assigns administrators the crucial role of dismantling these systemic barriers through clear policies, workflow integration, and performance accountability. Drawing a parallel to pathology, which long fought for recognition as the definitive diagnostic foundation of medicine, the article argues that nuclear medicine must similarly be repositioned as a navigational hub for precision medicine at the molecular level.

The first pillar of the framework, strategic resource allocation, tackles the physical roots of isolation. Nuclear medicine departments are often marginalized by strict radiation shielding requirements, frequently relegated to basements or remote corridors where spontaneous consultation with clinicians becomes nearly impossible. To counter this, the article proposes satellite workstations embedded within core clinical hubs such as oncology wards, cardiology centers, and neurology units. These nodes would function as interdisciplinary spaces where nuclear medicine specialists participate directly in clinical rounds, moving the field toward an imaging-to-bedside model that reduces consultation delays and ensures molecular insights inform treatment at an earlier stage.

Physical proximity alone, however, may not bridge interdisciplinary gaps. The framework therefore introduces a formal Clinical-NM Liaison role, distinct from nuclear medicine physicians focused on volume-based reporting. The liaison would serve as a central clinical coordinator, analogous to specialized coordinators in oncology multidisciplinary teams, synthesizing molecular data with genomic and pathological findings to provide a cohesive biological map for the treating physician. The liaison would proactively review complex cases and suggest adjustments to scanning parameters, such as tracer selection, imaging timing, or delayed scans, so that results are directly actionable for surgeons or oncologists. Candidates could be drawn from senior physicians undergoing targeted cross-training, supported by dedicated time allocations and direct integration with hospital information and imaging systems to mitigate burnout.

Technological support completes the resource allocation pillar. Cloud-based Internet of Things monitoring platforms could provide real-time visibility into scanner usage, patient flow, and appointment backlogs across multiple hospital sites. Administrators could then implement dynamic resource leveling that prioritizes cases by clinical value rather than chronological booking. When a primary cancer center’s scanner is overbooked, routine follow-up scans could be redirected to underutilized satellite scanners, while urgent, high-complexity cases are scheduled on the most advanced, high-resolution equipment. This approach is designed to improve patient access, reduce waiting times, prevent equipment idling, and deliver a measurable operational return on investment.

The second pillar, process re-engineering, institutionalizes interdisciplinary collaboration through protocol-based clinical pathways embedded in electronic health records. These pathways would identify key clinical inflection points, such as initial staging for high-risk prostate cancer or therapy response assessment in lymphoma, where PET/CT evaluations using PSMA or FDG tracers are mandated by hospital-wide standard operating procedures. Structured multidisciplinary team integration would then ensure nuclear medicine physicians provide integrative insights that synthesize imaging with therapeutic possibilities rather than merely reporting findings. An MDT feedback and decision-tracking loop, integrated into the hospital information system, would systematically capture measurable outcomes such as diagnostic upstaging, downstaging, or fundamental shifts in treatment plans, alongside operational metrics like average length of stay and total cost of care. Data on clinical return on investment would feed back into the resource allocation phase, allowing administrators to redeploy satellite workstations or liaison personnel to the highest-impact clinical areas and thereby complete the integration loop.

The third pillar, performance leverage, confronts a structural misalignment at the heart of hospital economics. Traditional fee-for-service compensation deters interdisciplinary collaboration because time spent in multidisciplinary meetings yields no direct financial return for the nuclear medicine department. The framework proposes a multidimensional Total Performance Index in which quantitative output such as scan counts or relative value units is weighted alongside Decision Contribution, capturing validated impacts on clinical staging or treatment plan changes, and Synergy and Research, capturing joint publications and clinical grants. Administrators could strategically adjust the weighting coefficients during the integration phase, for example allocating 0.4 to quantity, 0.4 to decision, and 0.2 to synergy, signaling that active clinical consultation and collaborative innovation matter as much as technical imaging volume. Decision contributions would be documented within the hospital information system and verified by an interdisciplinary audit committee to safeguard objectivity. Administratively protected seed grants, accessible only through joint applications from nuclear medicine and at least one other clinical department, would further break budget silos and foster a culture of mutual dependency.

The fourth pillar, brand building, envisions repositioning the department as a multidisciplinary Precision Diagnosis and Therapy Center, formally recognizing nuclear medicine as the hospital’s navigational hub for oncology, cardiology, and neurology. Leveraging IoT and cloud-based platforms, administrators could explore a one-stop diagnostic-to-treatment workflow in which patients move from PET/CT scanning to multidisciplinary consultation within a single day. A key proposed metric is Time-to-Decision, measuring the interval from initial clinical suspicion to an MDT-approved treatment plan. Benchmarking against international standards from the Society of Nuclear Medicine and Molecular Imaging and the European Association of Nuclear Medicine, participation in multicenter trials, and hosting regional management forums could generate an academic halo effect that elevates the reputation of the hospital and its associated departments.

The article acknowledges substantial implementation challenges. Large tertiary centers are best positioned to pilot the full suite of recommendations, while smaller hospitals may need phased adoption prioritizing virtual MDT participation and basic protocol alignment over structural overhauls. Value-based incentives may encounter regulatory hurdles in regions where reimbursement remains strictly tied to fee-for-service models, the liaison role may face certification and billing challenges, and technical fragmentation among hospital information systems from different vendors often blocks interoperability. Perhaps the most significant barrier is the deeply ingrained siloed culture of medical specialties, which requires top-tier leadership commitment to overcome. While the framework remains conceptual rather than derived from prospective pilot data, its illustrative example in high-risk prostate cancer management, where coordinated PSMA PET/CT evaluation before MDT discussion could reduce unnecessary procedures and shorten time-to-decision, offers a practical vision of how administrative coordination, specialized personnel, and molecular imaging could function synergistically. The article closes with a call to action for hospital leadership to drive institutional excellence and improve patient outcomes through proactive, systematic governance.

Subject of Research: Health

Article Title: Driving clinical excellence through a management driven framework for integrating nuclear medicine into hospital ecosystems

Article References: Zhai, C. (2026). Driving clinical excellence through a management driven framework for integrating nuclear medicine into hospital ecosystems. Frontiers in Nuclear Medicine, 6, Article 1837305. https://doi.org/10.3389/fnume.2026.1837305

Image Credits: AI Generated

DOI: 10.3389/fnume.2026.1837305

Keywords: nuclear medicine, hospital management, molecular imaging, PET/CT, interdisciplinary collaboration, health policy, Driving, clinical, excellence, management, driven, framework