The clinical problem the researchers set out to address is one of the most stubborn in urologic oncology. Current preoperative staging of upper tract urothelial carcinoma relies on cross-sectional imaging, such as computed tomography urography, and on ureteroscopic biopsy, in which a thin scope is threaded up the ureter to sample the tumor directly. Both tools have recognized limitations when it comes to predicting muscle invasion. Imaging can underestimate how deeply a tumor has grown, and ureteroscopic biopsies are often small, frequently non-diagnostic, and prone to undergrading the tumor’s true aggressiveness. Because the presence of muscle-invasive disease changes everything about treatment, including whether chemotherapy should be given before surgery, an accurate preoperative estimate of invasion risk carries real consequences for patients.

The team, led by Guopeng Wang together with senior and corresponding authors Dong Wang, Yu Mao and Shangqing Ren, focused on the fibrinogen-to-albumin ratio, or FAR, one of a family of so-called inflammation–nutrition indices that can be calculated from standard blood tests. The biological rationale is straightforward. Fibrinogen, the clotting protein, rises in response to systemic inflammation, and chronic inflammation is closely intertwined with tumor progression, invasion, and metastasis. Albumin, the most abundant blood protein, falls when the body is under inflammatory or nutritional stress. Dividing one by the other yields a single number that integrates both signals, rising when inflammation is high and nutritional reserve is low, a combination that in many cancers tracks with more aggressive biology.

To test whether FAR actually carries staging information, the researchers retrospectively analyzed 127 patients with upper tract urothelial carcinoma who underwent robot-assisted radical nephroureterectomy between 2018 and 2025. All patients had complete preoperative blood counts and biochemistry, and every tumor was staged definitively by pathologic examination after surgery. The disease burden in this cohort was substantial: 76.4 percent of patients turned out to have muscle-invasive disease, defined as pathologic stage pT2 or higher, and 40.2 percent had locally advanced tumors invading beyond the organ wall, stages pT3 to pT4. The researchers compared FAR against four other widely used indices computed from blood counts: the neutrophil-to-lymphocyte ratio, the platelet-to-lymphocyte ratio, the lymphocyte-to-monocyte ratio, and the systemic immune-inflammation index.

The head-to-head comparison produced a nuanced result. FAR showed the numerically highest discrimination among the five indices, with an area under the receiver operating characteristic curve of 0.631 for predicting muscle-invasive disease and 0.611 for predicting locally advanced disease. Those values indicate modest predictive power, better than a coin flip but far from definitive. More importantly, the authors were careful to note that FAR was not statistically superior to any of the other four indices. In other words, the apparent edge could plausibly reflect chance in a cohort of this size, and the honest conclusion is that FAR performs at least as well as its competitors rather than clearly better than them.

Where the analysis became more interesting was in the multivariable modeling. After adjusting for other clinical factors, FAR remained an independent predictor of both endpoints. Each 0.01 increase in the ratio was associated with an adjusted odds ratio of 1.15 for muscle-invasive disease, with a 95 percent confidence interval of 1.00 to 1.32, and an adjusted odds ratio of 1.13 for locally advanced disease, with a confidence interval of 1.02 to 1.26. The researchers then built a combined nomogram, a graphical scoring tool that clinicians can use at the bedside, incorporating FAR together with four routinely available variables: patient sex, tumor location, estimated glomerular filtration rate, and diabetes status. This combined model raised the area under the curve from 0.699 to 0.745 for muscle invasion and from 0.697 to 0.728 for locally advanced disease.

Notably, the authors resisted the temptation to oversell that improvement. The gains in discrimination did not reach statistical significance, with DeLong test P values of 0.154 and 0.287 for the two endpoints. However, several complementary performance measures moved in a supportive direction. Reclassification metrics, the net reclassification improvement and integrated discrimination improvement, suggested the combined model sorted patients into risk categories more accurately. Calibration, the agreement between predicted and observed probabilities, was favorable, and decision-curve analysis, which estimates the net clinical benefit of acting on a model’s predictions across a range of risk thresholds, also favored the combined tool. The authors explicitly characterized this added contribution of FAR as exploratory and preliminary, a level of caution that is refreshingly rare in biomarker research.

The study also employed a validation strategy more rigorous than most single-center biomarker papers attempt. Rather than relying on a random split, the team performed internal temporal validation, developing the model on patients treated from 2018 to 2022, a group of 83 individuals, and testing it on those treated from 2023 to 2025, a group of 44. This design simulates how a model behaves on future patients, who may differ in case mix from earlier cohorts. The combined model held up reasonably well, achieving an area under the curve of 0.703 for muscle-invasive disease and 0.741 for locally advanced disease in the temporal validation set. The confidence intervals, however, were wide, spanning roughly 0.53 to 0.85 and 0.59 to 0.87 respectively, a reminder that 44 validation patients cannot pin down performance precisely. The team additionally applied bootstrap optimism correction and case-mix re-weighting, and used a Firth penalized-likelihood sensitivity analysis to guard against instability from the limited number of predictor variables relative to events.

Perhaps the most scientifically valuable part of the paper is what the authors admit the study cannot show. Their reference model did not include biopsy grade, hydronephrosis, or radiological evidence of invasion, the very features that make up contemporary upper tract urothelial carcinoma risk-assessment tools. Because those established predictors were absent from the comparison, the data cannot establish whether FAR adds information beyond what urologists already use. The study also did not specifically evaluate patients in whom ureteroscopic biopsy failed or returned non-diagnostic results, the population that would arguably benefit most from an alternative risk signal. The authors therefore position the nomogram not as a replacement for biopsy and imaging but as a complementary, rule-out-oriented adjunct, one input among several in preoperative multidisciplinary assessment, potentially useful for flagging patients at low risk of muscle invasion.

The practical appeal of the approach is undeniable. FAR requires nothing beyond a preoperative blood sample that virtually every surgical patient already provides, no additional cost, no specialized equipment, and no new testing. If future work confirms its value, it could serve as an inexpensive early flag that prompts more intensive imaging review, a repeat biopsy attempt, or consideration of neoadjuvant chemotherapy in borderline cases. But the path from a single-center retrospective cohort of 127 patients to routine clinical use is long, and the authors are unambiguous that multicenter external validation is required before any clinical application. For now, the study stands as a careful, methodologically transparent demonstration that the inflammatory fingerprint visible in routine blood work carries genuine, if modest, information about how dangerous a kidney and ureter tumor may be, and as a model of how biomarker research should be reported, with its limitations stated as plainly as its promise.

Subject of Research: Preoperative prediction of muscle-invasive and locally advanced upper tract urothelial carcinoma using the fibrinogen-to-albumin ratio

Article Title: Preoperative fibrinogen-to-albumin ratio and prediction of muscle-invasive and locally advanced upper tract urothelial carcinoma: development and internal temporal validation of a nomogram

Article References: Wang, G., Dong, X., Zhang, X., Gu, C., Hu, T., Yang, F., Wang, D., Mao, Y., & Ren, S. (2026). Preoperative fibrinogen-to-albumin ratio and prediction of muscle-invasive and locally advanced upper tract urothelial carcinoma: development and internal temporal validation of a nomogram. BMC Cancer. https://doi.org/10.1186/s12885-026-17104-w

Image Credits: AI Generated

DOI: 10.1186/s12885-026-17104-w

Keywords: upper tract urothelial carcinoma, fibrinogen-to-albumin ratio, nomogram, muscle-invasive disease, locally advanced disease, preoperative staging, inflammation-nutrition indices, radical nephroureterectomy, biomarkers, decision-curve analysis, internal temporal validation, robot-assisted surgery

Hepatocellular carcinoma, the most common primary liver cancer, is a disease of stark contrasts. It is highly heterogeneous at the molecular level, yet for decades clinicians have had to rely on relatively blunt instruments to diagnose and characterize it. Contrast-enhanced computed tomography and contrast-enhanced magnetic resonance imaging remain the workhorses of detection, supported by standardized frameworks such as the LI-RADS criteria, which score liver lesions on the basis of how they take up and wash out contrast agents. These tools are effective, but they describe anatomy and blood flow rather than the underlying biology of the tumor. For a cancer whose behavior, prognosis, and response to therapy depend heavily on the richness and molecular character of its vasculature, that is a significant blind spot. The Bologna team set out to test whether a molecular probe could fill it.

The probe in question, [68Ga]Ga-PSMA-11, binds to prostate-specific membrane antigen, a cell surface enzyme whose name betrays its origins in prostate cancer research but whose biology is far broader. In hepatocellular carcinoma, PSMA is not typically produced by the tumor cells themselves. Instead, it appears on the endothelial cells lining the tumor-associated neovasculature, the chaotic network of new blood vessels that cancers recruit to supply themselves with oxygen and nutrients. This neoangiogenic expression is precisely what makes PSMA an attractive imaging target in the liver: a radiolabeled ligand injected into the bloodstream should accumulate in the vessels of aggressive tumors, effectively painting a portrait of the tumor’s blood supply on a PET scan. Prior retrospective studies and meta-analyses had suggested PSMA PET could detect hepatocellular carcinoma, but the field lacked prospective data directly correlating scan intensity with tissue-level PSMA expression.

The Bologna study was designed to close that gap. The researchers enrolled patients with suspected hepatocellular carcinoma who were scheduled for curative-intent treatment, either surgical liver resection or liver transplantation. Thirty-nine patients were found eligible, of whom thirty-one ultimately underwent surgery. Every participant received both contrast-enhanced MRI and [68Ga]Ga-PSMA-11 PET/CT within a three-month window, ensuring that the two imaging modalities captured the disease at roughly the same point in its natural history. After surgery, the resected specimens underwent full histopathological analysis, including immunohistochemical staining for PSMA, allowing the investigators to compare, lesion by lesion, what the scanner had measured against what the tissue actually expressed. The study was approved by the local ethics committee and registered on ClinicalTrials.gov, and its prospective, monocentric design lends a methodological rigor that earlier retrospective reports could not provide.

The results are striking. Twenty-seven of the thirty-one surgically treated patients, or eighty-seven percent, showed visible PSMA uptake on PET/CT, with a median maximum standardized uptake value, or SUVmax, of 12.6 and an interquartile range spanning 10.2 to 16.5. To put those numbers in perspective, an SUVmax above ten is generally considered intense uptake in nuclear medicine practice, indicating that the tracer was concentrating avidly within the tumors. On the pathology side, immunohistochemistry told a matching story: PSMA was expressed in twenty-two of twenty-four evaluable hepatocellular carcinomas, a rate of 91.6 percent. The near-concordance between imaging positivity and tissue expression is the study’s central achievement, because it demonstrates that the tracer’s biodistribution in patients is not an artifact of blood pool activity or nonspecific accumulation but a genuine readout of molecular biology.

The most consequential statistical finding concerns the vasculature. When the team correlated semi-quantitative PET parameters with the immunohistochemical metrics, they found that high PSMA uptake on PET/CT correlated significantly with strong PSMA expression in the tumor-associated vasculature, with a p-value of 0.028. In practical terms, the brighter the tumor glowed on the scan, the more densely its feeding blood vessels expressed the target protein. This is more than a technical curiosity. PSMA expression in tumor-associated neovasculature has previously been linked to poor prognosis in hepatocellular carcinoma, meaning that a noninvasive scan capable of quantifying this feature could, in principle, stratify patients by aggressiveness before a scalpel is ever lifted. It also opens a theranostic door: the same target that can be imaged with gallium-68 can, in principle, be attacked with therapeutic radionuclides such as lutetium-177, an approach already established in PSMA-expressing prostate cancer.

Not every correlation held up, and the negative results are themselves informative. The researchers found no significant relationships between PET parameters and conventional histological features such as Edmondson grade, the standard scheme for grading how differentiated or anaplastic hepatocellular carcinoma cells appear, or the presence of vascular invasion, a key prognostic marker. All of these comparisons yielded p-values above 0.05. This dissociation suggests that PSMA PET is measuring something distinct from tumor grade or invasiveness, namely the molecular character of the tumor’s blood supply, rather than simply serving as a proxy for how aggressive the cancer cells look under the microscope. For a biomarker to earn its place in clinical practice, it must add information beyond what existing tools provide, and this independence from traditional histological grading may be exactly that added value.

The diagnostic performance of the technique in this prospective cohort adds to a rapidly growing literature. Earlier work by Hirmas and colleagues showed that Ga-PSMA-11 PET/CT improves tumor detection and impacts management decisions in hepatocellular carcinoma patients, while comparative studies have pitted PSMA PET against fluorodeoxyglucose PET, the workhorse tracer of oncological imaging, with PSMA agents generally performing better in the liver. Systematic reviews and meta-analyses, including a 2024 analysis by Hannah and colleagues, have consolidated evidence that PSMA PET/CT is a credible detection tool for hepatocellular carcinoma. What the Bologna study contributes is the prospective, histopathologically anchored confirmation that the scan’s signal has a defined biological substrate, addressing the fundamental question that has hovered over the field since the first serendipitous observations of liver uptake in prostate cancer patients.

The clinical implications extend to the theranostic frontier. If PSMA PET/CT can reliably map vascular PSMA expression before treatment, clinicians could potentially select patients whose tumors are most likely to respond to PSMA-targeted radioligand therapy, monitor changes in neovascular PSMA expression during treatment, and identify patients whose tumors lack the target altogether, sparing them futile therapy. The authors conclude that PSMA PET/CT offers robust diagnostic accuracy for hepatocellular carcinoma and correlates with vascular PSMA expression, supporting its potential utility in preoperative staging and justifying further exploration of PSMA imaging as a biomarker in this disease. As a pilot study with thirty-one surgical patients from a single center, the work is a beginning rather than an endpoint, and the investigators themselves frame it as such. Larger multicenter trials will be needed to confirm the correlations, establish standardized uptake thresholds, and determine whether vascular PSMA imaging can genuinely predict prognosis or guide therapy selection.

Nevertheless, the trajectory is unmistakable. A molecule discovered in the prostate gland, exploited for a decade to image prostate cancer with unprecedented precision, is now being validated as a window into the angiogenic biology of liver cancer, one of the leading causes of cancer death worldwide. The Bologna team’s prospective correlation of scanner signal with microscope truth represents the kind of translational bridge that molecular imaging requires before it can change guidelines, and it arrives at a moment when the hepatocellular carcinoma community is actively searching for biomarkers beyond conventional imaging. If subsequent studies replicate these findings, the humble PSMA ligand may soon be doing double duty in oncology departments: first as a diagnostic spotlight on liver tumors and their blood supply, and ultimately as the targeting beacon for radioactive payloads aimed at the very vessels that keep those tumors alive.

Subject of Research: Correlation of 68Ga-PSMA-11 PET/CT biodistribution with immunohistochemical PSMA expression in hepatocellular carcinoma

Article Title: Correlation of 68Ga-PSMA-11 PET/CT biodistribution with PSMA expression by immunohistochemistry in patients with HCC: A pilot prospective monocentric study

Article References: Vetrone, L., Prosperi, E., Prosperi, E., Vasuri, F., Degiovanni, A., Allegri, V., Castellucci, P., Zanoni, L., Nanni, C., Renzulli, M., Lucidi, V., Cattabriga, A., Malizia, C., Ravaioli, M., Cescon, M., Fanti, S., & Farolfi, A. (2026). Correlation of 68Ga-PSMA-11 PET/CT biodistribution with PSMA expression by immunohistochemistry in patients with HCC: A pilot prospective monocentric study. European Journal of Nuclear Medicine and Molecular Imaging. https://doi.org/10.1007/s00259-026-08110-y

Image Credits: AI Generated

DOI: 10.1007/s00259-026-08110-y

Keywords: PSMA PET/CT, hepatocellular carcinoma, 68Ga-PSMA-11, molecular imaging, tumor neovasculature, immunohistochemistry, theranostics, liver cancer, SUVmax, preoperative staging, angiogenesis, nuclear medicine