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A. Salmasi

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Open access Aug 2026

Detection and Localization of Unfavorable-histology Prostate Cancer Using MRI and Whole-mount Histopathology.

BACKGROUND AND OBJECTIVE Detecting localized prostate cancer (PC) with metastatic potential-defined as unfavorable-histology PC (uhPC), comprising Grade Group (GG) ≥3 disease or GG 2 disease with cribriform/intraductal features-is critical for guiding appropriate intervention. We evaluated the utility of the Prostate Imaging Reporting and Data System (PI-RADS) and the automated Restriction Spectrum Imaging restriction score (RSIrs; a biophysics-based quantitative MRI biomarker) for uhPC detection and localization. METHODS We evaluated patient-level detection of uhPC in a multicenter cohort with biopsy as the reference standard and lesion-level localization in a separate cohort with whole-mount histopathology (WMHP) from radical prostatectomy. The area under the receiver operating characteristic curve (AUC) was calculated to compare patient-level detection of uhPC using PI-RADS and RSIrs. PI-RADS and RSIrs were used to evaluate sensitivity for the most aggressive tumor within the prostate (index tumor) and for all uhPC tumors on WMHP. KEY FINDINGS AND LIMITATIONS The AUC for patient-level detection of uhPC did not differ significantly between PI-RADS and RSIrs in 1022 patients from five centers (p = 0.13). At the lesion level (n = 103 patients), sensitivity for the index tumor was 87% (95% confidence intervals [CI], 79-94) for PI-RADS, 85% (95% CI, 78-93) for RSIrs, and 93% (95% CI, 86-98) for the two combined. For all uhPC tumors, sensitivity was 81% (95% CI, 73-90) for PI-RADS, 86% (95% CI, 78-93) for RSIrs, and 90% (95% CI, 82-97) for the two combined. A limitation of the lesion-level analyses was that only patients who opted for surgery could be included. CONCLUSIONS AND CLINICAL IMPLICATIONS MRI showed high sensitivity for detecting uhPC, reinforcing its value for identifying biologically aggressive disease. Both PI-RADS and automated RSIrs may be useful for targeted biopsy and tumor-focused treatment, such as focal radiation dose escalation to aggressive intraprostatic lesions.

Mariluz Rojo Domingo, Anna M Dornisch, C. Conlin et al. · 0 citations
Open access Aug 2026

Spatial transcriptomics reveals site-specific cellular and metabolic heterogeneity in bladder carcinoma in situ

Bladder carcinoma in situ (CIS) is a multifocal, non–muscle-invasive disease with a high risk of progression to muscle-invasive cancer. Current management strategies are often guided by genomic profiling of single tumor samples, which incompletely capture tumor heterogeneity and may contribute to treatment failure. In particular, the multifocal nature of CIS raises uncertainty regarding the uniformity of genomic, immunologic, and microenvironmental features across anatomically distinct sites within the same patient. To address this, we performed spatial transcriptomic profiling of CIS-containing tissue from four anatomically distinct sites within a single individual. Unsupervised clustering with marker-based annotation, integrated with metabolic inference, identified epithelial tumor populations alongside stromal, immune, and smooth muscle compartments. While key cellular states were conserved, their spatial organization and relative abundance varied by site. Metabolic analysis further revealed region-specific microenvironments shaped by local cellular architecture. These findings indicate that both cellular composition and metabolic activity are spatially structured. Collectively, these results demonstrate that CIS exhibits significant intra-patient heterogeneity not captured by single-site profiling. These findings require validation in larger cohorts but support multi-region sampling could help improve risk stratification, biomarker development, and prediction of response to intravesical therapies, with potential implications for more personalized treatment strategies.

Tyler D. Myers, A. Salmasi, M. Meagher et al. · 0 citations

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