Carcinome intracanalaire de la prostate

Sci Rep. 2025 Jan 11;15(1):1745. doi: 10.1038/s41598-025-85857-8.ABSTRACTRecently, as the number of cancer patients has increased, much research is being conducted for efficient treatment, including the use of artificial intelligence in genitourinary pathology. Recent research has focused largely on the classification of renal cell carcinoma subtypes. Nonetheless, the broader categorization of renal tissue into non-neoplastic normal tissue, benign tumor and malignant tumor remains understudied. This gap in research can primarily be attributed to the limited availability of extensive datasets including benign tumor and normal tissue in addition to specific type of renal cell carcinoma, which hampers the ability to conduct comprehensive studies in these broader categories. This research introduces a model aimed at classifying renal tissue into three primary categories: normal (non-neoplastic), benign tumor, and malignant tumor. Utilizing digital pathology while slide images (WSIs) from nephrectomy specimens of 2,535 patients from multiple institutions, the model provides a foundational approach for distinguishing these key tissue types. The study utilized a dataset of 12,223 WSIs comprising 1,300 WSIs of normal tissue, 700 WSIs of benign tumors, and 10,223 WSIs of malignant tumors. Employing the ResNet-18 architecture and a Multiple Instance Learning approach, the model demonstrated high accuracy, with F1-scores of 0.934 (CI: 0.933-0.934) for normal tissue, 0.684 (CI: 0.682-0.687) for benign tumors, and 0.878 (CI: 0.877-0.879) for malignant tumors. The overall performance was also notable, achieving a weighted average F1-score of 0.879 (CI: 0.879-0.880) and a weighted average area under the receiver operating characteristic curve of 0.969 (CI: 0.969-0.969). This model significantly aids in the swift and accurate diagnosis of renal tissue, encompassing non-neoplastic normal tissue, benign tumor, and malignant tumor.PMID:39799164 | DOI:10.1038/s41598-025-85857-8

Cancers (Basel). 2025 Jan 3;17(1):134. doi: 10.3390/cancers17010134.ABSTRACTBACKGROUND/OBJECTIVE: The COVID-19 pandemic significantly disrupted healthcare systems worldwide including cancer diagnostics. This study aimed to assess the impact of the pandemic on histopathological cancer diagnostics in Lower Silesia, Poland, specifically focusing on prostate, breast, and colorectal cancer cases from 2018 to 2022. The objective was to evaluate diagnostic volumes and trends before, during, and after the pandemic and to understand the effect of healthcare disruptions on cancer detection.METHODS: Histopathological and cytological data were collected from multiple laboratories across Lower Silesia. Samples were categorized into three periods: pre-pandemic (January 2018-February 2020), pandemic (March 2020-May 2022), and post-pandemic (June-December 2022). Statistical analyses included comparisons of diagnostic volumes and positive diagnoses across these periods.RESULTS: A significant reduction in the number of histopathological examinations occurred during the pandemic, particularly during its early phase. This decline was accompanied by a higher frequency of positive cancer diagnoses, suggesting the prioritization of high-risk cases. Post-pandemic, diagnostic activity showed partial recovery, though it remained below the pre-pandemic levels, with notable differences across cancer types.CONCLUSIONS: The COVID-19 pandemic significantly disrupted cancer diagnostics in Lower Silesia, delaying detection and highlighting healthcare system vulnerabilities. These findings underscore the importance of resilient healthcare systems that can ensure the continuity of essential diagnostic services and address inequalities in access to care during crises.PMID:39796761 | DOI:10.3390/cancers17010134

Quant Imaging Med Surg. 2024 Dec 5;14(12):9444-9458. doi: 10.21037/qims-24-694. Epub 2024 Nov 29.ABSTRACTBACKGROUND: Renal cell carcinoma (RCC), the most common malignant renal tumor, is primarily treated by surgical resection, including radical nephrectomy (RN) and partial nephrectomy (PN). At present, the choice of surgery mainly depends on the comprehensive evaluation of patients' clinical data, including histological classification, such as clear cell renal cell carcinoma (ccRCC) and non-clear cell renal cell carcinoma (nccRCC), and RENAL (radius, exophytic/endophytic, nearness, anterior/posterior, and location) score. Compared with biopsy and contrast-enhanced computed tomography (CECT), contrast-enhanced ultrasound (CEUS) is safer and less invasive. The purpose of this study was to assess the value of CEUS in the preoperative evaluation of histological classification and RENAL score of RCC.METHODS: This retrospective study was conducted on a consecutive series of patients with renal tumors who underwent CEUS examination within 1 week prior to treatment at Lanzhou University Second Hospital between March 2021 and November 2023. The conventional ultrasound and CEUS features of RCCs were recorded and used to evaluate the RENAL score. Binary logistic regression was applied to analyze the independent risk factors of ccRCC. Diagnostic efficacy in evaluating ccRCC and nccRCC was compared between CEUS and CECT with the McNemar test.RESULTS: Among 246 patients, 248 RCCs were enrolled and were categorized into two groups: ccRCC (n=196) and nccRCC (n=52), with surgical pathology as the reference standard. The likelihood of hyperenhancement (P<0.001), heterogeneous enhancement (P<0.001), internal nonenhanced region ≤50% (P=0.001), and fast wash-in (P<0.001) in the ccRCC group was significantly higher than that in the nccRCC group, and these were independent risk factors of ccRCC. Moreover, the ccRCC group, as compared to the nccRCC, had a lower region of interest area of the largest range of tumor (Areamax) (P=0.045) and the difference between the local tumor and cortex in arrive time (∆ATtumor-cortex) (P=0.012) and shorter time to peak of the local tumor (TTPtumor) (P=0.022). The performance of CEUS in differentiating between ccRCC and nccRCC was comparable to that of CECT and showed high sensitivity (99.5%). Additionally, there was a significant difference in RENAL score based on the ultrasound features between the RN and PN group (P<0.001).CONCLUSIONS: The conventional ultrasound and CEUS features may help differentiate ccRCC from nccRCC and have significant potential in scoring the complexity prior to surgery, which could provide more precise and valuable information for diagnosis and treatment. CEUS has the capacity to optimize the treatment plan in a noninvasive manner and improve the prognosis of patients and should thus be further verified in multicenter, large-cohort, prospective research.PMID:39698685 | PMC:PMC11651922 | DOI:10.21037/qims-24-694

Pathol Res Pract. 2024 Dec 12;266:155764. doi: 10.1016/j.prp.2024.155764. Online ahead of print.ABSTRACTTo predict the therapeutic response of systemic therapy, comprehensive analyses of the tumor microenvironment in papillary renal cell carcinoma (pRCC) have been conducted previously using immunohistochemistry and RNA sequencing. This study aimed to evaluate the correlation between hematoxylin and eosin-based histological immunophenotypes and gene signatures employed in several clinical trials predicting responsiveness to immune checkpoint inhibitors and tyrosine kinase inhibitors, using data from the Cancer Genome Atlas (TCGA)-KIRP cohort (n = 254). Herein, we evaluated tumor-associated immune cells (TAICs) using three methodologies previously reported in clear cell RCC: a 3-tier immunophenotype (desert, excluded, and inflamed) based on the spatial distribution of TAICs; a 4-tier immunophenotype (cold, immune-low, excluded, and hot) considering both the location and degree of TAICs; and an inflammation score (score 0, 1, and 2) focusing only on the degree of TAICs. Furthermore, we compared the predictive ability of the three immunophenotypes. The histological immunophenotype in pRCC exhibited a correlation with adverse clinicopathological factors (including higher stage, WHO/ISUP grade, and the presence of sarcomatoid/rhabdoid changes), gene signatures related to angiogenesis, Teff, myeloid cells, JAVELIN Renal 101 Immuno, and immune checkpoints, as well as a poorer prognosis. Among the three methodologies, the 4-tier immunophenotype demonstrated the strongest correlation with gene signatures. In conclusion, the 4-tier immunophenotype may yield potential predictive biomarkers for pRCC and guide treatment decisions.PMID:39689398 | DOI:10.1016/j.prp.2024.155764

Jpn J Clin Oncol. 2024 Dec 22:hyae183. doi: 10.1093/jjco/hyae183. Online ahead of print.ABSTRACTOBJECTIVE: This study aimed to assess the oncological outcomes of the subtype of urothelial carcinoma (SUC), including divergent differentiation and histologic subtype, in comparison with those of pure urothelial carcinoma (PUC) in nonmuscle-invasive bladder cancer.METHODS: We retrospectively evaluated patients who were initially treated with transurethral resection of the bladder tumor (TURBT) between March 2005 and August 2020 at a single institution. Patients with PUC and SUC were compared in terms of recurrence-free survival (RFS), progression-free survival (PFS), and overall survival (OS).RESULTS: Out of 853 enrolled patients, 783 (91.8%) and 70 (8.2%) had PUC and SUC, respectively. SUC presence was significantly associated with old age, tumor size (≥3 cm), higher pT1 rate, high grade, concomitant carcinoma in situ, and lymphovascular invasion. RFS rates after TURBT did not significantly differ between the PUC and SUC groups. With a median follow-up period of 66 months (interquartile range, 38-103 months), the rates and median time of progression to muscle invasion were 6.9% and 22.5 months in the PUC group, and 22.9% and 10.0 months in the SUC group. Moreover, the incidence of progression to metastasis was 4.6% and 15.7% in the PUC and SUC groups, respectively. The 5-year PFS rates (64.5% and 81.9%, P < .001) and 5-year OS rates (71.7% and 86.2%, P = .009) were lower in the SUC group than in the PUC group. On multivariate analysis, SUC presence independently predicted progression to muscle invasion and metastasis.CONCLUSION: At initial TURBT diagnosis, we must pay more attention to higher progression risk of SUC than that of PUC in nonmuscle-invasive bladder cancer.PMID:39709558 | DOI:10.1093/jjco/hyae183

Prostate. 2024 Dec 12:e24838. doi: 10.1002/pros.24838. Online ahead of print.ABSTRACTBACKGROUND: Multiparametric magnetic resonance imaging (mpMRI) is pivotal in prostate cancer (PCa) diagnosis, but some clinically significant (cs) PCa remain undetected. This study aims to understand the pathological and molecular basis for csPCa visibility at mpMRI.METHODS: We performed a retrospective matched-pair cohort study, including patients undergoing radical prostatectomy (RP) for csPCa (i.e., ISUP grade group ≥ 2) from 2015 to 2020, in our tertiary-referral center. We screened for inclusion in the "mpMRI-invisible" cohort all consecutive men (N = 45) having a negative preoperative mpMRI. The "mpMRI-visible" cohort was matched based on age, PSA, prostate volume, ISUP grade group. Included patients underwent radiological and pathological open-label revisions and characterization of the tumor mRNA expression profile (analyzing 780 gene transcripts, signaling pathways, and cell-type profiling). We compared the clinical-pathological variables and the gene expression profile between matched pairs. The analysis was stratified according to histological characteristics and lesion diameter.RESULTS: We included 34 patients (17 per cohort); mean age at RP and PSA were 70.5 years (standard deviation [SD] = 7.7), 7.1 ng/mL (SD = 3.3), respectively; 65% of men were ISUP 2. Overall, no significant differences in histopathological features, tumor diameter and location, mRNA profile, pathways, and cell-type scores emerged between cohorts. In the stratified analysis, an upregulation of cell adhesion and motility, of extracellular matrix remodeling and of metastatic process pathways was present in specific subgroups of mpMRI-invisible cancers.CONCLUSIONS: No PCa pathological or gene-expression hallmarks explaining mp-MRI invisibility were identified. Aggressive features can be present both in mpMRI-invisible and -visible tumors.PMID:39665170 | DOI:10.1002/pros.24838

Abdom Radiol (NY). 2024 Dec 11. doi: 10.1007/s00261-024-04734-6. Online ahead of print.NO ABSTRACTPMID:39658736 | DOI:10.1007/s00261-024-04734-6