Description
Carcinome intracanalaire de la prostate
- Atypical Intraductal Proliferation (AIP) of the Prostate: Findings in Repeat Biopsy or Radical Prostatectomy in Patients who Met Pathologic Criteria for Active Surveillanceon 20 juin 2025
Hum Pathol. 2025 Jun 14:105854. doi: 10.1016/j.humpath.2025.105854. Online ahead of print.ABSTRACTThe clinical significance of 'atypical intraductal proliferation' (AIP) is uncertain when found in prostate needle biopsy without intraductal carcinoma (IDC-P) or intermediate/high-grade prostate carcinoma (PCa). A retrospective review identified 168 patients diagnosed with AIP. Twenty-five (15%) were AIP alone, the rest with PCa. Follow-up biopsy or RP within 12 months was collected on patients with AIP-only, AIP and grade-group (GG)1, and AIP and GG2 PCa [<20% Gleason pattern 4 (GP4) without cribriform glands] who met pathologic criteria for active surveillance (AS). From 110 patients who met pathologic AS criteria, 66 did not have follow-up tissue. The findings among 28 patients with repeat biopsy were as follows: 14 (50%) were reclassified as a higher GG, including 3/6 (50%) from AIP-only [1 to GG1 and 2 to GG2 (60% and 20% GP4)], 8/16 from AIP/GG1 [50%, all to GG2 (1 with 30%, all others with <20% GP4)], 3/6 (50%) from AIP/GG2 (<20% GP4) [1 to GG3, and 2 to AIP/GG2 but with ≥20% GP4]. Five (18%) patients no longer met pathologic criteria for AS. Among patients with RP, 4 (33%) showed IDC-P. Quantitative and morphologic evaluation showed that higher number of cores, foci, and lumina in AIP with cribriform glands were more frequent in patients who were reclassified into higher grade-groups. In conclusion, AIP should be considered a potential marker for aggressive disease, warranting further evaluation. Although similar to IDC-P, it should remain a separate entity, as repeat biopsy does not show higher-than-expected AS exit rate.PMID:40523446 | DOI:10.1016/j.humpath.2025.105854
- Intraductal carcinoma of the prostate: A comprehensive literature review focused on grading challenges and controversieson 17 juin 2025
Histol Histopathol. 2025 May 16:18939. doi: 10.14670/HH-18-939. Online ahead of print.ABSTRACTIntraductal carcinoma of the prostate (IDC-P) is characterized by neoplastic cell proliferation within pre-existing ducts or acini, exhibiting architectural and cytological atypia exceeding that of high-grade prostatic intraepithelial neoplasia. Its presence in needle biopsies and prostatectomies is associated with adverse clinical and pathological features, including large tumor volume, high grade, advanced stage, early biochemical recurrence, and intrinsic resistance to systemic therapy. Although rare, IDC-P can occasionally occur without concurrent invasive cancer or be associated with low-grade prostate cancer. Molecularly, IDC-P resembles its associated invasive carcinoma, sharing alterations typical of high-grade aggressive tumors. These findings support the hypothesis that IDC-P arises from the retrograde spread of invasive carcinoma, with ducts providing a protective niche against the tumor microenvironment. In contrast, isolated IDC-P and IDC-P associated with low-grade invasive carcinoma may represent precursor lesions. IDC-P must be distinguished from other intraductal lesions, both benign and malignant, particularly in needle biopsies, as its detection impacts therapeutic decisions. While grading does not apply to isolated IDC-P, there is an ongoing debate regarding IDC-P with synchronous invasive cancer. The International Society of Urological Pathology (2019) recommends incorporating IDC-P into Gleason score calculations, whereas the Genitourinary Pathology Society advises against grading it at all. Both approaches have merit, but further validation studies focusing on cases where IDC-P inclusion alters the final grade, though uncommon, are warranted.PMID:40452312 | DOI:10.14670/HH-18-939
- Atypical intraductal proliferation (AIP) of the prostate: Findings in repeat biopsy or radical prostatectomy in patients who met pathologic criteria for active surveillanceon 17 juin 2025
Hum Pathol. 2025 Jun 13:105841. doi: 10.1016/j.humpath.2025.105841. Online ahead of print.ABSTRACTThe clinical significance of 'atypical intraductal proliferation' (AIP) is uncertain when found in prostate needle biopsy without intraductal carcinoma (IDC-P) or intermediate/high-grade prostate carcinoma (PCa). A retrospective review identified 168 patients diagnosed with AIP. Twenty-five (15 %) were AIP alone, the rest with PCa. Follow-up biopsy or RP within 12 months was collected on patients with AIP-only, AIP and grade-group (GG)1, and AIP and GG2 PCa [<20 % Gleason pattern 4 (GP4) without cribriform glands] who met pathologic criteria for active surveillance (AS). From 110 patients who met pathologic AS criteria, 66 did not have follow-up tissue. The findings among 28 patients with repeat biopsy were as follows: 14 (50 %) were reclassified as a higher GG, including 3/6 (50 %) from AIP-only [1 to GG1 and 2 to GG2 (60 % and 20 % GP4)], 8/16 from AIP/GG1 [50 %, all to GG2 (1 with 30 %, all others with <20 % GP4)], 3/6 (50 %) from AIP/GG2 (<20 % GP4) [1 to GG3, and 2 to AIP/GG2 but with ≥20 % GP4]. Five (18 %) patients no longer met pathologic criteria for AS. Among patients with RP, 4 (33 %) showed IDC-P. Quantitative and morphologic evaluation showed that higher number of cores, foci, and lumina in AIP with cribriform glands were more frequent in patients who were reclassified into higher grade-groups. In conclusion, AIP should be considered a potential marker for aggressive disease, warranting further evaluation. Although similar to IDC-P, it should remain a separate entity, as repeat biopsy does not show higher-than-expected AS exit rate.PMID:40516578 | DOI:10.1016/j.humpath.2025.105841
Critères diagnostiques histologiques
- Artificial Intelligence-Based Digital Histologic Classifier for Prostate Cancer Risk Stratification: Independent Blinded Validation in Patients Treated With Radical Prostatectomyon 20 juin 2025
JCO Clin Cancer Inform. 2025 Jun;9:e2400292. doi: 10.1200/CCI-24-00292. Epub 2025 Jun 18.ABSTRACTPURPOSE: Artificial intelligence (AI) tools that identify pathologic features from digitized whole-slide images (WSIs) of prostate cancer (CaP) generate data to predict outcomes. The objective of this study was to evaluate the clinical validity of an AI-enabled prognostic test, PATHOMIQ_PRAD, using a clinical cohort from the Cleveland Clinic.METHODS: We conducted a retrospective analysis of PATHOMIQ_PRAD using CaP WSIs from patients who underwent radical prostatectomy (RP) between 2009 and 2022 and did not receive adjuvant therapy. Patients also had Decipher genomic testing available. WSIs were deidentified, anonymized, and outcomes were blinded. Patients were stratified into high-risk and low-risk categories on the basis of predetermined thresholds for PATHOMIQ_PRAD scores (0.45 for biochemical recurrence [BCR] and 0.55 for distant metastasis [DM]).RESULTS: The study included 344 patients who underwent RP with a median follow-up of 4.3 years. Both PathomIQ and Decipher scores were associated with rates of biochemical recurrence-free survival (BCRFS; PathomIQ score >0.45 v ≤0.45, P <.001; Decipher score >0.6 v ≤0.6, P = .002). There were 16 patients who had DM, and 15 were in the high-risk PathomIQ group (Mets Score >0.55). Both PathomIQ and Decipher scores were associated with rates of metastasis-free survival (PathomIQ score >0.55 v ≤0.55, P <.001; Decipher score >0.6 v ≤0.6, P = .0052). Despite the low event rates for metastasis, multivariable regression demonstrated that high PathomIQ score was significantly associated with DM (>0.55 v ≤0.55, hazard ratio, 10.10 [95% CI, 1.28 to 76.92], P = .0284).CONCLUSION: These findings independently validate PATHOMIQ_PRAD as a reliable predictor of clinical risk in the postprostatectomy setting. PATHOMIQ_PRAD therefore merits prospective evaluation as a risk stratification tool to select patients for adjuvant or early salvage interventions.PMID:40532127 | DOI:10.1200/CCI-24-00292
- Histopathology-Based Prostate Cancer Classification Using ResNet: A Comprehensive Deep Learning Analysison 17 juin 2025
J Imaging Inform Med. 2025 May 20. doi: 10.1007/s10278-025-01543-1. Online ahead of print.ABSTRACTProstate cancer is the most prevalent solid tumor in males and one of the most common causes of male mortality. It is the most common type of cancer in men, a major global public health issue, and accounts for up to 7.3% of all male cancer diagnoses worldwide. To optimize patient outcomes and ensure therapeutic success, an accurate diagnosis must be made promptly. To achieve this, we focused on using ResNet50, a convolutional neural network (CNN) architecture, to analyze prostate histological images to classify prostate cancer. ResNet50, due to its efficiency in medical image classification, was used to classify the histological images as benign or malignant. In this study, a total of 1276 prostate biopsy images were used on the ResNet50 model. We employed evaluation metrics such as accuracy, precision, recall, and F1 score. The results showed that the ResNet50 model performed excellently with an overall accuracy of 0.98, 1.00 as precision, 0.98 as recall, and 0.97 as F1 score for benign. The malignant histological image has 0.99, 0.98, and 0.97 as precision, recall, and F1 scores. It also recorded a 95% confidence interval (CI) for accuracy as (0.91, 1.00) and a performance gain of 4.26% compared to MobileNet and CNN-RNN. The result of our model was also compared with the state-of-the-art (SOTA) DL models to ensure robustness. This study has demonstrated the potential of the ResNet50 model in the classification of prostate cancer. Again, the clinical integration of the results of this study will aid decision-makers in enhancing patient outcomes.PMID:40394318 | DOI:10.1007/s10278-025-01543-1
- Prostate cancer prediction through a hybrid deep learning method applied to histopathological imageon 17 juin 2025
Expert Rev Anticancer Ther. 2025 May 24. doi: 10.1080/14737140.2025.2512040. Online ahead of print.ABSTRACTBACKGROUND: Prostate Cancer (PCa) is a severe disease that affects males globally. The Gleason grading system is a widely recognized method for diagnosing the aggressiveness of PCa using histopathological images. This system evaluates prostate tissue to determine the severity of the disease and guide treatment decisions. However, manual analysis of histopathological images requires highly skilled professionals and is time-consuming.METHODS: To address these challenges, deep learning (DL) is utilized, as it has shown promising results in medical image analysis. Although numerous DL networks have been developed for Gleason grading, many existing methods have limitations such as suboptimal accuracy and high computational complexity. The proposed network integrates MobileNet, an Attention Mechanism (AM), and a capsule network. MobileNet efficiently extracts features from images while addressing computational complexity. The AM focuses on selecting the most relevant features, enhancing the accuracy of Gleason grading. Finally, the capsule network classifies the Gleason grades from histopathological images.RESULTS: The validation of the proposed network used two datasets, PANDA and Gleason-2019. Ablation studies were conducted and evaluated in the proposed architecture. The results highlight the effectiveness of the proposed network.CONCLUSIONS: The proposed network outperformed existing approaches, achieving an accuracy of 98.08% on the PANDA dataset and 97.07% on the Gleason-2019 dataset.PMID:40411485 | DOI:10.1080/14737140.2025.2512040
- Correlation between MRI, biopsy and radical prostatectomy histological analysis results applied to focal therapyon 17 juin 2025
Fr J Urol. 2025 May 29:102913. doi: 10.1016/j.fjurol.2025.102913. Online ahead of print.ABSTRACTINTRODUCTION: Prostate cancer localization is essential before performing focal therapy. We analyzed the concordance between MRIs, systematic and targeted biopsies, and whole prostate gland removals with the aim of half-gland treatment.MATERIALS AND METHODS: Between 2016 and 2022, we analyzed 132 patients who benefited from positive MRIs (i.e. PI-RADS ≥ 3), biopsies (ISUP 2-3) and radical prostatectomies (RP). MRIs were performed in any imaging office, without double reading. Biopsies were taken after MRI/US fusion by prostate cancer specialist urologists. The hemi-gland of significant prostate cancer localization was collected on MRIs (PI-RADS), biopsies (ISUP) and prostatectomies. Concordance analyses and predictive values were calculated between MRIs and biopsies, MRIs and RPs, biopsies and RPs, and in the concordant MRI/biopsy and RP population. ISUP 1 was considered as negative.RESULTS: Concordance rates vary from 74.24% to 85.05%; Kappa's ratio from 0.42 to 0.65. Neither MRIs nor biopsies detect a significant prostate locus in 24% of cases. PPVs and NPVs for MRIs/biopsies and prostatectomies are 99% and 51.5%, respectively. Grading prediction is accurate in 85% of cases.DISCUSSION: The concordance rate is moderate with NPVs synonymous with the risk of undertreatment. The absence of MRI target (but with significant carcinoma after RPs) is a key part of this risk but not always corrected with systematic standard biopsies. Targeted biopsies confirm the MRI foci.CONCLUSION: Due to significant cancer in negative MRI areas, the selection method before focal therapy, i.e. half-gland treatment, may be improved and underlines the importance of systematic biopsies.PMID:40449849 | DOI:10.1016/j.fjurol.2025.102913
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