Gleason grade 4 prostate adenocarcinoma patterns: an interobserver agreement study among genitourinary pathologists

Histopathological evaluation and grading for prostate cancer: current issues and crucial aspects

A crucial aspect of prostate cancer grading, especially in low- and intermediate-risk cancer, is the accurate identification of Gleason pattern 4 glands, which includes ill-formed or fused glands. However, there is notable inconsistency among pathologists in recognizing these glands, especially when mixed with pattern 3 glands. This inconsistency has significant implications for patient management and treatment decisions. Conversely, the recognition of glomeruloid and cribriform architecture has shown higher reproducibility. Cribriform architecture, in particular, has been linked to the worst prognosis among pattern 4 subtypes. Intraductal carcinoma of the prostate (IDC-P) is also associated with high-grade cancer and poor prognosis. Accurate identification, classification, and tumor size evaluation by pathologists are vital for determining patient treatment. This review emphasizes the importance of prostate cancer grading, highlighting challenges like distinguishing between pattern 3 and pattern 4 and the prognostic implications of cribriform architecture and intraductal proliferations. It also addresses the inherent grading limitations due to interobserver variability and explores the potential of computational pathology to enhance pathologist accuracy and consistency.

Validation of prostate and breast cancer detection artificial intelligence algorithms for accurate histopathological diagnosis and grading: a retrospective study with a Japanese cohort

Prostate and breast cancer incidence rates have been on the rise in Japan, emphasising the need for precise histopathological diagnosis to determine patient prognosis and guide treatment decisions. However, existing diagnostic methods face numerous challenges and are susceptible to inconsistencies between observers. To tackle these issues, artificial intelligence (AI) algorithms have been developed to aid in the diagnosis of prostate and breast cancer. This study focuses on validating the performance of two such algorithms, Galen Prostate and Galen Breast, in a Japanese cohort, with a particular focus on the grading accuracy and the ability to differentiate between invasive and non-invasive tumours. The research entailed a retrospective examination of 100 consecutive prostate and 100 consecutive breast biopsy cases obtained from a Japanese institution. Our findings demonstrated that the AI algorithms showed accurate cancer detection, with AUCs of 0.969 and 0.997 for the Galen Prostate and Galen Breast, respectively. The Galen Prostate was able to detect a higher Gleason score in four adenocarcinoma cases and detect a previously unreported cancer. The two algorithms successfully identified relevant pathological features, such as perineural invasions and lymphovascular invasions. Although further improvements are required to accurately differentiate rare cancer subtypes, these findings highlight the potential of these algorithms to enhance the precision and efficiency of prostate and breast cancer diagnosis in Japan. Furthermore, this validation paves the way for broader adoption of these algorithms as decision support tools within the Asian population.

Cribriform versus Intraductal: How to Determine the Difference

Over the years, our understanding of cribriform and intraductal prostate cancer (PCa) has evolved significantly, leading to substantial changes in their classification and clinical management. This review discusses the histopathological disparities between intraductal and cribriform PCa from a diagnostic perspective, aiming to aid pathologists in achieving accurate diagnoses. Furthermore, it discusses the ongoing debate surrounding the different recommendations between ISUP and GUPS, which pose challenges for practicing pathologists and complicates consensus among them. Recent studies have shown promising results in integrating these pathological features into clinical decision-making tools, improving predictions of PCa recurrence, cancer spread, and mortality. Future research efforts should focus on further unraveling the biological backgrounds of these entities and their implications for clinical management to ultimately improve PCa patient outcomes.

Ductal, intraductal, and cribriform carcinoma of the prostate: Molecular characteristics and clinical management

Prostatic acinar adenocarcinoma accounts for approximately 95% of prostate cancer (CaP) cases. The remaining 5% of histologic subtypes of CaP are known to be more aggressive and have recently garnered substantial attention. These histologic subtypes - namely, prostatic ductal adenocarcinoma (PDA), intraductal carcinoma of the prostate (IDC-P), and cribriform carcinoma of the prostate (CC-P) - typically exhibit distinct growth characteristics, genomic features, and unique oncologic outcomes. For example, PTEN mutations, which cause uncontrolled cell growth, are frequently present in IDC-P and CC-P. Germline mutations in homologous DNA recombination repair (HRR) genes (e.g., BRCA1, BRCA2, ATM, PALB2, and CHEK2) are discovered in 40% of patients with IDC-P, while only 9% of patients without ductal involvement had a germline mutation. CC-P is associated with deletions in common tumor suppressor genes, including PTEN, TP53, NKX3-1, MAP3K7, RB1, and CHD1. Evidence suggests abiraterone may be superior to docetaxel as a first-line treatment for patients with IDC-P. To address these and other critical pathological attributes, this review examines the molecular pathology, genetics, treatments, and oncologic outcomes associated with CC-P, PDA, and IDC-P with the objective of creating a comprehensive resource with a centralized repository of information on PDA, IDC-P, and CC-P.

Contemporary Diagnostic Reporting for Prostatic Adenocarcinoma: Morphologic Aspects, Molecular Correlates, and Management Perspectives

The diagnosis and reporting of prostatic adenocarcinoma have evolved from the classic framework promulgated by Dr Donald Gleason in the 1960s into a complex and nuanced system of grading and reporting that nonetheless retains the essence of his remarkable observations. The criteria for the "Gleason patterns" originally proposed have been continually refined by consensuses in the field, and Gleason scores have been stratified into a patient-friendly set of prognostically validated and widely adopted Grade Groups. One product of this successful grading approach has been the opportunity for pathologists to report diagnoses that signal carefully personalized management, placing the surgical pathologist's interpretation at the center of patient care. At one end of the continuum of disease aggressiveness, personalized diagnostic care means to sub-stratify patients with more indolent disease for active surveillance, while at the other end of the continuum, reporting histologic markers signaling aggression allows sub-stratification of clinically significant disease. Whether contemporary reporting parameters represent deeper nuances of more established ones (eg, new criteria and/or quantitation of Gleason patterns 4 and 5) or represent additional features reported alongside grade (intraductal carcinoma, cribriform patterns of carcinoma), assessment and grading have become more complex and demanding. Herein, we explore these newer reporting parameters, highlighting the state of knowledge regarding morphologic, molecular, and management aspects. Emphasis is made on the increasing value and stakes of histopathologists' interpretations and reporting into current clinical risk stratification and treatment guidelines.

Harnessing artificial intelligence for prostate cancer management

Prostate cancer (PCa) is a common malignancy in males. The pathology review of PCa is crucial for clinical decision-making, but traditional pathology review is labor intensive and subjective to some extent. Digital pathology and whole-slide imaging enable the application of artificial intelligence (AI) in pathology. This review highlights the success of AI in detecting and grading PCa, predicting patient outcomes, and identifying molecular subtypes. We propose that AI-based methods could collaborate with pathologists to reduce workload and assist clinicians in formulating treatment recommendations. We also introduce the general process and challenges in developing AI pathology models for PCa. Importantly, we summarize publicly available datasets and open-source codes to facilitate the utilization of existing data and the comparison of the performance of different models to improve future studies.

Expected impact of MRI-targeted biopsy interreader variability among uropathologists on ProScreen prostate cancer screening trial: a pre-trial validation study

PURPOSE

Prostate cancer (PCa) histology, particularly the Gleason score, is an independent prognostic predictor in PCa. Little is known about the inter-reader variability in grading of targeted prostate biopsy based on magnetic resonance imaging (MRI). The aim of this study was to assess inter-reader variability in Gleason grading of MRI-targeted biopsy among uropathologists and its potential impact on a population-based randomized PCa screening trial (ProScreen).

METHODS

From June 2014 to May 2018, 100 men with clinically suspected PCa were retrospectively selected. All men underwent prostate MRI and 86 underwent targeted prostate of the prostate. Six pathologists individually reviewed the pathology slides of the prostate biopsies. The five-tier ISUP (The International Society of Urological Pathology) grade grouping (GG) system was used. Fleiss' weighted kappa (κ) and Model-based kappa for associations were computed to estimate the combined agreement between individual pathologists.

RESULTS

GG reporting of targeted prostate was highly consistent among the trial pathologists. Inter-reader agreement for cancer (GG1-5) vs. benign was excellent (Model-based kappa 0.90, Fleiss' kappa κ = 0.90) and for clinically significant prostate cancer (csPCa) (GG2-5 vs. GG0 vs. GG1), it was good (Model-based kappa 0.70, Fleiss' kappa κ 0.67).

CONCLUSIONS

Inter-reader agreement in grading of MRI-targeted biopsy was good to excellent, while it was fair to moderate for MRI in the same cohort, as previously shown. Importantly, there was wide consensus by pathologists in assigning the contemporary GG on MRI-targeted biopsy suggesting high reproducibility of pathology reporting in the ProScreen trial.

Artificial Intelligence-Enabled Prostate Cancer Diagnosis and Prognosis: Current State and Future Implications

In this modern era of digital pathology, artificial intelligence (AI)-based diagnostics for prostate cancer has become a hot topic. Multiple retrospective studies have demonstrated the benefits of AI-based diagnostic solutions for prostate cancer that includes improved prostate cancer detection, quantification, grading, interobserver concordance, cost and time savings, and a potential to reduce pathologists' workload and enhance pathology laboratory workflow. One of the major milestones is the Food and Drug Administration approval of Paige prostate AI for a second review of prostate cancer diagnosed using core needle biopsies. However, implementation of these AI tools for routine prostate cancer diagnostics is still lacking. Some of the limiting factors include costly digital pathology workflow, lack of regulatory guidelines for deployment of AI, and lack of prospective studies demonstrating the actual benefits of AI algorithms. Apart from diagnosis, AI algorithms have the potential to uncover novel insights into understanding the biology of prostate cancer and enable better risk stratification, and prognostication. This article includes an in-depth review of the current state of AI for prostate cancer diagnosis and highlights the future prospects of AI in prostate pathology for improved patient care.

Is cribriform pattern in prostate biopsy a risk factor for metastatic disease on 68Ga-PSMA-11 PET/CT?

INTRODUCTION

Cribriform growth pattern (CP) in prostate cancer (PCa) has been associated with different unfavourable oncological outcomes. This study addresses if CP in prostate biopsies is an independent risk factor for metastatic disease on PSMA PET/CT.

METHODS

Treatment-naive patients with ISUP GG ≥ 2 staged with 68Ga-PSMA-11 PET/CT diagnosed from 2020 to 2021 were retrospectively enrolled. To test if CP in biopsies was an independent risk factor for metastatic disease on 68Ga-PSMA PET/CT, regression analyses were performed. Secondary analyses were performed in different subgroups.

RESULTS

A total of 401 patients were included. CP was reported in 252 (63%) patients. CP in biopsies was not an independent risk factor for metastatic disease on the 68Ga-PSMA PET/CT (p = 0.14). ISUP grade group (GG) 4 (p = 0.006), GG 5 (p = 0.003), higher PSA level groups per 10 ng/ml until > 50 (p-value between 0.02 and > 0.001) and clinical EPE (p > 0.001) were all independent risk factors. In the subgroups with GG 2 (n = 99), GG 3 (n = 110), intermediate-risk group (n = 129) or the high-risk group (n = 272), CP in biopsies was also not an independent risk factor for metastatic disease on 68Ga-PSMA PET/CT. If the EAU guideline recommendation for performing metastatic screening was applied as threshold for PSMA PET/CT imaging, in 9(2%) patients, metastatic disease was missed, and 18% fewer PSMA PET/CT would have been performed.

CONCLUSION

This retrospective study found that CP in biopsies was not an independent risk factor for metastatic disease on 68Ga-PSMA PET/CT.

Nondestructive 3D pathology with analysis of nuclear features for prostate cancer risk assessment

Prostate cancer treatment decisions rely heavily on subjective visual interpretation [assigning Gleason patterns or International Society of Urological Pathology (ISUP) grade groups] of limited numbers of two-dimensional (2D) histology sections. Under this paradigm, interobserver variance is high, with ISUP grades not correlating well with outcome for individual patients, and this contributes to the over- and undertreatment of patients. Recent studies have demonstrated improved prognostication of prostate cancer outcomes based on computational analyses of glands and nuclei within 2D whole slide images. Our group has also shown that the computational analysis of three-dimensional (3D) glandular features, extracted from 3D pathology datasets of whole intact biopsies, can allow for improved recurrence prediction compared to corresponding 2D features. Here we seek to expand on these prior studies by exploring the prognostic value of 3D shape-based nuclear features in prostate cancer (e.g. nuclear size, sphericity). 3D pathology datasets were generated using open-top light-sheet (OTLS) microscopy of 102 cancer-containing biopsies extracted ex vivo from the prostatectomy specimens of 46 patients. A deep learning-based workflow was developed for 3D nuclear segmentation within the glandular epithelium versus stromal regions of the biopsies. 3D shape-based nuclear features were extracted, and a nested cross-validation scheme was used to train a supervised machine classifier based on 5-year biochemical recurrence (BCR) outcomes. Nuclear features of the glandular epithelium were found to be more prognostic than stromal cell nuclear features (area under the ROC curve [AUC] = 0.72 versus 0.63). 3D shape-based nuclear features of the glandular epithelium were also more strongly associated with the risk of BCR than analogous 2D features (AUC = 0.72 versus 0.62). The results of this preliminary investigation suggest that 3D shape-based nuclear features are associated with prostate cancer aggressiveness and could be of value for the development of decision-support tools. © 2023 The Pathological Society of Great Britain and Ireland.

Reliability of whole mount radical prostatectomy histopathology as the ground truth for artificial intelligence assisted prostate imaging

The development of artificial intelligence-based imaging techniques for prostate cancer (PCa) detection and diagnosis requires a reliable ground truth, which is generally based on histopathology from radical prostatectomy specimens. This study proposes a comprehensive protocol for the annotation of prostatectomy pathology slides. To evaluate the reliability of the protocol, interobserver variability was assessed between five pathologists, who annotated ten radical prostatectomy specimens consisting of 74 whole mount pathology slides. Interobserver variability was assessed for both the localization and grading of PCa. The results indicate excellent overall agreement on the localization of PCa (Gleason pattern ≥ 3) and clinically significant PCa (Gleason pattern ≥ 4), with Dice similarity coefficients (DSC) of 0.91 and 0.88, respectively. On a per-slide level, agreement for primary and secondary Gleason pattern was almost perfect and substantial, with Fleiss Kappa of .819 (95% CI .659-.980) and .726 (95% CI .573-.878), respectively. Agreement on International Society of Urological Pathology Grade Group was evaluated for the index lesions and showed agreement in 70% of cases, with a mean DSC of 0.92 for all index lesions. These findings show that a standardized protocol for prostatectomy pathology annotation provides reliable data on PCa localization and grading, with relatively high levels of interobserver agreement. More complicated tissue characterization, such as the presence of cribriform growth and intraductal carcinoma, remains a source of interobserver variability and should be treated with care when used in ground truth datasets.

Prostate Cancer Morphologies: Cribriform Pattern and Intraductal Carcinoma Relations to Adverse Pathological and Clinical Outcomes-Systematic Review and Meta-Analysis

The present study aimed to assess the association between the cribriform pattern (CP)/intraductal carcinoma (IDC) and the adverse pathological and clinical outcomes in the radical prostatectomy (RP) cohort. A systematic search was performed according to the Preferred Reporting Items for Systematic Review and Meta-Analysis statement (PRISMA). The protocol from this review was registered on the PROSPERO platform. We searched PubMed^®, the Cochrane Library and EM-BASE^® up to the 30th of April 2022. The outcomes of interest were the extraprostatic extension (EPE), seminal vesicle invasion (SVI), lymph node metastasis (LNS met), risk of biochemical recurrence (BCR), distant metastasis (MET) and disease-specific death (DSD). As a result, we identified 16 studies with 164 296 patients. A total of 13 studies containing 3254 RP patients were eligible for the meta-analysis. The CP/IDC was associated with adverse outcomes, including EPE (pooled OR = 2.55, 95%CI 1.23-5.26), SVI (pooled OR = 4.27, 95%CI 1.90-9.64), LNs met (pooled OR = 6.47, 95%CI 3.76-11.14), BCR (pooled OR = 5.09, 95%CI 2.23-11.62) and MET/DSD (pooled OR = 9.84, 95%CI 2.75-35.20, p < 0.001). In conclusion, the CP/IDC belong to highly malignant prostate cancer patterns which have a negative impact on both the pathological and clinical outcomes. The presence of the CP/IDC should be included in the surgical planning and postoperative treatment guidance.

Interobserver reproducibility of cribriform cancer in prostate needle biopsies and validation of International Society of Urological Pathology criteria

AIMS

There is strong evidence that cribriform morphology indicates a worse prognosis of prostatic adenocarcinoma. Our aim was to investigate its interobserver reproducibility in prostate needle biopsies.

METHODS AND RESULTS

A panel of nine prostate pathology experts from five continents independently reviewed 304 digitised biopsies for cribriform cancer according to recent International Society of Urological Pathology criteria. The biopsies were collected from a series of 702 biopsies that were reviewed by one of the panellists for enrichment of high-grade cancer and potentially cribriform structures. A 2/3 consensus diagnosis of cribriform and noncribriform cancer was reached in 90% (272/304) of the biopsies with a mean kappa value of 0.56 (95% confidence interval 0.52-0.61). The prevalence of consensus cribriform cancers was estimated to 4%, 12%, 21%, and 20% of Gleason scores 7 (3 + 4), 7 (4 + 3), 8, and 9-10, respectively. More than two cribriform structures per level or a largest cribriform mass with ≥9 lumina or a diameter of ≥0.5 mm predicted a consensus diagnosis of cribriform cancer in 88% (70/80), 84% (87/103), and 90% (56/62), respectively, and noncribriform cancer in 3% (2/80), 5% (5/103), and 2% (1/62), respectively (all P < 0.01).

CONCLUSION

Cribriform prostate cancer was seen in a minority of needle biopsies with high-grade cancer. Stringent diagnostic criteria enabled the identification of cribriform patterns and the generation of a large set of consensus cases for standardisation.

An update on computational pathology tools for genitourinary pathology practice: A review paper from the Genitourinary Pathology Society (GUPS)

Machine learning has been leveraged for image analysis applications throughout a multitude of subspecialties. This position paper provides a perspective on the evolutionary trajectory of practical deep learning tools for genitourinary pathology through evaluating the most recent iterations of such algorithmic devices. Deep learning tools for genitourinary pathology demonstrate potential to enhance prognostic and predictive capacity for tumor assessment including grading, staging, and subtype identification, yet limitations in data availability, regulation, and standardization have stymied their implementation.

Assessing extra-prostatic extension for surgical guidance in prostate cancer: Comparing two PSMA-PET tracers with the standard-of-care

BACKGROUND

Incontinence and impotence occur following radical prostatectomy due to injury to nerves and sphincter muscle. Preserving nerves and muscle adjacent to prostate cancer risks positive surgical margins. Advanced imaging with MRI has improved cancer localization but limitations exist.

OBJECTIVE

To measure the accuracy for assessing extra-prostatic extension at nerve bundles for 2 PSMA-PET tracers and to compare the PET accuracy to standard-of-care predictors including MRI and biopsy results.

MATERIALS AND METHODS

We studied men with PSMA-targeted PET imaging, performed prior to prostatectomy in men largely with intermediate to high-risk prostate cancer, and retrospectively evaluated for assessment of extra-prostatic extension with whole-mount analysis as reference standard. Two different PSMA-PET tracers were included: 68Ga-PSMA-11 and 68Ga-P16-093. Blinded reviews of the PET and MRI scans were performed to assess extra-prostatic extension (EPE). Sensitivity and specificity for extra-prostatic extension were compared using McNemar's Chi2.

RESULTS

Pre-operative PSMA-PET imaging was available for 71 patients with either 68Ga-P16-093 (n = 25) or 68Ga-PSMA-11 (n = 46). There were 24 (34%) with pT3a (EPE) and 16 (23%) with pT3b (SVI). EPE Sensitivity (87% vs. 92%), Specificity (77% vs. 76%), and ROC area (0.82 vs. 0.84) were similar between P16-093 and PSMA-11, respectively (P = 0.87). MRI (available in only 45) found high specificity (83%) but low sensitivity (60%) for EPE when using a published grading system. MRI sensitivity was significantly lower than the PSMA-PET (60% vs. 90%, P = 0.02), but similar to PET when using a >5 mm capsular contact (76% vs. 90%, P = 0.38). A treatment change to "nerve sparing" was recommended in 21 of 71 (30%) patients based on PSMA-PET imaging.

CONCLUSIONS

Presurgical PSMA-PET appeared useful as a tool for surgical planning, changing treatment plans in men with ≥4+3 or multi-core 3+4 prostate cancer resulting in preservation of nerve-bundles.

Cribriform Lesions of the Prostate Gland

"Cribriform lesions of the prostate represent an important and often diagnostically challenging spectrum of prostate pathology. These lesions range from normal anatomical variation, benign proliferative lesions, premalignant, suspicious to frankly malignant and biologically aggressive entities. The concept of cribriform prostate adenocarcinoma (CrP4) and intraductal carcinoma of the prostate (IDC-P), in particular, has evolved significantly in recent years with a growing body of evidence suggesting that the presence of these morphologies is important for clinical decision-making in prostate cancer management. Therefore, accurate recognition and reporting of CrP4 and IDC-P architecture are especially important. This review discusses a contemporary diagnostic approach to cribriform lesions of the prostate with a focus on their key morphologic features, differential diagnosis, underlying molecular alterations, clinical significance, and reporting recommendations."

The 2022 World Health Organization Classification of Tumors of the Urinary System and Male Genital Organs-Part B: Prostate and Urinary Tract Tumors

The 2022 World Health Organization (WHO) classification of the urinary and male genital tumors was recently published by the International Agency for Research on Cancer. This fifth edition of the WHO "Blue Book" offers a comprehensive update on the terminology, epidemiology, pathogenesis, histopathology, diagnostic molecular pathology, and prognostic and predictive progress in genitourinary tumors. In this review, the editors of the fifth series volume on urologic and male genital neoplasms present a summary of the salient changes introduced to the classification of tumors of the prostate and the urinary tract.

WHO Classification of Tumours fifth edition: evolving issues in the classification, diagnosis, and prognostication of prostate cancer

The fifth edition of the WHO Classification of Tumours of the Urinary and Male Genital Systems encompasses several updates to the classification and diagnosis of prostatic carcinoma as well as incorporating advancements in the assessment of its prognosis, including recent grading modifications. Some of the salient aspects include: (1) recognition that prostatic intraepithelial neoplasia (PIN)-like carcinoma is not synonymous with a pattern of ductal carcinoma, but better classified as a subtype of acinar adenocarcinoma; (2) a specific section on treatment-related neuroendocrine prostatic carcinoma in view of the tight correlation between androgen deprivation therapy and the development of prostatic carcinoma with neuroendocrine morphology, and the emerging data on lineage plasticity; (3) a terminology change of basal cell carcinoma to "adenoid cystic (basal cell) cell carcinoma" given the presence of an underlying MYB::NFIB gene fusion in many cases; (4) discussion of the current issues in the grading of acinar adenocarcinoma and the prognostic significance of cribriform growth patterns; and (5) more detailed coverage of intraductal carcinoma of prostate (IDC-P) reflecting our increased knowledge of this entity, while recommending the descriptive term atypical intraductal proliferation (AIP) for lesions falling short of IDC-P but containing more atypia than typically seen in high-grade prostatic intraepithelial neoplasia (HGPIN). Lesions previously regarded as cribriform patterns of HGPIN are now included in the AIP category. This review discusses these developments, summarising the existing literature, as well as the emerging morphological and molecular data that underpins the classification and prognostication of prostatic carcinoma.

Analysis of separate training and validation radical prostatectomy cohorts identifies 0.25 mm diameter as an optimal definition for "large" cribriform prostatic adenocarcinoma

Cribriform growth pattern is well-established as an adverse pathologic feature in prostate cancer. The literature suggests "large" cribriform glands associate with aggressive behavior; however, published studies use varying definitions for "large". We aimed to identify an outcome-based quantitative cut-off for "large" vs "small" cribriform glands. We conducted an initial training phase using the tissue microarray based Canary retrospective radical prostatectomy cohort. Of 1287 patients analyzed, cribriform growth was observed in 307 (24%). Using Kaplan-Meier estimates of recurrence-free survival curves (RFS) that were stratified by cribriform gland size, we identified 0.25 mm as the optimal cutoff to identify more aggressive disease. In univariable and multivariable Cox proportional hazard analyses, size >0.25 mm was a significant predictor of worse RFS compared to patients with cribriform glands ≤0.25 mm, independent of pre-operative PSA, grade, stage and margin status (p < 0.001). In addition, two different subset analyses of low-intermediate risk cases (cases with Gleason score ≤ 3 + 4 = 7; and cases with Gleason score = 3 + 4 = 7/4 + 3 = 7) likewise demonstrated patients with largest cribriform diameter >0.25 mm had a significantly lower RFS relative to patients with cribriform glands ≤0.25 mm (each subset p = 0.004). Furthermore, there was no significant difference in outcomes between patients with cribriform glands ≤ 0.25 mm and patients without cribriform glands. The >0.25 mm cut-off was validated as statistically significant in a separate 419 patient, completely embedded whole-section radical prostatectomy cohort by biochemical recurrence, metastasis-free survival, and disease specific death, even when cases with admixed Gleason pattern 5 carcinoma were excluded. In summary, our findings support reporting cribriform gland size and identify 0.25 mm as an optimal outcome-based quantitative measure for defining "large" cribriform glands. Moreover, cribriform glands >0.25 mm are associated with potential for metastatic disease independent of Gleason pattern 5 adenocarcinoma.

Rapid Histological Assessment of Prostate Specimens in the Three-dimensional Space by Hydrophilic Tissue Clearing and Confocal Microscopy

Microscopic examination of biopsied and resected prostatic specimens is the mainstay in the diagnosis of prostate cancer. However, conventional analysis of hematoxylin and eosin (H&E)-stained tissue is time-consuming and offers limited two-dimensional (2D) information. In the current study, we devised a method-termed Prostate Rapid Optical examination for cancer STATus (proSTAT)-for rapid screening of prostate cancer using high-resolution 2D and three-dimensional (3D) confocal images obtained after hydrophilic tissue clearing of 100-µm-thick tissue slices. The results of the proSTAT method were compared with those of traditional H&E stains for the analysis of cores (n=15) obtained from radical prostatectomy specimens (n=5). Gland lumen formation, consistent with Gleason pattern 3, was evident following tracking of multiple optical imaging sections. In addition, 3D rendering allowed visualizing a tubular network of interconnecting branches. Rapid 3D fluorescent labeling of tumor protein p63 accurately distinguished prostate adenocarcinoma from normal tissue and benign lesions. Compared with conventional stains, the 3D spatial and molecular information extracted from proSTAT may significantly increase the amount of available data for pathological assessment of prostate specimens. Our approach is amenable to automation and-subject to independent validation-can find a wide spectrum of clinical and research applications.

Cultivating Clinical Clarity through Computer Vision: A Current Perspective on Whole Slide Imaging and Artificial Intelligence

Diagnostic devices, methodological approaches, and traditional constructs of clinical pathology practice, cultivated throughout centuries, have transformed radically in the wake of explosive technological growth and other, e.g., environmental, catalysts of change. Ushered into the fray of modern laboratory medicine are digital imaging devices and machine-learning (ML) software fashioned to mitigate challenges, e.g., practitioner shortage while preparing clinicians for emerging interconnectivity of environments and diagnostic information in the era of big data. As computer vision shapes new constructs for the modern world and intertwines with clinical medicine, cultivating clarity of our new terrain through examining the trajectory and current scope of computational pathology and its pertinence to clinical practice is vital. Through review of numerous studies, we find developmental efforts for ML migrating from research to standardized clinical frameworks while overcoming obstacles that have formerly curtailed adoption of these tools, e.g., generalizability, data availability, and user-friendly accessibility. Groundbreaking validatory efforts have facilitated the clinical deployment of ML tools demonstrating the capacity to effectively aid in distinguishing tumor subtype and grade, classify early vs. advanced cancer stages, and assist in quality control and primary diagnosis applications. Case studies have demonstrated the benefits of streamlined, digitized workflows for practitioners alleviated by decreased burdens.

Predictive value of Cribriform and Intraductal Carcinoma for the Nomogram-Based Selection of Prostate Cancer Patients for Pelvic Lymph Node Dissection

OBJECTIVE

To assess the predictive value of biopsy-identified cribriform carcinoma and/or intraductal carcinoma (CR/IDC) within the Briganti and MSKCC nomograms predicting lymph node metastasis (LNM) in patients with primary prostate cancer (PCa).

METHODS

We retrospectively included 393 PCa patients who underwent radical prostatectomy with extended pelvic lymph node dissection at three tertiary referral centers. We externally validated two prediction tools: the Briganti 2012 nomogram and the Memorial Sloan Kettering Cancer Center (MSKCC) nomogram. Both nomograms were augmented with CR/IDC. The original model was compared with the CR/IDC-updated model using the likelihood ratio test. The performance of the prediction tools was assessed using calibration, discrimination, and clinical utility.

RESULTS

Overall, 109 (28%) men were diagnosed with LNM. Calibration plots of the Briganti and MSKCC nomograms demonstrated an underestimation of the LNM risk across clinically relevant thresholds (≤15%). The addition of CR/IDC to the Briganti nomogram increased the fit of the data (χ²(1)=4.30, p=0.04), but did not improve the area under the curve (AUC) (0.69, 95% CI 0.63-0.75 vs. 0.69, 95% CI 0.64-0.75). Incorporation of CR/IDC in the MSKCC nomogram resulted in an increased fit on the data (χ²(1)=10.04, p<0.01), but did not increase the AUC (0.66, 95% CI 0.60-0.72 vs 0.68, 95% CI 0.62-0.74). The addition of CR/IDC to the Briganti and MSKCC nomograms did not improve the clinical risk prediction.

CONCLUSIONS

Incorporation of CR/IDC into the two clinically most used pre-radical prostatectomy nomograms does not improve LNM prediction in a multinational, contemporary PCa cohort.

Cribriform Patterned Lesions in the Prostate Gland with Emphasis on Differential Diagnosis and Clinical Significance

Simple Summary

A cribriform structure is defined as a continuous proliferation of cells with intermingled lumina. Various entities may have a cribriform morphology within the prostate gland, ranging from normal, to benign, to borderline and even to malignant lesions. This review summarizes the morphologic features of entities that have a cribriform morphology within the prostate gland, with an emphasis on their differential diagnosis, molecular profile and clinical significance. The basic aim is to assist the pathologist with challenging and controversial cases and inform the clinician on the clinical implications of cribriform morphology.

Abstract

Cribriform glandular formations are characterized by a continuous proliferation of cells with intermingled lumina and can constitute a major or minor part of physiologic (normal central zone glands), benign (clear cell cribriform hyperplasia and basal cell hyperplasia), premalignant (high-grade prostatic intraepithelial neoplasia), borderline (atypical intraductal cribriform proliferation) or clearly malignant (intraductal, acinar, ductal and basal cell carcinoma) lesions. Each displays a different clinical course and variability in clinical management and prognosis. The aim of this review is to summarize the current knowledge regarding the morphological features, differential diagnosis, molecular profile and clinical significance of the cribriform-patterned entities of the prostate gland. Areas of controversy regarding their management, i.e., the grading of Intaductal Carcinoma, will also be discussed. Understanding the distinct nature of each cribriform lesion leads to the correct diagnosis and ensures accuracy in clinical decision-making, prognosis prediction and personalized risk stratification of patients.

Large and small cribriform architecture have similar adverse clinical outcome on prostate cancer biopsies

Aims

Invasive cribriform and intraductal carcinoma (IDC) are associated with adverse outcome in prostate cancer patients, with the large cribriform pattern having the worst outcome in radical prostatectomies. Our objective was to determine the impact of the large and small cribriform patterns in prostate cancer biopsies.

Methods and results

Pathological revision was carried out on biopsies of 1887 patients from the European Randomised Study of Screening for Prostate Cancer. The large cribriform pattern was defined as having at least twice the size of adjacent benign glands. The median follow‐up time was 13.4 years. Hazard ratios for metastasis‐free survival (MFS) and disease‐specific survival (DSS) were calculated using Cox proportional hazards regression. Any cribriform pattern was found in 280 of 1887 men: 1.1% IDC in grade group (GG) 1, 18.2% in GG2, 57.1% in GG3, 55.4% in GG4 and 59.3% in GG5; the large cribriform pattern was present in 0, 0.5, 9.8, 18.1 and 17.3%, respectively. In multivariable analyses, small and large cribriform patterns were both (P < 0.005) associated with worse MFS [small: hazard ratio (HR) = 3.04, 95% confidence interval (CI) = 1.93–4.78; large: HR = 3.17, 95% CI = 1.68–5.99] and DSS (small: HR = 4.07, 95% CI = 2.51–6.62; large: HR = 4.13, 95% CI = 2.14–7.98). Patients with the large cribriform pattern did not have worse MFS (P = 0.77) or DSS (P = 0.96) than those with the small cribriform pattern.

Conclusions

Both small and large cribriform patterns are associated with worse MFS and DSS in prostate cancer biopsies. Patients with the large cribriform pattern on biopsy have a similar adverse outcome as those with the small cribriform pattern.

Prostate Pathology: What is New in the 2022 WHO Classification of Urinary and Male Genital Tumors?

In 2022, after a six-year interval, the International Agency for Research on Cancer (IARC) has published the 5th edition of the WHO Classification of Urinary and Male Genital Tumors, which provides a comprehensive update on tumor classification of the genitourinary system. This review article focuses on prostate carcinoma and underscores changes in the prostate chapter as well as those made across the entire series of the 5th edition of WHO Blue Books. Although no major alterations were made to this chapter, some of the most notable updates include restructure of contents and introduction of a new format; standardization of mitotic counts, genomic nomenclatures, and units of length; refined definition for the terms "variant", "subtype", and "histologic pattern"; reclassification of prostatic intraepithelial neoplasia (PIN)-like adenocarcinoma as a subtype of prostatic acinar adenocarcinoma; and recognition of treatment-related neuroendocrine prostatic carcinoma as a distinct tumor type. Evolving and unsettled issues related to grading of intraductal carcinoma of the prostate and reporting of tertiary Gleason pattern, the definition and prognostic significance of cribriform growth pattern, and molecular pathology of prostate cancer will also be covered in this review.

Significant Inter- and Intralaboratory Variation in Gleason Grading of Prostate Cancer: A Nationwide Study of 35,258 Patients in The Netherlands

Simple Summary

Gleason grading of prostate cancer is essential for treatment strategies and patient prognosis. Previous studies showed grading variation between pathologists when grading prostate cancer. Our study analyzed the presence and extent of grading variation between and within pathology laboratories in The Netherlands. In our nationwide retrospective study, we analyzed prostate needle biopsy reports of 35,258 patients in The Netherlands graded by 40 pathology laboratories. We found a considerable variation between and within pathology laboratories, as over half of the laboratories graded significantly different from the national mean. This likely affects treatment strategy and prognosis assessment of prostate cancer patients.

Abstract

Purpose: Our aim was to analyze grading variation between pathology laboratories and between pathologists within individual laboratories using nationwide real-life data. Methods: We retrieved synoptic (n = 13,397) and narrative (n = 29,377) needle biopsy reports from the Dutch Pathology Registry and prostate-specific antigen values from The Netherlands Cancer Registration for prostate cancer patients diagnosed between January 2017 and December 2019. We determined laboratory-specific proportions per histologic grade and unadjusted odds ratios (ORs) for International Society of Urological Pathologists Grades 1 vs. 2–5 for 40 laboratories due to treatment implications for higher grades. Pathologist-specific proportions were determined for 21 laboratories that consented to this part of analysis. The synoptic reports of 21 laboratories were used for analysis of case-mix correction for PSA, age, year of diagnosis, number of biopsies and positive cores. Results: A total of 38,321 reports of 35,258 patients were included. Grade 1 ranged between 19.7% and 44.3% per laboratory (national mean = 34.1%). Out of 40 laboratories, 22 (55%) reported a significantly deviant OR, ranging from 0.48 (95% confidence interval (CI) 0.39–0.59) to 1.54 (CI 1.22–1.93). Case-mix correction was performed for 10,294 reports, altering the status of 3/21 (14%) laboratories, but increasing the observed variation (20.8% vs. 17.7%). Within 15/21 (71%) of laboratories, significant inter-pathologist variation existed. Conclusion: Substantial variation in prostate cancer grading was observed between and within Dutch pathology laboratories. Case-mix correction did not explain the variation. Better standardization of prostate cancer grading is warranted to optimize and harmonize treatment.

Cribriform architecture outperforms percent Gleason pattern 4 and tertiary pattern 5 in predicting outcome of Grade group 2 prostate cancer patients

Aims

Gleason pattern 4 (GP4) percentage, invasive cribriform and/or intraductal carcinoma (IC/IDC) and the presence of tertiary Gleason pattern 5 (TP5) in radical prostatectomy (RP) specimens all aid in the risk stratification of Grade Group (GG) 2 prostate cancer patients. However, it is unclear to what extent these pathological features are mutually related and what are their individual values if they are investigated simultaneously. The aims of this study were: (i) to determine the mutual relationships of the GP4 percentage, IC/IDC and TP5 in GG2 RP specimens; and (ii) to assess their prognostic value for biochemical recurrence‐free survival (BCRFS).

Methods and results

Of 1064 RP specimens, 472 (44.4%) showed GG2 prostate cancer. Patients with ≥25% GP4 more frequently had IC/IDC (67.0% versus 43.9%; P < 0.001) and TP5 (20.6% versus 5.8%; P < 0.001) than those with <25% GP4. In unadjusted analysis, an increased GP4 percentage [hazard ratio (HR) 1.3; 95% confidence interval (CI) 1.0–1.6; P = 0.04] and IC/IDC (log rank P < 0.001) were associated with shorter BCRFS, whereas TP5 (P = 0.12) and a dichotomised (<25%, ≥25%) GP4 percentage (P = 0.10) were not. In multivariable analysis, IC/IDC was an independent prognostic factor (HR 1.9; 95% CI 1.2–2.9; P = 0.005) for BCRFS, whereas a continuous or dichotomised GP4 percentage and TP5 were not independent prognostic factors.

Conclusion

In conclusion, a higher GP4 percentage in RP specimens was associated with more frequent IC/IDC and TP5. IC/IDC was an independent predictor for BCRFS, whereas the GP4 percentage and TP5 were not. These findings underscore the importance of routinely including the presence of IC/IDC in RP pathology reports.

[Localized prostate cancer]

Prostate cancer is the most prevalent noncutaneous cancer in men. The Gleason grading is considered to be the strongest prognostic parameter regarding progression-free survival and overall survival. The original grading system has been modified during the last decade resulting in a more precise prognostic tool. The pretreatment Gleason score guides clinical management and is a key component in S3 guidelines for prostate cancer. In addition to Gleason score several other histologic findings in prostate needle biopsy influence patient management. In this second part of our CME series about prostate cancer, we will discuss the diagnosis of prostate cancer and current guidelines for reporting prostate cancer. In addition, we will highlight prostate lesions of urothelial origin and neuroendocrine prostate cancer as well as prognostic biomarkers.

Prognostic value of cribriform size, percentage, and intraductal carcinoma in Gleason score 7 prostate cancer with cribriform Gleason pattern 4

Cribriform Gleason pattern 4 (CGP4) is an indicator of poor prognosis in Gleason Score 7 prostate cancer; however, the significance of the size and percentage of this pattern and the presence of concomitant intraductal carcinoma (IDC) in these patients is unclear. To study the significance of these parameters in radical prostatectomy specimens, 165 cases with CGP4 were identified and reviewed (2017-2019). The size and percentage cribriform pattern and presence of IDC were noted and correlated with adverse pathological features and biochemical recurrence (BCR)-free survival. On review, 156 cases had CGP4 (Grade Group 2: 87 and Grade Group 3: 69). Large cribriform pattern and cribriform percentage of >20% showed significant association with extraprostatic extension, surgical margin positivity, and presence of IDC, whereas the presence of IDC was associated with all the analyzed adverse pathological features. BCR was seen in 22 of 111 (20%) patients after a median follow-up of 11 months, and of these, 21 had large cribriform pattern. On univariate analysis, all parameters had significant predictive values for BCR-free survival except for tertiary Gleason pattern 5. On multivariate analysis, while >20% cribriform pattern was trending to be an independent predictor, only lymphovascular invasion was statistically significant. Large cribriform pattern, >20% cribriform, and presence of IDC are additional pathologic parameters of potential value in identifying patients with high risk for early BCR.

Addressing the Diagnostic Miscommunication in Pathology

OBJECTIVES

The pathology report serves as a crucial communication tool among a number of stakeholders. It can sometimes be challenging to understand. A communication barrier exists among pathologists, other clinicians, and patients when interpreting the pathology report, leaving both clinicians and patients less empowered when making treatment decisions. Miscommunication can lead to delays in treatment or other costly medical interventions.

METHODS

In this review, we highlight miscommunication in pathology reporting and provide potential solutions to improve communication.

RESULTS

Up to one-third of clinicians do not always understand pathology reports. Several causes of report misinterpretation include the use of pathology-specific jargon, different versions of staging or grading systems, and expressions indicative of uncertainty in the pathologist's report. Active communication has proven to be crucial between the clinician and the pathologist to clarify different aspects of the pathology report. Direct communication between pathologists and patients is evolving, with promising success in proof-of-principle studies. Special attention needs to be paid to avoiding inaccuracy while trying to simplify the pathology report.

CONCLUSIONS

There is a need for active and adequate communication among pathologists, other clinicians, and patients. Clarity and consistency in reporting, quantifying the level of confidence in diagnosis, and avoiding misnomers are key steps toward improving communications.

PTEN and DNA Ploidy Status by Machine Learning in Prostate Cancer

Simple Summary

Molecular tissue-based prognostic biomarkers are anticipated to complement the current risk stratification systems in prostate cancer, but their manual assessment is subjective and time-consuming. Objective assessment of such biomarkers by machine learning-based methods could advance their adoption in a clinical workflow. PTEN and DNA ploidy status are well-studied biomarkers, which can provide clinically relevant information in prostate cancer at a low cost. Using a cohort of 253 patients who received radical prostatectomy, we developed a novel, fully-automated PTEN scoring in immunohistochemically-stained tissue slides, which could be used to assess PTEN status in a reliable and reproducible manner. In an independent validation cohort of 259 patients, automatically assessed PTEN status was significantly associated with time to biochemical recurrence after radical prostatectomy, and the combination of PTEN and DNA ploidy status further improved risk stratification. These results demonstrate the utility of machine learning in biomarker assessment.

Abstract

Machine learning (ML) is expected to improve biomarker assessment. Using convolution neural networks, we developed a fully-automated method for assessing PTEN protein status in immunohistochemically-stained slides using a radical prostatectomy (RP) cohort (n = 253). It was validated according to a predefined protocol in an independent RP cohort (n = 259), alone and by measuring its prognostic value in combination with DNA ploidy status determined by ML-based image cytometry. In the primary analysis, automatically assessed dichotomized PTEN status was associated with time to biochemical recurrence (TTBCR) (hazard ratio (HR) = 3.32, 95% CI 2.05 to 5.38). Patients with both non-diploid tumors and PTEN-low had an HR of 4.63 (95% CI 2.50 to 8.57), while patients with one of these characteristics had an HR of 1.94 (95% CI 1.15 to 3.30), compared to patients with diploid tumors and PTEN-high, in univariable analysis of TTBCR in the validation cohort. Automatic PTEN scoring was strongly predictive of the PTEN status assessed by human experts (area under the curve 0.987 (95% CI 0.968 to 0.994)). This suggests that PTEN status can be accurately assessed using ML, and that the combined marker of automatically assessed PTEN and DNA ploidy status may provide an objective supplement to the existing risk stratification factors in prostate cancer.

ISUP Consensus Definition of Cribriform Pattern Prostate Cancer

The presence of a cribriform pattern is now recognized as a clinically important, independent adverse prognostic indicator for prostate cancer. For this reason the International Society of Urological Pathology (ISUP) recently recommended its inclusion in standard reporting. In order to improve interobserver agreement as to the diagnosis of cribriform patterns, the ISUP assembled an international panel of 12 expert urogenital pathologists for the purpose of drafting a consensus definition of cribriform pattern in prostate cancer, and provide their opinions on a set of 32 images and on potential diagnostic criteria. These images were selected by the 2 nonvoting convenors of the study and included the main categories where disagreement was anticipated. The Delphi method was applied to promote consensus among the 12 panelists in their review of the images during 2 initial rounds of the study. Following a virtual meeting, convened to discuss selected images and diagnostic criteria, the following definition for cribriform pattern in prostate cancer was approved: "A confluent sheet of contiguous malignant epithelial cells with multiple glandular lumina that are easily visible at low power (objective magnification ×10). There should be no intervening stroma or mucin separating individual or fused glandular structures" together with a set of explanatory notes. We believe this consensus definition to be practical and that it will facilitate reproducible recognition and reporting of this clinically important pattern commonly seen in prostate cancer. The images and the results of the final Delphi round are available at the ISUP website as an educational slide set (https://isupweb.org/isup/blog/slideshow/cribriform-slide-deck/).

The 2019 Genitourinary Pathology Society (GUPS) White Paper on Contemporary Grading of Prostate Cancer

CONTEXT.—

Controversies and uncertainty persist in prostate cancer grading.

OBJECTIVE.—

To update grading recommendations.

DATA SOURCES.—

Critical review of the literature along with pathology and clinician surveys.

CONCLUSIONS.—

Percent Gleason pattern 4 (%GP4) is as follows: (1) report %GP4 in needle biopsy with Grade Groups (GrGp) 2 and 3, and in needle biopsy on other parts (jars) of lower grade in cases with at least 1 part showing Gleason score (GS) 4 + 4 = 8; and (2) report %GP4: less than 5% or less than 10% and 10% increments thereafter. Tertiary grade patterns are as follows: (1) replace "tertiary grade pattern" in radical prostatectomy (RP) with "minor tertiary pattern 5 (TP5)," and only use in RP with GrGp 2 or 3 with less than 5% Gleason pattern 5; and (2) minor TP5 is noted along with the GS, with the GrGp based on the GS. Global score and magnetic resonance imaging (MRI)-targeted biopsies are as follows: (1) when multiple undesignated cores are taken from a single MRI-targeted lesion, an overall grade for that lesion is given as if all the involved cores were one long core; and (2) if providing a global score, when different scores are found in the standard and the MRI-targeted biopsy, give a single global score (factoring both the systematic standard and the MRI-targeted positive cores). Grade Groups are as follows: (1) Grade Groups (GrGp) is the terminology adopted by major world organizations; and (2) retain GS 3 + 5 = 8 in GrGp 4. Cribriform carcinoma is as follows: (1) report the presence or absence of cribriform glands in biopsy and RP with Gleason pattern 4 carcinoma. Intraductal carcinoma (IDC-P) is as follows: (1) report IDC-P in biopsy and RP; (2) use criteria based on dense cribriform glands (>50% of the gland is composed of epithelium relative to luminal spaces) and/or solid nests and/or marked pleomorphism/necrosis; (3) it is not necessary to perform basal cell immunostains on biopsy and RP to identify IDC-P if the results would not change the overall (highest) GS/GrGp part per case; (4) do not include IDC-P in determining the final GS/GrGp on biopsy and/or RP; and (5) "atypical intraductal proliferation (AIP)" is preferred for an intraductal proliferation of prostatic secretory cells which shows a greater degree of architectural complexity and/or cytological atypia than typical high-grade prostatic intraepithelial neoplasia, yet falling short of the strict diagnostic threshold for IDC-P. Molecular testing is as follows: (1) Ki67 is not ready for routine clinical use; (2) additional studies of active surveillance cohorts are needed to establish the utility of PTEN in this setting; and (3) dedicated studies of RNA-based assays in active surveillance populations are needed to substantiate the utility of these expensive tests in this setting. Artificial intelligence and novel grading schema are as follows: (1) incorporating reactive stromal grade, percent GP4, minor tertiary GP5, and cribriform/intraductal carcinoma are not ready for adoption in current practice.

Computationally Derived Cribriform Area Index from Prostate Cancer Hematoxylin and Eosin Images Is Associated with Biochemical Recurrence Following Radical Prostatectomy and Is Most Prognostic in Gleason Grade Group 2

BACKGROUND

The presence of invasive cribriform adenocarcinoma (ICC), an expanse of cells containing punched-out lumina uninterrupted by stroma, in radical prostatectomy (RP) specimens has been associated with biochemical recurrence (BCR). However, ICC identification has only moderate inter-reviewer agreement.

OBJECTIVE

To investigate quantitative machine-based assessment of the extent and prognostic utility of ICC, especially within individual Gleason grade groups.

DESIGN, SETTING, AND PARTICIPANTS

A machine learning approach was developed for ICC segmentation using 70 RP patients and validated in a cohort of 749 patients from four sites whose median year of surgery was 2007 and with median follow-up of 28 mo. ICC was segmented on one representative hematoxylin and eosin RP slide per patient and the fraction of tumor area composed of ICC, the cribriform area index (CAI), was measured.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The association between CAI and BCR was measured in terms of the concordance index (c index) and hazard ratio (HR).

RESULTS AND LIMITATIONS

CAI was correlated with BCR (c index 0.62) in the validation set of 411 patients with ICC morphology, especially those with Gleason grade group 2 cancer (n = 192; c index 0.66), and was less prognostic when patients without ICC were included (c index 0.54). A doubling of CAI in the group with ICC morphology was prognostic after controlling for Gleason grade, surgical margin positivity, preoperative prostate-specific antigen level, pathological T stage, and age (HR 1.19, 95% confidence interval 1.03-1.38; p = 0.018).

CONCLUSIONS

Automated image analysis and machine learning could provide an objective, quantitative, reproducible, and high-throughput method of quantifying ICC area. The performance of CAI for grade group 2 cancer suggests that for patients with little Gleason 4 pattern, the ICC fraction has a strong prognostic role.

PATIENT SUMMARY

Machine-based measurement of a specific cell pattern (cribriform; sieve-like, with lots of spaces) in images of prostate specimens could improve risk stratification for patients with prostate cancer. In the future, this could help in expanding the criteria for active surveillance.

Pathomics in urology

PURPOSE OF REVIEW

Pathomics, the fusion of digitalized pathology and artificial intelligence, is currently changing the landscape of medical pathology and biologic disease classification. In this review, we give an overview of Pathomics and summarize its most relevant applications in urology.

RECENT FINDINGS

There is a steady rise in the number of studies employing Pathomics, and especially deep learning, in urology. In prostate cancer, several algorithms have been developed for the automatic differentiation between benign and malignant lesions and to differentiate Gleason scores. Furthermore, several applications have been developed for the automatic cancer cell detection in urine and for tumor assessment in renal cancer. Despite the explosion in research, Pathomics is not fully ready yet for widespread clinical application.

SUMMARY

In prostate cancer and other urologic pathologies, Pathomics is avidly being researched with commercial applications on the close horizon. Pathomics is set to improve the accuracy, speed, reliability, cost-effectiveness and generalizability of pathology, especially in uro-oncology.

Cribriform prostate cancer: Morphologic criteria enabling a diagnosis, based on survey of experts

Among four sub-patterns of Gleason grade 4 prostate cancer, voluminous evidence supports that the cribriform pattern holds an unfavorable prognostic impact, as compared with poorly-formed, fused, or glomeruloid. The International Society of Urological Pathology (ISUP) recommends specifying whether invasive grade 4 cancer is cribriform. Recently, ISUP experts published a consensus definition of cribriform pattern highlighting criteria that distinguish it from mimickers. The current study aimed to analyze morphologic features separately to identify those that define the essence of the cribriform pattern. Thirty-two selected photomicrographs were classified by 12 urologic pathologists as: definitely cribriform cancer, probably cribriform, unsure, probably not cribriform, or definitely not cribriform. Consensus was defined as 9/12 agree or disagree, with ≤1 strongly supporting the opposite choice. Final consensus was achieved in 21 of 32 cases. Generalized estimating equation (GEE) model with logit link was fitted to estimate effect of multiple morphologic predictors. Fisher exact test was used for categorical findings. Presence of intervening stroma precluded calling cribriform cancer (p = 0.006). Mucin presence detracted (p = 0.003) from willingness to call cribriform cancer (only 3 cases had mucin). Lumen number was associated with cribriform consensus (p = 0.0006), and all consensus cases had ≥9 lumens. Predominant papillary pattern or an irregular outer boundary detracted (p = NS). Invasive cribriform carcinoma should have absence of intervening stroma, and usually neither papillary pattern, irregular outer boundary, nor very few lumens. Setting the criteria for cribriform will help prevent over- or undercalling this important finding.

Harnessing non-destructive 3D pathology

High-throughput methods for slide-free three-dimensional (3D) pathological analyses of whole biopsies and surgical specimens offer the promise of modernizing traditional histology workflows and delivering improvements in diagnostic performance. Advanced optical methods now enable the interrogation of orders of magnitude more tissue than previously possible, where volumetric imaging allows for enhanced quantitative analyses of cell distributions and tissue structures that are prognostic and predictive. Non-destructive imaging processes can simplify laboratory workflows, potentially reducing costs, and can ensure that samples are available for subsequent molecular assays. However, the large size of the feature-rich datasets that they generate poses challenges for data management and computer-aided analysis. In this Perspective, we provide an overview of the imaging technologies that enable 3D pathology, and the computational tools-machine learning, in particular-for image processing and interpretation. We also discuss the integration of various other diagnostic modalities with 3D pathology, along with the challenges and opportunities for clinical adoption and regulatory approval.

Interchangeability of light and virtual microscopy for histopathological evaluation of prostate cancer

Virtual microscopy (VM) holds promise to reduce subjectivity as well as intra- and inter-observer variability for the histopathological evaluation of prostate cancer. We evaluated (i) the repeatability (intra-observer agreement) and reproducibility (inter-observer agreement) of the 2014 Gleason grading system and other selected features using standard light microscopy (LM) and an internally developed VM system, and (ii) the interchangeability of LM and VM. Two uro-pathologists reviewed 413 cores from 60 Swedish men diagnosed with non-metastatic prostate cancer 1998–2014. Reviewer 1 performed two reviews using both LM and VM. Reviewer 2 performed one review using both methods. The intra- and inter-observer agreement within and between LM and VM were assessed using Cohen’s kappa and Bland and Altman’s limits of agreement. We found good repeatability and reproducibility for both LM and VM, as well as interchangeability between LM and VM, for primary and secondary Gleason pattern, Gleason Grade Groups, poorly formed glands, cribriform pattern and comedonecrosis but not for the percentage of Gleason pattern 4. Our findings confirm the non-inferiority of VM compared to LM. The repeatability and reproducibility of percentage of Gleason pattern 4 was poor regardless of method used warranting further investigation and improvement before it is used in clinical practice.

Going deeper through the Gleason scoring scale: An automatic end-to-end system for histology prostate grading and cribriform pattern detection

BACKGROUND AND OBJECTIVE

Prostate cancer is one of the most common diseases affecting men worldwide. The Gleason scoring system is the primary diagnostic and prognostic tool for prostate cancer. Furthermore, recent reports indicate that the presence of patterns of the Gleason scale such as the cribriform pattern may also correlate with a worse prognosis compared to other patterns belonging to the Gleason grade 4. Current clinical guidelines have indicated the convenience of highlight its presence during the analysis of biopsies. All these requirements suppose a great workload for the pathologist during the analysis of each sample, which is based on the pathologist's visual analysis of the morphology and organisation of the glands in the tissue, a time-consuming and subjective task. In recent years, with the development of digitisation devices, the use of computer vision techniques for the analysis of biopsies has increased. However, to the best of the authors' knowledge, the development of algorithms to automatically detect individual cribriform patterns belonging to Gleason grade 4 has not yet been studied in the literature. The objective of the work presented in this paper is to develop a deep-learning-based system able to support pathologists in the daily analysis of prostate biopsies. This analysis must include the Gleason grading of local structures, the detection of cribriform patterns, and the Gleason scoring of the whole biopsy.

METHODS

The methodological core of this work is a patch-wise predictive model based on convolutional neural networks able to determine the presence of cancerous patterns based on the Gleason grading system. In particular, we train from scratch a simple self-design architecture with three filters and a top model with global-max pooling. The cribriform pattern is detected by retraining the set of filters of the last convolutional layer in the network. Subsequently, a biopsy-level prediction map is reconstructed by bi-linear interpolation of the patch-level prediction of the Gleason grades. In addition, from the reconstructed prediction map, we compute the percentage of each Gleason grade in the tissue to feed a multi-layer perceptron which provides a biopsy-level score.

RESULTS

In our SICAPv2 database, composed of 182 annotated whole slide images, we obtained a Cohen's quadratic kappa of 0.77 in the test set for the patch-level Gleason grading with the proposed architecture trained from scratch. Our results outperform previous ones reported in the literature. Furthermore, this model reaches the level of fine-tuned state-of-the-art architectures in a patient-based four groups cross validation. In the cribriform pattern detection task, we obtained an area under ROC curve of 0.82. Regarding the biopsy Gleason scoring, we achieved a quadratic Cohen's Kappa of 0.81 in the test subset. Shallow CNN architectures trained from scratch outperform current state-of-the-art methods for Gleason grades classification. Our proposed model is capable of characterising the different Gleason grades in prostate tissue by extracting low-level features through three basic blocks (i.e. convolutional layer + max pooling). The use of global-max pooling to reduce each activation map has shown to be a key factor for reducing complexity in the model and avoiding overfitting. Regarding the Gleason scoring of biopsies, a multi-layer perceptron has shown to better model the decision-making of pathologists than previous simpler models used in the literature.

Prostate cancer growth patterns beyond the Gleason score: entering a new era of comprehensive tumour grading

The Gleason grading system is one of the most important factors in clinical decision‐making for prostate cancer patients, and is entirely based on the classification of tumour growth patterns. In recent years it has become clear that some individual growth patterns themselves have independent prognostic value, and could be used for better personalised risk stratification. In this review we summarise recent literature on the clinicopathological value and molecular characteristics of individual prostate cancer growth patterns, and show how these, most particularly cribriform architecture, could alter treatment decisions for prostate cancer patients.

Automated detection of cribriform growth patterns in prostate histology images

Cribriform growth patterns in prostate carcinoma are associated with poor prognosis. We aimed to introduce a deep learning method to detect such patterns automatically. To do so, convolutional neural network was trained to detect cribriform growth patterns on 128 prostate needle biopsies. Ensemble learning taking into account other tumor growth patterns during training was used to cope with heterogeneous and limited tumor tissue occurrences. ROC and FROC analyses were applied to assess network performance regarding detection of biopsies harboring cribriform growth pattern. The ROC analysis yielded a mean area under the curve up to 0.81. FROC analysis demonstrated a sensitivity of 0.9 for regions larger than \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${0.0150}\,\hbox {mm}^{2}$$\end{document}0.0150mm2 with on average 7.5 false positives. To benchmark method performance for intra-observer annotation variability, false positive and negative detections were re-evaluated by the pathologists. Pathologists considered 9% of the false positive regions as cribriform, and 11% as possibly cribriform; 44% of the false negative regions were not annotated as cribriform. As a final experiment, the network was also applied on a dataset of 60 biopsy regions annotated by 23 pathologists. With the cut-off reaching highest sensitivity, all images annotated as cribriform by at least 7/23 of the pathologists, were all detected as cribriform by the network and 9/60 of the images were detected as cribriform whereas no pathologist labelled them as such. In conclusion, the proposed deep learning method has high sensitivity for detecting cribriform growth patterns at the expense of a limited number of false positives. It can detect cribriform regions that are labelled as such by at least a minority of pathologists. Therefore, it could assist clinical decision making by suggesting suspicious regions.

Histopathological re-evaluations of biopsies in prostate cancer: a nationwide observational study

BACKGROUND

Grading prostate biopsies has an important role in determining treatment strategy. Histopathological evaluations suffer from interobserver variability and therefore biopsies may be re-evaluated.

OBJECTIVE

To provide insight into the extent of, characteristics associated with and clinical implications of prostate biopsy re-evaluations in daily clinical practice.

METHODS

Patients diagnosed with prostate cancer (PCa) by biopsy between October 2015 and April 2016 identified through the Netherlands Cancer Registry were included. The proportion of re-evaluations was assessed and characteristics were compared between patients with and without biopsy re-evaluation. Interobserver concordance of ISUP grade and EAU prognostic risk classification was determined by calculating Cohen's kappa.

RESULTS

Biopsy re-evaluation was performed in 172 (3.3%) of 5214 patients. Primary reason for re-evaluation in patients treated with curative intent was referral to another hospital. Most referred patients treated with curative intent (n = 1856) had no re-evaluation (93.0%, n = 1727). Patients with biopsy re-evaluation were younger and underwent more often prostatectomy compared to patients without re-evaluation. The disagreement rate for ISUP grade was 26.1% and interobserver concordance was substantial (κ-weighted = 0.74). Re-evaluation resulted in 21.1% (n = 14) of patients with localised PCa in a different prognostic risk group. More tumours were downgraded (57.1%) than upgraded (42.9%). Interobserver concordance was very good (κ _weighted = 0.85).

CONCLUSION

Pathology review of prostate biopsies is infrequently requested by clinicians in the Netherlands but in a non-negligible minority of patients with localised PCa the pathology review led to a change in prognostic risk group which might impact their treatment.

Inter-observer variability of cribriform architecture and percent Gleason pattern 4 in prostate cancer: relation to clinical outcome

The Grade group is an important parameter for clinical decision-making in prostate cancer. Recently, percent Gleason pattern 4 and presence of invasive cribriform and/or intraductal carcinoma (CR/IDC) have been recognized for their independent predictive value for prostate cancer outcome. There is sparse data on the inter-observer agreement for these pathologic features in practice. Our objectives were to investigate inter-observer variability of percent Gleason pattern and CR/IDC and to relate individual tumour scores to clinical outcome. Our cohort included 80 consecutive radical prostatectomies with a median follow-up 87.1 months (interquartile range 43.3-119.2), of which the slide with largest tumour volume was scored by six pathologists for Grade group (four tiers: 1, 2, 3 and 4/5), percent Gleason pattern 4 (four tiers: 0-25%, 26-50%, 51-75% and 76-100%) and presence of CR/IDC (two tiers: absent, present). The individual assignments were related to post-operative biochemical recurrence (20/80). Inter-observer agreement was substantial (Krippendorff's α 0.626) for assessment of Grade group and moderate for CR/IDC (α 0.507) and percent Gleason pattern 4 (α 0.551). For each individual pathologist, biochemical recurrence rates incremented by Grade group and presence of CR/IDC, although such relation was less clear for percent Gleason pattern 4. In conclusion, inter-observer agreement for CR/IDC and percent Gleason pattern 4 is lower than for Grade groups, indicating awareness of these features needs further improvement. Grade group and CR/IDC, but not percent Gleason pattern 4 was related to biochemical recurrence for each pathologist, indicating overall validity of individual grade assignments despite inter-observer variability.

The 2019 International Society of Urological Pathology (ISUP) Consensus Conference on Grading of Prostatic Carcinoma

Five years after the last prostatic carcinoma grading consensus conference of the International Society of Urological Pathology (ISUP), accrual of new data and modification of clinical practice require an update of current pathologic grading guidelines. This manuscript summarizes the proceedings of the ISUP consensus meeting for grading of prostatic carcinoma held in September 2019, in Nice, France. Topics brought to consensus included the following: (1) approaches to reporting of Gleason patterns 4 and 5 quantities, and minor/tertiary patterns, (2) an agreement to report the presence of invasive cribriform carcinoma, (3) an agreement to incorporate intraductal carcinoma into grading, and (4) individual versus aggregate grading of systematic and multiparametric magnetic resonance imaging-targeted biopsies. Finally, developments in the field of artificial intelligence in the grading of prostatic carcinoma and future research perspectives were discussed.

Clinicopathological characteristics of glomeruloid architecture in prostate cancer

Glomeruloid architecture is the least common Gleason 4 growth pattern in prostate adenocarcinoma. Its clinicopathological features and relation with cribriform architecture, which has been recognized as an adverse feature, remains to be established. Our objective was to investigate clinicopathological features of glomeruloid architecture in radical prostatectomies. We reviewed 1064 radical prostatectomy specimens and recorded Grade Group, pT-stage, margin status, Gleason pattern percentages, and growth patterns. Simple and complex glomerulations were distinguished by gland size and intraluminal cribriform protrusions. Clinical endpoint was biochemical recurrence-free survival. Glomerulations were identified in 365 (34%) specimens. In 472 Grade Group 2 patients, 210 (44%) had simple and 92 (19%) complex glomerulations. Complex glomerulations coincided with cribriform architecture more often than simple glomerulations (67% versus 52%; P = 0.01). Men with simple glomerulations had significantly lower prostate specific antigen (PSA) levels (9.7 versus 12.1 ng/ml; P = 0.03), percentage Gleason pattern 4 (19% versus 25%; P = 0.001), extra-prostatic extension (34% versus 50%; P = 0.01), and positive surgical margins (25% versus 39%; P = 0.04) than those with cribriform architecture. Extra-prostatic extension (37%) and positive surgical margins (30%) in men with complex glomerulations resembled those with simple glomeruloid rather than those with cribriform architecture. In multivariate Cox regression analysis adjusted for PSA, pT-stage, margin status, and lymph node metastases, cribriform architecture had independent predictive value for biochemical recurrence-free survival (hazard ratio (HR)) 1.9; 95% confidence interval (CI) 1.2-2.9; P = 0.004), while simple (HR 0.8; 95% CI 0.5-1.2; P = 0.26) and complex (HR 0.9; 95% CI 0.5-1.6; P = 0.67) glomerulations did not. Both simple and complex glomeruloid architecture are associated with better outcome than cribriform architecture in Grade Group 2 prostate cancer patients. Therefore, glomeruloid pattern and particularly complex glomerulations should not be classified as a cribriform growth pattern variant in radical prostatectomy specimens.

Identification of areas of grading difficulties in prostate cancer and comparison with artificial intelligence assisted grading

The International Society of Urological Pathology (ISUP) hosts a reference image database supervised by experts with the purpose of establishing an international standard in prostate cancer grading. Here, we aimed to identify areas of grading difficulties and compare the results with those obtained from an artificial intelligence system trained in grading. In a series of 87 needle biopsies of cancers selected to include problematic cases, experts failed to reach a 2/3 consensus in 41.4% (36/87). Among consensus and non-consensus cases, the weighted kappa was 0.77 (range 0.68-0.84) and 0.50 (range 0.40-0.57), respectively. Among the non-consensus cases, four main causes of disagreement were identified: the distinction between Gleason score 3 + 3 with tangential cutting artifacts vs. Gleason score 3 + 4 with poorly formed or fused glands (13 cases), Gleason score 3 + 4 vs. 4 + 3 (7 cases), Gleason score 4 + 3 vs. 4 + 4 (8 cases) and the identification of a small component of Gleason pattern 5 (6 cases). The AI system obtained a weighted kappa value of 0.53 among the non-consensus cases, placing it as the observer with the sixth best reproducibility out of a total of 24. AI may serve as a decision support and decrease inter-observer variability by its ability to make consistent decisions. The grading of these cancer patterns that best predicts outcome and guides treatment warrants further clinical and genetic studies. Results of such investigations should be used to improve calibration of AI systems.