Added Clinical Value of Whole-mount Histopathology of Radical Prostatectomy Specimens: A Collaborative Review

RAPHIA: A deep learning pipeline for the registration of MRI and whole-mount histopathology images of the prostate

Image registration can map the ground truth extent of prostate cancer from histopathology images onto MRI, facilitating the development of machine learning methods for early prostate cancer detection. Here, we present RAdiology PatHology Image Alignment (RAPHIA), an end-to-end pipeline for efficient and accurate registration of MRI and histopathology images. RAPHIA automates several time-consuming manual steps in existing approaches including prostate segmentation, estimation of the rotation angle and horizontal flipping in histopathology images, and estimation of MRI-histopathology slice correspondences. By utilizing deep learning registration networks, RAPHIA substantially reduces computational time. Furthermore, RAPHIA obviates the need for a multimodal image similarity metric by transferring histopathology image representations to MRI image representations and vice versa. With the assistance of RAPHIA, novice users achieved expert-level performance, and their mean error in estimating histopathology rotation angle was reduced by 51% (12 degrees vs 8 degrees), their mean accuracy of estimating histopathology flipping was increased by 5% (95.3% vs 100%), and their mean error in estimating MRI-histopathology slice correspondences was reduced by 45% (1.12 slices vs 0.62 slices). When compared to a recent conventional registration approach and a deep learning registration approach, RAPHIA achieved better mapping of histopathology cancer labels, with an improved mean Dice coefficient of cancer regions outlined on MRI and the deformed histopathology (0.44 vs 0.48 vs 0.50), and a reduced mean per-case processing time (51 vs 11 vs 4.5 min). The improved performance by RAPHIA allows efficient processing of large datasets for the development of machine learning models for prostate cancer detection on MRI. Our code is publicly available at: https://github.com/pimed/RAPHIA.

Advantage of whole-mount histopathology in prostate cancer: current applications and future prospects

BACKGROUND

Whole-mount histopathology (WMH) has been a powerful tool to investigate the characteristics of prostate cancer. However, the latest advancement of WMH was yet under summarization. In this review, we offer a comprehensive exposition of current research utilizing WMH in diagnosing and treating prostate cancer (PCa), and summarize the clinical advantages of WMH and outlines potential on future prospects.

METHODS

An extensive PubMed search was conducted until February 26, 2023, with the search term "prostate", "whole-mount", "large format histology", which was limited to the last 4 years. Publications included were restricted to those in English. Other papers were also cited to contribute a better understanding.

RESULTS

WMH exhibits an enhanced legibility for pathologists, which improved the efficacy of pathologic examination and provide educational value. It simplifies the histopathological registration with medical images, which serves as a convincing reference standard for imaging indicator investigation and medical image-based artificial intelligence (AI). Additionally, WMH provides comprehensive histopathological information for tumor volume estimation, post-treatment evaluation, and provides direct pathological data for AI readers. It also offers complete spatial context for the location estimation of both intraprostatic and extraprostatic cancerous region.

CONCLUSIONS

WMH provides unique benefits in several aspects of clinical diagnosis and treatment of PCa. The utilization of WMH technique facilitates the development and refinement of various clinical technologies. We believe that WMH will play an important role in future clinical applications.

A comparison of whole-mount and conventional sections for pathological mesorectal extension and circumferential resection margin assessment after total mesorectal excision

INTRODUCTION

The objective of the study is to compare 2 techniques for histological handling of rectal cancer specimens, namely whole-mount in a large block vs conventional sampling using small blocks, for mesorectal pathological assessment of circumferential resection margin status and depth of tumor invasion into the mesorectal fat.

METHODS

This is a prospective study including 27 total mesorectal excision specimens of rectal cancer from patients treated for primary rectal carcinoma between 2020 and 2022 in a specialized multidisciplinary Colorectal Unit. For each total mesorectal excision specimen, 2 contiguous representative tumoral slices were selected and comparatively analyzed with whole-mount and small blocks macroscopic dissection techniques, enabling comparison between them in the same surgical specimen. The agreement between the 2 techniques to assess the distance of the tumor from the circumferential resection margin as well as the depth of tumor invasion was evaluated with the Student's t-test for paired samples, Pearson's correlation coefficient, and the Bland-Altman method comparison analysis.

RESULTS

Complete mesorectal excision was observed in 8% of cases. Circumferential resection margin involvement was observed in only one case (4 %). The whole-mount and small block techniques obtained similar results when we assessed the distance to the circumferential resection margin (t-test P = 0.8, r = 0.92) and the depth of mesorectal infiltration (t-test P = 0.6, r = 0.95).

CONCLUSIONS

Both gross dissection techniques (whole-mount vs multiple small cassettes) are equivalent and reliable to assess the distance to circumferential resection margin and the depth of mesorectal infiltration in the mesorectal fat in rectal cancer staging.

Full resolution reconstruction of whole-mount sections from digitized individual tissue fragments

Whole-mount sectioning is a technique in histopathology where a full slice of tissue, such as a transversal cross-section of a prostate specimen, is prepared on a large microscope slide without further sectioning into smaller fragments. Although this technique can offer improved correlation with pre-operative imaging and is paramount for multimodal research, it is not commonly employed due to its technical difficulty, associated cost and cumbersome integration in (digital) pathology workflows. In this work, we present a computational tool named PythoStitcher which reconstructs artificial whole-mount sections from digitized tissue fragments, thereby bringing the benefits of whole-mount sections to pathology labs currently unable to employ this technique. Our proposed algorithm consists of a multi-step approach where it (i) automatically determines how fragments need to be reassembled, (ii) iteratively optimizes the stitch using a genetic algorithm and (iii) efficiently reconstructs the final artificial whole-mount section on full resolution (0.25 µm/pixel). PythoStitcher was validated on a total of 198 cases spanning five datasets with a varying number of tissue fragments originating from different organs from multiple centers. PythoStitcher successfully reconstructed the whole-mount section in 86-100% of cases for a given dataset with a residual registration mismatch of 0.65-2.76 mm on automatically selected landmarks. It is expected that our algorithm can aid pathology labs unable to employ whole-mount sectioning through faster clinical case evaluation and improved radiology-pathology correlation workflows.

SARIFA as a new histopathological biomarker is associated with adverse clinicopathological characteristics, tumor-promoting fatty-acid metabolism, and might predict a metastatic pattern in pT3a prostate cancer

BACKGROUND

Recently, we introduced Stroma-AReactive-Invasion-Front-Areas (SARIFA) as a novel hematoxylin-eosin (H&E)-based histopathologic prognostic biomarker for various gastrointestinal cancers, closely related to lipid metabolism. To date, no studies on SARIFA, which is defined as direct tumor-adipocyte-interaction, beyond the alimentary tract exist. Hence, the objective of our current investigation was to study the significance of SARIFA in pT3a prostate cancer (PCa) and explore its association with lipid metabolism in PCa as lipid metabolism plays a key role in PCa development and progression.

METHODS

To this end, we evaluated SARIFA-status in 301 radical prostatectomy specimens and examined the relationship between SARIFA-status, clinicopathological characteristics, overall survival, and immunohistochemical expression of FABP4 and CD36 (proteins closely involved in fatty-acid metabolism). Additionally, we investigated the correlation between SARIFA and biochemical recurrence-free survival (BRFS) and PSMA-positive recurrences in PET/CT imaging in a patient subgroup. Moreover, a quantitative SARIFA cut-off was established to further understand the underlying tumor biology.

RESULTS

SARIFA positivity occurred in 59.1% (n = 178) of pT3a PCas. Our analysis demonstrated that SARIFA positivity is strongly associated with established high-risk features, such as R1 status, extraprostatic extension, and higher initial PSA values. Additionally, we observed an upregulation of immunohistochemical CD36 expression specifically at SARIFAs (p = 0.00014). Kaplan-Meier analyses revealed a trend toward poorer outcomes, particularly in terms of BRFS (p = 0.1). More extensive tumor-adipocyte interaction, assessed as quantity-dependent SARIFA-status on H&E slides, is also significantly associated with high-risk features, such as lymph node metastasis, and seems to be associated with worse survival outcomes (p = 0.16). Moreover, SARIFA positivity appeared to be linked to more distant lymph node and bone metastasis, although statistical significance was slightly not achieved (both p > 0.05).

CONCLUSIONS

This is the first study to introduce SARIFA as easy-and-fast-to-assess H&E-based biomarker in locally advanced PCa. SARIFA as the histopathologic correlate of a distinct tumor biology, closely related to lipid metabolism, could pave the way to a more detailed patient stratification and to the development of novel drugs targeting lipid metabolism in pT3a PCa. On the basis of this biomarker discovery study, further research efforts on the prognostic and predictive role of SARIFA in PCa can be designed.

Combination of DNA methylation biomarkers with multiparametric magnetic resonance and ultrasound imaging fusion biopsy to detect the local spread of prostate cancer

BACKGROUND

This study aimed to investigate the extent of field cancerization adjacent to index lesions in prostate cancer (PCa) by measuring DNA methylation of selected tumor suppressor genes in the perifocal tissue of PCa not visible on multiparametric magnetic resonanse imaging (mpMRI) for the safe zone of focal therapy identification.

METHODS

A total of 272 patients were enrolled in this study, 44 patients' tissue biosamples were included in the field cancerization research, and 272 urine samples were included in the urine-based test development. Targeted biopsies were performed using the mpMRI/ultrasoundimage fusion system.

RESULTS

Quantitative analysis revealed significantly higher DNA methylation levels of RARB, RASSF1, GSTP1 & APC genes in the index lesion compared with perifocal tissue samples 10 mm away from it (p < 0.0001). Notably, the RARB, GSTP1 & APC and RARB, RASSF1, GSTP1 & APC biomarker combinations exhibited the highest sensitivity and specificity comparing the extent of DNA methylation in index lesions and noncancerous prostate tissues 20 mm away (both area under the curve [AUC] = 0.98; p < 0.0001). The analysis of the potential urinary biomarkers showed that the combination of all four DNA methylation biomarkers with prostate-specific antigen (PSA) or PSA density (PSAD) in the blood significantly improves the detection of clinically significant PCa (csPCa). The combination of the four-biomarker test with PSAD allowed the identification of csPCa with ≥90% sensitivity and specificity.

CONCLUSION

Thus, this study suggests that for focal therapy by region target hemi-ablation, the safe distance from the index lesion is no less than 10 mm. Noninvasive urine DNA methylation tests in combination with PSAD could be used for further follow-up of the patients, but larger prospective studies with external validation are needed.

Histopathology of Prostate Cancer and its Precursors

Starting in the mid-1970s, we formed a group of pathologists with a major interest in uropathology. Originally, it included 2 (R.M. and M.S.). In the years the followed, the group was enlarged to include 4 more people, 2 in the mid- and late-1980s (A.L.B. and L.C.) and another in the mid-1990s (R.Ma.); a sixth (A.C.) joined the group ∼5 years ago. Two have reached the retirement age (R.M. and M.S.), while others are in the process of joining the group to replace them. A fruitful collaboration spanned for ∼45 years. This contribution is based on a series of personal recollections of the successive changes in the interpretation of prostate cancer and its precursors, starting in the mid-1970s. Here we have retraced our involvement steps, sharing issues related to them with a junior uropathologist (A.C.).

The pathway of isolated seminal vesicle invasion has a different impact on biochemical recurrence after radical prostatectomy and pelvic lymphadenectomy

OBJECTIVE

Prostate cancer with seminal vesicle invasion (SVI) has been considered an aggressive cancer. To evaluate the prognostic significance of different patterns of isolated SVI in patients undergoing radical prostatectomy (RP) and pelvic lymphadenectomy.

METHODS AND MATERIALS

We retrospectively analyzed all patients who underwent RP between 2007 and 2019. Inclusion criteria were localized prostate adenocarcinoma, SVI at RP, at least 24-months follow-up, and no adjuvant treatment. Patterns of SVI were following Ohori's classification: type 1: direct spread along the ejaculatory duct from inside; type 2: seminal vesicle invasion outside the prostate, through the capsule; type 3: the presence of cancer island(s) in the seminal vesicle with no continuity from the primary tumor (discontinuous metastases). Patients with type 3 SVI (isolated or in association) were included in the same group. Biochemical recurrence (BCR) was defined as any postoperative PSA ≥0.2 ng/ml. A logistic regression analysis was performed to assess predictors of BCR. Time to BCR was investigated using the Kaplan-Meier analysis with the log-rank test.

RESULTS

Sixty-one out of 1,356 patients were included. Median age was 67(7.2) years. Median PSA was 9.4(8.92) ng/ml. Mean follow-up was 85.28 ± 45.27 months. BCR occurred in 28(45.9%) patients. Logistic regression showed that a positive surgical margin (OR 19.964, 95%CI:1.172-29.322, P = 0.038) was predictor of BCR. Kaplan-Meier analysis demonstrated that patients with pattern 3 had a significantly shorter time to BCR compared to other groups (log-rank, P = 0.016). The estimated time to BCR was 48.7 months in type 3, 60.9 months in pattern 1 + 2, 74.8, and 100.8 months in isolated patterns 1 and 2, respectively. In patients with negative surgical margins, pattern 3 confirmed a shorter time to BCR compared to other types of invasions, with an estimated time to BCR of 30.8 months.

CONCLUSIONS

Patients with type 3 SVI demonstrated a shorter time to BCR compared to other patterns.

Characteristic of Perineural Invasion in Hilar Cholangiocarcinoma Based on Whole-Mount Histologic Large Sections of Liver

Background & Objective

Perineural invasion is an important biological feature of hilar cholangiocarcinoma (HCCA). We developed a whole-mount histologic large sections (WHLS) of the liver to evaluate peripheral nerve invasion (PNI) of HCCA.

Methods

Using sampling, fixation, dehydration, embedding, sectioning, hematoxylin and eosin (H&E) and immunohistochemical (IHC) staining, and scanning, the characteristics of intrahepatic and extrahepatic PNI in 20 patients with Bismuth type III and type IV HCCA were analyzed with WHLS. Correlation between the characteristics of nerve invasion and tumor size, vascular invasion (artery, portal vein), degree of differentiation, microvascular invasion (MVI), carbohydrate antigen19-9 (CA19-9), and differentiation degree of HCCA was statistically evaluated.

Results

The WHLS of the liver was successfully established, which enabled us to observe intrahepatic and extrahepatic distribution of HCCA and whether surrounding tissues including nervous, blood, and lymph vessels were infiltrated. Extrahepatic and intrahepatic PNI were identified in 20 (100%) patients and 1 (5.0%) patient, respectively. Vessel density decreased in most invaded nerves presented by CD-34, which correlated with 100% of poorly differentiated and 83% of moderately differentiated tumors (P<0.008).

Conclusion

This study established a WHLS of the liver that can be used for clinical diagnosis and research, and confirmed that extrahepatic PNI is prevalent, but intrahepatic nerve invasion is rare and does not accompany the invasion scope of bile ducts in types III and IV HCCA. In addition, moderately and poorly differentiated malignant tumors are more prone to PNI, independent of blood supply.

MRI Texture Features are Associated with Vestibular Schwannoma Histology

OBJECTIVES/HYPOTHESIS

To determine if commonly used radiomics features have an association with histological findings in vestibular schwannomas (VS).

STUDY DESIGN

Retrospective case-series.

METHODS

Patients were selected from an internal database of those who had a gadolinium-enhanced T1-weighted MRI scan captured prior to surgical resection of VS. Texture features from the presurgical magnetic resonance image (MRI) were extracted, and pathologists examined the resected tumors to assess for the presence of mucin, lymphocytes, necrosis, and hemosiderin and used a validated computational tool to determine cellularity. Sensitivity, specificity, and positive likelihood ratios were also computed for selected features using the Youden index to determine the optimal cut-off value.

RESULTS

A total of 45 patients were included. We found significant associations between multiple MRI texture features and the presence of mucin, lymphocytes, hemosiderin, and cellularity. No significant associations between MRI texture features and necrosis were identified. We were able to identify significant positive likelihood ratios using Youden index cut-off values for mucin (2.3; 95% CI 1.2-4.3), hemosiderin (1.5; 95% CI 1.04-2.1), lymphocytes (3.8; 95% CI 1.2-11.7), and necrosis (1.5; 95% CI 1.1-2.2).

CONCLUSIONS

MRI texture features are associated with underlying histology in VS.

LEVEL OF EVIDENCE

3 Laryngoscope, 131:E2000-E2006, 2021.