Clinical map document based on XML (cMDX): document architecture with mapping feature for reporting and analysing prostate cancer in radical prostatectomy specimens

Critical evaluation of artificial intelligence as a digital twin of pathologists for prostate cancer pathology

Prostate cancer pathology plays a crucial role in clinical management but is time-consuming. Artificial intelligence (AI) shows promise in detecting prostate cancer and grading patterns. We tested an AI-based digital twin of a pathologist, vPatho, on 2603 histological images of prostate tissue stained with hematoxylin and eosin. We analyzed various factors influencing tumor grade discordance between the vPatho system and six human pathologists. Our results demonstrated that vPatho achieved comparable performance in prostate cancer detection and tumor volume estimation, as reported in the literature. The concordance levels between vPatho and human pathologists were examined. Notably, moderate to substantial agreement was observed in identifying complementary histological features such as ductal, cribriform, nerve, blood vessel, and lymphocyte infiltration. However, concordance in tumor grading decreased when applied to prostatectomy specimens (κ = 0.44) compared to biopsy cores (κ = 0.70). Adjusting the decision threshold for the secondary Gleason pattern from 5 to 10% improved the concordance level between pathologists and vPatho for tumor grading on prostatectomy specimens (κ from 0.44 to 0.64). Potential causes of grade discordance included the vertical extent of tumors toward the prostate boundary and the proportions of slides with prostate cancer. Gleason pattern 4 was particularly associated with this population. Notably, the grade according to vPatho was not specific to any of the six pathologists involved in routine clinical grading. In conclusion, our study highlights the potential utility of AI in developing a digital twin for a pathologist. This approach can help uncover limitations in AI adoption and the practical application of the current grading system for prostate cancer pathology.

Electronic Documentation of Intraoperative Observation of Cystoscopic Procedures Using the cMDX Information System

PURPOSE

Accurate documentation of lesions during transurethral resection of bladder tumors (TURBT) is essential for precise diagnosis, treatment planning, and follow-up care. However, optimizing schematic documentation techniques for bladder lesions has received limited attention.

MATERIALS AND METHODS

This prospective observational study used a cMDX-based documentation system that facilitates graphical representation, a lesion-specific questionnaire, and heatmap analysis with a posterization effect. We designed a graphical scheme for bladder covering bladder landmarks to visualize anatomic features and to document the lesion location. The lesion-specific questionnaire was integrated for comprehensive lesion characterization. Finally, spatial analyses were applied to investigate the anatomic distribution patterns of bladder lesions.

RESULTS

A total of 97 TURBT cases conducted between 2021 and 2023 were included, identifying 176 lesions. The lesions were distributed in different bladder areas with varying frequencies. The distribution pattern, sorted by frequency, was observed in the following areas: posterior, trigone, lateral right and anterior, and lateral left and dome. Suspicious levels were assigned to the lesions, mostly categorized either as indeterminate or moderate. Lesion size analysis revealed that most lesions fell between 5 and 29 mm.

CONCLUSION

The study highlights the potential of schematic documentation techniques for informed decision making, quality assessment, primary research, and secondary data utilization of intraoperative data in the context of TURBT. Integrating cMDX and heatmap analysis provides valuable insights into lesion distribution and characteristics.

Ex Vivo Fluorescence Confocal Microscopy (FCM) Ensures Representative Tissue in Prostate Cancer Biobanking: A Feasibility Study

Background: Biobanking of prostate carcinoma is particularly challenging due to the actual cancer within the organ often without clear margins. Frozen sections are to date the only way to examine the biobank material for its tumor content. We used ex vivo fluorescence confocal microscopy (FCM) to analyze biobank samples prior to cryoasservation. Methods: 127 punch biopsies were acquired from prostatectomy-specimens from 40 patients. These biopsies were analyzed with a Vivascope 2500-G4 prior to their transfer to the biobank. In difficult cases, larger samples of the prostatectomy specimens were FCM scanned in order to locate tumor foci. After patient acquisition, all samples were taken from the biobank and analyzed. We compared the results of the FCM examinations with the results of conventional histology and measured the DNA content. Results: With upstream FCM, the tumor content of biobank samples could be determined with high confidence. The detection rate of representative biobank samples was increased due to the rapid feedback. The biobank samples were suitable for further molecular analysis. Conclusion: FCM allows for the first time lossless microscopic analysis of biobank samples prior to their cryoasservation and guarantees representative tumor and normal tissue for further molecular analysis.

Specific spatial distribution patterns of tumor foci are associated with a low risk of biochemical recurrence in pT2pN0R0 prostate cancer

BACKGROUND

The previous attempts for pT2 substaging of prostate cancer (PCa) were insufficient in providing prognostic subgroups and the search for new prognostic parameters to subcategorize pT2 PCa is, therefore, needed. Therefore, the current study investigated the association between tumor distribution patterns and the biochemical recurrence (BCR)-free survival rate in pT2pN0R0 PCa.

METHODS

Following radical prostatectomy, the anatomical distribution of PCa in 743 men with pT1-pT3pN0 disease was analyzed to determine 20 types of PCa distribution patterns. Then, 245 men with pT2pN0R0 PCa was considered for prognostic evaluation with a mean follow-up period of 60 months. The spatial distribution patterns of PCa were evaluated using a cMDX^©-based map model of the prostate. An analysis including 552,049 comparison operations was performed to assist in the evaluation of the similarity levels of the distribution patterns. A k-mean cluster analysis was applied to determine groups with similar distribution patterns. A decision-tree analysis was performed to divide these groups according to frequency of BCR. The BCR-free survival rate was analyzed using Kaplan-Meier curves. Predictors of progression were investigated using a Cox proportional hazards model.

RESULTS

BCR occurred in 8.2% of the 245 men with pT2pN0R0 PCa. The median time of recurrence was 60 months (interquartile range [IQR]: 42-77). In univariate and multivariate analyses, the prostate volume and the distribution patterns were independent predictors for BCR, whereas the sub-staging of pT2 tumors, Gleason grading, prostate-specific antigen (PSA) level, and relative tumor volume were not. In the patients with pT2pN0R0 disease, PCa distribution patterns with the apical involvement were significantly associated with the risk of BCR (P = 0.001).

CONCLUSION

The spread tumor patterns with the apical involvement are associated with a high-risk of BCR in the pT2 tumor stage. The vertical tumor spread could be considered in developing improved prognostic pT2 sub-categories.

Blind Biobanking of the Prostatectomy Specimen: Critical Evaluation of the Existing Techniques and Development of the New 4-Level Tissue Extraction Model With High Sampling Efficacy

BACKGROUND

Fresh tissue is mandatory to perform high-quality translation studies. Several models for tissue extraction from prostatectomy specimens without guidance by frozen sections are already introduced. However, little is known about the sampling efficacy of these models, which should provide representative tissue in adequate volumes, account for multifocality and heterogeneity of tumor, not violate the routine final pathological examination, and perform quickly without frozen section-based histological control. The aim of the study was to evaluate the sampling efficacy of the existing tissue extraction models without guidance by frozen sections ("blind") and to develop an optimized model for tissue extraction.

METHODS

Five hundred thirty-three electronic maps of the tumor distribution in prostates from a single-center cohort of the patients subjected to radical prostatectomy were used for analysis. Six available models were evaluated in silico for their sampling efficacy. Additionally, a novel model achieving the best sampling efficacy was developed.

RESULTS

The available models showed high efficacies for sampling "any part" from the tumor (up to 100%), but were uniformly low in efficacy to sample all tumor foci from the specimens (with the best technique sampling only 51.6% of the all tumor foci). The novel 4-level extraction model achieved a sampling efficacy of 93.1% for all tumor foci.

CONCLUSIONS

The existing "blind" tissue extraction models from prostatectomy specimens without frozen sections control are suitable to target tumor tissues but these tissues do not represent the whole tumor. The novel 4-level model provides the highest sampling efficacy and a promising potential for integration into routine. Prostate 77: 396-405, 2017. © 2016 Wiley Periodicals, Inc.

Analysis of topographical distribution of prostate cancer and related pathological findings in prostatectomy specimens using cMDX document architecture

INTRODUCTION

Understanding the topographical distribution of prostate cancer (PCa) foci is necessary to optimize the biopsy strategy. This study was done to develop a technical approach that facilitates the analysis of the topographical distribution of PCa foci and related pathological findings (i.e., Gleason score and foci dimensions) in prostatectomy specimens.

MATERIAL & METHODS

The topographical distribution of PCa foci and related pathologic evaluations were documented using the cMDX documentation system. The project was performed in three steps. First, we analyzed the document architecture of cMDX, including textual and graphical information. Second, we developed a data model supporting the topographic analysis of PCa foci and related pathologic parameters. Finally, we retrospectively evaluated the analysis model in 168 consecutive prostatectomy specimens of men diagnosed with PCa who underwent total prostate removal. The distribution of PCa foci were analyzed and visualized in a heat map. The color depth of the heat map was reduced to 6 colors representing the PCa foci frequencies, using an image posterization effect. We randomly defined 9 regions in which the frequency of PCa foci and related pathologic findings were estimated.

RESULTS

Evaluation of the spatial distribution of tumor foci according to Gleason score was enabled by using a filter function for the score, as defined by the user. PCa foci with Gleason score (Gls) 6 were identified in 67.3% of the patients, of which 55 (48.2%) also had PCa foci with Gls between 7 and 10. Of 1173 PCa foci, 557 had Gls 6, whereas 616 PCa foci had Gls>6. PCa foci with Gls 6 were mostly concentrated in the posterior part of the peripheral zone of the prostate, whereas PCa foci with Gls>6 extended toward the basal and anterior parts of the prostate. The mean size of PCa foci with Gls 6 was significantly lower than that of PCa with Gls>6 (P<0.0001).

CONCLUSION

The cMDX-based technical approach facilitates analysis of the topographical distribution of PCa foci and related pathologic findings in prostatectomy specimens.

Preoperative Serum Prostate-Specific Antigen Levels Vary According to the Topographical Distribution of Prostate Cancer in Prostatectomy Specimens

OBJECTIVE

To evaluate whether the spatial distribution of prostate cancer (PCa) influences the concentration of prostate-specific antigen (PSA).

METHODS

An observational prospective study was performed in 775 consecutive men with preoperative PSA levels ≤20 ng/mL who underwent radical prostatectomy for organ-confined PCa. We evaluated prostate specimens using a cMDX-based map model of the prostate and determined the prostate volume, number of cancer foci, relative tumor volume, Gleason score, zone of origin, localization, and pathologic stage after stratification according to PSA levels categorized into 3 groups: <4 ng/mL, 4-10 ng/mL, and 10.1-20 ng/mL. The distribution of 5254 PCa foci was analyzed after stratification according to PSA levels and visualized on heat maps. A logistic regression analysis was performed to assess the odds ratios of PSA levels for the presence of PCa in 16 regions.

RESULTS

PCa with PSA <4 ng/mL was predominantly localized to the apical part and the peripheral zone of the prostate. PCa with a PSA level 10.1-20 ng/mL (16.4% of cases) was observed more frequently in the anterior part and the base of the prostate than PCa with a PSA level <4 or 4-10 ng/mL (6% and 10%, respectively).

CONCLUSION

Preoperative PSA levels vary according to the spatial distribution of PCa in radical prostatectomy specimens. The probability of anterior PCa is increased with higher PSA serum levels. Regions of interest harboring the PCa can be defined according to preoperative PSA and prostate volume. These findings are useful to optimize the focal therapy or to adjust the radiation fields.

Preoperative prostate-specific antigen isoform p2PSA ≤ 22.5 pg/ml predicts advanced prostate cancer in patients undergoing radical prostatectomy

BACKGROUND

The prediction value of prostate-specific antigen (PSA) isoform [-2]proPSA (p2PSA) for detecting advanced prostate cancer (PCa) remains unclear. Our objective was to evaluate the additional clinical utility of p2PSA compared with total PSA (tPSA), free PSA (fPSA), and preoperative Gleason score (Gls) in predicting locally advanced PCa (pT3/T4) with high-accuracy discrimination. The aim was to develop a novel classification based on p2PSA and preoperative Gls for predicting advanced PCa.

MATERIALS AND METHODS

In 208 consecutive men diagnosed with clinically localized PCa who underwent radical prostatectomy, we determined the predictive and discriminatory accuracy of serum tPSA, fPSA, percentage of fPSA to tPSA, p2PSA, p2PSA density, percentage of p2PSA to fPSA, and the Prostate Health Index. The cutoff level of p2PSA with best accuracy was estimated. The novel classification was developed by analyzing the interaction between p2PSA and Gls in predicting pathologic outcomes using a chi-square automatic interaction detection analysis. Decision curve analysis was applied to test the clinical consequences of using the novel classification.

RESULTS

On univariate analyses, p2PSA, p2PSA density, percentage of p2PSA to fPSA, and Prostate Health Index were accurate but were not independent predictors by multivariate analysis. The p2PSA cutoff level of 22.5 pg/ml showed the best accuracy level for predicting and discriminating advanced diseases (area under the curve [AUC] = 0.725, sensitivity = 51.4%, specificity = 81.8%). By chi-square automatic interaction detection, univariate and multivariate analysis, a p2PSA level > 22.5 pg/ml was significantly associated with an increased frequency and risk of advanced disease. In patients with a p2PSA level ≤ 22.5 pg/ml, 91.8% of Gleason sum 6 PCa was organ confined. The combination of p2PSA and Gls enhanced slightly but significantly the predictive and discriminatory accuracy for advanced disease (0.6%-3.6%).

CONCLUSIONS

The p2PSA cutoff level of 22.5 pg/ml can accurately discriminate between organ-confined and advanced PCa. The additional use of p2PSA enhanced slightly the predictive accuracy for advanced PCa (pT3/pT4) and has limited additional predictive value in identifying aggressive PCa (Gls > 7a).

Tumor percentage but not number of tumor foci predicts disease-free survival after radical prostatectomy especially in high-risk patients

OBJECTIVE

To evaluate the predictive value of tumor volume (TV), tumor percentage (TP), and number of tumor foci (NF) in patients with prostate cancer. The prognostic relevance of TV, TP, and NF as predictors of biochemical recurrence (BCR) following radical prostatectomy (RPE) is controversial.

PATIENTS AND METHODS

The cohort consisted of 758 referred subjects who underwent RPE between 2000 and 2005 at the University of Muenster. The mean time of follow-up was 62 months. TV, TP, and NF were estimated visually with the assistance of a pathologic mapping grid for embedded whole-mount RPE specimens. In addition, TV and TP were assessed in a categorized fashion by using quartiles as cutoff points. Subgroup analyses for high- and low-risk patients using univariate and multivariate Cox proportional hazard analyses for BCR were performed.

RESULTS

TV, TP, and NF were strongly related to tumor stage, Gleason score, surgical margin status, and preoperative prostate-specific antigen (PSA). In univariate analysis, all pathologic parameters including TV, TP, and NF were predictive for BCR. In multivariate analysis, only TP, tumor stage, and PSA level were independent predictors. In subgroup analysis, TP was an independent predictor for BCR in the high-risk group but not in the low-risk group.

CONCLUSIONS

TP, but not TV or NF, was found to be an independent predictor for BCR in patients after RPE. TP seems to be more relevant in high-risk patients (i.e., any of the following: > pT2, Gleason score > 6, or PSA > 20 ng/ml).

High-grade prostatic intraepithelial neoplasia (HGPIN) and topographical distribution in 1,374 prostatectomy specimens: existence of HGPIN near prostate cancer

PURPOSE

High-grade prostatic intraepithelial neoplasia (HGPIN) is believed to be a precursor of prostate cancer (PCa). This study evaluated whether HGPIN was located close to PCa in whole radical prostatectomy specimens (RPSs).

MATERIALS AND METHODS

We evaluated 1,374 prostate specimens from 1999 to 2010 using a cMDX-based map model of the prostate. The distribution of 10,439 PCa foci was analyzed and visualized on a heat map. The color gradient of the heat map was reduced to six colors representing the frequency classification of the relative frequency of PCa using an image posterization effect. We defined 22 regions in the prostate according to the frequency of PCa occurrence. Seven hundred ninety RPSs containing 6,374 PCa foci and 4,502 HGPIN foci were evaluated. The topographical association between PCa and HGPIN in the RPSs was analyzed by estimating the frequencies of PCa and HGPIN in 22 regions. A logistic regression analysis was performed to assess the odds ratios of HGPIN for the presence of PCa in 22 regions.

RESULTS

Fifty-eight percent of PCa specimens included HGPIN and had significantly more favorable Gleason scores, lower PSA levels and smaller relative tumor volumes than isolated PCa specimens. HGPIN (68%) and PCa (69%) were predominantly localized to the apical half of the prostate. HGPIN was mainly concentrated in the peripheral zone medial to regions with high PCa frequencies. Upon logistic regression analysis, HGPIN was a significant predictor of PCa co-existence in 11 regions.

CONCLUSIONS

HGPIN was located adjacent to PCa in whole RPSs. PCa concomitant with HGPIN had more favorable pathologic features than isolated PCa.

Genome-wide investigation of multifocal and unifocal prostate cancer-are they genetically different?

Prostate cancer is widely observed to be biologically heterogeneous. Its heterogeneity is manifested histologically as multifocal prostate cancer, which is observed more frequently than unifocal prostate cancer. The clinical and prognostic significance of either focal cancer type is not fully established. To investigate prostate cancer heterogeneity, the genetic profiles of multifocal and unifocal prostate cancers were compared. Here, we report observations deduced from tumor-tumor comparison of copy number alteration data of both focal categories. Forty-one fresh frozen prostate cancer foci from 14 multifocal prostate cancers and eight unifocal prostate cancers were subjected to copy number variation analysis with the Affymetrix SNP 6.0 microarray tool. With the investigated cases, tumors obtained from a single prostate exhibited different genetic profiles of variable degrees. Further comparison identified no distinct genetic pattern or signatures specific to multifocal or unifocal prostate cancer. Our findings suggest that samples obtained from multiple sites of a single unifocal prostate cancer show as much genetic heterogeneity and variability as separate tumors obtained from a single multifocal prostate cancer.

CMDX©-based single source information system for simplified quality management and clinical research in prostate cancer

BACKGROUND

Histopathological evaluation of prostatectomy specimens is crucial to decision-making and prediction of patient outcomes in prostate cancer (PCa). Topographical information regarding PCa extension and positive surgical margins (PSM) is essential for clinical routines, quality assessment, and research. However, local hospital information systems (HIS) often do not support the documentation of such information. Therefore, we investigated the feasibility of integrating a cMDX-based pathology report including topographical information into the clinical routine with the aims of obtaining data, performing analysis and generating heat maps in a timely manner, while avoiding data redundancy.

METHODS

We analyzed the workflow of the histopathological evaluation documentation process. We then developed a concept for a pathology report based on a cMDX data model facilitating the topographical documentation of PCa and PSM; the cMDX SSIS is implemented within the HIS of University Hospital Muenster. We then generated a heat map of PCa extension and PSM using the data. Data quality was assessed by measuring the data completeness of reports for all cases, as well as the source-to-database error. We also conducted a prospective study to compare our proposed method with recent retrospective and paper-based studies according to the time required for data analysis.

RESULTS

We identified 30 input fields that were applied to the cMDX-based data model and the electronic report was integrated into the clinical workflow. Between 2010 and 2011, a total of 259 reports were generated with 100% data completeness and a source-to-database error of 10.3 per 10,000 fields. These reports were directly reused for data analysis, and a heat map based on the data was generated. PCa was mostly localized in the peripheral zone of the prostate. The mean relative tumor volume was 16.6%. The most PSM were localized in the apical region of the prostate. In the retrospective study, 1623 paper-based reports were transferred to cMDX reports; this process took 15 ± 2 minutes per report. In a paper-based study, the analysis data preparation required 45 ± 5 minutes per report.

CONCLUSIONS

cMDX SSIS can be integrated into the local HIS and provides clinical routine data and timely heat maps for quality assessment and research purposes.