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Eminaga O, Lee TJ, La V, Breil B, Xing L, Liao JC. Electronic Documentation of Intraoperative Observation of Cystoscopic Procedures Using the cMDX Information System. JCO Clin Cancer Inform 2024; 8:e2300114. [PMID: 38484216 PMCID: PMC10954066 DOI: 10.1200/cci.23.00114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 12/02/2023] [Accepted: 01/31/2024] [Indexed: 03/19/2024] Open
Abstract
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.
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Affiliation(s)
| | - Timothy Jiyong Lee
- Department of Urology, Stanford University School of Medicine, Stanford, CA
| | - Vinh La
- Department of Urology, Stanford University School of Medicine, Stanford, CA
| | - Bernhard Breil
- Faculty of Health Care, Health Informatics, Hochschule Niederrhein, University of Applied Sciences, Krefeld, Germany
| | - Lei Xing
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - Joseph C. Liao
- Department of Urology, Stanford University School of Medicine, Stanford, CA
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Han W, Johnson C, Warner A, Gaed M, Gomez JA, Moussa M, Chin J, Pautler S, Bauman G, Ward AD. Automatic cancer detection on digital histopathology images of mid-gland radical prostatectomy specimens. J Med Imaging (Bellingham) 2020; 7:047501. [PMID: 32715024 DOI: 10.1117/1.jmi.7.4.047501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Accepted: 07/06/2020] [Indexed: 11/14/2022] Open
Abstract
Purpose: Automatic cancer detection on radical prostatectomy (RP) sections facilitates graphical and quantitative surgical pathology reporting, which can potentially benefit postsurgery follow-up care and treatment planning. It can also support imaging validation studies using a histologic reference standard and pathology research studies. This problem is challenging due to the large sizes of digital histopathology whole-mount whole-slide images (WSIs) of RP sections and staining variability across different WSIs. Approach: We proposed a calibration-free adaptive thresholding algorithm, which compensates for staining variability and yields consistent tissue component maps (TCMs) of the nuclei, lumina, and other tissues. We used and compared three machine learning methods for classifying each cancer versus noncancer region of interest (ROI) throughout each WSI: (1) conventional machine learning methods and 14 texture features extracted from TCMs, (2) transfer learning with pretrained AlexNet fine-tuned by TCM ROIs, and (3) transfer learning with pretrained AlexNet fine-tuned with raw image ROIs. Results: The three methods yielded areas under the receiver operating characteristic curve of 0.96, 0.98, and 0.98, respectively, in leave-one-patient-out cross validation using 1.3 million ROIs from 286 mid-gland whole-mount WSIs from 68 patients. Conclusion: Transfer learning with the use of TCMs demonstrated state-of-the-art overall performance and is more stable with respect to sample size across different tissue types. For the tissue types involving Gleason 5 (most aggressive) cancer, it achieved the best performance compared to the other tested methods. This tool can be translated to clinical workflow to assist graphical and quantitative pathology reporting for surgical specimens upon further multicenter validation.
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Affiliation(s)
- Wenchao Han
- Baines Imaging Research Laboratory, London Regional Cancer Program, London, Canada.,Lawson Health Research Institute, London, Ontario, Canada.,Western University, Department of Medical Biophysics, London, Ontario, Canada
| | - Carol Johnson
- Baines Imaging Research Laboratory, London Regional Cancer Program, London, Canada
| | - Andrew Warner
- Baines Imaging Research Laboratory, London Regional Cancer Program, London, Canada
| | - Mena Gaed
- Western University, Department of Pathology and Laboratory Medicine, London, Ontario, Canada
| | - Jose A Gomez
- Western University, Department of Pathology and Laboratory Medicine, London, Ontario, Canada
| | - Madeleine Moussa
- Western University, Department of Pathology and Laboratory Medicine, London, Ontario, Canada
| | - Joseph Chin
- Western University, Department of Oncology, London, Ontario, Canada.,Western University, Department of Surgery, London, Ontario, Canada
| | - Stephen Pautler
- Western University, Department of Oncology, London, Ontario, Canada.,Western University, Department of Surgery, London, Ontario, Canada
| | - Glenn Bauman
- Lawson Health Research Institute, London, Ontario, Canada.,Western University, Department of Medical Biophysics, London, Ontario, Canada.,Western University, Department of Oncology, London, Ontario, Canada
| | - Aaron D Ward
- Baines Imaging Research Laboratory, London Regional Cancer Program, London, Canada.,Lawson Health Research Institute, London, Ontario, Canada.,Western University, Department of Medical Biophysics, London, Ontario, Canada.,Western University, Department of Oncology, London, Ontario, Canada
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Eminaga O, Al-Hamad O, Boegemann M, Breil B, Semjonow A. Combination possibility and deep learning model as clinical decision-aided approach for prostate cancer. Health Informatics J 2019; 26:945-962. [PMID: 31238766 DOI: 10.1177/1460458219855884] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
This study aims to introduce as proof of concept a combination model for classification of prostate cancer using deep learning approaches. We utilized patients with prostate cancer who underwent surgical treatment representing the various conditions of disease progression. All possible combinations of significant variables from logistic regression and correlation analyses were determined from study data sets. The combination possibility and deep learning model was developed to predict these combinations that represented clinically meaningful patient's subgroups. The observed relative frequencies of different tumor stages and Gleason score Gls changes from biopsy to prostatectomy were available for each group. Deep learning models and seven machine learning approaches were compared for the classification performance of Gleason score changes and pT2 stage. Deep models achieved the highest F1 scores by pT2 tumors (0.849) and Gls change (0.574). Combination possibility and deep learning model is a useful decision-aided tool for prostate cancer and to group patients with prostate cancer into clinically meaningful groups.
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Affiliation(s)
- Okyaz Eminaga
- Stanford University School of Medicine, USA; University Hospital of Cologne, Germany
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4
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Eminaga O, Semjonow A, Eltze E, Bettendorf O, Schultheis A, Warnecke-Eberz U, Akbarov I, Wille S, Engelmann U. Analysis of topographical distribution of prostate cancer and related pathological findings in prostatectomy specimens using cMDX document architecture. J Biomed Inform 2015; 59:240-7. [PMID: 26707451 DOI: 10.1016/j.jbi.2015.12.009] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2015] [Revised: 12/10/2015] [Accepted: 12/13/2015] [Indexed: 11/25/2022]
Abstract
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.
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Affiliation(s)
- Okyaz Eminaga
- Dept. of Urology, University Hospital of Cologne, Kerpener Straße 62, D-50937 Cologne, Germany.
| | - Axel Semjonow
- Prostate Center, Dept. of Urology, University Hospital Muenster, Albert-Schweitzer-Campus 1, D-48149 Muenster, Germany
| | - Elke Eltze
- Institute for Pathology Saarbrücken-Rastpfuhl, Rheinstrasse 2, D-66113 Saarbrücken, Germany
| | - Olaf Bettendorf
- Institute of Pathology and Cytology, Technikerstrasse 14, D-48465 Schüttorf, Germany
| | - Anne Schultheis
- Institute for Pathology, University Hospital of Cologne, Kerpener Straße 62, D-50937 Cologne, Germany
| | - Ute Warnecke-Eberz
- Department for Visceral Surgery, University Hospital Cologne, Kerpener Straße 62, D-50937 Cologne, Germany
| | - Ilgar Akbarov
- Dept. of Urology, University Hospital of Cologne, Kerpener Straße 62, D-50937 Cologne, Germany
| | - Sebastian Wille
- Dept. of Urology, University Hospital of Cologne, Kerpener Straße 62, D-50937 Cologne, Germany
| | - Udo Engelmann
- Dept. of Urology, University Hospital of Cologne, Kerpener Straße 62, D-50937 Cologne, Germany
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Castaneda C, Nalley K, Mannion C, Bhattacharyya P, Blake P, Pecora A, Goy A, Suh KS. Clinical decision support systems for improving diagnostic accuracy and achieving precision medicine. J Clin Bioinforma 2015; 5:4. [PMID: 25834725 PMCID: PMC4381462 DOI: 10.1186/s13336-015-0019-3] [Citation(s) in RCA: 123] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2014] [Accepted: 02/27/2015] [Indexed: 01/08/2023] Open
Abstract
As research laboratories and clinics collaborate to achieve precision medicine, both communities are required to understand mandated electronic health/medical record (EHR/EMR) initiatives that will be fully implemented in all clinics in the United States by 2015. Stakeholders will need to evaluate current record keeping practices and optimize and standardize methodologies to capture nearly all information in digital format. Collaborative efforts from academic and industry sectors are crucial to achieving higher efficacy in patient care while minimizing costs. Currently existing digitized data and information are present in multiple formats and are largely unstructured. In the absence of a universally accepted management system, departments and institutions continue to generate silos of information. As a result, invaluable and newly discovered knowledge is difficult to access. To accelerate biomedical research and reduce healthcare costs, clinical and bioinformatics systems must employ common data elements to create structured annotation forms enabling laboratories and clinics to capture sharable data in real time. Conversion of these datasets to knowable information should be a routine institutionalized process. New scientific knowledge and clinical discoveries can be shared via integrated knowledge environments defined by flexible data models and extensive use of standards, ontologies, vocabularies, and thesauri. In the clinical setting, aggregated knowledge must be displayed in user-friendly formats so that physicians, non-technical laboratory personnel, nurses, data/research coordinators, and end-users can enter data, access information, and understand the output. The effort to connect astronomical numbers of data points, including ‘-omics’-based molecular data, individual genome sequences, experimental data, patient clinical phenotypes, and follow-up data is a monumental task. Roadblocks to this vision of integration and interoperability include ethical, legal, and logistical concerns. Ensuring data security and protection of patient rights while simultaneously facilitating standardization is paramount to maintaining public support. The capabilities of supercomputing need to be applied strategically. A standardized, methodological implementation must be applied to developed artificial intelligence systems with the ability to integrate data and information into clinically relevant knowledge. Ultimately, the integration of bioinformatics and clinical data in a clinical decision support system promises precision medicine and cost effective and personalized patient care.
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Affiliation(s)
- Christian Castaneda
- Genomics and Biomarkers Program, Hackensack University Medical Center, Hackensack, NJ 07601 USA
| | - Kip Nalley
- Sophic Alliance, 2275 Research Blvd., Suite 500, Rockville, MD 20850 USA
| | - Ciaran Mannion
- Department of Pathology, Hackensack University Medical Center, Hackensack, NJ 07601 USA
| | - Pritish Bhattacharyya
- Department of Pathology, Hackensack University Medical Center, Hackensack, NJ 07601 USA
| | - Patrick Blake
- Sophic Alliance, 2275 Research Blvd., Suite 500, Rockville, MD 20850 USA
| | - Andrew Pecora
- John Theurer Cancer Center, Hackensack University Medical Center, D. Jurist Research Building, 40 Prospect Avenue, Hackensack, NJ 07601 USA
| | - Andre Goy
- John Theurer Cancer Center, Hackensack University Medical Center, D. Jurist Research Building, 40 Prospect Avenue, Hackensack, NJ 07601 USA
| | - K Stephen Suh
- Genomics and Biomarkers Program, Hackensack University Medical Center, Hackensack, NJ 07601 USA ; John Theurer Cancer Center, Hackensack University Medical Center, D. Jurist Research Building, 40 Prospect Avenue, Hackensack, NJ 07601 USA
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Ibeawuchi C, Schmidt H, Voss R, Titze U, Abbas M, Neumann J, Eltze E, Hoogland AM, Jenster G, Brandt B, Semjonow A. Exploring prostate cancer genome reveals simultaneous losses of PTEN, FAS and PAPSS2 in patients with PSA recurrence after radical prostatectomy. Int J Mol Sci 2015; 16:3856-69. [PMID: 25679447 PMCID: PMC4346930 DOI: 10.3390/ijms16023856] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2014] [Accepted: 02/05/2015] [Indexed: 01/03/2023] Open
Abstract
The multifocal nature of prostate cancer (PCa) creates a challenge to patients' outcome prediction and their clinical management. An approach that scrutinizes every cancer focus is needed in order to generate a comprehensive evaluation of the disease, and by correlating to patients' clinico-pathological information, specific prognostic biomarker can be identified. Our study utilized the Affymetrix SNP 6.0 Genome-wide assay to investigate forty-three fresh frozen PCa tissue foci from twenty-three patients. With a long clinical follow-up period that ranged from 2.0-9.7 (mean 5.4) years, copy number variation (CNV) data was evaluated for association with patients' PSA status during follow-up. From our results, the loss of unique genes on 10q23.31 and 10q23.2-10q23.31 were identified to be significantly associated to PSA recurrence (p < 0.05). The implication of PTEN and FAS loss (10q23.31) support previous reports due to their critical roles in prostate carcinogenesis. Furthermore, we hypothesize that the PAPSS2 gene (10q23.2-10q23.31) may be functionally relevant in post-operative PSA recurrence because of its reported role in androgen biosynthesis. It is suggestive that the loss of the susceptible region on chromosome 10q, which implicates PTEN, FAS and PAPSS2 may serve as genetic predictors of PSA recurrence after radical prostatectomy.
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Affiliation(s)
- Chinyere Ibeawuchi
- Prostate Center, Department of Urology, University Hospital Muenster, Albert-Schweitzer-Campus 1, Gebaeude 1A, Muenster D-48149, Germany.
| | - Hartmut Schmidt
- Center for Laboratory Medicine, University Hospital Muenster, Albert-Schweitzer-Campus 1, Gebaeude 1A, Muenster D-48149, Germany.
| | - Reinhard Voss
- Interdisciplinary Center for Clinical Research, University of Muenster, Albert-Schweitzer-Campus 1, Gebaeude D3, Domagkstrasse 3, Muenster D-48149, Germany.
| | - Ulf Titze
- Pathology, Lippe Hospital Detmold, Röntgenstrasse 18, Detmold D-32756, Germany.
| | - Mahmoud Abbas
- Institute of Pathology, Mathias-Spital-Rheine, Frankenburg Street 31, Rheine D-48431, Germany.
| | - Joerg Neumann
- Institute of Pathology, Klinikum Osnabrueck, Am Finkenhuegel 1, Osnabrueck D-49076, Germany.
| | - Elke Eltze
- Institute of Pathology, Saarbrücken-Rastpfuhl, Rheinstrasse 2, Saarbrücken D-66113, Germany.
| | - Agnes Marije Hoogland
- Department of Pathology, Erasmus Medical Center, 's-Gravendijkwal 230, 3015-CE Rotterdam, The Netherlands.
| | - Guido Jenster
- Department of Urology, Erasmus Medical Center, 's-Gravendijkwal 230, 3015-CE Rotterdam, The Netherlands.
| | - Burkhard Brandt
- Institute for Clinical Chemistry, University Clinic Schleswig-Holsteins, Arnold-Heller-Strasse 3, Haus 17, Kiel D-24105, Germany.
| | - Axel Semjonow
- Prostate Center, Department of Urology, University Hospital Muenster, Albert-Schweitzer-Campus 1, Gebaeude 1A, Muenster D-48149, Germany.
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Bruland P, Forster C, Breil B, Ständer S, Dugas M, Fritz F. Does single-source create an added value? Evaluating the impact of introducing x4T into the clinical routine on workflow modifications, data quality and cost-benefit. Int J Med Inform 2014; 83:915-28. [PMID: 25220487 DOI: 10.1016/j.ijmedinf.2014.08.007] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2013] [Revised: 03/14/2014] [Accepted: 08/21/2014] [Indexed: 01/03/2023]
Abstract
OBJECTIVES The first objective of this study is to evaluate the impact of integrating a single-source system into the routine patient care documentation workflow with respect to process modifications, data quality and execution times in patient care as well as research documentation. The second one is to evaluate whether it is cost-efficient using a single-source system in terms of achieved savings in documentation expenditures. METHODS We analyzed the documentation workflow of routine patient care and research documentation in the medical field of pruritus to identify redundant and error-prone process steps. Based on this, we established a novel documentation workflow including the x4T (exchange for Trials) system to connect hospital information systems with electronic data capture systems for the exchange of study data. To evaluate the workflow modifications, we performed a before/after analysis as well as a time-motion study. Data quality was assessed by measuring completeness, correctness and concordance of previously and newly collected data. A cost-benefit analysis was conducted to estimate the savings using x4T per collected data element and the additional costs for introducing x4T. RESULTS The documentation workflow of patient care as well as clinical research was modified due to the introduction of the x4T system. After x4T implementation and workflow modifications, half of the redundant and error-prone process steps were eliminated. The generic x4T system allows direct transfer of routinely collected health care data into the x4T research database and avoids manual transcription steps. Since x4T has been introduced in March 2012, the number of included patients has increased by about 1000 per year. The average entire documentation time per patient visit has been significantly decreased by 70.1% (from 1116±185 to 334±83 s). After the introduction of the x4T system and associated workflow changes, the completeness of mandatory data elements raised from 82.2% to 100%. In case of the pruritus research study, the additional costs for introducing the x4T system are €434.01 and the savings are 0.48ct per collected data element. So, with the assumption of a 5-year runtime and 82 collected data elements per patient, the amount of documented patients has to be higher than 1102 to create a benefit. CONCLUSION Introduction of the x4T system into the clinical and research documentation workflow can optimize the data collection workflow in both areas. Redundant and cumbersome process steps can be eliminated in the research documentation, with the result of reduced documentation times as well as increased data quality. The usage of the x4T system is especially worthwhile in a study with a large amount of collected data or a high number of included patients.
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Affiliation(s)
- Philipp Bruland
- Institute of Medical Informatics, University of Münster, Germany.
| | | | - Bernhard Breil
- Faculty of Health Care, University of Applied Sciences, Krefeld, Germany
| | - Sonja Ständer
- Competence Center Chronic Pruritus, Department of Dermatology, University of Münster, Germany
| | - Martin Dugas
- Institute of Medical Informatics, University of Münster, Germany
| | - Fleur Fritz
- Institute of Medical Informatics, University of Münster, Germany
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Linkage of Data from Diverse Data Sources (LDS): A Data Combination Model Provides Clinical Data of Corresponding Specimens in Biobanking Information System. J Med Syst 2013; 37:9975. [DOI: 10.1007/s10916-013-9975-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2013] [Accepted: 08/29/2013] [Indexed: 11/26/2022]
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Eminaga O, Hinkelammert R, Abbas M, Titze U, Eltze E, Bettendorf O, Semjonow A. High-grade prostatic intraepithelial neoplasia (HGPIN) and topographical distribution in 1,374 prostatectomy specimens: existence of HGPIN near prostate cancer. Prostate 2013; 73:1115-22. [PMID: 23532797 DOI: 10.1002/pros.22660] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2012] [Accepted: 02/13/2013] [Indexed: 11/09/2022]
Abstract
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.
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Affiliation(s)
- Okyaz Eminaga
- Department of Urology, University Hospital of Cologne, Cologne, Germany.
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