Comparison of Diffusion Kurtosis Imaging and Standard Mono-Exponential Apparent Diffusion Coefficient in Diagnosis of Signiﬁcant Prostate Cancer - A Correlation with Gleason Score Assessed on Whole-Mount Histopathology Specimens

Sep 24, 2026

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Study compares diffusion kurtosis imaging (DKI) with the standard monoexponential (ME) apparent diffusion coefficient (ADC) model for detecting significant prostate cancer using whole-mount histopathology after radical prostatectomy. A cohort of 155 patients underwent 3T multiparametric MRI before surgery, and diffusion parameters (Dapp, kurtosis K, ADC1200, ADC2000) were correlated with Gleason score and contrasted across malignant versus benign tissue and across GS 3+3 versus GS 3+4 tumors. Although kurtosis fitted DWI data better, ROC-based diagnostic performance was similar in peripheral and combined peripheral–transitional zones.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages17

Reading Time43 min

AccessFree to download

Abstract

Introduction

Prostate cancer context and diagnostic challenge

Role of diffusion-weighted imaging and ADC model

Rationale for diffusion kurtosis imaging

Methods

Results

Discussion

diagnostics Article Comparison of Diffusion Kurtosis Imaging and Standard Mono-Exponential Apparent Diffusion Coefﬁcient in Diagnosis of Signiﬁcant Prostate Cancer—A Correlation with Gleason Score Assessed on Whole-Mount Histopathology Specimens Anna Z˙ urowska 1,*, Rafał P˛eksa 2, Małgorzata Grzywi ´nska 3, Damian Panas 4, Marek Sowa 5, Katarzyna Skrobisz 6, Marcin Matuszewski 5 and Edyta Szurowska 1 Citation: Z˙ urowska, A.; P˛eksa, R.; Grzywi ´nska, M.; Panas, D.; Sowa, M.; Skrobisz, K.; Matuszewski, M.; Szurowska, E. Comparison of Diffusion Kurtosis Imaging and Standard Mono-Exponential Apparent Diffusion Coefﬁcient in Diagnosis of Signiﬁcant Prostate Cancer—A Correlation with Gleason Score Assessed on Whole-Mount Histopathology Specimens. Diagnostics 2023, 13, 173 . [https://doi.org/10.3390/](https://doi.org/10.3390/)[ ](https://doi.org/10.3390/)diagnostics13020173 Academic Editor: Nicola Longo Received: 30 November 2022 Revised: 29 December 2022 Accepted: 1 January 2023 Published: 4 January 2023 Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) . 1 Second Department of Radiology, Medical University of Gdansk, 80-214 Gdansk, Poland 2 Department of Pathomorphology, Medical University of Gdansk, 80-214 Gdansk, Poland 3 Department of Human Physiology, Medical University of Gdansk, 80-214 Gdansk, Poland 4 Molecular Biology Laboratory, Institute of Animal Reproduction and Food Research Polish Academy of Sciences, 10-748 Olsztyn, Poland 5 Department of Urology, Medical University of Gdansk, 80-214 Gdansk, Poland 6 Department of Radiology, Medical University of Gdansk, 80-214 Gdansk, Poland * Correspondence: [anna.zurowska@gumed.edu.pl](anna.zurowska@gumed.edu.pl) Abstract: Background: The study was undertaken to compare the diagnostic performance of diffusion kurtosis imaging (DKI) with the standard monoexponential (ME) apparent diffusion coefﬁcient (ADC) model in the detection of signiﬁcant prostate cancer (PCa), using whole-mount histopathology of radical prostatectomy specimens as a reference standard. Methods: 155 patients with prostate cancer had undergone multiparametric magnetic resonance imaging (mpMRI) at 3T before prostatectomy. Quantitative diffusion parameters—the apparent diffusion coefﬁcient corrected for non-Gaussian behavior (Dapp ), kurtosis (K), ADC 1200, and ADC2000 were correlated with Gleason score and compared between cancerous and benign tissue and between GS 􀀔 3 + 3 and GS 􀀕 3 + 4 tumors. Results: The mean values of all diffusion parameters (Dapp, K, ADC1200, ADC2000 ) were signiﬁcantly different both between malignant and benign tissue and between GS 􀀔 3 + 3 and GS 􀀕 3 + 4 tumors. Although the kurtosis model was better ﬁtted to DWI data, the diagnostic performance in receiver operating characteristic (ROC) analysis of DKI and the standard ADC model in the detection of signiﬁcant PCa was similar in the peripheral zone (PZ) and in peripheral and transitional zones (TZ) together. In conclusion, our study was not able to demonstrate a clear superiority of the kurtosis model over standard ADC in the diagnosis of signiﬁcant PCa in PZ and in both zones combined. Keywords: prostate cancer; Magnetic Resonance Imaging (MRI); Diffusion Weighted Imaging (DWI); Diffusion Kurtosis Imaging (DKI); Gleason score 1. Introduction Prostate cancer (PCa) is the second most common malignancy in men with an incidence of over 1.4 million and the ﬁfth most common cause of cancer-related mortality with 375,000 deaths worldwide [1] . Due to the heterogeneity of prostate cancer, its clinical course may vary widely, from relatively benign to very aggressive; as a result, the terms non-si

FAQs

What is the goal of comparing DKI with the standard ADC model in this study?

The study evaluates and compares diagnostic performance of diffusion kurtosis imaging versus the standard monoexponential ADC model for detecting significant prostate cancer, using whole-mount histopathology as reference.

How many patients were included, and what imaging was performed before prostatectomy?

The study included 155 prostate cancer patients who underwent 3T multiparametric MRI before prostatectomy.

Do the results show that the kurtosis model is clearly superior to standard ADC?

No. Although the kurtosis model provided a better fit to DWI data, ROC analysis showed similar diagnostic performance for DKI and the standard ADC model in peripheral zone and in peripheral plus transitional zones combined.

Sep 24, 2026

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