Skip to main content

ORIGINAL RESEARCH article

Front. Oncol.
Sec. Cancer Imaging and Image-directed Interventions
Volume 14 - 2024 | doi: 10.3389/fonc.2024.1431536
This article is part of the Research Topic Quantitative Imaging: Revolutionizing Cancer Management with biological sensitivity, specificity, and AI integration View all 13 articles

Assessment of Pathological Grade and Variants of Bladder Cancer with a Continuous-Time Random-Walk Diffusion Model

Provisionally accepted
Wei Wang Wei Wang 1Jingyun Wu Jingyun Wu 1Qi Shen Qi Shen 1Wei Li Wei Li 1Ke Xue Ke Xue 2Yu-Xin Yang Yu-Xin Yang 2Jianxing Qiu Jianxing Qiu 1*
  • 1 First Hospital, Peking University, Beijing, China
  • 2 Beijing United Imaging Intelligent Imaging Technology Research Institute, Beijing, Beijing Municipality, China

The final, formatted version of the article will be published soon.

    To evaluate the efficacy of high b-value diffusion-weighted imaging (DWI) with a continuous-time random-walk (CTRW) diffusion model in determining the pathological grade and variant histology (VH) of bladder cancer (BCa).A total of 81 patients (median age, 70 years; range, 35-92 years; 18 females; 66 high grades; 30 with VH) with pathologically confirmed bladder urothelial carcinoma were retrospectively enrolled and underwent bladder MRI on a 3.0T MRI scanner. Multi-bvalue DWI was performed using 11 b-values. Three CTRW model parameters were obtained: an anomalous diffusion coefficient (D) and two parameters reflecting temporal (α) and spatial (β) diffusion heterogeneity. The apparent diffusion coefficient (ADC) was calculated using b0 and b800. D, α, β, and ADC were statistically compared between high-and low-grade BCa, and between pure urothelial cancer (pUC) and VH. Comparisons were made using the Mann-Whitney U test between different pathological states. Receiver operating characteristic curve analysis was used to assess performance in differentiating the pathological states of BCa.ADC, D, and α were significantly lower in high-grade BCa compared to low-grade, and in VH compared to pUC (p < 0.001), while β showed no significant differences (p > 0.05). The combination of D and α yielded the best performance for determining BCa grade and VH (area under the curves = 0.913, 0.811), significantly outperforming ADC (area under the curves = 0.823, 0.761).The CTRW model effectively discriminated pathological grades and variants in BCa, highlighting its potential as a noninvasive diagnostic tool.

    Keywords: Urinary Bladder Neoplasms, Pathology, Neoplasm Grading, Tumor Microenvironment, Diffusion Magnetic Resonance Imaging

    Received: 12 May 2024; Accepted: 30 Jul 2024.

    Copyright: © 2024 Wang, Wu, Shen, Li, Xue, Yang and Qiu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Jianxing Qiu, First Hospital, Peking University, Beijing, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.