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• Clinical Article •
Prediction of zonal heterogeneity in prostate cancer using multi-parametric magnetic resonance habitat imaging
YUAN Lei  ZHANG Jingliang  MA Lina  XIA Yuwei  HAN Ye  HOU Guorui  QIN Weijun  ZHANG Jing  HUAN Yi  REN Jing 

DOI:10.12015/issn.1674-8034.2025.11.021.


[Abstract] Objective To explore the feasibility of habitat imaging (HI) for non-invasive quantitative visualization of zonal heterogeneity and risk prediction in prostate cancer (PCa).Materials and Methods This retrospective study involved 147 patients who underwent multi-parametric magnetic resonance imaging (mpMRI) and confirmed PCa by radical prostatectomy (RP) at Xijing Hospital from January 2018 to August 2024. Patients were divided into training and test sets in a 7∶3 ratio. According to RP results, PCa was categorized into transition zone (TZ) and peripheral zone (PZ). The apparent diffusion coefficient (ADC), perfusion fraction (f) and mean kurtosis (MK) values of each voxel were integrated to delineated habitat subregions and generate habitat maps. The differences between PZ and TZ PCa were compared from multiple perspectives including clinical, pathological and imaging. According to the 2019 International Society of Urological Pathology (ISUP) guidelines, the habitat maps were matched with RP specimens to assess the ISUP grade of each subregion, and the patients were classified into low-risk (ISUP ≤ 2) and high-risk (ISUP ≥ 3) groups. Logistic regression analysis was applied to identify factors associated with high-risk PCa and to construct a predictive model called zone-based habitat imaging (zHI)-clinial imaging. Then the model's efficacy was evaluated.Results Habitat 1 had lower ADC, f and higher MK values compared to habitats 2 and 3. Compared with TZ, PZ PCa exhibited worse clinical and pathological features, with a higher proportion of habitat 1. Logistic regression analysis indicated that anatomical zone (OR = 3.50, 95% CI: 1.01 to 12.09) and the proportion of Habitat 1 (OR = 3.63, 95% CI: 1.37 to 9.62) were independent risk factors for high-risk PCa (P < 0.05). The area under the curve (AUC) of the zHI-clinical imaging model for risk assessment in the training and test sets were 0.889 (95% CI: 0.822 to 0.955) and 0.883 (95% CI: 0.740 to 0.925), respectively.Conclusions This study comprehensively verified the zonal heterogeneity of PCa and constructed a model based on anatomical zone and HI features, which demonstrated enhanced efficacy in non-invasive quantitative visualization and prediction of PCa risk.
[Keywords] habitat imaging；multi-parameteric magnetic resonance imaging；prostate cancer；risk degree；zonal heterogeneity；radical prostatectomy

YUAN Lei1   ZHANG Jingliang2   MA Lina1   XIA Yuwei3   HAN Ye1   HOU Guorui1   QIN Weijun2   ZHANG Jing4   HUAN Yi1   REN Jing1*  

1 Department of Radiology, Xijing Hospital, Air Force Medical University, Xi'an 710032, China

2 Department of Urology, Xijing Hospital, Air Force Medical University, Xi'an 710032, China

3 Department of Research and Development, Shanghai United Imaging Intelligence Co, Ltd, Shanghai 200232, China

4 Department of Pathology, Xijing Hospital, Air Force Medical University, Xi'an 710032, China

Corresponding author: REN J, E-mail: jrenmm@126.com

Conflicts of interest   None.

Received  2025-06-17
Accepted  2025-11-10
DOI: 10.12015/issn.1674-8034.2025.11.021
DOI:10.12015/issn.1674-8034.2025.11.021.

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