Quantitative Estimation of Iron and Fat Content in Prostate Cancer by Multiparametric MRI and Its Application in Optimizing D'Amico Score

• Published in: Journal of magnetic resonance imaging Vol. 61; no. 5; pp. 2223 - 2233
• Main Authors: Zhao, Yunshu, Li, Guangzheng, Tian, Zhen, Zhu, Mengying, Han, Shuting, Jin, Minmin, Huang, Yuhua, Li, Yonggang
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01.05.2025; Wiley Subscription Services, Inc
• Subjects: Adipose Tissue - diagnostic imaging; Aged; Cell proliferation; Contrast Media; D'Amico score; Diffusion coefficient; fat fraction; Field strength; Humans; Iron; Iron - analysis; Lesions; Lipids; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Male; Males; Medical imaging; Middle Aged; Multiparametric Magnetic Resonance Imaging - methods; multiparametric MRI; Neoplasm Recurrence, Local - diagnostic imaging; Prospective Studies; Prostate - diagnostic imaging; Prostate cancer; Prostatic Neoplasms - diagnostic imaging; Regression analysis; Risk assessment; ROC Curve; Statistical analysis; Statistical tests; Thickness; multiparametric MRI; prostate cancer; fat fraction; D'Amico score; T2
• DOI: 10.1002/jmri.29661
• ISSN: 1053-1807; 1522-2586

Background The risk of biochemical recurrence (BCR) in prostate cancer (PCa) is typically assessed using D'Amico score. However, iron and fat content in PCa are closely related to tumor cell proliferation and the risk of BCR may be estimated using multiparametric MRI (mpMRI). Purpose To noninvasively estimate fat and iron content in PCa and to evaluate their utility in enhancing D'Amico scores for predicting BCR in PCa patients. Study Type Prospective. Subjects Forty‐eight male patients in the BCR group (age 71.31 ± 5.74 years) and 27 male patients in the non‐BCR group (age 70.3 ± 6.04 years). Field Strength/Sequence 3.0 T, Turbo‐spin echo T2‐weighted imaging, diffusion‐weighted imaging (DWI), dynamic contrast‐enhanced (DCE) imaging, Gradient echo Q‐Dixon sequence. Assessment The mean fat fraction (FF) and T2* values of lesions were extracted from the FF map and the T2* map. Additionally, prostate volume, mean apparent diffusion coefficient (ADC) value, periprostatic fat thickness (PPFT), subcutaneous fat thickness (SFT), blood lipid content, pre‐ and post‐operative prostate‐specific antigen (PSA) values were collected. Statistical Tests Stepwise‐COX regression analysis was employed to identify the significant predictors of BCR, which led to the construction of an improvement‐adjusted (IA) model. Then the IA model as well as the D'Amico score were evaluated using C‐index and time‐dependent AUC, decision‐curve analysis, and Kaplan–Meier curve. P < 0.05 was statistically significant. Results Significant differences were observed in PSA, D'Amico score, ISUP grade, T2*, FF, and ADC values of the lesions in the BCR group compared with the non‐BCR group. Mean T2*, FF, and ADC values of the lesions were screened to construct the IA model incorporated into the D'Amico score (IA Model: C‐index = 0.749; AUC = 0.812; D'Amico score: C‐index = 0.672; AUC = 0.723). Data Conclusion This study demonstrated that mpMRI can quantitatively estimate fat and iron within PCa lesions. By integrating ADC, FF, and T2* values into the D'Amico score, the preoperative‐risk assessment for BCR can be improved. Evidence Level 2 Technical Efficacy Stage 2