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

IF 3.3 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Yunshu Zhao, Guangzheng Li, Zhen Tian, Mengying Zhu, Shuting Han, Minmin Jin, Yuhua Huang, Yonggang Li
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引用次数: 0

Abstract

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.

通过多参数磁共振成像定量估算前列腺癌中的铁和脂肪含量及其在优化达米科评分中的应用
背景:前列腺癌(PCa)的生化复发(BCR)风险通常使用D'Amico评分进行评估。然而,PCa中的铁和脂肪含量与肿瘤细胞的增殖密切相关,因此可使用多参数磁共振成像(mpMRI)估算生化复发的风险。研究类型:前瞻性研究:研究对象48名BCR组男性患者(年龄为71.31 ± 5.74岁)和27名非BCR组男性患者(年龄为70.3 ± 6.04岁):3.0 T、涡轮自旋回波 T2 加权成像、弥散加权成像(DWI)、动态对比增强(DCE)成像、梯度回波 Q-Dixon 序列:从 FF 图和 T2* 图中提取病变的平均脂肪分数(FF)和 T2* 值。此外,还收集了前列腺体积、平均表观扩散系数(ADC)值、前列腺周围脂肪厚度(PPFT)、皮下脂肪厚度(SFT)、血脂含量、术前和术后前列腺特异性抗原(PSA)值:采用逐步-COX 回归分析法确定 BCR 的重要预测因素,从而建立改进调整(IA)模型。然后使用 C 指数和随时间变化的 AUC、决策曲线分析和 Kaplan-Meier 曲线对 IA 模型和 D'Amico 评分进行评估。P 结果:与非 BCR 组相比,BCR 组病变的 PSA、D'Amico 评分、ISUP 分级、T2*、FF 和 ADC 值均有显著差异。对病变的平均 T2*、FF 和 ADC 值进行筛选,以构建纳入 D'Amico 评分的 IA 模型(IA 模型:C-index = 0.749; AUC = 0.812; D'Amico score:数据结论:这项研究表明,mpMRI 可以定量估算 PCa 病灶内的脂肪和铁含量。通过将 ADC、FF 和 T2* 值纳入 D'Amico 评分,可以改善 BCR 的术前风险评估。
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来源期刊
CiteScore
9.70
自引率
6.80%
发文量
494
审稿时长
2 months
期刊介绍: The Journal of Magnetic Resonance Imaging (JMRI) is an international journal devoted to the timely publication of basic and clinical research, educational and review articles, and other information related to the diagnostic applications of magnetic resonance.
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