Time-dependent diffusion MRI of soft tissue tumors: correlations with Ki-67 proliferation status

有效扩散系数 软组织 磁共振成像 接收机工作特性 磁共振弥散成像 热扩散率 医学 材料科学 扩散 生物医学工程 核医学 病理 成像生物标志物 核磁共振 肿瘤组织 曲线下面积 曲线下面积 细胞外液 细胞外 磁共振弥散加权成像 化学 放射科 扩散成像 医学影像学
作者
Zhi-Xin Yan,Meng Wang,Jian Zhao,Lisha Duan,Xiaohan Feng,Xinying Zhang,Haitian Liu,Wenhua Liang,Bing Wang,Xiaohui Cao,Yueluan Jiang,Mengzhu Wang,Thorsten Feiweier,Hong Yu
出处
期刊:Quantitative imaging in medicine and surgery [AME Publishing Company]
卷期号:16 (3): 209-209
标识
DOI:10.21037/qims-2025-1815
摘要

Background: Time-dependent diffusion magnetic resonance imaging (MRI) has the potential to help characterize tumor cell properties; however, its application in imaging soft tissue tumors is still unclear. The objective of this study was to assess whether quantitative parameters obtained from time-dependent diffusion MRI (td-dMRI) correlate with the Ki-67 proliferation status in soft tissue tumors. Methods: Participants with soft tissue tumors who underwent pretreatment td-dMRI between December 2023 and August 2024 were prospectively enrolled. The Imaging Microstructural Parameters Using Limited Spectrally Edited Diffusion (IMPULSED) model was utilized to fit td-dMRI signals. The microstructural parameters extracted included the intracellular volume fraction (vin), cell diameter (d), cellularity, and extracellular diffusivity (Dex). Apparent diffusion coefficient (ADC) values were calculated from diffusion-weighted imaging (DWI). Ki-67 was categorized into high (>20%) or low (≤20%) groups, and the area under the receiver operating characteristic (ROC) curve (AUC) was used to assess its effectiveness in differentiating between the high and low proliferation groups. These parameters were analyzed for their correlations with the Ki-67 index. Results: The analysis included 31 participants with soft tissue tumors (mean age 52.1±19.9 years). Among all the parameters, the relative change in ADC (rcADC) of td-dMRI exhibited the highest AUC of 0.91, with 81.3% sensitivity and 86.7% specificity for differentiating low and high Ki-67 states. Except for parameter d, the AUC values of other parameters were greater than 0.7 (P<0.05). The rcADC and vin values from td-dMRI exhibited strong positive correlations with the Ki-67 index (rrcADC=0.68, rvin=0.61; all P<0.001). Cellularity and change in ADC (cADC) showed moderate positive correlations with the Ki-67 index (rcelluarity=0.54, rcADC=0.54; all P=0.002), whereas ADC0 Hz and ADC25 Hz exhibited moderate negative correlations (rADC0 Hz=−0.52, rADC25 Hz=−0.42; P=0.003, P=0.020). Weak negative correlations with the Ki-67 index were observed for Dex and ADC40 Hz (rDex=−0.37, rADC40 Hz =−0.37; P=0.038, P=0.040). Conclusions: Several quantitative parameters derived from td-dMRI were correlated with Ki-67 proliferation status in soft tissue tumors. The rcADC was identified as the most robust predictor of Ki-67 status.
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