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用连续时间随机游走扩散模型评估膀胱癌的病理分级和亚型

Assessment of pathological grade and variants of bladder cancer with a continuous-time random-walk diffusion model.

作者信息

Wang Wei, Wu Jingyun, Shen Qi, Li Wei, Xue Ke, Yang Yuxin, Qiu Jianxing

机构信息

Department of Radiology, Peking University First Hospital, Beijing, China.

Department of Urology, Peking University First Hospital, Institute of Urology, National Research Center for Genitourinary Oncology, Peking University, Beijing, China.

出版信息

Front Oncol. 2024 Aug 15;14:1431536. doi: 10.3389/fonc.2024.1431536. eCollection 2024.

Abstract

PURPOSE

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).

METHODS

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-b-value 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.

RESULTS

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).

CONCLUSION

The CTRW model effectively discriminated pathological grades and variants in BCa, highlighting its potential as a noninvasive diagnostic tool.

摘要

目的

评估采用连续时间随机游走(CTRW)扩散模型的高b值扩散加权成像(DWI)在确定膀胱癌(BCa)病理分级和组织学变异(VH)方面的疗效。

方法

回顾性纳入81例经病理证实的膀胱尿路上皮癌患者(中位年龄70岁;范围35 - 92岁;18例女性;66例高级别;30例有VH),并在3.0T MRI扫描仪上进行膀胱MRI检查。使用11个b值进行多b值DWI检查。获得三个CTRW模型参数:异常扩散系数(D)以及反映时间(α)和空间(β)扩散异质性的两个参数。使用b0和b800计算表观扩散系数(ADC)。对高级别和低级别BCa之间以及纯尿路上皮癌(pUC)和VH之间的D、α、β和ADC进行统计学比较。使用Mann-Whitney U检验对不同病理状态进行比较。采用受试者操作特征曲线分析评估区分BCa病理状态的性能。

结果

与低级别BCa相比,高级别BCa的ADC、D和α显著更低,与pUC相比,VH的ADC、D和α也显著更低(p < 0.001),而β无显著差异(p > 0.05)。D和α的组合在确定BCa分级和VH方面表现最佳(曲线下面积 = 0.913, 0.811),显著优于ADC(曲线下面积 = 0.823, 0.761)。

结论

CTRW模型有效区分了BCa的病理分级和变异,凸显了其作为无创诊断工具的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b07b/11357921/e5d09d9018dd/fonc-14-1431536-g001.jpg

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