Yang Ao, Xu Hao, Zhang Xin, Zheng Ping, Lin Li Bo, Liu Jie Ke, Zhou Peng, Chen Xiao Li
Department of Radiology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
GE Healthcare, Shanghai, China.
Insights Imaging. 2025 Sep 19;16(1):199. doi: 10.1186/s13244-025-02075-6.
To explore intravoxel incoherent motion (IVIM) for evaluation of the perineural invasion (PNI) status and survival in patients with rectal cancer.
The true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and microvascular volume fraction (f) were recorded together with histogram metrics. Differences in IVIM histogram metrics between the PNI-positive group and the PNI-negative group were analyzed. Univariable and multivariable logistic regression analysis were used for model construction. The area under the receiver operating characteristic curve (AUC) was used to assess the diagnostic performance of the models. Histopathology was used as the PNI endpoint. Kaplan-Meier curve analysis was employed to estimate the disease-free survival (DFS) and overall survival (OS) of patients.
A total of 175 patients were retrospectively enrolled in this study. Multivariable logistic regression analysis showed that higher D_median (odds ratio (OR) = 2.036, p = 0.003) and D_min (OR = 1.479, p = 0.002) and lower f_SD (OR = 0.697, p < 0.001) and f_kurtosis (OR = 0.485, p < 0.001) were independently associated with PNI-positive. The combined model showed the best performance in predicting the PNI status with AUCs, sensitivity, specificity, and accuracy of 0.885, 81.67%, 82.61%, and 82.29%, respectively. Kaplan-Meier curves analysis revealed that the patients with higher scores (> -1.12) of the combined model showed relatively lower 2-year DFS (81.6% vs 93.2%, p = 0.014) compared to the patients with lower scores (≤ -1.12).
IVIM histogram metrics could predict the PNI status and serve as a preoperative risk stratification tool.
The combination of IVIM histogram metrics and clinical characteristics could discriminate the PNI status and serve as a surrogate for PNI.
The PNI is an important prognostic factor in rectal cancer. The IVIM histogram metrics were associated with the PNI status. The combination of IVIM and clinical factors could serve as a surrogate for PNI.
探讨体素内不相干运动(IVIM)用于评估直肠癌患者的神经周围侵犯(PNI)状态及生存情况。
记录真实扩散系数(D)、伪扩散系数(D*)和微血管容积分数(f)以及直方图指标。分析PNI阳性组和PNI阴性组之间IVIM直方图指标的差异。采用单变量和多变量逻辑回归分析进行模型构建。采用受试者工作特征曲线(ROC)下面积(AUC)评估模型的诊断性能。以组织病理学作为PNI终点。采用Kaplan-Meier曲线分析评估患者的无病生存期(DFS)和总生存期(OS)。
本研究共回顾性纳入175例患者。多变量逻辑回归分析显示,较高的D中位数(比值比(OR)=2.036,p=0.003)和D最小值(OR=1.479,p=0.002)以及较低的f标准差(OR=0.697,p<0.001)和f峰度(OR=0.485,p<0.001)与PNI阳性独立相关。联合模型在预测PNI状态方面表现最佳,AUC、敏感性、特异性和准确性分别为0.885、81.67%、82.61%和82.29%。Kaplan-Meier曲线分析显示,联合模型得分较高(> -1.12)的患者与得分较低(≤ -1.12)的患者相比,2年DFS相对较低(81.6%对93.2%,p=0.014)。
IVIM直方图指标可预测PNI状态,并可作为术前风险分层工具。
IVIM直方图指标与临床特征相结合可区分PNI状态,并可作为PNI的替代指标。
PNI是直肠癌的重要预后因素。IVIM直方图指标与PNI状态相关。IVIM与临床因素相结合可作为PNI的替代指标。