Cui Yingying, Wang Xinhui, Wang Ying, Meng Nan, Wu Yaping, Shen Yu, Roberts Neil, Bai Yan, Song Xiaosheng, Shen Guofeng, Guo Yongjun, Guo Jinxia, Wang Meiyun
Department of Radiology, Henan Provincial People's Hospital & Zhengzhou University People's Hospital, Zhengzhou, China (Y.C., X.W., Y.W., N.M., Y.W., Y.S., Y.B., M.W.).
Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK (N.R.); Biomedical Research Institute, Henan Academy of Sciences, Zhengzhou, China (N.R., X.S., M.W.).
Acad Radiol. 2025 Jan;32(1):201-209. doi: 10.1016/j.acra.2024.08.021. Epub 2024 Aug 26.
To investigate the application of the three-compartment restriction spectrum imaging (RSI) model, diffusion kurtosis imaging (DKI), and diffusion-weighted imaging (DWI) in predicting Ki-67 status in rectal carcinoma.
A total of 80 rectal carcinoma patients, including 47 high-proliferation (Ki-67 > 50%) cases and 33 low-proliferation (Ki-67 ≤ 50%) cases, underwent pelvic MRI were enrolled. Parameters derived from RSI (f, f, and f), DKI (MD and MK), and DWI (ADC) were calculated and compared between the two groups. Logistic regression (LR) analysis was conducted to identify independent predictors and assess combined diagnosis. Area under the receiver operating characteristic curve (AUC), DeLong analysis, and calibration curve analyses were performed to evaluate diagnostic performance.
The patients with high-proliferation rectal carcinoma exhibited significantly higher f and MK values and significantly lower ADC, MD, f, and f values than those with low-proliferation rectal carcinoma (P < 0.05). LR analysis showed that MD, MK, and f were independent predictors for Ki-67 status in rectal carcinoma. Moreover, the combination of these three parameters achieved an optimal diagnostic efficacy (AUC = 0.877, sensitivity = 80.85%, specificity = 84.85%) that was significantly better than that obtained using ADC (AUC = 0.783, Z = 2.347, P = 0.019), f (AUC = 0.732, Z = 2.762, P = 0.006), and f (AUC = 0.700, Z = 3.071, P = 0.002). The combined diagnosis also showed good performance (AUC = 0.859) in the internal validation analysis based on 1000 bootstrap samples, while the calibration curve demonstrated that the combined diagnosis provided good stability.
RSI, DKI, and DWI can effectively differentiate between patients with high- and low-proliferation rectal carcinoma. Furthermore, the MD, MK, and f imaging parameters may be a novel and promising combination biomarker for examining Ki-67 status in rectal carcinoma.
探讨三室限制谱成像（RSI）模型、扩散峰度成像（DKI）和扩散加权成像（DWI）在预测直肠癌Ki-67状态中的应用。
纳入80例直肠癌患者，其中高增殖（Ki-67>50%）47例，低增殖（Ki-67≤50%）33例，均接受盆腔MRI检查。计算并比较两组患者从RSI（f、f和f）、DKI（MD和MK）和DWI（ADC）得出的参数。进行逻辑回归（LR）分析以确定独立预测因素并评估联合诊断。绘制受试者工作特征曲线（AUC）下面积、DeLong分析和校准曲线分析以评估诊断性能。
高增殖性直肠癌患者的f和MK值显著高于低增殖性直肠癌患者，而ADC、MD、f和f值显著低于低增殖性直肠癌患者（P<0.05）。LR分析表明，MD、MK和f是直肠癌Ki-67状态的独立预测因素。此外，这三个参数的组合实现了最佳诊断效能（AUC=0.877，灵敏度=80.85%，特异性=84.85%），明显优于单独使用ADC（AUC=0.783，Z=2.347，P=0.019）、f（AUC=0.732，Z=2.762，P=0.006）和f（AUC=0.700，Z=3.071，P=0.002）。在基于1000次自抽样的内部验证分析中，联合诊断也显示出良好的性能（AUC=0.859），而校准曲线表明联合诊断具有良好的稳定性。
RSI、DKI和DWI能够有效区分高增殖性和低增殖性直肠癌患者。此外，MD、MK和f成像参数可能是一种用于检测直肠癌Ki-67状态的新型且有前景的联合生物标志物。
