Xie Peiyi, Huang Qitong, Zheng Litao, Li Jiao, Fu Shuai, Zhu Pan, Pan Ximin, Shi Lishuo, Zhao Yandong, Meng Xiaochun
Department of Radiology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, People's Republic of China.
Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University Guangzhou, Guangzhou, People's Republic of China.
Eur Radiol. 2025 Mar;35(3):1382-1393. doi: 10.1007/s00330-024-11172-x. Epub 2024 Nov 5.
To explore the sub-regional histogram features of amide proton transfer-weighted (APTw) MRI, compared with those of diffusion-weighted imaging (DWI), in predicting the tumor budding (TB) grade of rectal cancer (RC).
This study prospectively enrolled 74 patients with pathologically confirmed RC, who underwent APTw MRI before surgery from July 2022 to March 2023. Hematoxylin-eosin staining was used for TB scoring. K-means clustering (K = 4-6) was applied to obtain multiple sub-regions (n = 3-5), and corresponding histogram features (including mean, standard deviation, minimum, maximum, and 10th, 25th, 50th, 75th, and 90th quantile) of APT and apparent diffusion coefficient (ADC) maps were extracted and filtered using stepwise regression.
When K = 5, the K-means clustering is four sub-regions, showing the best prediction for TB grade compared to K = 4 or 6. When K = 5, there were significantly higher histogram features of the APT map in sub-regions 3 and 4 in the high TB grade group compared to the low-intermediate TB grade group. Receiver operating characteristic (ROC) curve and internal validation suggested that the predictive efficiency of the model was highest when K = 5, with AUC, sensitivity, specificity, accuracy, and kappa values of 0.92, 93%, 71%, 87%, and 0.65, respectively. There were no significant differences in the histogram features of each sub-region in the ADC map (p > 0.05).
The sub-regional histogram features of APTw images can help to distinguish the heterogeneous regions of RC, which can be used to predict the TB grade of RC.
Question Can the sub-regional histogram features of APTw MRI predict the tumor budding (TB) grade of rectal cancer (RC)? Findings Differences exist in histogram features of APT map subregions between high and low-intermediate TB grade groups; subregions of the APT map have different predictive abilities. Clinical relevance APT-weighted imaging might outperform DWI in predicting TB grade in RC.
探讨酰胺质子转移加权(APTw)磁共振成像(MRI)的亚区域直方图特征,并与扩散加权成像(DWI)的特征进行比较,以预测直肠癌(RC)的肿瘤芽生(TB)分级。
本研究前瞻性纳入74例经病理证实的RC患者,这些患者于2022年7月至2023年3月在手术前行APTw MRI检查。采用苏木精-伊红染色进行TB评分。应用K均值聚类(K = 4 - 6)获得多个亚区域(n = 3 - 5),并提取APT图和表观扩散系数(ADC)图的相应直方图特征(包括均值、标准差、最小值、最大值以及第10、25、50、75和90百分位数),并使用逐步回归进行筛选。
当K = 5时,K均值聚类为四个亚区域,与K = 4或6相比,对TB分级的预测效果最佳。当K = 5时,高TB分级组亚区域3和4中APT图的直方图特征显著高于低 - 中级TB分级组。受试者操作特征(ROC)曲线和内部验证表明,当K = 5时模型的预测效率最高,曲线下面积(AUC)、灵敏度、特异度、准确度和kappa值分别为0.92、93%、71%、87%和0.65。ADC图各亚区域的直方图特征无显著差异(p > 0.05)。
APTw图像的亚区域直方图特征有助于区分RC的异质区域,可用于预测RC的TB分级。
问题APTw MRI的亚区域直方图特征能否预测直肠癌(RC)的肿瘤芽生(TB)分级?发现高、低 - 中级TB分级组之间APT图亚区域的直方图特征存在差异;APT图的亚区域具有不同的预测能力。临床意义在预测RC的TB分级方面,APTw成像可能优于DWI。