磁共振成像2026，Vol.17Issue(9)：16-24,9.DOI:10.12015/issn.1674-8034.2026.09.003
基于腹部CT体成分分析结合扩散峰度成像术前预测T3～T4期直肠癌肿瘤出芽级别的价值
The value of preoperative prediction of tumor budding grade in stage T3-T4 rectal cancer based on abdominal CT body composition analysis combined with diffusion kurtosis imaging technique
摘要
Abstract
Objective:This study aims to investigate the value of abdominal CT body composition analysis combined with diffusion kurtosis imaging(DKI)for the preoperative prediction of tumor budding(TB)grade in patients with T3 to T4 rectal cancer.Materials and Methods:A retrospective analysis was conducted on data from 89 patients diagnosed with T3 to T4 rectal adenocarcinoma,confirmed by postoperative pathology.All patients underwent pelvic 3.0 T MRI and whole abdominal CT examinations prior to surgery.Based on the pathological results,the TB grade was categorized into two groups:a low-intermediate grade TB group(52 cases)and a high grade TB group(37 cases).Two observers measured the quantitative parameters of DKI in the lesions of both groups,including fractional anisotropy(FA)value,mean diffusivity(MD)value,and mean kurtosis(MK)value.The TotalSegmentator tool was utilized to automatically segment subcutaneous fat,visceral fat,and muscle at the L3 level of the abdominal CT scans.Python software facilitated the automatic calculation of subcutaneous fat area(SFA),visceral fat area(VFA),and muscle area(MA).The ratios of VFA to SFA(VFA/SFA),SFA to standard body weight(SBW)(SFA/SBW),VFA to SBW(VFA/SBW),MA to SBW(MA/SBW),and the difference between VFA and SFA(VFA-SFA)were calculated.The consistency of DKI parameters assessed by two observers was evaluated using the intra-class correlation coefficient(ICC).To examine the differences in DKI parameters and body composition indicators across the groups,either a Mann-Whitney U test or an independent sample t-test was utilized.A multivariate logistic regression analysis was performed to determine independent risk factors,which facilitated the creation of a combined prediction model based on these factors.The diagnostic performance of each individual risk factor,as well as the combined prediction model,was evaluated through the receiver operating characteristic(ROC)curve.To compare the diagnostic efficacy between the individual variables and the combined model,the DeLong test was employed,whereas the McNemar test was used to assess differences in sensitivity and specificity.Results:The consistency of the DKI quantitative parameters measured by the two observers was good,with ICC values exceeding 0.75.In the high grade TB group,the MK,VFA,and VFA/SBW values were 0.938(0.891,1.019),[150.620(107.685,199.840)]cm2,and 2.490(1.730,3.210),respectively,significantly surpassing those in the low-intermediate grade TB group,which had values of 0.776(0.685,0.878),[117.205(72.067,169.762)]cm2,and 2.115(1.242,2.650).The MD value in the high grade TB group was(1.113±0.105)μm2/ms,which was lower than that in the low-intermediate grade TB group(1.347±0.257)μm²/ms.The differences between the two groups for all the aforementioned parameters were statistically significant(P<0.05).The results of multivariate logistic regression analysis indicated that the MK value[odds ratio:4.104,95%confidence interval(CI):2.223 to 7.578]and the VFA/SBW value[odds ratio:2.335(95%CI:1.300 to 4.195)]were independent risk predictors for TB grade(P<0.05).The area under the curve(AUC)for predicting TB grade based on the MK and VFA/SBW values,as well as their combined prediction model,were 0.838,0.627,and 0.886,respectively.The sensitivity of these models was 91.89%,72.97%,and 81.08%,respectively,while the specificity was 67.31%,50.00%,and 80.77%,respectively.The diagnostic efficacy of the combined prediction model was superior to that of VFA/SBW alone,and its specificity exceeded that of both MK and VFA/SBW,with statistically significant differences(P<0.05).Conclusions:For patients with T3 to T4 rectal cancer,DKI has been shown to effectively predict TB grade.Additionally,body composition analysis serves to preliminarily stratify the risk of TB.The integration of these two modalities significantly enhances the accuracy of predicting TB grade,thereby providing more comprehensive insights into the interplay between host factors and local tumor characteristics for preoperative TB risk assessment.关键词
直肠癌/肿瘤出芽/体成分分析/定量计算机断层扫描/磁共振成像/扩散峰度成像Key words
rectal cancer/tumor budding/body composition analysis/quantitative computed tomography/magnetic resonance imaging/diffusion kurtosis imaging分类
医药卫生引用本文复制引用
陈安良,张钦和,李文豪,谢素玲,王秀林,王洪凯,孙祎楠,魏强,刘爱连..基于腹部CT体成分分析结合扩散峰度成像术前预测T3～T4期直肠癌肿瘤出芽级别的价值[J].磁共振成像,2026,17(9):16-24,9.基金项目
辽宁省科技计划联合计划项目(编号:2025-MSLH-199) （编号:2025-MSLH-199）
大连医科大学附属第一医院院内基金项目(编号:2019HZ007)Joint Research Program of Liaoning Provincial Science and Technology Plan(No.2025-MSLH-199),Fund Project of the First Affiliated Hospital of Dalian Medical University(No.2019HZ007). （编号:2019HZ007）
