Suppr超能文献

CT 测量的疝参数可预测腹直肌分离:来自中国的一项横断面研究。

CT-measured hernia parameters can predict component separation: a cross-sectional study from China.

机构信息

Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, No.5 Jingyuan Road, Shijingshan District, Beijing, 100043, China.

Department of Hernia and Abdominal Wall Surgery, Beijing Chaoyang Hospital, Capital Medical University, No.5 Jingyuan Road, Shijingshan District, Beijing, 100043, China.

出版信息

Hernia. 2023 Aug;27(4):979-986. doi: 10.1007/s10029-023-02761-8. Epub 2023 Mar 18.

Abstract

PURPOSE

Currently, there are no reliable preoperative methods for predicting component separation (CS) during incisional hernia repair. By quantitatively measuring preoperative computed tomography (CT) imaging, we aimed to assess the value of hernia defect size, abdominal wall muscle quality, and hernia volume in predicting CS.

METHODS

The data of 102 patients who underwent open Rives-Stoppa retro-muscular mesh repair for midline incisional hernia between January 2019 and March 2022 were retrospectively analyzed. The patients were divided into two groups: ''CS group'' patients who required CS to attempt fascial closure, and ''non-CS'' group patients who required only Rives-Stoppa retro-muscular release to achieve fascial closure. Hernia defect width, hernia defect angle, rectus width, abdominal wall muscle area and CT attenuation, hernia volume (HV), and abdominal cavity volume (ACV) were measured on CT images. The rectus width to defect width ratio (RDR), HV/ACV, and HV/peritoneal volume (PV; i.e., HV + ACV) were calculated. Differences between the indices of the two groups were compared. Logistic regression models were applied to analyze the relationships between the above CT parameters and CS. Receiver operator characteristic (ROC) curves were generated to evaluate the potential utility of CT parameters in predicting CS.

RESULTS

Of the102 patients, 69 were in the non-CS group and 33 were in the CS group. Compared with the non-CS group, hernia defect width (P < 0.001), hernia defect angle (P < 0.001), and hernia volume (P < 0.001) were larger in the CS group, while RDR (P < 0.001) was smaller. The abdominal wall muscle area in the CS group was slightly greater than that in the non-CS group (P = 0.046), and there was no significant difference in the CT attenuation of the abdominal wall muscle between the two groups (P = 0.089). Multivariate logistic regression identified hernia defect width (OR 1.815, 95% CI 1.428-2.308, P < 0.001), RDR (OR 0.018, 95% CI 0.003-0.106, P < 0.001), hernia defect angle (OR 1.077, 95% CI 1.042-1.114, P < 0.001), hernia volume (OR 1.002, 95% CI 1.001-1.003, P < 0.001), and CT attenuation of abdominal wall muscle (OR 0.962, 95% CI 0.927-0.998, P = 0.037) as independent predictors of CS. Hernia defect width was the best predictor for CS, with a cut-off point of 9.2 cm and an area under the curve (AUC) of 0.890. The AUCs of RDR, hernia defect angle, hernia volume, and abdominal wall muscle CT attenuation were 0.843, 0.812, 0.747, and 0.572, respectively.

CONCLUSION

Quantitative CT measurements are of great value for preoperative prediction of CS. Hernia defect size, hernia volume, and the CT attenuation of abdominal wall muscle are all preoperative predictive indicators of CS.

摘要

目的

目前,尚无可靠的术前方法可预测切口疝修补术中的切口分离(CS)。本研究旨在通过定量测量术前计算机断层扫描(CT)成像,评估疝缺损大小、腹壁肌肉质量和疝体积在预测 CS 中的价值。

方法

回顾性分析了 2019 年 1 月至 2022 年 3 月间 102 例接受开放式 Rives-Stoppa 肌后补片修复中线切口疝的患者的数据。患者被分为两组:需要 CS 尝试筋膜闭合的“CS 组”患者和仅需要 Rives-Stoppa 肌后松解以实现筋膜闭合的“非 CS 组”患者。在 CT 图像上测量疝缺损宽度、疝缺损角度、直肌宽度、腹壁肌肉面积和 CT 衰减、疝体积(HV)和腹腔体积(ACV)。计算直肌宽度与缺损宽度比(RDR)、HV/ACV 和 HV/腹膜体积(即 HV+ACV)。比较两组间各指数的差异。应用 logistic 回归模型分析上述 CT 参数与 CS 的关系。绘制受试者工作特征(ROC)曲线,以评估 CT 参数预测 CS 的潜在效能。

结果

102 例患者中,69 例为非 CS 组,33 例为 CS 组。与非 CS 组相比,CS 组的疝缺损宽度(P<0.001)、疝缺损角度(P<0.001)和疝体积(P<0.001)更大,而 RDR(P<0.001)更小。CS 组的腹壁肌肉面积略大于非 CS 组(P=0.046),两组腹壁肌肉 CT 衰减无显著差异(P=0.089)。多变量 logistic 回归确定了疝缺损宽度(OR 1.815,95%CI 1.428-2.308,P<0.001)、RDR(OR 0.018,95%CI 0.003-0.106,P<0.001)、疝缺损角度(OR 1.077,95%CI 1.042-1.114,P<0.001)、疝体积(OR 1.002,95%CI 1.001-1.003,P<0.001)和腹壁肌肉 CT 衰减(OR 0.962,95%CI 0.927-0.998,P=0.037)是 CS 的独立预测因子。疝缺损宽度是 CS 的最佳预测指标,截断值为 9.2cm,曲线下面积(AUC)为 0.890。RDR、疝缺损角度、疝体积和腹壁肌肉 CT 衰减的 AUC 分别为 0.843、0.812、0.747 和 0.572。

结论

定量 CT 测量对于 CS 的术前预测具有重要价值。疝缺损大小、疝体积和腹壁肌肉 CT 衰减均为 CS 的术前预测指标。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验