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.
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All the authors (Xuechao Du, Cuihong Jin, Yuchang Yan, Pengtao Sun, Yingmo Shen, Zhenyu Pan, Tao Jiang) report no conflicts of interest.
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This study was approved by the Ethics Committee of Beijing Chaoyang Hospital, Capital Medical University.
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Du, X., Jin, C., Yan, Y. et al. CT-measured hernia parameters can predict component separation: a cross-sectional study from China. Hernia 27, 979–986 (2023). https://doi.org/10.1007/s10029-023-02761-8
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DOI: https://doi.org/10.1007/s10029-023-02761-8