Wu Tianchong, Huang Wenhao, He Baochun, Guo Yuehua, Peng Gongzhe, Li Mingyue, Bao Shiyun
Department of Hepatobiliary and Pancreatic Surgery, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, China.
The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China.
J Gastrointest Oncol. 2022 Jun;13(3):1224-1236. doi: 10.21037/jgo-22-282.
The risk of post-hepatectomy liver failure (PHLF) is difficult to predict preoperatively. Accurate preoperative assessment of residual liver volume is critical in PHLF. Three-dimensional (3D) imaging and intra-operative ultrasound (IOUS) offer significant advantages in calculating liver volume and have been widely used in hepatectomy risk assessment. Our research aimed to explore the accuracy of 3D imaging technique combining IOUS in predicting PHLF after hepatectomy.
We used a retrospective study design to analyze patients who underwent hepatectomy with 3D imaging combined with IOUS between 2017 and 2020. Utilizing 3D reconstruction, the patient's residual liver volumes (PRLVs) and ratio of PRLV to standard liver volume (SLV) were calculated preoperatively. Hepatectomy were performed and actual hepatectomy volume (AHV) were measured. Consistency between preoperative planned hepatectomy volume (PPHV) and AHV was quantified postoperatively by Bland-Altman analysis. Multiple logistic regression and receiver-operating characteristic (ROC) curves were utilized to discuss the predictive value of PRLV/SLV in PHLF.
Among the 214 included patients, 58 (27.1%) had PHLF. Patients with PHLF had significantly higher residual rates of ICG-R15 (%) (P=0.000) and a lower PRLV/SLV ratio (P=0.000). Bland-Altman analysis showed that PPHV was consistent with AHV (P=0.301). Multivariate analysis confirmed that PRLV/SLV ratio >60% (OR, 0.178; 95% CI: 0.084-0.378; P<0.01) was a protective factor for PHLF. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 75.8% (95% CI: 64.5.3-87.2%), 66.6% (95% CI: 59.1-74.1%), 45.8%, and 88.1%, respectively. The area under the ROC curve (AUC) was 73.7% (95% CI: 65.7-85.8%) and the diagnostic accuracy of PRLV/SLV for PHLF was moderate (P<0.001). These results were validated in the validation cohort perfectly. The primary cohort included 214 patients with a PHLF rate of 27.1% (n=58, 28 grade B and 13 grade C). The validation cohort included 135 patients with a PHLF rate of 35.6% (n=48, 24 grade B and 11 grade C).
The calculation of PRLV/SLV has predictive value in PHLF and can be exploited as a predictive factor. The 3D imaging technique combined with IOUS may be useful for PHLF risk assessment in hepatectomy patients.
肝切除术后肝衰竭（PHLF）的风险在术前难以预测。术前准确评估残余肝体积对PHLF至关重要。三维（3D）成像和术中超声（IOUS）在计算肝体积方面具有显著优势，已广泛应用于肝切除风险评估。我们的研究旨在探讨结合IOUS的3D成像技术预测肝切除术后PHLF的准确性。
我们采用回顾性研究设计，分析2017年至2020年间接受3D成像联合IOUS肝切除术的患者。利用3D重建技术，术前计算患者的残余肝体积（PRLV）以及PRLV与标准肝体积（SLV）的比值。进行肝切除术并测量实际肝切除体积（AHV）。术后通过Bland-Altman分析量化术前计划肝切除体积（PPHV）与AHV之间的一致性。采用多因素逻辑回归和受试者工作特征（ROC）曲线探讨PRLV/SLV对PHLF的预测价值。
在纳入的214例患者中，58例（27.1%）发生PHLF。发生PHLF的患者吲哚菁绿滞留率（ICG-R15）（%）显著更高（P = 0.000），PRLV/SLV比值更低（P = 0.000）。Bland-Altman分析显示PPHV与AHV一致（P = 0.301）。多因素分析证实PRLV/SLV比值>60%（OR，0.178；95%CI：0.084 - 0.378；P<0.01）是PHLF的保护因素。敏感性、特异性、阳性预测值（PPV）和阴性预测值（NPV）分别为75.8%（95%CI：64.5 - 87.2%）、66.6%（95%CI：59.1 - 74.1%）、45.8%和88.1%。ROC曲线下面积（AUC）为73.7%（95%CI：65.7 - 85.8%），PRLV/SLV对PHLF的诊断准确性中等（P<0.001）。这些结果在验证队列中得到了完美验证。主要队列包括214例患者，PHLF发生率为27.1%（n = 58，28例B级和13例C级）。验证队列包括135例患者，PHLF发生率为35.6%（n = 48，24例B级和11例C级）。
PRLV/SLV的计算对PHLF具有预测价值，可作为预测因素。3D成像技术联合IOUS可能有助于肝切除患者的PHLF风险评估。
