Radiomics model based on preoperative gadoxetic acid-enhanced MRI for predicting liver failure

BACKGROUND Postoperative liver failure is the most severe complication in cirrhotic patients with hepatocellular carcinoma(HCC) after major hepatectomy. Current available clinical indexes predicting postoperative residual liver function are not sufficiently accurate.AIM To determine a radiomics model based on preoperative gadoxetic acid-enhanced magnetic resonance imaging for predicting liver failure in cirrhotic patients with HCC after major hepatectomy.METHODS For this retrospective study, a radiomics-based model was developed based on preoperative hepatobiliary phase gadoxetic acid-enhanced magnetic resonance images in 101 patients with HCC between June 2012 and June 2018. Sixty-one radiomic features were extracted from hepatobiliary phase images and selected by the least absolute shrinkage and selection operator method to construct a radiomics signature. A clinical prediction model, and radiomics-based model incorporating significant clinical indexes and radiomics signature were built using multivariable logistic regression analysis. The integrated radiomics-based model was presented as a radiomics nomogram. The performances of clinical prediction model, radiomics signature, and radiomics-based model for predicting post-operative liver failure were determined using receiver operating characteristics curve, calibration curve, and decision curve analyses.RESULTS Five radiomics features from hepatobiliary phase images were selected to construct the radiomics signature. The clinical prediction model, radiomics signature, and radiomics-based model incorporating indocyanine green clearance rate at 15 min and radiomics signature showed favorable performance for predicting postoperative liver failure(area under the curve: 0.809-0.894). The radiomics-based model achieved the highest performance for predicting liver failure(area under the curve: 0.894; 95%CI: 0.823-0.964). The integrated discrimination improvement analysis showed a significant improvement in the accuracy of liver failure prediction when radiomics signature was added to the clinical prediction model(integrated discrimination improvement = 0.117, P =0.002). The calibration curve and an insignificant Hosmer-Lemeshow test statistic(P = 0.841) demonstrated good calibration of the radiomics-based model. The decision curve analysis showed that patients would benefit more from a radiomics-based prediction model than from a clinical prediction model and radiomics signature alone.CONCLUSION A radiomics-based model of preoperative gadoxetic acid–enhanced MRI can be used to predict liver failure in cirrhotic patients with HCC after major hepatectomy.     

干扰素在恶性淋巴瘤自体移植后早期干预的应用

目的:观察非霍奇金淋巴瘤（non-Hodgkin's lymphoma，NHL）患者自体造血干细胞移植（autologous hematopoietic stem cell transplantation，ASCT）术后应用重组人α-2b干扰素（α-2b IFN）进行早期干预治疗的临床疗效。方法:选取18例行ASCT的NHL患者为研究对象，移植前疾病评估均未达到完全缓解（complete remission，CR），试验组血象恢复后给予IFN 3 000 000 U次/隔日干预治疗，3个月后停用；对照组未行干扰素干预治疗，分析总体疗效及两组对比的生存情况。结果:随访中位时间为34（10~50）个月，患者中位生存时间为37（31~45）个月，3年总体无进展生存（progressive free survival，PFS）、总生存（overall survivial，OS）分别为54.7%、66.8%。ASCT后试验组1年内无疾病复发，2年内复发率为12.5%；对照组1年内复发率为20%，2年内复发率为30%。结论:NHL患者在ASCT后给予重组人α-2b IFN早期干预治疗，患者耐受性好，可能降低移植后早期复发率。     

Utility of Tissue Similarity Maps Based on Relative Cerebral Blood Volume for Grading Gliomas as Validated by Histological Results

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