Dataset related to article "Virtual Biopsy for Diagnosis of Chemotherapy-Associated Liver Injuries and Steatohepatitis: A Combined Radiomic and Clinical Model in Patients with Colorectal Liver Metastases "

This record contains raw data related to article "Virtual Biopsy for Diagnosis of Chemotherapy-Associated Liver Injuries and Steatohepatitis: A Combined Radiomic and Clinical Model in Patients with Colorectal Liver Metastases " Non-invasive diagnosis of chemotherapy-associated liver injuries (CALI) is still an unmet need. The present study aims to elucidate the contribution of radiomics to the diagnosis of sinusoidal dilatation (SinDil), nodular regenerative hyperplasia (NRH), and non-alcoholic steatohepatitis (NASH). Patients undergoing hepatectomy for colorectal metastases after chemotherapy (January 2018-February 2020) were retrospectively analyzed. Radiomic features were extracted from a standardized volume of non-tumoral liver parenchyma outlined in the portal phase of preoperative post-chemotherapy computed tomography. Seventy-eight patients were analyzed: 25 had grade 2-3 SinDil, 27 NRH, and 14 NASH. Three radiomic fingerprints independently predicted SinDil: GLRLM_f3 (OR = 12.25), NGLDM_f1 (OR = 7.77), and GLZLM_f2 (OR = 0.53). Combining clinical, laboratory, and radiomic data, the predictive model had accuracy = 82%, sensitivity = 64%, and specificity = 91% (AUC = 0.87 vs. AUC = 0.77 of the model without radiomics). Three radiomic parameters predicted NRH: conventional_HUQ2 (OR = 0.76), GLZLM_f2 (OR = 0.05), and GLZLM_f3 (OR = 7.97). The combined clinical/laboratory/radiomic model had accuracy = 85%, sensitivity = 81%, and specificity = 86% (AUC = 0.91 vs. AUC = 0.85 without radiomics). NASH was predicted by conventional_HUQ2 (OR = 0.79) with accuracy = 91%, sensitivity = 86%, and specificity = 92% (AUC = 0.93 vs. AUC = 0.83 without radiomics). In the validation set, accuracy was 72%, 71%, and 91% for SinDil, NRH, and NASH. Radiomic analysis of liver parenchyma may provide a signature that, in combination with clinical and laboratory data, improves the diagnosis of CALI.本数据集包含与论文《虚拟活检用于诊断化疗相关肝损伤及脂肪性肝炎：结直肠肝转移患者的放射组学与临床联合模型》相关的原始数据。化疗相关肝损伤（Chemotherapy-Associated Liver Injuries, CALI）的无创诊断仍是尚未满足的临床需求。本研究旨在阐明放射组学（radiomics）对诊断窦状隙扩张（Sinusoidal Dilatation, SinDil）、结节状再生性增生（Nodular Regenerative Hyperplasia, NRH）以及非酒精性脂肪性肝炎（Non-Alcoholic Steatohepatitis, NASH）的贡献。本研究回顾性分析了2018年1月至2020年2月期间，接受化疗后结直肠转移瘤肝切除术的患者。从化疗后术前门静脉期计算机断层扫描（Computed Tomography, CT）图像中，于勾画的标准化非肿瘤肝实质体积内提取放射组学特征。本研究共纳入78例患者：其中25例为2~3级窦状隙扩张，27例为结节状再生性增生，14例为非酒精性脂肪性肝炎。 三个放射组学特征可独立预测窦状隙扩张：GLRLM_f3（优势比OR=12.25）、NGLDM_f1（OR=7.77）以及GLZLM_f2（OR=0.53）。联合临床、实验室及放射组学数据的预测模型准确率达82%，灵敏度为64%，特异度为91%（曲线下面积AUC=0.87，而未加入放射组学的模型AUC为0.77）。 另有三个放射组学参数可预测结节状再生性增生：conventional_HUQ2（OR=0.76）、GLZLM_f2（OR=0.05）以及GLZLM_f3（OR=7.97）。联合临床/实验室/放射组学的模型准确率达85%，灵敏度为81%，特异度为86%（AUC=0.91，未加入放射组学的模型AUC为0.85）。 非酒精性脂肪性肝炎可通过conventional_HUQ2（OR=0.79）进行预测，该模型准确率达91%，灵敏度为86%，特异度为92%（AUC=0.93，未加入放射组学的模型AUC为0.83）。在验证集中，窦状隙扩张、结节状再生性增生及非酒精性脂肪性肝炎的预测准确率分别为72%、71%及91%。 肝实质的放射组学分析可提供一种特征标签，将其与临床及实验室数据联合后，可改善化疗相关肝损伤的诊断效能。