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基于 PET/CT 的肿块型肝内胆管细胞癌影像组学可提高病理数据和生存预测的准确性。

PET/CT-based radiomics of mass-forming intrahepatic cholangiocarcinoma improves prediction of pathology data and survival.

机构信息

Department of Nuclear Medicine, IRCCS Humanitas Research Hospital, Milan, Italy.

MOX Laboratory, Department of Mathematics, Politecnico Di Milano, Milan, Italy.

出版信息

Eur J Nucl Med Mol Imaging. 2022 Aug;49(10):3387-3400. doi: 10.1007/s00259-022-05765-1. Epub 2022 Mar 26.

Abstract

PURPOSE

Intrahepatic cholangiocarcinoma (IHC) is an aggressive disease with few reliable preoperative biomarkers. This study aims to elucidate if radiomics extracted from preoperative [18F]FDG PET/CT may grant a non-invasive biological characterization of IHC and predict outcome after complete resection of the tumor.

METHODS

All patients preoperatively imaged by [18F]FDG PET/CT who underwent hepatectomy for mass-forming IHC in the period 2010-2019 were retrospectively evaluated. On PET images, manual slice-by-slice segmentation of IHC was performed (Tumor-VOI). A 5-mm margin region was semi-automatically generated around the tumor (Margin-VOI). Textural analysis was performed using the LifeX software. Analyzed outcomes included tumor grading (G3 vs. G1-2), microvascular invasion (MVI), overall survival (OS), and progression-free survival (PFS). The performances of the combined clinical-radiomic models were compared with those of standard clinical models.

RESULTS

Overall, 74 patients (40 females, median age 68 years) were included. Considering tumor grading and MVI, the models combining the clinical data and radiomics of the Tumor-VOI had better performances than the clinical ones (AUC = 0.78 vs. 0.72 for grading; 0.87 vs. 0.78 for MVI). The inclusion into the models of radiomics of the Margin-VOI further improved the prediction of grading (AUC = 0.83), but not of MVI. Considering OS and PFS, the models including the preoperative clinical data and radiomics of the Tumor-VOI and Margin-VOI had better performances than the pure clinical ones (C-index = 0.81 vs. 0.76 for OS; 0.81 vs. 0.72 for PFS) and similar to the models including the pathology and postoperative data (C-index = 0.81 for OS; 0.79 for PFS). No model retained the standard SUV measures.

CONCLUSION

The PET-based radiomics of IHC can predict pathology data and allow a reliable preoperative evaluation of prognosis. The radiomics of both the tumoral and peritumoral areas had clinical relevance. The combined clinical-radiomic models outperformed the pure preoperative clinical ones and achieved performances non-inferior to the postoperative models.

摘要

目的

肝内胆管细胞癌(IHC)是一种侵袭性疾病,可靠的术前生物标志物较少。本研究旨在阐明从术前 [18F]FDG PET/CT 提取的放射组学是否可以对 IHC 进行非侵入性的生物学特征描述,并预测肿瘤完全切除后的结果。

方法

回顾性分析 2010 年至 2019 年间因肿块形成性 IHC 行肝切除术的所有接受 [18F]FDG PET/CT 术前成像的患者。在 PET 图像上,对 IHC 进行手动逐层分段(肿瘤-VOI)。肿瘤周围自动生成 5mm 的边界区域(边界-VOI)。使用 LifeX 软件进行纹理分析。分析结果包括肿瘤分级(G3 与 G1-2)、微血管侵犯(MVI)、总生存率(OS)和无进展生存率(PFS)。比较了联合临床-放射组学模型与标准临床模型的性能。

结果

共有 74 名患者(40 名女性,中位年龄 68 岁)入组。考虑到肿瘤分级和 MVI,与临床模型相比,结合肿瘤-VOI 临床数据和放射组学的模型具有更好的性能(分级的 AUC=0.78 与 0.72;MVI 的 AUC=0.87 与 0.78)。将边界-VOI 的放射组学纳入模型可进一步提高分级预测的准确性(AUC=0.83),但对 MVI 无影响。考虑 OS 和 PFS,包括术前临床数据和肿瘤-VOI 及边界-VOI 放射组学的模型优于纯临床模型(OS 的 C 指数=0.81 与 0.76;PFS 的 C 指数=0.81 与 0.72),与包括病理和术后数据的模型相当(OS 的 C 指数=0.81;PFS 的 C 指数=0.79)。没有模型保留了标准 SUV 测量值。

结论

基于 PET 的 IHC 放射组学可以预测病理数据,并允许对预后进行可靠的术前评估。肿瘤和肿瘤周围区域的放射组学均具有临床相关性。联合临床-放射组学模型优于纯术前临床模型,且与术后模型的性能相当。

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