Prediction of microvascular invasion in HCC by a scoring model combining Gd-EOB-DTPA MRI and biochemical indicators

Kun Zhang; Shuang-Shuang Xie; Wen-Cui Li; Zhao-Xiang Ye; Zhi-Wei Shen; Wen Shen

doi:10.1007/s00330-021-08502-8

Prediction of microvascular invasion in HCC by a scoring model combining Gd-EOB-DTPA MRI and biochemical indicators

Eur Radiol. 2022 Jun;32(6):4186-4197. doi: 10.1007/s00330-021-08502-8. Epub 2022 Jan 20.

Authors

Kun Zhang¹, Shuang-Shuang Xie², Wen-Cui Li³, Zhao-Xiang Ye³, Zhi-Wei Shen⁴, Wen Shen⁵

Affiliations

¹ Department of Radiology, First Central Clinical College, Tianjin Medical University, 22 Qixiangtai Road, Heping District, Tianjin, 300070, China.
² Department of Radiology, Tianjin Medical Imaging Institute, School of Medicine, Tianjin First Central Hospital, Nankai University, Nankai District, No. 24 Fukang Road, Tianjin, 300192, China.
³ Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China.
⁴ Philips Healthcare, The World Profit Centre, No. 16 Tianze Road, Chaoyang District, Beijing, 100125, China.
⁵ Department of Radiology, Tianjin Medical Imaging Institute, School of Medicine, Tianjin First Central Hospital, Nankai University, Nankai District, No. 24 Fukang Road, Tianjin, 300192, China. shen_hos@163.com.

PMID: 35048134
DOI: 10.1007/s00330-021-08502-8

Abstract

Objectives: This study aimed to establish a reliable diagnostic scoring model for the preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients based on gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) and biochemical indicators.

Methods: This retrospective study included 129 patients with HCC at our hospital from 2014 to 2020. Based on the intratumoral and peritumoral features on Gd-EOB-DTPA MRI and biochemical indicators, a scoring model was developed for preoperative prediction of MVI, and examined for diagnostic efficacy according to postoperative pathological results. The scoring model was further externally validated in an independent cohort of 63 HCC patients.

Results: Logistic regression analysis was performed to identify five parameters related to MVI, including maximum tumor diameter, peritumoral low intensity in the hepatobiliary phase, incomplete capsule, apparent diffusion coefficient (ADC), and [alkaline phosphatase (ALP) (U/L) + gamma-glutamyl transpeptidase (GGT) (U/L)] / lymphocyte count (× 10⁹/L) ratio (AGLR). Based on these five parameters, a scoring model was developed, and the accuracy, sensitivity, specificity, PPV, and NPV in predicting MVI were 93.6%, 94.7%, 93.2%, 85.7%, and 97.6%, respectively, with a score > 8 set as the threshold.

Conclusion: The scoring model based on Gd-EOB-DTPA MRI and biochemical indicators provides a reliable tool for preoperative prediction of MVI in HCC patients.

Key points: • The scoring model based on Gd-EOB-DTPA MRI and biochemical indicators is practical for preoperative prediction of MVI in HCC patients. • AGLR is an independent risk factor for MVI. • The scoring model could help implement more appropriate interventions, potentially leading to precise and individualized treatments based on the biological characteristics of the tumor.

Keywords: Biomarkers; Hepatocellular carcinoma; Magnetic resonance imaging; Neoplasm invasion; Statistical model.

MeSH terms

Carcinoma, Hepatocellular* / pathology
Contrast Media
Gadolinium DTPA
Humans
Liver Neoplasms* / pathology
Magnetic Resonance Imaging / methods
Retrospective Studies

Substances

Contrast Media
gadolinium ethoxybenzyl DTPA
Gadolinium DTPA