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Determination of prognostic predictors in patients with solitary hepatocellular carcinoma: histogram analysis of multiparametric MRI

  • Hepatobiliary
  • Published:
Abdominal Radiology Aims and scope

Abstract

Purpose

To evaluate the histogram parameters of preoperative multiparametric magnetic resonance imaging (MRI) and clinical-radiological (CR) characteristics as prognostic predictors in patients with solitary hepatocellular carcinoma ≤ 5 cm and to determine the optimal time window for histogram analysis.

Methods

We retrospectively included 151 patients who underwent preoperative MRI between January 2012 and December 2017. All patients were randomly separated into training and validation cohorts (n = 105 and 46). Eight whole-lesion histogram parameters were extracted from T2-weighted images, apparent diffusion coefficient maps, and dynamic contrast-enhanced images. Univariate and multivariate logistic regression analyses were performed to evaluate these histogram parameters and CR variables related to early recurrence (ER) and recurrence-free survival. A nomogram was derived from the clinical-radiological-histogram (CRH) model that incorporated these risk factors. Kaplan–Meier survival analysis was performed to evaluate the prognostic performance of the CRH model.

Results

In total, 151 patients (male: female, 130: 21; median age, 54.46 ± 9.09 years) were evaluated. Multivariate logistic regression analysis revealed that the significant risk factors of ER were Mean Absolute Deviation and Minimum in the histogram analysis of the delayed phase images, as well as three important CR variables: albumin-bilirubin grade, microvascular invasion, and tumor size. The nomogram built by incorporating these risk factors showed satisfactory predictive ability in the training and validation cohorts with AUC values of 0.747 and 0.765, respectively. Furthermore, the prognostic nomogram can effectively classify patients into high- and low-risk groups (p < 0.05).

Conclusion

Multiparametric MRI-derived histogram parameters provide additional value in predicting patient prognosis. The CRH model may be a useful and noninvasive method for achieving prognostic stratification and personalized disease management.

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Abbreviations

ADC:

Apparent diffusion coefficient

ALBI:

Albumin-bilirubin

APHE:

Arterial phase hyperenhancement

AP:

Arterial phase

AUC:

Area under the curve

CI:

Confidence interval

CR:

Clinical-radiological

CRH:

Clinical-radiological-histogram

DP:

Delayed phase

DWI:

Diffusion-weighted imaging

ER:

Early recurrence

HCC:

Hepatocellular carcinoma

ICC:

Interclass correlation coefficient

LI-RADS:

Liver imaging reporting and data system

MAD:

Mean absolute deviation

MRI:

Magnetic resonance imaging

MVI:

Microvascular invasion

OR:

Odds ratio

PVP:

Portal venous phase

ROC:

Receiver operating characteristic

RFS:

Recurrence-free survival

VOI:

Volume of interest

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Acknowledgements

This study is supported by the National Key Research and Development Program of China (No. 2020AAA0109503).

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Author notes

  1. Leyao Wang, Rong Cong and Zhaowei Chen have contributed equally to this work.

  2. Xiaohong Ma and Xinming Zhao have contributed equally to this work.

Authors and Affiliations

  1. Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China

    Leyao Wang, Rong Cong, Zhaowei Chen, Dengfeng Li, Bing Feng, Meng Liang, Xiaohong Ma & Xinming Zhao

  2. Magnetic Resonance Imaging Research, General Electric Healthcare (China), Beijing, 100176, China

    Sicong Wang

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  1. Leyao Wang
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Wang, L., Cong, R., Chen, Z. et al. Determination of prognostic predictors in patients with solitary hepatocellular carcinoma: histogram analysis of multiparametric MRI. Abdom Radiol 48, 3362–3372 (2023). https://doi.org/10.1007/s00261-023-04015-8

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