Radiomics Models for Predicting Microvascular Invasion in Hepatocellular Carcinoma: A Systematic Review and Radiomics Quality Score Assessment - PubMed (original) (raw)

Review

Radiomics Models for Predicting Microvascular Invasion in Hepatocellular Carcinoma: A Systematic Review and Radiomics Quality Score Assessment

Qiang Wang et al. Cancers (Basel). 2021.

Abstract

Preoperative prediction of microvascular invasion (MVI) is of importance in hepatocellular carcinoma (HCC) patient treatment management. Plenty of radiomics models for MVI prediction have been proposed. This study aimed to elucidate the role of radiomics models in the prediction of MVI and to evaluate their methodological quality. The methodological quality was assessed by the Radiomics Quality Score (RQS), and the risk of bias was evaluated by the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). Twenty-two studies using CT, MRI, or PET/CT for MVI prediction were included. All were retrospective studies, and only two had an external validation cohort. The AUC values of the prediction models ranged from 0.69 to 0.94 in the test cohort. Substantial methodological heterogeneity existed, and the methodological quality was low, with an average RQS score of 10 (28% of the total). Most studies demonstrated a low or unclear risk of bias in the domains of QUADAS-2. In conclusion, a radiomics model could be an accurate and effective tool for MVI prediction in HCC patients, although the methodological quality has so far been insufficient. Future prospective studies with an external validation cohort in accordance with a standardized radiomics workflow are expected to supply a reliable model that translates into clinical utilization.

Keywords: microvascular invasion; prediction model; primary liver cancer; radiomics; systematic review.

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Conflict of interest statement

The authors have declared that there is no conflict of interest.

Figures

Figure 1

Figure 1

A typical workflow of radiomics research for microvascular invasion (MVI) prediction in hepatocellular carcinoma.

Figure 2

Figure 2

Flow chart of the study selection.

Figure 3

Figure 3

Methodological quality evaluated by using the Radiomics Quality Score (RQS) tool. (A). Proportion of studies with different RQS percentage score. (B). Average scores of each RQS item (gray bars stand for the full points of each item, and red bars show actual points).

Figure 4

Figure 4

Grouped bar charts of the risk of bias (A) and applicability concerns (B) of the included studies assessed by using a revised tool for the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2).

References

    1. Sheng X., Ji Y., Ren G.P., Lu C.L., Yun J.P., Chen L.H., Meng B., Qu L.J., Duan G.J., Sun Q., et al. A standardized pathological proposal for evaluating microvascular invasion of hepatocellular carcinoma: A multicenter study by LCPGC. Hepatol. Int. 2020;14:1034–1047. doi: 10.1007/s12072-020-10111-4. - DOI - PubMed
    1. Hong S.B., Choi S.H., Kim S.Y., Shim J.H., Lee S.S., Byun J.H., Park S.H., Kim K.W., Kim S., Lee N.K. MRI Features for Predicting Microvascular Invasion of Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis. Liver Cancer. 2021;10:94–106. doi: 10.1159/000513704. - DOI - PMC - PubMed
    1. Lei Z., Li J., Wu D., Xia Y., Wang Q., Si A., Wang K., Wan X., Lau W.Y., Wu M., et al. Nomogram for Preoperative Estimation of Microvascular Invasion Risk in Hepatitis B Virus-Related Hepatocellular Carcinoma Within the Milan Criteria. JAMA Surg. 2016;151:356–363. doi: 10.1001/jamasurg.2015.4257. - DOI - PubMed
    1. Lee S., Kim S.H., Lee J.E., Sinn D.H., Park C.K. Preoperative gadoxetic acid-enhanced MRI for predicting microvascular invasion in patients with single hepatocellular carcinoma. J. Hepatol. 2017;67:526–534. doi: 10.1016/j.jhep.2017.04.024. - DOI - PubMed
    1. Zhang T., Pandey G., Xu L., Chen W., Gu L., Wu Y., Chen X. The Value of TTPVI in Prediction of Microvascular Invasion in Hepatocellular Carcinoma. Cancer Manag. Res. 2020;12:4097–4105. doi: 10.2147/CMAR.S245475. - DOI - PMC - PubMed

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