Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma via Multi-Parametric MRI Radiomics

Zhang, Yang; Shu, Zhenyu; Ye, Qin; Chen, Junfa; Zhong, Jianguo; Jiang, Hongyang; Wu, Cuiyun; Yu, Tao; Pang, Peipei; Lin, Chunmiao

doi:10.3389/fonc.2021.633596

Cited by 20 publications

(14 citation statements)

References 38 publications

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“…However, the results of our meta-analysis showed that the combination of clinical risk factors with radiomics did not improve the diagnostic ability. This indicates that radiomics alone could also achieve high diagnostic performance, which was consistent with the results of other previous studies ( 14 , 19 , 33 ).…”

Section: Discussionsupporting

confidence: 92%

Radiomics for the Preoperative Evaluation of Microvascular Invasion in Hepatocellular Carcinoma: A Meta-Analysis

Huang

et al. 2022

Front. Oncol.

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BackgroundMicrovascular invasion (MVI) is an independent risk factor for postoperative recurrence of hepatocellular carcinoma (HCC). To perform a meta-analysis to investigate the diagnostic performance of radiomics for the preoperative evaluation of MVI in HCC and the effect of potential factors.Materials and MethodsA systematic literature search was performed in PubMed, Embase, and the Cochrane Library for studies focusing on the preoperative evaluation of MVI in HCC with radiomics methods. Data extraction and quality assessment of the retrieved studies were performed. Statistical analysis included data pooling, heterogeneity testing and forest plot construction. Meta-regression and subgroup analyses were performed to reveal the effect of potential explanatory factors [design, combination of clinical factors, imaging modality, number of participants, and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) applicability risk] on the diagnostic performance.ResultsTwenty-two studies with 4,129 patients focusing on radiomics for the preoperative prediction of MVI in HCC were included. The pooled sensitivity, specificity and area under the receiver operating characteristic curve (AUC) were 84% (95% CI: 81, 87), 83% (95% CI: 78, 87) and 0.90 (95% CI: 0.87, 0.92). Substantial heterogeneity was observed among the studies (I²=94%, 95% CI: 88, 99). Meta-regression showed that all investigative covariates contributed to the heterogeneity in the sensitivity analysis (P < 0.05). Combined clinical factors, MRI, CT and number of participants contributed to the heterogeneity in the specificity analysis (P < 0.05). Subgroup analysis showed that the pooled sensitivity, specificity and AUC estimates were similar among studies with CT or MRI.ConclusionRadiomics is a promising noninvasive method that has high preoperative diagnostic performance for MVI status. Radiomics based on CT and MRI had a comparable predictive performance for MVI in HCC. Prospective, large-scale and multicenter studies with radiomics methods will improve the diagnostic power for MVI in the future.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=259363, identifier CRD42021259363.

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Section: Discussionsupporting

confidence: 92%

Radiomics for the Preoperative Evaluation of Microvascular Invasion in Hepatocellular Carcinoma: A Meta-Analysis

Huang

et al. 2022

Front. Oncol.

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“…The systematic literature search initially yielded 188 records from the four databases. After removing 82 duplicates, 50 inappropriate types of publications, and 34 ineligible studies, a total of 22 studies were included in this systematic review [ 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 ] ( Figure 2 ).…”

Section: Resultsmentioning

confidence: 99%

“…It is worth mentioning that the reproducibility evaluation of imaging features can also be used for feature selection. Among the 10 studies that performed interclass correlation coefficient (ICC) analysis, 4 of them set a threshold of 0.8 for robust features and selected those for further analysis [ 32 , 38 , 40 , 41 ].…”

Section: Resultsmentioning

confidence: 99%

“…Two studies validated their models using an independent cohort with AUCs of 0.84 and 0.80 [ 29 , 31 ]. Only five studies reported the cut-off value when presenting the performance metrics [ 21 , 26 , 32 , 34 , 41 ]. Nine studies (9/22) evaluated the calibrated ability of their model in the form of a calibration curve and clinical usefulness of the model in the form of decision curve analysis.…”

Section: Resultsmentioning

confidence: 99%

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

Wang

Zhang

et al. 2021

Cancers

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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.

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“…Mulé et al [ 15 ] studied the degree of gadobenate dimeglubine enhancement in the tumor during the delayed hepatobiliary phase and concluded that a lesion-to-liver contrast enhancement ratio of −4.72% or less could accurately predict MVI and moderate-poor differentiation grade in an HCC while the work by Ahn et al [ 16 ] revealed that the peritumoral enhancement of gadoxetic acid may suggest MVI. However, conventional imaging techniques (CT and MRI) still face several difficulties in predicting tumor biology although the recent introduction of a radiomics evaluation on MRI could help overcome a few of these limitations [ 17 ]. In this fashion, a recently published systematic review and meta-analysis [ 8 ] compared radiomics and non-radiomics features in different imaging techniques to predict MVI before an HCC surgery.…”

Section: Discussionmentioning

confidence: 99%

2-[18F]FDG PET/CT as a Predictor of Microvascular Invasion and High Histological Grade in Patients with Hepatocellular Carcinoma

Sabaté‐Llobera

Mestres-Martí

Reynés-Llompart

et al. 2021

Cancers

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Hepatocellular carcinoma (HCC) generally presents a low avidity for 2-deoxy-2-[18F]fluoro-d-glucose (FDG) in PET/CT although an increased FDG uptake seems to relate to more aggressive biological factors. To define the prognostic value of PET/CT with FDG in patients with an HCC scheduled for a tumor resection, forty-one patients were prospectively studied. The histological factors of a poor prognosis were determined and FDG uptake in the HCC lesions was analyzed semi-quantitatively (lean body mass-corrected standardized uptake value (SUL) and tumor-to-liver ratio (TLR) at different time points). The PET metabolic parameters were related to the histological characteristics of the resected tumors and to the evolution of patients. Microvascular invasion (MVI) and a poor grade of differentiation were significantly related to a worse prognosis. The SULpeak of the lesion 60 min post-FDG injection was the best parameter to predict MVI while the SULpeak of the TLR at 60 min was better for a poor differentiation. Moreover, the latter parameter was also the best preoperative variable available to predict any of these two histological factors. Patients with an increased TLRpeak60 presented a significantly higher incidence of poor prognostic factors than the rest (75% vs. 28.6%, p = 0.005) and a significantly higher incidence of recurrence at 12 months (38% vs. 0%, p = 0.014). Therefore, a semi-quantitative analysis of certain metabolic parameters on PET/CT can help identify, preoperatively, patients with histological factors of a poor prognosis, allowing an adjustment of the therapeutic strategy for those patients with a higher risk of an early recurrence.

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Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma via Multi-Parametric MRI Radiomics

Cited by 20 publications

References 38 publications

Radiomics for the Preoperative Evaluation of Microvascular Invasion in Hepatocellular Carcinoma: A Meta-Analysis

Radiomics for the Preoperative Evaluation of Microvascular Invasion in Hepatocellular Carcinoma: A Meta-Analysis

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

2-[18F]FDG PET/CT as a Predictor of Microvascular Invasion and High Histological Grade in Patients with Hepatocellular Carcinoma

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