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Preoperative Microvascular Invasion Prediction to Assist in Surgical Plan for Single Hepatocellular Carcinoma: Better Together with Radiomics
Background Prediction models with or without radiomic analysis for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) have been reported, but the potential for model-predicted MVI in surgical planning is unclear. Therefore, we aimed to explore the effect of predicted MVI on early recurre...
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Published in: | Annals of surgical oncology 2022-05, Vol.29 (5), p.2960-2970 |
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Main Authors: | , , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Background
Prediction models with or without radiomic analysis for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) have been reported, but the potential for model-predicted MVI in surgical planning is unclear. Therefore, we aimed to explore the effect of predicted MVI on early recurrence after anatomic resection (AR) and non-anatomic resection (NAR) to assist surgical strategies.
Methods
Patients with a single HCC of 2–5 cm receiving curative resection were enrolled from 2 centers. Their data were used to develop (
n
= 230) and test (
n
= 219) two prediction models for MVI using clinical factors and preoperative computed tomography images. The two prediction models, clinico-radiologic model and clinico-radiologic-radiomic (CRR) model (clinico-radiologic variables + radiomic signature), were compared using the Delong test. Early recurrence based on model-predicted high-risk MVI was evaluated between AR (
n
= 118) and NAR (
n
= 85) via propensity score matching using patient data from another 2 centers for external validation.
Results
The CRR model showed higher area under the curve values (0.835–0.864 across development, test, and external validation) but no statistically significant improvement over the clinico-radiologic model (0.796–0.828). After propensity score matching, difference in 2-year recurrence between AR and NAR was found in the CRR model predicted high-risk MVI group (
P
= 0.005) but not in the clinico-radiologic model predicted high-risk MVI group (
P
= 0.31).
Conclusions
The prediction model incorporating radiomics provided an accurate preoperative estimation of MVI, showing the potential for choosing the more appropriate surgical procedure between AR and NAR. |
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ISSN: | 1068-9265 1534-4681 |
DOI: | 10.1245/s10434-022-11346-1 |