TY - JOUR
T1 - Radiomics on gadoxetic acid-enhanced magnetic resonance imaging for prediction of postoperative early and late recurrence of single hepatocellular carcinoma
AU - Kim, Sungwon
AU - Shin, Jaeseung
AU - Kim, Do Young
AU - Choi, Gi Hong
AU - Kim, Myeong Jin
AU - Choi, Jin Young
N1 - Publisher Copyright:
© 2019 American Association for Cancer Research.
PY - 2019
Y1 - 2019
N2 - Purpose: To evaluate the usefulness of the radiomic model in predicting early (≤2 years) and late (>2 years) recurrence after curative resection in cases involving a single hepatocellular carcinoma (HCC) 2-5 cm in diameter using preoperative gadoxetic acid-enhanced magnetic resonance imaging (MRI), in comparison with the clinicopathologic model. Experimental Design: This retrospective study included 167 patients with surgically resected and pathologically confirmed single HCC 2-5 cm in diameter (n = 167, training set:validation set = 128:39) who underwent preoperative gadoxetic acid-enhanced MRI between January 2010 and December 2015. A radiomic model, a clinicopathologic model, and a combined clinicopathologic-radiomic (CCR) model were built using a random survival forest to predict disease-free survival (DFS) in the following conditions: early DFS versus late DFS, dynamic phases, and the peritumoral area included in the segmentation. Results: The radiomic model showed a prognostic performance comparable with the clinicopathologic model only with 3-mm peritumoral border extension [c-index difference (radiomic-clinicopathologic),-0.021, P = 0.758]. The CCR model with the 3-mm border extension showed the highest c-index value but no statistically significant improvement over the clinicopathologic model [CCR, 0.716 (0.627-0.799); clinicopathologic model, 0.696 (0.557-0.799)]. Conclusions: The prognostic value of the preoperative radiomic model with 3-mm border extension showed comparable performance with that of the postoperative clinicopathologic model for predicting DFS of early recurrence of HCC using gadoxetic acid-enhanced MRI. This suggests the importance of including peritumoral changes in the radiomic analysis of HCC.
AB - Purpose: To evaluate the usefulness of the radiomic model in predicting early (≤2 years) and late (>2 years) recurrence after curative resection in cases involving a single hepatocellular carcinoma (HCC) 2-5 cm in diameter using preoperative gadoxetic acid-enhanced magnetic resonance imaging (MRI), in comparison with the clinicopathologic model. Experimental Design: This retrospective study included 167 patients with surgically resected and pathologically confirmed single HCC 2-5 cm in diameter (n = 167, training set:validation set = 128:39) who underwent preoperative gadoxetic acid-enhanced MRI between January 2010 and December 2015. A radiomic model, a clinicopathologic model, and a combined clinicopathologic-radiomic (CCR) model were built using a random survival forest to predict disease-free survival (DFS) in the following conditions: early DFS versus late DFS, dynamic phases, and the peritumoral area included in the segmentation. Results: The radiomic model showed a prognostic performance comparable with the clinicopathologic model only with 3-mm peritumoral border extension [c-index difference (radiomic-clinicopathologic),-0.021, P = 0.758]. The CCR model with the 3-mm border extension showed the highest c-index value but no statistically significant improvement over the clinicopathologic model [CCR, 0.716 (0.627-0.799); clinicopathologic model, 0.696 (0.557-0.799)]. Conclusions: The prognostic value of the preoperative radiomic model with 3-mm border extension showed comparable performance with that of the postoperative clinicopathologic model for predicting DFS of early recurrence of HCC using gadoxetic acid-enhanced MRI. This suggests the importance of including peritumoral changes in the radiomic analysis of HCC.
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U2 - 10.1158/1078-0432.CCR-18-2861
DO - 10.1158/1078-0432.CCR-18-2861
M3 - Article
C2 - 30808773
AN - SCOPUS:85068563562
SN - 1078-0432
VL - 25
SP - 3847
EP - 3855
JO - Clinical Cancer Research
JF - Clinical Cancer Research
IS - 13
ER -