Apparent Diffusion Coefficient as a Noninvasive Biomarker for the Early Response in Hepatocellular Carcinoma After
Basen Li1, Lei Zhou2, Anhui Xu1
1Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Background:
Prognostic evaluation for Hepatocellular Carcinoma (HCC) after Transcatheter Arterial Chemoembolization (TACE) using Drug-Eluting Beads (DEBs) is essential for guiding the personalized treatment and follow-up strategy. Apparent Diffusion Coefficient (ADC) has been reported as a biomarker in conventional TACE.
Objective:
This study aimed to evaluate the diagnostic value of ADCbaseline, ADC change, and ADCratio in predicting the early objective response for HCC after DEB-TACE.
Methods:
This prospective single-center study included 32 consecutive patients undergoing dynamic contrast-enhanced magnetic resonance imaging (MRI) and diffusion-weighted imaging before and 1 month after DEB-TACE. After DEB-TACE, patients were grouped based on the modified Response Evaluation Criteria in Solid Tumors (mRECIST) criteria into responders (complete response [CR], partial response [PR]) and nonresponders (stable disease [SD], progressive disease [PD]). The Mann- Whitney U test and receiver operating characteristic (ROC) curves were performed to assess the statistical differences in ADCbaseline, ADC change, and ADCratio between responders and nonresponders.
Results:
At post-DEB-TACE follow-up MRI, 62.5% (n = 20, 11 CRs, and 9 PRs) of patients showed objective response, and 37.5% (n = 12, 7 SDs, and 5 PDs) did not respond to chemoembolization. Nonresponders had a significantly higher ADCbaseline value than responders (p < 0.001). The ROC for identifying the response to chemoembolization demonstrated that the threshold ADCbaseline value of 0.920 × 10-3 mm2/s had 100% sensitivity and 70% specificity. The ADC change and ADCratio of responders were higher than that of nonresponders (p < 0.001).
Conclusion:
ADCbaseline, ADC change, and ADCratio may be utilized as a noninvasive biomarker for predicting the early response of HCC to DEB-TACE.
More Related Videos
04:09Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
Published on: October 10, 2018
15:48Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
