Predictive factors for complete response of chemoembolization with drug-eluting beads (DEB-TACE) for hepatocellular
Guillaume Vesselle1, Camille Quirier-Leleu2, Stéphane Velasco3
1Diagnostic, Functional and Therapeutic Imaging Department, Poitiers University Hospital, 2 rue de la Milétrie, 86021, Poitiers Cedex, France. guillaumevesselle@gmail.com.
Objectives:
To identify clinical and imaging features associated with complete response (CR) to first session of transarterial chemoembolization (TACE) with drug-eluting beads (DEB) in patients with hepatocellular carcinoma.
Methods:
In this prospective historical cohort, 172 patients with 315 tumours who received at least one DEB-TACE from 2007 to 2013 were studied. Imaging response was evaluated according to the modified Response Evaluation Criteria in Solid Tumours (mRECIST). Age, gender, aetiology of cirrhosis, Child and BCLC scores, particles size, location in the liver, size of the tumour, presence of a capsule, hypervascularisation on DSA and CT/MRI scans, and blush extinction were analysed.
Results:
After one session of treatment, CR was observed in 36 % of the 315 tumours treated. Nodule size, location in the liver, and complete blush extinction on DSA was statistically correlated to complete response, whereas capsule aspect on imaging and demographic criteria were not. In multivariate analysis only, location in the liver and nodule size were significant features.
Conclusions:
Tumour location in the segments 1 and 4 is a pejorative factor for CR, whereas tumour size <5 cm is a positive predictive factor. These criteria could, therefore, be taken into consideration to improve the selection of patients for DEB-TACE.
Key Points:
• Literature on predictive factors of complete response after DEB-TACE is under-studied. • Tumour size <5 cm is associated with complete response. • Location in segments 1 or 4 is a pejorative factor for response. • No demographic parameter influences complete response.
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
09:11Y-90 Radioembolization and PD-1 Inhibitor as Neoadjuvant Treatment in Hepatocellular Carcinoma
Published on: May 24, 2024