Hepatocellular carcinoma response to transcatheter arterial chemoembolisation using automatically generated
A M Khalaf1, D Fuentes1, A Morshid1
1Department of Imaging Physics, The University of Texas Anderson Cancer Center, Houston, TX 77030, USA.
Aim:
To demonstrate the feasibility of correlating pre-therapeutic volumes and residual liver volume (RLV) with clinical outcomes: time to progression (TTP) and overall survival (OS) in hepatocellular carcinoma (HCC) treated with transcatheter arterial chemoembolisation (TACE).
Materials And Methods:
TTP was calculated from a database of 105 patients, receiving first-line treatment with TACE. TTP cut-off for stratifying patients into responders and non-responders was 28 weeks. Pre-treatment tumour and liver volumes were correlated with the TTP and OS following treatment. Univariate cox-regression model was used to assess whether these volumes could predict TTP and/or OS. Kaplan-Meier analysis with log-rank test was used to compare the TTP between high and low volume groups for viable, necrotic, and total tumour. Kaplan-Meier analysis was performed comparing the OS of 10 patients with the longest TTP (mean=122 weeks) in the responder group and 10 patients with the shortest TTP (mean=7 weeks) in the non-responder group.
Results:
HCC in high tumour volume groups had a shorter TTP than lesions in low tumour volume groups (p=0.05, p=0.04, p=0.02, for enhancing, non-enhancing, total tumour groups, respectively). A negative (correlation coefficient [CC] 0.3) linear correlation between TTP and tumour volumes, and a positive linear correlation between TTP and residual liver volumes were also demonstrated (CC 0.3). Patients with the longest TTP had a higher OS than with the shortest TTP (p=0.03).
Conclusion:
This demonstrates the feasibility of predicting treatment response of HCC to TACE using volumetric measurements of pre-treatment lesion and the feasibility of correlating RLV with TACE outcome data in HCC patients.
Related Concept Videos
04:09Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
08:25Mass Cytometry Analysis of Systemic and Local Immune Responses in Hepatocellular Carcinoma
10:35Generation of Subcutaneous and Intrahepatic Human Hepatocellular Carcinoma Xenografts in Immunodeficient Mice
09:49Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization
08:16Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
05:06A "Patient-Like" Orthotopic Syngeneic Mouse Model of Hepatocellular Carcinoma Metastasis


