Role of dynamic contrast enhanced MRI and Diffusion Weighted Imaging in Prediction of Tumor Response to TACE in Unresectable H.C.C Patients

Abstract

Background: To evaluate the role of MRI in the detection of recurrent or residual tumor viability in prediction of the response of the irresectable HCC patients who had locally treated with TACE by studying the enhancement (vascularity) pattern and the volume changes of the HCC after TACE. We were also aiming to improve the technique and to standardize MR protocol to be used after interventional therapy for malignant hepatic tumors. Results: The study group consisted of 20 patients and the results were analyzed as 31 treated hepatic focal lesions. The patients underwent DCE MRI with DWI in one / three months duration following TACE procedure and were radiologically assessed to observe tumoral post treatment response for non-viable, viable post treatment response categories Statistical analysis showed that dynamic MRI had 100% level of sensitivity, specificity of 88.89 %, PPV of 91.67% and NPV of 100% with an overall agreement of 95%. While on the other hand, statistics showed that DWI has 81.82 % level of sensitivity, specificity of 88.9%, PPV of 90%, NPV of 80% with an overall agreement of 85%. The difference between non-viable and viable groups' ADC variables was found statistically significant at P value < 0.018 and best cut off value that augments sensitivity and specificity is 1.24. At this ADC value, showed 90.91% level of sensitivity, specificity of 87.5%, PPV of 90.9%, NPV of 87.50% with an overall agreement of 79.5%. Conclusion: Dynamic contrast enhanced MRI is a powerful tool in detection of tumour viability and complications after TACE of hepatocellular carcinoma. Imaging protocol should include dynamic study combined with diffusion imaging with post processing of the images to obtain ADC measurements for better tissue characterization and should be performed at regular time intervals to enhance the diagnostic confidence of MRI for post treatment response viability detection.