Article Sidebar
Views pdf: 36
EVALUATION OF THE VALUE OF AUTOMATIC SOFTWARE IN IDENTIFYING THE ARTERIAL SUPPLY FOR CHEMOEMBOLIZATION IN THE TREATMENT OF HEPATOCELLULAR CARCINOMA
Main Article Content
Abstract
Objective: To evaluate the use of automated feeder detection software – AFD in the accurate detection of feeding arteries for HCC, and how its use affects radiation exposure time, radiation dose, and the amount of contrast agent used in transarterial chemoembolization (TACE). Subjects and Methods: A descriptive prospection, controlled study. The research group consisted of 14 patients with 18 lesions of hepatocellular carcinoma (HCC) indicated for transarterial chemoembolization (TACE), and a control group of 16 patients with 18 HCC lesions. TACE in the study group was performed on an angiography machine with AFD software for automatic identification of feeding vessels (Emboguide; Siemens Healthineers, Germany), while the control group underwent TACE on a similar angiography machine (Artis Q, Siemens, Germany) without AFD software. Results: The correct detection rate of the feeding branches by AFD software was 64.3%. The radiation exposure time and average contrast agent volume in the study group were less than those in the control group. The radiation dose was higher in the AFD group compared to the control group. Conclusion: AFD software and CBCT provide additional information about the feeding vessels of the tumor, allowing for more targeted and effective embolization, especially for small tumors where feeding vessels are difficult to detect on conventional DSA. The radiation exposure time and contrast agent volume were lower. Larger studies are needed.
Article Details
Keywords
: transarterial chemoembolization, emboguidance software, feeding artery detection for HCC
References
2. Shukla S, Chug A, Afrashtehfar K. Role of cone beam computed tomography in diagnosis and treatment planning in dentistry: An update. J Int Soc Prevent Communit Dent. 2017;7(9):125.
3. Tacher V, Radaelli A, Lin M. How I Do It: Cone-Beam CT during Transarterial Chemoembolization for Liver Cancer. Radiology. 2015;274(2):320-334.
4. Iwazawa J, Ohue S, Hashimoto N. Clinical utility and limitations of tumor-feeder detection software for liver cancer embolization. European Journal of Radiology. 2013;82(10):1665-1671.
5. Miyayama S. Ultraselective conventional transarterial chemoembolization: When and how? Clin Mol Hepatol. 2019;25(4):344-353.
6. Chiaradia M, Izamis ML, Radaelli A. Sensitivity and Reproducibility of Automated Feeding Artery Detection Software during Transarterial Chemoembolization of Hepatocellular Carcinoma. Journal of Vascular and Interventional Radiology. 2018;29(3):425-431.
7. Miyayama S, Yamashiro M, Ikuno M. Ultraselective transcatheter arterial chemoembolization for small hepatocellular carcinoma guided by automated tumor-feeders detection software: technical success and short-term tumor response. Abdom Imaging. 2014;39(3):645-656.
8. Cornelis FH, Borgheresi A, Petre EN. Hepatic Arterial Embolization Using Cone Beam CT with Tumor Feeding Vessel Detection Software: Impact on Hepatocellular Carcinoma Response. Cardiovasc Intervent Radiol. 2018;41(1):104-111.
9. Abdelsalam H, Emara DM, Hassouna EM. The efficacy of TACE; how can automated feeder software help? Egypt J Radiol Nucl Med. 2022;53(1):43.
10. Deschamps F, Solomon SB, Thornton RH. Computed Analysis of Three-Dimensional Cone-Beam Computed Tomography Angiography for Determination of Tumor-Feeding Vessels During Chemoembolization of Liver Tumor: A Pilot Study. Cardiovasc Intervent Radiol. 2010;33(6):1235-1242.