• Chao Yang, Jing Guo, Li Chen, Luping Zhang, Lian Zhang, Kequan Li, Jinyun Chen, and Wenzhi Chen.
• State Key Laboratory of Ultrasound in Medicine and Engineering, College of Biomedical Engineering, Chongqing Medical University, Chongqing, China.
• Medicine (Baltimore). 2023 Sep 22; 102 (38): e34684e34684.

AbstractTo analyze the influencing factors of energy efficiency factors (EEF) in focused ultrasound ablation surgery (FUAS) for unresectable pancreatic cancer and build a dosimetry model. The patients with unresectable pancreatic cancer that underwent FUAS were enrolled from 3 clinical centers between June 2015 and June 2022 for retrospective analysis. The significance of the factors with the potential to affect the EEF was assessed, correlations among the factors were analyzed, and the accuracy of the prediction models established by the factors containing different imaging features was compared. From a total of 236 cases, 215 cases were screened for study, EEF was significantly correlated with mode of anesthesia, grayscale change, tumor volume, tumor location, the distance from the tumor center to skin, contrast-enhanced computer tomography enhancement type, T2-weighted imaging fat suppression signal intensity and contrast-enhanced T1-weighted imaging enhancement type on magnetic resonance imaging. The resultant multiple regression models of EEF achieved significance, contains predictors of Tumor volume, the distance from tumor center to skin, T2-weighted imaging fat suppression signal intensity, and contrast-enhanced T1-weighted imaging enhancement type had better goodness of fit. Compared with CT, the EEF prediction model established by adding magnetic resonance imaging features showed better prediction in FUAS treatment of unresectable pancreatic cancer.Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc.

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