Share:
Peer-Reviewed Publication
PLoS One2025;20(1):e0317469.January 1, 2025Journal Article

Retrospective evaluation of a novel ultrasound-based imaging analysis software for predicting radiofrequency ablation areas.

Masaya Sato1,2, Ryosuke Tateishi2, Yogev Zohar3, Jiro Sato4, Takeyuki Watadani5, Makoto Moriyama2, Taijiro Wake2, Ryo Nakagomi2, Mizuki Nishibatake Kinoshita2, Takuma Nakatsuka2, Tatsuya Minami2, Koji Uchino2, Kenichiro Enooku2, Hayato Nakagawa2,6, Yoshinari Asaoka2,7, Ryo Yamada8, Nitzan Even3, Inbal Amitai3, Yossi Abu3, Mitsuhiro Fujishiro2, Kazuhiko Koike2
1Department of Clinical Laboratory Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
2Department of Gastroenterology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
3TechsoMed Medical Technologies Ltd., Rehovot, Israel.
4Department of Radiology, Tokyo Metropolitan Police Hospital, Tokyo, Japan.
5Department of Radiology, The University of Tokyo, Tokyo, Japan.
6Department of Gastroenterology and Hepatology Mie University Graduate School of Medicine, Mie, Japan.
7Department of Medicine, Teikyo University School of Medicine, Tokyo, Japan.
8Development Department 2, SCREEN Advanced System Solutions Co., Ltd, Kyoto, Japan.

Abstract

OBJECTIVE: This study aimed to introduce and evaluate a novel software-based system, BioTrace, designed for real-time monitoring of thermal ablation tissue damage during image-guided radiofrequency ablation for hepatocellular carcinoma (HCC). METHODS: BioTrace utilizes a proprietary algorithm to analyze the temporo-spatial behavior of thermal gas bubble activity during ablation, as seen in conven…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.