Magnetic resonance imaging parameter-based machine learning for prognosis prediction of high-intensity focused ultrasound ablation of uterine fibroids
Objectives: To develop and apply magnetic resonance imaging (MRI) parameter-based machine learning (ML) models to predict non-perfused volume (NPV) reduction and residual regrowth of uterine fibroids after high-intensity focused ultrasound (HIFU) ablation.Methods: MRI data of 573 uterine fibroids in...
Main Authors: | Jinwei Zhang, Chao Yang, Chunmei Gong, Ye Zhou, Chenghai Li, Faqi Li |
---|---|
Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2022-12-01
|
Series: | International Journal of Hyperthermia |
Subjects: | |
Online Access: | https://www.tandfonline.com/doi/10.1080/02656736.2022.2090622 |
Similar Items
-
Preliminary insights into high-intensity focused ultrasound ablation for symptomatic uterine fibroids: a first look in Egypt
by: Mohamed Fawzi, et al.
Published: (2024-02-01) -
Therapeutic Outcome of MR-Guided High-Intensity Focused Ultrasound (MR-HIFU) in Solitary versus Multiple Uterine Fibroids
by: Bernd Erber, et al.
Published: (2022-08-01) -
Prediction of postoperative reintervention risk for uterine fibroids using clinical-imaging features and T2WI radiomics before high-intensity focused ultrasound ablation
by: Shize Qin, et al.
Published: (2023-12-01) -
Prediction of non-perfusion volume ratio for uterine fibroids treated with ultrasound-guided high-intensity focused ultrasound based on MRI radiomics combined with clinical parameters
by: Ye Zhou, et al.
Published: (2023-12-01) -
Effect of Paracervical Block Before Ultrasound Guided High Intensity Focused Ultrasound Treatment in Uterine Fibroids and Adenomyosise
by: Jae-Seong Lee, et al.
Published: (2022-07-01)