Optimization of MR-Guided Focused Ultrasound System: Comparative Study of Water Bolus and Electrically Optimized Material Using Automated Machine Learning

IF 3 4区计算机科学 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Imaging Systems and Technology Pub Date : 2025-03-10 DOI:10.1002/ima.70061

Eunwoo Lee, Taewoo Nam, Daniel Hernandez, Eugene Ozhinsky, Kazim Narsinh, Leo Sugrue, Yeji Han, Kisoo Kim, Kyoung-Nam Kim

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引用次数: 0

Abstract

Magnetic resonance-guided focused ultrasound (MRgFUS) is a therapeutic technology designed for the treatment of neurological disorders, enabling precise focal heating under magnetic resonance imaging (MRI) guidance. However, electromagnetic (EM) interaction between the radiofrequency (RF) coil and the MRgFUS system leads to increased specific absorption rate (SAR), reduced RF transmit magnetic (|B₁⁺|)-field homogeneity, and decreased signal-to-noise ratio (SNR). In this study, we compared a conventional water bolus containing sodium chloride and sterile water with an electrically optimized material (EOM) optimized using an automated machine learning (Auto-ML) approach to minimize SAR while maximizing |B₁⁺|-field quality. EM simulation results demonstrated that our EOM achieved significant improvements in |B₁⁺|-field homogeneity and a reduction in peak spatial SAR averaged over 10 g (psSAR_10g) compared to the conventional water bolus. These findings suggest that Auto-ML-based EOM can enhance the safety and efficiency of MRgFUS procedures.

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来源期刊

International Journal of Imaging Systems and Technology 工程技术-成像科学与照相技术

CiteScore

6.90

自引率

6.10%

发文量

138

审稿时长

3 months

期刊介绍： The International Journal of Imaging Systems and Technology (IMA) is a forum for the exchange of ideas and results relevant to imaging systems, including imaging physics and informatics. The journal covers all imaging modalities in humans and animals. IMA accepts technically sound and scientifically rigorous research in the interdisciplinary field of imaging, including relevant algorithmic research and hardware and software development, and their applications relevant to medical research. The journal provides a platform to publish original research in structural and functional imaging. The journal is also open to imaging studies of the human body and on animals that describe novel diagnostic imaging and analyses methods. Technical, theoretical, and clinical research in both normal and clinical populations is encouraged. Submissions describing methods, software, databases, replication studies as well as negative results are also considered. The scope of the journal includes, but is not limited to, the following in the context of biomedical research: Imaging and neuro-imaging modalities: structural MRI, functional MRI, PET, SPECT, CT, ultrasound, EEG, MEG, NIRS etc.; Neuromodulation and brain stimulation techniques such as TMS and tDCS; Software and hardware for imaging, especially related to human and animal health; Image segmentation in normal and clinical populations; Pattern analysis and classification using machine learning techniques; Computational modeling and analysis; Brain connectivity and connectomics; Systems-level characterization of brain function; Neural networks and neurorobotics; Computer vision, based on human/animal physiology; Brain-computer interface (BCI) technology; Big data, databasing and data mining.