{"title":"基于学习的机器人辅助mri引导低/高强度聚焦超声治疗的快速相位像差校正和控制","authors":"Jing Dai, Xiaomei Wang, Bohao Zhu, Liyuan Liang, Hing-Chiu Chang, James Lam, Xiaochen Xie, Ka-Wai Kwok","doi":"10.1002/rob.22606","DOIUrl":null,"url":null,"abstract":"<p>Magnetic resonance imaging (MRI)-guided focused ultrasound (MRg-FUS) is an effective and noninvasive procedure for treating diseases such as neurological disorders. Phase adjustment on ultrasound transducers can only achieve a limited focal-spot steering range. When treating large abdominopelvic targets, mechanical adjustment on the transducers' position and orientation is the prerequisite for enlarging the steering range. Therefore, we previously designed an MRI-guided robot to manipulate the transducers to offer sufficient focal-spot movement range. This could provide more modulation solutions to constructive ultrasound interference. However, full-wave ultrasound propagation inside a patient's heterogeneous abdominal media is complex and nonlinear, posing significant challenges in ultrasound modulation and beam motion control. Here, we propose a novel learning-based phase-aberration correction and model-free control framework for robot-assisted MRg-FUS treatments. The correction policy guarantees rapid aberration compensation within 5.0 ms. Submillimeter refocusing accuracy is achieved in both the liver (0.32 mm) and pancreas (0.51 mm), meeting clinical requirements for focal targeting. Our controller can accommodate nonlinear phase actuation with fast convergence (< 5.7 ms) and ensure accurate positional tracking with a mean error of 0.26 mm, without prior knowledge of inhomogeneous media. Compared with the conventional model-based method, it contributes to 61.77%–70.39% mean error reduction without requiring model parameter tuning.</p>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 7","pages":"3935-3951"},"PeriodicalIF":5.2000,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rob.22606","citationCount":"0","resultStr":"{\"title\":\"Learning-Based Rapid Phase-Aberration Correction and Control for Robot-Assisted MRI-Guided Low-/High-Intensity Focused Ultrasound Treatments\",\"authors\":\"Jing Dai, Xiaomei Wang, Bohao Zhu, Liyuan Liang, Hing-Chiu Chang, James Lam, Xiaochen Xie, Ka-Wai Kwok\",\"doi\":\"10.1002/rob.22606\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Magnetic resonance imaging (MRI)-guided focused ultrasound (MRg-FUS) is an effective and noninvasive procedure for treating diseases such as neurological disorders. Phase adjustment on ultrasound transducers can only achieve a limited focal-spot steering range. When treating large abdominopelvic targets, mechanical adjustment on the transducers' position and orientation is the prerequisite for enlarging the steering range. Therefore, we previously designed an MRI-guided robot to manipulate the transducers to offer sufficient focal-spot movement range. This could provide more modulation solutions to constructive ultrasound interference. However, full-wave ultrasound propagation inside a patient's heterogeneous abdominal media is complex and nonlinear, posing significant challenges in ultrasound modulation and beam motion control. Here, we propose a novel learning-based phase-aberration correction and model-free control framework for robot-assisted MRg-FUS treatments. The correction policy guarantees rapid aberration compensation within 5.0 ms. Submillimeter refocusing accuracy is achieved in both the liver (0.32 mm) and pancreas (0.51 mm), meeting clinical requirements for focal targeting. Our controller can accommodate nonlinear phase actuation with fast convergence (< 5.7 ms) and ensure accurate positional tracking with a mean error of 0.26 mm, without prior knowledge of inhomogeneous media. Compared with the conventional model-based method, it contributes to 61.77%–70.39% mean error reduction without requiring model parameter tuning.</p>\",\"PeriodicalId\":192,\"journal\":{\"name\":\"Journal of Field Robotics\",\"volume\":\"42 7\",\"pages\":\"3935-3951\"},\"PeriodicalIF\":5.2000,\"publicationDate\":\"2025-06-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rob.22606\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Field Robotics\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/rob.22606\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ROBOTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Field Robotics","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/rob.22606","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ROBOTICS","Score":null,"Total":0}
Learning-Based Rapid Phase-Aberration Correction and Control for Robot-Assisted MRI-Guided Low-/High-Intensity Focused Ultrasound Treatments
Magnetic resonance imaging (MRI)-guided focused ultrasound (MRg-FUS) is an effective and noninvasive procedure for treating diseases such as neurological disorders. Phase adjustment on ultrasound transducers can only achieve a limited focal-spot steering range. When treating large abdominopelvic targets, mechanical adjustment on the transducers' position and orientation is the prerequisite for enlarging the steering range. Therefore, we previously designed an MRI-guided robot to manipulate the transducers to offer sufficient focal-spot movement range. This could provide more modulation solutions to constructive ultrasound interference. However, full-wave ultrasound propagation inside a patient's heterogeneous abdominal media is complex and nonlinear, posing significant challenges in ultrasound modulation and beam motion control. Here, we propose a novel learning-based phase-aberration correction and model-free control framework for robot-assisted MRg-FUS treatments. The correction policy guarantees rapid aberration compensation within 5.0 ms. Submillimeter refocusing accuracy is achieved in both the liver (0.32 mm) and pancreas (0.51 mm), meeting clinical requirements for focal targeting. Our controller can accommodate nonlinear phase actuation with fast convergence (< 5.7 ms) and ensure accurate positional tracking with a mean error of 0.26 mm, without prior knowledge of inhomogeneous media. Compared with the conventional model-based method, it contributes to 61.77%–70.39% mean error reduction without requiring model parameter tuning.
期刊介绍:
The Journal of Field Robotics seeks to promote scholarly publications dealing with the fundamentals of robotics in unstructured and dynamic environments.
The Journal focuses on experimental robotics and encourages publication of work that has both theoretical and practical significance.