Renata Montes Garcia Barbosa, Joyce Yuri Silvestre Yamamoto, Miriam Carvalho Soares, Isabela Bruzzi Bezerra Paraguay, Sara Carvalho Barbosa Casagrande, Jorge Dornellys da Silva Lapa, Marcos Eugênio Ramalho Bezerra, Guilherme Sperling Torezani, Vanessa Milanese Holanda, Gabriel de Castro Micheli, Egberto Reis Barbosa, Rubens Gisbert Cury
{"title":"两种脑深部刺激导联重建方法的比较及其预测能力。","authors":"Renata Montes Garcia Barbosa, Joyce Yuri Silvestre Yamamoto, Miriam Carvalho Soares, Isabela Bruzzi Bezerra Paraguay, Sara Carvalho Barbosa Casagrande, Jorge Dornellys da Silva Lapa, Marcos Eugênio Ramalho Bezerra, Guilherme Sperling Torezani, Vanessa Milanese Holanda, Gabriel de Castro Micheli, Egberto Reis Barbosa, Rubens Gisbert Cury","doi":"10.1016/j.neurom.2025.04.013","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>Deep brain stimulation (DBS) technology has become increasingly advanced, and tools capable of optimizing programming are necessary. Three-dimensional (3D) electrode imaging reconstruction has the potential to assist clinicians in selecting the most effective DBS contacts. In this study, we evaluated the predictive capacity of two different methods (Matlab software [Mathworks, Inc., Natick, MA] and Brainlab software [Brainlab, Munich, Germany]) in identifying effective DBS contacts, compared with clinical examination (the standard of care). The study also analyzes whether one method is superior.</p><p><strong>Materials and methods: </strong>Overall, 29 patients were included: 27 with Parkinson's disease (PD) and two with dystonia (DT). Therefore, images of the 58 brain hemispheres were obtained. Of these, 56 had directional leads, and two had leads with eight-ring contacts. Electrode reconstruction was performed using Matlab software and Brainlab software. The anatomic relationship between the electrodes and the targets (subthalamic nucleus or globus pallidus internus) was analyzed. Contacts within the sweet spot of the target were chosen through 3D reconstruction visualization. In addition, if the best contact levels were directional, the best located directional contacts were chosen (this was possible in 40 leads). The best contact was defined as that with the highest motor symptoms improvement rate based on clinical examination (standard of care).</p><p><strong>Results: </strong>The mean age of the patients was 56 years; 24 patients underwent surgery within ≤one year from the surgery, and the maximum time from surgery was three years. The difference in contact-level suggestion was only one hemisphere, with Matlab software correctly suggesting the best clinical contact in 83% (48/58) and Brainlab software in 84% (49/58). The suggestion capacity of the directional contacts was 80% for both methods. Furthermore, there was a 94.8% concordance rate between the two methods (55/58) on choosing the best contacts on the basis of image reconstruction.</p><p><strong>Conclusion: </strong>Matlab software and Brainlab software are effective image reconstruction methods for accurately suggesting the best contact on the basis of clinical examination.</p>","PeriodicalId":19152,"journal":{"name":"Neuromodulation","volume":" ","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparison of Two Methods of Deep Brain Stimulation Lead Reconstruction and Their Prediction Capacities.\",\"authors\":\"Renata Montes Garcia Barbosa, Joyce Yuri Silvestre Yamamoto, Miriam Carvalho Soares, Isabela Bruzzi Bezerra Paraguay, Sara Carvalho Barbosa Casagrande, Jorge Dornellys da Silva Lapa, Marcos Eugênio Ramalho Bezerra, Guilherme Sperling Torezani, Vanessa Milanese Holanda, Gabriel de Castro Micheli, Egberto Reis Barbosa, Rubens Gisbert Cury\",\"doi\":\"10.1016/j.neurom.2025.04.013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objectives: </strong>Deep brain stimulation (DBS) technology has become increasingly advanced, and tools capable of optimizing programming are necessary. Three-dimensional (3D) electrode imaging reconstruction has the potential to assist clinicians in selecting the most effective DBS contacts. In this study, we evaluated the predictive capacity of two different methods (Matlab software [Mathworks, Inc., Natick, MA] and Brainlab software [Brainlab, Munich, Germany]) in identifying effective DBS contacts, compared with clinical examination (the standard of care). The study also analyzes whether one method is superior.</p><p><strong>Materials and methods: </strong>Overall, 29 patients were included: 27 with Parkinson's disease (PD) and two with dystonia (DT). Therefore, images of the 58 brain hemispheres were obtained. Of these, 56 had directional leads, and two had leads with eight-ring contacts. Electrode reconstruction was performed using Matlab software and Brainlab software. The anatomic relationship between the electrodes and the targets (subthalamic nucleus or globus pallidus internus) was analyzed. Contacts within the sweet spot of the target were chosen through 3D reconstruction visualization. In addition, if the best contact levels were directional, the best located directional contacts were chosen (this was possible in 40 leads). The best contact was defined as that with the highest motor symptoms improvement rate based on clinical examination (standard of care).</p><p><strong>Results: </strong>The mean age of the patients was 56 years; 24 patients underwent surgery within ≤one year from the surgery, and the maximum time from surgery was three years. The difference in contact-level suggestion was only one hemisphere, with Matlab software correctly suggesting the best clinical contact in 83% (48/58) and Brainlab software in 84% (49/58). The suggestion capacity of the directional contacts was 80% for both methods. 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Comparison of Two Methods of Deep Brain Stimulation Lead Reconstruction and Their Prediction Capacities.
Objectives: Deep brain stimulation (DBS) technology has become increasingly advanced, and tools capable of optimizing programming are necessary. Three-dimensional (3D) electrode imaging reconstruction has the potential to assist clinicians in selecting the most effective DBS contacts. In this study, we evaluated the predictive capacity of two different methods (Matlab software [Mathworks, Inc., Natick, MA] and Brainlab software [Brainlab, Munich, Germany]) in identifying effective DBS contacts, compared with clinical examination (the standard of care). The study also analyzes whether one method is superior.
Materials and methods: Overall, 29 patients were included: 27 with Parkinson's disease (PD) and two with dystonia (DT). Therefore, images of the 58 brain hemispheres were obtained. Of these, 56 had directional leads, and two had leads with eight-ring contacts. Electrode reconstruction was performed using Matlab software and Brainlab software. The anatomic relationship between the electrodes and the targets (subthalamic nucleus or globus pallidus internus) was analyzed. Contacts within the sweet spot of the target were chosen through 3D reconstruction visualization. In addition, if the best contact levels were directional, the best located directional contacts were chosen (this was possible in 40 leads). The best contact was defined as that with the highest motor symptoms improvement rate based on clinical examination (standard of care).
Results: The mean age of the patients was 56 years; 24 patients underwent surgery within ≤one year from the surgery, and the maximum time from surgery was three years. The difference in contact-level suggestion was only one hemisphere, with Matlab software correctly suggesting the best clinical contact in 83% (48/58) and Brainlab software in 84% (49/58). The suggestion capacity of the directional contacts was 80% for both methods. Furthermore, there was a 94.8% concordance rate between the two methods (55/58) on choosing the best contacts on the basis of image reconstruction.
Conclusion: Matlab software and Brainlab software are effective image reconstruction methods for accurately suggesting the best contact on the basis of clinical examination.
期刊介绍:
Neuromodulation: Technology at the Neural Interface is the preeminent journal in the area of neuromodulation, providing our readership with the state of the art clinical, translational, and basic science research in the field. For clinicians, engineers, scientists and members of the biotechnology industry alike, Neuromodulation provides timely and rigorously peer-reviewed articles on the technology, science, and clinical application of devices that interface with the nervous system to treat disease and improve function.