“Leadership and innovation in any medical field requires not only practical product development to deliver value for clinicians, but also robust validation and peer review to show how and why those products work,” commented
MRI-guided neuro interventions require rapid, accurate, and reproducible segmentation of anatomical brain structures for identification of targets during surgical procedures. This manuscript introduces the methodology for shape-constrained deformable brain segmentation behind Maestro, describes the validation performed for its FDA clearance, and presents a comparison with manual expert segmentation and FreeSurfer, an open-source segmentation software. Quantitative analysis indicates superior performance compared to both manual expert segmentation and FreeSurfer. The shape-constrained methodology results in accurate and highly reproducible segmentation. Furthermore, inherent point based-correspondence provides consistent target identification ideal for MRI-guided neuro interventions. A link to the open source publication can be found here.
Reproducibility error of Maestro (green), FreeSurfer 7.2 (blue) and manual segmentation (red) for common brain structures (left), and average over all structures (right). Bars represent range of measured relative volume difference.
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1 Zagorchev L, Hyde DE, Li C, et al. Shape-constrained deformable brain segmentation: Methods and quantitative validation. Neuroimage. Published online
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Contact: Media Contact:Jacqueline Keller , Vice President of Marketing (949) 900-6833 info@clearpointneuro.com Investor Relations: Danilo D’Alessandro, Chief Financial Officer (888) 287-9109 ir@clearpointneuro.com
ClearPoint Maestro Brain Model
ClearPoint Maestro Brain Model
ClearPoint Neuro Maestro Brain Model Comparative Reproducibility Error Results
Reproducibility error of Maestro (green), FreeSurfer 7.2 (blue) and manual segmentation (red) for common brain structures (left), and average over all structures (right). Bars represent range of measured relative volume difference.
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