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ClearPoint Neuro, Inc. (NASDAQ:CLPT) (the "Company"), a global device, cell, and gene therapy-enabling company offering precise navigation to the brain and spine, today announced FDA Clearance and first-in-human cases using the ClearPoint 2.2 Software with integrated Maestro Brain Modeling, and also the publication of a key validation study for its ClearPoint Maestro® Brain Model in the peer-reviewed journal NeuroImage.1
"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 Joe Burnett, President and CEO at ClearPoint Neuro. "The Maestro Brain Model, and its integration into the recently FDA cleared ClearPoint 2.2 navigation software, is our latest example of just that. The ClearPoint system can now offer fast, peri-procedural segmentation of the cortical structures of the brain to identify both targets and safety zones for cell and gene therapy delivery, laser ablation, biopsy and deep brain stimulation. At the same time, we are pleased to announce that one of many planned validation studies has been published online in the journal NeuroImage to give surgeons confidence in the performance and accuracy of the Maestro Tool. The first clinical cases using ClearPoint 2.2 were completed successfully this quarter, and we expect full market release in the second half of this year."
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.
Posted In: CLPT
