What neurosurgeons need to see: synthetic intra-operative MRI from ultrasound for brain-shift compensation in brain tumour surgery
Quick Answer
This paper shows that A novel pipeline integrates preoperative MRI with synthetic intraoperative MRI from ultrasound, enhancing brain-shift compensation in glioma surgery.
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A novel pipeline integrates preoperative MRI with synthetic intraoperative MRI from ultrasound, enhancing brain-shift compensation in glioma surgery. The ResViT-2.5D model achieved a mean target registration error of 5.86 mm, closely matching the classical NiftyReg baseline of 5.85 mm, thereby providing surgeons with an MRI-like update of the operative field.
Key Points
- Proposed an end-to-end pipeline for intraoperative MRI generation.
- ResViT-2.5D model closely matches intraoperative T2 across various metrics.
- Mean target registration error reduced from 6.27 mm to 5.86 mm.
- Synthetic volume reflects the intraoperative post-resection state.
- Potential integration into surgical-navigation workflows enhances surgical precision.
Paper Resources
Article Content
From source RSS / original summaryarXiv:2606. 07658v1 Announce Type: new Abstract: Maximal safe resection is the primary objective in glioma surgery. Neuronavigation guidance is progressively degraded by brain shift after dural opening. Intraoperative MRI can compensate but needs dedicated infrastructure and is rarely available, whereas intraoperative ultrasound (ioUS) is inexpensive, repeatable, and compatible with routine workflows.
Navigation systems combining ioUS with preoperative MRI usually rely on rigid registration; even deformable multimodal registration is limited by ultrasound speckle contrast, a narrow field of view, and the inability to represent structures absent from the preoperative scan, most critically the resection cavity and residual tumor.
We propose an end-to-end pipeline that generates a new whole-brain MRI volume in the preoperative imaging space by merging the preoperative MRI, a synthetic MRI generated from the ioUS, and a deformable registration anchored on that synthetic image. It integrates a 2. 5D residual-transformer synthesis backbone (ResViT-2. 5D) and a two-stage registration coupling NiftyReg with a synthesis-anchored SynthMorph stage, operating directly on raw scanner inputs. On a post-resection ReMIND cohort, ResViT-2.
5D produced synthetic images closely matching the intraoperative T2 across structural, intensity, and perceptual metrics. In 14 subjects with 215 expert landmarks, the synthesis-anchored registration reduced the mean target registration error from 6. 27 to 5. 86 mm, matching a strong classical NiftyReg baseline (5. 85 mm) while yielding a diffeomorphic deformation field in every subject.
The contribution is not a gain in registration accuracy but the integrated volume itself, which inside the ultrasound field of view it reflects the intraoperative post-resection state. This provides the surgeon with an MRI-like update of the operative field with potential for integration into surgical-navigation workflows.
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