arXiv:2606.07658cs.CVcs.LG2026-06

用超声生成术中脑部MRI,帮医生实时看清肿瘤切除后的脑组织变化。

What neurosurgeons need to see: synthetic intra-operative MRI from ultrasound for brain-shift compensation in brain tumour surgery

论文配图:What neurosurgeons need to see: synthetic intra-operative MRI from ultrasound for brain-shift compensation in brain tumour surgery
图 1 · 摘自论文原文
  • 用超声数据合成MRI,再与术前MRI融合做变形配准
  • 配准误差降至5.86毫米,且每个病例都得到光滑形变场
  • 为手术导航提供类似MRI的实时脑部更新,适合神经外科使用

胶质瘤手术以最大安全切除为目标,但开颅后脑组织移位会降低术中导航精度。术中MRI虽可补偿但设备昂贵且罕见;而术中超声成本低、可重复、兼容常规流程。现有结合术中超声与术前MRI的导航系统多依赖刚性配准,即使采用可变形多模态配准,也受限于超声斑点对比度弱、视野窄,且无法反映术前扫描中不存在的结构(如切除腔和残留肿瘤)。本文提出端到端流程:通过融合术前MRI、由术中超声生成的合成MRI,以及基于该合成图像的可变形配准,重建术前空间下的全脑MRI体积。方法包含2.5D残差变压器合成主干(ResViT-2.5D)和两阶段配准——先用NiftyReg,再用合成锚定的SynthMorph阶段,直接处理原始扫描输入。在术后切除的ReMIND队列上,ResViT-2.5D生成的合成图像在结构、强度和感知上均接近术中T2加权影像。在14名受试者共215个专家标记点下,合成锚定配准将平均目标配准误差从6.27毫米降至5.86毫米,媲美强基线经典NiftyReg(5.85毫米),且每例均获得微分同胚形变场。贡献不在于配准精度提升,而在于生成的整合体积——在超声视野内真实反映术后状态,为外科医生提供类MRI的术中更新,具备嵌入手术导航流程的潜力。

原文摘要 · Abstract (English)

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.

神经外科超声成像图像合成手术导航

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