Institute of Child Health, University College London, Guilford Street, London, United Kingdom.
Department of Neurosurgery, Great Ormond Street Hospital for Children, Great Ormond Street, London, United Kingdom.
Int J Comput Assist Radiol Surg. 2022 Sep;17(9):1559-1567. doi: 10.1007/s11548-022-02617-z. Epub 2022 Apr 25.
Intraoperative diffusion MRI could provide a means of visualising brain fibre tracts near a neurosurgical target after preoperative images have been invalidated by brain shift. We propose an atlas-based intraoperative tract segmentation method, as the standard preoperative method, streamline tractography, is unsuitable for intraoperative implementation.
A tract-specific voxel-wise fibre orientation atlas is constructed from healthy training data. After registration with a target image, a radial tumour deformation model is applied to the orientation atlas to account for displacement caused by lesions. The final tract map is obtained from the inner product of the atlas and target image fibre orientation data derived from intraoperative diffusion MRI.
The simple tumour model takes only seconds to effectively deform the atlas into alignment with the target image. With minimal processing time and operator effort, maps of surgically relevant tracts can be achieved that are visually and qualitatively comparable with results obtained from streamline tractography.
Preliminary results demonstrate feasibility of intraoperative streamline-free tract segmentation in challenging neurosurgical cases. Demonstrated results in a small number of representative sample subjects are realistic despite the simplicity of the tumour deformation model employed. Following this proof of concept, future studies will focus on achieving robustness in a wide range of tumour types and clinical scenarios, as well as quantitative validation of segmentations.
术中弥散磁共振成像(MRI)可以提供一种方法,在术前图像因脑移位而失效后,可视化神经外科目标附近的脑纤维束。我们提出了一种基于图谱的术中束分割方法,因为标准的术前方法——流线追踪技术不适合术中实施。
从健康的训练数据中构建特定于束的体素级纤维方向图谱。与目标图像配准后,应用径向肿瘤变形模型对方向图谱进行处理,以解释病变引起的位移。最终的束图是从术中弥散 MRI 获得的图谱和目标图像纤维方向数据的内积得到的。
简单的肿瘤模型只需要几秒钟的时间就可以有效地将图谱与目标图像对齐。通过最小的处理时间和操作人员的努力,可以获得手术相关束的图谱,其视觉和定性效果与流线追踪技术获得的结果相当。
初步结果表明,在具有挑战性的神经外科病例中,无需进行术中流线追踪即可实现束分割的可行性。尽管所采用的肿瘤变形模型很简单,但在少数有代表性的样本受试者中得到的结果是现实的。在这个概念验证之后,未来的研究将集中在实现广泛的肿瘤类型和临床场景的稳健性上,并对分割进行定量验证。