DataSheet_1_Automatic bundle-specific white matter fiber tracking tool using diffusion tensor imaging data: A pilot trial in the application of language-related glioma resection.pdf

Cerebral neoplasms like gliomas may cause intracranial pressure increasing, neural tract deviation, infiltration, or destruction in peritumoral areas, leading to neuro-functional deficits. Novel tracking technology, such as DTI, can objectively reveal and visualize three-dimensional white matter trajectories; in combination with intraoperative navigation, it can help achieve maximum resection whilst minimizing neurological deficit. Since the reconstruction of DTI raw data largely relies on the technical engineering and anatomical experience of the operator; it is time-consuming and prone to operator-induced bias. Here, we develop new user-friendly software to automatically segment and reconstruct functionally active areas to facilitate precise surgery. In this pilot trial, we used an in-house developed software (DiffusionGo) specially designed for neurosurgeons, which integrated a reliable diffusion-weighted image (DWI) preprocessing pipeline that embedded several functionalities from software packages of FSL, MRtrix3, and ANTs. The preprocessing pipeline is as follows: 1. DWI denoising, 2. Gibbs-ringing removing, 3. Susceptibility distortion correction (process if opposite polarity data were acquired), 4. Eddy current and motion correction, and 5. Bias correction. Then, this fully automatic multiple assigned criteria algorithms for fiber tracking were used to achieve easy modeling and assist precision surgery. We demonstrated the application with three language-related cases in three different centers, including a left frontal, a left temporal, and a left frontal-temporal glioma, to achieve a favorable surgical outcome with language function preservation or recovery. The DTI tracking result using DiffusionGo showed robust consistency with direct cortical stimulation (DCS) finding. We believe that this fully automatic processing pipeline provides the neurosurgeon with a solution that may reduce time costs and operating errors and improve care quality and surgical procedure quality across different neurosurgical centers.

胶质瘤等脑肿瘤可引发颅内压升高、神经束移位、瘤周区域浸润或破坏，进而导致神经功能缺损。新型追踪技术如弥散张量成像（Diffusion Tensor Imaging，DTI）可客观显示并可视化三维白质纤维束走行轨迹；联合术中导航技术，可在实现肿瘤最大切除的同时，最大程度降低神经功能缺损风险。由于DTI原始数据的重建高度依赖操作者的工程技术与解剖学经验，不仅耗时较长，还易产生操作者诱导偏倚。为此，我们开发了一款易用型新型软件，可自动分割并重建功能活动脑区，以辅助精准手术。在本预试验中，我们使用了专为神经外科医生研发的自研软件DiffusionGo，该软件集成了可靠的弥散加权成像（Diffusion Weighted Image，DWI）预处理流程，整合了FSL、MRtrix3及ANTs三款软件包的多项功能。该预处理流程如下：1. DWI去噪；2. Gibbs环伪影去除；3. 磁化率畸变校正（若采集了反向极性数据则执行该步骤）；4. 涡流与运动校正；5. 偏倚校正。随后采用全自动多分配准则纤维追踪算法，实现便捷建模并辅助精准手术。我们纳入3家不同中心的3例语言相关胶质瘤病例（分别为左侧额叶、左侧颞叶及左侧额颞叶胶质瘤）验证了该软件的应用效果，最终均获得了良好的手术结局，患者语言功能得以保留或恢复。使用DiffusionGo生成的DTI追踪结果与直接皮层电刺激（Direct Cortical Stimulation，DCS）结果具有高度一致性。我们认为，这套全自动处理流程可为神经外科医生提供一套可行方案，有望降低时间成本与操作误差，提升不同神经外科中心的诊疗质量与手术操作质量。