Huang Huiyuan, Ding Zhongxiang, Mao Dewang, Yuan Jianhua, Zhu Fangmei, Chen Shuda, Xu Yan, Lou Lin, Feng Xiaoyan, Qi Le, Qiu Wusi, Zhang Han, Zang Yu-Feng
Center for Cognition and Brain Disorders, Hangzhou Normal University, 58 Haishu Road, Hangzhou, 311121, People's Republic of China.
School of Education Science, Hangzhou Normal University, Hangzhou, Zhejiang, 311121, People's Republic of China.
Neuroinformatics. 2016 Oct;14(4):421-38. doi: 10.1007/s12021-016-9304-y.
The main goal of brain tumor surgery is to maximize tumor resection while minimizing the risk of irreversible postoperative functional sequelae. Eloquent functional areas should be delineated preoperatively, particularly for patients with tumors near eloquent areas. Functional magnetic resonance imaging (fMRI) is a noninvasive technique that demonstrates great promise for presurgical planning. However, specialized data processing toolkits for presurgical planning remain lacking. Based on several functions in open-source software such as Statistical Parametric Mapping (SPM), Resting-State fMRI Data Analysis Toolkit (REST), Data Processing Assistant for Resting-State fMRI (DPARSF) and Multiple Independent Component Analysis (MICA), here, we introduce an open-source MATLAB toolbox named PreSurgMapp. This toolbox can reveal eloquent areas using comprehensive methods and various complementary fMRI modalities. For example, PreSurgMapp supports both model-based (general linear model, GLM, and seed correlation) and data-driven (independent component analysis, ICA) methods and processes both task-based and resting-state fMRI data. PreSurgMapp is designed for highly automatic and individualized functional mapping with a user-friendly graphical user interface (GUI) for time-saving pipeline processing. For example, sensorimotor and language-related components can be automatically identified without human input interference using an effective, accurate component identification algorithm using discriminability index. All the results generated can be further evaluated and compared by neuro-radiologists or neurosurgeons. This software has substantial value for clinical neuro-radiology and neuro-oncology, including application to patients with low- and high-grade brain tumors and those with epilepsy foci in the dominant language hemisphere who are planning to undergo a temporal lobectomy.
脑肿瘤手术的主要目标是在将术后不可逆功能后遗症风险降至最低的同时，使肿瘤切除最大化。明确的功能区应在术前进行划定，特别是对于肿瘤靠近明确功能区的患者。功能磁共振成像（fMRI）是一种无创技术，在术前规划方面显示出巨大潜力。然而，用于术前规划的专业数据处理工具包仍然匮乏。基于开源软件中的多种功能，如统计参数映射（SPM）、静息态功能磁共振成像数据分析工具包（REST）、静息态功能磁共振成像数据处理助手（DPARSF）和多独立成分分析（MICA），在此，我们介绍一个名为PreSurgMapp的开源MATLAB工具箱。该工具箱可以使用综合方法和各种互补的功能磁共振成像模式来揭示明确的功能区域。例如，PreSurgMapp既支持基于模型的方法（一般线性模型，GLM，和种子相关性），也支持数据驱动的方法（独立成分分析，ICA），并且可以处理基于任务的和静息态的功能磁共振成像数据。PreSurgMapp专为高度自动化和个性化的功能映射而设计，具有用户友好的图形用户界面（GUI），可实现省时的流水线处理。例如，使用具有判别性指数的有效、准确的成分识别算法，可以在无人为输入干扰的情况下自动识别感觉运动和语言相关成分。生成的所有结果都可以由神经放射科医生或神经外科医生进一步评估和比较。该软件对临床神经放射学和神经肿瘤学具有重要价值，包括应用于低级别和高级别脑肿瘤患者以及计划接受颞叶切除术的优势语言半球癫痫灶患者。
