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Multiomics and blood-based biomarkers of moyamoya disease: protocol of Moyamoya Omics Atlas (MOYAOMICS)

中华神经外科杂志(英文) 2024年第03期

作者： Ge Peicong Yin Zihan Tao Chuming Zeng Chaofan Yu Xiaofan Lei Shixiong Li Junsheng zhai yuanren Ma Long He Qiheng Liu Chenglong Liu Wei Zhang Bojian Zheng Zhiyao Mou Siqi Zhao Zhikang Wang Shuang Sun Wei Guo Min Zheng Shuai Zhang Jia Deng Xiaofeng Liu Xingju Ye Xun Zhang Qian Wang Rong Zhang Yan Zhang Shaosen Wang Chengjun Yang Ziwen Zhang Nijia Wu Mingxing Sun Jian Zhou Yujia Shi Zhiyong Ma Yonggang Zhou Jianpo Yu Shaochen Li Jiaxi Lu Junli Gao Faliang Wang Wenjing Chen Yanming Zhu Xingen Zhang Dong Zhao Jizong Department of Neurosurgery Beijing Tiantan Hospital Capital Medical University Beijing China China National Clinical Research Center for Neurological Diseases Beijing China Department of Neurosurgery Beijing Hospital National Center of Gerontology Beijing China Department of Radiology Beijing Tiantan Hospital Beijing China Department of Ultrasound Beijing Tiantan Hospital Capital Medical University Beijing China Department of Neurology Beijing Tiantan Hospital Beijing China Department of Neurosurgery Beijing Friendship Hospital Capital Medical University Beijing China Department of Neurosurgery Beijing Chaoyang Hospital Capital Medical University Beijing China Department of Neurosurgery Beijing Childrens Hospital Capital Medical University Beijing China Department of Neurosurgery The Affiliated Children’s Hospital Capital Institute of Pediatrics Beijing China Department of Neurosurgery Beijing Changping District Hospital Beijing China Department of Neurosurgery Dongfang Hospital Beijing University of Chinese Medicine Beijing China Department of Neurosurgery Nanjing Drum Tower Hospital The Affiliated Hospital of Nanjing University Medical School Nanjing China Department of NeuroInterventional Surgery Binzhou Medical University Hospital Binzhou Shandong China Department of Neurosurgery Renji Hospital Shanghai Jiao Tong University School of Medicine Shanghai China Department of Neurosurgery The First Affiliated Hospital Zhejiang University School of Medicine Hangzhou China Department of Neurosurgery The First Affiliated Hospital of Xi’an Jiaotong University Shaanxi Xi’an China Department of Neurosurgery West China Hospital Sichuan University Chengdu China Department of Neurosurgery Center for Rehabilitation Medicine Zhejiang Provincial Peoples Hospital Affiliated Peoples Hospital Hangzhou Medical College Hangzhou Zhejiang China Beijing Institute of Hepatology Beijing YouAn Hospital Capital Medical University Beijing China Department of Neu

Background Moyamoya disease (MMD) is a rare and complex cerebrovascular disorder characterized by the progressive narrowing of the internal carotid arteries and the formation of compensatory collateral vessels. The etiology of MMD remains enigmatic, making diagnosis and management challenging. The MOYAOMICS project was initiated to investigate the molecular underpinnings of MMD and explore potential diagnostic and therapeutic *** The MOYAOMICS project employs a multidisciplinary approach, integrating various omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, to comprehensively examine the molecular signatures associated with MMD pathogenesis. Additionally, we will investigate the potential influence of gut microbiota and brain-gut peptides on MMD development, assessing their suitability as targets for therapeutic strategies and dietary interventions. Radiomics, a specialized field in medical imaging, is utilized to analyze neuroimaging data for early detection and characterization of MMD-related brain changes. Deep learning algorithms are employed to differentiate MMD from other conditions, automating the diagnostic process. We also employ single-cellomics and mass cytometry to precisely study cellular heterogeneity in peripheral blood samples from MMD *** The MOYAOMICS project represents a significant step toward comprehending MMD’s molecular underpinnings. This multidisciplinary approach has the potential to revolutionize early diagnosis, patient stratification, and the development of targeted therapies for MMD. The identification of blood-based biomarkers and the integration of multiple omics data are critical for improving the clinical management of MMD and enhancing patient outcomes for this complex disease.

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基于SHAP方法的颅内动静脉畸形相关癫痫影像学特征分析

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中华神经外科杂志 2023年第10期39卷 984-990页

作者：张绍森李楠李力王乔翟苑任王基源张谦崔壮张东北京医院神经外科国家老年医学中心中国医学科学院老年医学研究院北京100730 太原市中心医院神经外科太原030009 驻马店市中心医院神经外科驻马店463000 首都医科大学附属北京天坛医院神经外科学中心北京100070

目的通过机器学习算法和SHAP方法探讨与颅内动静脉畸形(AVM)患者出现症状性癫痫相关的关键影像学特征。方法回顾性纳入2022年1月至2023年1月北京医院(134例)、首都医科大学附属北京天坛医院(100例)、太原市中心医院(20例)、驻马店市中... 详细信息

目的通过机器学习算法和SHAP方法探讨与颅内动静脉畸形(AVM)患者出现症状性癫痫相关的关键影像学特征。方法回顾性纳入2022年1月至2023年1月北京医院(134例)、首都医科大学附属北京天坛医院(100例)、太原市中心医院(20例)、驻马店市中心医院(17例)4个中心的神经外科收治的271例颅内AVM患者, 其中首发症状为癫痫者31例(癫痫组), 按照1 ∶2的比例对年龄和性别进行倾向性评分匹配, 纳入对照组患者62例。基于CT血管成像资料比较两组患者病灶的体积、表面积、平均密度、球度、平坦度、伸长度、所在部位等传统影像学和形态学信息, 同时提取病灶的影像组学特征, 基于XGBoost建立机器学习模型, 通过受试者工作特征(ROC)曲线的曲线下面积评价模型预测颅内AVM患者是否伴发癫痫的性能, 并使用SHAP方法分析各影像学特征的重要性。结果癫痫组病灶位于颞叶5例(16.1%), 对照组病灶位于颞叶19例(30.6%), 两组的差异无统计学意义(χ^(2)=1.42, P=0.208)。两组患者病灶的体积、表面积、平均密度、球度、平坦度、伸长度的差异均无统计学意义(均P>0.05)。影像组学特征经过L1正则化降维, 最终纳入6项, 与传统影像学及形态学信息共同纳入XGBoost模型, 模型训练集和独立测试集的ROC曲线下面积分别为1.00和0.80。SHAP分析结果显示, 5项颅内AVM相关症状性癫痫的特征(包括病灶高伸长度、高平坦度、低平均密度、位于颞叶及低峰度)及其他3个影像组学特征对模型具有中等或较大贡献。结论伴发癫痫的颅内AVM患者的畸形团在传统影像学、形态学及影像组学特征上存在显著特点, 其中病灶的平坦度、伸长度、平均密度、位于颞叶及峰度为最重要的5个癫痫相关的影像学特征。

关键词：颅内动静脉畸形癫痫机器学习影像组学 SHAP

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