基于CT影像搏动性耳鸣识别及高致病区域  

Identification of pulsatile tinnitus and visualization of high pathogenic regions based on CT images

作　　者：田山[1] 王治文 曹学鹏 苏磊 刘兆会[4] TIAN Shan;WANG Zhiwen;CAO Xuepeng;SU Lei;LIU Zhaohui(Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education,School of Biological Science and Medical Engineering,Beihang University,Beijing 100191,China;Key Laboratory of Traditional Chinese Medicine Modernization in Lvliang,Traditional Chinese Medicine Hospital of Lvliang,Shanxi Province,Lvliang 033099,China;Beijing Bombax Xiaoice Technology Co.,Ltd.,Beijing 100080,China;Department of Radiology,Beijing Tongren Hospital,Capital Medical University,Beijing 100005,China)

机构地区：[1]北京航空航天大学生物与医学工程学院生物力学与力生物学教育部重点实验室,北京100191 [2]山西省吕梁市中医院吕梁市中医药现代化工程重点实验室,吕梁033099 [3]北京红棉小冰科技有限公司,北京100080 [4]首都医科大学附属北京同仁医院放射科,北京100005

出　　处：《北京航空航天大学学报》2025年第2期625-632,共8页Journal of Beijing University of Aeronautics and Astronautics

基　　金：国家自然科学基金(12002024,82071882);北京市自然科学基金(7222029)。

摘　　要：搏动性耳鸣(PT)的病因诊断依赖于影像学检测,但病因众多,缺乏普适性强、机制明确的诊断标准。基于搏动性耳鸣患者和无耳鸣人群的计算机断层扫描(CT)影像横截面图,提出一种高精度的耳鸣识别神经网络模型,并自动标示高致病区域,辅助临床诊断。使用迁移学习Resnet-v1-50模型,取骨窗颞骨中部水平截面样本进行分类学习,并以梯度加权类激活映射(gradCAM)方法对分类高权重区域自动标注;统计CT截面大图(全颅)、中图(双侧颞骨)、小图(右侧颞骨)3种数据集的耳鸣分类高权重区域涉及的解剖结构,逐步细化感兴趣区域,提高分类高权重区域标注分辨率。实验结果显示:包含双侧颞骨的中图数据集分类精度最好,测试集精度达到100%。搏动性耳鸣分类高权重区域集中于双侧或单侧颞骨部位,主要包括颞骨蜂房、鼓窦、乙状窦骨板、上鼓室等部位。搏动性耳鸣与颞骨及附近骨质结构有密切关系;搏动性耳鸣患者在双侧颞骨或耳鸣对侧颞骨均有较大概率存在区别于无耳鸣人群的结构异常;颞骨蜂房、鼓窦、乙状窦骨板、鼓室等结构均有较高概率包含搏动性耳鸣的高致病区域。以上影像分析结论与搏动性耳鸣生物力学研究结论实现了相互佐证。The diagnosis of pulsatile tinnitus(PT)typically relies on medical imaging tests.However,due to the wide range of possible causes,there is still a lack of universally accepted diagnostic criteria with a clearly defined mechanism.This study aims to propose a neural network model for high-accuracy PT identification based on CT images of PT patients and non-PT individuals,as well as automatically label the high pathogenic regions to assist in diagnosis.Transfer learning based on the ResNet-v1-50 model was employed to identify PT using horizontal crosssections of the middle temporal bone in the bone window.The high-weight regions for identification were labeled using the grad-CAM method.These regions,along with related anatomical structures,were statistically analyzed across three databases:large sections(entire cranium),medium sections(bilateral temporal bones),and small sections(right-side temporal bone),allowing for the gradual refinement of the area of interest and increased resolution of highweight regions in classification.The best identification,which achieved 100%accuracy in the test set,came from the medium area that included both temporal bones.The high-weight regions identified in PT were concentrated in either bilateral or unilateral temporal bones,primarily involving the temporal bone air cells,tympanic antrum,sigmoid sinus cortical plate,and superior tympanum.The occurrence of PT is closely associated with temporal bone and nearby bone structures.PT patients have a probability of structural abnormalities in either bilateral or contralateral temporal bones,which are different from those without tinnitus.Specifically,bone structures including temporal bone air cells,tympanic antrum,sigmoid sinus cortical plate and tympanic cavity have a high probability of containing the primary pathogenic factors for PT.These imaging-based conclusions align with previous biomechanical findings,further corroborating the understanding of PT etiology.

关 键 词：搏动性耳鸣 机器学习 可视化策略 CT影像 神经网络模型 辅助诊断 

分 类 号：R737.11[医药卫生—肿瘤] R814.42[医药卫生—临床医学]