Artificial Intelligence for Lung Cancer Characterization in HIV affected populations in Uganda and Tanzania

乌干达和坦桑尼亚艾滋病毒感染人群肺癌特征的人工智能

• 批准号: 10084629
• 负责人: Anant Madabhushi
• 金额: $ 18.52万
• 依托单位: CASE WESTERN RESERVE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-21 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10084629
• 关键词: 3-Dimensional; Acquired Immunodeficiency Syndrome; Affect; Africa; Age; Appearance; Architecture; Area; Artificial Intelligence; Benign; Biological Markers; Biopsy; Blood Vessels; Cancer Patient; Cells; Chest; Chronic; Clinical; Computer-Assisted Diagnosis; Decision Support Model; Detection; Development; Diagnosis; Diagnostic Specificity; Diagnostic radiologic examination; Discrimination; Epidemiology; Granuloma; Granulomatous; HIV; HIV-1; Health; High Prevalence; Human; Human Resources; Image; Immune; Immune response; Incidence; Infection; Link; Lung; Lung nodule; Malignant - descriptor; Malignant Neoplasms; Malignant neoplasm of lung; Measurement; Medical center; Modeling; Molecular; Morphology; Nodule; Online Systems; Patients; Pattern; Phenotype; Population; ROC Curve; Radiology Specialty; Reaction; Reader; Reporting; Risk; Roentgen Rays; Scanning; Sensitivity and Specificity; Services; Shapes; Specificity; Specimen; Standardization; Surface; Tanzania; Technology; Teleradiology; Texture; Thoracic Radiography; Tissues; Transference; Tuberculosis; Uganda; Validation; X-Ray Computed Tomography; base; chest computed tomography; cohort; computerized; imaging biomarker; improved; innovation; low dose computed tomography; lung cancer screening; lung imaging; novel; radiologist; radiomics; respiratory; screening; screening program; success; support tools; symptomatology; tool; web portal

ABSTRACT – Project 3 The age standardized rates (ASRs) show a steady rise in the incidence of lung cancer in Uganda and Tanzania compared to other cancers. Unfortunately, there is no established lung cancer screening program in either of Tanzania or Uganda. The cases of lung cancer recorded have mostly been found incidentally on chest computed tomography (CT) scans done to establish the cause of patients' respiratory symptomatology. This problem of diagnostic specificity is exacerbated in Tanzania and Uganda on account of the high incidence of tuberculosis (TB) which can cause a chronic granulomatous reaction in the lungs manifesting as benign pulmonary nodules on CT and X-rays. Skilled personnel to acquire good quality chest x-ray and CT images and to interpret them is lacking in most tertiary health centers in Uganda and Tanzania. Additionally, the number of people living with HIV AIDS continues to rise, and in 2014, it was reported that Tanzania had 1,411,829 people living with HIV AIDS. However, very little is known about lung cancer and HIV in Africa. With the currently observed increasing incidence rates of lung cancer, there is an urgent need to study the link between lung cancer and HIV in Uganda and Tanzania. An additional intriguing question is whether the same radiographic criteria for lung cancer screening should be uniformly applied across both HIV+ and HIV- patients. Our group has been developing new classes of radiomic (computerized feature analysis of radiographic scans) features for improved discrimination of malignant from benign lung nodules. For instance, we have shown that the tortuosity of nodule vasculature is substantially different between benign and malignant nodules. Additionally, we have shown that radiomic features of the peri-nodular surface (immediately outside the lung nodule on CT and X-rays) were associated with degree of immune response on biopsy tissue specimens. Given that HIV patients tend to have a low immune cell population, a reasonable conjecture is that the radiomic signature on radiographic scans will reflect the absence of an immune signature. In this project we will develop a radiomics based machine classifier called LunIRiS (Lung Image Risk Score) for predicting risk of malignancy for a nodule on a chest CT or X-ray scan. We hypothesize that the new radiomic biomarkers can enable improved non-invasive lung diagnosis in Uganda and Tanzania which has a higher prevalence of TB and hence TB induced granulomas. Additionally, we will seek to employ these tools to identify possibly differences in the radiographic phenotype on CT and chest X-rays between HIV+ and HIV- lung cancer patients and to employ these differences to develop HIV status specific lung cancer screening models. Finally, the fourth objective will be to create a web-based deployment of LunIRiS to enable decision support and teleradiology based services between Cleveland and Uganda and Tanzania for improving lung nodule diagnosis on screening LDCT scans. This partnership will allow for transference of technology and radiology expertise (through the web portal) for improved lung cancer screening in Uganda and Tanzania.

摘要 - 项目3 年龄标准化率（ASRS）显示出乌干达和坦桑尼亚肺癌事件的稳定增加 与其他癌症相比。不幸的是，任何一个都没有建立的肺癌筛查计划 坦桑尼亚或乌干达。记录的肺癌病例主要是在计算的胸部偶然发现的 进行了断层扫描（CT）扫描以确定患者呼吸道症状的原因。这个问题 由于结核病的高事件，坦桑尼亚和乌干达诊断特异性会加剧 （TB）可能在表现为良性肺结节的肺中引起慢性肉芽肿反应 在CT和X射线上。熟练的人员获得高质量的胸部X射线和CT图像并解释它们是 在乌干达和坦桑尼亚的大多数三级卫生中心缺乏。此外，与 艾滋病毒艾滋病继续上升，据报道，据报道，坦桑尼亚有1,411,829人患艾滋病毒 艾滋病。但是，关于非洲的肺癌和艾滋病毒知之甚少。随着目前观察到的增加 肺癌发生率，迫切需要研究乌干达肺癌与艾滋病毒之间的联系 和坦桑尼亚。另一个有趣的问题是肺癌的同样的放射学标准是否 筛查应均匀地应用于HIV+和HIV患者。 我们的小组一直在开发新类别的放射线（放射线学计算机化特征分析） 扫描）特征，以改善良性肺结节的恶性歧视。例如，我们已经显示 良性结节和恶性结节之间的结节脉管系统的曲折性大不相同。 此外，我们已经证明了结节表面的放射线特征（紧邻肺部） CT和X射线上的结节与活检组织样品的免疫反应程度有关。给出 艾滋病毒患者的免疫力群体往往较低，一个合理的猜想是放射线 放射线照相扫描的签名将反映出没有免疫特征。 在这个项目中，我们将开发一个基于放射线的机器分类器，称为Luniris（肺图像风险 得分），以预测胸部CT或X射线扫描上的结节恶性肿瘤的风险。我们假设新的 放射线生物标志物可以在乌干达和坦桑尼亚改善无创肺诊断。 TB和TB诱导的肉芽肿的患病率较高。此外，我们将寻求使用这些工具 确定HIV+和HIV肺之间CT和胸部X射线的放射线型表型的可能差异 癌症患者并采用这些差异来发展艾滋病毒状况特定的肺癌筛查模型。 最后，第四个目标是创建基于网络的Luniris的部署，以实现决策支持和 克利夫兰，乌干达和坦桑尼亚之间的基于远导学的服务用于改善肺结诊断 筛选LDCT扫描。这种伙伴关系将允许技术和放射学专业知识转移 （通过Web门户）改善了乌干达和坦桑尼亚的肺癌筛查。