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（ASR）显示乌干达和坦桑尼亚的肺癌发病率稳步上升 不幸的是，与其他癌症相比，这两种癌症都没有既定的肺癌筛查计划。 坦桑尼亚或乌干达记录的肺癌病例大多是在胸部计算机上发现的。 进行断层扫描 (CT) 扫描以确定患者呼吸道症状的原因。 由于结核病发病率高，坦桑尼亚和乌干达的诊断特异性更高 (TB) 可引起肺部慢性肉芽肿反应，表现为良性肺结节 CT 和 X 射线技术人员能够获取高质量的胸部 X 射线和 CT 图像并对其进行解读。 乌干达和坦桑尼亚大多数三级卫生中心都缺乏。 艾滋病毒/艾滋病持续上升，据报道，2014年坦桑尼亚有1,411,829名艾滋病毒感染者 然而，随着目前观察到的非洲肺癌和艾滋病毒的增加，人们对其知之甚少。 肺癌的发病率，迫切需要研究乌干达肺癌与艾滋病毒之间的联系 另一个有趣的问题是肺癌的放射学标准是否相同。 筛查应统一应用于 HIV 阳性和 HIV 阴性患者。 我们的小组一直在开发新类别的放射组学（放射线照相的计算机化特征分析） 例如，我们已经证明，扫描）特征可以改善肺结节良恶性的区分。 良性结节和恶性结节之间的结节脉管系统的迂曲度有很大不同。 此外，我们还表明，结节周围表面（紧邻肺外侧）的放射学特征 CT 和 X 射线上的结节）与活检组织标本的免疫反应程度相关。 HIV 患者的免疫细胞群往往较低，一个合理的推测是放射组学 射线照相扫描上的签名将反映不存在免疫签名。 在这个项目中，我们将开发一种基于放射组学的机器分类器，称为 LunIRiS（肺图像风险） 分数）用于预测胸部 CT 或 X 射线扫描中结节的恶性肿瘤风险。 放射组学生物标志物可以改善乌干达和坦桑尼亚的无创肺部诊断，这两个国家的 结核病患病率较高，因此结核病诱发的肉芽肿也较高。此外，我们将寻求利用这些工具来治疗。 确定 HIV+ 和 HIV- 肺之间 CT 和胸部 X 光检查的放射线照相表型可能存在的差异 癌症患者并利用这些差异来开发艾滋病毒状态特异性肺癌筛查模型。 最后，第四个目标是创建基于 Web 的 LunIRiS 部署，以实现决策支持和 克利夫兰与乌干达和坦桑尼亚之间基于远程放射学的服务，以改善肺结节的诊断 此次合作将促进技术和放射学专业知识的转让。 （通过门户网站）改善乌干达和坦桑尼亚的肺癌筛查。