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

摘要-项目3 年龄标化率(ASR)显示，乌干达和坦桑尼亚的肺癌发病率稳步上升 与其他癌症相比。不幸的是，这两个地区都没有既定的肺癌筛查计划。 坦桑尼亚或乌干达。有记录的肺癌病例大多是在胸部计算机上偶然发现的 进行体层摄影(CT)扫描，以确定患者呼吸道症状的原因。这个问题就是 在坦桑尼亚和乌干达，由于结核病的高发病率，诊断的特异性加剧。 (TB)，可导致肺部慢性肉芽肿反应，表现为良性肺结节 在CT和X光片上。获得高质量的胸部X光和CT图像并对其进行解释的熟练人员是 乌干达和坦桑尼亚缺乏大多数三级卫生中心。此外，与之生活在一起的人数 艾滋病毒艾滋病继续上升，据报道，2014年，坦桑尼亚有1,411,829人感染艾滋病毒 艾滋病。然而，人们对非洲的肺癌和艾滋病毒知之甚少。随着目前观察到的不断增加 关于肺癌的发病率，乌干达迫切需要研究肺癌和艾滋病毒之间的联系 和坦桑尼亚。另一个耐人寻味的问题是，同样的肺癌放射学标准 筛查应统一适用于艾滋病毒患者和艾滋病毒患者。 我们小组一直在开发新的放射学类别(射线照相的计算机化特征分析 扫描)特征，以改进对肺结节良恶性的区分。例如，我们已经展示了 结节血管的曲折程度在良、恶性结节中有很大不同。 此外，我们已经证明，结节周围表面(紧靠肺外)的放射学特征 CT和X线片上的结节)与活检组织标本的免疫反应程度有关。vt.给出 HIV患者往往具有低免疫细胞群，合理的推测是放射学 放射扫描上的签名将反映缺乏免疫签名。 在这个项目中，我们将开发一个基于放射组学的机器分类器，称为LUNIRiS(肺部图像风险 分数)用于预测胸部CT或X光扫描上的结节的恶性风险。我们假设新的 在乌干达和坦桑尼亚，放射性生物标记物可以改善非侵入性肺诊断，后者有 结核病患病率较高，因此结核病引起的肉芽肿。此外，我们将寻求使用这些工具来 确定HIV和HIV-肺部在CT和胸部X光上的放射表型可能的差异 并利用这些差异来开发针对HIV状态的特定肺癌筛查模型。 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，以改善肺结节诊断 关于LDCT扫描的筛查。这一伙伴关系将允许转让技术和放射学专业知识。 (通过门户网站)改进乌干达和坦桑尼亚的肺癌筛查。

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.