Predicting Brain Changes in HIV/AIDS

描述(申请人提供)：在广泛使用联合抗逆转录病毒疗法(CART)的富裕国家，艾滋病毒携带者的预期寿命增加了10年以上，但这大大增加了艾滋病毒/艾滋病感染者的数量。目前有4000万人面临与艾滋病毒相关的进行性脑损伤的风险(Navia，2011年)，其中40%的人表现出一些神经或认知障碍。在我们最近在核磁共振和扩散张量成像方面的发现和创新的基础上，我们的项目绘制了艾滋病毒疾病在大脑中的动态图，揭示了预测临床下降和大脑下降的因素。通过分析HIVNC(HIV神经成像联盟)队列(218名HIV+受试者在3年中每26-32周进行一次MRI纵向扫描；900次扫描)，我们将使用我们敏感的图像分析方法，即基于张量的形态测量方法，来(1)绘制一段时间内脑组织丢失速度图，确定哪些大脑系统丢失最快；(2)将这些丢失模式与神经认知障碍(NCI)联系起来；以及(3)确定哪些宿主和疾病相关因素在基线时，预测3年内更高的萎缩率。为了深入探讨功能障碍的原因，我们将在267名受试者中使用基于扩散张量成像的全脑束成像来确定HIV+患者哪里的纤维完整性降低。我们将使用每个患者的DTI扫描来计算全脑连接矩阵，这是基于我们开发的最先进的全脑束成像方法。我们将把目标1和目标2中最好的神经成像方法结合到我们的支持向量机方法中，以预测(1)未来萎缩的比率，(2)在3年的随访中认知能力下降。根据我们对目标1和目标2下降的最佳预测因子，我们将预测哪些HIV+患者即将出现下降。我们将估计基于神经成像的药物试验所需的样本量，以检测5%、10%或25%的萎缩速度减缓，以及相同百分比的认知衰退速度减缓。我们将测试我们的预测器是否适用于HIVNC以外的大型、独立的Charge和MIriam数据集(参见伊戈尔·格兰特和罗恩·科恩博士的支持信)，以及当我们的许多艾滋病毒研究合作者使用我们的方法时；见试点数据)。如新的试点数据所示，我们评估成像协议差异如何影响测量；我们减少扫描协议混淆(例如，调整后的FA)的创新将指导选择最稳健的预测值。我们将评估这些新措施在预测认知能力下降和提高抗逆转录病毒药物试验中的能力方面的有效性。换句话说，DTI扫描和基于MRI的萎缩地图能在多大程度上帮助临床预测即将发生的认知损害？他们能帮助选择药物试验的样本吗？我们的活动将通过选择对未来治疗具有更大潜力的受试者来提高临床试验设计的效率。我们将一如既往地将我们的方法传播给医学、神经科学、工程学方面的专家和受训人员，以及我们由100多个合作实验室组成的网络(包括两个国家艾滋病毒联盟：HIVNC、CHEAT和Miriam HIV Cohort)，以加快他们的工作。

DESCRIPTION (provided by applicant): In affluent countries where combination anti-retroviral therapy (CART) is widely used, life expectancy with HIV has increased well beyond 10 years, but this has greatly increased the number of people living with HIV/AIDS. 40 million people are now at risk for progressive HIV-related damage to the brain (Navia 2011), and 40% show some neurological or cognitive impairment. Building on our recent discoveries and innovations in MRI and diffusion tensor imaging, our project charts the dynamics of HIV disease in the brain, revealing factors that predict clinical decline and brain decline. By analyzing data from the HIVNC (HIV Neuroimaging Consortium) cohort (218 HIV+ subjects scanned longitudinally with MRI every 26-32 weeks for 3 years; 900 scans), we will use our sensitive image analysis method, tensor-based morphometry to (1) map rates of brain tissue loss over time, determining which brain systems lose tissue fastest; (2) relate these loss patterns to neurocognitive impairment (NCI); and (3) determine which host and disease-related factors, at baseline, predict higher atrophic rates over the 3-year follow-up interval. To deeply probe the causes of dysfunction, we will use whole-brain tractography based on diffusion tensor imaging in 267 subjects to determine where HIV+ patients have reduced fiber integrity. We will use each patient's DTI scan to compute a whole-brain connection matrix, based on a state-of-the-art whole-brain tractography method we developed. We will combine the best neuroimaging measures from Aims 1 and 2 into our support vector machine method to predict (1) future rates of atrophy, and (2) cognitive decline over the 3-year follow-up. With our best predictors of decline from Aims 1 and 2, we will predict which HIV+ patients will show imminent decline. We will estimate the sample sizes needed for a neuroimaging-based drug trial to detect a 5%, 10%, or 25% slowing in the rate of atrophy, and the same percents of slowing in the rate of cognitive decline. We will test whether our predictors generalize to the large, independent Charter and Miriam datasets beyond HIVNC (see Support Letters from Drs. Igor Grant and Ron Cohen), and when used by our many HIV research collaborators now using our methods; see Pilot Data). As shown in new pilot data, we assess how imaging protocol differences affect the measures; our innovations to reduce scan protocol confounds (e.g., adjusted FA) will guide selection of the most robust predictors. We will evaluate how useful these new measures are for predicting cognitive decline, and boosting power in an antiretroviral drug trial. In other words, to what extent can a DTI scan, and an MRI-based map of atrophy, help to make clinical predictions of imminent cognitive impairment? Can they help select a sample for a drug trial? Our activities will make clinical trial design more efficient by selecting subjects with greater potential to respond t future therapies. As always, we will disseminate our methods to both experts and trainees in medicine, neuroscience, engineering, and to our network of over 100 collaborating labs (including two national HIV consortia: HIVNC, CHARTER, and the Miriam HIV cohort), to accelerate their work.