Comprehensive Assessment of MR-Phenotypes and Incidental Findings in the KORA-FF4 Population-based Cohort Study

本基金申请的目的是对KORA-FF 4人群队列研究中的磁共振成像（MRI）特征和偶然发现进行全面评估。我们建议建立在我们现有的MRI数据从全身评估的400名研究对象，并扩展我们的数据分析，重点是先进的MR功能和计算分析的综合评估（前）糖尿病疾病状态和广泛的分析的偶然发现，其相关性的研究参与者的健康和流行病学研究的结果。具体而言，我们的研究目的是：（1）确定糖尿病、前驱糖尿病和健康对照受试者亚临床疾病状态的晚期MR表型的差异。MR表型将包括肝脏体积和肝脏铁沉积，以及心外膜脂肪、左心室应变分析、心脏T1标测以及肺动脉和主动脉直径分析。我们预计，与健康对照相比，糖尿病前期和糖尿病受试者的这些先进成像参数证明，亚临床心血管和代谢疾病负担将会增加且变化。这些变化的程度和确切性质将提供对这些疾病的潜在病理机制和进展的见解。(2)使用基于放射组学的策略开发肝实质计算图像特征的自动分析，以识别除已建立的成像标记物之外的早期肝损伤标记物，并区分糖尿病疾病状态。我们假设新生物标志物的开发将允许对糖尿病前期受试者进行分层，对靶向干预和疾病进展具有潜在影响。(3)在KORA MRI研究中评估偶然发现报告对医疗后果、心理负担以及发病率和死亡率结局的影响。我们假设，将有可测量的痛苦在参与者等待一个偶然的发现报告，特别是披露后的发现。在MRI检查和报告偶然发现后，死亡率结局将增加，但死亡率不会由于充分的随访检查和治疗而增加。

The objective of this grant application is the comprehensive assessment of magnetic resonance imaging (MRI) features and incidental findings in the KORA-FF4 population-based cohort study. We propose to build on our existing MRI data from the whole-body assessment of 400 study subjects and extend our data analysis with a focus on advanced MR-features and computational analyses for comprehensive assessment of (pre-)diabetic disease states and extensive analysis of incidental findings with respect to their relevance for study participants' health and the outcome of epidemiological research. Specifically, the aims of our study are: (1) To determine differences in advanced MR phenotypes of subclinical disease states in subjects with diabetes, prediabetes, and healthy controls. MR phenotypes will include liver volume and hepatic iron deposition, as well as epicardial fat, left ventricular strain analysis, cardiac T1-mapping, and pulmonary artery and aortic diameter analysis. We expect that there will be increased and varied subclinical cardiovascular and metabolic disease burden as evidenced by these advanced imaging parameters in subjects with prediabetes and diabetes in comparison to healthy controls. The extent and exact nature of these changes will provide insights into the underlying patho-mechanisms and progression of these conditions. (2) To develop an automated analysis of computational image features of the liver parenchyma using radiomics-based strategies in order to identify markers of early liver damage beyond established imaging markers and to differentiate diabetic disease states. We hypothesize that the development of novel biomarkers will allow stratification of prediabetic subjects with a potential impact on targeted intervention and disease progression. (3) To assess the effect of incidental finding reporting on medical consequences, psychological burden, and morbidity and mortality outcomes in the KORA MRI study. We hypothesize that there will be measurable distress in participants waiting for an incidental finding report and especially after disclosure of the finding. Morbidity outcomes will be increased after MRI examinations and reporting of incidental findings but mortality will not due to adequate follow-up examinations and therapies.