Coronary artery disease (CAD) causes nearly 60% of deaths in patients with type 2 diabetes mellitus (T2DM). Subclinical CAD may silently progress over a long time period until coronary events, a group of symptoms attributed to myocardial ischemia, strike T2DM patients. Limited by invasiveness, X-ray exposure and nephrotoxic contrast media, current diagnostic methods are insufficient to estimate the severity of subclinical CAD in T2DM patients without documented or suspected cardiovascular diseases. Over the past decade, magnetic resonance imaging (MRI) has emerged as a promising noninvasive method for quantifying morphological and functional changes of remodeled coronary wall, which convey the risk of coronary events. Recent studies also provide evidence that MRI can evaluate changes in myocardial tissue structure (fibrosis and edema) and ventricular motion/function. Based on the technical advances, we hypothesize that MRI-derived characteristics of subclinical CAD and related myocardial abnormalities have the potential to serve as quantitative imaging biomarkers presenting the cardiovascular risk under pathophysiological circumstances of T2DM. In this proposal, we will build a novel 60-minute MRI protocol to delineate the prevalence and extent of subclinical CAD coupled with concomitant structure-function changes of the heart in T2DM patients with and without diabetic nephropathy (DN). DN is a common end-organ damage occurs in nearly 40% T2DM patients and has been considered as an independent predictor of coronary events. Then, we will link coronary/cardiac measurements to T2DM/DN biomarkers in the blood and urine. These investigations will be performed to preliminary test the potential clinical value of these MRI-derived signatures for indicating the efficacy of cardiovascular prevention and target-organ protection in T2DM regimens. The mentored research will facilitate my immediate goal of expanding my expertise in screening quantitative imaging biomarkers by applying the experience and knowledge acquired in my previous work to address unmet clinical needs for T2DM patients using quantitative MRI. The project also fits my long-term career goal of becoming an independent investigator in cardiovascular medicine by launching a clinical study for the estimation of cardiovascular risk in T2DM population. Taking advantage of the unique research environments and world-class educational opportunities at Northwestern University Feinberg School of Medicine (NU/FSM), I will receive intensive training and structured tutorials in clinical cardiovascular research, including hands-on training in advanced cardiovascular imaging and diabetic biomarker identification/testing; course work in epidemiology and biostatistics; and research seminars and scientific meetings, to achieve my career goals.

Public Health Relevance

In the present study, we will observe and quantify subclinical CAD in T2DM patients using quantitative MRI. We will also test the potential clinical value of coronary/cardiac features for indicating the efficacy of cardiovascular prevention and target-organ protection of T2DM management. A standardized measurement of the development of CAD is important for characterizing individual cardiovascular responses to diabetic therapies.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
1K01HL121162-01A1
Application #
8821778
Study Section
Special Emphasis Panel (ZHL1-CSR-K (O1))
Program Officer
Papanicolaou, George
Project Start
2015-09-01
Project End
2020-06-30
Budget Start
2015-09-01
Budget End
2016-06-30
Support Year
1
Fiscal Year
2015
Total Cost
$135,356
Indirect Cost
$9,656
Name
Northwestern University at Chicago
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
005436803
City
Chicago
State
IL
Country
United States
Zip Code
60611
Lin, Kai; Suwa, Kenichiro; Ma, Heng et al. (2018) Variability of native T1 values: implication for defining regional myocardial changes using MRI. Int J Cardiovasc Imaging 34:1637-1645
Ma, Heng; Yang, Jun; Xie, Haizhu et al. (2018) Regional myocardial motion in patients with mild cognitive impairment: a pilot study. BMC Cardiovasc Disord 18:79
Lin, Kai; Meng, Leng; Collins, Jeremy D et al. (2017) Heart deformation analysis: the distribution of regional myocardial motion patterns at left ventricle. Int J Cardiovasc Imaging 33:351-359
Lin, Kai; Meng, Leng; Collins, Jeremy D et al. (2017) Reproducibility of cine displacement encoding with stimulated echoes (DENSE) in human subjects. Magn Reson Imaging 35:148-153
Lin, Kai; Collins, Jeremy D; Chowdhary, Varun et al. (2016) Heart deformation analysis for automated quantification of cardiac function and regional myocardial motion patterns: A proof of concept study in patients with cardiomyopathy and healthy subjects. Eur J Radiol 85:1811-1817
Lin, Kai; Collins, Jeremy D; Chowdhary, Varun et al. (2016) Heart deformation analysis: measuring regional myocardial velocity with MR imaging. Int J Cardiovasc Imaging 32:1103-11
Lin, Kai; Collins, Jeremy D; Lloyd-Jones, Donald M et al. (2016) Automated Assessment of Left Ventricular Function and Mass Using Heart Deformation Analysis: Initial Experience in 160 Older Adults. Acad Radiol 23:321-5