Automated segmentation of routine clinical cardiac magnetic resonance imaging for assessment of left ventricular diastolic dysfunction.
BACKGROUND
Cardiac magnetic resonance (CMR) is established for assessment of left ventricular (LV) systolic function but has not been widely used to assess diastolic function. This study tested performance of a novel CMR segmentation algorithm (LV-METRIC) for automated assessment of diastolic function.


RESULTS
A total of 101 patients with normal LV systolic function underwent CMR and echocardiography (echo) within 7 days. LV-METRIC generated LV filling profiles via automated segmentation of contiguous short-axis images (204+/-39 images, 2:04+/-0:53 minutes). Diastolic function by CMR was assessed via early:atrial filling ratios, peak diastolic filling rate, time to peak filling rate, and a novel index-diastolic volume recovery (DVR), calculated as percent diastole required for recovery of 80% stroke volume. Using an echo standard, patients with versus without diastolic dysfunction had lower early:atrial filling ratios, longer time to peak filling rate, lower stroke volume-adjusted peak diastolic filling rate, and greater DVR (all P<0.05). Prevalence of abnormal CMR filling indices increased in relation to clinical symptoms classified by New York Heart Association functional class (P=0.04) or dyspnea (P=0.006). Among all parameters tested, DVR yielded optimal performance versus echo (area under the curve: 0.87+/-0.04, P<0.001). Using a 90% specificity cutoff, DVR yielded 74% sensitivity for diastolic dysfunction. In multivariate analysis, DVR (odds ratio, 1.82; 95% CI, 1.13 to 2.57; P=0.02) was independently associated with echo-evidenced diastolic dysfunction after controlling for age, hypertension, and LV mass (chi(2)=73.4, P<0.001).


CONCLUSIONS
Automated CMR segmentation can provide LV filling profiles that may offer insight into diastolic dysfunction. Patients with diastolic dysfunction have prolonged diastolic filling intervals, which are associated with echo-evidenced diastolic dysfunction independent of clinical and imaging variables.
Kawaji
Keigo
K
Department of Radiology and the Division of Cardiology, Weill Cornell Medical College, New York, NY 10021, USA.
Codella
Noel C F
NC
Prince
Martin R
MR
Chu
Christopher W
CW
Shakoor
Aqsa
A
LaBounty
Troy M
TM
Min
James K
JK
Swaminathan
Rajesh V
RV
Devereux
Richard B
RB
Wang
Yi
Y
Weinsaft
Jonathan W
JW
D000368:Aged; D000465:Algorithms; D001331:Automation; D016009:Chi-Square Distribution; D003971:Diastole; D015150:Echocardiography, Doppler; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016015:Logistic Models; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D012372:ROC Curve; D012680:Sensitivity and Specificity; D013318:Stroke Volume; D016277:Ventricular Function, Left / Q000502:physiology*