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. METHODS AND 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.
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. METHODS AND 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.
Authors: Jonathan W Weinsaft; Jiwon Kim; Chaitanya B Medicherla; Claudia L Ma; Noel C F Codella; Nina Kukar; Subhi Alaref; Raymond J Kim; Richard B Devereux Journal: JACC Cardiovasc Imaging Date: 2015-10-14
Authors: Jiwon Kim; Sara Rodriguez-Diego; Aparna Srinivasan; Rachel-Maria Brown; Meridith P Pollie; Antonino Di Franco; Samantha R Goldburg; Jonathan Y Siden; Mark B Ratcliffe; Robert A Levine; Richard B Devereux; Jonathan W Weinsaft Journal: Echocardiography Date: 2017-08-22 Impact factor: 1.724
Authors: Gastón A Rodríguez-Granillo; Marlon Mejía-Campillo; Miguel A Rosales; Gabriel Bolzán; Carlos Ingino; Federico López; Elina Degrossi; Pedro Lylyk Journal: Int J Cardiovasc Imaging Date: 2011-05-07 Impact factor: 2.357
Authors: Adam R Williams; Konstantinos E Hatzistergos; Benjamin Addicott; Fred McCall; Decio Carvalho; Viky Suncion; Azorides R Morales; Jose Da Silva; Mark A Sussman; Alan W Heldman; Joshua M Hare Journal: Circulation Date: 2012-12-05 Impact factor: 29.690
Authors: Jiwon Kim; Aparna Srinivasan; Tania Seoane; Antonino Di Franco; Charles S Peskin; David M McQueen; Tracy K Paul; Attila Feher; Alexi Geevarghese; Meenakshi Rozenstrauch; Richard B Devereux; Jonathan W Weinsaft Journal: J Am Soc Echocardiogr Date: 2016-06-11 Impact factor: 5.251