Prediction of Cardiac Resynchronization Therapy Response Using a Lead Placement Score Derived From 4-Dimensional Computed Tomography. (16th August 2022)

• Record Type: Journal Article
• Authors: Manohar, Ashish; Colvert, Gabrielle M.; Yang, James; Chen, Zhennong; Ledesma-Carbayo, Maria J.; Kronborg, Mads Brix; Sommer, Anders; Nørgaard, Bjarne L.; Nielsen, Jens Cosedis; McVeigh, Elliot R.
• Is Part Of: Circulation. Volume 15:Number 8(2022)
• Page Start: e014165
• Publication Date: 2022-08-16
• Subjects: cardiac imaging techniques -- cardiac resynchronization therapy -- four-dimensional computed tomography -- heart failure -- heart function tests -- support vector machine -- ventricular function; Cardiovascular system -- Imaging -- Periodicals; Heart -- Imaging -- Periodicals; 616.1075405
• DOI: 10.1161/CIRCIMAGING.122.014165
• Languages: English
• ISSNs: 1941-9651

Abstract

Abstract : Background: Cardiac resynchronization therapy (CRT) is an effective treatment for patients with heart failure; however, 30% of patients do not respond to the treatment. We sought to derive patient-specific left ventricle maps of lead placement scores (LPS) that highlight target pacing lead sites for achieving a higher probability of CRT response. Methods: Eighty-two subjects recruited for the ImagingCRT trial (Empiric Versus Imaging Guided Left Ventricular Lead Placement in Cardiac Resynchronization Therapy) were retrospectively analyzed. All 82 subjects had 2 contrast-enhanced full cardiac cycle 4-dimensional computed tomography scans: a baseline and a 6-month follow-up scan. CRT response was defined as a reduction in computed tomography–derived end-systolic volume ≥15%. Eight left ventricle features derived from the baseline scans were used to train a support vector machine via a bagging approach. An LPS map over the left ventricle was created for each subject as a linear combination of the support vector machine feature weights and the subject's own feature vector. Performance for distinguishing responders was performed on the original 82 subjects. Results: Fifty-two (63%) subjects were responders. Subjects with an LPS≤Q1 (lower-quartile) had a posttest probability of responding of 14% (3/21), while subjects with an LPS≥ Q3 (upper-quartile) had a posttest probability of responding of 90% (19/21). Subjects with Q1 3 had a posttest probability of responding that was essentially unchanged from the pretest probability (75% versus 63%, P =0.2). An LPS threshold that maximized the geometric mean of true-negative and true-positive rates identified 26/30 of the nonresponders. The area under the curve of the receiver operating characteristic curve for identifying responders with an LPS threshold was 87%. Conclusions: An LPS map was defined using 4-dimensional computed tomography–derived features of left ventricular mechanics. The LPS correlated with CRT response, reclassifying 25% of the subjects into low probability of response, 25% into high probability of response, and 50% unchanged. These encouraging results highlight the potential utility of 4-dimensional computed tomography in guiding patient selection for CRT. The present findings need verification in larger independent data sets and prospective trials.