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Matthew S Suffoletto

Publications and source records attributed to Matthew S Suffoletto.

5 recordsLinked to original sources
PubMed2006

A novel two-dimensional echocardiographic image analysis system using artificial intelligence-learned pattern recognition for rapid automated ejection fraction.

OBJECTIVES: We sought to test the hypothesis that a novel 2-dimensional echocardiographic image analysis system using artificial intelligence-learned pattern recognition can rapidly and reproducibly calculate ejection fraction (EF). BACKGROUND: Echocardiographic EF by manual tracing is time consuming, and visual assessment is inherently subjective. METHODS: We studied 218 patients (72 female), including 165 with abnormal left ventricular (LV) function. Auto EF incorporated a database trained on >10,000 human EF tracings to automatically locate and track the LV endocardium from routine grayscale digital cineloops and calculate EF in 15 s. Auto EF results were independently compared with manually traced biplane Simpson's rule, visual EF, and magnetic resonance imaging (MRI) in a subset. RESULTS: Auto EF was possible in 200 (92%) of consecutive patients, of which 77% were completely automated and 23% required manual editing. Auto EF correlated well with manual EF (r = 0.98; 6% limits of agreement) and required less time per patient (48 +/- 26 s vs. 102 +/- 21 s; p < 0.01). Auto EF correlated well with visual EF by expert readers (r = 0.96; p < 0.001), but interobserver variability was greater (3.4 +/- 2.9% vs. 9.8 +/- 5.7%, respectively; p < 0.001). Visual EF was less accurate by novice readers (r = 0.82; 19% limits of agreement) and improved with trainee-operated Auto EF (r = 0.96; 7% limits of agreement). Auto EF also correlated with MRI EF (n = 21) (r = 0.95; 12% limits of agreement), but underestimated absolute volumes (r = 0.95; bias of -36 +/- 27 ml overall). CONCLUSIONS: Auto EF can automatically calculate EF similarly to results by manual biplane Simpson's rule and MRI, with less variability than visual EF, and has clinical potential.

Aged↗
PubMed2006

Velocity vector imaging to quantify ventricular dyssynchrony and predict response to cardiac resynchronization therapy.

Velocity vector imaging is a novel quantitative echocardiographic technique that was applied to routine grayscale echocardiographic images of 23 patients with heart failure who underwent cardiac resynchronization therapy. The hypothesis was tested that velocity vector imaging can quantify left ventricular mechanical dyssynchrony and predict response to resynchronization therapy. Tissue velocities were determined by the automated tracking of periodic B-mode image patterns on digital cine loops from standard apical 4-chamber, 2-chamber, and long-axis views, with the user tracing the mid left ventricular wall from a single frame. Dyssynchrony was determined as the greatest opposing wall peak longitudinal systolic velocity delay from the 3 views. Responders, defined as those with >or=15% increases in the ejection fraction, had greater baseline dyssynchrony than nonresponders (opposing wall velocity delays of 131 +/- 83 vs 52 +/- 60 ms, p <0.05), and >or=75 ms predicted response with 85% sensitivity and 80% specificity when followed 8 +/- 5 months after resynchronization therapy. Baseline electrocardiographic QRS duration was not predictive in the same patients. In conclusion, echocardiographic velocity vector imaging has potential for clinical utility.

Blood Flow Velocity↗
PubMed2006

Novel speckle-tracking radial strain from routine black-and-white echocardiographic images to quantify dyssynchrony and predict response to cardiac resynchronization therapy.

BACKGROUND: Mechanical dyssynchrony is a potential means to predict response to cardiac resynchronization therapy (CRT). We hypothesized that novel echocardiographic image speckle tracking can quantify dyssynchrony and predict response to CRT. METHODS AND RESULTS: Seventy-four subjects were studied: 64 heart failure patients undergoing CRT (aged 64+/-12 years, ejection fraction 26+/-6%, QRS duration 157+/-28 ms) and 10 normal controls. Speckle tracking applied to routine midventricular short-axis images calculated radial strain from multiple circumferential points averaged to 6 standard segments. Dyssynchrony from timing of speckle-tracking peak radial strain was correlated with tissue Doppler measures in 47 subjects (r=0.94, P<0.001; 95% CI 0.90 to 0.96). The ability of baseline speckle-tracking radial dyssynchrony (time difference in peak septal wall-to-posterior wall strain > or =130 ms) to predict response to CRT was then tested. It predicted an immediate increase in stroke volume in 48 patients studied the day after CRT with 91% sensitivity and 75% specificity. In 50 patients with long-term follow-up 8+/-5 months after CRT, baseline speckle-tracking radial dyssynchrony predicted a significant increase in ejection fraction with 89% sensitivity and 83% specificity. Patients in whom left ventricular lead position was concordant with the site of latest mechanical activation by speckle-tracking radial strain had an increase in ejection fraction from baseline to a greater degree (10+/-5%) than patients with discordant lead position (6+/-5%; P<0.05). CONCLUSIONS: Speckle-tracking radial strain can quantify dyssynchrony and predict immediate and long-term response to CRT and has potential for clinical application.

Adult↗
PubMed2005

Utility of echocardiographic radial strain imaging to quantify left ventricular dyssynchrony and predict acute response to cardiac resynchronization therapy.

Echocardiographic strain imaging was used to quantify radial mechanical dyssynchrony in 38 patients who underwent cardiac resynchronization therapy. Dyssynchrony, defined as the time difference of peak radial strain in the septum versus the posterior wall, was significantly greater in patients with acute hemodynamic responses, and changes in radial dyssynchrony correlated with changes in stroke volume. A > or =130-ms difference in septal versus posterior wall peak strain when combined with a favorable left ventricular lead position was strongly predictive of immediate improvement in stroke volume with resynchronization therapy (95% sensitivity, 88% specificity), regardless of electrocardiographic QRS duration.

Aged↗