Key result
A 3D threshold-based segmentation algorithm for cardiac MRI yielded left ventricular volumes comparable to manual tracing (EDV 104.5 vs 104.7 mL, P>0.05) with significantly shorter evaluation times.
Why the study?
Does a 3D threshold-based segmentation algorithm provide accurate and faster assessment of left ventricular volumes compared to manual tracing and semiautomatic contour detection in patients undergoing cardiac MRI?
Observational (n=44)
Does a 3D threshold-based segmentation algorithm provide accurate and faster assessment of left ventricular volumes compared to manual tracing and semiautomatic contour detection in patients undergoing cardiac MRI?
Absolute Event Rate: 104.5% vs 104.7%
p-value: p=> 0.05
Automated 3D threshold-based segmentation allows for significantly faster and reproducible assessment of left ventricular volumes in cardiac MRI compared to manual and semiautomatic methods.
May accelerate LV volumetry in cardiac MRI; leaves open prospective validation across broader populations and endpoints.
OBJECTIVES: Our study aimed to evaluate a three-dimensional (3D) threshold-based, region-growing segmentation algorithm for the assessment of left ventricular (LV) volumes in cardiac MRI. MATERIALS AND METHODS: Two-dimensional cine steady-state free precession short-axis scans (TR 3 milliseconds, TE 1.5 milliseconds, FA 60 degrees , section thickness 8 mm) covering the entire LV without slice gap were acquired in 44 consecutive patients on a 1.5 Tesla MR system (Magnetom Avanto, Siemens, Germany). LV volumes were assessed with an in-house written 3D threshold-based, interslice region-growing segmentation algorithm, and were compared with manual tracing and short-axis planimetry with semiautomatic contour detection (Argus software, Siemens, Germany). RESULTS: Three-dimensional threshold-based segmentation was feasible in 41 of 44 patients. Results of threshold-based segmentation were not statistically significantly different to manual tracing for the assessment of end-diastolic (EDV: 104.5 +/- 32.3 mL vs. 104.7 +/- 33.26 mL, P > 0.05), end-systolic (ESV: 34.5 +/- 17.2 mL vs. 33.8 +/- 17.45 mL, P > 0.05), and stroke (SV: 69.9 +/- 25.0 mL vs. 70.9 +/- 25.0 mL, P > 0.05) volumes. Bland-Altmann plots showed systematic lower EDV (-12.0 +/- 6.7 mL), ESV (-4.8 +/- 3.7 mL), and SV (-7.3 +/- 7.6 mL), and a systematic higher ejection fraction (0.4% +/- 5.0%) for threshold-based segmentation compared with short-axis planimetry with semiautomatic contour detection. Threshold-based segmentation showed an excellent reproducibility with low absolute differences between 2 consecutive analyses (EDV: 0.2 +/- 2.2 mL; ESV: 0.5 +/- 1.9 mL; SV: 0.6 +/- 3.4 mL; EF: 0.5% +/- 2.1%). Evaluation times were significantly shorter for threshold-based segmentation (60 +/- 16 vs. 278 +/- 31 seconds/669 +/- 157 seconds, P < 0.0001). CONCLUSION: Automated threshold-based segmentation of the left ventricle allows fast and reproducible assessment of LV volumes in cardiac MRI. Exclusion of papillary muscles and myocardial trabeculations from LV volumes leads to systematically lower LV volumes compared with short axis planimetry with semi-automatic contour detection.
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Naßenstein et al. (2009) conducted an observational in Cardiac MRI assessment (n=44). 3D threshold-based region-growing segmentation algorithm vs. Manual tracing and short-axis planimetry with semiautomatic contour detection was evaluated on End-diastolic volume (EDV) (p=> 0.05). A 3D threshold-based segmentation algorithm for cardiac MRI yielded left ventricular volumes comparable to manual tracing (EDV 104.5 vs 104.7 mL, P>0.05) with significantly shorter evaluation times.
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