Key result
Automated motion-guided algorithm yields similar LVEF estimates to an existing vendor tool in post-chemotherapy patients.
Why the study?
To comprehensively outline the methodology of a fully automated, MRI motion-guided LV chamber quantification algorithm enhancing an existing semi-automated approach, and to validate it against a vendor tool in post-chemotherapy breast cancer patients susceptible to cardiotoxicity.
Does a fully automated MRI motion-guided algorithm accurately quantify LV chamber parameters compared to an existing vendor tool in post-chemotherapy breast cancer patients?
Observational (n=42)
No
Does a fully automated MRI motion-guided algorithm accurately quantify LV chamber parameters compared to an existing vendor tool in post-chemotherapy breast cancer patients?
Absolute Event Rate: 59% vs 58%
p-value: p=0.2
A novel automated MRI motion-guided algorithm provides comparable LV chamber quantification to existing vendor tools and can detect subclinical contractile abnormalities in post-chemotherapy patients.
May support automated LVEF quantification in post-chemotherapy monitoring; leaves open prospective validation before clinical adoption.
Purpose: To comprehensively outline the methodology of a fully automated, MRI motion-guided, left-ventricular (LV) chamber quantification algorithm that enhances a similar, existing semi-automated approach. Additionally, to validate the motion-guided technique in comparison to chamber quantification with a vendor tool in post-chemotherapy breast cancer patients susceptible to cardiotoxicity. Approach: LV deformation data were acquired with the displacement encoding with stimulated echoes (DENSE) sequence on N = 21 post-chemotherapy female patients and N = 21 age-matched healthy females. The new chamber quantification algorithm consists of detecting LV boundary motion via a combination of image quantization and DENSE phase-encoded displacements. LV contractility was analyzed via chamber quantification and computations of 3D strains and torsion. For validation, estimates of chamber quantification with the motion-guided algorithm on DENSE and steady-state free precession (SSFP) acquisitions, and similar estimates with an existing vendor tool on DENSE acquisitions were compared via repeated measures analysis. Patient results were compared to healthy subjects for observing abnormalities. Results: Repeated measures analysis showed similar LV ejection fractions (LVEF), 59 % ± 6 % , 58 % ± 6 % , and 58 % ± 6 % , p = 0.2, by applying the motion-guided algorithm on DENSE and SSFP and vendor tool on DENSE acquisitions, respectively. Differences found between patients and healthy subjects included enlarged basal diameters (5.0 ± 0.5 cm versus 4.4 ± 0.5 cm, p < 0.01), torsions (p < 0.001), and longitudinal strains (p < 0.001), but not LVEF (p = 0.1). Conclusions: Measurement similarities between new and existing tools, and between DENSE and SSFP validated the motion-guided algorithm and differences found between subpopulations demonstrate the ability to detect contractile abnormalities.
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Kar et al. (2020) conducted an observational in Chemotherapy-related cardiotoxicity (n=42). Automated motion-guided LV chamber quantification algorithm vs. Circle cvi42 vendor tool was evaluated on Left-ventricular ejection fraction (LVEF) (p=0.2). The automated motion-guided algorithm yielded similar left-ventricular ejection fraction estimates compared to an existing vendor tool (59% vs 58%, p=0.2), validating its use in post-chemotherapy patients.
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