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Abstract #0326

Sensor-free physiological guidance for free-breathing cardiac cine reconstruction using CineJENSE: example of an arrhythmic patient

Lucile Quillien1, Martin Doguet1, Nora Vogt1, Ziad Al-Haj Hemidi2, Pierre-André Vuissoz1, and Julien Oster1,3
1IADI, INSERM U1254, Université de Lorraine, Nancy, France, 2Institute of Medical Informatics, Universität zu Lübeck, Lübeck, Germany, 3CIC-IT, INSERM 1433, Université de Lorraine et CHRU de Nancy, Nancy, France

Synopsis

Keywords: Image Reconstruction, Cardiovascular

Motivation: Explore the estimation of physiological signals using the thermal noise variance of radiofrequency coils to reconstruct free-breathing cardiac cine images.

Goal(s): Evaluate the reliability of noise variance estimations for ungated free-breathing reconstruction.

Approach: Free-breathing reconstructions with reference signals (ECG and respiratory belts) were compared to sensor-free reconstructions using the CineJENSE algorithm with implicit neural representations. The motion estimation and reconstruction for an arrhythmic patient with a bigeminy were examined.

Results: The correlation coefficient for the respiration and the F1-score of the cardiac peak detections were computed for quantitative evaluation and showed good concordance with the reference signals, even for the arrhythmic patient.

Impact: Sensor-free physiological signal estimations using noise variance from k-space data for free-breathing ungated cardiac cine reconstruction were shown for two examples (healthy volunteer and arrhythmic patient). Results showed good concordance with reference signals and the reconstructions could be performed.

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Keywords