Multistage self-gated lung imaging in small rodents

• Published in: Magnetic resonance in medicine 2016-06, Vol.75 (6), p.2448-2454
• Main Authors: Tibiletti, Marta, Kjørstad, Åsmund, Bianchi, Andrea, Schad, Lothar R., Stiller, Detlef, Rasche, Volker
• Format: Article
• Language: English
• Subjects: Animals; free-breathing; gated acquisition; Image Processing, Computer-Assisted - methods; Lung - diagnostic imaging; Lung - physiology; lung MRI; Lung Volume Measurements; Magnetic Resonance Imaging - methods; Male; Rats; Rats, Wistar; self-gating; Signal-To-Noise Ratio; ultrashort echo time imaging; UTE
• ISSN: 0740-3194; 1522-2594
• DOI: 10.1002/mrm.25849

Purpose To investigate the exploitation of the self‐gating signal in ultrashort echo time (UTE) two‐dimensional (2D) acquisitions of freely breathing rats to reconstruct multiple respiratory stages. Methods Twelve rats were investigated with a 2D golden angle UTE protocol (12 coronal slices, echo time 0.343 ms, repetition time 120 ms, thickness 1 mm, flip angle 30°, matrix 256 × 256, 20‐fold oversampling). The self‐gating signal was extracted from the k‐space center and sorted into five respiration bins (expiration, inspiration, three intermediate stages). Lung volume, sharpness, signal to noise ratio (SNR) and normalized signal intensity (NSI) were investigated. Time resolved images were reconstructed to visualize global animal motion. Results The method delineated that the lung volume decreased gradually from inspiration to expiration. Sharpness index resulted higher in expiration than in the ungated images. SNR was higher in ungated images and in expiration, decreasing gradually toward inspiration. NSI values presented a similar trend, with ungated images showing lower values than the expiration images. In one animal clear global motion and in seven animals minor movements were identified. Conclusion The presented respiratory gating method allows the reconstruction of different respiratory positions. Improved sharpness in expiration images was observed compared with ungated images. SNR and NSI changes in parenchyma reflect the expected variation of lung tissue density during respiration. Magn Reson Med 75:2448–2454, 2016. © 2015 Wiley Periodicals, Inc.