Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
566-03-002 ISMRM Abstract

Lung UTE MRI in systemic sclerosis: impact of signal normalisation technique and correlation with cardiopulmonary function

Primary: Analysis Methods - Data Processing
Secondary: Body - Lung
566-03-002 · Radiomics Potpourri · Wednesday, 13 May, 1:40 PM–2:35 PM · Digital Posters Row G
Keywords: Lung Quantitative Imaging Ultra-short Echo Time (UTE) Lung MRI Quantitative MRI metrics
Accepted
Laura C Saunders 1,2, Muad M Almsaaid3, Amy V Simmons1, Mack Caraher3, Laurie Smith1, Alberto M Biancardi1,2, Neil J Stewart1,2, Andy J Swift3,4, Robin Condliffe3,4, Alexander Rothman3,4, David Kiely3,4, Roger Thompson3,4, Jim Wild1,2
1POLARIS, Division of Clinical Medicine, School of Medicine & Population Health, The University of Sheffield, Sheffield, United Kingdom
2INSIGNEO Institute for In Silico Medicine, The University of Sheffield, Sheffield, United Kingdom
3Division of Clinical Medicine, School of Medicine & Population Health, The University of Sheffield, Sheffield, United Kingdom
4Sheffield Teaching Hospitals, Sheffield, United Kingdom
Presenting Author: Laura C Saunders

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References

1. Landini, N., et al., Advanced and traditional chest MRI sequence for the clinical assessment of systemic sclerosis related interstitial lung disease, compared to CT: disease extent analysis and correlations with pulmonary function tests. Eur J Radiol, 2024. 170: p. 111239.
2. Landini, N., et al., Ultrashort Echo-Time Magnetic Resonance Imaging Sequence in the Assessment of Systemic Sclerosis-Interstitial Lung Disease. J Thorac Imaging, 2023. 38(2): p. 97-103.
3. Higano, N.S., et al., Quantification of neonatal lung parenchymal density via ultrashort echo time MRI with comparison to CT. J Magn Reson Imaging, 2017. 46(4): p. 992-1000.
4. Meadus, W.Q., et al., Quantification of lung water density with UTE Yarnball MRI. Magn Reson Med, 2021. 86(3): p. 1330-1344.
5. Johnson, K.M., et al., Optimized 3D ultrashort echo time pulmonary MRI. Magn Reson Med, 2013. 70(5): p. 1241-50.
6. Astley, J.R., et al., Implementable Deep Learning for Multi-sequence Proton MRI Lung Segmentation: A Multi-center, Multi-vendor, and Multi-disease Study. J Magn Reson Imaging, 2023. 58(4): p. 1030-1044.
7. D'Errico, J., Surface Fitting using gridfit. MATLAB Central File Exchange. 2025.
8. Heidenreich, J.F., et al., Three-dimensional Ultrashort Echo Time MRI for Functional Lung Imaging in Cystic Fibrosis. Radiology, 2020. 296(1): p. 191-199.
9. Tustison, N.J., et al., N4ITK: improved N3 bias correction. IEEE Trans Med Imaging, 2010. 29(6): p. 1310-20.
10. Uecker, M., et al., ESPIRiT--an eigenvalue approach to autocalibrating parallel MRI: where SENSE meets GRAPPA. Magn Reson Med, 2014. 71(3): p. 990-1001.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/566-03-002