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UTE-SENCEFUL: first results for 3D high-resolution lung ventilation imaging.
- Source :
-
Magnetic resonance in medicine [Magn Reson Med] 2019 Apr; Vol. 81 (4), pp. 2464-2473. Date of Electronic Publication: 2018 Nov 04. - Publication Year :
- 2019
-
Abstract
- Purpose: This study aimed to develop a 3D MRI technique to assess lung ventilation in free-breathing and without the administration of contrast agent.<br />Methods: A 3D-UTE sequence with a koosh ball trajectory was developed for a 3 Tesla scanner. An oversampled k-space was acquired, and the direct current signal from the k-space center was used as a navigator to sort the acquired data into 8 individual breathing phases. Gradient delays were corrected, and iterative SENSE was used to reconstruct the individual timeframes. Subsequently, the signal changes caused by motion were eliminated using a 3D image registration technique, and ventilation-weighted maps were created by analyzing the signal changes in the lung tissue. Six healthy volunteers and 1 patient with lung cancer were scanned with the new 3D-UTE and the standard 2D technique. Image quality and quantitative ventilation values were compared between both methods.<br />Results: UTE-based self-gated noncontrast-enhanced functional lung (SENCEFUL) MRI provided a time-resolved reconstruction of the breathing motion, with a 49% increase of the SNR. Ventilation quantification for healthy subjects was in statistical agreement with 2D-SENCEFUL and the literature, with a mean value of 0.11 ± 0.08 mL/mL for the whole lung. UTE-SENCEFUL was able to visualize and quantify ventilation deficits in a patient with lung tumor that were not properly depicted by 2D-SENCEFUL.<br />Conclusion: UTE-SENCEFUL represents a robust MRI method to assess both morphological and functional information of the lungs in 3D. When compared to the 2D approach, 3D-UTE offered ventilation maps with higher resolution, improved SNR, and reduced ventilation artifacts.<br /> (© 2018 International Society for Magnetic Resonance in Medicine.)
- Subjects :
- Adult
Algorithms
Artifacts
Carcinoma, Non-Small-Cell Lung diagnostic imaging
Female
Healthy Volunteers
Humans
Image Interpretation, Computer-Assisted methods
Magnetic Resonance Imaging
Male
Middle Aged
Motion
Perfusion
Respiratory-Gated Imaging Techniques methods
Signal-To-Noise Ratio
Young Adult
Contrast Media chemistry
Image Processing, Computer-Assisted methods
Imaging, Three-Dimensional methods
Lung diagnostic imaging
Lung Neoplasms diagnostic imaging
Respiration
Subjects
Details
- Language :
- English
- ISSN :
- 1522-2594
- Volume :
- 81
- Issue :
- 4
- Database :
- MEDLINE
- Journal :
- Magnetic resonance in medicine
- Publication Type :
- Academic Journal
- Accession number :
- 30393947
- Full Text :
- https://doi.org/10.1002/mrm.27576