Premium
UTE‐SENCEFUL: first results for 3D high‐resolution lung ventilation imaging
Author(s) -
Mendes Pereira L.,
Wech T.,
Weng A.M.,
Kestler C.,
Veldhoen S.,
Bley T.A.,
Köstler H.
Publication year - 2019
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.27576
Subject(s) - ventilation (architecture) , lung , nuclear medicine , gradient echo , lung ventilation , medicine , lung cancer , image quality , breathing , signal (programming language) , computer science , biomedical engineering , magnetic resonance imaging , radiology , computer vision , image (mathematics) , physics , pathology , anatomy , thermodynamics , programming language
Purpose This study aimed to develop a 3D MRI technique to assess lung ventilation in free‐breathing and without the administration of contrast agent. 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. 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. 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.