Related Experiment Video
Updated: Jun 12, 2025
Author Spotlight: Enhancing Diagnostic Strategies and Biomarker Development for Comprehensive Lung Function Analysis
Published on: August 9, 2024
An automated pipeline for computation and analysis of functional ventilation and perfusion lung MRI with matrix
Orso Pusterla1, Corin Willers2, Robin Sandkühler3
1Department of Radiology, Division of Radiological Physics, University Hospital Basel, University of Basel, Basel, Switzerland; Department of Biomedical Engineering, University of Basel, Basel, Switzerland; Division of Pediatric Respiratory Medicine and Allergology, Department of Pediatrics, Inselspital, Bern University Hospital, University of Bern, Switzerland.
Purpose:
To introduce and evaluate TrueLung, an automated pipeline for computation and analysis of free-breathing and contrast-agent free pulmonary functional magnetic resonance imaging.
Materials And Methods:
Two-dimensional time-resolved ultra-fast balanced steady-state free precession acquisitions were transferred to TrueLung, which included image quality checks, image registration, and computation of perfusion and ventilation maps with matrix pencil decomposition. Neural network whole-lung and lobar segmentations allowed quantification of impaired relative perfusion (RQ) and fractional ventilation (RFV). TrueLung delivered functional maps and quantitative outcomes, reported for clinicians in concise documents. We evaluated the pipeline using 1.5T data from 75 children with cystic fibrosis by assessing the feasibility of functional MR imaging, average scan time, and the robustness of the functional outcomes. Whole-lung and lobar segmentations were manually refined when necessary, and the impact on RQ and RFV was quantified.
Results:
Functional imaging was feasible in all included CF children without any dropouts. On average, 7.9 ± 1.8 (mean±SD) coronal slice positions per patient were acquired, resulting in a mean scan time of 6min 20s per patient. The whole pipeline required 20min processing time per subject. TrueLung delivered the functional maps of all the subjects for radiological assessment. Quality controlling maps and segmentations lasted 1min 12s per patient. The automated segmentations and quantification of whole-lung defects were satisfying in 88% of patients (97% of slices) and the lobar quantification in 73% (93% of slices). The segmentations refinements required 16s per patient for the whole-lung, and 2min 10s for the lobe masks. The relative differences in RFV and RQ between fully-automated and manually refined data were 0.7% (1.2%) and 2.0% (2.9%) for whole-lung quantification (median, [third quartile]), and excluding two outliers, 1.7% (3.9%) and 1.2% (3.8%) for the lobes, indicating the refinements could be potentially omitted in several patients.
Conclusions:
TrueLung quickly delivers functional maps and quantitative outcomes in an objective and standardized way, suitable for radiological and pneumological assessment with minimal manual input. TrueLung can be used for clinical research in cystic fibrosis and might be applied across various lung diseases.
