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Front Med (Lausanne). 2019 Feb 12;6:18. doi: 10.3389/fmed.2019.00018. eCollection 2019.

MR Volumetry of Lung Nodules: A Pilot Study.

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Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland.
Centre de Recherche Cardio-Thoracique de Bordeaux, Université de Bordeaux, Bordeaux, France.
Inserm, Centre de Recherche Cardio-Thoracique de Bordeaux, Bordeaux, France.
CHU de Bordeaux, Service d'Imagerie Thoracique et Cardiovasculaire, Service des Maladies Respiratoires, Service d'Exploration Fonctionnelle Respiratoire, Pessac, France.
Service of Pneumology, Department of Medicine, Lausanne University Hospital (CHUV), Lausanne, Switzerland.
Department of Physiotherapy, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland.
Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.
Center for Biomedical Imaging, Lausanne, Switzerland.
Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Lausanne, Switzerland.


Introduction: Computed tomography (CT) is currently the reference modality for the detection and follow-up of pulmonary nodules. While 2D measurements are commonly used in clinical practice to assess growth, increasingly 3D volume measurements are being recommended. The goal of this pilot study was to evaluate preliminarily the capabilities of 3D MRI using ultra-short echo time for lung nodule volumetry, as it would provide a radiation-free modality for this task. Material and Methods: Artificial nodules were manufactured out of Agar and measured using an ultra-short echo time MRI sequence. CT data were also acquired as a reference. Image segmentation was carried out using an algorithm based on signal intensity thresholding (SIT). For comparison purposes, we also performed manual slice by slice segmentation. Volumes obtained with MRI and CT were compared. Finally, the volumetry of a lung nodule was evaluated in one human subject in comparison with CT. Results: Using the SIT technique, minimal bias was observed between CT and MRI across the entire range of volumes (2%) with limits of agreement below 14%. Comparison of manually segmented MRI and CT resulted in a larger bias (8%) and wider limits of agreement (-23% to 40%). In vivo, nodule volume differed of <16% between modalities with the SIT technique. Conclusion: This pilot study showed very good concordance between CT and UTE-MRI to quantify lung nodule volumes, in both a phantom and human setting. Our results enhance the potential of MRI to quantify pulmonary nodule volume with similar performance to CT.


MRI; UTE; lung; nodules; segmentation; volumetry

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