Pompe disease is a progressive muscular disorder that will affect the respiratory muscles, in particular the diaphragm, thereby seriously limiting the respiratory function. Respiratory function is typically assessed using spirometry. However early stages of diaphragm impairment may not be detected by conventional spirometry measurements due to compensatory efforts of other inspiratory muscles. In this study we aimed to use 3D MRI as a sensitive method to assess diaphragm function and identify diaphragm impairment. Static breath-hold 3D MRI scans at maximal inspiration and maximal expiration were obtained from a previously used dataset in 18 healthy controls and 35 Pompe patients with varying degrees of diaphragm weakness. Images were segmented using an automatic script. The segmentations were used to create an anatomically accurate 3D mesh model of the lungs. The surface of the mesh was divided into topographical segments based on the anatomical surfaces of the lungs. Vital capacity (VC) measurements were retrieved from the mesh model (VCmesh) and compared against spirometry VC measurements made during the MRI acquisition (VCspiro) in order to validate the mesh model. Segmental volumes, derived from the topographical segments identified on the surface of the mesh model, were reallocated based on changes in lung dimensions to provide a more accurate functional topographical representation of the underlying diaphragm and intercostal muscle functions. The relative contributions of the diaphragm and intercostal muscles to the total increase in lung volume during inspiration were assesses for differences between healthy controls and Pompe patients and compared against common spirometry and 2D analysis outcomes. A large and significant correlation was established between VCmesh and VCspiro, rs = 0.971, p < 0.001. Median VCspiro was significantly larger than median VCmesh across all population groups (p < 0.001), by an average amount of 0.31 L. This represented a mean difference between the two measurement methods of 9.3% of the mean VC measurements. It has also been demonstrated that median changes in diaphragm volume (p < 0.001) and the median relative contribution of the diaphragm to the total increase in lung volume during inspiration (p = 0.009) were lower in Pompe patients with decreased spirometry results when compared against healthy controls. Changes in diaphragm volumes correlated well with conventional VC and FVC measurements (rs = 0.997, p < 0.001) as well as with changes in superoinferior lung sizes (rs = 0.936, p < 0.001). In some Pompe patients with decreased spirometry results no indication for diaphragm impairment was found when assessing the relative contribution of the diaphragm to the total increase in lung volume during inspiration. A mesh model based on 3D MRI segmentations provides an accurate method of assessing diaphragm function. Changes in diaphragm volume and the contribution of the diaphragm to the increase in lung volume during inspiration allow for the assessment of diaphragm impairment in Pompe patients. These biomarkers of diaphragm function may prove to be highly useful in determining a personalized treatment plan for Pompe patients as well as a sensitive outcome in trials to test future treatment modalities.

Many pulmonary diseases, such as cystic fibrosis (CF), chronic obstructive pulmonary disease (COPD) or asthma are disrupting the lung perfusion/ventilation ratio. Therefore, monitoring it gives a good overview on the evolution of the disease. There are several imaging modalities to assess the ventilation and perfusion, but they either use ionizing radiation, are expensive, uncomfortable or pose the risk of allergic reactions. Fourier decomposition MRI is a radiation and contrast free technique to image the lungs that is also used while the patient can breathe freely. It is based on the separation of the ventilation and perfusion signals, according to their frequency. Built on top of this is the Phase-Resolved Functional Lung MRI (PREFUL) which allows for the reconstruction of the breathing and cardiac cycle based on the phases of the acquired signal. The present study analysed different methods to extract the phase, to obtain the ventilation and perfusion maps and to threshold and detect the defects. It was found that the methods based on sine fitting and Morlet wavelet are the most promising, with the latter having the advantages of a variable window size and frequency. The most promising threshold for perfusion is the 75th percentile * 0.6 and for ventilation the 90th percentile * 0.4. Despite not correlating very well with the established methods, PREFUL analysis could still be useful in comparing different patients and tracking the progress of lung diseases.