Recently, regional ventilation deficits were estimated in asthmatics based on the change in signal-intensity measured at different lung volumes using conventional ¹H MR-methods and echo-times.¹ MRI signal-intensity is influenced by hardware factors such as RF amplifications and the positioning of the RF coils, which introduce inter-scan variability. Because of this, it is difficult to ascertain the physiological meaning of ¹H MR signal-intensity changes, especially in asthma where there are complex airway abnormalities that result in gas-trapping and ventilation/perfusion abnormalities. One way to better understand these MR signal-intensity differences in asthma is to compare these directly with well-established measurements with clear physical meaning, such as CT radio-density. This was recently accomplished using ultra-short echo-time (UTE) 2D MRI in COPD and bronchiectasis² but not in asthma patients. Thus, the objective of this work was to determine the underlying structural determinants of UTE MR signal-intensity by regionally evaluating multi-volume UTE maps with direct comparison to thoracic CT. We hypothesized that UTE MRI signal differences related to lung volume would be spatially related to pulmonary abnormalities as visualized using CT.

Subjects: Subjects with a clinical diagnosis of severe uncontrolled asthma provided written informed consent and were evaluated using UTE and noble gas MRI, thoracic CT, spirometry and plethysmography.

Image Acquisition: Imaging was performed on a whole body 3.0 Tesla Discovery MR750 (General Electric Health Care, Milwaukee, WI) with broadband imaging capability. UTE MRI was obtained using a 32-channel torso coil (GEHC) and 3D cones UTE sequence (GEHC). Eighteen slices were acquired in the coronal plane with the following parameters in breath-hold: 15s acquisition time, TE/TR/flip angle=0.03ms/3.5ms/5°, field-of-view=40×40cm, matrix=200×200, NEX=1, and slice-thickness=10mm. UTE MR images were acquired at four lung volumes including full expiration [FE], functional residual capacity [FRC], FRC plus one liter, and full inspiration [FI]. Hyperpolarized noble gas static ventilation images were acquired as previously described.³ Thoracic CT was performed at a lung volume of FRC+1L, as previously described.²

Image Analysis: UTE MR images were segmented using the Potts model as previously described⁴ and the signal-intensity was normalized to the mean liver signal-intensity, as previously described.² The images acquired at FE, FRC, and FI lung volumes were registered to the images acquired at a volume of FRC+1L, as previously described.⁵ The slope of the line that described the change in normalized signal-intensity over the four lung volumes was determined pixel-by-pixel to produce a multivolume slope map. Noble gas MR images were analyzed to produce the ventilation defect percent (VDP), as previously described.³ Lobar segmentation was performed using the CT images using Pulmonary Workstation 2.0 (VIDA Diagnostics Inc., Coralville, IA, USA). UTE slope values and CT radio-density was determined for each lobe.

Statistical Analysis: Univariate Spearman correlation coefficients (ρ) were generated using SPSS 23.0 software (IBM, Armonk, NY).

Figure 1 shows thoracic CT images, noble gas static ventilation images, and UTE slope maps for three representative subjects with decreasing whole lung slope. The yellow mask overlaid on the CT image identifies regions of the lung < -950HU. In the UTE slope maps, cool colours represent regions of larger signal-intensity change and hot colours represent regions of smaller signal-intensity change across the lung volumes. In six asthmatics (46±6yrs, 3M/3F), mean whole lung slope was significantly correlated with mean CT radio-density (ρ=-0.94/p=.02) and VDP (ρ=-0.88/p=.03). There was a trend towards a significant relationship between whole lung slope values with the ratio of residual volume to total lung capacity (RV/TLC) (ρ=0.83/p=.058) and the forced expiratory volume in 1s (ρ=-0.83/p=.058). As shown in Figure 2, regional lobar UTE slope measurements were significantly correlated with lobar CT radio-density measurements (ρ=-0.83/p<.001).Mean whole lung slope was related to radio-density and VDP, with a trend towards significance for RV/TLC, suggesting that changes in signal-intensity values may reflect gas-trapping and ventilation abnormalities. Taken together, these results demonstrate that UTE MRI measurements not only provide information about regional ventilation deficits, but provide similar information as CT in patients with a diagnosis of asthma. This is important, because UTE signal-intensity measurements may be used to identify regions of gas-trapping/ventilation abnormalities in severe asthma without the use of inhaled-gas contrast or ionizing radiation making this approach suitable for children where longitudinal monitoring may be required.