Variable flip angle 3D ultrashort echo time (UTE) T₁ mapping of mouse lung: A repeatability assessment

Background: Lung T₁ is a potential translational biomarker of lung disease. The precision and repeatability of variable flip angle (VFA) T₁ mapping using modern 3D ultrashort echo time (UTE) imaging of the whole lung needs to be established before it can be used to assess response to disease and therapy.

Purpose: To evaluate the feasibility of regional lung T₁ quantification with VFA 3D-UTE and to investigate long- and short-term T₁ repeatability in the lungs of naive mice.

Study type: Prospective preclinical animal study.

Population: Eight naive mice and phantoms.

Field strength/sequence: 3D free-breathing radial UTE (8 μs) at 4.7T.

Assessment: VFA 3D-UTE T₁ calculations were validated against T₁ values measured with inversion recovery (IR) in phantoms. Lung T₁ and proton density (S₀ ) measurements of whole lung and muscle were repeated five times over 1 month in free-breathing naive mice. Two consecutive T₁ measurements were performed during one of the imaging sessions.

Statistical tests: Agreement in T₁ between VFA 3D-UTE and IR in phantoms was assessed using Bland-Altman and Pearson 's correlation analysis. The T₁ repeatability in mice was evaluated using coefficient of variation (CV), repeated-measures analysis of variance (ANOVA), and paired t-test.

Results: Good T₁ agreement between the VFA 3D-UTE and IR methods was found in phantoms. T₁ in lung and muscle showed a 5% and 3% CV (1255 ± 63 msec and 1432 ± 42 msec, respectively, mean ± SD) with no changes in T₁ or S₀ over a month. Consecutive measurements resulted in an increase of 2% in both lung T₁ and S₀ .

Data conclusion: VFA 3D-UTE shows promise as a reliable T₁ mapping method that enables full lung coverage, high signal-to-noise ratio (∼25), and spatial resolution (300 μm) in freely breathing animals. The precision of the VFA 3D-UTE method will enable better design and powering of studies.

Level of evidence: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.