Free-breathing quantification of regional ventilation derived by phase-resolved functional lung (PREFUL) MRI

Area of Science:

• Pulmonary imaging
• Quantitative MRI
• Lung function assessment

Background:

• Accurate regional lung ventilation measurement is crucial for diagnosing and managing respiratory diseases.
• Conventional methods like fractional ventilation (FV) can be limited by image registration errors.
• Phase-resolved functional lung (PREFUL) MRI offers a potential solution for improved ventilation quantification.

Purpose of the Study:

• To assess the feasibility of regional, fully quantitative ventilation measurement using PREFUL MRI in free breathing.
• To evaluate PREFUL MRI in both supine and prone positions.
• To investigate the impact of T₂ * relaxation time on ventilation quantification.

Main Methods:

• Twelve healthy volunteers underwent 1.5 T functional MRI using a 2D triple-echo spoiled gradient echo sequence.
• Quantitative T₂ * relaxation time was measured.
• Minute ventilation (ΔV) was quantified using conventional fractional ventilation (FV) and a novel regional ventilation (VR) method.
• Comparison of ΔV_FV vs. ΔV_VR and ΔV_VR vs. ΔV_VR with T₂ * correction using Bland-Altman plots and correlation analysis.
• Repeatability and physiological plausibility were assessed in supine and prone positions.

Main Results:

• Strong correlations (r > 0.93) were found between ΔV_FV, ΔV_VR, and T₂ *-corrected ΔV_VR on global and regional scales.
• Regional Bland-Altman analysis revealed systematic differences (p < 0.0001).
• ΔV_VR and ΔV_FV demonstrated expected physiological anterior-posterior ventilation gradients, which differed between supine and prone positions.
• Moderate repeatability (CV < 20%) was observed for all quantification methods.
• T₂ * correction introduced challenges in quantification.

Conclusions:

• Fully quantified regional ventilation measurement using ΔV_VR in free breathing is feasible and yields physiologically plausible results.
• The ΔV_VR approach effectively eliminates volume errors caused by image registration, outperforming conventional ΔV_FV.
• Accurate correction for T₂ * effects in ventilation quantification remains a significant challenge.