Evaluation of Fractional Regional Ventilation Using 4D-CT and Effects of Breathing Maneuvers on Ventilation

Abstract

Current implementations of methods based on Hounsfield units to evaluate regional lung ventilation do not directly incorporate tissue-based mass changes that occur over the respiratory cycle. To overcome this, we developed a 4-dimensional computed tomography (4D-CT)-based technique to evaluate fractional regional ventilation (FRV) that uses an individualized ratio of tidal volume to end-expiratory lung volume for each voxel. We further evaluated the effect of different breathing maneuvers on regional ventilation. The results from this work will help elucidate the relationship between global and regional lung function. Eight patients underwent 3 sets of 4D-CT scans during 1 session using free-breathing, audiovisual guidance, and active breathing control. FRV was estimated using a density-based algorithm with mass correction. Internal validation between global and regional ventilation was performed by use of the imaging data collected during the use of active breathing control. The impact of breathing maneuvers on FRV was evaluated comparing the tidal volume from 3 breathing methods. Internal validation through comparison between the global and regional changes in ventilation revealed a strong linear correlation (slope of 1.01, R2 of 0.97) between the measured global lung volume and the regional lung volume calculated by use of the "mass corrected" FRV. A linear relationship was established between the tidal volume measured with the automated breathing control system and FRV based on 4D-CT imaging. Consistently larger breathing volumes were observed when coached breathing techniques were used. The technique presented improves density-based evaluation of lung ventilation and establishes a link between global and regional lung ventilation volumes. Furthermore, the results obtained are comparable with those of other techniques of functional evaluation such as spirometry and hyperpolarized-gas magnetic resonance imaging. These results were demonstrated on retrospective analysis of patient data, and further research using prospective data is under way to validate this technique against established clinical tests.