Imaging of regional ventilation: Is CT ventilation imaging the answer? A systematic review of the validation data

Abstract

Computed Tomography Ventilation Imaging (CTVI) is an experimental imaging modality that derives regional lung function information from non-contrast respiratory-correlated CT datasets. Despite CTVI being extensively studied in cross-modality imaging comparisons, there is a lack of consensus on the state of its clinical validation in humans. This systematic review evaluates the CTVI clinical validation studies to date, highlights their common strengths and weaknesses and makes recommendations. We performed a PUBMED and EMBASE search of all English language papers on CTVI between 2000 and 2018. The results of these searches were filtered in accordance to a set of eligibility criteria and analysed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Guidelines. One hundred and forty-four records were identified, and 66 full text records were reviewed. After detailed assessment, twenty-three full text papers met the selection criteria and were included in the final review. This included thirteen prospective studies, with 579 human subjects. Studies used diverse methodologies, with a large amount of heterogeneity between different studies in terms of the reference ventilation imaging modality (e.g. nuclear medicine, hyperpolarised gas MRI), imaging parameters, DIR algorithm(s) used, and ventilation metric(s) applied. The most common ventilation metrics used deformable image registration to evaluate the exhale-to-inhale motion field Jacobian determinant (DIR-Jac) or changes in air volume content based on Hounsfield Units (DIR-HU). The strength of correlation between CTVI and the reference ventilation imaging modalities was moderate to strong when evaluated at the lobar or global level, with the average ± S.D. (number of studies) linear regression correlation coefficients were 0.73 ± 0.25 (n = 6) and 0.86 ± 0.11 (n = 12) for DIR-Jac and DIR-HU respectively, and the SPC were 0.45 ± 0.31 (n = 6) and 0.41 ± 0.11 (n = 5) for DIR-Jac and DIR-HU respectively. We concluded that it is difficult to make a broad statement about the validity of CTVI due to the diverse methods used in the validation literature. Typically, CTVI appears to show reasonable cross-modality correlations at the lobar/whole lung level but poor correlations at the voxel level. Since CTVI is seeing new implementations in prospective trials, it is clear that refinement and standardization of the clinical validation methodologies are required. CTVI appears to be of relevance in radiotherapy planning, particularly in patients whose main pulmonary impairment is not a gas exchange problem but alternative imaging approaches may need to be considered in patients with other pulmonary diseases (i.e. restrictive or gas exchange problems).

Keywords: Computed tomography; Lung cancer; Pneumonitis; Radiotherapy; Ventilation.