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. 2023 Jun 22:5:1148310.
doi: 10.3389/fmedt.2023.1148310. eCollection 2023.

Association of x-ray velocimetry (XV) ventilation analysis compared to spirometry

Affiliations

Association of x-ray velocimetry (XV) ventilation analysis compared to spirometry

Jason P Kirkness et al. Front Med Technol. .

Abstract

Introduction: X-ray Velocimetry (XV) ventilation analysis is a 4-dimensional imaging-based method for quantifying regional ventilation, aiding in the assessment of lung function. We examined the performance characteristics of XV ventilation analysis by examining correlation to spirometry and measurement repeatability.

Methods: XV analysis was assessed in 27 patients receiving thoracic radiotherapy for non-lung cancer malignancies. Measurements were obtained pre-treatment and at 4 and 12-months post-treatment. XV metrics such as ventilation defect percent (VDP) and regional ventilation heterogeneity (VH) were compared to spirometry at each time point, using correlation analysis. Repeatability was assessed between multiple runs of the analysis algorithm, as well as between multiple breaths in the same patient. Change in VH and VDP in a case series over 12 months was used to determine effect size and estimate sample sizes for future studies.

Results: VDP and VH were found to significantly correlate with FEV1 and FEV1/FVC (range: -0.36 to -0.57; p < 0.05). Repeatability tests demonstrated that VDP and VH had less than 2% variability within runs and less than 8% change in metrics between breaths. Three cases were used to illustrate the advantage of XV over spirometry, where XV indicated a change in lung function that was either undetectable or delayed in detection by spirometry. Case A demonstrated an improvement in XV metrics over time despite stable spirometric values. Case B demonstrated a decline in XV metrics as early as 4-months, although spirometric values did not change until 12-months. Case C demonstrated a decline in XV metrics at 12 months post-treatment while spirometric values remained normal throughout the study. Based on the effect sizes in each case, sample sizes ranging from 10 to 38 patients would provide 90% power for future studies aiming to detect similar changes.

Conclusions: The performance and safety of XV analysis make it ideal for both clinical and research applications across most lung indications. Our results support continued research and provide a basis for powering future studies using XV as an endpoint to examine lung health and determine therapeutic efficacy.

Keywords: fluoroscopy; regional lung function; ventilation defect percentage; ventilation heterogeneity; x-ray velocimetry.

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Conflict of interest statement

JK, AF, JD, NE, PP are employees of 4DMedical. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Summary of patient enrollment and sample sizes for each time point. The n values represent the final number of patients included in the data analysis for each time point. The baseline time point includes both the screening and pre-treatment visits. Each time point includes a description of the total number of patients, the number excluded from analysis due to incomplete data, and the number lost to follow-up.
Figure 2
Figure 2
XV metrics VH and VDP significantly correlated with FEV1 and FEV1/FVC. These plots represent the combined spirometry and XV metrics for each patient at baseline, 4-months, and 12-months (n = 36). The gray line represents the linear regression. Pearson correlation coefficients and p-values are reported for each plot.
Figure 3
Figure 3
Case A XV ventilation visualization showed decreased ventilation heterogeneity over time. Ventilation visualizations represent the specific ventilation (normalized to the mean) throughout the lungs. Red represents areas with lower than average ventilation, green represent average ventilation, and blue represents higher than average ventilation. (A) The pre-treatment ventilation visualization for case A showed considerable heterogeneity, with regions of defect as well as higher than average ventilation throughout the lungs. (B) By 4-months post-treatment, the areas of red and blue had decreased, signifying reduced heterogeneity. (C) By 12-months post-treatment, ventilation was more homogeneous, with increased areas of green throughout the lungs.
Figure 4
Figure 4
Frequency distributions of normalized specific ventilation illustrated changes in ventilation in each case over time. (A) Case A had a relatively wide distribution at pre-treatment (black circles) that narrowed at 4-months (gray diamonds) and further narrowed at 12-months (red squares), demonstrating decreased ventilation heterogeneity over time. (B) Case B had a similarly wide distribution at pre-treatment that showed little change at 4-months. However, by 12-months the distribution had shifted significantly, showing an increase in the frequency of over-ventilated regions. (C) Case C had a relatively tight distribution pre-treatment that shifted slightly at 4-months. By 12-months the distribution had widened, showing two peaks with one centered at higher than average specific ventilation.

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