Comparison of ventilation defects quantified by Technegas SPECT and hyperpolarized 129Xe MRI

Introduction: The ideal contrast agents for ventilation SPECT and MRI are Technegas and 129Xe gas, respectively. Despite increasing interest in the clinical utility of ventilation imaging, these modalities have not been directly compared. Therefore, our objective was to compare the ventilation defect percent (VDP) assessed by Technegas SPECT and hyperpolarized 129Xe MRI in patients scheduled to undergo lung cancer resection with and without pre-existing obstructive lung disease. Methods: Forty-one adults scheduled to undergo lung cancer resection performed same-day Technegas SPECT, hyperpolarized 129Xe MRI, spirometry, and diffusing capacity of the lung for carbon monoxide (DLCO). Ventilation abnormalities were quantified as the VDP using two different methods: adaptive thresholding (VDPT) and k-means clustering (VDPK). Correlation and agreement between VDP quantified by Technegas SPECT and 129Xe MRI were determined by Spearman correlation and Bland-Altman analysis, respectively. Results: VDP measured by Technegas SPECT and 129Xe MRI were correlated (VDPT: r = 0.48, p = 0.001; VDPK: r = 0.63, p < 0.0001). A 2.0% and 1.6% bias towards higher Technegas SPECT VDP was measured using the adaptive threshold method (VDPT: 23.0% ± 14.0% vs. 21.0% ± 5.2%, p = 0.81) and k-means method (VDPK: 9.4% ± 9.4% vs. 7.8% ± 10.0%, p = 0.02), respectively. For both modalities, higher VDP was correlated with lower FEV1/FVC (SPECT VDPT: r = −0.38, p = 0.01; MRI VDPK: r = −0.46, p = 0.002) and DLCO (SPECT VDPT: r = −0.61, p < 0.0001; MRI VDPK: r = −0.68, p < 0.0001). Subgroup analysis revealed that VDP measured by both modalities was significantly higher for participants with COPD (n = 13) than those with asthma (n = 6; SPECT VDPT: p = 0.007, MRI VDPK: p = 0.006) and those with no history of obstructive lung disease (n = 21; SPECT VDPT: p = 0.0003, MRI VDPK: p = 0.0003). Discussion: The burden of ventilation defects quantified by Technegas SPECT and 129Xe MRI VDP was correlated and greater in participants with COPD when compared to those without. Our observations indicate that, despite substantial differences between the imaging modalities, quantitative assessment of ventilation defects by Technegas SPECT and 129Xe MRI is comparable.


Introduction
Pulmonary ventilation imaging modalities have been developed to provide a regional evaluation of airflow obstruction at highresolution and thus ultimately improve the clinical management of a variety of lung diseases. Nuclear medicine (Jögi et al., 2011;Bajc et al., 2017;Farrow et al., 2017), magnetic resonance imaging (MRI) (Kruger et al., 2016;Ohno et al., 2022;Sharma et al., 2022) and computed tomography (CT) (Park et al., 2010;Kim et al., 2012) based methods have all demonstrated abnormal and heterogeneous ventilation in patients with obstructive lung diseases, including chronic obstructive pulmonary disease (COPD) and asthma. While the potential added value of ventilation imaging modalities over conventional global measures of lung function made by breathing tests is recognized, few are widely available or used in the routine management of obstructive lung disease.
The most clinically established and widely used ventilation imaging modality is single photon emission computed tomography (SPECT) using a range of ventilation agents including krypton-81 m gas ( 81m Kr) and 99m Tc-labelled aerosols (e.g., diethylene-triamine-pentaacetate [DTPA] and Technegas) (Roach et al., 2013;Bajc et al., 2019). Beyond its primary use in conjunction with perfusion SPECT for the diagnosis of pulmonary embolism, ventilation SPECT is rarely utilized for other indications such as pre-operative quantification of lung function (Genseke et al., 2018) and functional lung avoidance in radiation therapy planning (Munawar et al., 2010;Yuan et al., 2011). Alternatively, inhaled hyperpolarized gas MRI, using either helium-3 ( 3 He) or xenon-129 ( 129 Xe), has undergone extensive research and development for obstructive lung disease applications (Kirby et al., 2012;Svenningsen et al., 2013;Ebner et al., 2017;Shammi et al., 2022;Stewart et al., 2022). Compared to SPECT, hyperpolarized gas MRI offers higher spatial and temporal resolution without exposure to ionizing radiation. However, its availability is currently limited to specialized academic centers. Previous cross-modality investigations have demonstrated the comparability of 81m Kr SPECT with 3 He MRI in 23 patients with COPD and 9 healthy volunteers (Stavngaard et al., 2005), and 99m Tc-DTPA SPECT with 129 Xe MRI in 11 patients with COPD (Doganay et al., 2019;Kim et al., 2019). While these preliminary investigations report good comparability, they were limited by the small number of patients and disease populations evaluated. Most importantly, the current ideal contrast agents for ventilation SPECT and MRI are generally accepted to be Technegas (Bajc et al., 2019) and 129 Xe gas (Niedbalski et al., 2021), respectively, and they have not been directly compared to each other.
With broadening interest in the clinical utility of ventilation imaging, and recent approval of 129 Xe MRI and impending approval of Technegas SPECT by the U.S. Food and Drug Administration, a direct quantitative comparison of the modalities is needed. Therefore, the primary objective of this study was to compare the ventilation defect percent (VDP) assessed by Technegas SPECT and 129 Xe MRI obtained the same day in a convenient sample of patients scheduled to undergo lung cancer resection with and without pre-existing obstructive lung disease. The secondary objective was to evaluate and compare the relationship of VDP assessed by both modalities with clinical history and standard lung function measures of obstructive lung diseases. To address these objectives, ventilation defects observed by Technegas SPECT and 129 Xe MRI were quantified as the whole-lung VDP using two previously published segmentation methods: adaptive thresholding (VDP T ), previously optimized for Technegas SPECT (Farrow et al., 2012); and, k-means clustering (VDP K ), previously optimized for 129 Xe MRI (Kirby et al., 2012).

Participants and study design
This was a prospectively planned sub-study of patients scheduled to undergo first-time lung cancer resection at the division of Thoracic Surgery, McMaster University, Hamilton, Ontario as part of their clinical care who were enrolled into a single-center, prospective, 5week observational study designed to evaluate the prevalence and clinical relevance of abnormal ventilation in lung cancer patients prior to lung resection. Eligible patients were greater than 18 years of age, first-time lung resection candidates in accordance with the British Thoracic Society guidelines (Callister et al., 2015), and they could not have had previous lung resection, previous chest radiation, or MRI contraindications. All participants provided written informed consent to an ethics-board approved (Hamilton Integrated Research Ethics Board #7770) and registered (ClinicalTrials.gov #NCT04191174) protocol. We report data acquired at a single pre-operative study visit, at which time baseline demographic data and clinical history were collected, and participants performed standard-of-care pulmonary function testing (spirometry and diffusing capacity of the lung for carbon monoxide (DL CO )), Technegas SPECT-CT and 129 Xe MRI. Image session order was randomized.

Technegas SPECT-CT acquisition
Technegas (Cyclomedica Australia, Sydney) was prepared with a Technegas Generator (Cyclomedica Australia, Sydney) according to the manufacturer recommendations and a 40 MBq dose was administered to the participant in the supine position via inhalation. The participant was coached to inhale Technegas, starting at functional residual capacity, until 40 μSv/h was measured by a hand-held Geiger counter positioned over the Frontiers in Physiology frontiersin.org 02 chest. Technegas SPECT was then acquired while supine, during 15min of tidal breathing using an Optima ™ Nuclear Medicine (NM)/ Computed Tomography (CT) 640 hybrid imaging system (GE Healthcare, Milwaukee, United States) and in accordance with The Canadian Association of Nuclear Medicine guidelines using the following acquisition parameters: LEHR collimator, energy window: 140 keV ± 20%, zoom factor of 1.0, 128 × 128 matrix and 4.42 mm isotropic voxels, step and shoot, 25 s/image, 60 images per acquisition (30 images per camera head), 360°rotation, 6°steps, body contour. A low dose non-contrast chest CT was subsequently acquired on the same NM/CT system during free breathing for attenuation correction and to allow for delineation of the thoracic cavity volume using the following acquisition and reconstruction parameters: 120 kVp, 20 mA, 1 s tube rotation time, 1.25 pitch, 512 × 512 matrix, 2.5 mm slice thickness, 2.5 mm slice spacing, standard reconstruction kernel, and 50 cm display field of view. Technegas SPECT reconstruction was performed using a Hermes Workstation (Hermes Medical Solutions, Stockholm, Sweden) with the following settings: OSEM reconstruction (2 iterations, 10 subsets), 3D Gaussian filter with 1.20 cm FWHM with corrections for attenuation, scatter, and collimator resolution recovery.

VDP quantification
Ventilation defects observed by Technegas SPECT and 129 Xe MRI were quantified as the whole-lung VDP using two different segmentation methods: adaptive thresholding (VDP T ) and k-means clustering (VDP K ), which have been optimized and validated for Technegas SPECT (Farrow et al., 2012) and 129 Xe MRI (Kirby et al., 2012), respectively. For the adaptive thresholding method (Farrow et al., 2012), voxels within the thoracic cavity were defined as "ventilation defect" if they were below a threshold determined as 0.5 x Mean 5-80 , where Mean 5-80 is the mean intensity of all voxels in the thoracic cavity that fall between the 5th and 80th percentile of voxel intensities. The k-means method (Kirby et al., 2012) used an iterative algorithm to bin the voxel intensities into five clusters, with the lowest signal cluster being considered "ventilation defect." For both segmentation methods, the whole-lung VDP was calculated as the volume of ventilation defects normalized to the thoracic cavity volume.

SPECT segmentation
The thoracic cavity was delineated by registering the CT to the Technegas SPECT and then segmenting the CT using semiautomated segmentation and registration software implemented on a HERMES workstation. Technegas SPECT ventilation segmentation using the threshold method was implemented on a HERMES workstation and the k-means method was implemented using the Image Processing Toolbox provided by MATLAB R2022b (The MathWorks Inc., Natick, MA, United States).

MRI segmentation
The thoracic cavity was delineated by registering the 1 H MRI to the 129 Xe MRI and then segmenting the 1 H MRI using a previously described semi-automated pipeline implemented in MATLAB (Kirby et al., 2012). 129 Xe MRI ventilation segmentation using the threshold method was implemented in MATLAB and the k-means method was performed using the previously described MATLAB pipeline (Kirby et al., 2012).

Statistical analysis
Data were tested for normality using the Shapiro-Wilk normality test and, when data were not normal, non-parametric tests were performed. Differences in demographic and clinical characteristics between participants with no history of lung disease, asthma, and COPD were determined using a one-way ANOVA with Tukey's multiple comparisons test for parametric data or Kruskal Wallis with Dunn's multiple comparisons test for non-parametric data. The correlation and agreement between VDP measured by Technegas SPECT and 129 Xe MRI were evaluated by Spearman (ρ) correlation coefficients and Bland-Altman analysis, respectively. The relationship of VDP measured by Technegas SPECT and 129 Xe MRI with age, packyear smoking history, spirometry, and DL CO were evaluated by Pearson (r) or Spearman (ρ) correlation coefficients. Statistical analyses were performed using GraphPad Prism 8.0 (GraphPad Software, San Diego, CA, United States) and all results were considered significant when the probability of making a Type I error was less than 5% (p < 0.05).

Results
Forty-four patients scheduled for resection of lung cancer were enrolled, and 41 who completed same-day Technegas SPECT and Frontiers in Physiology frontiersin.org 03 129 Xe MRI were included in our analysis. Three of the enrolled participants were excluded from our analysis because 129 Xe MRI was not performed; two participants had an MRI contraindication (brain aneurism clip), and one was unable to accommodate MRI scheduling. Of the 41 participants evaluated, 21 (51%) had no concomitant history of lung disease, while 6 (15%) had a history of asthma, 13 (32%) had COPD, and 1 (2%) had interstitial lung disease (ILD). Participant demographics, clinical characteristics, and primary tumor characteristics are summarized in Table 1. Participants with no history of lung disease, asthma, and COPD were well-balanced with respect to age (p = 0.41) and BMI (p = 0.08). Participants with COPD had a higher pack-year smoking history and lower DL CO % pred than participants with asthma (p = 0.01 and p = 0.0004) and those with no history of lung disease (p = 0.02 and p < 0.0001). FEV 1 % pred and FEV 1 / FVC were also lower for participants with COPD than those with no history of lung disease (p = 0.005 and p = 0.002).
Technegas SPECT and 129 Xe MRI were well-tolerated by all participants, with no occurrence of adverse events. The scanning sessions were performed 90 ± 30 min apart [minimum of 12 min, maximum of 120 min]. Dosing and measurements of image quality are provided in the online supplement (Supplementary Table S1). Figure 1 shows coronal Technegas SPECT, 129 Xe MRI, and corresponding structural 1 H MRI slices for four representative participants. For participant A, a never-smoker with no history of lung disease, both modalities revealed relatively normal ventilation. For participant B, an ex-smoker with no history of lung disease, both modalities revealed peripheral ventilation defects despite normal lung function assessed by spirometry. For participants C and D, past smokers with COPD, large and spatially concordant ventilation defects were observed by both modalities. While most ventilation defects, such as those highlighted by yellow arrows, were spatially concordant across  (80) 16 (76)  4 (66) 12 (92) -- Values are mean ± standard deviation or median [minimum-maximum] except when indicated otherwise. BMI = body mass index; COPD = chronic obstructive pulmonary disease; FEV 1 = forced expiratory volume in one second; FVC = forced vital capacity; DL CO = diffusion capacity for carbon monoxide; NSCLC = non-small cell lung cancer; SCLC = small cell lung cancer; % pred = percent of predicted value. # As per TNM-staging 8 th edition. *Significance of difference between groups was determined using a one-way ANOVA, with Tukey's multiple comparisons test (parametric data) or Kruskal Wallis with Dunn's multiple comparisons test (non-parametric data). Multiple comparisons revealed † COPD, different from asthma and none, ‡ COPD, different from none. Bold values denote statistical significance at the p < 0.05 level.
Frontiers in Physiology frontiersin.org 04 Frontiers in Physiology frontiersin.org 05 modalities, focal discordances were also observed, such as those highlighted by blue arrows for participants B and D.

FIGURE 2
Comparison of the ventilation defect percent (adaptive thresholding (VDP T ) and k-means clustering (VDP K )) quantified by Technegas SPECT and 129 Xe MRI. (A) Positive relationship between Technegas SPECT and 129 Xe MRI VDP T quantified using the adaptive threshold method (r = 0.48, r 2 = 0.49, p = 0.001, y = 1.86x-16.11). (B) Bland-Altman plot of the difference between Technegas SPECT and 129 Xe MRI VDP T quantified using the adaptive threshold method. Bias = −2.0% (95% limits of agreement, −23.4% to 19.4%). (C) Positive relationship between Technegas SPECT and 129 Xe MRI VDP K quantified using the k-means clustering method (r = 0.63, r 2 = 0.80, p < 0.0001, y = 0.84x+2.83). (D) Bland-Altman plot of the difference between Technegas SPECT and 129 Xe MRI VDP K quantified using the k-means clustering method. Bias = −1.6% (95% limits of agreement, −10.4% to 7.2%). For correlation plots, the dashed line represents the line of identity (y = x) and the dotted lines represent the 95% confidence intervals of the linear regression line. For Bland-Altman plots, the solid line represents the mean of the paired differences, and the dotted lines represent the 95% limits of agreement. Colored data points represent history of lung disease (no history, n = 21; asthma, n = 6; COPD, n = 13; ILD: n = 1). *Thresholding (VDP T ) and k-means clustering (VDP K ) methods previously optimized and validated for Technegas SPECT and 129 Xe MRI, respectively.
Frontiers in Physiology frontiersin.org 10.0%, p < 0.0001). Figure 2 summarizes the correlation and agreement of VDP T and VDP K measured by Technegas SPECT and 129 Xe MRI. For both quantification methods, VDP measured by Technegas SPECT and 129 Xe MRI were correlated (Figure 2A: VDP T , r = 0.48, p = 0.001; Figure 2C: VDP K , r = 0.63, p < 0.0001). Using the threshold method, Bland-Altman analysis ( Figure 2B) indicated a 2.0% bias (95% limit of agreement: −23.4% to 19.4%) for higher VDP T measured by Technegas SPECT (Technegas SPECT VDP T = 23.0 ± 14.0% vs. 129 Xe MRI VDP T = 21.0 ± 5.2%, p = 0.81). Using the k-means method, Bland-Altman analysis ( Figure 2D) indicated a similar 1.6% bias (95% limit of agreement: −10.4% to 7.2%) for higher VDP K measured by Technegas SPECT (Technegas SPECT VDP K = 9.4 ± 9.4% vs. 129 Xe MRI VDP K = 7.8 ± 10.0%, p = 0.02). Univariate relationships of Technegas SPECT VDP and 129 Xe MRI VDP with age, pack-year smoking history, spirometry and DL CO are summarized in Table 2. Using the threshold method, Technegas SPECT VDP T and 129 Xe MRI VDP T were negatively correlated with DL CO % pred (r = −0.61, p < 0.0001; and r = −0.37, p = 0.02) and FEV 1 /FVC (r = −0.38, p = 0.01; and r = −0.43, p = 0.005). 129 Xe MRI VDP T , but not Technegas SPECT VDP T , was correlated with FEV 1 % pred (r = −0.55, p = 0.0002). Using the k-means method, Technegas SPECT VDP K and 129 Xe MRI VDP K were negatively correlated with DL CO % pred (r = −0.52, p = 0.0005; and r = −0.68, p < 0.0001). 129 Xe MRI VDP K , but not Technegas SPECT VDP K , was correlated with pack-year smoking history (r = 0.56, p = 0.0002), FEV 1 % pred (r = −0.35, p = 0.03) and FEV 1 /FVC (r = −0.46, p = 0.002). For both modalities, VDP T and VDP K were not different for participants classified by tumor stage or tumor size (Supplementary  Table S2). Additionally, for both modalities, VDP T and VDP K of the ipsilateral lung (lung with tumor) was not different than the VDP T and VDP K of the contralateral lung (lung without tumor) (Supplementary Figure S1). Figure 3 summarizes VDP for 21 (51%) participants with no concomitant obstructive lung disease, 6 (15%) with a history of asthma, and 13 (32%) with COPD. The one (2%) participant with interstitial lung disease was excluded from this cross-sectional comparison. Using the threshold method ( Figures 3A, B), Technegas SPECT VDP T and 129 Xe MRI VDP T were significantly higher for participants with COPD than with those with no history of lung disease (p = 0.0003 and p = 0.0004). Technegas SPECT VDP T , but not 129 Xe MRI VDP T, was significantly higher for participants with COPD than with those with asthma (p = 0.007 and p = 0.45). There was no difference in Technegas SPECT VDP T or 129 Xe MRI VDP T between participants with asthma and those with no history of lung disease (p > 0.99 and p = 0.15). Using the k-means method ( Figures 3C, D), Technegas SPECT VDP K and 129 Xe MRI VDP K were significantly higher for participants with COPD than with those with asthma (p = 0.04 and p = 0.006) and no history of lung disease (p = 0.002 and p = 0.0003). There was no difference in Technegas SPECT VDP K or 129 Xe MRI VDP K between participants with asthma and those with no history of lung disease (p > 0.99 and p > 0.99).

Discussion
We prospectively compared ventilation defects assessed by same-day Technegas SPECT and 129 Xe MRI in 41 patients scheduled to undergo first-time lung cancer resection, a subset of whom had concomitant asthma or COPD. We report that ventilation defects quantified by Technegas SPECT and 129 Xe MRI VDP (determined using both adaptive thresholding and k-means clustering segmentation methods) were 1) correlated with one another, 2) similarly correlated with standard measures of airflow limitation (FEV 1 /FVC) and diffusing capacity (DL CO % pred ), and 3) significantly higher for participants with COPD than those with asthma and no history of obstructive lung disease.
Many segmentation methods have been developed and optimized to quantify ventilation defects as the VDP, including linear binning, thresholding, and k-means clustering. In this study, VDP was determined for both Technegas SPECT and 129 Xe MRI using adaptive thresholding and k-means segmentation methods. The basis for this decision was that the adaptive thresholding quantification method has been previously optimized and Relationships were evaluated with Pearson correlation coefficients for parametric data and Spearman's correlation coefficients for non-parametric data. VDP = ventilation defect percent; VDP T = VDP, determined by thresholding method; VDP K = VDP, determined by k-means method; FEV 1 = forced expiratory volume in one second; FVC = forced vital capacity; DL CO = diffusion capacity for carbon monoxide. *Thresholding (VDP T ) and k-means clustering (VDP K ) methods previously optimized and validated for Technegas SPECT, and 129 Xe MRI, respectively. Bold values denote statistical significance at the p <0.05 level.
Frontiers in Physiology frontiersin.org 07 validated for Technegas SPECT by Farrow et al., (2012), and the k-means method for 129 Xe MRI by Kirby et al., (2012). Using both segmentation approaches, we observed that the burden of ventilation defects quantified by Technegas SPECT and 129 Xe MRI VDP acquired on the same day were correlated. While this is the first comparison of ventilation defects assessed by Technegas SPECT and 129 Xe MRI, our observations are consistent with previous investigations demonstrating the comparability of ventilation assessed by SPECT and MRI when utilizing alternative ventilation agents. Stavngaard and colleagues previously reported a good correlation between 81m Kr SPECT and 3 He MRI for both visual and quantitative assessments of ventilation defect scores in a cohort of 23 COPD and 9 healthy participants (Stavngaard et al., 2005). In a smaller study of 11 COPD patients, Doganay et al. demonstrated a good correlation between 99m Tc-DTPA SPECT and 129 Xe MRI relative lobar percentage ventilation (Doganay et al., 2019). For ventilation SPECT, international guidelines now recommend Technegas as the preferred ventilation agent in patients with obstructive lung disease (Roach et al., 2013;Bajc et al., 2019) limiting the clinical relevance of previous comparisons that used 81m Kr and 99m Tc-DTPA. Additionally, for hyperpolarized gas ventilation MRI, 129 Xe gas is now preferred over 3 He gas due to its greater availability, lower cost, and higher solubility that permits dissolved-phase imaging (Niedbalski et al., 2021).
Frontiers in Physiology frontiersin.org 08 In most participants, visual assessment showed spatial agreement between focal ventilation defects observed by both modalities. However, as highlighted in Figure 1 by the blue arrows, some discordance was also observed. We also report a mean bias, 2.0% and 1.6%, towards higher VDP measured by Technegas SPECT than 129 Xe MRI, which was observed using the adaptive threshold and k-means method, respectively. This inter-modality bias and lack of absolute agreement in ventilation defects were not unexpected and may be explained by several factors. First, fundamental differences in the physical properties of the ventilation agents may contribute to differences in lung distribution. Technegas is an ultrafine aerosolized particle (0.005-0.2 μm (Lemb et al., 1993)) whose distribution in the lungs, unlike that of 129 Xe gas, is impacted by aerosol deposition mechanics. While Technegas behaves in a gas-like manner, permitting peripheral penetration and alveolar deposition (Bajc et al., 2019), it has been previously shown to aggregate at sites of severe obstruction leading to "hot-spots" (De Nijs et al., 2021). Shown in Figure 1D, we observed this effect in a 65-year-old male with severe COPD (FEV 1 = 28% pred , FEV 1 / FVC = 31%). Bilateral hotspots are observed on Technegas SPECT in the left and right main bronchi. Greater ventilation is observed distal to the right main bronchi hotspot by 129 Xe MRI than Technegas SPECT. Second, the different acquisition conditions and spatial resolutions between modalities must be considered. Technegas SPECT is acquired during 15 min of tidal breathing, while 129 Xe MRI is acquired during a 10 s breath hold at functional residual capacity plus 1 L. As a result, respiratory and cardiac motion have greater influence on ventilation assessed by SPECT, contributing to blurring and fewer counts at the lung borders. Additionally, lung inflation during imaging affects ventilation defects, with increased ventilation defects observed at lower levels of lung inflation (Hughes et al., 2019). As SPECT is on average acquired at a lower lung inflation (average over tidal volume) than 129 Xe MRI (functional residual capacity plus 1 L), higher VDP is expected. Taken together, the aforementioned factors likely account for the higher VDP quantified by Technegas SPECT and the spatial discordances in focal ventilation defects that were observed upon visual inspection.
It is important to emphasize that this study did not intend to determine the optimal quantification approach for each modality, rather to determine if there was correlation and some equivalency between the two modalities using established quantification practices for each modality that are implemented in the literature. There are reasons why each modality may best be served by different segmentation methods, which is beyond the scope of this article. However, we do note that for both modalities, the adaptive threshold method resulted in significantly higher VDPs compared to the k-means clustering method, irrespective of history of obstructive lung disease. In the subgroup of patients with no history of lung disease, the majority of whom had well-ventilated lungs by visual inspection, the VDPs determined using the k-means method were much closer to zero than the threshold method (Technegas SPECT: VDP K = 6.0% vs. VDP T = 17.4%; 129 Xe MRI: VDP K = 3.7% vs. VDP T = 18.5%), which better reflects what the images show (e.g., Figure 1A). We also noticed that when the VDP was determined using the threshold method (but not the k-means method), the bias towards higher Technegas SPECT VDP T increased with VDP T , or greater airflow limitation ( Figure 2C). This bias seems to be driven largely by a subset of patients with COPD in whom the Technegas SPECT VDP T was considerably higher than the 129 Xe MRI VDP T . Taken together, investigation of these cases reveals that the adaptive threshold classifies hypoventilated (or low ventilated) voxels as defect, leading to a significantly higher VDP T , which can be misleading when interpreted in absolute terms. This effect, in combination with severe obstruction leading to "hot-spots," likely explains the exceptionally high Technegas SPECT VDP T reported for two patients with COPD (62% and 84%).
Ventilation defect burden quantified by Technegas SPECT VDP T and 129 Xe MRI VDP K (VDPs determined using modalityspecific approach) were similarly correlated to standard measures of airflow limitation (FEV 1 /FVC) and diffusing capacity (DL CO ). For both modalities, the correlation with DL CO was stronger than with FEV 1 /FVC. One explanation for this may be that DL CO is a direct measurement of the capacity of communicating lung volume to transfer gas from inhaled air to the bloodstream, whereas FEV 1 /FVC is an indirect composite marker of the presence of airway obstruction with forced exhalation. Interestingly, 129 Xe MRI VDP K but not SPECT VDP T , was correlated with pack-year smoking history and FEV 1 . The reason for this discrepancy is unclear. Consistent with these relationships, we also observed greater ventilation defect burden quantified by both modalities in participants with COPD compared to those with asthma and no history of obstructive disease. However, VDP assessed by both modalities was not higher in patients who reported a history of asthma compared to those without any known history of obstructive disease. This result may be considered unexpected as abnormal ventilation is a characteristic feature of asthma. We do note that the VDPs in our cohort of asthmatics are similar to what has been previously reported by others, using 129 Xe MRI VDP K (Eddy et al., 2022) and Technegas SPECT VDP T (Farrow et al., 2012;Farrow et al., 2017), respectively. When interpreting this result, it should be considered that most of our cohort of patients without any known history of obstructive lung disease were current smokers (4 of 21, 19%) or past smokers (10 of 21, 48%), 36% of whom had an FEV 1 / FVC less than 0.70 and 7% had a DL CO less than 80% pred . As demonstrated by participant B in Figure 1, such patients may have subclinical or undiagnosed airways disease contributing to ventilation defects and increased VDP.
There are limitations to our study that should be considered. First, we evaluated a convenient sample of patients scheduled for lung cancer resection, in whom tumor burden may have influenced segmentation of the thoracic cavity and VDP quantification. However, in our cohort, tumor size was not associated with whole-lung VDP, and ipsilateral and contralateral VDP were not different (data provided online, Supplementary Figure S1; Table S2). These observations indicate that tumor burden did not significantly contribute to VDP assessed by either modality, which is not surprising given the small tumor sizes in our cohort (≤3 cm in 46%, >3 to ≤5 cm in 27%, >5 to ≤7 cm in 10%, and >7 cm in 7% of participants). Second, we did not quantitatively evaluate the spatial agreement of ventilation defects observed by Technegas SPECT and 129 Xe MRI. Such analysis is highly dependent on accurate registration and anatomical alignment of Technegas SPECT and 129 Xe MRI datasets, which was challenging due to differences in voxel size, acquisition conditions (tidal breathing vs. breath hold) and lung volume. Finally, our quantitative analysis distilled regional and voxel-wise measurements of ventilation down to a single whole-lung value, in this case the VDP. VDP is a binary whole-lung measurement Frontiers in Physiology frontiersin.org 09 that fails to characterize much of the information offered by ventilation imaging modalities. Furthermore, as our analysis demonstrates, different segmentation schemes yield different VDPs in the same individual.
In summary, using the current ideal contrast agents for ventilation SPECT and MRI, we imaged patients with and without obstructive lung disease prior to lung cancer resection to quantify and compare ventilation defects observed by both modalities. We report that the burden of ventilation defects quantified by Technegas SPECT and 129 Xe MRI are correlated and increased in participants with COPD. Our observations indicate that, despite substantial differences between the imaging modalities, assessment of ventilation defects using established quantification practices for Technegas SPECT and 129 Xe MRI are comparable, provided the same quantification approach is used. Future work is required to determine if superior and comparable improvements in patient outcomes are achieved by integrating ventilation assessment with Technegas SPECT and 129 Xe MRI into the clinical management of lung diseases and potential improvement in outcomes post-resection. For now, based on our findings, the selection of ventilation imaging modality can be guided by local availability and regulatory approval, contraindications, and concern of radiation burden.

Data availability statement
Data sharing requests will be considered from researchers that submit a proposal and an appropriate statistical analysis and dissemination plan. Data would be shared via a secure data access system by request to the corresponding author.

Ethics statement
The studies involving human participants were reviewed and approved by Hamilton Integrated Research Ethics Board. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

Author contributions
SS, YS, and PN were responsible for study conception and study design. YS, EP, CF, JA, and PN were responsible for identifying and characterizing the patients, and for clinical interpretation of the data. NR, MJ, and CH were responsible for recruiting study participants. CM, TF, and MD were responsible for ventilation SPECT-CT acquisition and/or interpretation. NBK and MDN were responsible for MRI acquisition and/or interpretation. NR, YF, and SS were responsible for data acquisition, analysis, and interpretation, and for preparing the first draft of the manuscript. All authors edited and reviewed the manuscript and approved the final version of the manuscript.

Funding
This was an investigator-initiated study funded by Cyclomedica Australia Pty Ltd. and The Lung Association. The funders had no role in the design of the study, the collection and analysis of the data, or the preparation of the manuscript.