Rui Carlos Sá

This article describes a method for the in vivo quantification and tracking of nitrogen through the mammalian body whilst exposed to hyperbaric pressure. The method has the potential to further our understanding of decompression sickness, and quantitatively evaluate the effectiveness of both the treatment and prevention of decompression sickness.

Ventilation-perfusion matching occurs passively and is also actively regulated through hypoxic pulmonary vasoconstriction (HPV). The extent of HPV activity in humans, particularly normal subjects, is uncertain. Current evaluation of HPV assesses changes in ventilation-perfusion relationships/pulmonary vascular resistance with hypoxia and is invasive, or unsuitable for patients because of safety concerns. We used a noninvasive imaging-based approach to quantify the pulmonary vascular response to oxygen as a metric of HPV by measuring perfusion changes between breathing 21% and 30%O-2 using arterial spin labeling (ASL) MRI. We hypothesized that the differences between 21% and 30%O-2 images reflecting HPV release would be 1) significantly greater than the differences without F-IO2 changes (e.g., 21-21% and 30-30%O-2) and 2) negatively associated with ventilation-perfusion mismatch. Perfusion was quantified in the right lung in normoxia (baseline), after 15 min of 30% O-2 breathing (hyperoxia) and 15 min normoxic recovery (recovery) in healthy subjects (7 M, 7 F; age = 41.4 +/- 19.6 yr). Normalized, smoothed, and registered pairs of perfusion images were subtracted and the mean square difference (MSD) was calculated. Separately, regional alveolar ventilation and perfusion were quantified from specific ventilation, proton density, and ASL imaging; the spatial variance of ventilation-perfusion (sigma(2)Va/Q) distributions was calculated. The O-2-responsive MSD was reproducible (R-2 = 0.94, P < 0.0001) and greater (0.16 +/- 0.06, P < 0.0001) than that from subtracted images collected under the same F-IO2 (baseline = 0.09 +/- 0.04, hyperoxia = 0.08 +/- 0.04, recovery = 0.08 +/- 0.03), which were not different from one another (P = 0.2). The O-2-responsive MSD was correlated with sigma(2)Va/Q (R-2 = 0.47, P = 0.007). These data suggest that active HPV optimizes ventilation-perfusion matching in normal subjects. This noninvasive approach could be applied to patients with different disease phenotypes to assess HPV and ventilation-perfusion mismatch.

Since the first identification of the SARS-CoV-2 coronavirus (and its associated infectious disease, COVID-19) in late 2019, there have been reports of differences in disease health outcomes by race, ethnicity, sex, and other demographics.^{1 – 14} Additionally, the relative difference in impact of COVID-19 to demographic subgroups has also changed over time.^15,16 Furthermore, differences in the utilization of medical imaging in healthcare have been observed in various demographic subgroups over the course of the pandemic.^{17 – 19} As a result, the use of medical imaging among different demographic subpopulations can be expected to change over time.

Artificial intelligence and machine learning (AI/ML) in medical imaging provide important methods for leveraging large amounts of data to build models to detect disease and provide diagnosis, prognosis, and risk assessment tools to support decision-making in medicine. The development and deployment of AI/ML models in a wide variety of fields have grown substantially in the past decade, broadening considerations for more careful evaluation of the algorithms. Researchers and developers note that there are persistent challenges in generalizability and bias along the model development and deployment pipeline, including the characteristics of data used in training models and testing them. These issues have been noted and studied in fields, such as economics and sociology¹ as well as the natural sciences.² Efforts to understand and address bias in the broader AI/ML literature involve expanding fairness metrics and definitions to include additional factors³ and the development of mitigation strategies. These concerns are especially important in healthcare and medicine broadly⁴ and have been an area of study in medical imaging by several groups and initiatives, including studies which demonstrate the potential for bias in medical imaging of COVID-19.⁵ Recently, a three-part series^{6 – 8} published in Radiology: Artificial Intelligence presented methods and insights for mitigating bias in AI/ML for medical imaging through considerations for data handling,⁶ model development,⁷ and performance metrics.⁸

Global fluctuation dispersion (FDglobal), a spatial-temporal metric derived from serial images of the pulmonary perfusion obtained with MRI-arterial spin labeling, describes temporal fluctuations in the spatial distribution of perfusion. In healthy subjects, FDglobal is increased by hyperoxia, hypoxia, and inhaled nitric oxide. We evaluated patients with pulmonary arterial hypertension (PAH, 4F, aged 47 ± 15, mean pulmonary artery pressure 48 ± 7 mmHg) and healthy controls (CON, 7F, aged 47 ± 12) to test the hypothesis that FDglobal is increased in PAH. Images were acquired at ∼4–5 s intervals during voluntary respiratory gating, inspected for quality, registered using a deformable registration algorithm, and normalized. Spatial relative dispersion (RD = SD/mean) and the percent of the lung image with no measurable perfusion signal (%NMP) were also assessed. FDglobal was significantly increased in PAH (PAH = 0.40 ± 0.17, CON = 0.17 ± 0.02, P = 0.006, a 135% increase) with no overlap in values between the two groups, consistent with altered vascular regulation. Both spatial RD and %NMP were also markedly greater in PAH vs. CON (PAH RD = 1.46 ± 0.24, CON = 0.90 ± 0.10, P = 0.0004; PAH NMP = 13.4 ± 6.1%; CON = 2.3 ± 1.4%, P = 0.001 respectively) consistent with vascular remodeling resulting in poorly perfused regions of lung and increased spatial heterogeneity. The difference in FDglobal between normal subjects and patients with PAH in this small cohort suggests that spatial-temporal imaging of perfusion may be useful in the evaluation of patients with PAH. Since this MR imaging technique uses no injected contrast agents and has no ionizing radiation it may be suitable for use in diverse patient populations. NEW & NOTEWORTHY Using proton MRI-arterial spin labeling to obtain serial images of pulmonary perfusion, we show that global fluctuation dispersion (FDglobal), a metric of temporal fluctuations in the spatial distribution of perfusion, was significantly increased in female patients with pulmonary arterial hypertension (PAH) compared with healthy controls. This potentially indicates pulmonary vascular dysregulation. Dynamic measures using proton MRI may provide new tools for evaluating individuals at risk of PAH or for monitoring therapy in patients with PAH.

Dynamic imaging providing maps of specific ventilation with a temporal resolution of ∼7 min with a spatial resolution of ∼1 cm³ using MRI was shown to be practical. The technique provides an ionizing radiation-free means of temporally following the spatial pattern of specific ventilation. Reanalysis of previously published data showed that the effects of inhaled methacholine and albuterol were largely complete at ∼22 min and ∼9 min, respectively after administration.

Objective: Inhalation of e-cigarettes aerosols (vaping) has the potential to disrupt pulmonary gas exchange, but the effects in asymptomatic users are unknown. We assessed ventilation-perfusion (V̇_A/Q̇) mismatch in asymptomatic e-cigarette users, using magnetic resonance imaging (MRI). We hypothesized that vaping induces V̇_A/Q̇ mismatch through alterations in both ventilation and perfusion distributions. Methods: Nine young, asymptomatic Vapers with a >1yr vaping history, and no history of cardiopulmonary disease, were imaged supine using proton MRI, to assess the right lung at baseline and immediately after vaping. Seven young Controls were imaged at baseline only. Relative dispersion (SD/Mean) was used to quantify the heterogeneity of the individual ventilation and perfusion distributions. V̇_A/Q̇ mismatch was quantified using the second moments of the ventilation and perfusion vs. V̇_A/Q̇ ratio distributions, log scale, LogSDV̇ and LogSDQ̇ respectively, analogous to the multiple inert gas elimination technique. Results: Spirometry was normal in both groups. Ventilation heterogeneity was similar between groups at baseline (Vapers: 0.43±0.13, Controls: 0.51±0.11, P=0.13) but increased after vaping (to 0.57±0.17, P=0.03). Perfusion heterogeneity was greater (P=0.04) in Vapers at baseline (0.53±0.06) compared to Controls (0.44±0.10) but decreased after vaping (to 0.42±0.07, P=0.005). Vapers had greater (P=0.01) V̇_A/Q̇ mismatchat baseline compared to Controls (LogSDQ̇ = 0.61±0.12 vs. 0.43±0.12), which was increased after vaping (LogSDQ̇ = 0.73±0.16, P=0.03). Conclusion: V̇_A/Q̇ mismatch is greater in Vapers and worsens after vaping. This suggests subclinical alterations in lung function not detected by spirometry.

Key points: The distribution of pulmonary perfusion is affected by gravity, vascular branching structure and active regulatory mechanisms, which may be disrupted by cardiopulmonary disease, but this is not well studied, particularly in rare conditions. We evaluated pulmonary perfusion in patients who had undergone Fontan procedure, patients with pulmonary arterial hypertension (PAH) and two groups of controls using a proton magnetic resonance imaging technique, arterial spin labelling to measure perfusion. Heterogeneity was assessed by the relative dispersion (SD/mean) and gravitational gradients. Gravitational gradients were similar between all groups, but heterogeneity was significantly increased in both patient groups compared to controls and persisted after removing contributions from large blood vessels and gravitational gradients. Patients with Fontan physiology and patients with PAH have increased pulmonary perfusion heterogeneity that is not explainable by differences in mean perfusion, gravitational gradients, or large vessel anatomy. This probably reflects vascular remodelling in PAH and possibly in Fontan physiology. Many factors affect the distribution of pulmonary perfusion, which may be disrupted by cardiopulmonary disease, but this is not well studied, particularly in rare conditions. An example is following the Fontan procedure, where pulmonary perfusion is passive, and heterogeneity may be increased because of the underlying pathophysiology leading to Fontan palliation, remodelling, or increased gravitational gradients from low flow. Another is pulmonary arterial hypertension (PAH), where gravitational gradients may be reduced secondary to high pressures, but remodelling may increase perfusion heterogeneity. We evaluated regional pulmonary perfusion in Fontan patients (n = 5), healthy young controls (Fontan control, n = 5), patients with PAH (n = 6) and healthy older controls (PAH control) using proton magnetic resonance imaging. Regional perfusion was measured using arterial spin labelling. Heterogeneity was assessed by the relative dispersion (SD/mean) and gravitational gradients. Mean perfusion was similar (Fontan = 2.50 ± 1.02 ml min⁻¹ ml⁻¹; Fontan control = 3.09 ± 0.58, PAH = 3.63 ± 1.95; PAH control = 3.98 ± 0.91, P = 0.26), and the slopes of gravitational gradients were not different (Fontan = −0.23 ± 0.09 ml min⁻¹ ml⁻¹ cm⁻¹; Fontan control = −0.29 ± 0.23, PAH = −0.27 ± 0.09, PAH control = −0.25 ± 0.18, P = 0.91) between groups. Perfusion relative dispersion was greater in both Fontan and PAH than controls (Fontan = 1.46 ± 0.18; Fontan control = 0.99 ± 0.21, P = 0.005; PAH = 1.22 ± 0.27, PAH control = 0.91 ± 0.12, P = 0.02) but similar between patient groups (P = 0.13). These findings persisted after removing contributions from large blood vessels and gravitational gradients (all P < 0.05). We conclude that patients with Fontan physiology and PAH have increased pulmonary perfusion heterogeneity that is not explained by differences in mean perfusion, gravitational gradients, or large vessel anatomy. This probably reflects the effects of remodelling in PAH and possibly in Fontan physiology.

Intermittent hyperoxia is used in proton magnetic resonance imaging to evaluate ventilation as part of measuring ventilation‐perfusion mismatch, but it may alter the underlying ventilation–perfusion ...