Assessment of Six-Minute Walk Test Among Discharge-Ready Severe COVID-19 Patients: A Cross-Sectional Study

Background

Among patients hospitalized for severe pneumonia due to coronavirus disease (COVID-19), clinical stability and normal resting peripheral oxygen saturation (SpO₂) levels are widely used as a discharge criterion after recovery. It is unknown whether a test to assess the functional exercise capacity, like a six-minute walk test (6MWT), can add to the appropriateness of discharge criteria.

Methods

A cross-sectional study was conducted at a tertiary care COVID-19 hospital in India from 01^st to 31^st May 2021. All patients considered fit for discharge after recovery from "severe" COVID-19 pneumonia were subjected to 6MWT. Fitness for discharge was assessed by clinical stability and resting SpO₂ above 93% for three consecutive days. Patients were considered to have failed the 6MWT if there was ≥4% fall in SpO₂ or if they could not complete the test. Serum samples were analyzed for levels of C-reactive protein (CRP), interleukin-6 (IL-6), and lactate dehydrogenase (LDH) at the time of discharge.

Results

Fifty-three discharge-ready patients with a mean age of 54.54 ± 14.35 years with a male preponderance (60.38%) were analyzed. Thirty-three (62.26%) patients failed the 6MWT with a median six-minute walk distance (6MWD) of 270 m (60-360). A total of 45 (84.91%) patients had a fall in SpO₂ during the test. The median change in SpO₂ (∆SpO₂) was 5% ranging from -6% to 8%. Serum LDH was significantly higher among patients who failed the 6MWT with a median LDH of 334 IU/L (38.96-2339) versus 261 IU/L (49.2-494) (p = 0.02). The difference was not significant for CRP or IL-6. There was no statistically significant correlation between the inflammatory markers with either 6MWD or (∆SpO₂).

Conclusion

Two-thirds of the patients considered fit for discharge after recovery from severe COVID-19 pneumonia failed 6MWT, implying reduced functional exercise capacity and exertional hypoxia. Serum LDH levels were higher in these patients but not in other inflammatory markers. None of the inflammatory markers at discharge correlated with 6MWD or ∆SpO₂ of 6MWT.

Virtual bronchoscopy-guided lung SAbR: dosimetric implications of using AAA versus Acuros XB to calculate dose in airways

In previous works, we showed that incorporating individual airways as organs-at-risk (OARs) in the treatment of lung stereotactic ablative radiotherapy (SAbR) patients potentially mitigates post-SAbR radiation injury. However, the performance of common clinical dose calculation algorithms in airways has not been thoroughly studied. Airways are of particular concern because their small size and the density differences they create have the potential to hinder dose calculation accuracy. To address this gap in knowledge, here we investigate dosimetric accuracy in airways of two commonly used dose calculation algorithms, the anisotropic analytical algorithm (AAA) and Acuros-XB (AXB), recreating clinical treatment plans on a cohort of four SAbR patients. A virtual bronchoscopy software was used to delineate 856 airways on a high-resolution breath-hold CT (BHCT) image acquired for each patient. The planning target volumes (PTVs) and standard thoracic OARs were contoured on an average CT (AVG) image over the breathing cycle. Conformal and intensity-modulated radiation therapy plans were recreated on the BHCT image and on the AVG image, for a total of four plan types per patient. Dose calculations were performed using AAA and AXB, and the differences in maximum and mean dose in each structure were calculated. The median differences in maximum dose among all airways were ≤0.3Gy in magnitude for all four plan types. With airways grouped by dose-to-structure or diameter, median dose differences were still ≤0.5Gy in magnitude, with no clear dependence on airway size. These results, along with our previous airway radiosensitivity works, suggest that dose differences between AAA and AXB correspond to an airway collapse variation ≤0.7% in magnitude. This variation in airway injury risk can be considered as not clinically relevant, and the use of either AAA or AXB is therefore appropriate when including patient airways as individual OARs so as to reduce risk of radiation-induced lung toxicity.

Validation of a CT-based motion model with in-situ fluoroscopy for lung surface deformation estimation

Many surrogate-based motion models (SMMs), proposed to guide motion management in radiotherapy, are constructed by correlating motion of an external surrogate and internal anatomy during CT-simulation. Changes in this correlation define model break down. We validate a methodology that incorporates fluoroscopic images (FL) acquired during treatment for SMM construction and update. Under a prospective IRB, 4DCT scans, VisionRT surfaces, and orthogonal FLs were collected from five lung cancer patients. VisionRT surfaces and two FL time-series were acquired pre- and post-treatment. A simulated annealing optimization scheme was used to estimate optimal lung deformations by maximizing the mutual information between digitally reconstructed radiographs (DRRs) of the SMM-estimated 3D images and FLs. Our SMM used partial-least-regression and was trained using the optimal deformations and VisionRT surfaces from the first breathing-cycle. SMM performance was evaluated using the mutual information score between reference FLs and the corresponding SMM or phase-assigned 4DCT DRRs. The Hausdorff distance for contoured landmarks was used to evaluate target position estimation error. For four out of five patients, two principal components approximated lung surface deformations with submillimeter accuracy. Analysis of the mutual information score between more than 4,000 pairs of FL and DRR demonstrated that our model led to more similarity between the FL and DRR images compared to 4DCT and DRR images from a model based on an a priori correlation model. Our SMM consistently displayed lower mean and 95^th percentile Hausdorff distances. For one patient, 95^th percentile Hausdorff distance was reduced by 11mm. Patient-averaged reductions in mean and 95^th percentile Hausdorff distances were 3.6mm and 7mm for right-lung, and 3.1mm and 4mm for left-lung targets. FL data were used to evaluate model performance and investigate the feasibility of model update. Despite variability in breathing, use of post-treatment FL preserved model fidelity and consistently outperformed 4DCT for position estimation.

Seasonal variation in photosynthetic rates and satellite-based GPP estimation over mangrove forest

In view of increasing anthropogenic influences and global changes, quantification of carbon assimilation through photosynthesis has gained tremendous significance. Precise estimation of Gross Primary Productivity (GPP) is essential for several ecosystem models and is typically done using coarser scale satellite data. The mangrove ecosystem, which offers significant protection to the coastal environment, is one of the critical habitats from a global change point of view. Light use efficiency (LUE) was measured using diurnal in situ photosynthetic rate observations for 13 dominant mangrove species for 3 seasons at each of the three mangrove dominant test-sites situated along the east and west coast of India. Variations in photosynthetic rates among these species were studied for 3 seasons that indicated varying responses of mangrove ecosystem at each site. Among all species, Rhizophora mucronata and Sonneratia apetala indicated higher values at two of the test-sites. IRS Resourcesat-2 LISS-IV datasets were used for the estimation of GPP. Mean GPP for all the sites varied from 1.2 to 7.7 g C m^-2 day^-1 with maximum value of 14.4 g C m^-2 day^-1. Mean values of GPP varied across the sites, based on its maximum LUE values and available photosynthetically active radiation (PAR). The results provide GPP values at much better spatial resolution for a threatened habitat like mangroves that typically survive in a narrow habitat along the coasts.

Regular physical activity postpones age of occurrence of first-ever stroke and improves long-term outcomes

OBJECTIVE

Few data are available on the associations between the level of pre-stroke physical activity and long-term outcomes in patients with stroke. This study is designed to assess the associations between pre-stroke physical activity and age of first-ever stroke occurrence and long-term outcomes.

METHODS

Six hundred twenty-four cases with first-ever stroke were recruited from the Mashhad Stroke Incidence Study a prospective population-based cohort in Iran. Data on Physical Activity Level (PAL) were collected retrospectively and were available in 395 cases. According to the PAL values, subjects were classified as inactive (PAL < 1.70) and active (PAL ≥ 1.70). Age at onset of stroke was compared between active and inactive groups. Using logistic model, we assessed association between pre-stroke physical activity and long-term (5-year) mortality, recurrence, disability, and functional dependency rates. We used multiple imputation to analyze missing data.

RESULTS

Inactive patients (PAL < 1.70) were more than 6 years younger at their age of first-ever-stroke occurrence (60.7 ± 15.5) than active patients (67.0 ± 13.2; p < 0.001). Patients with PAL< 1.7 also had a greater risk of mortality at 1 year [adjusted odds ratio (aOR) = 2.31; 95%CI: 1.14-4.67, p = 0.02] and 5 years after stroke (aOR = 1.81; 95%CI: 1.05-3.14, p = 0.03) than patients who were more physically active. Recurrence rate, disability, and functional dependency were not statistically different between two groups. Missing data analysis also showed a higher odds of death at one and 5 years for inactive patients.

CONCLUSIONS

In our cohort, we observed a younger age of stroke and a higher odds of 1- and 5-year mortality among those with less physical activity. This is an important health promotion strategy to encourage people to remain physically active.

Functionally weighted airway sparing (FWAS): a functional avoidance method for preserving post-treatment ventilation in lung radiotherapy

Recent changes to the guidelines for screening and early diagnosis of lung cancer have increased the interest in preserving post-radiotherapy lung function. Current investigational approaches are based on spatially mapping functional regions and generating regional avoidance plans that preferentially spare highly ventilated/perfused lung. A potentially critical, yet overlooked, aspect of functional avoidance is radiation injury to peripheral airways, which serve as gas conduits to and from functional lung regions. Dose redistribution based solely on regional function may cause irreparable damage to the 'supply chain'. To address this deficiency, we propose the functionally weighted airway sparing (FWAS) method. FWAS (i) maps the bronchial pathways to each functional sub-lobar lung volume; (ii) assigns a weighting factor to each airway based on the relative contribution of the sub-volume to overall lung function; and (iii) creates a treatment plan that aims to preserve these functional pathways. To evaluate it, we used four cases from a retrospective cohort of SAbR patients treated for lung cancer. Each patient's airways were auto-segmented from a diagnostic-quality breath-hold CT using a research virtual bronchoscopy software. A ventilation map was generated from the planning 4DCT to map regional lung function. For each terminal airway, as resolved by the segmentation software, the total ventilation within the sub-lobar volume supported by that airway was estimated and used as a function-based weighting factor. Upstream airways were weighted based on the cumulative volumetric ventilation supported by corresponding downstream airways. Using a previously developed model for airway radiosensitivity, dose constraints were determined for each airway corresponding to a <5% probability of airway collapse. Airway dose constraints, ventilation scores, and clinical dose constraints were input to a swarm optimization-based inverse planning engine to create a 3D conformal SAbR plan (CRT). The FWAS plans were compared to the patients' prescribed CRT clinical plans and the inverse-optimized clinical plans. Depending on the size and location of the tumour, the FWAS plan showed superior preservation of ventilation due to airflow preservation through open pathways (i.e. cumulative ventilation score from the sub-lobar volumes of open pathways). Improvements ranged between 3% and 23%, when comparing to the prescribed clinical plans, and between 3% and 35%, when comparing to the inverse-optimized clinical plans. The three plans satisfied clinical requirements for PTV coverage and OAR dose constraints. These initial results suggest that by sparing pathways to high-functioning lung subregions it is possible to reduce post-SAbR loss of respiratory function.

Controls to Minimize Disruption of the Pharmaceutical Supply Chain During the COVID-19 Pandemic

This article reviews currently available scientific literature related to the epidemiology, infectivity, survival, and susceptibility to disinfectants of Coronaviruses, in the context of the controls established to meet good manufacturing practice (GMP) regulations and guidance, and the public health guidance issued specifically to combat the COVID-19 pandemic. The possible impact of the COVID-19 pandemic on the pharmaceutical supply chain is assessed and recommendations are listed for risk mitigation steps to minimize supply disruption to pharmaceutical drug products. Areas addressed include a brief history of the COVID-19 viral pandemic, a description of the virus, the regulatory response to the pandemic, the screening of employees, the persistence of the virus on inanimate surfaces, cleaning and disinfection of manufacturing facilities, the use of GMP-mandated personal protective equipment to counter the spread of the disease, the role of air changes in viral clearance, and approaches to risk assessment and mitigation. Biological medicinal products have a great record of safety, yet the cell cultures used for production can be susceptible to viruses, and contamination events have occurred. Studies on SARS-CoV-2 for it ability to replicate in various mammalian cell lines used for biopharmaceutical manufacturing suggests that the virus poses a low risk and any contamination would be detected by currently used adventitious virus testing. The consequences of the potential virus exposure of manufacturing processes as well as the effectiveness of mitigation efforts are discussed. The pharmaceutical supply chain is complex, traversing many geographies and companies that range from large multinationals to mid- and small-size operations. This paper recommends practices that can be adopted by all companies, irrespective of their size, geographic location, or position in the supply chain.

Development and prospective in-patient proof-of-concept validation of a surface photogrammetry + CT-based volumetric motion model for lung radiotherapy

PURPOSE

We develop and validate a motion model that uses real-time surface photogrammetry acquired concurrently with four-dimensional computed tomography (4DCT) to estimate respiration-induced changes within the entire irradiated volume, over arbitrarily many respiratory cycles.

METHODS

A research, couch-mounted, VisionRT (VRT) system was used to acquire optical surface data (15 Hz, ROI = 15 × 20 cm² ) from the thoraco-abdominal surface of a consented lung SBRT patient, concurrently with their standard-of-care 4DCT. The end-exhalation phase from the 4DCT was regarded as reference and for each remaining phase, deformation vector fields (DVFs) with respect to the reference phase were computed. To reduce dimensionality, the first two principal components (PCs) of the matrix of nine DVFs were calculated. In parallel, ten phase-averaged VRT surfaces were created. Surface DVFs and corresponding PCs were computed. A principal least squares regression was used to relate the PCs of surface DVF to those of volume DVFs, establishing a relationship between time-varying surface and the underlying time-varying volume. Proof-of-concept validation was performed during each treatment fraction by concurrently acquiring 30 s time series of real-time surface data and "ground truth" kV fluoroscopic data (FL). A ray-tracing algorithm was used to create a digitally reconstructed fluorograph (DRF), and motion trajectories of high-contrast, soft-tissue, anatomical features in the DRF were compared with those from kV FL.

RESULTS

For five of the six fluoroscopic acquisition sessions, the model out-performed 4DCT in predicting contour Dice coefficient with respect to fluoroscopy-derived contours. Similarly, the model exhibited a marked improvement over 4DCT for patch positions on the diaphragm. Model patch position errors varied from 5 to -15 mm while 4DCT errors ranged between 5 and -22.4 mm. For one fluoroscopic acquisition, a marked change in the a priori internal-external correlation resulted in model errors comparable to those of 4DCT.

CONCLUSIONS

We described the development and a proof-of-concept validation for a volumetric motion model that uses surface photogrammetry to correlate the time-varying thoraco-abdominal surface to the time-varying internal thoraco-abdominal volume. These early results indicate that the proposed approach can result in a marked improvement over 4DCT. While limited by the duration of the fluoroscopic acquisitions as well as the resolution of the acquired images, the DRF-based proof-of-concept technique developed here is model-agnostic, and therefore, has the potential to be used as an in-patient validation tool for other volumetric motion models.

Predictive modeling of respiratory tumor motion for real-time prediction of baseline shifts

Baseline shifts in respiratory patterns can result in significant spatiotemporal changes in patient anatomy (compared to that captured during simulation), in turn, causing geometric and dosimetric errors in the administration of thoracic and abdominal radiotherapy. We propose predictive modeling of the tumor motion trajectories for predicting a baseline shift ahead of its occurrence. The key idea is to use the features of the tumor motion trajectory over a 1 min window, and predict the occurrence of a baseline shift in the 5 s that immediately follow (lookahead window). In this study, we explored a preliminary trend-based analysis with multi-class annotations as well as a more focused binary classification analysis. In both analyses, a number of different inter-fraction and intra-fraction training strategies were studied, both offline as well as online, along with data sufficiency and skew compensation for class imbalances. The performance of different training strategies were compared across multiple machine learning classification algorithms, including nearest neighbor, Naïve Bayes, linear discriminant and ensemble Adaboost. The prediction performance is evaluated using metrics such as accuracy, precision, recall and the area under the curve (AUC) for repeater operating characteristics curve. The key results of the trend-based analysis indicate that (i) intra-fraction training strategies achieve highest prediction accuracies (90.5-91.4%); (ii) the predictive modeling yields lowest accuracies (50-60%) when the training data does not include any information from the test patient; (iii) the prediction latencies are as low as a few hundred milliseconds, and thus conducive for real-time prediction. The binary classification performance is promising, indicated by high AUCs (0.96-0.98). It also confirms the utility of prior data from previous patients, and also the necessity of training the classifier on some initial data from the new patient for reasonable prediction performance. The ability to predict a baseline shift with a sufficient look-ahead window will enable clinical systems or even human users to hold the treatment beam in such situations, thereby reducing the probability of serious geometric and dosimetric errors.

Inverse 4D conformal planning for lung SBRT using particle swarm optimization

A critical aspect of highly potent regimens such as lung stereotactic body radiation therapy (SBRT) is to avoid collateral toxicity while achieving planning target volume (PTV) coverage. In this work, we describe four dimensional conformal radiotherapy using a highly parallelizable swarm intelligence-based stochastic optimization technique. Conventional lung CRT-SBRT uses a 4DCT to create an internal target volume and then, using forward-planning, generates a 3D conformal plan. In contrast, we investigate an inverse-planning strategy that uses 4DCT data to create a 4D conformal plan, which is optimized across the three spatial dimensions (3D) as well as time, as represented by the respiratory phase. The key idea is to use respiratory motion as an additional degree of freedom. We iteratively adjust fluence weights for all beam apertures across all respiratory phases considering OAR sparing, PTV coverage and delivery efficiency. To demonstrate proof-of-concept, five non-small-cell lung cancer SBRT patients were retrospectively studied. The 4D optimized plans achieved PTV coverage comparable to the corresponding clinically delivered plans while showing significantly superior OAR sparing ranging from 26% to 83% for D max heart, 10%-41% for D max esophagus, 31%-68% for D max spinal cord and 7%-32% for V 13 lung.

Association between muscle hydration measures acquired using bioelectrical impedance spectroscopy and magnetic resonance imaging in healthy and hemodialysis population

Establishing the effect of fluctuating extracellular fluid (ECF) volume on muscle strength in people with end-stage renal disease (ESRD) on hemodialysis (HD) is essential, as inadequate hydration of the skeletal muscles impacts its strength and endurance. Bioelectrical impedance spectroscopy (BIS) has been a widely used method for estimating ECF volume of a limb or calf segment. Magnetic resonance imaging (MRI)-acquired transverse relaxation times (T2) has also been used for estimating ECF volumes of individual skeletal muscles. The purpose of this study was to determine the association between T2 (gold standard) of tibialis anterior (TA), medial (MG), and lateral gastrocnemius (LG), and soleus muscles and calf BIS ECF, in healthy and in people with ESRD/HD. Calf BIS and MRI measures were collected on two occasions before and after HD session in people with ESRD/HD and on a single occasion for the healthy participants. Linear regression analysis was used to establish the association between these measures. Thirty-two healthy and 22 participants on HD were recruited. The association between T2 of TA, LG, MG, and soleus muscles and ratio of calf BIS-acquired ECF and intracellular fluids (ICF) were: TA: β = 0.30, P > 0.05; LG: β = 0.37, P = 0.035; MG: β = 0.43, P = 0.014; soleus: β = 0.60, P < 0.001. For the HD group, calf ECF was significantly associated with T2 of TA (β = 0.44, P = 0.042), and medial gastrocnemius (β = 0.47, P = 0.027) following HD only. Hence BIS-acquired measures cannot be used to measure ECF volumes of a single muscle in the ESRD/HD population; however, BIS could be utilized to estimate ratio of ECF: ICF in healthy population for the LG, MG, and soleus muscles.