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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Domain Shift Analysis in Chest Radiographs Classification in a Veterans Healthcare Administration Population

This study aims to assess the impact of domain shift on chest X-ray classification accuracy and to analyze the influence of ground truth label quality and demographic factors such as age group, sex, and study year. We used a DenseNet121 model pre-trained MIMIC-CXR dataset for deep learning-based multi-label classification using ground truth labels from radiology reports extracted using the CheXpert and CheXbert Labeler. We compared the performance of the 14 chest X-ray labels on the MIMIC-CXR and Veterans Healthcare Administration chest X-ray dataset (VA-CXR). The validation of ground truth and the assessment of multi-label classification performance across various NLP extraction tools revealed that the VA-CXR dataset exhibited lower disagreement rates than the MIMIC-CXR datasets. Additionally, there were notable differences in AUC scores between models utilizing CheXpert and CheXbert. When evaluating multi-label classification performance across different datasets, minimal domain shift was observed in the unseen VA dataset, except for the label “Enlarged Cardiomediastinum.” The subgroup with the most significant variations in multi-label classification performance was study year. These findings underscore the importance of considering domain shift in chest X-ray classification tasks, paying particular attention to the temporality of the exam. Our study reveals the significant impact of domain shift and demographic factors on chest X-ray classification, emphasizing the need for improved transfer learning and robust model development. Addressing these challenges is crucial for advancing medical imaging research and improving patient care.

chest X-ray image classification↗
NASA NTRS1975

Effect of shape and size of lung and chest wall on stresses in the lung

To understand better the effect of shape and size of lung and chest wall on the distribution of stresses, strains, and surface pressures, we analyzed a theoretical model using the technique of finite elements. First we investigated the effects of changing the chest wall shape during expansion, and second we studied lungs of a variety of inherent shapes and sizes. We found that, in general, the distributions of alveolar size, mechanical stresses, and surface pressures in the lungs were dominated by the weight of the lung and that changing the shape of the lung or chest wall had relatively little effect. Only at high states of expansion where the lung was very stiff did changing the shape of the chest wall cause substantial changes. Altering the inherent shape of the lung generally had little effect but the topographical differences in stresses and surface pressures were approximately proportional to lung height. The results are generally consistent with those found in the dog by Hoppin et al (1969).

Vawter, D. L.↗
NASA NTRS2013

Estimated Probabililty of Chest Injury During an International Space Station Mission

The Integrated Medical Model (IMM) is a decision support tool that is useful to spaceflight mission planners and medical system designers when assessing risks and optimizing medical systems. The IMM project maintains a database of medical conditions that could occur during a spaceflight. The IMM project is in the process of assigning an incidence rate, the associated functional impairment, and a best and a worst case end state for each condition. The purpose of this work was to develop the IMM Chest Injury Module (CIM). The CIM calculates the incidence rate of chest injury per person-year of spaceflight on the International Space Station (ISS). The CIM was built so that the probability of chest injury during one year on ISS could be predicted. These results will be incorporated into the IMM Chest Injury Clinical Finding Form and used within the parent IMM model.

Lewandowski, Beth E.↗
DOE OSTI2021

Computer-aided Abnormality Detection in Chest Radiographs in a Clinical Setting via Domain-adaptation

Deep learning (DL) models are being deployed at medical centers to aid radiologists for diagnosis of lung conditions from chest radiographs. Such models are often trained on a large volume of publicly available labeled radiographs. These pre-trained DL models’ ability to generalize in clinical settings is poor because of the changes in data distributions between publicly available and privately held radiographs. In chest radiographs, the heterogeneity in distributions arises from the diverse conditions in X-ray equipment and their configurations used for generating the images. In the machine learning community, the challenges posed by the heterogeneity in the data generation source is known as domain shift, which is a mode shift in the generative model. In this work, we introduce a domain-shift detection and removal method to overcome this problem. Our experimental results show the proposed method’s effectiveness in deploying a pre-trained DL model for abnormality detection in chest radiographs in a clinical setting.

Dubey, Abhishek↗
NASA NTRS1997

Ventilation distribution and chest wall mechanics in microgravity

The effect of gravity on lung ventilation distribution and the mechanisms of the chest wall were investigated. The following tests were performed with the respiratory monitoring system of the Anthorack, flown onboard Spacelab D2 mission: single breath washout (SBW), multiple breath washout (MBW) and argon rebreathing (ARB). In order to study chest wall mechanisms in microgravity, a respiratory inductive plethysmograph was used. The SBW tests did not reach statistical significance, while the ARB tests showed that gravity independent inhomogeneity of specific ventilation is larger than gravity dependent inhomogeneity. In which concerns the chest wall mechanisms, the analysis on the four astronauts during the normal respirations of the relaxation maneuver showed a 40 percent increase on the abdominal contribution to respiration.

Paiva, M.↗
NASA NTRS1974

Determination of cardiac size from chest roentgenograms following Skylab missions

Decreased cardiothoracic transverse diameter ratios following Mercury, Gemini and Apollo space flights have been reported previously. To evaluate further changes in cardiac size, standard posteroanterior chest films in systole and diastole were obtained before flight and within a few hours after recovery on each of the Skylab astronauts. Postflight chest X-rays were visually compared to the preflight roentgenograms for possible changes in pulmonary vasculature, lung parenchyma, bony or soft tissue structures. From these roentgenograms the following measurements were obtained: cardiac and thoracic transverse diameters, cardiothoracic transverse diameter ratio, cardiac area from the product of both diagonal diameters, cardiac silhouette area by planimetry, thoracic cage area and cardiothoracic area ratio. The postflight frontal cardiac silhouette sizes were significantly decreased when compared with the respective preflight values (P0.05 or 0.01). The observed changes are thought to be related to postflight decrease in the intracardiac chamber volume.

Nicogossian, A. E.↗
NASA NTRS1984

Pulmonary artery location during microgravity activity: Potential impact for chest-mounted Doppler during space travel

Doppler, or ultrasonic, monitoring for pain manifestations of decompression sickness (the bends) is accomplished by placing a sensor on the chest over the pulmonary artery and listening for bubbles. Difficulties have arisen because the technician notes that the pulmonary artery seems to move with subject movement in a one-g field and because the sensor output is influenced by only slight degrees of sensor movement. This study used two subjects and mapped the position of the pulmonary artery in one-g, microgravity, and two-g environments using ultrasound. The results showed that the pulmonary artery is fixed in location in microgravity and not affected by subject position change. The optimal position corresponded to where the Doppler signal is best heard with the subject in a supine position in a one-g environment. The impact of this result is that a proposed multiple sensor array on the chest proposed for microgravity use may not be necessary to monitor an astronaut during extravehicular activities. Instead, a single sensor of approximately 1 inch diameter and mounted in the position described above may suffice.

Hadley, A. T., III↗
DOE OSTI2021

Systematic Screening of COVID-19 Disease Based on Chest CT and RT-PCR for Cancer Patients Undergoing Radiation Therapy in a Coronavirus French Hotspot

Patients with cancer are presumed to be more vulnerable to COVID-19. We evaluated a screening strategy combining chest computed tomography (CT) and reverse-transcription polymerase chain reaction (RT-PCR) for patients treated with radiation therapy at our cancer center located in a COVID-19 French hotspot during the first wave of the pandemic.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Effect of image resolution on automated classification of chest X-rays

Deep learning (DL) models have received much attention lately for their ability to achieve expert-level performance on the accurate automated analysis of chest X-rays (CXRs). Recently available public CXR datasets include high resolution images, but state-of-the-art models are trained on reduced size images due to limitations on graphics processing unit memory and training time. As computing hardware continues to advance, it has become feasible to train deep convolutional neural networks on high-resolution images without sacrificing detail by downscaling. This study examines the effect of increased resolution on CXR classification performance. We used the publicly available MIMIC-CXR-JPG dataset, comprising 377,110 high resolution CXR images for this study. We applied image downscaling from native resolution to 2048 × 2048 pixels, 1024 × 1024 pixels, 512 × 512 pixels, and 256 × 256 pixels and then we used the DenseNet121 and EfficientNet-B4 DL models to evaluate clinical task performance using these four downscaled image resolutions. We find that while some clinical findings are more reliably labeled using high resolutions, many other findings are actually labeled better using downscaled inputs. We qualitatively verify that tasks requiring a large receptive field are better suited to downscaled low resolution input images, by inspecting effective receptive fields and class activation maps of trained models. Lastly, we show that stacking an ensemble across resolutions outperforms each individual learner at all input resolutions while providing interpretable scale weights, indicating that diverse information is extracted across resolutions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

New equations of state for saturated tuff based on the CHEST model

The CHemical Equilibrium for Saturated Tuff (CHEST) model was originally presented in Ref. 1, with numerical results depicted in Figure 1 and tabulated in Appendix B of that work. The results consisted of specific internal energy as a function of pressure and specific volume, E(P, V), spanning the domain P = 10 –4 – 10 4 kbar and V = 0.17 – 752 cm 3 /g (ρ = 1.33 × 10 –3 – 5.9 g/cm 3 ).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Validating deep learning inference during chest X-ray classification for COVID-19 screening

Abstract The new coronavirus unleashed a worldwide pandemic in early 2020, and a fatality rate several times that of the flu. As the number of infections soared, and capabilities for testing lagged behind, chest X-ray (CXR) imaging became more relevant in the early diagnosis and treatment planning for patients with suspected or confirmed COVID-19 infection. In a few weeks, proposed new methods for lung screening using deep learning rapidly appeared, while quality assurance discussions lagged behind. This paper proposes a set of protocols to validate deep learning algorithms, including our ROI Hide-and-Seek protocol, which emphasizes or hides key regions of interest from CXR data. Our protocol allows assessing the classification performance for anomaly detection and its correlation to radiological signatures, an important issue overlooked in several deep learning approaches proposed so far. By running a set of systematic tests over CXR representations using public image datasets, we demonstrate the weaknesses of current techniques and offer perspectives on the advantages and limitations of automated radiography analysis when using heterogeneous data sources.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1995

Device Assists Cardiac Chest Compression

Portable device facilitates effective and prolonged cardiac resuscitation by chest compression. Developed originally for use in absence of gravitation, also useful in terrestrial environments and situations (confined spaces, water rescue, medical transport) not conducive to standard manual cardiopulmonary resuscitation (CPR) techniques.

Eichstadt, Frank T.↗
NASA NTRS1998

Chest wall mechanics in sustained microgravity

We assessed the effects of sustained weightlessness on chest wall mechanics in five astronauts who were studied before, during, and after the 10-day Spacelab D-2 mission (n = 3) and the 180-day Euromir-95 mission (n = 2). We measured flow and pressure at the mouth and rib cage and abdominal volumes during resting breathing and during a relaxation maneuver from midinspiratory capacity to functional residual capacity. Microgravity produced marked and consistent changes (Delta) in the contribution of the abdomen to tidal volume [DeltaVab/(DeltaVab + DeltaVrc), where Vab is abdominal volume and Vrc is rib cage volume], which increased from 30.7 +/- 3. 5 (SE)% at 1 G head-to-foot acceleration to 58.3 +/- 5.7% at 0 G head-to-foot acceleration (P < 0.005). Values of DeltaVab/(DeltaVab + DeltaVrc) did not change significantly during the 180 days of the Euromir mission, but in the two subjects DeltaVab/(DeltaVab + DeltaVrc) was greater on postflight day 1 than on subsequent postflight days or preflight. In the two subjects who produced satisfactory relaxation maneuvers, the slope of the Konno-Mead plot decreased in microgravity; this decrease was entirely accounted for by an increase in abdominal compliance because rib cage compliance did not change. These alterations are similar to those previously reported during short periods of weightlessness inside aircrafts flying parabolic trajectories. They are also qualitatively similar to those observed on going from upright to supine posture; however, in contrast to microgravity, such postural change reduces rib cage compliance.

manned↗