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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
NASA NTRS1993

Automated System for Early Breast Cancer Detection in Mammograms

The increasing demand on mammographic screening for early breast cancer detection, and the subtlety of early breast cancer signs on mammograms, suggest an automated image processing system that can serve as a diagnostic aid in radiology clinics. We present a fully automated algorithm for detecting clusters of microcalcifications that are the most common signs of early, potentially curable breast cancer. By using the contour map of the mammogram, the algorithm circumvents some of the difficulties encountered with standard image processing methods. The clinical implementation of an automated instrument based on this algorithm is also discussed.

Bankman, Isaac N.↗
NASA NTRS2003

A Virtual Bioinformatics Knowledge Environment for Early Cancer Detection

Discovery of disease biomarkers for cancer is a leading focus of early detection. The National Cancer Institute created a network of collaborating institutions focused on the discovery and validation of cancer biomarkers called the Early Detection Research Network (EDRN). Informatics plays a key role in enabling a virtual knowledge environment that provides scientists real time access to distributed data sets located at research institutions across the nation. The distributed and heterogeneous nature of the collaboration makes data sharing across institutions very difficult. EDRN has developed a comprehensive informatics effort focused on developing a national infrastructure enabling seamless access, sharing and discovery of science data resources across all EDRN sites. This paper will discuss the EDRN knowledge system architecture, its objectives and its accomplishments.

knowledge systems↗
NASA NTRS2000

Breast Cancer Detection

The BioScan System was developed by OmniCorder Technologies, Inc. at the Jet Propulsion Laboratory. The system is able to locate cancerous lesions by detecting the cancer's ability to recruit a new blood supply. A digital sensor detects infrared energy emitted from the body and identifies the minute differences accompanying the blood flow changes associated with cancerous cells. It also has potential use as a monitoring device during cancer treatment. This technology will reduce the time taken to detect cancerous cells and allow for earlier intervention, therefore increasing the overall survival rates of breast cancer patients.

Source record↗
NASA NTRS2003

A National Virtual Specimen Database for Early Cancer Detection

Access to biospecimens is essential for enabling cancer biomarker discovery. The National Cancer Institute's (NCI) Early Detection Research Network (EDRN) comprises and integrates a large number of laboratories into a network in order to establish a collaborative scientific environment to discover and validate disease markers. The diversity of both the institutions and the collaborative focus has created the need for establishing cross-disciplinary teams focused on integrating expertise in biomedical research, computational and biostatistics, and computer science. Given the collaborative design of the network, the EDRN needed an informatics infrastructure. The Fred Hutchinson Cancer Research Center, the National Cancer Institute,and NASA's Jet Propulsion Laboratory (JPL) teamed up to build an informatics infrastructure creating a collaborative, science-driven research environment despite the geographic and morphology differences of the information systems that existed within the diverse network. EDRN investigators identified the need to share biospecimen data captured across the country managed in disparate databases. As a result, the informatics team initiated an effort to create a virtual tissue database whereby scientists could search and locate details about specimens located at collaborating laboratories. Each database, however, was locally implemented and integrated into collection processes and methods unique to each institution. This meant that efforts to integrate databases needed to be done in a manner that did not require redesign or re-implementation of existing system

distributed↗
DOE OSTI2022

Fully Integrated Ultra-thin Intraoperative Micro-imager for Cancer Detection Using Upconverting Nanoparticles

Abstract Purpose Intraoperative detection and removal of microscopic residual disease (MRD) remain critical to the outcome of cancer surgeries. Today’s minimally invasive surgical procedures require miniaturization and surgical integration of highly sensitive imagers to seamlessly integrate into the modern clinical workflow. However, current intraoperative imagers remain cumbersome and still heavily dependent on large lenses and rigid filters, precluding further miniaturization and integration into surgical tools. Procedures We have successfully engineered a chip-scale intraoperative micro-imager array—without optical filters or lenses—integrated with lanthanide-based alloyed upconverting nanoparticles (aUCNPs) to achieve tissue imaging using a single micro-chip. This imaging platform is able to leverage the unique optical properties of aUCNPs (long luminescent lifetime, high-efficiency upconversion, no photobleaching) by utilizing a time-resolved imaging method to acquire images using a 36-by-80-pixel, 2.3 mm $$\times$$ × 4.8 mm silicon-based electronic imager micro-chip, that is, less than 100-µm thin. Each pixel incorporates a novel architecture enabling automated background measurement and cancellation. We have validated the performance, spatial resolution, and the background cancellation scheme of the imaging platform, using resolution test targets and mouse prostate tumor sample intratumorally injected with aUCNPs. To demonstrate the ability to image MRD, or tumor margins, we evaluated the imaging platform in visualizing a single-cell thin section of the injected prostate tumor sample. Results Tested on USAF resolution targets, the imager is able to achieve a resolution of 71 µm. We have also demonstrated successful background cancellation, achieving a signal-to-background ratio of 8 when performing ex vivo imaging on aUCNP-injected prostate tumor sample, improved from originally 0.4. The performance of the imaging platform on single-cell layer sections was also evaluated and the sensor achieved a signal-to-background ratio of 4.3 in resolving cell clusters with sizes as low as 200 cells. Conclusion The imaging system proposed here is a scalable chip-scale ultra-thin alternative for bulky conventional intraoperative imagers. Its novel pixel architecture and background correction scheme enable visualization of microscopic-scale residual disease while remaining completely free of lenses and filters, achieving an ultra-miniaturized form factor—critical for intraoperative settings.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1998

Cancer Detection Device

Ratcom, Inc., has joined NASA Johnson Space Center in an active program to develop cytometry capabilities for space station freedom. This agreement results from a cooperative program that NASA entered into with the American Cancer Society to aid in cancer prevention, diagnosis, and treatment. The flow cytometer is used by cancer researchers to make cellular measurements.

Source record↗
NASA NTRS2001

Cancer Detection Using Neural Computing Methodology

This paper describes a novel learning methodology used to analyze bio-materials. The premise of this research is to help pathologists quickly identify anomalous cells in a cost efficient method. Skilled pathologists must methodically, efficiently and carefully analyze manually histopathologic materials for the presence, amount and degree of malignancy and/or other disease states. The prolonged attention required to accomplish this task induces fatigue that may result in a higher rate of diagnostic errors. In addition, automated image analysis systems to date lack a sufficiently intelligent means of identifying even the most general regions of interest in tissue based studies and this shortfall greatly limits their utility. An intelligent data understanding system that could quickly and accurately identify diseased tissues and/or could choose regions of interest would be expected to increase the accuracy of diagnosis and usher in truly automated tissue based image analysis.

liquid crystal tunable filters↗
NASA NTRS1977

Liquid-cooled bra for cancer detection

Garment cools entire breast area uniformly, improving sensitivity of thermographic techniques. Flow and temperature of coolant are controlled by system which also monitors skin temperature.

Williams, B. A.↗
NASA NTRS1977

Feasibility study on the design of a probe for rectal cancer detection

Rectal examination techniques are considered in terms of detection capability, patient acceptance, and cost reduction. A review of existing clinical techniques are considered in terms of detection capability, patient acceptance, and cost reduction. A review of existing clinical techniques and of relevant aerospace technology included evaluation of the applicability of visual, thermal, ultrasound, and radioisotope modalities of examination. The desired improvements can be obtained by redesigning the proctosigmoidoscope to have reduced size, additional visibility, and the capability of readily providing a color photograph of the entire rectosigmoid mucosa in a single composite view.

Anselm, V. J.↗
NASA NTRS1979

Improved probe for rectal-cancer detection

Modified protosigmoidoscope, with third partially mirrored lens, provides lateral as well as forward vision for thorough examination of patients for malignant or premalignant lesions of colon and rectum.

Frazer, R. E.↗
NASA NTRS1976

Breast Cancer Detection

NASA's Jet Propulsion Laboratory has come up with a technique to decrease exposure to harmful x-rays in mammographies or breast radiography. Usually, physicians make more than one exposure to arrive at an x-ray film of acceptable density. Now the same solar cells used to convert sunlight into electricity on space satellites can make a single exposure sufficient. When solar cell sensor is positioned directly beneath x-ray film, it can determine exactly when film has received sufficient radiation and has been exposed to optimum density. At that point associated electronic equipment sends signal to cut off x-ray source. Reduction of mammography to single exposures not only reduced x-ray hazard significantly, but doubled the number of patient examinations handled by one machine. The NASA laboratory used this control system at the Huntington Memorial Hospital with overwhelming success.

Source record↗
NASA NTRS1981

Dual-mode microwave system to enhance early detection of cancer

A dual-mode microwave system has been developed that will permit early detection of cancer. The system combines the use of the passive microwave radiometer with an active transmitter. The active transmitter will provide localized heating to enhance early detection by taking advantage of the differential heating (i.e., tumor temperature with respect to surrounding tissue) associated with the thermal characteristics of tumors.

Carr, K. L.↗
DOE OSTI2023

Use of Longitudinal Serum Analysis and Machine Learning to Develop a Classifier for Cancer Early Detection

Early detection of solid tumors through a simple screening process, such as the proteomic analysis of biofluids, has the potential to significantly alter the management and outcomes of cancers. The application of advanced targeted proteomics measurements and data analysis strategies to uniformly collected serum or plasma samples would enable longitudinal studies of cancer risk, progression, and response to therapy that have the potential to significantly reduce cancer burden in general. In this article, we describe a generalizable workflow combining robust, multiplexed targeted proteomics measurements applied to longitudinal samples from the Department of Defense Serum Repository with a Random Forest machine learning method for developing and initially evaluating the performance of candidate biomarker panels for early detection of cancers. The effectiveness of this approach was demonstrated in a cohort of 175 head and neck squamous cell carcinoma patients. The outlined protocols include methods for sample preparation, instrument analysis, and data analysis and interpretation using this workflow.

Longitudinal analysis, machine learning, cancer, e↗
DOE OSTI2024

Mortality of older construction and craft workers employed at Department of Energy (DOE) nuclear sites: Follow‐up through 2021

Background To determine if construction and trades workers formerly employed at US Department of Energy (DOE) nuclear weapons sites are at significant risk for occupational diseases, we studied the mortality experience of participants in the Building Trades National Medical Screening Program (BTMed). Methods The cohort included 26,922 participants enrolled between 1998 and 2021 and 8367 deaths. Standardized mortality ratios were calculated based on US death rates. Cox models compared construction workers (n = 22,747; 7487 deaths) to two nonconstruction subpopulations: administrative, scientific and security workers (n = 1894; 330 deaths), and all other nonconstruction workers (n = 2218; 550 deaths). Results Mortality was elevated for all causes, all cancers, cancers of the trachea, bronchus, lung, kidneys, and lymphatic and hematopoietic system, mesothelioma, chronic obstructive pulmonary disease (COPD), asbestosis, transportation injuries, and other injuries, particularly accidental poisonings. There were 167 deaths from coronavirus disease 2019 (COVID-19), which was lower than expected using US death rates. Overall cause-specific mortality was significantly higher among construction workers than for internal comparison groups. Conclusions Construction workers employed at DOE sites have a significantly increased risk for occupational illnesses. Apart from COVID-19 deaths, this update: (1) found that mortality among construction workers is significantly elevated compared to the US population and significantly higher than in the internal comparison populations, and (2) confirmed excess risk for these workers for first employment after 1990. Cancer mortality risks are similar to the cancers identified for DOE compensation from radiation exposures. In conclusion, the high lung cancer risk supports the value of early lung cancer detection. Continued medical surveillance is important.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2023

Evaluation of two extraction chromatography resins for scandium and titanium separation for medical isotope production

Scandium-47 ( 47 Sc) can be used in nuclear medicine as a therapeutic-diagnostic, or "theragnostic," radioactive medical isotope for cancer detection and treatment. The 47 Sc isotope can be produced through the photonuclear reaction 48 Ti(γ,p) 47 Sc by irradiating enriched 48 Ti target material. The enriched target material necessary for production is costly; 48 TiO 2 costs ~ $\$$1550/g, and targets can be > 50 g ($\$$77,500) to produce medically relevant amounts of 47 Sc. In order to keep costs low, a highly efficient separation of scandium from bulk titanium is desired, along with efficient methods for recycling the target material. Here this research is focused on evaluating efficient methods for the separation of scandium from bulk quantities of titanium using commercially available diglycolamide-based and hydroxamate-based extraction chromatography resins (DGA resin and ZR resin, respectively). The sorption of 47 Sc and Ti on these resins were investigated at varying concentrations of HNO 3 , HCl, H 2 SO 4 , and HF to explore how they might be used in a large-scale production/processing setting.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

MedNAS: Multiscale Training-Free Neural Architecture Search for Medical Image Analysis

Deep neural networks have demonstrated impressive results in medical image analysis, but designing suitable architectures for each specific task is expertise dependent and time consuming. Neural architecture search (NAS) offers an effective means of discovering architectures. It has been highly successful in numerous applications, particularly in natural image classification. Yet, medical images possess unique characteristics, such as small regions and a wide variety of lesion sizes, that differentiate them from natural images. Furthermore, most current NAS methods struggle with high computational costs, especially when dealing with high-resolution image datasets. In this article, we present a novel evolutionary NAS method called multiscale training-free neural architecture search (MSTF-NAS) to address these challenges. Specifically, to accommodate the broad range of lesion region sizes in disease diagnosis, we develop a new reduction cell search space that enables the search algorithm to explicitly identify the optimal scale combination for multiscale feature extraction. Further, to overcome the issue of high computational costs, we utilize training-free indicators as performance measures for candidate architectures, which allows us to search for the optimal architecture more efficiently. More specifically, by considering the capability and simplicity of various networks, we formulate a multiobjective optimization problem that involves two training-free indicators and model complexity for candidate architectures. Extensive experiments on a large medical image benchmark and a publicly available breast cancer detection dataset are conducted. The empirical results demonstrate that our MSTF-NAS outperforms both human-designed architectures and current state-of-the-art NAS algorithms on both datasets, indicating the effectiveness of our proposed method.

60 APPLIED LIFE SCIENCES↗