Bulletin of the American Physical Society
APS March Meeting 2023
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session Q52: Advanced Technologies for Medical PhysicsFocus
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Sponsoring Units: GMED GDS Chair: Wojciech Zbijewski, Johns Hopkins University; Alejandro Sisniega Room: Room 308 |
Wednesday, March 8, 2023 3:00PM - 3:36PM |
Q52.00001: Deep Learning Image Formation in Medical Imaging Invited Speaker: Alejandro Sisniega The rise in AI approaches to image processing in the last ten years, particularly via deep Convolutional Neural Networks (Deep-CNNs) opened a new paradigm for medical image acquisition, reconstruction, and processing, yielding the recently coined “Deep Imaging” concept. The Deep Imaging paradigm opened a new space of imaging system designs and image formation methods with potential to overcome limitations of conventional methods based on models of the system physics and conventional computational approaches alone. Example of application of Deep Imaging to medical image formation and processing, addressed numerous tasks including CT image denoising, mitigation of artifacts in sparsely sampled acquisition patterns or in incomplete sampling scenarios, compensation of image biases, and compensation of non-idealities caused by the elements of the anatomy being imaged, such as artifacts caused patient motion. |
Wednesday, March 8, 2023 3:36PM - 3:48PM |
Q52.00002: A phantom study of x-ray fluorescence measurements of iron and zinc concentrations in superficial cutaneous blood Mihai R Gherase, Vega Mahajan Monitoring essential trace elements in the human body is an important part of a clinical metabolic health assessment. Rapid, non-invasive, non-destructive, and low-dose monitoring of iron (Fe) and zinc (Zn) in the cutaneous blood was investigated by x-ray fluorescence (XRF) measurements. The method is as an alternative to clinical blood measurements using inductively coupled plasma mass spectrometry (ICP-MS). Six water solutions containing Fe in 0, 100, 200, 300, 400, and 500 mg/L and Zn in 0, 10, 20, 30, 40, and 50 mg/L concentrations were placed in polyoxymethylene cylinders (0.9 mm thick and 2.5 mm inner diameter) mimicking skin and its microvasculature. Spatially selective excitation of the elements in the solution was performed by employing a small x-ray beam (1.5-mm lateral size) from an integrated x-ray tube and polycapillary x-ray lens system. A silicon-based x-ray detector, a positioning stage, and a grazing-incidence method developed in our lab were used to acquire three 300-s x-ray spectra for each concentration. Spectral Kα peak area measurements yielded Fe and Zn calibration lines. Detection limits of (80±7) mg/L for Fe and (6.6±0.7) mg/L for Zn were computed by dividing the threefold peak area uncertainty with calibration line slope. Since blood levels are in the range of 310 to 610 mg/L for Fe and 4 to 17 mg/L for Zn, in vivo Fe and Zn measurements are feasible. Future work will assess radiation dose and the effects of varying skin x-ray attenuation on detection and concentration measurement. |
Wednesday, March 8, 2023 3:48PM - 4:00PM |
Q52.00003: Electrical Impedance Tomography (EIT) in 3D: Introducing the Sensitivity Method for Biomedical Imaging Matthew Grayson, Claire Onsager, Chulin Wang, Charles Costakis, Can C Aygen, Lauren Lang, Suzan van der Lee Electrical impedance tomography (EIT) is a noninvasive imaging method whereby electrical measurements on the periphery of a conductor are inverted to map its internal conductivity. The method proposed here, called the sensitivity method, is anticipated to outperform prior EIT methods since the model-space dimensionality is minimized for increased feature specificity and data importance is maximized through optimal reduction of data-space thereby allowing computationally efficient, noise-tolerant 3D mapping, a longstanding goal of biomedical imaging. Sensitivity vectors, defined as rows of the Jacobian matrix of the linearized EIT forward problem, are combined in sets of greatest length and maximal orthogonality and their volumetric outer-product in model-space is introduced as a previously absent figure-of-merit for optimal data-space selection. By increasing the contact number to expand the maximum data-space dimensionality, and by reducing the model-space to describe only the features of interest, optimal data-spaces can be identified according to this figure of merit. The reduction in model-space dimensionality accelerates inversion by several orders of magnitude, while the enhanced sensitivity tolerates noise levels up to 1,000 times larger than datasets generated from standard data-spaces. Phantom models of 2D and 3D conducting volumes will be simulated and experimentally demonstrated. |
Wednesday, March 8, 2023 4:00PM - 4:12PM |
Q52.00004: Model-based approaches for quantitative dual-energy cone-beam CT Stephen Z Liu, Joseph W Stayman, Wojciech Zbijewski Bone mineral density (BMD) and bone marrow edema (BME) are key biomarkers for early detection of musculoskeletal diseases (e.g., osteoarthritis), occult traumas and fracture non-unions. State-of-the-art methods for quantifying these biomarkers (e.g., biopsy, MRI, dual-energy (DE) CT) are limited by the cost, lengthy examination, radiation dose, and potential contraindications (e.g., metal implants). We present the current efforts in enabling BMD and BME quantification on a dedicated, point-of-care extremity cone-beam CT (CBCT). A unique multi-source hardware design of the system enables single-scan DE imaging (100 mg/mL BMD and is able to detect >8 mL increase in trabecular BME volume with <10% error. |
Wednesday, March 8, 2023 4:12PM - 4:24PM |
Q52.00005: Using natural language processing to extract features from clinical notes for medical physics quality assurance Connor Thropp, Laura Buchanan, Timothy Leech, Qiongge Li, Eric Klein Missing data present a problem in various data-driven models that take clinical data as input. Imputation methods are often inadequate and provide estimations for missing data. We found that physicians’ clinical notes are information rich and can be used to fill in missing features; however, they are in free text form which makes feature extraction a challenge. |
Wednesday, March 8, 2023 4:24PM - 4:36PM |
Q52.00006: Machine Learning Enabled Potential Approach for Cardiovascular Risks Prediction Anand Babu, Dipankar Mandal Cardiovascular diseases (CVDs) are one of the leading causes of death worldwide, which accounts for almost 30% of total deaths. The major deaths can be curbed via early detection of the risk factors of CVDs. Regular monitoring of the cardiovascular parameters is one of the feasible solutions; however, due to limitations of lack of information in real-time recording and instability in the constant acquisition of the cardiovascular signals in the existing technologies of monitoring, it seems not to be possible. We have introduced a highly sensitive flexible piezoelectric sensor fabricated from a simple solution processable technique. Which consists of a highly sensitive, flexible, conformable piezoelectric film of fluoride-based polymers. It is perfectly working for detecting the physiological parameters of the body such as arterial pulse, carotid pulse, and gait analysis; since it is prompt responsive in the subtle pressure range (0.001-1 kPa), which is tested for assessing risk factors of cardiovascular diseases based on arterial pulse data. The recorded data is further fed into the machine learning algorithms, which learn from the data and recognize if an anomaly is detected in the arterial pulse based on the analysis of the pattern, assisting in early predicting the disease based on its data learning. We have developed numerous machine learning algorithms for training the sensor, such as pattern recognition and random forest, which gives classification prediction accuracy of ~94% and 98%, respectively. |
Wednesday, March 8, 2023 4:36PM - 4:48PM |
Q52.00007: NMR Spectroscopic Investigation of the Effect of LDH inhibitor Sodium oxamate on Glucose metabolism in cancer cell Asiye Asaadzade, Lloyd Lumata Sodium oxamate is an inhibitor of lactate dehydrogenase (LDH) that specifically inhibit LDH-A, |
Wednesday, March 8, 2023 4:48PM - 5:00PM |
Q52.00008: The metabolism of galactose in hypoxic cancer cells Daniel L Anable, Lloyd Lumata The Le Loir pathway is a cellular metabolic pathway for the processing of galactose into glucose-1-phosphate which is then converted into glucose-6-phosphate for use in glycolysis. Traditionally, galactose is processed in the liver, kidney, and gut. However, significant metabolism of galactose has been found in breast and glioblastoma cancers. In preliminary trials, we examined the metabolism of galactose in Colo-205 and LoVo colorectal cancer cells, SFXL and U87 Glioblastoma cells, Miapaca2 pancreatic cancer cells, and HUH-7 liver cancer cells. When adding 5mM of [1-13C] Galactose to complete media, we saw only a negligible boost in the C3 lactate peak for all but HUH-7 cells. Additionally, we tested the response of the cells to a 2% O2 hypoxic environment using a 5% CO2 hypoxia incubator. Under hypoxia, the HUH-7 cells seemed to stop metabolizing galactose to lactate. These NMR results will be discussed together with other supporting data. |
Wednesday, March 8, 2023 5:00PM - 5:12PM |
Q52.00009: Sensitivity of QA testing to beam drifts in LINACs: a MC Study Alicia Martin, Thad A Harroun, Josef Dubicki Quality assurance guidelines for medical accelerators ensure patients get the dosage as established in their treatment plan. A portion of dose discrepancies seen in photon therapy are caused by changes in the initial electron beam, before they hit the target in the treatment head. We started by validating a Monte Carlo model of the Elekta Agility radiation therapy treatment head at three photon treatment energies, 6MV, 10MV and 18MV using GATE/Geant4. This model was then used to quantify the how electron beam deviations at the target manifest themselves in the resultant photon beams. Using deviated beams as the source from our validated model, standard quality assurance tests were simulated to determine if they were sensitive enough to detect and categorize these deviations. At all three treatment energies, simulated beam deviations of average beam energy, beam spot position and the incident angle were conducted and analyzed using the quality assurance setups for profile constancy, tissue phantom ratio and overall beam symmetry. The results of this research will be used to observe small beam drifts clinically and correct for errors before they become an issue that affects patient treatments and throughput. |
Wednesday, March 8, 2023 5:12PM - 5:24PM |
Q52.00010: Monte Carlo Simulations of the Effect of Magnetic field on Deposited dose in Proton Therapy Mike D Sumption, Abdelhai Benali, Lanchun Lu, Nilendu Gupta, E.W. Collings Proton therapy is well known to have a greater effectiveness for cancer cell disruption within targeted tumors as compared to X-ray and gamma rays, while minimizing entry and exit dose damage to healthy tissues. The combining of MRI with proton therapy has been proposed in order to allow for better beam guidance. However, the presence of the magnetic field associated with the MRI system both influences the beam trajectory, as well as having some effect on the deposited dose. This work focusses on the change in deposited dose with field strength applied either along the beam direction or perpendicular to it. We used Monte Carlo code PHITS (v.3.28) to calculate the absorbed dose contributed from primary and secondary particles inside a cylindrical water phantom during proton therapy, using proton pencil beam along Z-axis with energies ranging from 70±0.1 MeV to 220±0.1 MeV with a step of 10 MeV. Magnetic fields were applied either parallel to, or perpendicular to, the beam direction. Primary and secondary protons are the main contributor in the total dose with about 83% and 17%, respectively. The rest of the contribution comes mainly from heavy ions like deuterons, tritons, 3He, 4He and a small amount of neutrons, electrons and photons. For a 220MeV beam, the deposited dose at the Bragg Peak, is increased by about 0.5% per Tesla for perpendicular fields, while fields parallel experienced modified the deposited dose substantially less. These effects are discussed for various beam energies and possible mechanisms discussed. |
Wednesday, March 8, 2023 5:24PM - 5:36PM |
Q52.00011: Exploring Heavy-Ion Fusion as a Pathway for Production of Indium-111 Pete Miller Pathways for the production of indium-111 (111In) radionuclide, a radioisotope commonly used in medical imaging, via heavy-ion fusion is explored at energies around the barrier with the interaction potential taken as the sum of Coulomb and Wood-Saxon form. In particular, the following reactions have been studied: 37Cl + 74Ge, 26Al + 85Kr, 21Ne + 90Y along with other pathways not listed here. Fusion cross-sections and barrier distributions are calculated via the one-dimensional penetration model and the channel coupling model implemented via NRV code. The aims of the study are to suggest new reaction combinations for the production of 111In radionuclide, compare different models, and explore the impact of deformation parameters on the heavy-ion fusion cross-sections and barrier distribution. |
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