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At least 1,099 records · Page 61

Status of Cycle 23 Forecasts

A number of techniques for predicting solar activity on a solar cycle time scale are identified, described, and tested with historical data. Some techniques, e.g,, regression and curve-fitting, work well as solar activity approaches maximum and provide a month- by-month description of future activity, while others, e.g., geomagnetic precursors, work well near solar minimum but provide an estimate only of the amplitude of the cycle. A synthesis of different techniques is shown to provide a more accurate and useful forecast of solar cycle activity levels. A combination of two uncorrelated geomagnetic precursor techniques provides the most accurate prediction for the amplitude of a solar activity cycle at a time well before activity minimum. This precursor method gave a smoothed sunspot number maximum of 154+21 for cycle 23. A mathematical function dependent upon the time of cycle initiation and the cycle amplitude then describes the level of solar activity for the complete cycle. As the time of cycle maximum approaches a better estimate of the cycle activity is obtained by including the fit between recent activity levels and this function. This Combined Solar Cycle Activity Forecast now gives a smoothed sunspot maximum of 140+20 for cycle 23. The success of the geomagnetic precursors in predicting future solar activity suggests that solar magnetic phenomena at latitudes above the sunspot activity belts are linked to solar activity, which occurs many years later in the lower latitudes.

Hathaway, D. H.↗

Fast-RF-Shimming: Accelerate RF shimming in 7T MRI using deep learning

Ultrahigh field (UHF) Magnetic Resonance Imaging (MRI) offers an elevated signal-to-noise ratio (SNR), enabling exceptionally high spatial resolution that benefits both clinical diagnostics and advanced research. However, the jump to higher fields introduces complications, particularly transmit radiofrequency (RF) field ($B^{+}_{1}$) inhomogeneities, manifesting as uneven flip angles and image intensity irregularities. These artifacts can degrade image quality and impede broader clinical adoption. Traditional RF shimming methods, such as Magnitude Least Squares (MLS) optimization, effectively mitigate $B^{+}_{1}$ inhomogeneity, but remain time-consuming. Recent machine learning approaches, including RF Shim Prediction by Iteratively Projected Ridge Regression and other deep learning architectures, suggest alternative pathways. Although these approaches show promise, challenges such as extensive training periods, limited network complexity, and practical data requirements persist. In this paper, we introduce a holistic learning-based framework called Fast-RF-Shimming, which achieves a 5000 ​× ​speed-up compared to the traditional MLS method. In the initial phase, we employ random-initialized Adaptive Moment Estimation (Adam) to derive the desired reference shimming weights from multi-channel $B^{+}_{1}$ fields. Next, we train a Residual Network (ResNet) to map $B^{+}_{1}$ fields directly to the ultimate RF shimming outputs, incorporating the confidence parameter into its loss function. Finally, we design Non-uniformity Field Detector (NFD), an optional post-processing step, to ensure the extreme non-uniform outcomes are identified. Comparative evaluations with standard MLS optimization underscore notable gains in both processing speed and predictive accuracy, which indicates that our technique shows a promising solution for addressing persistent inhomogeneity challenges.

Deep learning↗

Analysis of Waste Material Feedstocks Using Laser-Induced Breakdown Spectroscopy and Machine Learning

Predicting properties such as heating value, ash fusion temperature, and mineral ash composition from Laser-Induced Breakdown Spectroscopy (LIBS) data can make gasifiers more flexible to different feedstocks. Understanding these feedstock properties in-situ improves feedstock conversion modelling methods that allow for consistent operation, higher carbon conversion, and reduced fouling and erosion rates. The purpose of this study is to demonstrate methods for model creation that take LIBS data as predictor features and estimate higher order material properties as a function of feedstock material properties. Six samples were chosen to represent a mixture of abundant and carbon rich waste materials. LIBS measurements were performed on these samples for elemental wavelengths and intensity values. Laboratory analytical results were obtained for each sample’s heating value, proximate and ultimate analysis, mineral ash composition, ash fusion temperatures, and viscosity temperatures. Thermal conductivity was measured using a HotDisk TPS 2500S. LIBS measurements were processed and used as predictor features for machine learning (ML) models to predict the sample’s material properties. Predictor feature selection algorithms, particularly minimum redundancy maximum relevance (mRMR), reduced the dimensionality of ML models. Many modelling methods such as Gaussian process regression (GPR), regression tree, neural networks (NN), and support vector machines (SVM) were demonstrated to be effective at predicting higher order properties; however, mRMR with GPR stood out as a clear winning combination.

01 COAL, LIGNITE, AND PEAT↗

TH-CD-202-06: A Method for Characterizing and Validating Dynamic Lung Density Change During Quiet Respiration

Purpose: To obtain a functional relationship that calibrates the lung tissue density change under free breathing conditions through correlating Jacobian values to the Hounsfield units. Methods: Free-breathing lung computed tomography images were acquired using a fast helical CT protocol, where 25 scans were acquired per patient. Using a state-of-the-art deformable registration algorithm, a set of the deformation vector fields (DVF) was generated to provide spatial mapping from the reference image geometry to the other free-breathing scans. These DVFs were used to generate Jacobian maps, which estimate voxelwise volume change. Subsequently, the set of 25 corresponding Jacobian and voxel intensity in Hounsfield units (HU) were collected and linear regression was performed based on the mass conservation relationship to correlate the volume change to density change. Based on the resulting fitting coefficients, the tissues were classified into parenchymal (Type I), vascular (Type II), and soft tissue (Type III) types. These coefficients modeled the voxelwise density variation during quiet breathing. The accuracy of the proposed method was assessed using mean absolute difference in HU between the CT scan intensities and the model predicted values. In addition, validation experiments employing a leave-five-out method were performed to evaluate the model accuracy. Results: The computed mean model errors were 23.30±9.54 HU, 29.31±10.67 HU, and 35.56±20.56 HU, respectively, for regions I, II, and III, respectively. The cross validation experiments averaged over 100 trials had mean errors of 30.02 ± 1.67 HU over the entire lung. These mean values were comparable with the estimated CT image background noise. Conclusion: The reported validation experiment statistics confirmed the lung density modeling during free breathing. The proposed technique was general and could be applied to a wide range of problem scenarios where accurate dynamic lung density information is needed. This work was supported in part by NIH R01 CA0096679.

60 APPLIED LIFE SCIENCES↗

The Solid Rocket Motor Slag Population: Results of a Radar-Based Regressive Statistical Evaluation

Solid rocket motor (SRM) slag has been identified as a potential source of man-made orbital debris. The possibility that SRMs (in addition to generating dust particles in the sub-millimeter range) may generate particles up to centimeters in size has caused concern regarding their contribution to the debris environment. Returned surfaces from space do not have sufficient area or exposure time to provide a clear picture of the SRM millimeter and centimeter debris population. Currently, radar observation is probably the only way to collect data showing the debris contribution from SRMs. Such observation is used to sample the debris environment, but it is difficult to obtain accurate orbital elements for the detected debris objects. NASA has developed several models to describe the different orbital debris populations, based on assumed debris production mechanisms to create clouds of debris objects that can be propagated in time. The NASA model, LEGEND (LEO-to-GEO Environment Debris), functions as a time-tested debris model for most debris sources. However, the current LEGEND model does not include contributions from the SRM population. An SRM model has recently been developed by NASA, based on purely theoretical details of SRM production and known SRM launches, but verification with hard data is needed. Because the detections of individual SRM objects cannot be deterministically separated from the total debris observed by radar, the validation of the SRM model can only be done by combining it with the LEGEND breakup model and comparing it with data. By applying observational constraints, the degree of SRM slag contribution to the environment may be estimated. This serves as an observationally sound method from which to calibrate a purely theoretical model into something more realistic. For this study, we use the populations observed by the Haystack radar from 1996 to present. For the SRM debris, we use a historical database of SRM launches, propellant masses, and estimated locations and times of tailoff to produce and propagate the SRM debris clouds. Comparisons with radar data from the ensuing years were made, and the SRM model was altered with respect to size and mass production of slag particles to reflect the populations estimated from the data. The result is a model SRM population that fits within the bounds of the observed environment and estimates of the production and contribution of SRM debris to the environment.

Horstman, Matthew F.↗

Study of Low Flow Rate Ladle Bottom Gas Stirring Using Triaxial Vibration Signals

Secondary steelmaking plays a great role in enhancing the quality of the final steel product. The metal quality is a function of metal bath stirring in ladles. The metal bath is often stirred by an inert gas to achieve maximum compositional and thermal uniformity throughout the melt. Ladle operators often observe the top surface phenomena, such as level of meniscus disturbance, to evaluate the status of stirring. However, this type of monitoring has significant limitations in assessing the process accurately especially at low gas flow rate bubbling. The present study investigates stirring phenomena using ladle wall triaxial vibration at a low flow rate on a steel-made laboratory model and plant scale for the case of the vacuum tank degasser. Cold model and plant data were successfully modeled by partial least-squares regression to predict the amount of stirring. In the cold model, it was found that the combined vibration signal could predict the stirring power and recirculation speed effectively in specific frequency ranges. Plant trials also revealed that there is a high structure in each data set and in the same frequency ranges at the water model. In the case of industrial data, the degree of linear relationship was strong for data taken from a single heat.

36 MATERIALS SCIENCE↗

Kinetic Study of Methyl Acetate Oxidation in a Pt/Al2O3 Fixed-Bed Reactor

To support technology development for future long-term missions, a metabolic simulator will be used in a closed chamber to test the functions of a Controlled Ecological Life Support System (CELSS). Methyl acetate (MA) was selected as the fuel because its metabolic respiratory quotient is near that of humans. A kinetic study of the catalytic oxidation of MA over Pt/Al203 was then conducted to support the design and operation of the simulator. Kinetic data were obtained as a conversion percentage of MA versus retention time. The reaction was studied at one atmosphere and temperatures from 220 to 340 deg. C. The inlet MA concentration was varied from 100 to 2000 ppm with retention times from 0.01 to 10 sec. A first-order rate law and a Langmuir-Hinshelwood rate equation were tested by nonlinear regression of the kinetic data to estimate rate constants in the rate law. Regression results of the L-H equation explain the kinetic data better than the results of the first-order rate law. A Taguchi experimental design was used to study the effects of temperature, retention time, and concentrations of MA, CO2, and O2 on the conversion of MA. Results indicate that temperature has greatest effect, followed by retention time, and finally MA concentration. It was further determined that the effects of CO2 and O2 concentrations, and the cross effects, are negligible.

Hoy, Michael↗

Additional Characterization of Dome-C to Improve its Use as an Invariant Visible Calibration Target

Dome-C is a recommended CEOS invariant target that has been utilized by the calibration community for several decades for monitoring onboard sensor calibration systems as well radiometric inter-comparisons. Dome-C is a high-altitude Earth target located on the East Antarctic interior plateau, which has a permanent bright, flat, and homogeneous snow-covered surface with little aerosol, cloud cover, snowfall, and water vapor burden. This paper describes angular directional models for characterizing the Dome-C top-of-atmosphere (TOA)radiances as a function of cosine solar zenith angle for pre-solstice and post-solstice conditions. The 0.86-μm channel Dome-C reflectance decreases over the summer due to snow metamorphosisis not observed by the visible channels. Coinciding Terra and AquaMODIS Dome-C reflectance showed occasional inter-annual anomalies when compared against the deep convective cloud and Libya-4 invariant targets observations. Further characterization of the Dome-C reflectances with the Dome-C surface broadband albedo, Antarctic Oscillation(AAO) index, and ozone concentration values were evaluated. A strong correlation with ozone was found for the 0.55-μm and 0.65-μm MODIS channels. The monthly Dome-C reflectances were linearly regressed with ozone to derive the ozone correction coefficients. The uncertainty in the Aqua-and Terra-MODIS Dome-C trends was reduced by half after applying ozone corrections to both the 0.55-μm and 0.65-μm channelTOA observations.

David R Doelling↗

Differing behavioral changes in crayfish and bluegill under short- and long-chain PFAS exposures: Field study in Northern Michigan, USA

The emergent contaminant family, per- and poly-fluorinated alkyl substances (PFAS) has gained research attention due to their widespread detection and stability within the environment. Despite the growing amount of research on perfluorooctanesulfonic acid (PFOS) and perfluoro-n-octanoic acid (PFOA) in aquatic organisms, investigations detailing behavioral and physiological effects of aquatic organisms exposed to a mixture of PFAS analytes in the wild have been limited. The objective of this study was to evaluate the potential behavioral and histological effects of environmental exposure to PFAS compounds within multiple trophic levels of aquatic ecosystems. The current study investigates effects of environmentally relevant PFAS concentration exposures in crayfish (Faxonius immunis, F. rusticus, F. virilis) and bluegill (Lepomis macrochirus) sourced from four water bodies in Northern Michigan. Antipredator response and foraging behavioral assays were used to investigate potential effects on crayfish; a swimming speed behavioral assay and liver and gill histology analysis were used to investigate potential effects on fish. Linear mixed model and multiple regression analyses resulted in significant relationships between tissue accumulation levels of long chain PFAS compounds and crayfish foraging and fish critical swimming speed responses. Crayfish foraging decreased and fish critical swim speeds increased with PFAS exposure which may lead to energetic and population concerns. Antipredator response in crayfish and liver and gill histology in fish were not significantly related to PFAS tissue or water concentrations. The sensitivity of crayfish and bluegill behavior contributes to the growing body of research regarding the differential toxicity of short-chain and long-chain PFAS compounds. The sensitivity of some aquatic organism behaviors to PFAS accumulated in tissue may have implications for PFAS transfer and alterations to ecosystem functioning; based on the results of this field study, further laboratory research is recommended to further evaluate these relationships.

59 BASIC BIOLOGICAL SCIENCES↗

SU-C-BRA-07: Virtual Bronchoscopy-Guided IMRT Planning for Mapping and Avoiding Radiation Injury to the Airway Tree in Lung SAbR

Purpose: Post-treatment radiation injury to central and peripheral airways is a potentially important, yet under-investigated determinant of toxicity in lung stereotactic ablative radiotherapy (SAbR). We integrate virtual bronchoscopy technology into the radiotherapy planning process to spatially map and quantify the radiosensitivity of bronchial segments, and propose novel IMRT planning that limits airway dose through non-isotropic intermediate- and low-dose spillage. Methods: Pre- and ∼8.5 months post-SAbR diagnostic-quality CT scans were retrospectively collected from six NSCLC patients (50–60Gy in 3–5 fractions). From each scan, ∼5 branching levels of the bronchial tree were segmented using LungPoint, a virtual bronchoscopic navigation system. The pre-SAbR CT and the segmented bronchial tree were imported into the Eclipse treatment planning system and deformably registered to the planning CT. The five-fraction equivalent dose from the clinically-delivered plan was calculated for each segment using the Universal Survival Curve model. The pre- and post-SAbR CTs were used to evaluate radiation-induced segmental collapse. Two of six patients exhibited significant segmental collapse with associated atelectasis and fibrosis, and were re-planned using IMRT. Results: Multivariate stepwise logistic regression over six patients (81 segments) showed that D0.01cc (minimum point dose within the 0.01cc receiving highest dose) was a significant independent factor associated with collapse (odds-ratio=1.17, p=0.010). The D0.01cc threshold for collapse was 57Gy, above which, collapse rate was 45%. In the two patients exhibiting segmental collapse, 22 out of 32 segments showed D0.01cc >57Gy. IMRT re-planning reduced D0.01cc below 57Gy in 15 of the 22 segments (68%) while simultaneously achieving the original clinical plan objectives for PTV coverage and OAR-sparing. Conclusion: Our results indicate that the administration of lung SAbR can Result in significant injury to bronchial segments, potentially impairing post-SAbR lung function. To our knowledge, this is the first investigation of functional avoidance based on mapping and minimizing dose to individual bronchial segments. The presenting author receives research funding from Varian Medical Systems, Elekta, and VisionRT.

60 APPLIED LIFE SCIENCES↗

Temporal Evolution of SL-9 Impact Sites on Jupiter and Global Maps of Jupiter from Multi-Observatory Visible and Infrared Images

The objective of this research was to investigate the temporal behavior of the impact features on Jupiter created by the fragments of the Shoemaker Levy-9 comet that collided with the planet in July 1994. The primary observations used in the study were ground based images of Jupiter acquired from the Swedish Solar Vacuum Tube on the island of La Palma in the Canary Islands. The measurement of position of the impact features in images acquired immediately after the impact over a period of a few days revealed that the apparent drift rates were too high and that a repetitive pattern could be seen in the longitude position on successive rotations. This could be explained only by the fact that the measured longitudes of the impact sites were being affected by parallax due to a significant elevation of the impact debris above the nominal cloud top altitude value used for image navigation. Once the apparent positions are analyzed as a function of the meridian angle, the parallax equation can be used to infer the height of the impact features above the cloud deck, once the true impact position (longitude) for the feature is known. Due to their inherent high spatial resolution, the HST measurements of the impact site locations have been accepted widely. However, these suffer from the parallax themselves since few of them were obtained at central meridian. Ground based imaging have the potential to improve this knowledge as they do observe most of the impact sites on either side of the central meridian, except for the degraded resolution. Measurements over a large number of images enables us to minimize the position error through regression and thus estimate both the actual impact site location devoid of parallax bias, and also of the altitude level of the impact debris above the cloud deck. With rapid imaging there is the potential to examine the time evolution of the altitude level. Several hundred ground based images were processed, navigated and subjected to the impact site location measurements. HST images were also acquired and used to calibrate the results and to improve the sample. The resources available enabled an in-depth study only of impact site A, however, many more images have since become available through the global network observations through Lowell Observatory.

Limaye, Sanjay S.↗

A Survey and Synthesis of Solar Cycle Prediction Techniques

A number of techniques for predicting solar activity on a solar cycle time scale are identified, described, and tested with historical data. Some techniques, e.g. regression and curve-fitting, work well as solar activity approaches maximum and provide a complete description of future activity, while others, e.g. geomagnetic precursors, work well near solar minimum but only provide an estimate of the amplitude of the cycle. A synthesis of different techniques is shown to provide a more accurate and useful forecast of solar cycle activity levels. A combination of two uncorrelated geomagnetic precursor techniques provides the most accurate prediction for the amplitude of a solar activity cycle at a time well before activity minimum. This Combined Precursor Method gives a smoothed sunspot number maximum of 154+/-21 at the 95% level of confidence for the next cycle maximum. A mathematical function dependent upon the time of cycle initiation and the cycle amplitude then describes the level of solar activity for the next complete cycle. As the time of cycle maximum approaches a better estimate of the cycle activity is obtained by including the fit between previous activity levels and this function. This Combined Solar Cycle Activity Forecast gives, as of January 1999, a smoothed sunspot maximum of 146+/-20 at the 95% level of confidence for the next cycle maximum. The success of the geomagnetic precursors in predicting future solar activity suggests that solar magnetic phenomena at latitudes above the sunspot activity belts are linked to solar activity which occurs many years later in the lower latitudes.

Hathaway, David H.↗

Defining Nitrogen Kinetics for Air Break in Prebreathe

Actual tissue nitrogen (N2) kinetics are complex; the uptake and elimination is often approximated with a single half-time compartment in statistical descriptions of denitrogenation [prebreathe (PB)] protocols. Air breaks during PB complicate N2 kinetics. A comparison of symmetrical versus asymmetrical N2 kinetics was performed using the time to onset of hypobaric decompression sickness (DCS) as a surrogate for actual venous N2 tension. Published results of 12 tests involving 179 hypobaric exposures in altitude chambers after PB, with and without air breaks, provide the complex protocols from which to model N2 kinetics. DCS survival time for combined control and air breaks were described with an accelerated log logistic model where N2 uptake and elimination before, during, and after the air break was computed with a simple exponential function or a function that changed half-time depending on ambient N2 partial pressure. P1N2-P2 = delta P defined DCS dose for each altitude exposure, where P2 was the test altitude and P1N2 was computed N2 pressure at the beginning of the altitude exposure. The log likelihood (LL) without DCS dose (null model) was -155.6, and improved (best-fit) to -97.2 when dose was defined with a 240 min half-time for both N2 elimination and uptake during the PB. The description of DCS survival time was less precise with asymmetrical N2 kinetics, for example, LL was -98.9 with 240 min half-time elimination and 120 min half-time uptake. The statistical regression described survival time mechanistically linked to symmetrical N2 kinetics during PBs that also included air breaks. The results are data-specific, and additional data may change the conclusion. The regression is useful to compute additional PB time to compensate for an air break in PB within the narrow range of tested conditions.

Conkin, Johnny↗

Effect Modification by Age on the Benefit or Harm of Antihypertensive Treatment for Elderly Hypertensives: A Systematic Review and Meta-analysis

Abstract BACKGROUND The influence of age on balance of benefit vs. potential harm of blood pressure (BP)-lowering therapy for elderly hypertensives is unclear. We evaluated the modifying effects of age on BP lowering for various adverse outcomes in hypertensive patients older than 60 years without specified comorbidities. METHODS All relevant randomized controlled trials (RCTs) were systematically identified. Coronary heart disease, stroke, heart failure (HF), cardiovascular death, major adverse cardiovascular events (MACE), renal failure (RF), and all-cause death were assessed. Meta-regression analysis was used to explore the relationship between achieved systolic BP (SBP) and the risk of adverse events. Random-effects meta-analysis was used to pool the estimates. RESULTS Our study included 18 RCTs (n = 53,993). Meta-regression analysis showed a lower achieved SBP related with a lower risk of stroke and cardiovascular death, but an increased risk of RF. The regression slopes were comparable between populations stratifying by age 75 years. In subgroup analysis, the relative risks of a more aggressive BP lowering strategy were similar between patients aged older or less than 75 years for all outcomes except for RF (P for interaction = 0.02). Compared to treatment with final achieved SBP 140–150 mm Hg, a lower achieved SBP (<140 mm Hg) was significantly associated with decreased risk of stroke (relative risk = 0.68; 95% confidence interval = 0.55–0.85), HF (0.77; 0.60–0.99), cardiovascular death (0.68; 0.52–0.89), and MACE (0.83; 0.69–0.99). CONCLUSIONS To treat hypertension in the elderly, age had trivial effect modification on most outcomes, except for renal failure. Close monitoring of renal function may be warranted in the management of elderly hypertension.

Huang, Chi-Jung↗

Effect of age and gender on sudomotor and cardiovagal function and blood pressure response to tilt in normal subjects

Normative data are limited on autonomic function tests, especially beyond age 60 years. We therefore evaluated these tests in a total of 557 normal subjects evenly distributed by age and gender from 10 to 83 years. Heart rate (HR) response to deep breathing fell with increasing age. Valsalva ratio varied with both age and gender. QSART (quantitative sudomotor axon-reflex test) volume was consistently greater in men (approximately double) and progressively declined with age for all three lower extremity sites but not the forearm site. Orthostatic blood pressure reduction was greater with increasing age. HR at rest was significantly higher in women, and the increment with head-up tilt fell with increasing age. For no tests did we find a regression to zero, and some tests seem to level off with increasing age, indicating that diagnosis of autonomic failure was possible to over 80 years of age.

Non-NASA Center↗

The effects of participatory mode and task workload on the detection of dynamic system failures

The ability of operators to detect step changes in the dynamics of control systems is investigated as a joint function of, (1) participatory mode: whether subjects are actively controlling those dynamics or are monitoring an autopilot controlling them, and (2) concurrent task workload. A theoretical analysis of detection in the two modes identifies factors that will favor detection in either mode. Three subjects detected system failures in either an autopilot or manual controlling mode, under single-task conditions and concurrently with a subcritical tracking task. Latency and accuracy of detection were assessed and related through a speed accuracy tradeoff representation. It was concluded that failure detection performance was better during manual control than during autopilot control, and that the extent of this superiority was enhanced as dual-task load increased. Ensemble averaging and multiple regression techniques were then employed to investigate the cues utilized by the subjects in making their detection decisions.

Wickens, C. D.↗

Defining Nitrogen Kinetics for Air Break in Prebreath

Actual tissue nitrogen (N2) kinetics are complex; the uptake and elimination is often approximated with a single half-time compartment in statistical descriptions of denitrogenation [prebreathe(PB)] protocols. Air breaks during PB complicate N2 kinetics. A comparison of symmetrical versus asymmetrical N2 kinetics was performed using the time to onset of hypobaric decompression sickness (DCS) as a surrogate for actual venous N2 tension. METHODS: Published results of 12 tests involving 179 hypobaric exposures in altitude chambers after PB, with and without airbreaks, provide the complex protocols from which to model N2 kinetics. DCS survival time for combined control and airbreaks were described with an accelerated log logistic model where N2 uptake and elimination before, during, and after the airbreak was computed with a simple exponential function or a function that changed half-time depending on ambient N2 partial pressure. P1N2-P2 = (Delta)P defined decompression dose for each altitude exposure, where P2 was the test altitude and P1N2 was computed N2 pressure at the beginning of the altitude exposure. RESULTS: The log likelihood (LL) without decompression dose (null model) was -155.6, and improved (best-fit) to -97.2 when dose was defined with a 240 min half-time for both N2 elimination and uptake during the PB. The description of DCS survival time was less precise with asymmetrical N2 kinetics, for example, LL was -98.9 with 240 min half-time elimination and 120 min half-time uptake. CONCLUSION: The statistical regression described survival time mechanistically linked to symmetrical N2 kinetics during PBs that also included airbreaks. The results are data-specific, and additional data may change the conclusion. The regression is useful to compute additional PB time to compensate for an airbreak in PB within the narrow range of tested conditions.

Conkin, Johnny↗

Temporal Cerebral Microbleeds Are Associated With Radiation Necrosis and Cognitive Dysfunction in Patients Treated for Nasopharyngeal Carcinoma

Purpose: Radiation therapy for patients with nasopharyngeal carcinoma (NPC) may be complicated with radiation-induced brain necrosis (RN), resulting in deteriorated cognitive function. However, the underlying mechanism of this phenomenon remains unclear. This study attempts to elucidate the association between cerebral microbleeds (CMBs) and radiation necrosis and cognitive dysfunction in NPC patients treated with radiation therapy. Methods and Materials: This cross-sectional study included 106 NPC patients who were exposed to radiation therapy (78 patients with RN and 28 without RN). Sixty-six patients without discernable intracranial pathology were included as the control group. CMBs were confirmed using susceptibility-weighted magnetic resonance imaging. Cognitive function was accessed using Montreal Cognitive Assessment. Patients with a total score below 26 were defined as cognitively dysfunction. Results: Seventy-seven patients (98.7%) in the RN group and 12 patients (42.9%) in the non-RN group had at least 1 CMB. In contrast, only 14 patients (21.2%) in the control group had CMBs. In patients with a history of radiation therapy, CMBs most commonly presented in temporal lobes (76.4%) followed by cerebellum (23.7%). Patients with RN had more temporal CMBs than those in the non-RN group (37.7 ± 51.9 vs 3.8 ± 12.6, respectively; P<.001). The number of temporal lobe CMBs was predictive for larger volume of brain necrosis (P<.001) in multivariate linear regression analysis. Although cognitive impairment was diagnosed in 55.1% of RN patients, only 7.1% of non-RN patients sustained cognitive impairment (P<.001). After adjusting for age, sex, education, period after radiation therapy, CMBs in other lobes, and RN volume, the number of temporal CMBs remained an independent risk factor for cognitive dysfunction (odds ratio [OR]: 1.03; 95% confidence interval [CI]: 1.01-1.04; P=.003). Conclusions: CMBs is a common radiological manifestation in NPC patients with RN. The number of temporal CMBs is independently associated with increased likelihood of cognitive dysfunction in patients with RN.

62 RADIOLOGY AND NUCLEAR MEDICINE↗