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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 OSTI2024

Reducing stomatal density by expression of a synthetic epidermal patterning factor increases leaf intrinsic water use efficiency and reduces plant water use in a C4 crop

Abstract Enhancing crop water use efficiency (WUE) is a key target trait for climatic resilience and expanding cultivation on marginal lands. Engineering lower stomatal density to reduce stomatal conductance (gs) has improved WUE in multiple C3 crop species. However, reducing gs in C3 species often reduces photosynthetic carbon gain. A different response is expected in C4 plants because they possess specialized anatomy and biochemistry which concentrates CO2 at the site of fixation. This modifies the relationship of photosynthesis (AN) with intracellular CO2 concentration (ci), such that photosynthesis is CO2 saturated and reductions in gs are unlikely to limit AN. To test this hypothesis, genetic strategies were investigated to reduce stomatal density in the C4 crop sorghum. Constitutive expression of a synthetic epidermal patterning factor (EPF) transgenic allele in sorghum led to reduced stomatal densities, reduced gs, reduced plant water use, and avoidance of stress during a period of water deprivation. In addition, moderate reduction in stomatal density did not increase stomatal limitation to AN. However, these positive outcomes were associated with negative pleiotropic effects on reproductive development and photosynthetic capacity. Avoiding pleiotropy by targeting expression of the transgene to specific tissues could provide a pathway to improved agronomic outcomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Prognostic Factors and Patterns of Locoregional Failure After Surgical Resection in Patients With Cholangiocarcinoma Without Adjuvant Radiation Therapy: Optimal Field Design for Adjuvant Radiation Therapy

Purpose: To identify prognostic factors and patterns of local failure in patients with cholangiocarcinoma (CCA), after surgical resection in the absence of adjuvant radiation, for optimal definition of target volumes encompassing the majority of local recurrences. Methods and Materials: A chart review was performed in patients who underwent resection for primary CCA (intrahepatic, hilar, and distal) between 1999 and 2014. Local failure was defined as recurrence in a theoretical reasonable postoperative radiation volume. This includes the cut surface of liver, biliary anastomosis, hilum, portal nodes, celiac nodes, peri-pancreatic nodes, gastro-hepatic nodes, and retroperitoneal nodes. Patients who received adjuvant radiation were excluded. Results: A total of 189 patients underwent surgical resection for CCA, of whom 145 patients had sufficient follow-up. Median follow-up was 41.6 months (95% confidence interval 35.4-48.7 months). Of the 145 cases, 102 were intrahepatic and 43 were hilar/distal CCA. Adjuvant chemotherapy was given in 38 cases (26%), of which 20 (54%) were gemcitabine-based. Eighty-six patients (59%) had a documented recurrence, of whom 44 (51%) had a locoregional component. Among patients who had a recurrence, 23 (27%) had a recurrence at the biliary anastomosis and/or cut liver surface. Twenty-eight patients (32.6%) had a recurrence in the regional lymph nodes, most prevalent in the portal (16.3%) and retroperitoneal (17.4%) lymph nodes. Univariable analysis identified tumor size, any vascular invasion, presence of satellites, stage/nodal status, and receipt of chemotherapy as significant prognostic factors of overall recurrence among intrahepatic patients. Presence of satellites, and stage 3/Nx status remained statistically significant in multivariable modeling. Conclusions: The areas at highest risk for locoregional recurrence after surgical resection for primary CCA are the biliary anastomosis/cut liver surface, portal lymph nodes, and retroperitoneal lymph nodes. Although these results need to be validated, adjuvant radiation should possibly cover these areas to maximize locoregional control.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

CRISPR/Cas9 Directed Reprogramming of iPSC for Accelerated Motor Neuron Differentiation Leads to Dysregulation of Neuronal Fate Patterning and Function

Neurodegeneration causes a significant disease burden and there are few therapeutic interventions available for reversing or slowing the disease progression. Induced pluripotent stem cells (iPSCs) hold significant potential since they are sourced from adult tissue and have the capacity to be differentiated into numerous cell lineages, including motor neurons. This differentiation process traditionally relies on cell lineage patterning factors to be supplied in the differentiation media. Genetic engineering of iPSC with the introduction of recombinant master regulators of motor neuron (MN) differentiation has the potential to shorten and streamline cell developmental programs. We have established stable iPSC cell lines with transient induction of exogenous LHX3 and ISL1 from the Tet-activator regulatory region and have demonstrated that induction of the transgenes is not sufficient for the development of mature MNs in the absence of neuron patterning factors. Comparative global transcriptome analysis of MN development from native and Lhx-ISL1 modified iPSC cultures demonstrated that the genetic manipulation helped to streamline the neuronal patterning process. However, leaky gene expression of the exogenous MN master regulators in iPSC resulted in the premature activation of genetic pathways characteristic of the mature MN function. Dysregulation of metabolic and regulatory pathways within the developmental process affected the MN electrophysiological responses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Greater aperture counteracts effects of reduced stomatal density on WUE: a case study on sugarcane and meta-analysis

Stomata regulate CO 2 and water vapor exchange between leaves and the atmosphere. Stomata are a target for engineering to improve crop intrinsic water use efficiency (iWUE). One example is by expressing genes that lower stomatal density (SD) and reduce stomatal conductance (g sw ). However, the quantitative relationship between reduced SD, g sw , and the mechanisms underlying it is poorly understood. We addressed this knowledge gap using low-SD sugarcane (Saccharum spp. hybrid) as a case study alongside a meta-analysis of data from 10 species. Transgenic expression of EPIDERMAL PATTERNING FACTOR 2 from Sorghum bicolor (SbEFP2) in sugarcane reduced SD by 26-38% but did not affect gsw compared to wildtype. Further, no changes occurred in stomatal complex size or proxies for photosynthetic capacity. Measurements of gas exchange at low CO 2 concentrations that promote complete stomatal opening to normalize aperture size between genotypes were combined with modeling of maximum gsw from anatomical data. These data suggest that increased stomatal aperture is the only possible explanation for maintaining gsw when SD is reduced. Meta-analysis across C 3 dicots, C 3 monocots, and C 4 monocots revealed engineered reductions in SD are strongly correlated with lower gsw (r 2 =0.60-0.98), but this response is damped relative to the change in anatomy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Brachypodium SPEECHLESS2 Promoter Drives Expression of a Synthetic EPF to Reduce Stomatal Density in Sugarcane Without Pleiotropic Effects

Stomata are microscopic pores that regulate the exchange of CO 2 and water vapour, making them a major target for engineering plants with improved intrinsic water use efficiency (iWUE). Proof-of-concept studies have demonstrated the potential to increase iWUE by reducing stomatal density (SD) and stomatal conductance (g sw ) by ubiquitously expressing EPIDERMAL PATTERNING FACTOR (EPF) family genes. However, unwanted effects on leaf, stem and reproductive traits are often observed when EPFs are misexpressed in this fashion. We sought to test if these effects result from pleiotropy and to identify a targeted promoter that can circumvent the side effects while retaining the desired reduction in SD. A previously reported synthetic EPF (EPF syn ) was expressed in sugarcane ( Saccharum spp.) using two putatively tissue-specific promoters from Brachypodium distachyon (BdCESA7p and BdSPCH2p) and a ubiquitous control from Zea mays (ZmUBI4p). BdSPCH2p control reduced SD to statistically equivalent levels as ZmUBI4p on the abaxial (23%) and adaxial (23%) leaf surfaces. ZmUB4p and BdCESA7p induce expression in four tissue types often associated with pleiotropic effects in EPF-expressing low SD plants. Transgenic plants carrying either the BdCESA7p or ZmUBI4p EPF syn cassettes displayed leaf chlorosis, reduced leaf nitrogen and chlorophyll content, and altered stem architecture. However, transgenic events harboring the BdSPCH2p EPF syn cassette restricted EPF syn expression to the stomatal development zone and leaf nodal tissues and produced transgenic plants without the associated pleiotropic effects. These results represent an important step toward engineering low-SD crops since they show that targeted gene expression can engineer stomatal patterning without impairing agronomically important traits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Effects of diisononyl phthalate on osteopenia in intact mice

Osteopenia is characterized by bone loss and deterioration of trabecular bone, which leads to osteoporotic fractures. This disease is highly prevalent in industrialized areas and is associated with exposure to endocrine disrupting chemicals (EDCs). Diisononyl phthalate (DINP) is one of these EDCs and is mainly used as a plasticizer in flexible polyvinyl chloride (PVC) products. Although it is well known that exposure to DINP is harmful to humans, no studies have been reported concerning its contribution to osteopenia. Therefore, in this study, we injected DINP (2, 20, and 200 mg/kg) into C3H/HeN mice for 6 weeks and found that the uterus weight, bone (femur and tibia) weight, and bone length of the DINP-exposed mice were reduced compared to those of the SHAM group. On the other hand, body weight, the serum alkaline phosphatase (ALP) and inorganic phosphorus (IP) levels in the DINP treated mice were increased compared with those of the SHAM group. The tartrate-resistant acid phosphatase (TRAP) activity (bone resorption marker) was increased and the bone alkaline phosphatase (BALP) activity was lowered by the treatment with DINP as compared with the SHAM group. Furthermore, the microarchitecture of the femur and tibia in the intact mice was destroyed by the DINP injection. The tissue volume (TV), bone volume (BV), BV/TV, bone surface (BS), BS/TV, trabecular thickness (Tb.Th), and trabecular number (Tb.N) were reduced and the trabecular pattern factor (Tb.Pf), structure model index (SMI), and trabecular separation (Tb.Sp) were increased by the DINP injection. The bone mineral density (BMD) of the femur and tibia was lower in the DINP group than in the SHAM group. These results indicate that DINP contributes to an increased risk of osteopenia via destruction of the microarchitecture and enhancement of osteoclast activity. - Highlights: • DINP induces reduction of the uterus weight, bone weight, bone length. • DINP induces enhancement of TRAP activity and suppression of BALP activity. • DINP induces cancellous bone loss in the tibia and femur. • DINP induces reduction of BMD in femur and tibia.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Hybrid electric buses fuel consumption prediction based on real-world driving data

Estimating fuel consumption by hybrid diesel buses is challenging due to its diversified operations and driving cycles. Here, long-term transit bus monitoring data were utilized to empirically compare fuel consumption of diesel and hybrid buses under various driving conditions. Artificial neural network (ANN) based high-fidelity microscopic (1 Hz) and mesoscopic (5–60 min) fuel consumption models were developed for hybrid buses. The microscopic model contained 1 Hz driving, grade, and environment variables. The mesoscopic model aggregated 1 Hz data into 5 to 60-minute traffic pattern factors and predicted average fuel consumption over its duration. The prediction results show mean absolute percentage errors of 1–2% for microscopic models and 5–8% for mesoscopic models. The data were partitioned by different driving speeds, vehicle engine demand, and road grade to investigate their impacts on prediction performance.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Identifying Key Environmental Factors Explaining Temporal Patterns of DOC Export From Watersheds in the Conterminous United States

The export of dissolved organic carbon (DOC) from a watershed is a key component of the terrestrial biosphere carbon cycle. There is a need to improve our understanding of how and by how much various environmental factors are driving the temporal patterns of DOC export in order to accurately model and evaluate terrestrial carbon storage and fluxes. In this synthesis, we compiled observational data sets from 14 watersheds in the conterminous United States spanning the time period from 1981 to 2017. We used these data sets to examine the relative impacts of various climate, atmospheric deposition, and land cover factors on the temporal patterns of DOC export across watersheds of different sizes and landscape conditions, as well as the time-series autocorrelation of DOC export. Overall, our results suggest that the dominant factor on an annual scale was the amount of precipitation, which had a positive correlation with DOC export from a watershed. Overall increasing nitrogen deposition was coincident with increasing DOC export, and increasing sulfur deposition was coincident with declining DOC export. The seasonal pattern of DOC export was strongly regulated by air temperature, the long-term trend was negatively influenced by increasing sulfur deposition, and no obvious autocorrelation was detected in DOC export. In addition, higher rates of DOC export were positively correlated with greater area of wetlands within a watershed, but was not found to be strongly related to any of the other land cover types.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Investigating explainable transfer learning for battery lifetime prediction under state transitions

Battery lifetime prediction at early cycles is crucial for researchers and manufacturers to examine product quality and promote technology development. Machine learning has been widely utilized to construct data-driven solutions for high-accuracy predictions. However, the internal mechanisms of batteries are sensitive to many factors, such as charging/discharging protocols, manufacturing/storage conditions, and usage patterns. These factors will induce state transitions, thereby decreasing the prediction accuracy of data-driven approaches. Transfer learning is a promising technique that overcomes this difficulty and achieves accurate predictions by jointly utilizing information from various sources. Hence, we develop two transfer learning methods, Bayesian Model Fusion and Weighted Orthogonal Matching Pursuit, to strategically combine prior knowledge with limited information from the target dataset to achieve superior prediction performance. From our results, our transfer learning methods reduce root-mean-squared error by 41% through adapting to the target domain. Furthermore, the transfer learning strategies identify the variations of impactful features across different sets of batteries and therefore disentangle the battery degradation mechanisms and the root cause of state transitions from the perspective of data mining. These findings suggest that the transfer learning strategies proposed in our work are capable of acquiring knowledge across multiple data sources for solving specialized issues.

25 ENERGY STORAGE↗
DOE OSTI2023

Regional biogeography versus intra-annual dynamics of the root and soil microbiome

Abstract Background Root and soil microbial communities constitute the below-ground plant microbiome, are drivers of nutrient cycling, and affect plant productivity. However, our understanding of their spatiotemporal patterns is confounded by exogenous factors that covary spatially, such as changes in host plant species, climate, and edaphic factors. These spatiotemporal patterns likely differ across microbiome domains (bacteria and fungi) and niches (root vs. soil). Results To capture spatial patterns at a regional scale, we sampled the below-ground microbiome of switchgrass monocultures of five sites spanning > 3 degrees of latitude within the Great Lakes region. To capture temporal patterns, we sampled the below-ground microbiome across the growing season within a single site. We compared the strength of spatiotemporal factors to nitrogen addition determining the major drivers in our perennial cropping system. All microbial communities were most strongly structured by sampling site, though collection date also had strong effects; in contrast, nitrogen addition had little to no effect on communities. Though all microbial communities were found to have significant spatiotemporal patterns, sampling site and collection date better explained bacterial than fungal community structure, which appeared more defined by stochastic processes. Root communities, especially bacterial, were more temporally structured than soil communities which were more spatially structured, both across and within sampling sites. Finally, we characterized a core set of taxa in the switchgrass microbiome that persists across space and time. These core taxa represented < 6% of total species richness but > 27% of relative abundance, with potential nitrogen fixing bacteria and fungal mutualists dominating the root community and saprotrophs dominating the soil community. Conclusions Our results highlight the dynamic variability of plant microbiome composition and assembly across space and time, even within a single variety of a plant species. Root and soil fungal community compositions appeared spatiotemporally paired, while root and soil bacterial communities showed a temporal lag in compositional similarity suggesting active recruitment of soil bacteria into the root niche throughout the growing season. A better understanding of the drivers of these differential responses to space and time may improve our ability to predict microbial community structure and function under novel conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Differential patterns of reproductive and lifestyle risk factors for breast cancer according to birth cohorts among women in China, Japan and Korea

Background: The birth cohort effect has been suggested to influence the rate of breast cancer incidence and the trends of associated reproductive and lifestyle factors. We conducted a cohort study to determine whether a differential pattern of associations exists between certain factors and breast cancer risk based on birth cohorts. Methods: This was a cohort study using pooled data from 12 cohort studies. We analysed associations between reproductive (menarche age, menopause age, parity and age at first delivery) and lifestyle (smoking and alcohol consumption) factors and breast cancer risk. We obtained hazard ratios (HRs) with 95% confidence intervals (CIs) using the Cox proportional hazard regression analysis on the 1920s, 1930s, 1940s and 1950s birth cohorts. Results: Parity was found to lower the risk of breast cancer in the older but not in the younger birth cohort, whereas lifestyle factors showed associations with breast cancer risk only among the participants born in the 1950s. In the younger birth cohort group, the effect size was lower for parous women compared to the other cohort groups (HR [95% CI] 0.86 [0.66–1.13] compared to 0.60 [0.49–0.73], 0.46 [0.38–0.56] and 0.62 [0.51–0.77]). Meanwhile, a higher effect size was found for smoking (1.45 [1.14–1.84] compared to 1.25 [0.99–1.58], 1.06 [0.85–1.32] and 0.86 [0.69–1.08]) and alcohol consumption (1.22 [1.01–1.48] compared to 1.10 [0.90–1.33], 1.15 [0.96–1.38], and 1.07 [0.91–1.26]). Conclusion: We observed different associations of parity, smoking and alcohol consumption with breast cancer risk across various birth cohorts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Approaching Angstrom-Scale Resolution in Lithography Using Low-Molecular-Mass Resists (<500 Da)

Resists that enable high-throughput and high-resolution patterning are essential in driving the semiconductor technology forward. The ultimate patterning performance of a resist in lithography is limited because of the trade-off between resolution, line-width roughness, and sensitivity; improving one or two of these parameters typically leads to a loss in the third. As the patterned feature sizes approach angstrom scale, the trade-off between these three metrics becomes increasingly hard to resolve and calls for a fundamental rethinking of the resist chemistry. Low-molecular-mass monodispersed metal-containing resists of high atom economy can provide not only very high resolution but also very low line-width roughness without sacrificing sensitivity. Here we describe a modular metal-containing resist platform (molecular mass <500 Da) where a molecular resist consists of just two components: a metal and a radical initiator bonded to it. This simple system not only is amenable to high-resolution electron beam lithography (EBL) and extreme ultraviolet lithography (EUVL) but also unites them mechanistically, giving a consolidated perspective of molecular and chemical processes happening during exposure. Irradiation of the resist leads to the production of secondary electrons that generate radicals in the initiator bonded to metal. This brings about an intramolecular rearrangement and causes solubility switch in the exposed resist. We demonstrate record 1.9–2.0 nm isolated patterns and 7 nm half-pitch dense line-space features over a large area using EBL. With EUVL, 12 nm half-pitch line-space features are shown at a dose of 68 mJ/cm 2 . In both of these patterning techniques, the line-width roughness was found to be ≤2 nm, a record low value for any resist platform, also leading to a low-performance trade-off metric, Z factor, of 0.6 × 10 –8 mJ·nm 3 . With the ultimate resolution limited by instrumental factors, potential patterning at the level of a unit cell can be envisaged, making low-molecular-mass resists best poised for angstrom-scale lithography.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Evaluation of data driven low-rank matrix factorization for accelerated solutions of the Vlasov equation

Low-rank methods have shown success in accelerating simulations of a collisionless plasma described by the Vlasov equation, but still rely on computationally costly linear algebra every time step. We propose a data-driven factorization method using artificial neural networks, specifically with convolutional layer architecture, that trains on existing simulation data. At inference time, the model outputs a low-rank decomposition of the distribution field of the charged particles, and we demonstrate that this step is faster than the standard linear algebra technique. Numerical experiments show that the method achieves comparable reconstruction accuracy for interpolation tasks, generalizing to unseen test data in a manner beyond just memorizing training data; patterns in factorization also inherently followed the same numerical trend as those within algebraic methods (e.g., truncated singular-value decomposition). However, when training on the first 70% of a time-series data and testing on the remaining 30%, the method fails to meaningfully extrapolate. Despite this limiting result, the technique may have benefits for simulations in a statistical steady-state or otherwise showing temporal stability. These results suggest that while the model offers a computationally efficient alternative for datasets with temporal stability, its current formulation is best suited for interpolation rather than for predicting future states in time-evolving systems. This study thus lays the groundwork for further refinement of neural network-based approaches to low-rank matrix factorization in high-dimensional plasma simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Supervised enhancer prediction with epigenetic pattern recognition and targeted validation

Enhancers are important non-coding elements, but they have traditionally been hard to characterize experimentally. The development of massively parallel assays allows the characterization of large numbers of enhancers for the first time. Here, we developed a framework using Drosophila STARR-seq to create shape-matching filters based on meta-profiles of epigenetic features. We integrated these features with supervised machine-learning algorithms to predict enhancers. We further demonstrated that our model could be transferred to predict enhancers in mammals. We comprehensively validated the predictions using a combination of in vivo and in vitro approaches, involving transgenic assays in mice and transduction-based reporter assays in human cell lines (153 enhancers in total). The results confirmed that our model can accurately predict enhancers in different species without re-parameterization. Finally, we examined the transcription factor binding patterns at predicted enhancers versus promoters. Here, we demonstrated that these patterns enable the construction of a secondary model that effectively distinguishes enhancers and promoters.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Understanding variation in salamander ionomes: A nutrient balance approach

1. Ecological stoichiometry uses information on a few key biological elements (C, N and P) to explain complex ecological patterns. Although factors driving variation in these elements are well established, expanding stoichiometric principles to explore dynamics of the many other essential elements comprising biological tissues (i.e. the ionome) is needed to determine their metabolic relationships and better understand biological control of elemental flows through ecosystems. 2. Here in this paper, we report observations of ionomic variation in two species of salamander (Ambystoma opacum and A. talpoideum) across ontogenic stages using specimens from biological collections of two wetlands sampled over a 30-year period. This unique data set allowed us to explore the extent of ionomic variation between species, among ontogenic stages, between sites and through time. 3. We found species- and, to a lesser extent, site-specific differences in C, N and P along with 13 other elements forming salamander ionomes but saw no evidence of temporal changes. Salamander ionomic composition was most strongly related to ontogeny with relatively higher concentrations of many elements in adult males (i.e. Ca, P, S, Mg, Zn and Cu) compared to metamorphic juveniles, which had greater amounts of C, Fe and Mn. 4. In addition to patterns of individual elements, covariance among elements was used to construct multi-elemental nutrient balances, which revealed differences in salamander elemental composition between species and sites and changes in elemental proportions across ontogenic development. These multi-elemental balances distinguished among species-site-ontogenic stage groups better than using only C, N and P. 5. Overall, this study highlights the responsiveness of consumer ionomes to life-history and environmental variation while reflecting underlying relationships among elements tied to biological function. As such, ionomic studies can provide important insights into factors shaping consumer elemental composition and for predicting how these changes might affect higher-order ecological processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Radiation-Induced Large Vessel Cerebral Vasculopathy in Pediatric Patients With Brain Tumors Treated With Proton Radiation Therapy

Purpose: The purpose of this research was to evaluate the incidence, time to development, imaging patterns, risk factors, and clinical significance of large vessel cerebral vasculopathy in pediatric patients with brain tumors treated with proton radiation therapy. Methods and Materials: A retrospective study was performed on 75 consecutive pediatric patients with primary brain tumors treated with proton radiation therapy. Radiation-induced large vessel cerebral vasculopathy (RLVCV) was defined as intracranial large vessel arterial stenosis or occlusion confirmed on magnetic resonance angiography, computed tomographic angiography, catheter angiography, or a combination of these within an anatomic region with previous exposure to proton beam therapy and not present before radiation therapy. Clinical records were used to determine the incidence, timing, radiation dose to the large vessels, and clinical significance associated with the development of large vessel vasculopathy in these patients. Results: RLVCV was present in 5 of 75 (6.7%) patients and included tumor pathologic features of craniopharyngioma (n=2), ATRT (n=1), medulloblastoma (n=1), and anaplastic astrocytoma (n=1). The median time from completion of radiation therapy to development was 1.5 years (mean, 3.0 years; range, 1.0-7.5 years). Neither mean age at the time of radiation therapy (5.1 years) nor mean radiation therapy dose to the large vessels (54.5 Gy) was a statistically significant risk factor. Four of the 5 patients with RLVCV presented with acute stroke and demonstrated magnetic resonance imaging evidence of acute infarcts in the expected vascular distributions. Angiography studies demonstrated collateral vessel formation in only 2 of the patients with RLVCV. No patients demonstrated acute hemorrhage or aneurysm. Two patients were treated with pial synangiomatosis surgery. Conclusions: RLVCV can occur in pediatric patients with brain tumors treated with proton radiation therapy. Further studies are necessary to determine potential risk factors for large vessel vasculopathy with proton radiation therapy in comparison with conventional photon radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗