Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “HISTOGRAM”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Convective cloud vertical velocity and mass-flux characteristics from radar wind profiler observations during GoAmazon2014/5: VERTICAL VELOCITY GOAMAZON2014/5

A radar wind profiler data set collected during the 2 year Department of Energy Atmospheric Radiation Measurement Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) campaign is used to estimate convective cloud vertical velocity, area fraction, and mass flux profiles. Vertical velocity observations are presented using cumulative frequency histograms and weighted mean profiles to provide insights in a manner suitable for global climate model scale comparisons (spatial domains from 20 km to 60 km). Convective profile sensitivity to changes in environmental conditions and seasonal regime controls is also considered. Aggregate and ensemble average vertical velocity, convective area fraction, and mass flux profiles, as well as magnitudes and relative profile behaviors, are found consistent with previous studies. Updrafts and downdrafts increase in magnitude with height to midlevels (6 to 10 km), with updraft area also increasing with height. Updraft mass flux profiles similarly increase with height, showing a peak in magnitude near 8 km. Downdrafts are observed to be most frequent below the freezing level, with downdraft area monotonically decreasing with height. Updraft and downdraft profile behaviors are further stratified according to environmental controls. These results indicate stronger vertical velocity profile behaviors under higher convective available potential energy and lower low-level moisture conditions. Sharp contrasts in convective area fraction and mass flux profiles are most pronounced when retrievals are segregated according to Amazonian wet and dry season conditions. During this deployment, wet season regimes favored higher domain mass flux profiles, attributed to more frequent convection that offsets weaker average convective cell vertical velocities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Diagnosing Cloud Biases in the GFDL AM3 Model With Atmospheric Classification

In this paper, we define a set of 21 atmospheric states, or recurring weather patterns, for a region surrounding the Atmospheric Radiation Measurement Program's Southern Great Plains site using an iterative clustering technique. The states are defined using dynamic and thermodynamic variables from reanalysis, tested for statistical significance with cloud radar data from the Southern Great Plains site, and are determined every 6 h for 14 years, creating a time series of atmospheric state. The states represent the various stages of the progression of synoptic systems through the region (e.g., warm fronts, warm sectors, cold fronts, cold northerly advection, and high-pressure anticyclones) with a subset of states representing summertime conditions with varying degrees of convective activity. We use the states to classify output from the NOAA/Geophysical Fluid Dynamics Laboratory AM3 model to test the model's simulation of the frequency of occurrence of the states and of the cloud occurrence during each state. The model roughly simulates the frequency of occurrence of the states but exhibits systematic cloud occurrence biases. Comparison of observed and model-simulated International Satellite Cloud Climatology Project histograms of cloud top pressure and optical thickness shows that the model lacks high thin cloud under all conditions, but biases in thick cloud are state-dependent. Frontal conditions in the model do not produce enough thick cloud, while fair-weather conditions produce too much. Finally, we find that increasing the horizontal resolution of the model improves the representation of thick clouds under all conditions but has little effect on high thin clouds. However, increasing resolution also changes the distribution of states, causing an increase in total cloud occurrence bias.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Value of Formalin Fixation for the Prolonged Preservation of Rodent Myocardial Microanatomical Organization: Evidence by MR Diffusion Tensor Imaging

Previous ex vivo diffusion tensor imaging (DTI) studies on formalin-fixed myocardial tissue assumed that, after some initial changes in the first 48 hr since the start of fixation, DTI parameters remain stable over time. Prolonged preservation of cardiac tissue in formalin prior to imaging has been seen many times in the DTI literature as it is considered orderly. Here, our objective is to define the effects of the prolonged cardiac tissue exposure to formalin on tissue microanatomical organization, as this is assessed by DTI parameters. DTI experiments were conducted on eight excised rodent hearts that were fixed by immersion in formalin. The samples were randomly divided into two equinumerous groups corresponding to shorter (~2 weeks) and more prolonged (~6–8 weeks) durations of tissue exposure to formalin prior to imaging. We found that when the duration of cardiac tissue exposure to formalin before imaging increased, water diffusion became less restricted, helix angle (HA) histograms flattened out and exhibited heavier tails (even though the classic HA transmural variation was preserved), and a significant loss of inter-voxel primary diffusion orientation integrity was introduced. The prolonged preservation of cardiac tissue in formalin profoundly affected its microstructural organization, as this was assessed by DTI parameters. The accurate interpretation of diffusivity profiles necessitates awareness of the pitfalls of prolonged cardiac tissue exposure duration to formalin. The acquired knowledge works to the advantage of a proper experimental design of DTI studies of fixed hearts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Predictive analytics of selections of russet potatoes

We explore the application of machine learning algorithms specifically to enhance the selection process of Russet potato (Solanum tuberosum L.) clones in breeding trials by predicting their suitability for advancement. This study addresses the challenge of efficiently identifying high-yield, disease-resistant, and climate-resilient potato varieties that meet processing industry standards. Leveraging manually collected data from trials in the state of Oregon, we investigate the potential of a wide variety of state-of-the-art binary classification models. The dataset includes 1086 clones, with data on 38 attributes recorded for each clone, focusing on yield, size, appearance, and frying characteristics, with several control varieties planted consistently across four Oregon regions from 2013 to 2021. We conduct a comprehensive analysis of the dataset that includes preprocessing, feature engineering, and imputation to address missing values. We focus on several key metrics such as accuracy, F1-score, and Matthews correlation coefficient (MCC) for model evaluation. The top-performing models, namely a feedforward neural network classifier (Neural Net), a histogram-based gradient boosting classifier (HGBC), and a support vector machine classifier (SVM), demonstrate consistent and significant results. To further validate our findings, we conducted a simulation study using the aims, data-generating mechanisms, estimands, methods, and performance measures (ADEMP) framework, simulating different data-generating scenarios to assess model robustness and performance through true positive, true negative, false positive, and false negative distributions, area under the receiver operating characteristic curve (AUC-ROC) and MCC. The simulation results highlight that non-linear models like SVM and HGBC consistently show higher AUC-ROC and MCC than logistic regression, thus outperforming the traditional linear model across various distributions, and emphasizing the importance of model selection and tuning in agricultural trials. Variable selection further enhances model performance and identifies influential features in predicting trial outcomes. The findings emphasize the potential of machine learning in streamlining the selection process for potato varieties, offering benefits such as increased efficiency, substantial cost savings, and judicious resource utilization. Our study contributes insights into precision agriculture and showcases the relevance of advanced technologies for informed decision-making in breeding programs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Comparison of Oncentra® Brachy IPSA and graphical optimisation techniques: a case study of HDR brachytherapy head and neck and prostate plans

There are a number of different dwell positions and time optimisation options available in the Oncentra® Brachy (Elekta Brachytherapy Solutions, Veenendaal, The Netherlands) brachytherapy treatment planning system. The purpose of this case study was to compare graphical (GRO) and inverse planning by simulated annealing (IPSA) optimisation techniques for interstitial head and neck (HN) and prostate plans considering dosimetry, modelled radiobiology outcome and planning time. Four retrospective brachytherapy patients were chosen for this study, two recurrent HN and two prostatic boosts. Manual GRO and IPSA plans were generated for each patient. Plans were compared using dose–volume histograms (DVH) and dose coverage metrics including; conformity index (CI), homogeneity index (HI) and conformity number (CN). Logit and relative seriality models were used to calculate tumour control probability (TCP) and normal tissue complication probability (NTCP). Approximate planning time was also recorded. There was no significant difference between GRO and IPSA in terms of dose metrics with mean CI of 1.30 and 1.57 (P > 0.05) respectively. IPSA achieved an average HN TCP of 0.32 versus 0.12 for GRO while for prostate there was no significant difference. Mean GRO planning times were greater than 75 min while average IPSA planning times were less than 10 min. Planning times for IPSA were greatly reduced compared to GRO and plans were dosimetrically similar. For this reason, IPSA makes for a useful planning tool in HN and prostate brachytherapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Carcinoma of the anal canal: Intensity modulated radiation therapy (IMRT) versus three-dimensional conformal radiation therapy (3DCRT)

Patients with anal canal carcinoma treated with standard conformal radiotherapy frequently experience severe acute and late toxicity reactions to the treatment area. Roohipour et al. (Dis Colon Rectum 2008; 51: 147–53) stated a patient's tolerance of chemoradiation to be an important prediction of treatment success. A new intensity modulated radiation therapy (IMRT) technique for anal carcinoma cases has been developed at the Andrew Love Cancer Centre aimed at reducing radiation to surrounding healthy tissue. A same-subject repeated measures design was used for this study, where five anal carcinoma cases at the Andrew Love Cancer Centre were selected. Conformal and IMRT plans were generated and dosimetric evaluations were performed. Each plan was prescribed a total of 54 Gray (Gy) over a course of 30 fractions to the primary site. The IMRT plans resulted in improved dosimetry to the planning target volume (PTV) and reduction in radiation to the critical structures (bladder, external genitalia and femoral heads). Statistically there was no difference between the IMRT and conformal plans in the dose to the small and large bowel; however, the bowel IMRT dose–volume histogram (DVH) doses were consistently lower. The IMRT plans were superior to the conformal plans with improved dose conformity and reduced radiation to the surrounding healthy tissue. Anecdotally it was found that patients tolerated the IMRT treatment better than the three-dimensional (3D) conformal radiation therapy. This study describes and compares the planning techniques.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Evaluating the dosimetric effect of treatment-induced changes in virally mediated head and neck cancer patients

Patients with virally mediated head and neck cancer (VMHNC) often present with advanced nodal disease that is highly radioresponsive as demonstrated by tumour and nodal regression during treatment. The resultant changes may impact on the planned dose distribution and so adversely affect the therapeutic ratio. The aim of this study was to evaluate the dosimetric effect of treatment-induced anatomical changes in VMHNC patients who had undergone a replan. Thirteen patients with virally mediated oropharyngeal or nasopharyngeal cancer who presented for definitive radiotherapy between 2005 and 2010 and who had a replan generated were investigated. The dosimetric effect of anatomical changes was quantified by comparing dose–volume histograms (DVH) of primary and nodal gross target volumes and organs at risk (OAR), including spinal cord and parotid glands, from the original plan and a comparison plan. Eleven three-dimensional conformal radiation therapy (3DCRT) and two intensity modulated radiation therapy (IMRT) plans were evaluated. Dose to the spinal cord and brainstem increased by 4.1% and 2.6%, respectively. Mean dose to the parotid glands also increased by 3.5%. In contrast, the dose received by 98% of the primary and nodal gross tumour volumes decreased by 0.15% and 0.3%, respectively, when comparing the initial treatment plan to the comparison plan. In this study, treatment-induced anatomical changes had the greatest impact on OAR dose with negligible effect on the dose to nodal gross tumour volumes. In the era of IMRT, accounting for treatment-induced anatomical changes is important as focus is placed on minimizing the acute and long-term side effects of treatment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

A survey of radiographers' confidence and self-perceived accuracy in frontline image interpretation and their continuing educational preferences

The provision of a written comment on traumatic abnormalities of the musculoskeletal system detected by radiographers can assist referrers and may improve patient management, but the practice has not been widely adopted outside the United Kingdom. The purpose of this study was to investigate Australian radiographers' perceptions of their readiness for practice in a radiographer commenting system and their educational preferences in relation to two different delivery formats of image interpretation education, intensive and non-intensive. A cross-sectional web-based questionnaire was implemented between August and September 2012. Participants included radiographers with experience working in emergency settings at four Australian metropolitan hospitals. Conventional descriptive statistics, frequency histograms, and thematic analysis were undertaken. A Wilcoxon signed-rank test examined whether a difference in preference ratings between intensive and non-intensive education delivery was evident. The questionnaire was completed by 73 radiographers (68% response rate). Radiographers reported higher confidence and self-perceived accuracy to detect traumatic abnormalities than to describe traumatic abnormalities of the musculoskeletal system. Radiographers frequently reported high desirability ratings for both the intensive and the non-intensive education delivery, no difference in desirability ratings for these two formats was evident (z = 1.66, P = 0.11). Some Australian radiographers perceive they are not ready to practise in a frontline radiographer commenting system. Overall, radiographers indicated mixed preferences for image interpretation education delivered via intensive and non-intensive formats. Further research, preferably randomised trials, investigating the effectiveness of intensive and non-intensive education formats of image interpretation education for radiographers is warranted.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Dose planning objectives in anal canal cancer IMRT: the TROG ANROTAT experience

Intensity modulated radiotherapy (IMRT) is ideal for anal canal cancer (ACC), delivering high doses to irregular tumour volumes whilst minimising dose to surrounding normal tissues. Establishing achievable dose objectives is a challenge. The purpose of this paper was to utilise data collected in the Assessment of New Radiation Oncology Treatments and Technologies (ANROTAT) project to evaluate the feasibility of ACC IMRT dose planning objectives employed in the Australian situation. Ten Australian centres were randomly allocated three data sets from 15 non-identifiable computed tomography data sets representing a range of disease stages and gender. Each data set was planned by two different centres, producing 30 plans. All tumour and organ at risk (OAR) contours, prescription and dose constraint details were provided. Dose–volume histograms (DVHs) for each plan were analysed to evaluate the feasibility of dose planning objectives provided. All dose planning objectives for the bone marrow (BM) and femoral heads were achieved. Median planned doses exceeded one or more objectives for bowel, external genitalia and bladder. This reached statistical significance for bowel V30 (P = 0.04), V45 (P < 0.001), V50 (P < 0.001), external genitalia V20 (P < 0.001) and bladder V35 (P < 0.001), V40 (P = 0.01). Gender was found to be the only significant factor in the likelihood of achieving the bowel V50 (P = 0.03) and BM V30 constraints (P = 0.04). The dose planning objectives used in the ANROTAT project provide a good starting point for ACC IMRT planning. To facilitate clinical implementation, it is important to prioritise OAR objectives and recognise factors that affect the achievability of these objectives.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Modeling Hot Spot Experiments on Shocked Octahydro-1,3,5,7-Tetranitro-1,3,5,7-Tetrazocine

The cover picture shows a shock-induced reaction in a porous bed of octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX). Our study shows compaction, reaction, and gas jetting during the initial stages of shock in the powder bed. Shock reflection at the glass window interface increases hot spot temperatures in HMX product gas in excess of 7000 K at higher impact speeds which is readily observable using pyrometry techniques. We extract a temperature histogram from simulations at discrete times, using it to calculate an effective emission spectrum and effective temperature, T eff , for comparison to data. Calculating T eff based on Planck's Law with a gray body assumption demonstrates good agreement with hot spot temperature data. The agreement with experimental results validates our mesoscale simulations as useful tools for elucidating the role of hot spot mechanisms in the shock initiation of heterogeneous explosives. Finally, more details can be found in the Full Paper by Harry Springer, Will Bassett, Sorin Bastea, Svjetlana Stekovic, and Craig Tarver on page 330 ff.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Image Distinguishability Analysis Testing Through Principal Components and Its Application to Hot Spot Scale Invariance

Hot spots are spatial regions of intense energy localization that govern initiation of secondary high explosives. Studies that characterize or compare simulated hot spots are frequently either qualitatively descriptive or resort to quantitative distribution functions that neglect stochastic variations and spatial correlations—effects that are also neglected in common comparison tests like the Kolmogorov–Smirnov test. To this end, we develop an image distinguishability analysis (IDA) test based on principal component (PC) analysis that makes pixel-by-pixel comparisons between small, for example, O(<10), image data sets. The IDA test makes comparisons through a generalized distance metric in the PC space and a test statistic that is derived to calculate mathematical equation-values. Here, we derive a statistical distribution and criticality criterion to determine whether images are distinguishable from established baselines. We apply the IDA test on images generated from molecular dynamics simulations of hot spots from pore collapse in TATB to assess scale invariance in the complex patterns of hot spots that form in a representative high explosive crystal. The IDA test shows that TATB hot spot spatial temperature fields and their derived temperature histograms exhibit scale-invariant features over specific intervals of shock orientation, strength, and initial pore diameter. However, the IDA test also shows that qualitatively different conclusions regarding invariance can be reached depending on whether the hot spot is treated as a spatially correlated field as opposed to a distribution function that lacks spatial information.

organic↗
DOE OSTI2021

Parameter inference from event ensembles and the top-quark mass

One of the key tasks of any particle collider is measurement. In practice, this is often done by fitting data to a simulation, which depends on many parameters. Sometimes, when the effects of varying different parameters are highly correlated, a large ensemble of data may be needed to resolve parameter-space degeneracies. An important example is measuring the top-quark mass, where other physical and unphysical parameters in the simulation must be profiled when fitting the top-quark mass parameter. We compare four different methodologies for top-quark mass measurement: a classical histogram fit similar to one commonly used in experiment augmented by soft-drop jet grooming; a 2D profile likelihood fit with a nuisance parameter; a machine-learning method called DCTR; and a linear regression approach, either using a least-squares fit or with a dense linearly-activated neural network. Despite the fact that individual events are totally uncorrelated, we find that the linear regression methods work most effectively when we input an ensemble of events sorted by mass, rather than training them on individual events. Although all methods provide robust extraction of the top-quark mass parameter, the linear network does marginally best and is remarkably simple. For the top study, we conclude that the Monte-Carlo-based uncertainty on current extractions of the top-quark mass from LHC data can be reduced significantly (by perhaps a factor of 2) using networks trained on sorted event ensembles. More generally, machine learning from ensembles for parameter estimation has broad potential for collider physics measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Data-driven high-dimensional statistical inference with generative models

Crucial to many measurements at the LHC is the use of correlated multi-dimensional information to distinguish rare processes from large backgrounds, which is complicated by the poor modeling of many of the crucial backgrounds in Monte Carlo simulations. In this work, we introduce HI-SIGMA, a method to perform unbinned high-dimensional statistical inference with data-driven background distributions. In contradistinction to many applications of Simulation Based Inference in High Energy Physics, HI-SIGMA relies on generative ML models, rather than classifiers, to learn the signal and background distributions in the high-dimensional space. These ML models allow for interpretable inference while also incorporating model errors and other sources of systematic uncertainties. We showcase this methodology on a simplified version of a di-Higgs measurement in the bbγγ final state, where the di-photon resonance allows for background interpolation from sidebands into the signal region. We demonstrate that HI-SIGMA provides improved sensitivity as compared to standard classifier-based methods, and that systematic uncertainties can be straightforwardly incorporated by extending methods which have been used for histogram based analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

MR texture analysis: potential imaging biomarker for predicting the chemotherapeutic response of patients with colorectal liver metastases

Purpose: The purpose of the study was to determine whether the pre-treated MR texture features of colorectal liver metastases (CRLMs) are predictive of therapeutic response after chemotherapy. Methods: The study included twenty-six consecutive patients (a total of 193 liver metastasis) with unrespectable CRLMs at our institution from August 2014 to February 2016. Lesions were categorized into either responding group or non-responding group according to changes in size. Texture analysis was quantified on T2-weighted images by two radiologists with consensus on regions of interest which were manually drawn on the largest cross-sectional area of the lesions. Five histogram features (mean, variance, skewness, kurtosis, and entropy{sup 1}) and five gray level co-occurrence matrix features (GLCM; angular second moment (ASM), entropy{sup 2}, contrast, correlation, and inverse difference moment (IDM)) were extracted. The texture parameters were statistically analyzed to identify the differences between the two groups, and the potential predictive parameters to differentiate the responding group from the non-responding group were subsequently tested using multivariable logistic regression analysis. Results: A total of 107 responding and 86 non-responding lesions were evaluated. A higher variance, entropy{sup 1}, contrast, entropy{sup 2} and a lower ASM, correlation, IDM were independently (P < 0.05) associated with a good response to chemotherapy with the areas under the ROC curves (AUCs) of 0.602–0.784. Variance (P < 0.001) and ASM (P = 0.001) remained potential predictive values to discriminate responding lesions from non-responding lesions when tested using multivariable logistic regression analysis. The highest AUC of the predictors from the association of variance and ASM was 0.814. Conclusion: MR texture features on pre-treated T2 images have the potential to predict the therapeutic response of colorectal liver metastases.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Computed tomography-based texture analysis of bladder cancer: differentiating urothelial carcinoma from micropapillary carcinoma

Purpose: The purpose of the study is to determine the feasibility of using computed tomography-based texture analysis (CTTA) in differentiating between urothelial carcinomas (UC) of the bladder from micropapillary carcinomas (MPC) of the bladder. Methods: Regions of interests (ROIs) of computerized tomography (CT) images of 33 MPCs and 33 UCs were manually segmented and saved. Custom MATLAB code was used to extract voxel information corresponding to the ROI. The segmented tumors were input to a pre-existing radiomics platform with a CTTA panel. A total of 58 texture metrics were extracted using four different texture extraction techniques and statistically analyzed using a Wilcoxon rank-sum test to determine the differences between UCs and MPCs. Results: Of the 58 texture metrics extracted using the gray level co-occurrence matrix (GLCM) and gray level difference matrix (GLDM), 28 texture metrics were statistically significant (p < 0.05) for differences in tumor textures and 27 texture metrics were statistically significant (p < 0.05) for peritumoral fat textures. The remaining nine metrics extracted using histogram and fast Fourier transform analyses did not show significant differences between the textures of the tumors and their peritumoral fat. Conclusions: CTTA shows that MPC have a more heterogeneous texture compared to UC. As visual discrimination of MPC from UC from clinical CT scans are difficult, results from this study suggest that tumor heterogeneity extracted using GLCM and GLDM may be a good imaging aid in segregating MPC from UC. This tool can aid clinicians in further sub-classifying bladder cancers on routine imaging, a process which has potential to alter treatment and patient care.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Can MRI be used to diagnose histologic grade in T1a (< 4 cm) clear cell renal cell carcinomas?

Objective: To assess whether MRI can differentiate low-grade from high-grade T1a cc-RCC. Materials and methods: With IRB approval, 49 consecutive solid < 4 cm cc-RCC (low grade [Grade 1 or 2] N = 38, high grade [Grade 3] N = 11) with pre-operative MRI before nephrectomy were identified between 2013 and 2018. Tumor size, apparent diffusion coefficient (ADC) histogram analysis, enhancement wash-in and wash-out rates, and chemical shift signal intensity index (SI index) were assessed by a blinded radiologist. Subjectively, two blinded Radiologists also assessed for (1) microscopic fat, (2) homogeneity (5-point Likert scale), and (3) ADC signal (relative to renal cortex); discrepancies were resolved by consensus. Outcomes were studied using Chi square, multivariate analysis, logistic regression modeling, and ROC. Inter-observer agreement was assessed using Cohen’s kappa. Results: Tumor size was 24 ± 7 (13–39) mm with no association to grade (p = 0.45). Among quantitative features studied, corticomedullary phase wash-in index (p = 0.015), SI index (p = 0.137), and tenth-centile ADC (p = 0.049) were higher in low-grade tumors. 36.8% (14/38) low-grade tumors versus zero high-grade tumors demonstrated microscopic fat (p = 0.015; Kappa = 0.67). Microscopic fat was specific for low-grade disease (100.0% [71.5–100.0]) with low sensitivity (36.8% [21.8–54.6]). Other subjective features did not differ between groups (p > 0.05). A logistic regression model combining microscopic fat + wash-in index + tenth-centile-ADC yielded area under ROC curve 0.98 (Confidence Intervals 0.94–1.0) with sensitivity/specificity 87.5%/100%. Conclusion: The combination of microscopic fat, higher corticomedullary phase wash-in and higher tenth-centile ADC is highly accurate for diagnosis of low-grade disease among T1a clear cell RCC.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Texture analysis of placental MRI: can it aid in the prenatal diagnosis of placenta accreta spectrum?

Purpose: To determine if texture analysis can differentiate placenta accreta spectrum (PAS) from normal placenta on MRI. Methods: We performed retrospective image analysis of 80 patients, comprised of 46 patients with PAS and 34 patients without PAS. Histopathology was used as the reference standard. Sagittal single shot fast spin echo T2-weighted MRI sequences acquired from a single institution were analyzed. Placental heterogeneity was quantified using in-house software on a Matlab platform, including the standard deviation of pixel intensity, coefficient of variation, gray-level co-occurrence matrices (GLCM), histogram-oriented gradients (HOG), and fractal analysis with box sizes from 2 to 512. Two-tailed unpaired Student’s t test was used with statistical significance of p < 0.05. Results: PAS was associated with higher values for standard deviation of pixel intensity and fractal analysis at every box size. Fractal analysis at box sizes 256 (p = 0.011) and 32 (p = 0.021), and standard deviation of pixel intensity (p = 0.023) were the most statistically significant. Fractal values at box size 256 for PAS was 0.13 versus 0.090 for patients without PAS, while standard deviation of pixel intensity was 3.7 for PAS versus 2.5 for patients without PAS. No statistically significant association between PAS and GLCM, coefficient of variation, and HOG was found. Conclusion: Statistically significant differences were found between normal and abnormal groups using standard deviation of pixel intensity and fractal analysis.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

PET/MRI of Hepatic 90Y Microsphere Deposition Determines Individual Tumor Response

PurposeThe purpose of our study is to determine if there is a relationship between dose deposition measured by PET/MRI and individual lesion response to yttrium-90 ({sup 90}Y) microsphere radioembolization.Materials and Methods26 patients undergoing lobar treatment with {sup 90}Y microspheres underwent PET/MRI within 66 h of treatment and had follow-up imaging available. Adequate visualization of tumor was available in 24 patients, and contours were drawn on simultaneously acquired PET/MRI data. Dose volume histograms (DVHs) were extracted from dose maps, which were generated using a voxelized dose kernel. Similar contours to capture dimensional and volumetric change of tumors were drawn on follow-up imaging. Response was analyzed using both RECIST and volumetric RECIST (vRECIST) criteria.ResultsA total of 8 hepatocellular carcinoma (HCC), 4 neuroendocrine tumor (NET), 9 colorectal metastases (CRC) patients, and 3 patients with other metastatic disease met inclusion criteria. Average dose was useful in predicting response between responders and non-responders for all lesion types and for CRC lesions alone using both response criteria (p < 0.05). D70 (minimum dose to 70 % of volume) was also useful in predicting response when using vRECIST. No significant trend was seen in the other tumor types. For CRC lesions, an average dose of 29.8 Gy offered 76.9 % sensitivity and 75.9 % specificity for response.ConclusionsPET/MRI of {sup 90}Y microsphere distribution showed significantly higher DVH values for responders than non-responders in patients with CRC. DVH analysis of {sup 90}Y microsphere distribution following treatment may be an important predictor of response and could be used to guide future adaptive therapy trials.

62 RADIOLOGY AND NUCLEAR MEDICINE↗