Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Models, Anatomic”

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 145 records · Page 8

SU-E-T-559: Monte Carlo Simulation of Cobalt-60 Teletherapy Unit Modeling In-Field and Out-Of-Field Doses for Applications in Computational Radiation Dosimetry

Purpose: Mean organ doses from structures located in field and outside of field boundaries during radiotherapy treatment must be considered when looking at secondary effects. Treatment planning in patients with 40 years of follow-up does not include 3-D treatment planning images and did not estimate dose to structures out of the direct field. Therefore, it is of interest to correlate actual clinical events with doses received. Methods: Accurate models of radiotherapy machines combined with whole body computational phantoms using Monte Carlo methods allow for dose reconstructions intended for studies on late radiation effects. The Theratron-780 radiotherapy unit and anatomically realistic hybrid computational phantoms are modeled in the Monte Carlo radiation transport code MCNPX. The major components of the machine including the source capsule, lead in the unit-head, collimators (fixed/adjustable), and trimmer bars are simulated. The MCNPX transport code is used to compare calculated values in a water phantom with published data from BJR suppl. 25 for in-field doses and experimental data from AAPM Task Group No. 36 for out-of-field doses. Next, the validated cobalt-60 teletherapy model is combined with the UF/NCI Family of Reference Hybrid Computational Phantoms as a methodology for estimating organ doses. Results: The model of Theratron-780 has shown to be agree with percentage depth dose data within approximately 1% and for out of field doses the machine is shown to agree within 8.8%. Organ doses are reported for reference hybrid phantoms. Conclusion: Combining the UF/NCI Family of Reference Hybrid Computational Phantoms along with a validated model of the Theratron-780 allows for organ dose estimates of both in-field and out-of-field organs. By changing field size, position, and adding patient-specific blocking more complicated treatment set-ups can be recreated for patients treated historically, particularly those who lack both 2D/3D image sets.

61 RADIATION PROTECTION AND DOSIMETRY↗

Automatic segmentation of head and neck CT images for radiotherapy treatment planning using multiple atlases, statistical appearance models, and geodesic active contours

Purpose: Accurate delineation of organs at risk (OARs) is a precondition for intensity modulated radiation therapy. However, manual delineation of OARs is time consuming and prone to high interobserver variability. Because of image artifacts and low image contrast between different structures, however, the number of available approaches for autosegmentation of structures in the head-neck area is still rather low. In this project, a new approach for automated segmentation of head-neck CT images that combine the robustness of multiatlas-based segmentation with the flexibility of geodesic active contours and the prior knowledge provided by statistical appearance models is presented. Methods: The presented approach is using an atlas-based segmentation approach in combination with label fusion in order to initialize a segmentation pipeline that is based on using statistical appearance models and geodesic active contours. An anatomically correct approximation of the segmentation result provided by atlas-based segmentation acts as a starting point for an iterative refinement of this approximation. The final segmentation result is based on using model to image registration and geodesic active contours, which are mutually influencing each other. Results: 18 CT images in combination with manually segmented labels of parotid glands and brainstem were used in a leave-one-out cross validation scheme in order to evaluate the presented approach. For this purpose, 50 different statistical appearance models have been created and used for segmentation. Dice coefficient (DC), mean absolute distance and max. Hausdorff distance between the autosegmentation results and expert segmentations were calculated. An average Dice coefficient of DC = 0.81 (right parotid gland), DC = 0.84 (left parotid gland), and DC = 0.86 (brainstem) could be achieved. Conclusions: The presented framework provides accurate segmentation results for three important structures in the head neck area. Compared to a segmentation approach based on using multiple atlases in combination with label fusion, the proposed hybrid approach provided more accurate results within a clinically acceptable amount of time.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

A 3D Computational Head Model Under Dynamic Head Rotation and Head Extension Validated Using Live Human Brain Data, Including the Falx and the Tentorium

We employ an advanced 3D computational model of the head with high anatomical fidelity, together with measured tissue properties, to assess the consequences of dynamic loading to the head in two distinct modes: head rotation and head extension. We use a subject-specific computational head model, using the material point method, built from T1 magnetic resonance images, and considering the anisotropic properties of the white matter which can predict strains in the brain under large rotational accelerations. The material model now includes the shear anisotropy of the white matter. We validate the model under head rotation and head extension motions using live human data, and advance a prior version of the model to include biofidelic falx and tentorium. Furthermore we then examine the consequences of incorporating the falx and tentorium in terms of the predictions from the computational head model.

61 RADIATION PROTECTION AND DOSIMETRY↗

An age- and sex-specific biokinetic model for radon *

Publication 137 of the International Commission on Radiological Protection (ICRP) describes a biokinetic model for radon used to derive dose coefficients for occupational intake of radon isotopes. The model depicts transfer of inhaled or ingested radon to blood, exchange of radon between blood and tissues, and gradual loss of radon from the body based on physical laws governing transfer of a non-reactive and soluble gas between materials. Here, this paper describes an age- and sex-specific variation of that model developed for use in an upcoming ICRP series of reports on environmental intake of radionuclides by members of the public titled ‘Dose Coefficients for Intakes of Radionuclides by Members of the Public’. The proposed model modifies the model structure and transfer coefficients presented in Publication 137 to allow more realistic dosimetric treatment of bone marrow and breast and expands the model to address pre-adult ages, based on the physical principles used in the development of the model of Publication 137 together with anatomical and physiological changes occurring during human development.

61 RADIATION PROTECTION AND DOSIMETRY↗

Hydraulic conductance, resistance, and resilience: how leaves of a tropical epiphyte respond to drought

Premise Because of its broad range in the neotropical rainforest and within tree canopies, the tank bromeliad Guzmania monostachia was investigated as a model of how varying leaf hydraulic conductance ( K leaf ) could help plants resist and recover from episodic drought. The two pathways of K leaf , inside and outside the xylem, were also examined to determine the sites and causes of major hydraulic resistances within the leaf. Methods We measured leaf hydraulic conductance for plants in the field and laboratory under wet, dry, and rewetted conditions and applied physiological, anatomical, and gene expression analysis with modeling to investigate changes in K leaf . Results After 7 d with no rain in the field or 14 days with no water in the glasshouse, K leaf decreased by 50% yet increased to hydrated values within 4 d of tank refilling. Staining to detect embolism combined with modeling indicated that changes outside the xylem were of greater importance to K leaf than were changes inside the xylem and were associated with changes in intercellular air spaces (aerenchyma), aquaporin expression and inhibition, and cuticular conductance. Conclusions Low values for all conductances during drying, particularly in pathways outside the xylem, lead to hydraulic resilience for this species and may also contribute to its broad environmental tolerances.

North, Gretchen B.↗

Mechanical separations of corn stover anatomical fractions in an integrated feedstock preprocessing system: An experimental and data-driven modeling study

High variabilities of material attributes in lignocellulosic biomass present risks for biofuel and biochemical productions and must be mitigated via preprocessing. Since almost no mechanical device is originally designed for processing biomass, how to operate existing apparatuses with efficient performance has not been investigated extensively. This work presents a study on an integrated screening and air classification to separate cobs and stalks from husks and leaves in corn stover. Prototype machine learning models were developed to assess the feasibility of predicting the process outcome based on the measurable parameters. The models trained upon limited experimental data rendered decent predictive accuracy of yield and purity. The experimental data and modeling results collectively suggest decreasing throughput leads to a higher purity. To the contrary, if throughput increases, a lower purity is likely. A possible trade-off between yield and purity of the separated streams indicates the need for optimal combinations of feedstock size, moisture, and throughput to achieve optimized separations. The results of this study also suggest the need to further improve model predictability by developing more accurate formulations for physics governing the integrated unit operations. To accomplish this, additional experimental data needs to be generated for model training.

09 - BIOMASS FUELS↗

Adaptive optical third-harmonic generation microscopy for in vivo imaging of tissues

Third-harmonic generation microscopy is a powerful label-free nonlinear imaging technique, providing essential information about structural characteristics of cells and tissues without requiring external labelling agents. In this work, we integrated a recently developed compact adaptive optics module into a third-harmonic generation microscope, to measure and correct for optical aberrations in complex tissues. Taking advantage of the high sensitivity of the third-harmonic generation process to material interfaces and thin membranes, along with the 1,300-nm excitation wavelength used here, our adaptive optical third-harmonic generation microscope enabled high-resolution in vivo imaging within highly scattering biological model systems. Examples include imaging of myelinated axons and vascular structures within the mouse spinal cord and deep cortical layers of the mouse brain, along with imaging of key anatomical features in the roots of the model plant Brachypodium distachyon. In all instances, aberration correction led to enhancements in image quality.

60 APPLIED LIFE SCIENCES↗

A deformable head and neck phantom with in-vivo dosimetry for adaptive radiotherapy quality assurance

Purpose: Patients’ interfractional anatomic changes can compromise the initial treatment plan quality. To overcome this issue, adaptive radiotherapy (ART) has been introduced. Deformable image registration (DIR) is an important tool for ART and several deformable phantoms have been built to evaluate the algorithms’ accuracy. However, there is a lack of deformable phantoms that can also provide dosimetric information to verify the accuracy of the whole ART process. The goal of this work is to design and construct a deformable head and neck (HN) ART quality assurance (QA) phantom with in vivo dosimetry. Methods: An axial slice of a HN patient is taken as a model for the phantom construction. Six anatomic materials are considered, with HU numbers similar to a real patient. A filled balloon inside the phantom tissue is inserted to simulate tumor. Deflation of the balloon simulates tumor shrinkage. Nonradiopaque surface markers, which do not influence DIR algorithms, provide the deformation ground truth. Fixed and movable holders are built in the phantom to hold a diode for dosimetric measurements. Results: The measured deformations at the surface marker positions can be compared with deformations calculated by a DIR algorithm to evaluate its accuracy. In this study, the authors selected a Demons algorithm as a DIR algorithm example for demonstration purposes. The average error magnitude is 2.1 mm. The point dose measurements from the in vivo diode dosimeters show a good agreement with the calculated doses from the treatment planning system with a maximum difference of 3.1% of prescription dose, when the treatment plans are delivered to the phantom with original or deformed geometry. Conclusions: In this study, the authors have presented the functionality of this deformable HN phantom for testing the accuracy of DIR algorithms and verifying the ART dosimetric accuracy. The authors’ experiments demonstrate the feasibility of this phantom serving as an end-to-end ART QA phantom.

60 APPLIED LIFE SCIENCES↗

SU-G-IeP2-08: Investigation On Signal Detectability in Volumetric Cone Beam CT Images with Anatomical Background

Purpose: To investigate the slice direction dependent detectability in cone beam CT images with anatomical background. Methods: We generated 3D anatomical background images using breast anatomy model. To generate 3D breast anatomy, we filtered 3D Gaussian noise with a square root of 1/f{sup 3}, and then assigned the attenuation coefficient of glandular (0.8cm{sup −1}) and adipose (0.46 cm{sup −1}) tissues based on voxel values. Projections were acquired by forward projection, and quantum noise was added to the projection data. The projection data were reconstructed by FDK algorithm. We compared the detectability of a 3 mm spherical signal in the image reconstructed from four different backprojection Methods: Hanning weighted ramp filter with linear interpolation (RECON1), Hanning weighted ramp filter with Fourier interpolation (RECON2), ramp filter with linear interpolation (RECON3), and ramp filter with Fourier interpolation (RECON4), respectively. We computed task SNR of the spherical signal in transverse and longitudinal planes using channelized Hotelling observer with Laguerre-Gauss channels. Results: Transverse plane has similar task SNR values for different backprojection methods, while longitudinal plane has a maximum task SNR value in RECON1. For all backprojection methods, longitudinal plane has higher task SNR than transverse plane. Conclusion: In this work, we investigated detectability for different slice direction in cone beam CT images with anatomical background. Longitudinal plane has a higher task SNR than transverse plane, and backprojection with hanning weighted ramp filter with linear interpolation method (i.e., RECON1) produced the highest task SNR among four different backprojection methods. This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the IT Consilience Creative Programs(IITP-2015-R0346-15-1008) supervised by the IITP (Institute for Information & Communications Technology Promotion), Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the MSIP (2015R1C1A1A01052268) and framework of international cooperation program managed by NRF (NRF-2015K2A1A2067635).

60 APPLIED LIFE SCIENCES↗

SU-G-BRA-07: An Innovative Fiducial-Less Tracking Method for Radiation Treatment of Abdominal Tumors by Diaphragm Disparity Analysis

Purpose: To investigate the feasibility of tracking abdominal tumors without the use of gold fiducial markers Methods: In this simulation study, an abdominal 4DCT dataset, acquired previously and containing 8 phases of the breathing cycle, was used as the testing data. Two sets of DRR images (45 and 135 degrees) were generated for each phase. Three anatomical points along the lung-diaphragm interface on each of the Digital Reconstructed Radiograph(DRR) images were identified by cross-correlation. The gallbladder, which simulates the tumor, was contoured for each phase of the breathing cycle and the corresponding centroid values serve as the measured center of the tumor. A linear model was created to correlate the diaphragm’s disparity of the three identified anatomical points with the center of the tumor. To verify the established linear model, we sequentially removed one phase of the data (i.e., 3 anatomical points and the corresponding tumor center) and created new linear models with the remaining 7 phases. Then we substituted the eliminated phase data (disparities of the 3 anatomical points) into the corresponding model to compare model-generated tumor center and the measured tumor center. Results: The maximum difference between the modeled and the measured centroid values across the 8 phases were 0.72, 0.29 and 0.30 pixels in the x, y and z directions respectively, which yielded a maximum mean-squared-error value of 0.75 pixels. The outcomes of the verification process, by eliminating each phase, produced mean-squared-errors ranging from 0.41 to 1.28 pixels. Conclusion: Gold fiducial markers, requiring surgical procedures to be implanted, are conventionally used in radiation therapy. The present work shows the feasibility of a fiducial-less tracking method for localizing abdominal tumors. Through developed diaphragm disparity analysis, the established linear model was verified with clinically accepted errors. The tracking method in real time under different radiation therapy platforms will be further investigated.

60 APPLIED LIFE SCIENCES↗

Image Segmentation for Connectomics Using Machine Learning

Reconstruction of neural circuits at the microscopic scale of individual neurons and synapses, also known as connectomics, is an important challenge for neuroscience. While an important motivation of connectomics is providing anatomical ground truth for neural circuit models, the ability to decipher neural wiring maps at the individual cell level is also important in studies of many neurodegenerative diseases. Reconstruction of a neural circuit at the individual neuron level requires the use of electron microscopy images due to their extremely high resolution. Computational challenges include pixel-by-pixel annotation of these images into classes such as cell membrane, mitochondria and synaptic vesicles and the segmentation of individual neurons. State-of-the-art image analysis solutions are still far from the accuracy and robustness of human vision and biologists are still limited to studying small neural circuits using mostly manual analysis. In this chapter, we describe our image analysis pipeline that makes use of novel supervised machine learning techniques to tackle this problem.

connectomics↗

Phase V of the single-breath washout test

A downward-deflecting phase V is often seen following the terminal rise (phase IV) in single-breath washout tests. To investigate the nature of phase V, experiments using simultaneous washouts of N2 and tracer boluses of Ar were performed on eight normal nonsmoking subjects aged 27-41 who exhibited a phase V. Phase V is found to occur in all subjects at expiratory flow rates between 0.1 and 2.0 l/sec shortly after expiration became flow limited. Volumes of both phases IV and V increase with increasing flow rate. The difference between the exhaled volumes at which flow became limited and phase V appeared is shown to be approximately equal to the anatomic dead space. Results support a model of lung emptying in a gravitational field in which flow limitation occurs first in the lower lung regions and then progresses toward the upper regions, causing phase IV. A decrease in the amount of flow from the upper relative to the lower regions after all regions have become flow limited then causes phase V.

Nichol, G. M.↗

SU-F-R-14: PET Based Radiomics to Predict Outcomes in Patients with Hodgkin Lymphoma

Purpose: To identify PET-based radiomics features associated with high refractory/relapsed disease risk for Hodgkin lymphoma patients. Methods: A total of 251 Hodgkin lymphoma patients including 19 primary refractory and 9 relapsed patients were investigated. All patients underwent an initial pre-treatment diagnostic FDG PET/CT scan. All cancerous lymph node regions (ROIs) were delineated by an experienced physician based on thresholding each volume of disease in the anatomical regions to SUV>2.5. We extracted 122 image features and evaluated the effect of ROI selection (the largest ROI, the ROI with highest mean SUV, merged ROI, and a single anatomic region [e.g. mediastinum]) on classification accuracy. Random forest was used as a classifier and ROC analysis was used to assess the relationship between selected features and patient’s outcome status. Results: Each patient had between 1 and 9 separate ROIs, with much intra-patient variability in PET features. The best model, which used features from a single anatomic region (the mediastinal ROI, only volumes>5cc: 169 patients with 12 primary refractory) had a classification accuracy of 80.5% for primary refractory disease. The top five features, based on Gini index, consist of shape features (max 3D-diameter and volume) and texture features (correlation and information measure of correlation1&2). In the ROC analysis, sensitivity and specificity of the best model were 0.92 and 0.80, respectively. The area under the ROC (AUC) and the accuracy were 0.86 and 0.86, respectively. The classification accuracy was less than 60% for other ROI models or when ROIs less than 5cc were included. Conclusion: This study showed that PET-based radiomics features from the mediastinal lymph region are associated with primary refractory disease and therefore may play an important role in predicting outcomes in Hodgkin lymphoma patients. These features could be additive beyond baseline tumor and clinical characteristics, and may warrant more aggressive treatment.

60 APPLIED LIFE SCIENCES↗

Vector-model-supported optimization in volumetric-modulated arc stereotactic radiotherapy planning for brain metastasis

Long planning time in volumetric-modulated arc stereotactic radiotherapy (VMA-SRT) cases can limit its clinical efficiency and use. A vector model could retrieve previously successful radiotherapy cases that share various common anatomic features with the current case. The prsent study aimed to develop a vector model that could reduce planning time by applying the optimization parameters from those retrieved reference cases. Thirty-six VMA-SRT cases of brain metastasis (gender, male [n = 23], female [n = 13]; age range, 32 to 81 years old) were collected and used as a reference database. Another 10 VMA-SRT cases were planned with both conventional optimization and vector-model-supported optimization, following the oncologists' clinical dose prescriptions. Planning time and plan quality measures were compared using the 2-sided paired Wilcoxon signed rank test with a significance level of 0.05, with positive false discovery rate (pFDR) of less than 0.05. With vector-model-supported optimization, there was a significant reduction in the median planning time, a 40% reduction from 3.7 to 2.2 hours (p = 0.002, pFDR = 0.032), and for the number of iterations, a 30% reduction from 8.5 to 6.0 (p = 0.006, pFDR = 0.047). The quality of plans from both approaches was comparable. From these preliminary results, vector-model-supported optimization can expedite the optimization of VMA-SRT for brain metastasis while maintaining plan quality.

61 RADIATION PROTECTION AND DOSIMETRY↗

The muscle spindle as a feedback element in muscle control

The muscle spindle, the feedback element in the myotatic (stretch) reflex, is a major contributor to muscular control. Therefore, an accurate description of behavior of the muscle spindle during active contraction of the muscle, as well as during passive stretch, is essential to the understanding of muscle control. Animal experiments were performed in order to obtain the data necessary to model the muscle spindle. Spectral density functions were used to identify a linear approximation of the two types of nerve endings from the spindle. A model reference adaptive control system was used on a hybrid computer to optimize the anatomically defined lumped parameter estimate of the spindle. The derived nonlinear model accurately predicts the behavior of the muscle spindle both during active discharge and during its silent period. This model is used to determine the mechanism employed to control muscle movement.

Andrews, L. T.↗

Creation of an atlas of filter positions for fluence field modulated CT

Purpose: Fluence field modulated CT (FFMCT) and volume of interest (VOI) CT imaging applications require adjustment of the profile of the x-ray fluence incident on a patient as a function of view angle. Since current FFMCT prototypes can theoretically take on an infinite number of configurations, measuring a calibration data set for all possible positions would not be feasible. The present work details a methodology for calculating an atlas of configurations that will span all likely body regions, patient sizes, patient positioning, and imaging modes. The hypothesis is that there exists a finite number of unique modulator configurations that effectively span the infinite number of possible fluence profiles with minimal loss in performance. Methods: CT images of a head, shoulder, thorax, abdominal, wrist, and leg anatomical slices were dilated and contracted to model small, medium, and large sized patients. Additionally, the images were positioned from iso-center by three different amounts. The modulator configurations required to compensate for each image were computed assuming a FFMCT prototype, digital beam attenuator, (DBA), was set to equalize the detector exposure. Each atlas configuration should be different from the other atlas configurations. The degree of difference was quantified using the sum of the absolute differences in filter thickness between configurations. Using this metric, a set of unique wedge configurations for which no two configurations have a metric value smaller than some threshold can be constructed. Differences in the total number of incident photons between the unconstrained filters and the atlas were studied as a function of the number of atlas positions for each anatomical site and size/off-centering combination. Results: By varying the threshold used in creating the atlas, it was found that roughly 322 atlas positions provided an incident number of photons within 20% of using 19 440 unique filters (the number of atlas entries ranged from 7213 to 1). Additionally, for VOI applications implemented with a single VOI region, the number of required filter configurations was expressed in a simple closed form solution. Conclusions: The methodology proposed in this work will enable DBA-FFMCT and DBA-VOI imaging in the clinic without the need for patient specific air-scans to be performed. In addition, the methodology proposed here is directly applicable to other modulator designs such as piecewise linear, TomoTherapy multi leaf collimators, 2D fluid arrays, and inverse geometry CT.

60 APPLIED LIFE SCIENCES↗

Techno-Economic Case Study: Low-Temperature Conversion Performance Based on Isolated Anatomical Fractions of Corn Stover

This report summarizes analysis conducted to support a case study under the Feedstock-Conversion Interface Consortium (FCIC) focused on techno-economic analysis (TEA) modeling to quantify the yield and cost ramifications for processing isolated anatomical fractions of corn stover through a low-temperature conversion (biochemical pathway) biorefinery. It is hypothesized that different individual anatomical fractions of corn stover vary in composition and recalcitrance, such that processing each fraction on its own e.g. through dedicated campaigns may enable economic benefits relative to processing the whole stover material. To investigate this concept, we worked with FCIC researchers to obtain data on compositional analysis, as well as processing conditions and yields, for conversion of whole corn stover plus three individual anatomical fractions (cobs, husks, and stalks) across key steps of the biorefinery conversion process within FCIC research scope, namely pretreatment and enzymatic hydrolysis. After running the data through the TEA models, fractionated cobs and husks achieved higher fuel yields and lower minimum fuel selling prices than whole corn stover, but stalks fared worse than whole stover on both metrics. The most direct takeaway from this assessment is that a biorefinery would stand to benefit economically from maximizing the use of cob and husk fractions while avoiding or minimizing the use of stalks, though recognizing practical constraints with this approach in maintaining an equivalent processing capacity (fixed at 2,000 dry metric tonne per day in all cases).

09 BIOMASS FUELS↗

Using root and soil traits to forecast woody encroachment dynamics in mesic grassland

Grasslands are a widespread and globally important biome providing key ecosystem services including C storage and regulation of the water cycle. Grasslands face multiple threats, including changes in drought intensity and woody encroachment - a process that results in increased woody plant abundance corresponding with decreased herbaceous plant abundance. The combination of reduced soil moisture and shifts in plant dominance from herbaceous to woody are likely to alter C pools in the soil profile. We currently do not have the capacity to predict either the magnitude or rates of change in these C pools. In order to predict changes in grassland vegetation structure and the associated impacts on C cycling requires greater understanding of changes in soil C pools at multiple soil depths, and the responses of these pools to changes in precipitation. To support and perform this parameterization of Land Surface Models, we performed detailed investigations of root (anatomical and physiological) and soil traits (microbial function) at varying soil depths, to capture the belowground impacts of changing dominant plant growth forms (grasses to shrubs) and the impacts of frequent drought.

54 ENVIRONMENTAL SCIENCES↗