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Purpose: The aim of this study was to report data from the first 3 years of operation of the RSNA-ACR 3D Printing Registry., Methods: Data from June 2020 to June 2023 were extracted, including demographics, indications, workflow, and user assessments. Clinical indications were stratified by 12 organ systems. Imaging modalities, printing technologies, and numbers of parts per case were assessed. Effort data were analyzed, dividing staff members into provider and nonprovider categories. The opinions of clinical users were evaluated using a Likert scale questionnaire, and estimates of procedure time saved were collected., Results: A total of 20 sites and 2,637 cases were included, consisting of 1,863 anatomic models and 774 anatomic guides. Mean patient ages for models and guides were 42.4 ± 24.5 years and 56.3 ± 18.5 years, respectively. Cardiac models were the most common type of model (27.2%), and neurologic guides were the most common type of guide (42.4%). Material jetting, vat photopolymerization, and material extrusion were the most common printing technologies used overall (85.6% of all cases). On average, providers spent 92.4 min and nonproviders spent 335.0 min per case. Providers spent most time on consultation (33.6 min), while nonproviders focused most on segmentation (148.0 min). Confidence in treatment plans increased after using 3-D printing (P < .001). Estimated procedure time savings for 155 cases was 40.5 ± 26.1 min., Conclusions: Three-dimensional printing is performed at health care facilities for many clinical indications. The registry provides insight into the technologies and workflows used to create anatomic models and guides, and the data show clinical benefits from 3-D printing., (Published by Elsevier Inc.)

Cardiac fluid dynamics fundamentally involves interactions between complex blood flows and the structural deformations of the muscular heart walls and the thin valve leaflets. There has been longstanding scientific, engineering, and medical interest in creating mathematical models of the heart that capture, explain, and predict these fluid-structure interactions (FSIs). However, existing computational models that account for interactions among the blood, the actively contracting myocardium, and the valves are limited in their abilities to predict valve performance, capture fine-scale flow features, or use realistic descriptions of tissue biomechanics. Here we introduce and benchmark a comprehensive mathematical model of cardiac FSI in the human heart. A unique feature of our model is that it incorporates biomechanically detailed descriptions of all major cardiac structures that are calibrated using tensile tests of human tissue specimens to reflect the heart's microstructure. Further, it is the first FSI model of the heart that provides anatomically and physiologically detailed representations of all four cardiac valves. We demonstrate that this integrative model generates physiologic dynamics, including realistic pressure-volume loops that automatically capture isovolumetric contraction and relaxation, and that its responses to changes in loading conditions are consistent with the Frank-Starling mechanism. These complex relationships emerge intrinsically from interactions within our comprehensive description of cardiac physiology. Such models can serve as tools for predicting the impacts of medical interventions. They also can provide platforms for mechanistic studies of cardiac pathophysiology and dysfunction, including congenital defects, cardiomyopathies, and heart failure, that are difficult or impossible to perform in patients., (© The Author(s) 2024. Published by Oxford University Press on behalf of National Academy of Sciences.)

Competing Interests: The authors reported no conflicts of interest. The Journal policy requires editors and reviewers to disclose conflicts of interest and to decline handling manuscripts for which they may have a conflict of interest. The editors and reviewers of this article have no conflicts of interest.

Objective: A new visualization and recording method used to assess and quantitate autogenic high-velocity motions in myocardial walls to provide a new description of cardiac function is described., Methods: The regional motion display (RMD) is based on high-speed difference ultrasound B-mode images and spatiotemporal processing to record propagating events (PEs). Sixteen normal participants and one patient with cardiac amyloidosis were imaged at rates of 500-1000/s using the Duke Phased Array Scanner, T5. RMDs were generated using difference images and spatially integrating these to display velocity as function of time along a cardiac wall., Results: In normal participants, RMDs revealed four discrete PEs with average onset timing with respect to the QRS complex of -31.7, +46, +365 and +536 ms. The late diastolic PE propagated apex to base in all participants at an average velocity of 3.4 m/s by the RMD. The RMD of the amyloidosis patient revealed significant changes in the appearance of PEs compared with normal participants. The late diastolic PE propagated at 5.3 m/s from apex to base. All four PEs lagged the average timing of normal participants., Conclusion: The RMD method reliably reveals PEs as discrete events and successfully allows reproducible measurement of PE timing and the velocity of at least one PE. The RMD method is applicable to live, clinical high-speed studies and may offer a new approach to characterization of cardiac function., Competing Interests: Conflict of interest O.T.v.R. is the Chief Technology Officer of Volumetrics Medical Systems. The remaining authors declare no competing interests., (Copyright © 2023 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.)

The double switch operation for congenitally corrected transposition of the great arteries (CC-TGA) has been associated with high rates of reintervention, including the need for pulmonary valve replacement. Hybrid interventional approaches can avoid bypass when complex anatomy complicates traditional catheter-based approaches. We present a case of successful transcatheter pulmonary valve replacement via hybrid per-ventricular approach with pre-procedural planning aided by 3D segmentation of skeletal and cardiac anatomy in a patient with surgically corrected CC-GTA.

We investigated PET image quantification when using a uniform attenuation coefficient ( μ ) for attenuation correction (AC) of anthropomorphic density phantoms derived from high-resolution breast CT scans. A breast PET system was modeled with perfect data corrections except for AC. Using uniform μ for AC resulted in quantitative errors roughly proportional to the difference between μ used in AC ( μ AC ) and local μ , yielding approximately ± 5% bias, corresponding to the variation of μ for 511 keV photons in breast tissue. Global bias was lowest when uniform μ AC was equal to the phantom mean μ ( μ mean ). Local bias in 10-mm spheres increased as the sphere μ deviated from μ mean , but remained only 2-3% when the μ sphere was 6.5% higher than μ mean . Bias varied linearly with and was roughly proportional to local μ mismatch. Minimizing local bias, e.g., in a small sphere, required the use of a uniform μ value between the local μ and the μ mean . Thus, biases from using uniform- μ AC are low when local μ sphere is close to μ mean . As the μ sphere increasingly differs from the phantom μ mean , bias increases, and the optimal uniform μ is less predictable, having a value between μ sphere and the phantom μ mean .

Objectives: Describe the use of three-dimensional (3D) patent ductus arteriosus (PDA) modeling to better define ductal anatomy to improve preprocedural planning for ductal stent placement., Background: Ductal stenting is an alternative to surgical shunting in patients with ductal dependent pulmonary blood flow. Ductal anatomy is often complex with extreme tortuosity and risk of pulmonary artery isolation, thus increasing procedural risks., Methods: CT angiograms were segmented to produce 3D PDA models. Ductal morphology was characterized with attention to access approach, degree of pulmonary artery offset/risk of isolation and ductal tortuosity. 3D models were retrospectively compared with biplane angiography., Results: 3D modeling was performed in 12 patients with adequate image quality for complete analysis in 11; median (interquartile range) age/weight 17 days (8-20 days) and 3.1 kg (2.4-3.9 kg). The PDA was reverse oriented in nine with average length of 17.2 ± 2.5 mm and high tortuosity (mean tortuosity index 52, range 3-108). From 3D modeling, two patients were excluded from ductal stenting-extreme ductal tortuosity and threatened pulmonary artery discontinuity, respectively. Ductal stenting was successful in the remaining nine with no major procedural complications. 3D modeling predicted a successful access approach based on the aortic orientation of the ductus in all patients (five carotid, two axillary, two femoral). When comparing 2D angiography with 3D models, angiography consistently underestimated ductal length (-3.2 mm ± 1.6 mm) and tortuosity (-14.8 ± 7.2)., Conclusions: 3D modeling prior to ductal stent placement for ductal dependent pulmonary blood flow is useful in procedural planning, specifically for eligibility, access approach, and accurate ductal measurements. Further studies are needed to determine if 3D planning improves procedural outcomes., (© 2019 Wiley Periodicals, Inc.)

The purpose of this study was to develop detailed and realistic models of the cortical and trabecular bones in the spine, ribs, and sternum and incorporate them into the library of virtual human phantoms (XCAT). Cortical bone was modeled by 3D morphological erosion of XCAT homogenously defined bones with an average thickness measured from the CT dataset upon which each individual XCAT phantom was based. The trabecular texture was modeled using a power law synthesis algorithm where the parameters were tuned using high-resolution anatomical images of the Human Visible Female. The synthesized bone textures were added into the XCAT phantoms. To qualitatively evaluate the improved realism of the bone modeling, CT simulations of the XCAT phantoms were acquired with and without the textured bone modeling. The 3D power spectrum of the anatomical images exhibited a power law behavior (R 2 = 0.84), as expected in fractal and porous textures. The proposed texture synthesis algorithm was able to synthesize textures emulating real anatomical images, with the simulated CT images with the prototyped bones were more realistic than those simulated with the original XCAT models. Incorporating intra-organ structures, the "textured" phantoms are envisioned to be used to conduct virtual clinical trials in the context of medical imaging in cases where the actual trials are infeasible due to the lack of ground truth, cost, or potential risks to the patients.

The 4D extended cardiac-torso (XCAT) phantom has provided a valuable tool to study the effects of anatomy and motion on medical images, especially cardiac motion. One limitation of the XCAT was that it did not have a physiological basis which to realistically simulate variations in cardiac function. In this work, we incorporate into the XCAT anatomy the four-chamber FE Living Heart Model (LHM) developed by the Living Heart Project (LHP). The LHM represents the state of the art in cardiac FE simulation because of its ability to accurately replicate the biomechanical motion of the entire heart and its variations. We create a new series of 4D phantoms capable of simulating patients with varying body sizes and shapes; cardiac positions, orientations, and dynamics. While extendable to other imaging modalities and technologies, our goal is to use the FE-enhanced XCAT models to investigate the optimal use of computed tomography (CT) for the evaluation of coronary artery disease (CAD). With the ability to simulate realistic, predictive, patient quality 4D imaging data, the enhanced XCAT models will enable optimization studies to identify the most promising systems or system parameters for further clinical validation.

The purpose of this paper was to extend the extended cardiac-torso (XCAT) series of computational phantoms to include a detailed lung architecture including airways and pulmonary vasculature. Eleven XCAT phantoms of varying anatomy were used in this paper. The lung lobes and initial branches of the airways, pulmonary arteries, and veins were previously defined in each XCAT model. These models were extended from the initial branches of the airways and vessels to the level of terminal branches using an anatomically-based volume-filling branching algorithm. This algorithm grew the airway and vasculature branches separately and iteratively without intersecting each other using cylindrical models with diameters estimated by order-based anatomical measurements. Geometrical features of the extended branches were compared with the literature anatomy values to quantitatively evaluate the models. These features include branching angle, length to diameter ratio, daughter to parent diameter ratio, asymmetrical branching pattern, diameter, and length ratios. The XCAT phantoms were then used to simulate CT images to qualitatively compare them with the original phantom images. The proposed growth model produced 46369 ± 12521 airways, 44737 ± 11773 arteries, and 39819 ± 9988 veins to the XCAT phantoms. Furthermore, the growth model was shown to produce asymmetrical airway, artery, and vein networks with geometrical attributes close to morphometry and model based studies. The simulated CT images of the phantoms were judged to be more realistic, including more airways and pulmonary vessels compared with the original phantoms. Future work will seek to add a heterogeneous parenchymal background into the XCAT lungs to make the phantoms even more representative of human anatomy, paving the way towards the use of XCAT models as a tool to virtually evaluate the current and emerging medical imaging technologies.

The purpose of this study was to develop a dynamic physical cardiac phantom with a realistic coronary plaque to investigate stenosis measurement accuracy under clinically relevant heart-rates. The coronary plaque model (5 mm diameter, 50% stenosis, and 32 mm long) was designed and 3D-printed with tissue equivalent materials (calcified plaque with iodine-enhanced lumen). Realistic cardiac motion was modeled by converting computational cardiac motion vectors into compression and rotation profiles executed by a commercial base cardiac phantom. The phantom was imaged on a dual-source CT system applying a retrospective gated coronary CT angiography (CCTA) protocol using synthesized motion-synchronized electrocardiogram (ECG) waveforms. Multiplanar reformatted images were reconstructed along vessel centerlines. Enhanced lumens were segmented by five independent operators. On average, stenosis measurement accuracy was 0.9% positively biased for the motion-free condition. Average measurement accuracy monotonically decreased from 0.9% positive bias for the motion-free condition to 18.5% negative bias at 90 beats per minute. Contrast-to-noise ratio, lumen circularity, and segmentation conformity also decreased monotonically with increasing heart-rate. These results demonstrate successful implementation of a base cardiac phantom with a 3D-printed coronary plaque model, relevant motion profile, and coordinated ECG waveform. They further show the utility of the model to ascertain metrics of CCTA accuracy and image quality under realistic plaque, motion, and acquisition conditions.

Purpose: The limited number of 3D patient-based breast phantoms available could be augmented by synthetic breast phantoms in order to facilitate virtual clinical trials (VCTs) using model observers for breast imaging optimization and evaluation., Methods: These synthetic breast phantoms were developed using Principal Component Analysis (PCA) to reduce the number of dimensions needed to describe a training set of images. PCA decomposed a training set of M breast CT volumes (with millions of voxels each) into an M-1-dimensional space of eigenvectors, which we call eigenbreasts. Each of the training breast phantoms was compactly represented by the mean image plus a weighted sum of eigenbreasts. The distribution of weights observed from training was then sampled to create new synthesized breast phantoms., Results: The resulting synthesized breast phantoms demonstrated a high degree of realism, as supported by an observer study. Two out of three experienced physicist observers were unable to distinguish between the synthesized breast phantoms and the patient-based phantoms. The fibroglandular density and noise power law exponent of the synthesized breast phantoms agreed well with the training data., Conclusions: Our method extends our series of digital breast phantoms based on breast CT data, providing the capability to generate new, statistically varying ensembles consisting of tens of thousands of virtual subjects. This work represents an important step toward conducting future virtual trials for task-based assessment of breast imaging, where it is vital to have a large ensemble of realistic phantoms for statistical power as well as clinical relevance., (© 2017 American Association of Physicists in Medicine.)

This study aimed to estimate the organ dose reduction potential for organ-dose-based tube current modulated (ODM) thoracic computed tomography (CT) with a wide dose reduction arc. Twenty-one computational anthropomorphic phantoms (XCAT) were used to create a virtual patient population with clinical anatomic variations. The phantoms were created based on patient images with normal anatomy (age range: 27 to 66 years, weight range: 52.0 to 105.8 kg). For each phantom, two breast tissue compositions were simulated: [Formula: see text] and [Formula: see text] (glandular-to-adipose ratio). A validated Monte Carlo program (PENELOPE, Universitat de Barcelona, Spain) was used to estimate the organ dose for standard tube current modulation (TCM) (SmartmA, GE Healthcare) and ODM (GE Healthcare) for a commercial CT scanner (Revolution, GE Healthcare) using a typical clinical thoracic CT protocol. Both organ dose and [Formula: see text]-to-organ dose conversion coefficients ([Formula: see text] factors) were compared between TCM and ODM. ODM significantly reduced all radiosensitive organ doses ([Formula: see text]). The breast dose was reduced by [Formula: see text]. For [Formula: see text] factors, organs in the anterior region (e.g., thyroid and stomach) exhibited substantial decreases, and the medial, distributed, and posterior region saw either an increase of less than 5% or no significant change. ODM significantly reduced organ doses especially for radiosensitive superficial anterior organs such as the breasts.

Purpose: This study aimed to investigate the breast dose reduction potential of a breast-positioning (BP) technique for thoracic CT examinations with organ-based tube current modulation (OTCM)., Methods: This study included 13 female anthropomorphic computational phantoms (XCAT, age range: 27-65 y.o., weight range: 52-105.8 kg). Each phantom was modified to simulate three breast sizes in standard supine geometry. The modeled breasts were then morphed to emulate BP that constrained the majority of the breast tissue inside the 120° anterior tube current (mA) reduction zone. The OTCM mA value was modeled using a ray-tracing program, which reduced the mA to 20% in the anterior region with a corresponding increase to the posterior region. The organ doses were estimated by a validated Monte Carlo program for a typical clinical CT system (SOMATOM Definition Flash, Siemens Healthcare). The simulated organ doses and organ doses normalized by CTDI vol were used to compare three CT protocols: attenuation-based tube current modulation (ATCM), OTCM, and OTCM with BP (OTCM BP )., Results: On average, compared to ATCM, OTCM reduced breast dose by 19.3 ± 4.5%, whereas OTCM BP reduced breast dose by 38.6 ± 8.1% (an additional 23.8 ± 9.4%). The dose saving of OTCM BP was more significant for larger breasts (on average 33, 38, and 44% reduction for 0.5, 1, and 2 kg breasts, respectively). Compared to ATCM, OTCM BP also reduced thymus and heart dose by 15.1 ± 7.4% and 15.9 ± 6.2% respectively., Conclusions: In thoracic CT examinations, OTCM with a breast-positioning technique can markedly reduce unnecessary exposure to radiosensitive organs in anterior chest wall, specifically breast tissue. The breast dose reduction is more notable for women with larger breasts., (© 2016 American Association of Physicists in Medicine.)

Purpose: The authors are developing a series of computational breast phantoms based on breast CT data for imaging research. In this work, the authors develop a program that will allow a user to alter the phantoms to simulate the effect of gravity and compression of the breast (craniocaudal or mediolateral oblique) making the phantoms applicable to multimodality imaging., Methods: This application utilizes a template finite-element (FE) breast model that can be applied to their presegmented voxelized breast phantoms. The FE model is automatically fit to the geometry of a given breast phantom, and the material properties of each element are set based on the segmented voxels contained within the element. The loading and boundary conditions, which include gravity, are then assigned based on a user-defined position and compression. The effect of applying these loads to the breast is computed using a multistage contact analysis in FEBio, a freely available and well-validated FE software package specifically designed for biomedical applications. The resulting deformation of the breast is then applied to a boundary mesh representation of the phantom that can be used for simulating medical images. An efficient script performs the above actions seamlessly. The user only needs to specify which voxelized breast phantom to use, the compressed thickness, and orientation of the breast., Results: The authors utilized their FE application to simulate compressed states of the breast indicative of mammography and tomosynthesis. Gravity and compression were simulated on example phantoms and used to generate mammograms in the craniocaudal or mediolateral oblique views. The simulated mammograms show a high degree of realism illustrating the utility of the FE method in simulating imaging data of repositioned and compressed breasts., Conclusions: The breast phantoms and the compression software can become a useful resource to the breast imaging research community. These phantoms can then be used to evaluate and compare imaging modalities that involve different positioning and compression of the breast.

Purpose: To create a database of highly realistic and anatomically variable 3D virtual breast phantoms based on dedicated breast computed tomography (bCT) data., Methods: A tissue classification and segmentation algorithm was used to create realistic and detailed 3D computational breast phantoms based on 230 + dedicated bCT datasets from normal human subjects. The breast volume was identified using a coarse three-class fuzzy C-means segmentation algorithm which accounted for and removed motion blur at the breast periphery. Noise in the bCT data was reduced through application of a postreconstruction 3D bilateral filter. A 3D adipose nonuniformity (bias field) correction was then applied followed by glandular segmentation using a 3D bias-corrected fuzzy C-means algorithm. Multiple tissue classes were defined including skin, adipose, and several fractional glandular densities. Following segmentation, a skin mask was produced which preserved the interdigitated skin, adipose, and glandular boundaries of the skin interior. Finally, surface modeling was used to produce digital phantoms with methods complementary to the XCAT suite of digital human phantoms., Results: After rejecting some datasets due to artifacts, 224 virtual breast phantoms were created which emulate the complex breast parenchyma of actual human subjects. The volume breast density (with skin) ranged from 5.5% to 66.3% with a mean value of 25.3% ± 13.2%. Breast volumes ranged from 25.0 to 2099.6 ml with a mean value of 716.3 ± 386.5 ml. Three breast phantoms were selected for imaging with digital compression (using finite element modeling) and simple ray-tracing, and the results show promise in their potential to produce realistic simulated mammograms., Conclusions: This work provides a new population of 224 breast phantoms based on in vivo bCT data for imaging research. Compared to previous studies based on only a few prototype cases, this dataset provides a rich source of new cases spanning a wide range of breast types, volumes, densities, and parenchymal patterns.

Purpose: We previously developed a set of highly detailed 4D reference pediatric extended cardiac-torso (XCAT) phantoms at ages of newborn, 1, 5, 10, and 15 yr with organ and tissue masses matched to ICRP Publication 89 values. In this work, we extended this reference set to a series of 64 pediatric phantoms of varying age and height and body mass percentiles representative of the public at large. The models will provide a library of pediatric phantoms for optimizing pediatric imaging protocols., Methods: High resolution positron emission tomography-computed tomography data obtained from the Duke University database were reviewed by a practicing experienced radiologist for anatomic regularity. The CT portion of the data was then segmented with manual and semiautomatic methods to form a target model defined using nonuniform rational B-spline surfaces. A multichannel large deformation diffeomorphic metric mapping algorithm was used to calculate the transform from the best age matching pediatric XCAT reference phantom to the patient target. The transform was used to complete the target, filling in the nonsegmented structures and defining models for the cardiac and respiratory motions. The complete phantoms, consisting of thousands of structures, were then manually inspected for anatomical accuracy. The mass for each major tissue was calculated and compared to linearly interpolated ICRP values for different ages., Results: Sixty four new pediatric phantoms were created in this manner. Each model contains the same level of detail as the original XCAT reference phantoms and also includes parameterized models for the cardiac and respiratory motions. For the phantoms that were 10 yr old and younger, we included both sets of reproductive organs. This gave them the capability to simulate both male and female anatomy. With this, the population can be expanded to 92. Wide anatomical variation was clearly seen amongst the phantom models, both in organ shape and size, even for models of the same age and sex. The phantoms can be combined with existing simulation packages to generate realistic pediatric imaging data from different modalities., Conclusions: This work provides a large cohort of highly detailed pediatric phantoms with 4D capabilities of varying age, height, and body mass. The population of phantoms will provide a vital tool with which to optimize 3D and 4D pediatric imaging devices and techniques in terms of image quality and radiation-absorbed dose.

Purpose: Physical phantoms are essential for the development, optimization, and evaluation of x-ray breast imaging systems. Recognizing the major effect of anatomy on image quality and clinical performance, such phantoms should ideally reflect the three-dimensional structure of the human breast. Currently, there is no commercially available three-dimensional physical breast phantom that is anthropomorphic. The authors present the development of a new suite of physical breast phantoms based on human data., Methods: The phantoms were designed to match the extended cardiac-torso virtual breast phantoms that were based on dedicated breast computed tomography images of human subjects. The phantoms were fabricated by high-resolution multimaterial additive manufacturing (3D printing) technology. The glandular equivalency of the photopolymer materials was measured relative to breast tissue-equivalent plastic materials. Based on the current state-of-the-art in the technology and available materials, two variations were fabricated. The first was a dual-material phantom, the Doublet. Fibroglandular tissue and skin were represented by the most radiographically dense material available; adipose tissue was represented by the least radiographically dense material. The second variation, the Singlet, was fabricated with a single material to represent fibroglandular tissue and skin. It was subsequently filled with adipose-equivalent materials including oil, beeswax, and permanent urethane-based polymer. Simulated microcalcification clusters were further included in the phantoms via crushed eggshells. The phantoms were imaged and characterized visually and quantitatively., Results: The mammographic projections and tomosynthesis reconstructed images of the fabricated phantoms yielded realistic breast background. The mammograms of the phantoms demonstrated close correlation with simulated mammographic projection images of the corresponding virtual phantoms. Furthermore, power-law descriptions of the phantom images were in general agreement with real human images. The Singlet approach offered more realistic contrast as compared to the Doublet approach, but at the expense of air bubbles and air pockets that formed during the filling process., Conclusions: The presented physical breast phantoms and their matching virtual breast phantoms offer realistic breast anatomy, patient variability, and ease of use, making them a potential candidate for performing both system quality control testing and virtual clinical trials.

Purpose: The authors previously developed an adult population of 4D extended cardiac-torso (XCAT) phantoms for multimodality imaging research. In this work, the authors develop a reference set of 4D pediatric XCAT phantoms consisting of male and female anatomies at ages of newborn, 1, 5, 10, and 15 years. These models will serve as the foundation from which the authors will create a vast population of pediatric phantoms for optimizing pediatric CT imaging protocols., Methods: Each phantom was based on a unique set of CT data from a normal patient obtained from the Duke University database. The datasets were selected to best match the reference values for height and weight for the different ages and genders according to ICRP Publication 89. The major organs and structures were segmented from the CT data and used to create an initial pediatric model defined using nonuniform rational B-spline surfaces. The CT data covered the entire torso and part of the head. To complete the body, the authors manually added on the top of the head and the arms and legs using scaled versions of the XCAT adult models or additional models created from cadaver data. A multichannel large deformation diffeomorphic metric mapping algorithm was then used to calculate the transform from a template XCAT phantom (male or female 50th percentile adult) to the target pediatric model. The transform was applied to the template XCAT to fill in any unsegmented structures within the target phantom and to implement the 4D cardiac and respiratory models in the new anatomy. The masses of the organs in each phantom were matched to the reference values given in ICRP Publication 89. The new reference models were checked for anatomical accuracy via visual inspection., Results: The authors created a set of ten pediatric reference phantoms that have the same level of detail and functionality as the original XCAT phantom adults. Each consists of thousands of anatomical structures and includes parameterized models for the cardiac and respiratory motions. Based on patient data, the phantoms capture the anatomic variations of childhood, such as the development of bone in the skull, pelvis, and long bones, and the growth of the vertebrae and organs. The phantoms can be combined with existing simulation packages to generate realistic pediatric imaging data from different modalities., Conclusions: The development of patient-derived pediatric computational phantoms is useful in providing variable anatomies for simulation. Future work will expand this ten-phantom base to a host of pediatric phantoms representative of the public at large. This can provide a means to evaluate and improve pediatric imaging devices and to optimize CT protocols in terms of image quality and radiation dose.

Purpose: To estimate patient-specific radiation dose and cancer risk for pediatric chest computed tomography (CT) and to evaluate factors affecting dose and risk, including patient size, patient age, and scanning parameters., Materials and Methods: The institutional review board approved this study and waived informed consent. This study was HIPAA compliant. The study included 30 patients (0-16 years old), for whom full-body computer models were recently created from clinical CT data. A validated Monte Carlo program was used to estimate organ dose from eight chest protocols, representing clinically relevant combinations of bow tie filter, collimation, pitch, and tube potential. Organ dose was used to calculate effective dose and risk index (an index of total cancer incidence risk). The dose and risk estimates before and after normalization by volume-weighted CT dose index (CTDI(vol)) or dose-length product (DLP) were correlated with patient size and age. The effect of each scanning parameter was studied., Results: Organ dose normalized by tube current-time product or CTDI(vol) decreased exponentially with increasing average chest diameter. Effective dose normalized by tube current-time product or DLP decreased exponentially with increasing chest diameter. Chest diameter was a stronger predictor of dose than weight and total scan length. Risk index normalized by tube current-time product or DLP decreased exponentially with both chest diameter and age. When normalized by DLP, effective dose and risk index were independent of collimation, pitch, and tube potential (<10% variation)., Conclusion: The correlations of dose and risk with patient size and age can be used to estimate patient-specific dose and risk. They can further guide the design and optimization of pediatric chest CT protocols., Supplemental Material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.11101900/-/DC1., (RSNA, 2011)

Purpose: Current methods for estimating and reporting radiation dose from CT examinations are largely patient-generic; the body size and hence dose variation from patient to patient is not reflected. Furthermore, the current protocol designs rely on dose as a surrogate for the risk of cancer incidence, neglecting the strong dependence of risk on age and gender. The purpose of this study was to develop a method for estimating patient-specific radiation dose and cancer risk from CT examinations., Methods: The study included two patients (a 5-week-old female patient and a 12-year-old male patient), who underwent 64-slice CT examinations (LightSpeed VCT, GE Healthcare) of the chest, abdomen, and pelvis at our institution in 2006. For each patient, a nonuniform rational B-spine (NURBS) based full-body computer model was created based on the patient's clinical CT data. Large organs and structures inside the image volume were individually segmented and modeled. Other organs were created by transforming an existing adult male or female full-body computer model (developed from visible human data) to match the framework defined by the segmented organs, referencing the organ volume and anthropometry data in ICRP Publication 89. A Monte Carlo program previously developed and validated for dose simulation on the LightSpeed VCT scanner was used to estimate patient-specific organ dose, from which effective dose and risks of cancer incidence were derived. Patient-specific organ dose and effective dose were compared with patient-generic CT dose quantities in current clinical use: the volume-weighted CT dose index (CTDIvol) and the effective dose derived from the dose-length product (DLP)., Results: The effective dose for the CT examination of the newborn patient (5.7 mSv) was higher but comparable to that for the CT examination of the teenager patient (4.9 mSv) due to the size-based clinical CT protocols at our institution, which employ lower scan techniques for smaller patients. However, the overall risk of cancer incidence attributable to the CT examination was much higher for the newborn (2.4 in 1000) than for the teenager (0.7 in 1000). For the two pediatric-aged patients in our study, CTDIvol underestimated dose to large organs in the scan coverage by 30%-48%. The effective dose derived from DLP using published conversion coefficients differed from that calculated using patient-specific organ dose values by -57% to 13%, when the tissue weighting factors of ICRP 60 were used, and by -63% to 28%, when the tissue weighting factors of ICRP 103 were used., Conclusions: It is possible to estimate patient-specific radiation dose and cancer risk from CT examinations by combining a validated Monte Carlo program with patient-specific anatomical models that are derived from the patients' clinical CT data and supplemented by transformed models of reference adults. With the construction of a large library of patient-specific computer models encompassing patients of all ages and weight percentiles, dose and risk can be estimated for any patient prior to or after a CT examination. Such information may aid in decisions for image utilization and can further guide the design and optimization of CT technologies and scan protocols.

This paper describes an automated procedure for creating detailed patient-specific pediatric dosimetry phantoms from a small set of segmented organs in a child's CT scan. The algorithm involves full body mappings from adult template to pediatric images using multichannel large deformation diffeomorphic metric mapping (MC-LDDMM). The parallel implementation and performance of MC-LDDMM for this application is studied here for a sample of 4 pediatric patients, and from 1 to 24 processors. 93.84% of computation time is parallelized, and the efficiency of parallelization remains high until more than 8 processors are used. The performance of the algorithm was validated on a set of 24 male and 18 female pediatric patients. It was found to be accurate typically to within 1-2 voxels (2-4 mm) and robust across this large and variable data set.

Purpose: Radiation-dose awareness and optimization in CT can greatly benefit from a dose-reporting system that provides dose and risk estimates specific to each patient and each CT examination. As the first step toward patient-specific dose and risk estimation, this article aimed to develop a method for accurately assessing radiation dose from CT examinations., Methods: A Monte Carlo program was developed to model a CT system (LightSpeed VCT, GE Healthcare). The geometry of the system, the energy spectra of the x-ray source, the three-dimensional geometry of the bowtie filters, and the trajectories of source motions during axial and helical scans were explicitly modeled. To validate the accuracy of the program, a cylindrical phantom was built to enable dose measurements at seven different radial distances from its central axis. Simulated radial dose distributions in the cylindrical phantom were validated against ion chamber measurements for single axial scans at all combinations of tube potential and bowtie filter settings. The accuracy of the program was further validated using two anthropomorphic phantoms (a pediatric one-year-old phantom and an adult female phantom). Computer models of the two phantoms were created based on their CT data and were voxelized for input into the Monte Carlo program. Simulated dose at various organ locations was compared against measurements made with thermoluminescent dosimetry chips for both single axial and helical scans., Results: For the cylindrical phantom, simulations differed from measurements by -4.8% to 2.2%. For the two anthropomorphic phantoms, the discrepancies between simulations and measurements ranged between (-8.1%, 8.1%) and (-17.2%, 13.0%) for the single axial scans and the helical scans, respectively., Conclusions: The authors developed an accurate Monte Carlo program for assessing radiation dose from CT examinations. When combined with computer models of actual patients, the program can provide accurate dose estimates for specific patients.

The strong influence of subsurface heterogeneity on contaminant migration and in situ remediation calls for an improved understanding of its origins and more efficient methods of characterization. Accordingly, an outcrop study of physical and chemical heterogeneity was conducted in a glaciofluvial deposit in Deerfield, New Hampshire, in order to uncover processes controlling the spatial variation of sediment properties and evaluate the extent to which geologic information can be used to characterize the observed variation. The results indicate that physical and chemical properties at the Deerfield site have distinctly different spatial correlation structures. Lithologic facies explain 31% to 60% of the variation in permeability, dithionite citrate (DC)-extractable manganese, and DC-extractable aluminum. Lithofacies bounding surfaces do not separate regions of significantly different DC-extractable iron; instead, 49% of its variation is explained by sediment color. Color also accounts for 34% of the variation in DC-extractable aluminum and 60% of the variation in DC-extractable manganese. Strong relationships with sediment facies and/or color enable detailed mapping of permeability, extractable iron, and extractable manganese. Differences in the geometries of iron and manganese enrichment, petrographic observations, and scanning electron microscope analyses indicate that (hydr)oxide grain coatings originated from the postdepositional weathering of biotite and garnet, coupled with local, redox-driven redistribution of the liberated iron and manganese. The findings suggest that lithofacies and color information can aid the characterization and modeling of heterogeneity at similar carbon-poor glaciofluvial sites.