Anatomical Phantom Research Articles

Development of age-specific population-based paediatric computational phantoms for image-based data mining and other radiotherapy applications

Objective.Computational anatomical models have many applications in paediatric radiotherapy. Age-specific computational anatomical models were historically developed to represent average and/or healthy individuals, where cancer patients may present with anatomical variations caused by the disease and/or treatment effects. We developed RT-PAL, a library of computational age-specific voxelized anatomical models tailored to represent the paediatric radiotherapy population.Approach.Data from patients undergoing craniospinal irradiation (CSI) were used (n = 74, median age 7.3y, range: 1-17y). The RT-PAL phantoms were generated using groupwise deformable image registration to spatially normalize and average a sub-set of twenty clinical CTs and contours (n = 74, median age 7.7y, range: 3-14 y). To assess their anatomical and age-dependency plausibility, the RT-PAL models were compared against clinical cancer patient data and two healthy population based libraries of phantoms: the International Commission on Radiological Protection (ICRP) pediatric reference computational phantoms (n = 8, median age 7.5y, range: 1-15y) and a range of 4D paediatric extended cardiac torso (XCAT) phantoms (n = 75, median age 9.1y, range: 1-18y). For each dataset, nineteen organs were segmented on all age models to determine their volume. Each set was evaluated through a linear fit of organ volume with age, where comparisons were made relative to the linear fit of the clinical data.Main Results.Overall good anatomical plausibility was found for the RT-PAL phantoms. The age-dependency reported was comparable to both the clinical data and other phantoms, demonstrating their efficacy as a library of age-specific phantoms. Larger discrepancies with the clinical, ICRP and XCAT organ data were attributable to differences in organ filling, segmentation strategy and age distribution of the datasets, limitations of RT-PAL generation methodology, and/or possible anatomical differences between healthy and cancer populations.Significance.The RT-PAL models showed potential in representing the paediatric radiotherapy cohort, who are most likely to benefit from dedicated, age-specific anatomical phantoms.

Re-evaluation of F-FDG absorbed and effective dose in adult and pediatric phantoms using DoseCalcs Monte Carlo platform: a validation study.

Positron emission tomography (PET) using F-FDG is a well-known modality for the diagnosis of various diseases in patients of different ages, sexes, and states of health, which implies that internal radiation dosimetry is highly desired for different phantom anatomies. In this study, we validate "DoseCalcs," a new Monte Carlo platform that combines personalized internal dosimetry calculations with Monte Carlo simulations. To achieve that, we used the specific absorbed fraction (SAF) calculated by DoseCalcs and those from ICRP publication 133 to estimate the absorbed dose per injected activity (AD/IA) and effective dose per injected activity (ED/IA) for F-FDG. The investigation focused on various voxelized phantoms representing different age groups, including adult male and female, and pediatric phantoms of various ages, from newborn to 15 years old. Using the DoseCalcs Monte Carlo platform, we have simulated the emission of F-FDG positrons based on the energy spectrum provided in ICRP publication 107. The results demonstrated the impact of anatomical differences and different organ/tissue compositions on radiation absorption, with significant variations in the AD/IA across different phantoms. Interestingly, organs/tissues near the emission source showed higher AD/IA, highlighting the anatomical dependence on the phantom. When our results were compared to established reference data, especially from ICRP128, most organs/tissues had good agreement. Still, some cases have shown differences. This shows how important it is to use accurate radionuclide data and biokinetic modeling in internal dosimetry calculations. Furthermore, we compared AD/IA and ED/IA values calculated in newborns by DoseCalcs with those derived from alternative codes, MCNP and EGSnrc. While the results generally exhibited consistency, subtle variations underscored the influence of biokinetics modeling choices and computational methodologies. Overall, this research contributes valuable insights into the precision of internal dosimetry calculations using "DoseCalcs-Gui" by providing one platform for Monte Carlo simulation and personalized internal dosimetry in nuclear medicine. The DoseCalcs platform is free for research and available for download at www.github.com/TarikEl/DoseCalcs-Gui .

In silico dosimetry for a prostate cancer treatment using 198Au nanoparticles

Objective. To estimate dose rates delivered by using radioactive198Au nanoparticles for prostate cancer nanobrachytherapy, identifying contribution by photons and electrons emmited from the source.Approach. Utilizingin silicomodels, two different anatomical representations were compared: a mathematical model and a unstructured mesh model based on the International Commission on Radiological Protection (ICRP) Publication 145 phantom. Dose rates by activity were calculated to the tumor and nearby healthy tissues, including healthy prostate tissue, urinary bladder wall and rectum, using Monte Carlo code MCNP6.2.Main results. Results indicate that both models provide dose rate estimates within the same order of magnitude, with the mathematical model overestimating doses to the prostate and bladder by approximately 20% compared to the unstructured mesh model. The discrepancies for the tumor and rectum were below 4%. Photons emmited from the source were defined as the primary contributors to dose to other organs, while 97.9% of the dose to the tumor was due to electrons emmited from the source.Significance. Our findings emphasize the importance of model selection in dosimetry, particularly the advantages of using realistic anatomical phantoms for accurate dose calculations. The study demonstrates the feasibility and effectiveness of198Au nanoparticles in achieving high dose concentrations in tumor regions while minimizing exposure to surrounding healthy tissues. Beta emissions were found to be predominantly responsible for tumor dose delivery, reinforcing the potential of198Au nanoparticles in localized radiation therapy. We advocate for using realistic body phantoms in further research to enhance reliability in dosimetry for nanobrachytherapy, as the field still lacks dedicated protocols.

Sinogram-characteristic-informed network for efficient restoration of low-dose SPECT projection data.

Single Photon Emission Computed Tomography (SPECT) sinogram restoration for low-dose imaging is a critical challenge in medical imaging. Existing methods often overlook the characteristics of the sinograms, necessitating innovativeapproaches. In this study, we introduce the Sinogram-characteristic-informed network (SCI-Net) to address the restoration of low-dose SPECT sinograms. Our aim is to build and train a model based on the characteristics of sinograms, including continuity, periodicity, multi-scale properties of lines in sinograms, and others, to enhance the model's understanding of the restorationprocess. SCI-Net incorporates several novel mechanisms tailored to exploit the inherent characteristics of sinograms. We implement a channel attention module with a decay mechanism to leverage continuity across adjacent sinograms, while a position attention module captures global correlations within individual sinograms. Additionally, we propose a multi-stage progressive integration mechanism to balance local detail and overall structure. Multiple regularization terms, customized to sinogram image characteristics, are embedded into the loss function for modeltraining. The experimental evaluations are divided into two parts: simulation data evaluation and clinical evaluation. The simulation data evaluation is conducted on a dataset comprising ten organ types, generated by the SIMIND Monte Carlo program from extended cardiac-torso (XCAT) anatomical phantoms. The dataset includes a total of SPECT sinograms with low-dose as input data and normal-dose as ground truth, consisting of 3881 sinograms in the training dataset and 849 sinograms in the testing set. When comparing the restoration of low-dose sinograms to normal-dose references, SCI-Net effectively improves performance. Specifically, the peak signal-to-noise ratio (PSNR) and the structural similarity (SSIM) on sinograms increase from 15.72 to 34.66 ( 0.001) and 0.6297 to 0.9834 ( 0.001), respectively, and on reconstructed images, reconstructed by maximum likelihood-expectation maximization (ML-EM), the PSNR and the SSIM improve from 21.95 to 33.14 ( 0.001) and 0.9084 to 0.9866 ( 0.001), respectively. We compared SCI-Net with existing methods, including baseline models, traditional reconstruction algorithms, end-to-end methods, sinogram restoration methods, and image post-processing methods. The experimental results and visual examples demonstrate that SCI-Net surpasses these existing methods in SPECT sinogram restoration. The clinical evaluation is conducted on clinical data of low-dose SPECT sinograms for spleen, thyroid, skull, and bone. These SPECT projection data are obtained from Discovery NM/CT670 scans. We compare the reconstructed images from the SCI-Net restored sinograms, the reconstructed images from the original low-dose sinograms, and the reconstructed images using the built-in algorithm of the Discovery NM/CT670. The results show that our method effectively reduces the coefficient of variation (COV) in the regions of interest (ROI) of the reconstructed images, thereby enhancing the quality of the reconstructed images through SPECT sinogramrestoration. Our proposed SCI-Net exhibits promising performance in the restoration of low-dose SPECT projection data. In the SCI-Net, we have implemented three mechanisms based on distinct forms, which are advantageous for the model to more effectively leverage the characteristics of sinograms and achieve commendable restorationoutcomes.

A 32-channel high-impedance honeycomb-shaped receive array for temporal lobes exploration at 11.7T.

The newly operational 11.7T Iseult scanner provides an improved global SNR in the human brain. This gain in SNR can be pushed even further locally by designing region-focused dense receive arrays. The temporal lobes are particularly interesting to neuroscientists as they are associated with language and concept recognition. Our main goal was to maximize the SNR in the temporal lobes and provide high-acceleration capabilities for fMRI studies. We designed and developed a 32-channel receive array made of non-overlapped hexagonal loops. The loops were arranged in a honeycomb pattern and targeted the temporal lobes. They were placed on a flexible neoprene cap closely fitting the head. A new stripline design with a high impedance was proposed and applied for the first time at 11.7T. Specific homebuilt miniaturized low-impedance preamplifiers were directly mounted on the loops, providing preamplifier decoupling in a compact and modular design. Using an anatomical phantom, we experimentally compared the SNR and parallel imaging performance of the region-focused cap to a 32-channel whole-brain receive array at 11.7T. The experimental results showed a 1.7-time higher SNR on average in the temporal lobes compared to the whole brain receive array. The g-factor is also improved when undersampling in the antero-posterior and head-foot directions. A significant SNR boost in the temporal lobes was demonstrated at 11.7T compared to the whole-brain receive array. The parallel imaging capabilities were also improved in the temporal lobes in some acceleration directions.

Investigation of a novel 2.5 MV sintered diamond target beam for intracranial linac-based stereotactic treatments.

This work investigates the small-field dosimetric characteristics of a 2.5 MV sintered diamond target beam and its feasibility for use in linac-based intracranial stereotactic treatments. Due to the increased proportion of low energy photons in the low-Z beam, it was hypothesized that this novel beam would provide sharper dose fall-off compared to the 6 MV beam owing to the reduced energy, and therefore range, of secondary electrons. Stereotactic treatments of ocular melanoma and trigeminal neuralgia were simulated for 2.5 MV low-Z and 6 MV beams using Monte Carlo to calculate dose in a voxelized anatomical phantom. Two collimation methods were investigated, including a 5x3 mm2 HDMLC field and a 4 mm cone to demonstrate isolated and combined effects of geometric and radiological contributions to the penumbral width. The measured 2.5 MV low-Z dosimetric profiles demonstrated reduced penumbra by 0.5 mm in both the inline and crossline directions across all depths for both collimation methods, compared to 6 MV. In both treatment cases, the 2.5 MV low-Z beam collimated with the 4 mm cone produced the sharpest dose fall off in profiles captured through isocenter. This improved fall-off resulted in a 59% decrease to the maximum brainstem dose in the trigeminal neuralgia case for the 2.5 MV low-Z MLC collimated beam compared to 6 MV. Reductions to the maximum and mean doses to ipsilateral and contralateral OARs in the ocular melanoma case were observed for the 2.5 MV low-Z beam compared to 6 MV with both collimation methods. While the low dose rate of this novel beam prohibits immediate clinical translation, the results of this study support the further development of this prototype beam to decrease toxicity in intracranial SRS treatments.&#xD.

Technical note: Phantom-based evaluation of CBCT dose calculation accuracy for use in adaptive radiotherapy.

High-quality 3D-anatomy of the day is needed for treatment plan adaptation in radiotherapy. For online x-ray-based CBCT workflows, one approach is to create a synthetic CT or to utilize a fan-beam CT with corresponding registrations. The former potentially introduces uncertainties in the dose calculation if deformable image registration is used. The latter can introduce burden and complexity to the process, the facility, and thepatient. Using the CBCT of the day, acquired on the treatment device, for direct dose calculation and plan adaptation can overcome these limitations. This study aims to assess the accuracy of the calculated dose on the CBCT scans acquired on a Halcyon linear accelerator equipped withHyperSight. HyperSight's new CBCT reconstruction algorithm includes improvements in scatter correction, HU calibration of the imager, and beam shape adaptation. Furthermore, HyperSight introduced a new x-ray detector. To show the effect of the implemented improvements, gamma comparisons of 2%/2mm, 2%/1mm, and 1%/1mm were made between the dose distribution in phantoms calculated on the CBCT reconstructions and the simulation CT scans, considering this the standard of care. The resulting gamma passing rates were compared to those obtained with the Halcyon 3.0 reconstruction and hardware without HyperSight's technologies. Various anatomical phantoms for dosimetric evaluations on brain, head and neck, lung, breast, and prostate cases have been used in thisstudy. The overall results demonstrated that HyperSight outperformed the Halcyon 3.0 version. Based on the gamma analysis, the calculated dose using HyperSight was closer to the CT scan-based doses than the calculated dose using iCBCT Halcyon 3.0 for most cases. Over all plans and gamma criteria, Halcyon 3.0 achieved an average passing rate of 92.9%, whereas HyperSight achieved 98.1%. Using HyperSight CBCT images for direct dose calculation, for example, in (online) plan adaptation, seems feasible for the investigatedcases.

High-Resolution Ultrasound Platform for Infant Meningitis Detection: An In Vitro Demonstration.

Infant meningitis remains a severe burden on global health, particularly for young infants. Traditional ultrasound imaging techniques are limited in spatial resolution to visualize white blood cells (WBCs) in the cerebrospinal fluid (CSF), which is considered a well-established marker for meningitis detection. This work presents a novel platform that uses high-resolution ultrasound to detect the backscatter signals from microscopic CSF WBCs through the anterior fontanelle of neonates and young infants. The whole system was built around a custom probe that allows for a 20 MHz focused transducer to be mechanically controlled to map the area of interest in the CSF. Data processing can be performed internally in the device without the need to extract the images for further analysis. The in vitro feasibility of the proposed solution was evaluated in imaging 7 μm particle suspensions at different concentrations relevant to meningitis diagnosis ranging from 7- to 646-particles (pp)/μL. The experimental tests were conducted from a simple setup using a sample container to a more realistic setup based on an anatomical phantom of the neonatal head. The results show high-quality images, where 7 μm particles can be resolved for the different concentrations.

StepBrain: A 3-Dimensionally Printed Multicompartmental Anthropomorphic Brain Phantom to Simulate PET Activity Distributions.

An innovative multicompartmental anatomic brain phantom (StepBrain) is described to simulate the invivo tracer uptake of gray matter, white matter, and striatum, overcoming the limitations of currently available phantoms. Methods: StepBrain was created by exploiting the potential of fused deposition modeling 3-dimensional printing to replicate the real anatomy of the brain compartments, as modeled through ad hoc processing of healthy-volunteer MR images. Results: A realistic simulation of 18F-FDG PET brain studies, using target activity to obtain the real concentration ratios, was obtained, and the results of postprocessing with partial-volume effect correction tools developed for human PET studies confirmed the accuracy of these methods in recovering the target activity concentrations. Conclusion: StepBrain compartments (gray matter, white matter, and striatum) can be simultaneously filled, achieving different concentration ratios and allowing the simulation of different (e.g., amyloid, tau, or 6-fluoro-l-dopa) tracer distributions, with a potentially valuable role for multicenter PET harmonization studies.

Collateral flow and pulsatility during large vessel occlusions: insights from a quantitative in vitro study.

Acute ischemic stroke caused by large vessel occlusions is being increasingly treated with neurovascular interventions. The hemodynamics within the collateral system of the circle of Willis (CoW) hemodynamics play a fundamental role in therapy success. However, transient in vivo data on pathological collateral flow during large vessel occlusions are not available. Moreover, there are no flow models that accurately simulate the hemodynamic conditions in the CoW during large vessel occlusions. We used a circulatory loop to generate highly reproducible cerebrovascular-like flows and pressures and used non-invasive flow visualization and high-resolution flow and pressure measurements to acquire detailed, time-dependent hemodynamics inside an anatomical phantom of the CoW. After calibrating a physiological reference case, we induced occlusions in the 1. middle cerebral artery, 2. terminal carotid artery, and 3. basilar artery; and measured the left posterior communicating artery flow. Mean arterial pressure and pulse pressure remained unchanged in the different occlusion cases compared to the physiological reference case, while total cerebral flow decreased by up to 19%. In all three occlusion cases, reversed flow was found in the left posterior communicating artery compared to the reference case with different flow magnitudes and pulsatility index values. The experimental results were compared with clinical findings, demonstrating the capability of this realistic cerebrovascular flow setup. This novel cerebrovascular flow setup opens the possibility for investigating different topics of neurovascular interventions under various clinical conditions in controlled preclinical laboratory studies.

Artificial Intelligence-Based Thermal Imaging for Breast Tumor Location and Size Estimation Using Thermal Impedance

Abstract Tumors can be detected from a temperature gradient due to high vascularization and increased metabolic activity of cancer cells. Thermal infrared images have been recognized as potential alternatives to detect these tumors. However, even the use of artificial intelligence directly on these images has failed to accurately locate and detect the tumor size due to the low sensitivity of temperatures and position within the breast. Thus, we aimed to develop techniques based on applying the thermal impedance method and artificial intelligence to determine the origin of the heat source (abnormal cancer metabolism) and its size. The low sensitivity to tiny and deep tumors is circumvented by utilizing the concept of thermal impedance and artificial intelligence techniques such as deep learning. We describe the development of a thermal model and the creation of a database based on its solution. We also outline the choice of detectable parameters in the thermal image, the use of deep learning libraries, and network training using convolutional neural networks (CNNs). Lastly, we present tumor location and size estimates based on thermographic images obtained from simulated thermal models of a breast, using Cartesian geometry and a scanned geometric shape of an anatomical phantom model.

Multi-institution single geometry plan complexity characteristics based on IROC phantoms.

Clinical intensity modulated radiation therapy plans have been described using various complexity metrics to help identify problematic radiotherapy plans. Most previous studies related to the quantification of plan complexity and their utility have relied on institution-specific plans which can be highly variable depending on the machines, planning techniques, delivery modalities, and measurement devices used. In this work, 1723 plans treating one of only four standardized geometries were simultaneously analyzed to investigate how radiation plan complexity metrics vary across four different sets of common objectives. To assess the treatment plan complexity characteristics of plans developed for Imaging and Radiation Oncology Core (IROC) phantoms. Specifically, to understand the variability in plan complexity between institutions for a common plan objective, and to evaluate how various complexity metrics differentiate relevant groups of plans. 1723 plans treating one of four standardized IROC phantom geometries representing four different anatomical sites of treatment were analyzed. For each plan, 22 MLC-descriptive plan complexity metrics were calculated, and principal component analysis (PCA) was applied to the 22 metrics in order to evaluate differences in plan complexity between groups. Across all metrics, pairwise comparisons of the IROC phantom data were made for the following classifications of the data: anatomical phantom treated, treatment planning system (TPS), and the combination of MLC model and treatment planning system. An objective k-means clustering algorithm was also applied to the data to determine if any meaningful distinctions could be made between different subgroups. The IROC phantom database was also compared to a clinical database from the University of Wisconsin-Madison (UW) which included plans treating the same four anatomical sites as the IROC phantoms using a TrueBeam™ STx and Pinnacle3 TPS. The IROC head and neck and spine plans were distinct from the prostate and lung plans based on comparison of the 22 metrics. All IROC phantom plan group complexity metric distributions were highly variable despite all plans being designed for identical geometries and plan objectives. The clusters determined by the k-means algorithm further supported that the IROC head and neck and spine plans involved similar amounts of complexity and were largely distinct from the prostate and lung plans, but no further distinctions could be made. Plan complexity in the head and neck and spine IROC phantom plans were similar to the complexity encountered in the UW clinical plans. There is substantial variability in plan complexity between institutions when planning for the same objective. For each IROC anatomical phantom treated, the magnitude of variability in plan complexity between institutions is similar to the variability in plan complexity encountered within a single institution database containing several hundred unique clinical plans treating corresponding anatomies in actual patients.

Evaluating the accuracy of cerebrovascular computational fluid dynamics modeling through time-resolved experimental validation

Accurate modeling of cerebral hemodynamics is crucial for better understanding the hemodynamics of stroke, for which computational fluid dynamics (CFD) modeling is a viable tool to obtain information. However, a comprehensive study on the accuracy of cerebrovascular CFD models including both transient arterial pressures and flows does not exist. This study systematically assessed the accuracy of different outlet boundary conditions (BCs) comparing CFD modeling and an in-vitro experiment. The experimental setup consisted of an anatomical cerebrovascular phantom and high-resolution flow and pressure data acquisition. The CFD model of the same cerebrovascular geometry comprised five sets of stationary and transient BCs including established techniques and a novel BC, the phase modulation approach. The experiment produced physiological hemodynamics consistent with reported clinical results for total cerebral blood flow, inlet pressure, flow distribution, and flow pulsatility indices (PI). The in-silico model instead yielded time-dependent deviations between 19–66% for flows and 6–26% for pressures. For cerebrovascular CFD modeling, it is recommended to avoid stationary outlet pressure BCs, which caused the highest deviations. The Windkessel and the phase modulation BCs provided realistic flow PI values and cerebrovascular pressures, respectively. However, this study shows that the accuracy of current cerebrovascular CFD models is limited.

Technical note: development of a simulation framework, enabling the investigation of locally tuned single energy proton radiography

Range uncertainties remain a limitation for the confined dose distribution that proton therapy can offer. The uncertainty stems from the ambiguity when translating CT Hounsfield Units (HU) into proton stopping powers. Proton Radiography (PR) can be used to verify the proton range. Specifically, PR can be used as a quality-control tool for CBCT-based synthetic CTs. An essential part of the work illustrating the potential of PR has been conducted using multi-layer ionization chamber (MLIC) detectors and mono-energetic PR. Due to the dimensions of commercially available MLICs, clinical adoption is cumbersome. Here, we present a simulation framework exploring locally-tuned single energy (LTSE) proton radiography and corresponding potential compact PR detector designs. Based on a planning CT data set, the presented framework models the water equivalent thickness. Subsequently, it analyses the proton energies required to pass through the geometry within a defined ROI. In the final step, an LTSE PR is simulated using the MCsquare Monte Carlo code. In an anatomical head phantom, we illustrate that LTSE PR allows for a significantly shorter longitudinal dimension of MLICs. We compared PR simulations for two exemplary 30 × 30 mm2 proton fields passing the phantom at a 90° angle at an anterior and a posterior location in an iso-centric setup. The longitudinal distance over which all spots per field range out is significantly reduced for LTSE PR compared to mono-energetic PR. In addition, we illustrate the difference in shape of integral depth dose (IDD) when using constrained PR energies. Finally, we demonstrate the accordance of simulated and experimentally acquired IDDs for an LTSE PR acquisition. As the next steps, the framework will be used to investigate the sensitivity of LTSE PR to various sources of errors. Furthermore, we will use the framework to systematically explore the dimensions of an optimized MLIC design for daily clinical use.

Development of Population-Based Pediatric Computational Phantoms for Radiotherapy Applications.

Age-specific pediatric computational phantoms are used in radiotherapy (RT) for quality assurance and for reconstruction of historical RT doses (within others). Phantoms are typically developed from healthy patients and may not effectively represent those with cancer due to pathology and/or treatment effects. This study evaluated a set of population-based pediatric computational phantoms developed in-house in terms of anatomical plausibility. Planning CTs and contours from historical craniospinal irradiation (CSI) patients (n = 74, median age 7y, range: 1-17y) were used to generate and evaluate a set of in-house age-specific population-based RT phantoms (RT-P). The RT-P were generated by combining a sub-set of clinical CTs and contours through groupwise deformable image registration, generating average models of CSI sub-populations (n = 74, median age 7y, range: 3-14y). Models were then compared against clinical data and two libraries of phantoms representing healthy populations: the International Commission on Radiological Protection (ICRP) pediatric reference computational phantoms (n = 8, median age 8y, range: 1-15y) and a variety of default 4D extended cardiac torso (XCAT) phantoms (n = 75, median age 9y, range: 1-18y). Variation between organ volumes for the different datasets was assessed through a linear fit of organ volume with age, reporting the slope (∑) of each fit [y-1]. Average difference between the volume datapoints and the linear fit for clinical data (Δ) [%] were also reported. This allowed for comparisons of the RT-P to clinical and reference data in terms of organ volumes across developmental stages. The table shows 9 of the 19 investigated organs. The ∑ reported for RT-P models were of similar magnitude as the clinical data and other phantoms, effectively modelling changes with age. The greatest and least ∑ were reported from lungs and thyroid respectively, in agreement with expected relative sizes between organs. Larger values for Δ were likely due to differences in organ filling and segmentation strategy between datasets, limitations of RT-P methodology, and/or anatomical differences between healthy and cancer populations. The RT-P models show promise in representing the RT cohort that may benefit from specialized anatomical phantoms. Further work is needed to address the limitations of the current methodology and its applicability to other RT cohorts.

Design and Production of an Anatomical Lung Research and Education Phantom Using 3 Dimensional (3D) Printing Technology

Amaç: 3 boyutlu (3B) baskı teknolojisi sağlık çalışmalarında organ baskısı olarak araştırma ve eğitim materyallerinde sıkça kullanılmaktadır. 3B fantomlar, görüntüleme tekniklerinin test edilip değerlendirilmesi ile cihazda yapılan ölçümlerin gözden geçirilmesinde pratik yaklaşımlar sunmaktadır. Çalışmada, fantomun akciğer yüzey anatomisinin tasarımıyla beraber, çalışmamıza özgünlük kazandıran, organ modeline radyonüklidi güvenli ve kolayca transfer edip, görüntü almayı sağlayan özel bir iç tasarım düşünülmüştür. Yöntem: Akciğer iç tasarımının bu formda yapılmasının sebebi organa radyonüklid temasının olduğu durumları fantom aracılığıyla canlandırılıp gerekli ölçümlerin yapılabilmesidir. 3B anatomik akciğer fantomu, tasarlanan şekilde ve ölçülerde uygun Hounsfield Unit (HU) değerlerinde basılmıştır ve fantomun içyapısının tıbbi görüntüleme cihazları ile görüntülenmiştir. Bulgular: Fantomda, Bilgisayarlı Tomografi (BT) görüntülerinde akciğer iç boşlukları ve dış parankim doku yapısı doğal akciğer yapısına benzer özellikte görüntülenmiştir. Sonuç: Araştırma ve eğitimde kullanılmak üzere, insan anatomisine benzer, Tek Foton Emisyon Bilgisayarlı Tomografi (SPECT), Pozitron Emisyon Tomografi (PET), Manyetik Rezonans Görüntüleme (MRG) ve BT uyumlu anatomik akciğer fantomu tasarlanarak, 3B basımı yapılmış ve gerekli radyolojik görüntüleri alınmıştır. Bunun neticesinde üretilen 3B akciğer fantomu eğitim ve araştırma materyali olarak sürekli kullanılacaktır.

Simulation of consequences of using nonideal detectors during beam data commissioning measurements.

Beam data commissioning is a core task of radiotherapy physicists. Despite multiple detectors available, a feasible measurement program compromises between detector properties and time constraints. Therefore, it is important to understand how nonideal measurement data propagates into patient dose calculation. We simulated the effects of realistic errors, due to beam commissioning with presumably nonoptimal detectors, on the resulting patient dose distributions. Additionally, the detectability of such beam commissioning errors during patient plan quality assurance (QA) was evaluated. A clinically used beam model was re-commissioned introducing changes to depth dose curves, output factors, profiles or combinations of those. Seventeen altered beam models with incremental changes of the modelling parameters were created to analyze dose changes on simplified anatomical phantoms. Additionally, fourteen altered models incorporate changes in the order of signal differences reported for typically used detectors. Eighteen treatment plans of different types were recalculated on patient CT data sets using the altered beam models. For the majority of clinical plans, dose distributions in the target volume recalculated on the patient computed tomography data were similar between the original and the modified beam models, yielding global 2%/2mm gamma pass rates above 98.9%. Larger changes were observed for certain combinations of beam modelling errors and anatomical sites, most extreme for output factor changes in a small target volume plan with a pass rate of 80.6%. Modelling an enlarged penumbra as if measured with a 0.125cm3 ion chamber had the largest effect on the dose distribution (average pass rate of 96.5%, lowest 85.4%). On different QA phantom geometries, dose distributions between calculations with modified and unmodified models typically changed too little to be detected in actual measurements. While the simulated errors during beam modelling had little effect on most plans, in some cases changes were considerable. High-quality penumbra and small field output factor should be a main focus of commissioning measurements. Detecting modelling issues using standard patient QA phantoms is unlikely. Verification of a beam model should be performed especially for plans with high modulation and in different depths or geometries representing the variety of situations expected clinically.

Development of a bespoke phantom to optimize molecular PET imaging of pituitary tumors

BackgroundImage optimization is a key step in clinical nuclear medicine, and phantoms play an essential role in this process. However, most phantoms do not accurately reflect the complexity of human anatomy, and this presents a particular challenge when imaging endocrine glands to detect small (often subcentimeter) tumors. To address this, we developed a novel phantom for optimization of positron emission tomography (PET) imaging of the human pituitary gland. Using radioactive 3D printing, phantoms were created which mimicked the distribution of 11C-methionine in normal pituitary tissue and in a small tumor embedded in the gland (i.e., with no inactive boundary, thereby reproducing the in vivo situation). In addition, an anatomical phantom, replicating key surrounding structures [based on computed tomography (CT) images from an actual patient], was created using material extrusion 3D printing with specialized filaments that approximated the attenuation properties of bone and soft tissue.ResultsThe phantom enabled us to replicate pituitary glands harboring tumors of varying sizes (2, 4 and 6 mm diameters) and differing radioactive concentrations (2 ×, 5 × and 8 × the normal gland). The anatomical phantom successfully approximated the attenuation properties of surrounding bone and soft tissue. Two iterative reconstruction algorithms [ordered subset expectation maximization (OSEM); Bayesian penalized likelihood (BPL)] with a range of reconstruction parameters (e.g., 3, 5, 7 and 9 OSEM iterations with 24 subsets; BPL regularization parameter (β) from 50 to 1000) were tested. Images were analyzed quantitatively and qualitatively by eight expert readers. Quantitatively, signal was the highest using BPL with β = 50; noise was the lowest using BPL with β = 1000; contrast was the highest using BPL with β = 100. The qualitative review found that accuracy and confidence were the highest when using BPL with β = 400.ConclusionsThe development of a bespoke phantom has allowed the identification of optimal parameters for molecular pituitary imaging: BPL reconstruction with TOF, PSF correction and a β value of 400; in addition, for small (< 4 mm) tumors with low contrast (2:1 or 5:1), sensitivity may be improved using a β value of 100. Together, these findings should increase tumor detection and confidence in reporting scans.

Silicone phantoms fabricated with multi-material extrusion 3D printing technology mimicking imaging properties of soft tissues in CT

Recently, 3D printing has been widely used to fabricate medical imaging phantoms. So far, various rigid 3D printable materials have been investigated for their radiological properties and efficiency in imaging phantom fabrication. However, flexible, soft tissue materials are also needed for imaging phantoms for simulating several clinical scenarios where anatomical deformations is important. Recently, various additive manufacturing technologies have been used to produce anatomical models based on extrusion techniques that allow the fabrication of soft tissue materials. To date, there is no systematic study in the literature investigating the radiological properties of silicone rubber materials/fluids for imaging phantoms fabricated directly by extrusion using 3D printing techniques. The aim of this study was to investigate the radiological properties of 3D printed phantoms made of silicone in CT imaging. To achieve this goal, the radiodensity as described as Hounsfield Units (HUs) of several samples composed of three different silicone printing materials were evaluated by changing the infill density to adjust their radiological properties. A comparison of HU values with a Gammex Tissue Characterization Phantom was performed. In addition, a reproducibility analysis was performed by creating several replicas for specific infill densities. A scaled down anatomical model derived from an abdominal CT was also fabricated and the resulting HU values were evaluated. For the three different silicone materials, a spectrum ranging from −639 to +780 HU was obtained on CT at a scan setting of 120 kVp. In addition, using different infill densities, the printed materials were able to achieve a similar radiodensity range as obtained in different tissue-equivalent inserts in the Gammex phantom (238 HU to −673 HU). The reproducibility results showed good agreement between the HU values of the replicas compared to the original samples, confirming the reproducibility of the printed materials. A good agreement was observed between the HU target values in abdominal CT and the HU values of the 3D-printed anatomical phantom in all tissues.

The design of a family of parametric anatomically-based compliant buttock models to evaluate wheelchair cushion performance.

The evaluation of wheelchair cushion performance is of interest to a variety of stakeholders, including standards organizations, cushion manufacturers, clinicians, users and payers. The objective of this project was to develop a family of compliant buttock models that are based upon the anatomical parameters of persons with varying body sizes. The models are parametrically designed so can be scaled to evaluate different sized cushions. This paper will detail the designs, describe the anatomical basis for the design and provide the rationale for the design decisions. The manuscript also serves a secondary purpose to illustrate how anthropometric data can be applied to the design of anatomical phantoms that reflect both soft tissue and skeletal anthropometry. Supplemental material includes greater detail and the full CAD files and model fabrication instructions are available in an open access repository for persons who wish to fabricate the models.