A set of 4D pediatric XCAT reference phantoms for multimodality research

Contrast and quantum noise in single-exposure dual-energy thoracic imaging with photon-counting x-ray detectors

Objective.Photon-counting x-ray detectors (PCDs) can produce dual-energy (DE) x-ray images of lung cancer in a single x-ray exposure. It is important to understand the factors that affect contrast, noise and the contrast-to-noise ratio (CNR). This study quantifies the dependence of CNR on tube voltage, energy threshold and patient thickness in single exposure, DE, bone-suppressed thoracic imaging with PCDs, and elucidates how the fundamental processes inherent in x-ray detection by PCDs contribute to CNR degradation.Approach.We modeled the DE CNR for five theoretical PCDs, ranging from an ideal PCD that detects every primary photon in the correct energy bin while rejecting all scattered radiation to a non-ideal PCD that suffers from charge-sharing and electronic noise, and detects scatter. CNR was computed as a function of tube voltage and high energy threshold for average and larger-than-average patients. Model predictions were compared with experimental data extracted from images acquired using a cadmium telluride (CdTe) PCD with two energy bins and analog charge summing for charge-sharing suppression. The imaging phantom simulated attenuation, scatter and contrast in lung nodule imaging. We quantified CNR improvements achievable with anti-correlated noise reduction (ACNR) and measured the range of exposure rates over which pulse pile-up is negligible.Main Results.The realistic model predicted overall trends observed in the experimental data. CNR improvements with ACNR were approximately five-fold, and modeled CNR-enhancements were on average within 10% of experiment. CNR increased modestly (i.e.<20%) when increasing the tube voltage from 90 kV to 130 kV. Optimal energy thresholds ranged from 50 keV to 70 keV across all tube voltages and patient thicknesses with and without ACNR. Quantum efficiency, electronic noise, charge sharing and scatter degraded CNR by ~50%. Charge sharing and scatter had the largest effect on CNR, degrading it by ~30% and ~15% respectively. Dead-time losses were less than 5% for patient exposure rates within the range of clinical exposure rates.Significance.In this study, we (1) employed analytical and computational models to assess the impact of different factors on CNR in single-exposure DE imaging with PCDs, (2) evaluated the accuracy of these models in predicting experimental trends, (3) quantified improvements in CNR achievable through ACNR and (4) determined the range of patient exposure rates at which pulse pile-up can be considered negligible. To the best of our knowledge, this study represents the first systematic investigation of single-exposure DE imaging of lung nodules with PCDs.

Paediatric Anatomical Models in Radiotherapy Applications

Anatomical models have key applications in radiotherapy, notably to help understand the relationship between radiation dose and risk of developing side effects. This review analyses whether age-specific computational phantoms, developed from healthy subjects and paediatric cancer patient data, are adequate to model a paediatric population. The phantoms used in the study were International Commission on Radiological Protection (ICRP), 4D extended cardiac torso (XCAT) and Radiotherapy Paediatric Atlas (RT-PAL), which were also compared to literature data. Organ volume data for 19 organs was collected for all phantoms and literature. ICRP was treated as the reference for comparison, and percentage difference (P.D) for the other phantoms were calculated relative to ICRP. Overall comparisons were made for each age category (1, 5, 10, 15) and each organ. Statistical analysis was performed using Microsoft Excel (version 16.59). The smallest P.D to ICRP was for Literature (-17.4%), closely followed by XCAT (26.6%). The largest was for RT-PAL (88.1%). The rectum had the largest average P.D (1,049.2%) and the large bowel had the smallest (2.0%). The P.D was 122.6% at age 1 but this decreased to 43.5% by age 15. Linear regression analysis showed a correlation between organ volume and age to be the strongest for ICRP (R2 = 0.943) and weakest for XCAT (R2 = 0.676). The phantoms are similar enough to ICRP for potential use in modelling paediatric populations. ICRP and XCAT could be used to model a healthy population, whereas RT-PAL could be used for a population undergoing/after radiotherapy.

A high-resolution pediatric female whole-body numerical model with comparison to a male model

Objective. Numerical models are central in designing and testing novel medical devices and in studying how different anatomical changes may affect physiology. Despite the numerous adult models available, there are only a few whole-body pediatric numerical models with significant limitations. In addition, there is a limited representation of both male and female biological sexes in the available pediatric models despite the fact that sex significantly affects body development, especially in a highly dynamic population. As a result, we developed Athena, a realistic female whole-body pediatric numerical model with high-resolution and anatomical detail.Approach. We segmented different body tissues through Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) images of a healthy 3.5 year-old female child using 3D Slicer. We validated the high anatomical accuracy segmentation through two experienced sub-specialty-certified neuro-radiologists and the inter and intra-operator variability of the segmentation results comparing sex differences in organ metrics with physiologic values. Finally, we compared Athena with Martin, a similar male model, showing differences in anatomy, organ metrics, and MRI dosimetric exposure.Main results. We segmented 267 tissue compartments, which included 50 brain tissue labels. The tissue metrics of Athena displayed no deviation from the literature value of healthy children. We show the variability of brain metrics in the male and female models. Finally, we offer an example of computing Specific Absorption Rate and Joule heating in a toddler/preschooler at 7 T MRI.Significance. This study introduces a female realistic high-resolution numerical model using MRI and CT scans of a 3.5 year-old female child, the use of which includes but is not limited to radiofrequency safety studies for medical devices (e.g. an implantable medical device safety in MRI), neurostimulation studies, and radiation dosimetry studies. This model will be open source and available on the Athinoula A. Martinos Center for Biomedical Imaging website.

A Fetal Brain magnetic resonance Acquisition Numerical phantom (FaBiAN)

Accurate characterization of in utero human brain maturation is critical as it involves complex and interconnected structural and functional processes that may influence health later in life. Magnetic resonance imaging is a powerful tool to investigate equivocal neurological patterns during fetal development. However, the number of acquisitions of satisfactory quality available in this cohort of sensitive subjects remains scarce, thus hindering the validation of advanced image processing techniques. Numerical phantoms can mitigate these limitations by providing a controlled environment with a known ground truth. In this work, we present FaBiAN, an open-source Fetal Brain magnetic resonance Acquisition Numerical phantom that simulates clinical T2-weighted fast spin echo sequences of the fetal brain. This unique tool is based on a general, flexible and realistic setup that includes stochastic fetal movements, thus providing images of the fetal brain throughout maturation comparable to clinical acquisitions. We demonstrate its value to evaluate the robustness and optimize the accuracy of an algorithm for super-resolution fetal brain magnetic resonance imaging from simulated motion-corrupted 2D low-resolution series compared to a synthetic high-resolution reference volume. We also show that the images generated can complement clinical datasets to support data-intensive deep learning methods for fetal brain tissue segmentation.

Synthetic 4DCT(MRI) lung phantom generation for 4D radiotherapy and image guidance investigations

Purpose

Respiratory motion is one of the major challenges in radiotherapy. In this work, a comprehensive and clinically plausible set of 4D numerical phantoms, together with their corresponding “ground truths,” have been developed and validated for 4D radiotherapy applications.

Methods

The phantoms are based on CTs providing density information and motion from multi‐breathing‐cycle 4D Magnetic Resonance imagings (MRIs). Deformable image registration (DIR) has been utilized to extract motion fields from 4DMRIs and to establish inter‐subject correspondence by registering binary lung masks between Computer Tomography (CT) and MRI. The established correspondence is then used to warp the CT according to the 4DMRI motion. The resulting synthetic 4DCTs are called 4DCT(MRI)s. Validation of the 4DCT(MRI) workflow was conducted by directly comparing conventional 4DCTs to derived synthetic 4D images using the motion of the 4DCTs themselves (referred to as 4DCT(CT)s). Digitally reconstructed radiographs (DRRs) as well as 4D pencil beam scanned (PBS) proton dose calculations were used for validation.

Results

Based on the CT image appearance of 13 lung cancer patients and deformable motion of five volunteer 4DMRIs, synthetic 4DCT(MRI)s with a total of 871 different breathing cycles have been generated. The 4DCT(MRI)s exhibit an average superior–inferior tumor motion amplitude of 7 ± 5 mm (min: 0.5 mm, max: 22.7 mm). The relative change of the DRR image intensities of the conventional 4DCTs and the corresponding synthetic 4DCT(CT)s inside the body is smaller than 5% for at least 81% of the pixels for all studied cases. Comparison of 4D dose distributions calculated on 4DCTs and the synthetic 4DCT(CT)s using the same motion achieved similar dose distributions with an average 2%/2 mm gamma pass rate of 90.8% (min: 77.8%, max: 97.2%).

Conclusion

We developed a series of numerical 4D lung phantoms based on real imaging and motion data, which give realistic representations of both anatomy and motion scenarios and the accessible “ground truth” deformation vector fields of each 4DCT(MRI). The open‐source code and motion data allow foreseen users to generate further 4D data by themselves. These numeric 4D phantoms can be used for the development of new 4D treatment strategies, 4D dose calculations, DIR algorithm validations, as well as simulations of motion mitigation and different online image guidance techniques for both proton and photon radiation therapy.

Development of Chinese mesh-type pediatric reference phantom series and application in dose assessment of Chinese undergoing computed tomography scanning

Pediatric patients are in a growing stage with more dividing cells than adults. Therefore, they are more sensitive to the radiation dose when undergoing computed tomography (CT) scanning. It is necessary and essential to assess the organ absorbed dose and effective dose to children. Monte Carlo simulation with computational phantoms is one of the most used methods for dose calculation in medical imaging and radiotherapy. Because of the vast change of the pediatric body with age increasing, many research groups developed series pediatric phantoms for various ages. However, most of the existing pediatric reference phantoms were developed based on Caucasian populations, which is not conformable to Chinese pediatric patients. The use of different phantoms can contribute to a difference in the dose calculation. To assess the CT dose of Chinese pediatric patients more accurately, we developed the Chinese pediatric reference phantoms series, including the 3-month (CRC3m), 1-year-old (CRC01), 5-year-old (CRC05), 10-year-old (CRC10), 15-year-old male (CRCM15), and a 15-year-old female (CRCF15) phantoms. Furthermore, we applied them to dose assessment of patients undergoing CT scanning. The GE LightSpeed 16 CT scanner was simulated and the paper presents the detailed process of phantoms development and the establishment of the CT dose database (with x-ray tube voltages of 120, 100 and 80 kVp, with collimators of 20, 10, and 5 mm width, with filters for head and body), compares for the 1-year-old results with other results based on different phantoms and analyzes the CT dose calculation results. It was found that the difference in phantoms' characteristics, organ masses and positions had a significant impact on the CT dose calculation outcomes. For the 1-year-old phantom, the dose results of organs fully covered by the x-ray beam were within 10% difference from the results of other studies. For organs partially covered and not covered by the scan range, the maximum differences came up to 84% (stomach dose, chest examinations) and 463% (gonads dose, chest examinations) respectively. The findings are helpful for the dose optimization of Chinese pediatric patients undergoing CT scanning. The developed phantoms could be applied in dose estimation of other medical modalities.

Risk of radiation-induced second malignant neoplasms from photon and proton radiotherapy in paediatric abdominal neuroblastoma

BACKGROUND AND PURPOSE

State-of-the-art radiotherapy modalities have the potential of reducing late effects of treatment in childhood cancer survivors. Our aim was to investigate the carcinogenic risk associated with 3D conformal (photon) radiation (3D-CRT), intensity modulated arc therapy (IMAT) and pencil beam scanning proton therapy (PBS-PT) in the treatment of paediatric abdominal neuroblastoma.

MATERIALS AND METHODS

The risk of radiation-induced second malignant neoplasm (SMN) was estimated using the concept of organ equivalent dose (OED) for eleven organs (lungs, rectum, colon, stomach, small intestine, liver, bladder, skin, central nervous system (CNS), bone, and soft tissues). The risk ratio (RR) between radiotherapy modalities and lifetime absolute risks (LAR) were reported for twenty abdominal neuroblastoma patients (median, 4y; range, 1-9y) historically treated with 3D-CRT that were also retrospectively replanned for IMAT and PBS-PT.

RESULTS

The risk of SMN due to primary radiation was reduced in PBS-PT against 3D-CRT and IMAT for most patients and organs. The RR across all organs ranged from 0.38 ± 0.22 (bladder) to 0.98 ± 0.04 (CNS) between PBS-PT and IMAT, and 0.12 ± 0.06 (rectum and bladder) to 1.06 ± 0.43 (bone) between PBS-PT and 3D-CRT. The LAR for most organs was within 0.01-1% (except the colon) with a cumulative risk of 21 ± 13%, 35 ± 14% and 35 ± 16% for PBS-PT, IMAT and 3D-CRT, respectively.

CONCLUSIONS

PBS-PT was associated with the lowest risk of radiation-induced SMN compared to IMAT and 3D-CRT in abdominal neuroblastoma treatment. Other clinical endpoints and plan robustness should also be considered for optimal plan selection.

Development, validation, and pilot MRI safety study of a high-resolution, open source, whole body pediatric numerical simulation model

Numerical body models of children are used for designing medical devices, including but not limited to optical imaging, ultrasound, CT, EEG/MEG, and MRI. These models are used in many clinical and neuroscience research applications, such as radiation safety dosimetric studies and source localization. Although several such adult models have been reported, there are few reports of full-body pediatric models, and those described have several limitations. Some, for example, are either morphed from older children or do not have detailed segmentations. Here, we introduce a 29-month-old male whole-body native numerical model, "MARTIN", that includes 28 head and 86 body tissue compartments, segmented directly from the high spatial resolution MRI and CT images. An advanced auto-segmentation tool was used for the deep-brain structures, whereas 3D Slicer was used to segment the non-brain structures and to refine the segmentation for all of the tissue compartments. Our MARTIN model was developed and validated using three separate approaches, through an iterative process, as follows. First, the calculated volumes, weights, and dimensions of selected structures were adjusted and confirmed to be within 6% of the literature values for the 2-3-year-old age-range. Second, all structural segmentations were adjusted and confirmed by two experienced, sub-specialty certified neuro-radiologists, also through an interactive process. Third, an additional validation was performed with a Bloch simulator to create synthetic MR image from our MARTIN model and compare the image contrast of the resulting synthetic image with that of the original MRI data; this resulted in a "structural resemblance" index of 0.97. Finally, we used our model to perform pilot MRI safety simulations of an Active Implantable Medical Device (AIMD) using a commercially available software platform (Sim4Life), incorporating the latest International Standards Organization guidelines. This model will be made available on the Athinoula A. Martinos Center for Biomedical Imaging website.

Simultaneous respiratory motion correction and image reconstruction in 4D-multi pinhole small animal SPECT

PURPOSE

Respiratory motion in the chest region during single photon emission computed tomography (SPECT) is a major degrading factor that reduces the accuracy of image quantification. This effect is more notable when the tumor is very small, or the spatial resolution of the imaging system is less than the respiratory motion amplitude. Small animals imaging systems with sub-millimeter spatial resolution need more attention to the respiratory motion for quantitative studies. We developed a motion-embedded four-dimensional (4D)-multi pinhole SPECT (MPS) reconstruction algorithm for respiratory motion correction. This algorithm makes full use of projection statistics for reconstruction of every individual frame.

METHODS

The ROBY phantom with small tumors in liver was generated in eight different phases during one respiratory cycle. The MPS projections were modeled using a fast ray tracing method simulating an MPS acquisition. Individual frames were reconstructed and used for motion estimation. The Demons non-rigid registration algorithm was used to calculate deformation vector fields (DVFs) for simultaneous motion correction and image reconstruction. A motion-embedded 4D-MPS method was used to reconstruct images using all the projections and corresponding DVFs, simultaneously. The 4D-MPS reconstructed images were compared to the low-count single frame (LCSF) reconstructed image, the three-dimensional (3D)-MPS images reconstructed using individual frames, and post reconstruction registration (PRR) that aligns all individual phases to a reference frame using Demons-derived DVFs. The tumor volume relative error (TVE), tumor contrast relative error (TCE), and dice index (DI) for 2, 3, and 4 mm liver were calculated and compared for different reconstruction methods.

RESULTS

For the 4D-MPS reconstruction method, TVE was reduced and DI was higher compared to PRR, 3D-MPS, and LCSF. The extent of the improvement was higher for the small tumor size (i.e. 2 mm). For the biggest tumor in contrast 3 (i.e. 4 mm) TVE for 4D-MPS, PRR, 3D-MPS and, LCSF were 1.33%, 8%, 8%, and 14.67%, respectively.

CONCLUSIONS

The results suggest that motion-embedded 4D-MPS method is an effective and practical way for respiratory motion correction. It reconstructs high quality gated frames while using all projection data to reconstruct each frame.

Size-specific dose estimations for pediatric chest, abdomen/pelvis and head CT scans with the use of GATE

PURPOSE

The purpose of this study is to create an organ dose database for pediatric individuals undergoing chest, abdomen/pelvis, and head computed tomography (CT) examinations, and to report the differences in absorbed organ doses, when anatomical differences exist for pediatric patients.

METHODS

The GATE Monte Carlo (MC) toolkit was used to model the GE BrightSpeed Elite CT model. The simulated scanner model was validated with the standard Computed Tomography Dose Index (CTDI) head phantom. Twelve computational models (2.1-14 years old) were used. First, contributions to effective dose and absorbed doses per CTDI_vol and per 100 mAs were estimated for all organs. Then, doses per CTDI_vol were correlated with patient model weight for the organs inside the scan range for chest and abdomen/pelvis protocols. Finally, effective doses per dose-length product (DLP) were estimated and compared with the conventional conversion k-factors.

RESULTS

The system was validated against experimental CTDI_w measurements. The doses per CTDI_vol and per 100 mAs for selected organs were estimated. The magnitude of the dependency between the dose and the anatomical characteristics was calculated with the coefficient of determination at 0.5-0.7 for the internal scan organs for chest and abdomen/pelvis protocols. Finally, effective doses per DLP were compared with already published data, showing discrepancies between 13 and 29% and were correlated strongly with the total weight (R² > 0.8) for the chest and abdomen protocols.

CONCLUSIONS

Big differences in absorbed doses are reported even for patients of similar age or same gender, when anatomical differences exist on internal organs of the body.

A personalized, Monte Carlo-based method for internal dosimetric evaluation of radiopharmaceuticals in children

PURPOSE

Herein, we introduce a methodology for estimating the absorbed dose in organs at risk that is based on specified clinically derived radiopharmaceutical biodistributions and personalized anatomical characteristics.

METHODS

To evaluate the proposed methodology, we used realistic Monte Carlo (MC) simulations and computational pediatric models to calculate a parameter called in this work the "specific absorbed dose rate" (SADR). The SADR is a unique quantitative metric in that it is specific to a particular organ. It is defined as the absorbed dose rate in an organ when the biodistribution of radioactivity over the whole body is considered. Initially, we applied a validation procedure that calculated specific absorbed fractions (SAFs) from mono-energetic photon sources in the range of 10 keV-2 MeV and compared them with previously published data. We calculated the SADRs for five different radiopharmaceuticals (99m Tc-MDP, 123 I-mIBG, 131 I-MIBG, 131 I-NaI, and 153 Sm-EDTMP) based on their biodistributions at four or five different times; the biodistributions were derived from the clinical scintigraphic data of pediatric patients. We used six models representing male and female patients aged 5, 8, and 14 yr to investigate the absorbed dose variability due to anatomical variations. The GATE Monte Carlo toolkit was used to calculate absorbed doses per organ. Finally, we compared the SADR methodology to that of OLINDA/EXM 1.1 using rescaled masses according to the studied models. Four target organs were considered for calculating the absorbed doses.

RESULTS

The ratios of SAFs calculated with GATE simulations to those based on previously published data were between 0.9 and 2.2 when the liver was used as a source organ. Subsequently, we used GATE to calculate a dataset of SADRs for the six pediatric models. The SADRs for pediatric models whose total body weights ranged from 20 to 40 kg varied up to approximately 90%, whereas those for models of similar body masses varied less than 15%. Finally, we found absorbed dose discrepancies of approximately 10-150% between the SADR methodology and OLINDA for two different radiopharmaceuticals. Absorbed doses from SADRs and from individualized S-values in the same pediatric model differed approximately 1-50%.

CONCLUSIONS

Because pediatric radiopharmaceutical dosimetric estimates demonstrate large variation due to the patient's anatomical characteristics, personalized data should be considered. Using our SADR method in a larger population of phantoms and for a variety of radiopharmaceuticals could enhance the personalization of dosimetry in pediatric nuclear medicine. The proposed methodology provides the advantage of creating time-dependent organ dose rate curves.

Application of the 4-D XCAT Phantoms in Biomedical Imaging and Beyond

The four-dimensional (4-D) eXtended CArdiac-Torso (XCAT) series of phantoms was developed to provide accurate computerized models of the human anatomy and physiology. The XCAT series encompasses a vast population of phantoms of varying ages from newborn to adult, each including parameterized models for the cardiac and respiratory motions. With great flexibility in the XCAT's design, any number of body sizes, different anatomies, cardiac or respiratory motions or patterns, patient positions and orientations, and spatial resolutions can be simulated. As such, the XCAT phantoms are gaining a wide use in biomedical imaging research. There they can provide a virtual patient base from which to quantitatively evaluate and improve imaging instrumentation, data acquisition, techniques, and image reconstruction and processing methods which can lead to improved image quality and more accurate clinical diagnoses. The phantoms have also found great use in radiation dosimetry, radiation therapy, medical device design, and even the security and defense industry. This review paper highlights some specific areas in which the XCAT phantoms have found use within biomedical imaging and other fields. From these examples, we illustrate the increasingly important role that computerized phantoms and computer simulation are playing in the research community.

[Redundancy information-induced image reconstruction for low-dose myocardial perfusion computed tomography]

OBJECTIVE

In the clinic, myocardial perfusion computed tomography (MPCT) imaging is commonly used to detect and assess myocardial ischemia quantitatively. However, repeated scanning on the myocardial region in the cine mode will increase the radiation dose for patients. With lowering radiation dose, the quality of images are degraded by noise induced artifact, which hampers the diagnostic accuracy. Therefore, in this paper, we propose a redundancy information induced iterative reconstruction framework for high quality MPCT images at the case of low dose.

METHODS

MPCT images have redundant structural information within frames and highly similarity between adjacent frames. Inspired by the two properties, in this work we propose a penalized weighted least-squares (PWLS) model incorporating NLM and TV based hybrid constraints, which is referred to as PWLS-aviNLM-TV for simplicity. The proposed algorithm can effectively eliminate noise and artifacts by taking into account the similarity between adjacent frames and redundancy information within frames, which also can improve spatial resolution within frames and maintain temporal resolution.

RESULTS

The experimental results on the 4D extended cardiac-torso (XCAT) phantom and preclinical porcine dataset demonstrates that the PWLS-aviNLM-TV algorithm obtains better performance in terms of noise reduction and artifacts suppression than the PWLS-TV and PWLSaviNLM algorithm. Moreover, the proposed algorithm can preserve the edges and detail information thereby efficiently differentiate ischemia from myocardium.

CONCLUSIONS

The present redundancy information induced reconstruction algorithm can reconstruct high-quality images from low-dose MPCT for better clinical imaging diagnosis.

Feasibility of reducing differences in estimated doses in nuclear medicine between a patient-specific and a reference phantom

The feasibility of reducing the differences between patient-specific internal doses and doses estimated using reference phantoms was evaluated. Relatively simple adjustments to a polygon-surface ICRP adult male reference phantom were applied to fit selected individual dimensions using the software Rhinoceros®4.0. We tested this approach on two patient-specific phantoms: the biggest and the smallest phantoms from the Helmholtz Zentrum München library. These phantoms have unrelated anatomy and large differences in body-mass-index. Three models approximating each patient's anatomy were considered: the voxel and the polygon-surface ICRP adult male reference phantoms and the adjusted polygon-surface reference phantom. The Specific Absorbed Fractions (SAFs) for internal photon and electron sources were calculated with the Monte Carlo code EGSnrc. Employing the time-integrated activity coefficients of a radiopharmaceutical (S)-4-(3-¹⁸F-fluoropropyl)-l-glutamic acid and the calculated SAFs, organ absorbed-dose coefficients were computed following the formalism promulgated by the Committee on Medical Internal Radiation Dose. We compared the absorbed-dose coefficients between each patient-specific phantom and other models considered with emphasis on the cross-fire component. The corresponding differences for most organs were notably lower for the adjusted reference models compared to the case when reference models were employed. Overall, the proposed approach provided reliable dose estimates for both tested patient-specific models despite the pronounced differences in their anatomy. To capture the full range of inter-individual anatomic variability more patient-specific phantoms are required. The results of this test study suggest a feasibility of estimating patient-specific doses within a relative uncertainty of 25% or less using adjusted reference models, when only simple phantom scaling is applied.

IMAGING DOSE OF HUMAN ORGANS FROM kV-CBCT IN IMAGE-GUIDED RADIATION THERAPY

This study investigates dose distribution due to kV cone-beam computed tomography (CBCT) for the patients undergoing CBCT-based image-guided radiation therapy (IGRT). The kV-CBCT provides an efficient image-guidance tool for acquiring the latest volumetric image of a patient's anatomy, and has been being routinely used in clinics for an accurate treatment setup. Imaging radiation doses resulting from six different acquisition protocols of the on-board imager (OBI) were calculated using a Geant4 Application for Tomographic Emission (GATE) Monte Carlo simulation toolkit, and the absorbed doses by various organs were analyzed for the adult and pediatric numerical XCAT phantoms in this study. The calculated organ doses range from 0.1 to 24.1 mGy in the adult phantom, and from 0.1 to 36.8 mGy in the pediatric one. The imaging organ doses to the pediatric phantom turn out to be consistently higher than those to the adult phantom. It is believed that our results would provide reliable data to the clinicians for their making better decisions on CBCT scanning options and would also provide a platform for developing a new kV-CBCT scanning protocol in conjunction with a low-dose capability.

Realistic phantoms to characterize dosimetry in pediatric CT

BACKGROUND

The estimation of organ doses and effective doses for children receiving CT examinations is of high interest. Newer, more realistic anthropomorphic body models can provide information on individual organ doses and improved estimates of effective dose.

MATERIALS AND METHODS

Previously developed body models representing 50th-percentile individuals at reference ages (newborn, 1, 5, 10 and 15 years) were modified to represent 10th, 25th, 75th and 90th height percentiles for both genders and an expanded range of ages (3, 8 and 13 years). We calculated doses for 80 pediatric reference phantoms from simulated chest-abdomen-pelvis exams on a model of a Philips Brilliance 64 CT scanner. Individual organ and effective doses were normalized to dose-length product (DLP) and fit as a function of body diameter.

RESULTS

We calculated organ and effective doses for 80 reference phantoms and plotted them against body diameter. The data were well fit with an exponential function. We found DLP-normalized organ dose to correlate strongly with body diameter (R2>0.95 for most organs). Similarly, we found a very strong correlation with body diameter for DLP-normalized effective dose (R2>0.99). Our results were compared to other studies and we found average agreement of approximately 10%.

CONCLUSION

We provide organ and effective doses for a total of 80 reference phantoms representing normal-stature children ranging in age and body size. This information will be valuable in replacing the types of vendor-reported doses available. These data will also permit the recording and tracking of individual patient doses. Moreover, this comprehensive dose database will facilitate patient matching and the ability to predict patient-individualized dose prior to examination.

Practical Nuclear Medicine and Utility of Phantoms for Internal Dosimetry: XCAT Compared with Zubal

PURPOSE

The absorbed doses for two radioisotopes, 99mTc and 131I, between previously validated Zubal phantom and the recently developed XCAT phantom were compared.

MATERIALS AND METHODS

GATE Monte Carlo code was used to simulate the statistical process of radiation. A XCAT phantom with voxel and matrix sizes similar to a standard Zubal phantom was generated. According to Medical International Radiation Dose formalism, specific absorbed fraction (SAF) values for photons and S-factors for beta particles were tabulated. The amounts of absorbed doses were calculated and compared in different organs.

RESULTS

The differences of gamma radiation doses, SAFs, between Zubal and XCAT are >50% in adrenal from adrenal, pancreas from pancreas and thyroid from thyroid, in lung from kidney, kidneys from lungs and in kidneys from thyroid and thyroid from kidneys. The beta radiation doses differences between Zubal and XCAT are >50% in thyroid from thyroid, bladder from bladder, kidney from kidney, liver from bladder, thyroid from bladder and kidney from thyroid. The size and distances of the organs were different between XCAT and Zubal phantoms. Denoted differences of SAF and S-factors correspond to the different organ geometries in phantoms.

CONCLUSION

The results of absorbed doses in Zubal and XCAT phantoms are different. The variations prohibit easy comparison or interchangeability of dosimetry between these phantoms.

A MONTE-CARLO SIMULATION FRAMEWORK FOR JOINT OPTIMISATION OF IMAGE QUALITY AND PATIENT DOSE IN DIGITAL PAEDIATRIC RADIOGRAPHY

In paediatric radiography, according to the as low as reasonably achievable (ALARA) principle, the imaging task should be performed with the lowest possible radiation dose. This paper describes a Monte-Carlo simulation framework for dose optimisation of imaging parameters in digital paediatric radiography. Patient models with high spatial resolution and organ segmentation enable the simultaneous evaluation of image quality and patient dose on the same simulated radiographic examination. The accuracy of the image simulation is analysed by comparing simulated and acquired images of technical phantoms. As a first application example, the framework is applied to optimise tube voltage and pre-filtration in newborn chest radiography. At equal patient dose, the highest CNR is obtained with low-kV settings in combination with copper filtration.

The development of a population of 4D pediatric XCAT phantoms for imaging research and optimization

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.

Determining organ dose: the holy grail

Among the various metrics to quantify CT radiation dose, organ dose is generally regarded as one of the best to reflect patient radiation burden. Organ dose is dependent on two main factors, namely patient anatomy and irradiation field. An accurate estimation of organ dose requires detailed modeling of both factors. The modeling of patient anatomy needs to reflect the anatomical diversity and complexity across the population so that the attributes of a given clinical patient can be properly accounted for. The modeling of the irradiation field needs to accurately reflect the CT system condition, especially the tube current modulation (TCM) technique. We present an atlas-based method to model patient anatomy via a library of computational phantoms with representative ages, sizes and genders. A clinical patient is matched with a corresponding computational phantom to obtain a representation of patient anatomy. The irradiation field of the CT system is modeled using a validated Monte Carlo simulation program. The tube current modulation profiles are simulated using a manufacturer-generalizable ray-tracing algorithm. Combining the patient model, Monte Carlo results, and TCM profile, organ doses are obtained by multiplying organ dose values from a fixed mA scan (normalized to CTDIvol-normalized, denoted as h organ ) and an adjustment factor that reflects the specific irradiation of each organ. The accuracy of the proposed method was quantified by simulating clinical abdominopelvic examinations of 58 patients. The predicted organ doses showed good agreement with simulated organ dose across all organs and modulation schemes. For an average CTDIvol of a CT exam of 10 mGy, the absolute median error across all organs was 0.64 mGy (-0.21 and 0.97 for 25th and 75th percentiles, respectively). The percentage differences were within 15%. The study demonstrates that it is feasible to estimate organ doses in clinical CT examinations for protocols without and with tube current modulation. The methodology can be used for both prospective and retrospective estimation of organ dose.