Computed Tomography Phantom Research Articles

Evaluation of Image Uniformity and Radiolucency for Computed Tomography Phantom Made of 3-Dimensional Printing of Fused Deposition Modeling Technology by Using Acrylonitrile Butadiene Styrene Resin

Evaluation of Image Uniformity and Radiolucency for Computed Tomography Phantom Made of 3-Dimensional Printing of Fused Deposition Modeling Technology by Using Acrylonitrile Butadiene Styrene Resin

EGS_cbct: Simulation of a fan beam CT and RMI phantom for measured HU verification

IntroductionA mathematical 3D model of an existing computed tomography (CT) scanner was created and used in the EGSnrc-based BEAMnrc and egs_cbct Monte Carlo codes. Simulated transmission dose profiles of a RMI-465 phantom were analysed to verify Hounsfield numbers against measured data obtained from the CT scanner. Methods and materialsThe modelled CT unit is based on the design of a Toshiba Aquilion 16 LB CT scanner. As a first step, BEAMnrc simulated the X-ray tube, filters, and secondary collimation to obtain phase space data of the X-ray beam. A bowtie filter was included to create a more uniform beam intensity and to remove the beam hardening effects. In a second step the Interactive Data Language (IDL) code was used to build an EGSPHANT file that contained the RMI phantom which was used in egs_cbct simulations. After simulation a series of profiles were sampled from the detector model and the Feldkamp-Davis-Kress (FDK) algorithm was used to reconstruct transversal images. The results were tested against measured data obtained from CT scans. ResultsThe egs_cbct code can be used for the simulation of a fan beam CT unit. The calculated bowtie filter ensured a uniform flux on the detectors. Good correlation between measured and simulated CT numbers was obtained. ConclusionsIn principle, Monte Carlo codes such as egs_cbct can model a fan beam CT unit. After reconstruction, the images contained Hounsfield values comparable to measured data.

MO-DE-207B-04: Impact of Reconstruction Field of View On Radiomics Features in Computed Tomography (CT) Using a Texture Phantom

Purpose: To investigate the impact of reconstruction Field of View on Radiomics features in computed tomography (CT) using a texture phantom. Methods: A rectangular Credence Cartridge Radiomics (CCR) phantom, composed of 10 different cartridges, was scanned on four different CT scanners from two manufacturers. A pre-defined scanning protocol was adopted for consistency. The slice thickness and reconstruction interval of 1.5 mm was used on all scanners. The reconstruction FOV was varied to result a voxel size ranging from 0.38 to 0.98 mm. A spherical region of interest (ROI) was contoured on the shredded rubber cartridge from CCR phantom CT scans. Ninety three Radiomics features were extracted from ROI using an in-house program. These include 10 shape, 22 intensity, 26 GLCM, 11 GLZSM, 11 RLM, 5 NGTDM and 8 fractal dimensional features. To evaluate the Interscanner variability across three scanners, a coefficient of variation (COV) was calculated for each feature group. Each group was further classified according to the COV by calculating the percentage of features in each of the following categories: COV≤ 5%, between 5 and 10% and ≥ 10%. Results: Shape features were the most robust, as expected, because of the spherical contouring of ROI. Intensity features were the second most robust with 54.5 to 64% of features with COV < 5%. GLCM features ranged from 31 to 35% for the same category. RLM features were sensitive to specific scanner and 5% variability was 9 to 54%. Almost all GLZM and NGTDM features showed COV ≥10% among the scanners. The dependence of fractal dimensions features on FOV was not consistent across different scanners. Conclusion: We concluded that reconstruction FOV greatly influence Radiomics features. The GLZSM and NGTDM are highly sensitive to FOV. funded in part by Grant NIH/NCI R01CA190105-01

Fabrication and control of CT number through polymeric composites based on coronary plaque CT phantom applications.

Biomedical phantoms are commonly used for various medical imaging modalities to improve imaging quality and procedures. Current biomedical phantoms fabricated commercially are high in cost and limited in the specificity of human environments and structures that can be mimicked. This study aimed to control the measurable computed tomography (CT) number in Hounsfield units through polymeric biomedical phantom materials using controlled amounts of hydroxyapatite (hA). The purpose was to fabricate CT phantoms capable of mimicking various coronary plaque types while introducing a fabrication technique and basis for a numerical model to which the technique may be applied. The CT number is tunable based on the controlled material properties of electron density and atomic numbers. Three different polymeric matrices of polyethylene (PE), thermoplastic polyurethane (TPU), and polyvinylidene fluoride (PVDF) were selected due to their varied specific densities and ease of fabrication acting as integral properties for CT phantom fabrication. These polymers were processed together with additions of hA in mass percentages of 2.5, 5, 10, and 20%hA as well as a 0%hA as a control for each polymeric material. By adding hA to PE, TPU, and PVDF an increasing trend was exhibited between CT number and weight percent of hA.

Automatic Synthesis of Anthropomorphic Pulmonary CT Phantoms.

The great density and structural complexity of pulmonary vessels and airways impose limitations on the generation of accurate reference standards, which are critical in training and in the validation of image processing methods for features such as pulmonary vessel segmentation or artery–vein (AV) separations. The design of synthetic computed tomography (CT) images of the lung could overcome these difficulties by providing a database of pseudorealistic cases in a constrained and controlled scenario where each part of the image is differentiated unequivocally. This work demonstrates a complete framework to generate computational anthropomorphic CT phantoms of the human lung automatically. Starting from biological and image-based knowledge about the topology and relationships between structures, the system is able to generate synthetic pulmonary arteries, veins, and airways using iterative growth methods that can be merged into a final simulated lung with realistic features. A dataset of 24 labeled anthropomorphic pulmonary CT phantoms were synthesized with the proposed system. Visual examination and quantitative measurements of intensity distributions, dispersion of structures and relationships between pulmonary air and blood flow systems show good correspondence between real and synthetic lungs (p > 0.05 with low Cohen’s d effect size and AUC values), supporting the potentiality of the tool and the usefulness of the generated phantoms in the biomedical image processing field.

Evaluation of single-photon emission computed tomography images obtained with and without copper filter by segmentation.

Background:Measurement of accurate attenuation of photon flux in tissue is important to obtain reconstructed images using single-photon emission computed tomography (SPECT). Computed tomography (CT) scanner provides attenuation correction data for SPECT as well as anatomic information for diagnostic purposes. Segmentation is a process of dividing an image into regions having similar properties such as gray level, color, texture, brightness, and contrast. Image segmentation is an important tool for evaluation of medical images. X-ray beam used in CT scan is poly-energetic; therefore, we have used a copper filter to remove the low energy X-rays for obtaining correct attenuation factor. Images obtained with and without filters were quantitatively evaluated by segmentation method to avoid human error.Materials and Methods:Axial images of AAPM CT phantom were acquired with 3 mm copper filter (low intensity) and without copper filter (high intensity) using low-dose CT (140 kvp and 2.5 mA) of SPECT/CT system (Hawkeye, GE Healthcare). For segmentation Simulated Annealing Based Fuzzy c-means, algorithm is applied. Quantitative measurement of quality is done based on universal image quality index. Further, for the validation of attenuation correction map of filtered CT images, Jaszczak SPECT phantom was filled with 500 MBq of 99mTc and SPECT study was acquired. Low dose CT images were acquired for attenuation correction to be used for reconstruction of SPECT images. Another set of CT images were acquired after applying additional 3 mm copper filter. Two sets of axial SPECT images were reconstructed using attenuation map from both the CT images obtained without and with a filter.Results and Conclusions:When we applied Simulated Annealing Based Fuzzy c-means segmentation on both the CT images, the CT images with filter shows remarkable improvement and all the six section of the spheres in the Jaszczak SPECT phantom were clearly visualized.

Computational and human observer image quality evaluation of low dose, knowledge-based CT iterative reconstruction.

Aims in this study are to (1) develop a computational model observer which reliably tracks the detectability of human observers in low dose computed tomography (CT) images reconstructed with knowledge-based iterative reconstruction (IMR™, Philips Healthcare) and filtered back projection (FBP) across a range of independent variables, (2) use the model to evaluate detectability trends across reconstructions and make predictions of human observer detectability, and (3) perform human observer studies based on model predictions to demonstrate applications of the model in CT imaging. Detectability (d') was evaluated in phantom studies across a range of conditions. Images were generated using a numerical CT simulator. Trained observers performed 4-alternative forced choice (4-AFC) experiments across dose (1.3, 2.7, 4.0 mGy), pin size (4, 6, 8 mm), contrast (0.3%, 0.5%, 1.0%), and reconstruction (FBP, IMR), at fixed display window. A five-channel Laguerre-Gauss channelized Hotelling observer (CHO) was developed with internal noise added to the decision variable and/or to channel outputs, creating six different internal noise models. Semianalytic internal noise computation was tested against Monte Carlo and used to accelerate internal noise parameter optimization. Model parameters were estimated from all experiments at once using maximum likelihood on the probability correct, PC. Akaike information criterion (AIC) was used to compare models of different orders. The best model was selected according to AIC and used to predict detectability in blended FBP-IMR images, analyze trends in IMR detectability improvements, and predict dose savings with IMR. Predicted dose savings were compared against 4-AFC study results using physical CT phantom images. Detection in IMR was greater than FBP in all tested conditions. The CHO with internal noise proportional to channel output standard deviations, Model-k4, showed the best trade-off between fit and model complexity according to AICc. With parameters fixed, the model reasonably predicted detectability of human observers in blended FBP-IMR images. Semianalytic internal noise computation gave results equivalent to Monte Carlo, greatly speeding parameter estimation. Using Model-k4, the authors found an average detectability improvement of 2.7 ± 0.4 times that of FBP. IMR showed greater improvements in detectability with larger signals and relatively consistent improvements across signal contrast and x-ray dose. In the phantom tested, Model-k4 predicted an 82% dose reduction compared to FBP, verified with physical CT scans at 80% reduced dose. IMR improves detectability over FBP and may enable significant dose reductions. A channelized Hotelling observer with internal noise proportional to channel output standard deviation agreed well with human observers across a wide range of variables, even across reconstructions with drastically different image characteristics. Utility of the model observer was demonstrated by predicting the effect of image processing (blending), analyzing detectability improvements with IMR across dose, size, and contrast, and in guiding real CT scan dose reduction experiments. Such a model observer can be applied in optimizing parameters in advanced iterative reconstruction algorithms as well as guiding dose reduction protocols in physical CT experiments.

Adaptive iterative dose reduction 3D (AIDR 3D) vs. filtered back projection: radiation dose reduction capabilities of wide volume and helical scanning techniques on area-detector CT in a chest phantom study.

Computed tomography (CT) has important roles for lung cancer screening, and therefore radiation dose reduction by using iterative reconstruction technique and scanning methods receive widespread attention. To evaluate the effect of two reconstruction techniques (filtered back projection [FBP] and adaptive iterative dose reduction using three-dimensional processing [AIDR 3D]) and two acquisition techniques (wide-volume scan [WVS] and helical scan as 64-detector-row CT [64HS]) on the lung nodule identifications of using a chest phantom. A chest CT phantom including lung nodules was scanned using WVS and 64HS at nine different tube currents (TCs; range, 270-10 mA). All CT datasets were reconstructed with AIDR 3D and FBP. Standard deviation (SD) measurements by region of interest placement and qualitative nodule identifications were statistically compared. 64HS and WVS were evaluated separately, and FBP images acquired with 270 mA was defined as the standard reference. SDs of all datasets with AIDR 3D showed no significant differences (P > 0.05) with standard reference. When comparing nodule identifications, area under the curve on WVS with AIDR 3D with TC <30 mA, on 64HS with AIDR 3D with TC <40 mA, and on reconstructions with FBP and each scan method with TC <60 mA was significantly lower than with standard reference (P < 0.05). With the same TC and reconstruction, SDs and nodule identifications of WVS were not significantly different from 64HS (P > 0.05). In term of SD of lung parenchyma and nodule identification, AIDR 3D can achieve more radiation dose reduction than FBP and there is no significant different between WVS and 64HS.

Dedicated mobile volumetric cone-beam computed tomography for human brain imaging: A phantom study.

Mobile computed tomography (CT) with a cone-beam source is increasingly used in the clinical field. Mobile cone-beam CT (CBCT) has great merits; however, its clinical utility for brain imaging has been limited due to problems including scan time and image quality. The aim of this study was to develop a dedicated mobile volumetric CBCT for obtaining brain images, and to optimize the imaging protocol using a brain phantom. The mobile volumetric CBCT system was evaluated with regards to scan time and image quality, measured as signal-to-noise-ratio (SNR), contrast-to-noise-ratio (CNR), spatial resolution (10% MTF), and effective dose. Brain images were obtained using a CT phantom. The CT scan took 5.14 s at 360 projection views. SNR and CNR were 5.67 and 14.5 at 120 kV/10 mA. SNR and CNR values showed slight improvement as the x-ray voltage and current increased (p < 0.001). Effective dose and 10% MTF were 0.92 mSv and 360 μ m at 120 kV/10 mA. Various intracranial structures were clearly visible in the brain phantom images. Using this CBCT under optimal imaging acquisition conditions, it is possible to obtain human brain images with low radiation dose, reproducible image quality, and fast scan time.

Concomitant Imaging Dose and Cancer Risk in Image Guided Thoracic Radiation Therapy

Kilovoltage cone beam computed tomography (CT) (kVCBCT) imaging guidance improves the accuracy of radiation therapy but imposes an extra radiation dose to cancer patients. This study aimed to investigate concomitant imaging dose and associated cancer risk in image guided thoracic radiation therapy. The planning CT images and structure sets of 72 patients were converted to CT phantoms whose chest circumferences (Cchest) were calculated retrospectively. A low-dose thorax protocol on a Varian kVCBCT scanner was simulated by a validated Monte Carlo code. Computed doses to organs and cardiac substructures (for 5 selected patients of various dimensions) were regressed as empirical functions of Cchest, and associated cancer risk was calculated using the published models. The exposures to nonthoracic organs in children were also investigated. The structural mean doses decreased monotonically with increasing Cchest. For all 72 patients, the median doses to the heart, spinal cord, breasts, lungs, and involved chest were 1.68, 1.33, 1.64, 1.62, and 1.58 cGy/scan, respectively. Nonthoracic organs in children received 0.6 to 2.8 cGy/scan if they were directly irradiated. The mean doses to the descending aorta (1.43 ± 0.68 cGy), left atrium (1.55 ± 0.75 cGy), left ventricle (1.68 ± 0.81 cGy), and right ventricle (1.85 ± 0.84 cGy) were significantly different (P<.05) from the heart mean dose (1.73 ± 0.82 cGy). The blade shielding alleviated the exposure to nonthoracic organs in children by an order of magnitude. As functions of patient size, a series of models for personalized estimation of kVCBCT doses to thoracic organs and cardiac substructures have been proposed. Pediatric patients received much higher doses than did the adults, and some nonthoracic organs could be irradiated unexpectedly by the default scanning protocol. Increased cancer risks and disease adverse events in the thorax were strongly related to higher imaging doses and smaller chest dimensions.

SU‐E‐T‐52: A New Device for Quality Assurance of a Single Isocenter Technique for the Simultaneous Treatment of Multiple Brain Metastases

Purpose:Comprehensive quality assurance (QA) of a single isocenter technique for the simultaneous treatment of multiple brain metastases is presently impractical due to the time consuming nature of measuring each lesion's dose on film or with a micro‐chamber. Three dimensional diode array and full field film measurements are sometimes used to evaluate these plans, but gamma analysis may not reveal local errors that have significant effects on one or a few of several targets. This work aimed to design, build and test a phantom to simplify comprehensive measurement and evaluation.Methods:A phantom was designed with 28 stackable slabs. The top and bottom slabs are 1.5 centimeters (cm) in thickness, and central 26 slabs are 0.5 cm thick. When assembled with radiochromic film in all 27 gaps, the phantom measures 16.5 × 15 × 19 cm. Etchings were designed to aide in identification of specific film planes on computed tomography (CT) images and correlation of individual PTVs with closest bisecting planes. Patient verification plans with a total of 16 PTVs were calculated on the phantom CT, and test deliveries both with and without couch kicks were performed to test the ability to identify correct film placements and subsequent PTV specific dose distributions on the films.Results:Bisecting planes corresponding to PTV locations were easily identified, and PTV specific dose distributions were clear for all 16 targets. For deliveries with couch kicks, the phantom PTV dose distributions closely approximated those calculated on the patient's CT. For deliveries without couch kicks, PTV specific dosimetry was also possible, although the distributions had ‘ghosts’ equaling the number of couch kicks, with distance between ghosts increasing with distance from the isocenter.Conclusion:A new phantom facilitates fast comprehensive commissioning validation and PTV specific dosimetry for a single isocenter technique for treating multiple brain metastases.This work was partially funded by CIRS, Inc.

An assessment of image distortion and CT number accuracy within a wide-bore CT extended field of view.

Although wide bore computed tomography (CT) scanners provide increased space for patients, the scan field of view (sFOV) remains considerably smaller than the bore size. Consequently, patient anatomy which spans beyond the sFOV is truncated and the information is lost. As a solution, some manufacturers provide the capacity to reconstruct CT images from a partial dataset at an extended field of view (eFOV). To assess spatial distortion within this eFOV three phantoms were considered a 30×30×20cm(3) slab of solid water, the Gammex electron density CT phantom and a female anthropomorphic phantom. For each phantom, scans were taken centrally within the sFOV as a reference image and with the phantom edge extended at 1cm intervals from 0 to 5cm beyond the sFOV into the eFOV. To assess CT number accuracy various tissue equivalent materials were scanned in the eFOV and resulting CT numbers were compared to inserts scanned within the sFOV. For all phantom geometries, objects within the eFOV were geometrically overestimated with elongation of phantom shapes into the eFOV. The percentage increase in size ranged from 0.22 to 15.94% over all phantoms considered. The difference between eFOV and sFOV CT numbers was dependent upon insert density. The eFOV underestimated CT numbers in the range of -127 to -230HU for soft tissue densities and -278 to -640 for bone densities. This trend reversed for low tissue densities with the CT numbers in the eFOV being overestimated by 100-130 HU for lung equivalent inserts. Initial correlation between eFOV and sFOV CT numbers was seen and a correction function was successfully applied to better estimate the CT number representative of that seen within the sFOV.

WE-D-BRA-05: Pseudo In Vivo Patient Dosimetry Using a 3D-Printed Patient-Specific Phantom

Purpose: To test the feasibility of using 3D-printed patient-specific phantoms for intensity-modulated radiation therapy (IMRT) quality assurance (QA). Methods: We created a patient-specific whole-head phantom using a 3D printer. The printer data file was created from high-resolution DICOM computed tomography (CT) images of 3-year old child treated at our institution for medulloblastoma. A custom-modified extruder system was used to create tissue-equivalent materials. For the printing process, the Hounsfield Units from the CT images were converted to proportional volumetric densities. A 5-field IMRT plan was created from the patient CT and delivered to the 3D- phantom. Dose was measured by an ion chamber placed through the eye. The ion chamber was placed at the posterior edge of the planning target volume in a high dose gradient region. CT scans of the patient and 3D-phantom were fused by using commercial treatment planning software (TPS). The patient's plan was calculated on the phantom CT images. The ion chamber's active volume was delineated in the TPS; dose per field and total dose were obtained. Measured and calculated doses were compared. Results: The 3D-phantom dimensions and tissue densities were in good agreement with the patient. However, because of a printing error, there was a large discrepancy in the density in the frontal cortex. The calculated and measured treatment plan doses were 1.74 Gy and 1.72 Gy, respectively. For individual fields, the absolute dose difference between measured and calculated values was on average 3.50%. Conclusion: This study demonstrated the feasibility of using 3D-printed patient-specific phantoms for IMRT QA. Such phantoms would be particularly advantageous for complex IMRT treatment plans featuring high dose gradients and/or for anatomical sites with high variation in tissue densities. Our preliminary findings are promising. We anticipate that, once the printing process is further refined, the agreement between measured and calculated doses will improve.

Installation of a Neuromate Robot for Stereotactic Surgery: Efforts to Conform to Japanese Specifications and an Approach for Clinical Use-Technical Notes.

The neuromate is a commercially available, image-guided robotic system for use in stereotactic surgery and is employed in Europe and North America. In June 2015, this device was approved in accordance with the Pharmaceutical Affairs Law in Japan. The neuromate can be specified to a wide range of stereotactic procedures in Japan. The stereotactic X-ray system, developed by a Japanese manufacturer, is normally attached to the operating table that provides lateral and anteroposterior images to verify the positions of the recording electrodes. The neuromate is designed to be used with the patient in the supine position on a flat operating table. In Japan, deep brain stimulation surgery is widely performed with the patient's head positioned upward so as to minimize cerebrospinal fluid leakage. The robot base where the patient's head is fixed has an adaptation for a tilted head position (by 25 degrees) to accommodate the operating table at proper angle to hold the patient's upper body. After these modifications, the accuracy of neuromate localization was examined on a computed tomography phantom preparation, showing that the root mean square error was 0.12 ± 0.10 mm. In our hospital, robotic surgeries, such as those using the Da Vinci system or neuromate, require operative guidelines directed by the Medical Risk Management Office and Biomedical Research and Innovation Office. These guidelines include directions for use, procedural manuals, and training courses.

Monte Carlo calculated CT numbers for improved heavy ion treatment planning

Abstract Better knowledge of CT number values and their uncertainties can be applied to improve heavy ion treatment planning. We developed a novel method to calculate CT numbers for a computed tomography (CT) scanner using the Monte Carlo (MC) code, BEAMnrc/EGSnrc. To generate the initial beam shape and spectra we conducted full simulations of an X-ray tube, filters and beam shapers for a Siemens Emotion CT. The simulation output files were analyzed to calculate projections of a phantom with inserts. A simple reconstruction algorithm (FBP using a Ram-Lak filter) was applied to calculate the pixel values, which represent an attenuation coefficient, normalized in such a way to give zero for water (Hounsfield unit (HU)). Measured and Monte Carlo calculated CT numbers were compared. The average deviation between measured and simulated CT numbers was 4 ± 4 HU and the standard deviation σ was 49 ± 4 HU. The simulation also correctly predicted the behaviour of H-materials compared to a Gammex tissue substitutes. We believe the developed approach represents a useful new tool for evaluating the effect of CT scanner and phantom parameters on CT number values.

A training phantom for ultrasound-guided needle insertion and suturing

During gynecologic brachytherapy (BT), suturing and image-guided needle insertions are highly skill-dependent tasks. Medical residents often have to practice these techniques in the operating room; this is sub-optimal for many reasons. We present a fast and low-cost method of building realistic and disposable gynecologic phantoms, which can be used to train physicians new to gynecologic BT. Phantoms comprised a rectal cavity large enough to accommodate a standard transrectal ultrasound (US) probe, a vaginal cavity, a uterus, a uterine canal, and a cervix, all embedded in a gelatin matrix. The uterus was made of gelatin and coated with rubber to mimic the texture of soft tissue and for computed tomography (CT) and US image contrast. The phantom's durability, longevity, construction times, materials costs, CT, and US image quality were recorded. The speed of sound in the gelatin was measured using pulse echo measurements. Anatomic structures were distinguishable using CT and US. For the first phantom, material costs were under $200, curing time was approximately 48 hours, and active participation time was 3 hours. Reusable parts allowed for reduction in time and cost for subsequent phantoms: under $20, 24 hours curing time, and 1 hour active participation time. The speed of sound in the gelatin ranged from 1495 to 1506m/s. A method for constructing gelatin gynecologic phantoms was developed. It can be used for training in image-guided BT needle insertion, placing a suture on the vaginal wall, and suturing the cervical lip.

Optimization of CT procedures in two radiology departments

Optimization of CT procedures in two radiology departments

Accuracy of 3D fluoroscopy in cranial stereotactic surgery: A comparative study in phantoms and patients

To assess the precision and accuracy of 3D fluoroscopy (XT) in phantoms and patients compared to computed tomography (CT) in localizing stereotactic probes. Approval was obtained from the institutional research ethics board. The prospective phantom study was compared to a retrospective patient cohort. Accuracy was assessed by the mean error and precision by the mean dispersion between XT and CT with a cubic or a skull phantom containing metallic spheres installed on plates or along trajectories. Significance was assessed by Friedman's and Levene's test. Secondary endpoints were Euclidean error, other influences e.g. installed frame and radiation exposure. A total of 3,342 distances were assessed in 17 XT and 13 CT phantom scans. The cubic phantom showed mean distance errors of 0.33 mm (SD + -0.46 mm) for XT compared to 0.19 mm (SD + -0.83 mm) for CT scans (p = 0.0004) and a dispersion of 0.22 mm (XT) and 0.70 mm (CT). The dispersion was 0.36 mm with and 0.63 mm without a stereotactic frame (p < 0.0001). The mean Euclidean error was 0.72 mm (SD + -0.59 mm) in the skull phantom and 1.34 mm (SD + -0.82 mm) in the patient cohort. The effective dose was 0.65 mSv for the XT and 1.12 mSv for the CT. The accuracy of XT imaging in phantoms revealed a slightly lower accuracy but higher precision than the CT. The overall accuracy of XT was higher than that of the stereotactic frame allowing stereotactic localization with about half of the effective dose of a CT-scan.

Creation and Characterization of an Ultrasound and CT Phantom for Noninvasive Ultrasound Thermometry Calibration

Ultrasound thermometry provides noninvasive 2-D temperature monitoring, and in this paper, we have investigated the use of computed tomography (CT) radiodensity to characterize tissues to improve the accuracy of ultrasound thermometry. Agarose-based tissue-mimicking phantoms were created with glyceryl trioleate (a fat-mimicking material) concentration of 0%, 10%, 20%, 30%, 40%, and 50%. The speed of sound (SOS) of the phantoms was measured over a temperature range of 22.1-41.1 °C. CT images of the phantoms were acquired by a clinical dedicated breast CT scanner, followed by calculation of the Hounsfield units (HU). The phantom was heated with a therapeutic acoustic pulse (1.54 MHz), while RF data were acquired with a 10-MHz linear-array transducer. Two-dimensional speckle tracking was used to calculate the thermal strain offline. The tissue-dependent thermal strain parameter required for ultrasound thermometry was analyzed and correlated with CT radiodensity, followed by the validation of the temperature prediction. Results showed that the change in SOS with the temperature increase was opposite in sign between the 0%-10% and 20%-50% trioleate phantoms. The inverse of the tissue-dependent thermal strain parameter of the phantoms was correlated with the CT radiodensity (R(2) = 0.99). A blinded ultrasound thermometry study on phantoms with a trioleate range of 5%-35% demonstrated the capability to estimate the tissue-dependent thermal strain parameter and estimate temperature with error less than ~1 °C. In conclusion, CT radiodensity may provide a method for improving ultrasound thermometry in heterogeneous tissues.

Low-dose computed tomography via spatially adaptive Monte–Carlo reconstruction

Low-dose computed tomography (CT) reduces radiation exposure but decreases signal-to-noise ratio (SNR) and diagnostic capabilities. Noise compensation can improve SNR so low-dose CT can provide valuable information for diagnosis without risking patient radiation exposure. In this study, a novel noise-compensated CT reconstruction method that uses spatially adaptive Monte–Carlo sampling to produce noise-compensated reconstructions is investigated. By adapting to local noise statistics, a non-parametric estimation of the noise-free image is computed that successfully handles non-stationary noise found in low-dose CT images. Using phantom and real low-dose CT images, effective noise suppression is shown to be accomplished while maintaining structures and details.