Specific CT Scanner Research Articles

Methodology for computed tomography characterization of commercially available 3D printing materials for use in radiology/radiation oncology.

3D printing in medical physics provides opportunities for creating patient-specific treatment devices and in-house fabrication of imaging/dosimetry phantoms. This study characterizes several commercial fused deposition 3D printing materials with some containing nonstandard compositions. It is important to explore their similarities to human tissues and other materials encountered in patients. Uniform cylinders with infill from 50 to 100% at six evenly distributed intervals were printed using 13 different filaments. A novel approach rotating infill angle 10o between each layer avoids unwanted patterns. Five materials contained high-Z/metallic components. A clinical CT scanner with a range of tube potentials (70, 80, 100, 120, 140 kVp) was used. Density and average Hounsfield unit (HU) were measured. A commercial GAMMEX phantom mimicking various human tissues provides a comparison. Utility of the lookup tables produced is demonstrated. A methodology for calibrating print materials/parameters for a desired HU is presented. Density and HU were determined for all materials as a function of tube voltage (kVp) and infill percentage. The range of HU (-732.0-10047.4 HU) and physical densities (0.36-3.52g/cm3 ) encompassed most tissues/materials encountered in radiology/radiotherapy applications with many overlapping those of human tissues. Printing filaments doped with high-Z materials demonstrated increased attenuation due to the photoelectric effect with decreased kVp, as found in certain endogenous materials (e.g., bone). HU was faithfully reproduced (within one standard deviation) in a 3D-printed mimic of a commercial anthropomorphic phantom section. Characterization of commercially available 3D print materials facilitates custom object fabrication for use in radiology and radiation oncology, including human tissue and common exogenous implant mimics. This allows for cost reduction and increased flexibility to fabricate novel phantoms or patient-specific devices imaging and dosimetry purposes. A formalism for calibrating to specific CT scanner, printer, and filament type/batch is presented. Utility is demonstrated by printing a commercial anthropomorphic phantom copy.

PO-1628 Evaluation of material properties retrieved with a radiotherapy specific CT scanner

PO-1628 Evaluation of material properties retrieved with a radiotherapy specific CT scanner

Erratum to Medical Physics article "Principles and applications of multienergy CT: Report of AAPM Task Group 291"

In AAPM Report 291, “Principles and applications of multienergy CT: Report of AAPM Task Group 291,”1 scientists from Canon Medical Systems Corporation, GE Healthcare Technologies, Philips Healthcare, and Siemens Healthcare GmbH participated as authors and contributed sections to describe, in general, the technology used in their company’s dual- or multi-energy CT systems. Specific scanner models were sometimes mentioned to provide examples of the overall approach. The general statements made about the approach may not, however, apply to the specific scanner model used as an example. The intermingling of the general and specific statements is regrettable, as it is ready source of potential confusion. Readers should view each section as a description of an overall dual- or multi-energy CT approach, even if a specific scanner model is mentioned as an example. Readers should refer to manufacturer specifications and the published literature to assess the specifications and performance of a specific CT system. A numerical error exists on page e895 in the second paragraph of the limitations section for kV switching. The statement “… so the system software currently prevents the use of gantry rotation times of less than approximately 500 ms, which may limit the quality of cardiac examinations,” implies that a minimum 500 ms rotation time applies to the scanner used as an example in the kV switching setting (GE Discovery CT750 HD). However, this value (500 msec) does not reflect the minimum rotation time on the GE Discovery CT750 HD. Rather, from the earliest publications on the use of this specific CT scanner model for dual-energy cardiac imaging, the minimum rotation time of 350 ms was used.2, 3 The second and third paragraphs in this same section on the limitations of kV switching reiterate the physics principles discussed on page e894, at the top of the second. Namely, as first demonstrated in 1979 by Kelcz et al., decreased spectral separation causes increased noise in decomposed material-specific images.4 In 2009, Primak et al. demonstrated that tube-specific filtration can increase spectral separation and decrease image noise in material decomposed images using a commercial dual-source CT system.5 While spectral separation is indeed an important determinant of the underlying noise properties of the acquired data, noise reduction methods can be applied such that the material decomposition calculations performed using kV switching (or other non-dual-source approaches) can also yield accurate quantification of iodine concentration.6

Evaluation of CT calibration curves from stoichiometric and tissue substitute methods according to tissue characteristics

In order to optimize and increase the precision of dose determination, it is important to obtain the relationship between CT Hounsfield units and electron densities, as the basic inputs for radiotherapy planning systems. Therefore, the aim of this study was to plot and compare the CT calibration curves resulted from both tissue substitute calibration (based on the tissue equivalent materials) and stoichiometric calibration (based on biological tissues) methods for a specific CT scanner at tube voltage of 120 kVp by applying a precise homemade physical phantom. Hence, the Hounsfield units of all phantom materials were measured experimentally and also calculated by related formulas. Considering the CT numbers and the electron densities of various tissue equivalent materials and real tissues, the calibration curves were plotted. According to the results, the higher accuracy of the stoichiometric method relative to tissue substitute method was confirmed in this study. On the other hand, since estimating Hounsfield unit of each human tissue strongly depends on the physical properties of tissue substitutes of the physical phantom, the high precision of this phantom led to increase the accuracy of the calibration curves obtained based on the stoichiometric method.

Monte Carlo proton dose calculations using a radiotherapy specific dual-energy CT scanner for tissue segmentation and range assessment

Proton beam ranges derived from dual-energy computed tomography (DECT) images from a dual-spiral radiotherapy (RT)-specific CT scanner were assessed using Monte Carlo (MC) dose calculations. Images from a dual-source and a twin-beam DECT scanner were also used to establish a comparison to the RT-specific scanner. Proton ranges extracted from conventional single-energy CT (SECT) were additionally performed to benchmark against literature values. Using two phantoms, a DECT methodology was tested as input for Geant4 MC proton dose calculations. Proton ranges were calculated for different mono-energetic proton beams irradiating both phantoms; the results were compared to the ground truth based on the phantom compositions. The same methodology was applied in a head-and-neck cancer patient using both SECT and dual-spiral DECT scans from the RT-specific scanner. A pencil-beam-scanning plan was designed, which was subsequently optimized by MC dose calculations, and differences in proton range for the different image-based simulations were assessed. For phantoms, the DECT method yielded overall better material segmentation with >86% of the voxel correctly assigned for the dual-spiral and dual-source scanners, but only 64% for a twin-beam scanner. For the calibration phantom, the dual-spiral scanner yielded range errors below 1.2 mm (0.6% of range), like the errors yielded by the dual-source scanner (<1.1 mm, <0.5%). With the validation phantom, the dual-spiral scanner yielded errors below 0.8 mm (0.9%), whereas SECT yielded errors up to 1.6 mm (2%). For the patient case, where the absolute truth was missing, proton range differences between DECT and SECT were on average in −1.2 ± 1.2 mm (−0.5% ± 0.5%). MC dose calculations were successfully performed on DECT images, where the dual-spiral scanner resulted in media segmentation and range accuracy as good as the dual-source CT. In the patient, the various methods showed relevant range differences.

Implementation of Size-Dependent Local Diagnostic Reference Levels for CT Angiography.

Diagnostic reference levels (DRLs) are established for standard-sized patients; however, patient dose in CT depends on patient size. The purpose of this study was to introduce a method for setting size-dependent local diagnostic reference levels (LDRLs) and to evaluate these LDRLs in comparison with size-independent LDRLs and with respect to image quality. One hundred eighty-four aortic CT angiography (CTA) examinations performed on either a second-generation or third-generation dual-source CT scanner were included; we refer to the second-generation dual-source CT scanner as "CT1" and the third-generation dual-source CT scanner as "CT2." The volume CT dose index (CTDIvol) and patient diameter (i.e., the water-equivalent diameter) were retrieved by dose-monitoring software. Size-dependent DRLs based on a linear regression of the CTDIvol versus patient size were set by scanner type. Size-independent DRLs were set by the 5th and 95th percentiles of the CTDIvol values. Objective image quality was assessed using the signal-to-noise ratio (SNR), and subjective image quality was assessed using a 4-point Likert scale. The CTDIvol depended on patient size and scanner type (R2 = 0.72 and 0.78, respectively; slope = 0.05 and 0.02 mGy/mm; p < 0.001). Of the outliers identified by size-independent DRLs, 30% (CT1) and 67% (CT2) were adequately dosed when considering patient size. Alternatively, 30% (CT1) and 70% (CT2) of the outliers found with size-dependent DRLs were not identified using size-independent DRLs. A negative correlation was found between SNR and CTDIvol (R2 = 0.36 for CT1 and 0.45 for CT2). However, all outliers had a subjective image quality score of sufficient or better. We introduce a method for setting size-dependent LDRLs in CTA. Size-dependent LDRLs are relevant for assessing the appropriateness of the radiation dose for an individual patient on a specific CT scanner.

Mathematical modelling of scanner-specific bowtie filters for Monte Carlo CT dosimetry

The purpose of bowtie filters in CT scanners is to homogenize the x-ray intensity measured by the detectors in order to improve the image quality and at the same time to reduce the dose to the patient because of the preferential filtering near the periphery of the fan beam. For CT dosimetry, especially for Monte Carlo calculations of organ and tissue absorbed doses to patients, it is important to take the effect of bowtie filters into account. However, material composition and dimensions of these filters are proprietary. Consequently, a method for bowtie filter simulation independent of access to proprietary data and/or to a specific scanner would be of interest to many researchers involved in CT dosimetry. This study presents such a method based on the weighted computer tomography dose index, CTDIw, defined in two cylindrical PMMA phantoms of 16 cm and 32 cm diameter. With an EGSnrc-based Monte Carlo (MC) code, ratios CTDIw/CTDI100,a were calculated for a specific CT scanner using PMMA bowtie filter models based on sigmoid Boltzmann functions combined with a scanner filter factor (SFF) which is modified during calculations until the calculated MC CTDIw/CTDI100,a matches ratios CTDIw/CTDI100,a, determined by measurements or found in publications for that specific scanner. Once the scanner-specific value for an SFF has been found, the bowtie filter algorithm can be used in any MC code to perform CT dosimetry for that specific scanner. The bowtie filter model proposed here was validated for CTDIw/CTDI100,a considering 11 different CT scanners and for CTDI100,c, CTDI100,p and their ratio considering 4 different CT scanners. Additionally, comparisons were made for lateral dose profiles free in air and using computational anthropomorphic phantoms. CTDIw/CTDI100,a determined with this new method agreed on average within 0.89% (max. 3.4%) and 1.64% (max. 4.5%) with corresponding data published by CTDosimetry (www.impactscan.org) for the CTDI HEAD and BODY phantoms, respectively. Comparison with results calculated using proprietary data for the PHILIPS Brilliance 64 scanner showed agreement on average within 2.5% (max. 5.8%) and with data measured for that scanner within 2.1% (max. 3.7%). Ratios of CTDI100,c/CTDI100, p for this study and corresponding data published by CTDosimetry (www.impactscan.org) agree on average within about 11% (max. 28.6%). Lateral dose profiles calculated with the proposed bowtie filter and with proprietary data agreed within 2% (max. 5.9%), and both calculated data agreed within 5.4% (max. 11.2%) with measured results. Application of the proposed bowtie filter and of the exactly modelled filter to human phantom Monte Carlo calculations show agreement on the average within less than 5% (max. 7.9%) for organ and tissue absorbed doses.

Effective and equivalent doses for CT head examinations calculated using the voxelized phantoms MASH and FASH

The voxelized phantoms MASH and FASH have been used for calculating conversion coefficients (CCs) for a specific CT head examination performed in a specific Toshiba CT scanner. The X-ray spectrum was selected according to the concordance between the calculated C 100,c and measured C 100,c. For 120 kV, the X-raytbc code presented the smaller deviation, equal to −7.11%. Finally, effective doses calculated for the voxelized phantoms MASH and FASH were 6.1 and 4.5, respectively, smaller than the effective dose obtained though the European guidelines on quality criteria for computed tomography.

Radiation safety summit – method to estimate radiation dose to pediatric patients from CT scans

State-of-the-art CT scanners typically display two dose indices, CTDIvol (mGy) and DLP (mGy-cm), along with which two standard CTDI phantoms, 16or 32-cm diameter, are used to estimate the two indices. CTDIvol is based on radiation dose measurements on an individual scanner completed by a medical physicist with a pencil ionization chamber and either a 16or 32-cm diameter CTDI cylindrical plastic phantom. CTDIvol represents the radiation dose delivered to a standard plastic phantom from a specific model CT scanner using specified scan parameters: tube voltage, tube current, rotation time, pitch and selected bowtie filter. CTDIvol provides a standardized method to estimate and compare the radiation output of different CT scanners. CTDIvol is defined to be a dose index of CT scanners, not an indication of patient dose. The inability of CTDIvol to accurately reflect pediatric patient dose is illustrated in Fig. 1. Three cylindrical phantoms with diameters of 10 cm, 16 cm, and 32 cm (representing the smallest pediatric patient to an adult) were scanned with the same scanner using the same scan parameters. While this delivered the same radiation energy to each phantom, the measured CTDIvol in the phantoms (top row of data in figure) ranged from 47 mGy to 18 mGy. This clearly indicates that the dose to various-size patients (represented by the three phantoms) is a function of the energy produced by the scanner (determined by scan techniques) and the size of the patient. The superficial tissues of the large patient attenuate the radiation beam, reducing the dose delivered to the core of the large patient. In the figure, the center of the 10-cm phantom received 47 mGy of dose while the center of the 32-cm phantom received a dose of only 10.8 mGy for the same scan techniques. While the measured dose index in the previous example with an ionization chamber, CTDIvol, is very dependent on patient size when scan parameters for all three phantoms are identical, the displayed CTDIvol on a CT scanner is independent of changes in patient size by definition. The displayed scan index assumes the actual scan parameters but by definition assumes the patient is either a 16-cm or 32-cm diameter cylindrical plastic phantom. If the 16-cm phantom is assumed, the scanner will display 37 mGy for CTDIvol for each of the three represented patient sizes (second row of data in Fig. 1); this overestimates the dose to adult patients and underestimates dose to infants. If the 32-cm phantom is assumed, the scanner displays 18 mGy for all patients (third row of data in figure); this underestimates the dose to all patients smaller than adults. In either case, the displayed CTDIvol does not represent the pediatric patient dose and can mislead the technologist or radiologist. A task group of the American Association of Physicists in Medicine (AAPM), co-chaired by John Boone and Keith Strauss, is currently preparing a report that will provide scaling factors as a function of patient size that can be used by the technologist or radiologist to more accurately estimate the radiation dose to the tissues of the pediatric patient that are directly irradiated by the primary X-ray beam of the CT scanner. These scaling factors will be based on attenuation data collected from numerous CT scanners by multiple investigators. Hopefully, these scaling factors will be available by the time of this presentation. These scaling factors should allow the operator of the CT scanner to estimate the radiation dose to the Disclaimer Dr. Strauss has no financial interests, investigational or off-label uses to disclose.

Differentiating Emery-Dreifuss muscular dystrophy and collagen VI-related myopathies using a specific CT scanner pattern

Bethlem myopathy and Ullrich congenital muscular dystrophy are part of the heterogeneous group of collagen VI-related muscle disorders. They are caused by mutations in collagen VI (ColVI) genes ( COL6A1, COL6A2, and COL6A3) while LMNA mutations cause autosomal dominant Emery-Dreifuss muscular dystrophy. A muscular dystrophy pattern and contractures are found in all three conditions, making differential diagnosis difficult especially in young patients when cardiomyopathy is absent. We retrospectively assessed upper and lower limb muscle CT scans in 14 Bethlem/Ullrich patients and 13 Emery-Dreifuss patients with identified mutations. CT was able to differentiate Emery-Dreifuss muscular dystrophy from ColVI-related myopathies in selected thigh muscles and to a lesser extent calves muscles: rectus femoris fatty infiltration was selectively present in Bethlem/Ullrich patients while posterior thigh muscles infiltration was more prominently found in Emery-Dreifuss patients. A more severe fatty infiltration particularly in the leg posterior compartment was found in the Emery-Dreifuss group.

G.P.6.03 Specific CT scanner muscle pattern helps to differentiate contractural lamin A/C and collagen VI related myopathies

G.P.6.03 Specific CT scanner muscle pattern helps to differentiate contractural lamin A/C and collagen VI related myopathies

WE-B-351-01: Patient Dose Estimates From CT Examinations

The assessment of radiation dose from computed tomography has become an important issue due to the increased utilization of computed tomography in a large number of clinical applications, from CT urography to cardiac CT. The traditional metrics used for CT dose assessment (CTDI-100) have come under assault from a number of investigators, because of its limitations in describing the radiation dose in realistic CT examinations. While there remains no real consensus in the field, a number of groups are working on the development of CT dose metrics which convey a better understanding of the radiation dose received by individual patients for specific CT examinations. In this presentation, the perspective of a number of groups will be presented. Primarily, the work of a committee of the International Commission of Radiological Units (ICRU) commissioned in 2005 will be discussed. The ICRU committee has preliminarily defined a multi-tier system for the assessment of radiation dose metrics in computed tomography. At the first level, machine-dependent performance factors are described and measured, and these include the traditional CTDI-100 metric for the 16 cm and 32 cm diameter polymethylmethacrylate dosimetry phantoms, at the center and at the periphery. There is a consensus amongst the ICRU community that radiation dose to patients undergoing CT examinations is best established using the known geometry of the CT examination, coupled with measured output characteristics of the specific CT scanner (including bow-tie characteristics), combined with Monte Carlo computations. In the rare instance in which the CT dose to a specific patient needs to be computed, image-based methodologies will be presented which enable these computations with a high degree of accuracy. It is emphasized that the effective dose (measured in milliseiverts) is not an appropriate measure for individual patient doses, as this metric includes population-based radiation epidemiological data which may not be applicable to a specific individual. Therefore, the ICRU efforts towards radiation dosimetry of the individual patient focus on dosimetric units which are physical in nature, and describe the individual organ doses and the overall average dose to the patient, depending upon the specific CT examination and the patient's physical characteristics. Educational Objectives: 1. Convey some of the issues in accurate dose assessment in CT. 2. Describe some of the ongoing efforts of the ICRU committee on CT towards dose assessment.

TU‐SAMS‐L100J‐01: Determination of Dose From CT Examinations

The assessment of radiation dose from computed tomography has become an important issue due to the increased utilization of computed tomography in a large number of clinical applications, from CT urography to cardiac CT. The traditional metrics used for CT dose assessment (CTDI‐100) have come under assault from a number of investigators, because of its limitations in describing the radiation dose in realistic CT examinations. While there remains no real consensus in the field, a number of groups are working on the development of CT dose metrics which convey a better understanding of the radiation dose received by individual patients for specific CT examinations. In this presentation, the perspective of a number of groups will be presented. Primarily, the work of a committee of the International Commission of Radiological Units (ICRU) commissioned in 2005 will be discussed.The ICRU committee has preliminarily defined a multi‐tier system for the assessment of radiation dose metrics in computed tomography. At the first level, machine‐dependent performance factors are described and measured, and these include the traditional CTDI‐100 metric for the 16 cm and 32 cm diameter polymethylmethacrylate dosimetry phantoms, at the center and at the periphery. There is a consensus amongst the ICRU community that radiation dose to patients undergoing CT examinations is best established using the known geometry of the CT examination, coupled with measured output characteristics of the specific CT scanner (including bow‐tie characteristics), combined with Monte Carlo computations. In the rare instance in which the CT dose to a specific patient needs to be computed, image‐based methodologies will be presented which enable these computations with a high degree of accuracy. It is emphasized that the effective dose (measured in milliseiverts) is not an appropriate measure for individual patient doses, as this metric includes population‐based radiation epidemiological data which may not be applicable to a specific individual. Therefore, the ICRU efforts towards radiation dosimetry of the individual patient focus on dosimetric units which are physical in nature, and describe the individual organ doses and the overall average dose to the patient, depending upon the specific CT examination and the patient's physical characteristics.Educational Objectives:1. Convey some of the issues in accurate dose assessment in CT.2. Describe some of the ongoing efforts of the ICRU committee on CT towards dose assessment.

TU‐EE‐A4‐04: Comparison of the CT Scatter Fractions Provided in NCRP Report No. 147 to Scanner‐Specific Scatter Fractions and the Consequences for Calculated Barrier Thickness

Purpose: NCRP Report No. 147 provides fixed values of the scatter fraction per centimeter (κ) for the peripheral axis of the head and body CT phantoms. This study was performed to determine scatter fractions for different makes and models of CT scanner and to examine the consequence of any differences in κ on a typical shielding calculation. Method and Materials: κ values for five GE CT models, four Siemens CT models and one Toshiba CT model were determined. They were calculated using an equation for the scattered air kerma at 1 m from NCRP 147 (Kermascatter=κ*ScanLength*CTDI100/pitch) and using scattered air kerma data provided by the manufacturers and measured CTDI100 (periphery) values. Typical barrier calculations, following NCRP 147 methodology, were performed for each CT scanner using the fixed κ values and, separately, using the calculated scanner‐specific values. Results: The κ values from NCRP 147 are 3×10−4/cm and 9×10−5/cm for the periphery of the body and head phantoms, respectively. Calculated κ values varied from 3.2×10−4 to 5.2×10−4/cm for the body and 5.6×10−5 to 1.1×10−4/cm for the head. The results of a typical barrier calculation indicate that for the scanners studied, the fixed κ values produced lead barrier thicknesses that ranged from 0 to 0.2 mm less than those determined from scanner‐specific κ values. Similar calculations for the floor gave a maximum underestimate of 1.2 cm. Conclusion: The actual κ values of a specific CT scanner can vary significantly from the fixed values provided in NCRP 147. Using the fixed values for some scanners may slightly underestimate the required barrier thickness. Any small underestimate in barrier thickness would likely be more than compensated by a conservative estimate of the scanner's workload.

The indirect use of CT numbers to establish material properties needed for Monte Carlo calculation of dose distributions in patients.

A number of Monte Carlo codes are available, which can be used to calculate dose distributions n patients with high accuracy. Patient geometry can readily be derived with adequate spatial resolution from CT scans. To perform the Monte Carlo calculation with the same spatial resolution, it is necessary to enter the atomic composition and density of the tissue in each voxel of the CT image. This means entering 65,536 discrete values for a CT slice with a 256 x 256 matrix size. The need for automated methods of setting up the material data files is obvious. Because there is no direct unique relationship between CT numbers and material composition, the aim of our work was to devise a method whereby the atomic composition and density in each voxel could be assigned automatically by indirect derivation from the CT numbers. The set of all tissues types in the human body was divided into subsets that are dosimetrically equivalent, based on Monte Carlo calculated depth dose curves in homogeneous phantoms of each tissue. CT number ranges corresponding to each tissue subset were determined from the calibration curve linking electron density with CT number for the specific CT scanner. Further subdivision was found to be necessary for the lung and bone type tissues. This was done by keeping the atomic composition constant and varying the physical density. It was found that 57 distinct tissue subsets were needed to represent the 16 main tissue types in the body at a 1% dose level. Corresponding CT number intervals of 30 HU were needed in the lung and soft tissue region, whereas in the bone region the intervals could be increased to 100 HU. A computer algorithm was set up to convert automatically from CT number to corresponding equivalent material number for the Monte Carlo preprocessor code.