Thomas J. Vrieze

CT Dosimetry : Comparison of Measurement Techniques and Devices

In x-ray computed tomography (CT), the most common parameter used to estimate and minimize patient dose is the CT dose index (CTDI). The CTDI is a volume-averaged measure that is used in situations where the table is incremented in conjunction with the tube rotation. Variants of the CTDI correct for averaging across the field of view and for adjacent beam overlaps or gaps. CTDI is usually measured with a pencil-shaped ionization chamber, although methods have been developed that use alternative detectors, including an optically stimulated luminescence probe and a solid-state real-time dosimeter. Because the CTDI represents an averaged dose to a homogeneous cylindrical phantom, the measurements are only an approximation of the patient dose. Furthermore, dose from interventional or perfusion CT, in which the table remains stationary between multiple scans, is best evaluated with point dose measurements made with small detectors. CTDI and point dose values are nearly the same for measurement of surface dose from spiral CT. However, for measurement of surface dose from perfusion CT, the dose is overestimated by a factor of two or more with CTDI values in comparison with point dose values. Both CTDI and point dose measurement are valuable for evaluating CT scanner output and estimating patient dose.

Radiation Dose Levels for Interventional CT Procedures

OBJECTIVE The purpose of this study was to determine typical radiation dose levels to patients undergoing CT-guided interventional procedures. MATERIALS AND METHODS A total of 571 patients undergoing CT interventional procedures were included in this retrospective data analysis study. Enrolled patients underwent one of five procedures: cryoablation, aspiration, biopsy, drain, or injection. With each procedure, two scan modes were used, either intermittent (no table increment) or helical mode. Skin dose was estimated from the volumetric CT dose index (CTDI(vol)) and phantom measurements. Effective dose was calculated by multiplying dose-length product (DLP) and conversion factor (k factor) for helical mode, and using Monte Carlo organ dose coefficients for intermittent mode. RESULTS The mean (± SD) skin doses were 728 ± 382, 130 ± 104, 128 ± 81, 152 ± 105, and 195 ± 147 mGy, and the mean effective doses were 119.7 ± 50.3, 20.1 ± 11.0, 13.8 ± 9.2, 25.3 ± 15.4, and 9.1 ± 5.5 mSv for each of the five procedures, respectively. The maximum skin dose was 1.95 Gy. The mean effective dose across all procedure types was 24.1 mSv, with 2.3 mSv from intermittent scans and 21.8 mSv from helical scans. CONCLUSION Substantial dose differences were observed among the five procedures. The risk of deterministic effects appears to be very low, because the maximum observed skin dose did not exceed the threshold for transient skin erythema (2 Gy). The average risk of stochastic effects was comparable to that of 1-10 abdomen and pelvis CT examinations. Although the intermittent mode can contribute substantially to skin dose, it contributes minimally to the effective dose because of the much shorter scan range used.

Dose and Image Quality Evaluation of a Dedicated Cone-Beam CT System for High-Contrast Neurologic Applications

OBJECTIVE The purpose of our study was to evaluate the dose and image quality performance of a dedicated cone-beam CT (CBCT) scanner in comparison with an MDCT scanner. MATERIALS AND METHODS The conventional dose metric, CT dose index (CTDI), is no longer applicable to CBCT scanners. We propose to use two dose metrics, the volume average dose and the mid plane average dose, to quantify the dose performance in a circular cone-beam scan. Under the condition of equal mid plane average dose, we evaluated the image quality of a CBCT scanner and an MDCT scanner, including high-contrast spatial resolution, low-contrast spatial resolution, noise level, CT number uniformity, and CT number accuracy. RESULTS For the sinus scanning protocol, the CBCT system had comparable high-contrast resolution and inferior low-contrast resolution to those obtained with the MDCT scanner when the doses were matched (mid plane average dose 9.2 mGy). The CT number uniformity and accuracy were worse on the CBCT scanner. The image artifacts caused by beam hardening and scattering were also much more severe on the CBCT system. CONCLUSION With a matched radiation dose, the CBCT system for sinus study has comparable high-contrast resolution and inferior low-contrast resolution relative to the MDCT scanner. Because of the more severe image artifacts on the CBCT system due to the small field of view and the lack of accurate scatter and beam-hardening correction, the utility of the CBCT system for diagnostic tasks related to soft tissue should be carefully assessed.

Technical Note: Measuring contrast- and noise-dependent spatial resolution of an iterative reconstruction method in CT using ensemble averaging

PURPOSE The spatial resolution of iterative reconstruction (IR) in computed tomography (CT) is contrast- and noise-dependent because of the nonlinear regularization. Due to the severe noise contamination, it is challenging to perform precise spatial-resolution measurements at very low-contrast levels. The purpose of this study was to measure the spatial resolution of a commercially available IR method using ensemble-averaged images acquired from repeated scans. METHODS A low-contrast phantom containing three rods (7, 14, and 21 HU below background) was scanned on a 128-slice CT scanner at three dose levels (CTDIvol = 16, 8, and 4 mGy). Images were reconstructed using two filtered-backprojection (FBP) kernels (B40 and B20) and a commercial IR method (sinogram affirmed iterative reconstruction, SAFIRE, Siemens Healthcare) with two strength settings (I40-3 and I40-5). The same scan was repeated 100 times at each dose level. The modulation transfer function (MTF) was calculated based on the edge profile measured on the ensemble-averaged images. RESULTS The spatial resolution of the two FBP kernels, B40 and B20, remained relatively constant across contrast and dose levels. However, the spatial resolution of the two IR kernels degraded relative to FBP as contrast or dose level decreased. For a given dose level at 16 mGy, the MTF50% value normalized to the B40 kernel decreased from 98.4% at 21 HU to 88.5% at 7 HU for I40-3 and from 97.6% to 82.1% for I40-5. At 21 HU, the relative MTF50% value decreased from 98.4% at 16 mGy to 90.7% at 4 mGy for I40-3 and from 97.6% to 85.6% for I40-5. CONCLUSIONS A simple technique using ensemble averaging from repeated CT scans can be used to measure the spatial resolution of IR techniques in CT at very low contrast levels. The evaluated IR method degraded the spatial resolution at low contrast and high noise levels.

Reducing image noise in computed tomography (CT) colonography: effect of an integrated circuit CT detector.

Objective To investigate whether the integrated circuit (IC) detector results in reduced noise in computed tomography (CT) colonography (CTC). Methods Three hundred sixty-six consecutive patients underwent clinically indicated CTC using the same CT scanner system, except for a difference in CT detectors (IC or conventional). Image noise, patient size, and scanner radiation output (volume CT dose index) were quantitatively compared between patient cohorts using each detector system, with separate comparisons for the abdomen and pelvis. Results For the abdomen and pelvis, despite significantly larger patient sizes in the IC detector cohort (both P < 0.001), image noise was significantly lower (both P < 0.001), whereas volume CT dose index was unchanged (both P > 0.18). Based on the observed image noise reduction, radiation dose could alternatively be reduced by approximately 20% to result in similar levels of image noise. Conclusion Computed tomography colonography images acquired using the IC detector had significantly lower noise than images acquired using the conventional detector. This noise reduction can permit further radiation dose reduction in CTC.

Spatial resolution improvement and dose reduction potential for inner ear CT imaging using a z‐axis deconvolution technique

PURPOSE To assess the z-axis resolution improvement and dose reduction potential achieved using a z-axis deconvolution technique with iterative reconstruction (IR) relative to filtered backprojection (FBP) images created with the use of a z-axis comb filter. METHODS Each of three phantoms were scanned with two different acquisition modes: (1) an ultrahigh resolution (UHR) scan mode that uses a comb filter in the fan angle direction to increase in-plane spatial resolution and (2) a z-axis ultrahigh spatial resolution (zUHR) scan mode that uses comb filters in both the fan and cone angle directions to improve both in-plane and z-axis spatial resolution. All other scanning parameters were identical. First, the ACR CT Accreditation phantom, rotated by 90° so that the high-contrast spatial resolution targets were parallel to the coronal plane, was scanned to assess limiting spatial resolution and image noise. Second, section sensitivity profiles (SSPs) were measured using a copper foil embedded in an acrylic cylinder and the full-width-at-half-maximum (FWHM) and full-width-at-tenth-maximum (FWTM) of the SSPs were calculated. Third, an anthropomorphic head phantom containing a human skull was scanned to assess clinical acceptability for imaging of the temporal bone. For each scan, FBP images were reconstructed for the zUHR scan using the narrowest image thickness available. For the CT accreditation phantom, zUHR images were also reconstructed using an IR algorithm (SAFIRE, Siemens Healthcare, Forchheim, Germany) to assess the influence of the IR algorithm on image noise. A z-axis deconvolution technique combined with the IR algorithm was used to reconstruct images at the narrowest image thickness possible from the UHR scan data. Images of the ACR and head phantoms were reformatted into the coronal plane. The head phantom images were evaluated by a neuroradiologist to assess acceptability for use in patients undergoing clinically indicated CT imaging of the temporal bone. RESULTS The limiting spatial resolution was 12 lp/cm for the FBP-zUHR images and the IR-UHR images, although visual assessment indicated a slight improvement for the IR-UHR images. Image noise was 213.0, 181.8, and 153.5 for the FBP-zUHR, IR-zUHR, and IR-UHR images, respectively. While the FWHM was essentially the same for the FBP-zUHR and IR-UHR images, the FWTM of the IR-UHR images was almost 50% smaller compared to the FBP-zUHR images (0.83 vs 1.25 mm, respectively). Images of the anthropomorphic head phantom were judged to be of higher quality for the IR-UHR images compared to the FBP-zUHR images. CONCLUSIONS With use of a z-axis deconvolution technique, z-axis spatial resolution was improved for scans acquired using a comb filter only in the fan angle direction relative to FBP images acquired with a comb filter in both the fan and cone angle directions. By avoiding use of the comb filter in the cone angle direction and use of an IR algorithm, image noise was substantially reduced for the same scanner output (CTDIvol). Thus, overall image quality (spatial resolution and image noise) can be maintained relative to the FBP-zUHR technique at a lower radiation dose.PURPOSE To assess the z-axis resolution improvement and dose reduction potential achieved using a z-axis deconvolution technique with iterative reconstruction (IR) relative to filtered backprojection (FBP) images created with the use of a z-axis comb filter. METHODS Each of three phantoms were scanned with two different acquisition modes: (1) an ultrahigh resolution (UHR) scan mode that uses a comb filter in the fan angle direction to increase in-plane spatial resolution and (2) a z-axis ultrahigh spatial resolution (zUHR) scan mode that uses comb filters in both the fan and cone angle directions to improve both in-plane and z-axis spatial resolution. All other scanning parameters were identical. First, the ACR CT Accreditation phantom, rotated by 90° so that the high-contrast spatial resolution targets were parallel to the coronal plane, was scanned to assess limiting spatial resolution and image noise. Second, section sensitivity profiles (SSPs) were measured using a copper foil embedded in an acrylic cylinder and the full-width-at-half-maximum (FWHM) and full-width-at-tenth-maximum (FWTM) of the SSPs were calculated. Third, an anthropomorphic head phantom containing a human skull was scanned to assess clinical acceptability for imaging of the temporal bone. For each scan, FBP images were reconstructed for the zUHR scan using the narrowest image thickness available. For the CT accreditation phantom, zUHR images were also reconstructed using an IR algorithm (SAFIRE, Siemens Healthcare, Forchheim, Germany) to assess the influence of the IR algorithm on image noise. A z-axis deconvolution technique combined with the IR algorithm was used to reconstruct images at the narrowest image thickness possible from the UHR scan data. Images of the ACR and head phantoms were reformatted into the coronal plane. The head phantom images were evaluated by a neuroradiologist to assess acceptability for use in patients undergoing clinically indicated CT imaging of the temporal bone. RESULTS The limiting spatial resolution was 12 lp/cm for the FBP-zUHR images and the IR-UHR images, although visual assessment indicated a slight improvement for the IR-UHR images. Image noise was 213.0, 181.8, and 153.5 for the FBP-zUHR, IR-zUHR, and IR-UHR images, respectively. While the FWHM was essentially the same for the FBP-zUHR and IR-UHR images, the FWTM of the IR-UHR images was almost 50% smaller compared to the FBP-zUHR images (0.83 vs 1.25 mm, respectively). Images of the anthropomorphic head phantom were judged to be of higher quality for the IR-UHR images compared to the FBP-zUHR images. CONCLUSIONS With use of a z-axis deconvolution technique, z-axis spatial resolution was improved for scans acquired using a comb filter only in the fan angle direction relative to FBP images acquired with a comb filter in both the fan and cone angle directions. By avoiding use of the comb filter in the cone angle direction and use of an IR algorithm, image noise was substantially reduced for the same scanner output (CTDIvol). Thus, overall image quality (spatial resolution and image noise) can be maintained relative to the FBP-zUHR technique at a lower radiation dose.

Technical note: precision and accuracy of a commercially available CT optically stimulated luminescent dosimetry system for the measurement of CT dose index.

PURPOSE To determine the precision and accuracy of CTDI(100) measurements made using commercially available optically stimulated luminescent (OSL) dosimeters (Landaur, Inc.) as beam width, tube potential, and attenuating material were varied. METHODS One hundred forty OSL dosimeters were individually exposed to a single axial CT scan, either in air, a 16-cm (head), or 32-cm (body) CTDI phantom at both center and peripheral positions. Scans were performed using nominal total beam widths of 3.6, 6, 19.2, and 28.8 mm at 120 kV and 28.8 mm at 80 kV. Five measurements were made for each of 28 parameter combinations. Measurements were made under the same conditions using a 100-mm long CTDI ion chamber. Exposed OSL dosimeters were returned to the manufacturer, who reported dose to air (in mGy) as a function of distance along the probe, integrated dose, and CTDI(100). RESULTS The mean precision averaged over 28 datasets containing five measurements each was 1.4% ± 0.6%, range = 0.6%-2.7% for OSL and 0.08% ± 0.06%, range = 0.02%-0.3% for ion chamber. The root mean square (RMS) percent differences between OSL and ion chamber CTDI(100) values were 13.8%, 6.4%, and 8.7% for in-air, head, and body measurements, respectively, with an overall RMS percent difference of 10.1%. OSL underestimated CTDI(100) relative to the ion chamber 21∕28 times (75%). After manual correction of the 80 kV measurements, the RMS percent differences between OSL and ion chamber measurements were 9.9% and 10.0% for 80 and 120 kV, respectively. CONCLUSIONS Measurements of CTDI(100) with commercially available CT OSL dosimeters had a percent standard deviation of 1.4%. After energy-dependent correction factors were applied, the RMS percent difference in the measured CTDI(100) values was about 10%, with a tendency of OSL to underestimate CTDI relative to the ion chamber. Unlike ion chamber methods, however, OSL dosimeters allow measurement of the radiation dose profile.

SU‐GG‐I‐38: A Direct Skin Dose Calculation Method in CT Scans without Table Motion: Influence of Patient Size and Beam Collimation

Purpose: To calculate skin dose from console dose (CTDIvol) in CT scan modes without table motion, such as interventional and perfusion CT applications, and to investigate the influence of phantom size and beam collimation.Materials and Methods:Skin doses were measured using a solid state detector placed on the anterior surface of six oblong water phantoms with measured lateral widths from 25 to 50 cm. Surface doses were measured using a sequential scan mode without table increment, 12×0.6mm collimation, 120kV, 80mAs and 0.5s rotation time on a 64‐slice CT system. Console CTDIvol was recorded and the ratio between surface dose and console CTDIvol calculated for each phantom size. To investigate the dependence of this ratio on beam width, surface doses were measured at collimations of 1×5, 12×0.6, 1×10, 12×1.2, 30×0.6 and 24×1.2 mm using the 40cm phantom. Results: The console CTDIvol for the 12×0.6mm collimation was 7.12 mGy, while measuredsurface doses were 4.23, 4.65, 4.24, 3.86, 3.55, and 3.47 mGy, respectively, for phantom size of 25, 30, 35, 40, 45 and 50 cm. The surface dose as a percentage of CTDIvol varied from 49% to 65%, increasing with decreasing phantom size except for the 25cm phantom. The measuredsurface doses (and percentage of CTDIvol) for the 40 cm phantom at different collimations were: 3.32 (68%), 3.77 (53%), 3.76 (78%), 4.23 (74%), 4.4 (74%), 4.79 (89%) mGy for collimations from 1×5 mm to 24×1.2 mm. Conclusions: For the same technical parameters (and CTDIvol), surface dose in CT scans without table increment varied with phantom size and beam collimation. For a given collimation and CTDIvol, surface dose in general increased with decreasing phantom size. For a given phantom size, surface dose and CTDIvol both depended on beam collimation, with surface dose as a percentage of CTDIvol generally increasing with beam width.

Implementation and evaluation of a protocol management system for automated review of CT protocols

Protocol review is important to decrease the risk of patient injury and increase the consistency of CT image quality. A large volume of CT protocols makes manual review labor-intensive, error-prone, and costly. To address these challenges, we have developed a software system for automatically managing and monitoring CT protocols on a frequent basis. This article describes our experiences in the implementation and evaluation of this protocol monitoring system. In particular, we discuss various strategies for addressing each of the steps in our protocol-monitoring workflow, which are: maintaining an accurate set of master protocols, retrieving protocols from the scanners, comparing scanner protocols to master protocols, reviewing flagged differences between the scanner and master protocols, and updating the scanner and/or master protocols. In our initial evaluation focusing only on abdomen and pelvis protocols, we detected 309 modified protocols in a 24-week trial period. About one-quarter of these modified protocols were determined to contain inappropriate (i.e., erroneous) protocol parameter modifications that needed to be corrected on the scanner. The most frequently affected parameter was the series description, which was inappropriately modified 47 times. Two inappropriate modifications were made to the tube current, which is particularly important to flag as this parameter impacts both radiation dose and image quality. The CT protocol changes detected in this work provide strong motivation for the use of an automated CT protocol quality control system to ensure protocol accuracy and consistency. PACS number(s): 87.57.Q.Protocol review is important to decrease the risk of patient injury and increase the consistency of CT image quality. A large volume of CT protocols makes manual review labor‐intensive, error‐prone, and costly. To address these challenges, we have developed a software system for automatically managing and monitoring CT protocols on a frequent basis. This article describes our experiences in the implementation and evaluation of this protocol monitoring system. In particular, we discuss various strategies for addressing each of the steps in our protocol‐monitoring workflow, which are: maintaining an accurate set of master protocols, retrieving protocols from the scanners, comparing scanner protocols to master protocols, reviewing flagged differences between the scanner and master protocols, and updating the scanner and/or master protocols. In our initial evaluation focusing only on abdomen and pelvis protocols, we detected 309 modified protocols in a 24‐week trial period. About one‐quarter of these modified protocols were determined to contain inappropriate (i.e., erroneous) protocol parameter modifications that needed to be corrected on the scanner. The most frequently affected parameter was the series description, which was inappropriately modified 47 times. Two inappropriate modifications were made to the tube current, which is particularly important to flag as this parameter impacts both radiation dose and image quality. The CT protocol changes detected in this work provide strong motivation for the use of an automated CT protocol quality control system to ensure protocol accuracy and consistency. PACS number(s): 87.57.Q‐

Construction of realistic liver phantoms from patient images using 3D printer and its application in CT image quality assessment

The purpose of this study is to use 3D printing techniques to construct a realistic liver phantom with heterogeneous background and anatomic structures from patient CT images, and to use the phantom to assess image quality with filtered back-projection and iterative reconstruction algorithms. Patient CT images were segmented into liver tissues, contrast-enhanced vessels, and liver lesions using commercial software, based on which stereolithography (STL) files were created and sent to a commercial 3D printer. A 3D liver phantom was printed after assigning different printing materials to each object to simulate appropriate attenuation of each segmented object. As high opacity materials are not available for the printer, we printed hollow vessels and filled them with iodine solutions of adjusted concentration to represent enhance levels in contrast-enhanced liver scans. The printed phantom was then placed in a 35×26 cm oblong-shaped water phantom and scanned repeatedly at 4 dose levels. Images were reconstructed using standard filtered back-projection and an iterative reconstruction algorithm with 3 different strength settings. Heterogeneous liver background were observed from the CT images and the difference in CT numbers between lesions and background were representative for low contrast lesions in liver CT studies. CT numbers in vessels filled with iodine solutions represented the enhancement of liver arteries and veins. Images were run through a Channelized Hotelling model observer with Garbor channels and ROC analysis was performed. The AUC values showed performance improvement using the iterative reconstruction algorithm and the amount of improvement increased with strength setting.