Image Quality Assessment of Deep Learning Image Reconstruction in Torso Computed Tomography Using Tube Current Modulation

Novel deep learning image reconstruction (DLIR) reportedly changes the image quality characteristics based on object contrast and image noise. In clinical practice, computed tomography image noise is usually controlled by tube current modulation (TCM) to accommodate changes in object size. This study aimed to evaluate the image quality characteristics of DLIR for different object sizes when the in-plane noise was controlled by TCM. Images acquisition was performed on a GE Revolution CT system to investigate the impact of the DLIR algorithm compared to the standard reconstructions of filtered-back projection (FBP) and hybrid iterative reconstruction (hybrid-IR). The image quality assessment was performed using phantom images, and an observer study was conducted using clinical cases. The image quality assessment confirmed the excellent noise- reduction performance of DLIR, despite variations due to phantom size. Similarly, in the observer study, DLIR received high evaluations regardless of the body parts imaged. We evaluated a novel DLIR algorithm by replicating clinical behaviors. Consequently, DLIR exhibited higher image quality than those of FBP and hybrid-IR in both phantom and observer studies, albeit the value depended on the reconstruction strength, and proved itself capable of providing stable image quality in clinical use.

Evaluation of automatic tube current modulation of CT scanners using a dedicated and the CTDI dosimetry phantoms

PURPOSE

To investigate the operation principles of the automatic tube current modulation (ATCM) of a CT scanner, using a dedicated phantom and the CT dosimetry index (CTDI) phantom.

MATERIAL AND METHODS

The Mercury 4.0 phantom and three different configurations of the CTDI dosimetry phantom were employed. A frequently used clinical scanning protocol was employed as a basis for the acquisitions performed with all phantoms, using both scanning directions. Additional acquisitions with different pitch and examination protocols were performed with Mercury phantom, to further explore their effect on ATCM and the resulting image quality. Different software named DICOM Info Extractor, ImageJ, and imQuest, were used to derive CTDI_vol and table position, image noise, and water equivalent diameter (WED) of each phantom CT image, respectively. ImQuest was also used to derive the detectability index (d') of five different materials (air, solid water, polystyrene, iodine, and bone) embedded in the Mercury phantom.

RESULTS

It was exhibited with all four phantoms that the scanning direction greatly affects the modulation curves. The fitting of the dose modulations curves suggested that for each table position what determines the CTDI_vol value is the WED values of the phantom structures laying ahead towards the scanning direction, for a length equal to the effective width of the X-ray beam. Furthermore, it was also exhibited that ATCM does not fully compensate for larger thicknesses, since images of larger WED phantom sections present more noise (larger SD) in all four phantoms and in Mercury 4.0 phantom smaller detectability (d').

CONCLUSION

Mercury 4.0 is a dedicated phantom for a complete and in-depth evaluation of the ATCM operation and the resulting image quality. However, in its absence, different CTDI configurations can be used as an alternative to investigate and comprehend some basic operation principles of the CT scanners' ATCM systems.

Patient-specific radiation risk-based tube current modulation for diagnostic CT

PURPOSE

Modern CT scanners use automatic exposure control (AEC) techniques, such as tube current modulation (TCM), to reduce dose delivered to patients while maintaining image quality. In contrast to conventional approaches that minimize the tube current time product of the CT scan, referred to as mAsTCM in the following, we herein propose a new method referred to as riskTCM which aims at reducing the radiation risk to the patient by taking into account the specific radiation risk of every dose-sensitive organ.

METHODS

For current mAsTCM implementations, the mAs-product is used as a surrogate for the patient dose. Thus they do not take into account the varying dose sensitivity of different organs. Our riskTCM framework assumes that a coarse CT reconstruction, an organ segmentation and an estimation of the dose distribution can be provided in real time, e.g. by applying machine learning techniques. Using this information riskTCM determines a tube current curve that minimizes a patient risk measure, e.g. the effective dose, while keeping the image quality constant. We retrospectively applied riskTCM to 20 patients covering all relevant anatomical regions and tube voltages from 70 kV to 150 kV. The potential reduction of effective dose at same image noise is evaluated as a figure of merit and compared to mAsTCM and to a situation with a constant tube current referred to as noTCM.

RESULTS

Anatomical regions like the neck, thorax, abdomen and the pelvis benefit from the proposed riskTCM. On average, a reduction of effective dose of about 23 % for the thorax, 31 % for the abdomen, 24 % for the pelvis, and 27% for the neck have been evaluated compared to today's state-of-the-art mAsTCM. For the head, the resulting reduction of effective dose is lower, about 13 % on average compared to mAsTCM.

CONCLUSIONS

With a risk-minimizing tube current modulation, significant higher reduction of effective dose compared to mAs-minimizing tube current modulation is possible. This article is protected by copyright. All rights reserved.

Automatic tube current modulation (ATCM)

PURPOSE

The purpose of this work was to estimate and compare breast and lung doses of chest CT scans using organ-based tube current modulation (OBTCM) to those from conventional, attenuation-based automatic tube current modulation (ATCM) across a range of patient sizes.

METHODS

Thirty-four patients (17 females, 17 males) who underwent clinically indicated CT chest/abdomen/pelvis (CAP) examinations employing OBTCM were collected from two multi-detector row CT scanners. Patient size metric was assessed as water equivalent diameter (Dw ) taken at the center of the scan volume. Breast and lung tissues were segmented from patient image data to create voxelized models for use in a Monte Carlo transport code. The OBTCM schemes for the chest portion were extracted from the raw projection data. ATCM schemes were estimated using a recently developed method. Breast and lung doses for each TCM scenario were estimated for each patient model. CTDIvol -normalized breast (nDbreast ) and lung (nDlung ) doses were subsequently calculated. The differences between OBTCM and ATCM normalized organ dose estimates were tested using linear regression models that included CT scanner and Dw as covariates.

RESULTS

Mean dose reduction from OBTCM in nDbreast was significant after adjusting for the scanner models and patient size (P = 0.047). When pooled with females and male patient, mean dose reduction from OBTCM in nDlung was observed to be trending after adjusting for the scanner model and patient size (P = 0.085).

CONCLUSIONS

One specific manufacturer's OBTCM was analyzed. OBTCM was observed to significantly decrease normalized breast relative to a modeled version of that same manufacturer's ATCM scheme. However, significant dose savings were not observed in lung dose over all. Results from this study support the use of OBTCM chest protocols for females only.

Improving linac integrated cone beam computed tomography image quality using tube current modulation

PURPOSE

Linac integrated cone beam CT (CBCT) scanners have become widespread tool for image guidance in radiotherapy. The current implementation uses constant imaging fluence across all the projection angles, which leads to anisotropic noise properties and suboptimal image quality for noncircular symmetric objects. Tube current modulation (TCM) is widely used in conventional CT. The purpose of this work was to implement TCM on a linac integrated CBCT scanner and evaluate its impact on image quality under varying scatter conditions and scatter correction strategies.

METHODS

We have implemented TCM on a nonclinical Elekta Versa HD linear accelerator with enhanced x-ray generator functionality including pulse width modulation. The pulse width was modulated using two Arduino programmable microcontrollers: one placed on the kV arm to measure the projection angle and the other connected to the kV generator control board to vary x-ray pulse width as function of gantry angle and precalculated transmission. An in-house developed phantom with a ratio of the left-right to anterior-posterior path length of 1.85:1 was scanned. Image quality was determined using the anisotropicity of the 2D noise power spectra (NPS) in the transverse plane and the contrast-to-noise ratio (CNR). In addition, to determine the impact of scatter on the applicability of the TCM method we have modified the generated scatter using three different collimators in the cranio-caudal direction as well as with and without an antiscatter grid (ASG).

RESULTS

Application of the TCM led to 30-78% reduction of the angular anisotropicity of the NPS in the transverse plane. The amount of reduction depended on the scatter conditions, with lower values corresponding to higher scatter conditions. The same was true for the CNR: when scatter contribution was low (presence of an ASG or very aggressive collimation) the CNR was improved by about 30%, while in high scatter conditions the CNR was improved by about 12%.

CONCLUSIONS

TCM has the potential to improve CBCT image quality, but this depends on the amount of detected x-ray scatter.

Technical Note: Evaluating automatic tube current modulation in CT using the standard CTDI dosimetry phantom

PURPOSE

To assess the utility of the standard body CTDI phantom in characterizing the operation scheme of tube current modulation (TCM) systems in CT.

METHODS

The body CDTI phantom was used to characterize two TCM systems: TCM₁ and TCM₂ , implemented in scanners from different vendors. The phantom was aligned at the gantry isocenter in two configurations. In configuration A, the facet planes of the phantom were parallel to the patient table, while in configuration B they were vertical to the patient table and parallel to the patient's long axis. Acquisitions were performed using the routine abdominal examination protocol. mA(z) profiles were recorded from images' DICOM header. The water equivalent diameter (d_w ) and oval ratio (OR) were calculated as a function of z-axis location. Image noise was defined as the standard deviation (SD) of the mean Hounsfield unit value measured in a region of interest at the center of the phantom's image. Regression analysis was performed to modulated mA and SD vs d_w and OR. The spatial concordance between the change in phantom size and change in mA (SC_mA ) was calculated as the percent difference in the slope of mA(z) change between the 1st and 2nd half of the phantom. The corresponding spatial concordance between the change in phantom size and change in image noise (SC_noise ) was calculated.

RESULTS

Modulated mA(z) along the z-axis did not substantially differentiate between configurations A and B. Correlation between ln(mA) and OR was found to be higher compared to correlation between ln(mA) and d_w . SC_mA was 48% for TCM₁ and 33% for TCM₂ . The corresponding SC_noise was 29% for TCM₁ and 16% for TCM₂ .

CONCLUSION

Apart from routine CT dosimetry evaluations, the standard CTDI phantom positioned in configuration A or B may additionally be used by medical physicists to evaluate the performance of TCM operational characteristics.

Patient size matters: Effect of tube current modulation on size-specific dose estimates (SSDE) and image quality in low-dose lung cancer screening CT

Purpose

We compare the effect of tube current modulation (TCM) and fixed tube current (FTC) on size‐specific dose estimates (SSDE) and image quality in lung cancer screening with low‐dose CT (LDCT) for patients of all sizes.

Methods

Initially, 107 lung screening examinations were performed using FTC, which satisfied the Centers for Medicare & Medicaid Services' volumetric CT dose index (CTDI_vol) limit of 3.0 mGy for standard‐sized patients. Following protocol modification, 287 examinations were performed using TCM. Patient size and examination parameters were collected and water‐equivalent diameter (D_w) and SSDE were determined for each patient. Regression models were used to correlate CTDI_vol and SSDE with D_w. Objective and subjective image quality were measured in 20 patients who had consecutive annual screenings with both FTC and TCM.

Results

CTDI_vol was 2.3 mGy for all FTC scans and increased exponentially with D_w (range = 0.96–4.50 mGy, R² = 0.73) for TCM scans. As patient D_w increased, SSDE decreased for FTC examinations (R² = 1) and increased for TCM examinations (R² = 0.54). Image quality measurements were superior with FTC for smaller sized patients and with TCM for larger sized patients (R² > 0.5, P < 0.005). Radiologist graded all images acceptable for diagnostic evaluation of lung cancer screening.

Conclusion

Although FTC protocol offered a consistently low CTDI_vol for all patients, it yielded unnecessarily high SSDE for small patients and increased image noise for large patients. Lung cancer screening with LDCT using TCM produces radiation doses that are appropriately reduced for small patients and increased for large patients with diagnostic image quality for all patients.

Low-Dose Radiation Advances in Coronary Computed Tomography Angiography in the Diagnosis of Coronary Artery Disease

Background

Coronary computed tomography angiography (CCTA) is now widely used in the diagnosis of coronary artery disease since it is a rapid, minimally invasive test with a diagnostic accuracy comparable to coronary angiography. However, to meet demands for increasing spatial and temporal resolution, higher x-ray radiation doses are required to circumvent the resulting increase in image noise. Exposure to high doses of ionizing radiation with CT imaging is a major health concern due to the potential risk of radiation-associated malignancy. Given its increasing use, a number of dose saving algorithms have been implemented to CCTA to minimize radiation exposure to “as low as reasonably achievable (ALARA)” without compromising diagnostic image quality.

Objective

The purpose of this review is to outline the most recent advances and current status of dose saving techniques in CCTA.

Method

PubMed, Medline, EMBASE and Scholar databases were searched to identify feasibility studies, clinical trials, and technology guidelines on the technical advances in CT scanner hardware and reconstruction software.

Results

Sub-millisievert (mSv) radiation doses have been reported for CCTA due to a combination of strategies such as prospective electrocardiogram-gating, high-pitch helical acquisition, tube current modulation, tube voltage reduction, heart rate reduction, and the most recent novel adaptive iterative reconstruction algorithms.

Conclusion

Advances in radiation dose reduction without loss of image quality justify the use of CCTA as a non-invasive alternative to coronary catheterization in the diagnosis of coronary artery disease.

Estimating fetal dose from tube current-modulated (TCM) and fixed tube current (FTC) abdominal/pelvis CT examinations

PURPOSE

The purpose of this work was to estimate scanner-independent CTDI_vol -to-fetal-dose coefficients for tube current-modulated (TCM) and fixed tube current (FTC) computed tomography (CT) examinations of pregnant patients of various gestational ages undergoing abdominal/pelvic CT examinations.

METHODS

For 24 pregnant patients of gestational age from <5 to 36 weeks who underwent clinically indicated CT examinations, voxelized models of maternal and fetal (or embryo) anatomy were created from abdominal/pelvic image data. Absolute fetal dose (D_fetus ) was estimated using Monte Carlo (MC) simulations of helical scans covering the abdomen and pelvis for TCM and FTC scans. Estimated TCM schemes were generated for each patient model using a validated method that accounts for patient attenuation and scanner output limits for one scanner model and were incorporated into MC simulations. FTC scans were also simulated for each patient model with multidetector row CT scanners from four manufacturers. Normalized fetal dose estimates, nD_fetus , was obtained by dividing D_fetus from the MC simulations by CTDI_vol . Patient size was described using water equivalent diameter (D_w ) measured at the three-dimensional geometric centroid of the fetus. Fetal depth (DE_f ) was measured from the anterior skin surface to the anterior part of the fetus. nD_fetus and D_w were correlated using an exponential model to develop equations for fetal dose conversion coefficients for TCM and FTC abdominal/pelvic CT examinations. Additionally, bivariate linear regression was performed to analyze the correlation of nD_fetus with D_w and fetal depth (DE_f ). For one scanner model, nD_fetus from TCM was compared to FTC and the size-specific dose estimate (SSDE) conversion coefficients (f-factors) from American Association of Physicists in Medicine (AAPM) Report 204. nD_fetus from FTC simulations was averaged across all scanners for each patient ( n D fetus ¯ ) . n D fetus ¯ was then compared with SSDE f-factors and correlated with D_w using an exponential model and with D_w and DE_f using a bivariate linear model.

RESULTS

For TCM, the coefficient of determination (R² ) of nD_fetus and D_w was observed to be 0.73 using an exponential model. Using the bivariate linear model with D_w and DE_f , an R² of 0.78 was observed. For the TCM technology modeled, TCM yielded nD_fetus values that were on average 6% and 17% higher relative to FTC and SSDE f-factors, respectively. For FTC, the R² of n D fetus ¯ with respect to D_w was observed to be 0.64 using an exponential model. Using the bivariate linear model, an R² of 0.75 was observed for n D fetus ¯ with respect to D_w and DE_f . A mean difference of 0.4% was observed between n D fetus ¯ and SSDE f-factors.

CONCLUSION

Good correlations were observed for nD_fetus from TCM and FTC scans using either an exponential model with D_w or a bivariate linear model with both D_w and DE_f . These results indicate that fetal dose from abdomen/pelvis CT examinations of pregnant patients of various gestational ages may be reasonably estimated with models that include (a) scanner-reported CTDI_vol and (b) D_w as a patient size metric, in addition to (c) DE_f if available. These results also suggest that SSDE f-factors may provide a reasonable (within ±25%) estimate of nD_fetus for TCM and FTC abdomen/pelvis CT exams.

Estimating lung, breast, and effective dose from low-dose lung cancer screening CT exams with tube current modulation across a range of patient sizes

PURPOSE

The purpose of this study was to estimate the radiation dose to the lung and breast as well as the effective dose from tube current modulated (TCM) lung cancer screening (LCS) scans across a range of patient sizes.

METHODS

Monte Carlo (MC) methods were used to calculate lung, breast, and effective doses from a low-dose LCS protocol for a 64-slice CT that used TCM. Scanning parameters were from the protocols published by AAPM's Alliance for Quality CT. To determine lung, breast, and effective doses from lung cancer screening, eight GSF/ICRP voxelized phantom models with all radiosensitive organs identified were used to estimate lung, breast, and effective doses. Additionally, to extend the limited size range provided by the GSF/ICRP phantom models, 30 voxelized patient models of thoracic anatomy were generated from LCS patient data. For these patient models, lung and breast were semi-automatically segmented. TCM schemes for each of the GSF/ICRP phantom models were generated using a validated method wherein tissue attenuation and scanner limitations were used to determine the TCM output as a function of table position and source angle. TCM schemes for voxelized patient models were extracted from the raw projection data. The water equivalent diameter, Dw, was used as the patient size descriptor. Dw was estimated for the GSF/ICRP models. For the thoracic patient models, Dw was extracted from the DICOM header of the CT localizer radiograph. MC simulations were performed using the TCM scheme for each model. Absolute organ doses were tallied and effective doses were calculated using ICRP 103 tissue weighting factors for the GSF/ICRP models. Metrics of scanner radiation output were determined based on each model's TCM scheme, including CTDI_vol , dose length product (DLP), and CTDI_{vol, Low Att} , a previously described regional metric of scanner output covering most of the lungs and breast. All lung and breast doses values were normalized by scan-specific CTDI_vol and CTDI_{vol, Low Att} . Effective doses were normalized by scan-specific CTDI_vol and DLP. Absolute and normalized doses were reported as a function of Dw.

RESULTS

Lung doses normalized by CTDI_{vol, Low Att} were modeled as an exponential relationship with respect to Dw with coefficients of determination (R² ) of 0.80. Breast dose normalized by CTDI_{vol, Low Att} was modeled with an exponential relationship to Dw with an R² of 0.23. For all eight GSF/ICRP phantom models, the effective dose using TCM protocols was below 1.6 mSv. Effective doses showed some size dependence but when normalized by DLP demonstrated a constant behavior.

CONCLUSION

Lung, breast, and effective doses from LCS CT exams with TCM were estimated with respect to patient size. Normalized lung dose can be reasonably estimated with a measure of a patient size such as Dw and regional metric of CTDI_vol covering the thorax such as CTDI_{vol, Low Att} , while normalized breast dose can also be estimated with a regional metric of CTDI_vol but with a larger degree of variability than observed for lung. Effective dose normalized by DLP can be estimated with a constant multiplier.

A Projection Quality-Driven Tube Current Modulation Method in Cone-Beam CT for IGRT: Proof of Concept

Purpose:

To develop a projection quality-driven tube current modulation method in cone-beam computed tomography for image-guided radiotherapy based on the prior attenuation information obtained by the planning computed tomography and then evaluate its effect on a reduction in the imaging dose.

Materials and Methods:

The QCKV-1 phantom with different thicknesses (0-400 mm) of solid water upon it was used to simulate different attenuation (μ). Projections were acquired with a series of tube current–exposure time product (mAs) settings, and a 2-dimensional contrast to noise ratio was analyzed for each projection to create a lookup table of mAs versus 2-dimensional contrast to noise ratio, μ. Before a patient underwent computed tomography, the maximum attenuation μmaxθ within the 95% range of each projection angle (θ) was estimated according to the planning computed tomography images. Then, a desired 2-dimensional contrast to noise ratio value was selected, and the mAs setting at θ was calculated with the lookup table of mAs versus 2-dimensional contrast to noise ratio,μmaxθ. Three-dimensional cone-beam computed tomography images were reconstructed using the projections acquired with the selected mAs. The imaging dose was evaluated with a polymethyl methacrylate dosimetry phantom in terms of volume computed tomography dose index. Image quality was analyzed using a Catphan 503 phantom with an oval body annulus and a pelvis phantom.

Results:

For the Catphan 503 phantom, the cone-beam computed tomography image obtained by the projection quality-driven tube current modulation method had a similar quality to that of conventional cone-beam computed tomography . However, the proposed method could reduce the imaging dose by 16% to 33% to achieve an equivalent contrast to noise ratio value. For the pelvis phantom, the structural similarity index was 0.992 with a dose reduction of 39.7% for the projection quality-driven tube current modulation method.

Conclusions:

The proposed method could reduce the additional dose to the patient while not degrading the image quality for cone-beam computed tomography. The projection quality-driven tube current modulation method could be especially beneficial to patients who undergo cone-beam computed tomography frequently during a treatment course.

Relationship between the radiation doses at nonenhanced CT studies using different tube voltages and automatic tube current modulation during anthropomorphic phantoms of young children

To compare the radiation dose and image noise of nonenhanced CT scans performed at 80, 100, and 120 kVp with tube current modulation (TCM) we used anthropomorphic phantoms of newborn, 1‐year‐old, and 5‐year‐old children. The noise index was set at 12. The image noise in the center of the phantoms at the level of the chest and abdomen was measured within a circumscribed region of interest. We measured the doses in individual tissues or organs with radio‐photoluminescence glass dosimeters for each phantom. Various tissues or organs were assigned and the radiation dose was calculated based on the international commission on radiological protection definition. With TCM the respective radiation dose at tube voltages of 80, 100, and 120 was 29.71, 31.60, and 33.79 mGy for the newborn, 32.00, 36.79, and 39.48 mGy for the 1‐year‐old, and 32.78, 38.11, and 40.85 mGy for the 5‐year‐old phantom. There were no significant differences in the radiation dose among the tube voltages and phantoms (P > 0.05). Our comparison of the radiation dose using anthropomorphic phantoms of young children showed that the radiation dose of nonenhanced CT performed at different tube voltages with TCM was not significantly different.

Physical validation of a Monte Carlo-based, phantom-derived approach to computed tomography organ dosimetry under tube current modulation

PURPOSE

To physically validate the accuracy of a Monte Carlo-based, phantom-derived methodology for computed tomography (CT) dosimetry that utilizes organ doses from precomputed axial scans and that accounts for tube current modulation (TCM).

METHODS

The output of a Toshiba Aquilion ONE CT scanner was modeled, based on physical measurement, in the Monte Carlo radiation transport code MCNPX (v2.70). CT examinations were taken of two anthropomorphic phantoms representing pediatric and adult patients (15-yr-old female and adult male) at various energies, in which physical organ dose measurements were made using optically stimulated luminescence dosimeters (OSLDs). These exams (chest-abdomen-pelvis) were modeled using organ dose data obtained from the computationally equivalent phantom of each anthropomorphic phantom. TCM was accounted for by weighting all organ dose contributions by both the relative attenuation of the phantom and the image-derived mA value (from the DICOM header) at the same z-extent (cranial-caudal direction) of the axial dose data.

RESULTS

The root mean squares of percent difference in organ dose when comparing the physical organ dose measurements to the computational estimates were 21.2, 12.1, and 15.1% for the uniform (no attenuation weighting), weighted (computationally derived), and image-based methodologies, respectively.

CONCLUSIONS

Overall, these data suggest that the Monte Carlo-based dosimetry presented in this work is viable for CT dosimetry. Additionally, for CT exams with TCM, local attenuation weighting of organ dose contributions from precomputed axial dosimetry libraries increases organ dose accuracy.

Breast dose reduction with organ-based, wide-angle tube current modulated CT

This study aimed to estimate the organ dose reduction potential for organ-dose-based tube current modulated (ODM) thoracic computed tomography (CT) with a wide dose reduction arc. Twenty-one computational anthropomorphic phantoms (XCAT) were used to create a virtual patient population with clinical anatomic variations. The phantoms were created based on patient images with normal anatomy (age range: 27 to 66 years, weight range: 52.0 to 105.8 kg). For each phantom, two breast tissue compositions were simulated: [Formula: see text] and [Formula: see text] (glandular-to-adipose ratio). A validated Monte Carlo program (PENELOPE, Universitat de Barcelona, Spain) was used to estimate the organ dose for standard tube current modulation (TCM) (SmartmA, GE Healthcare) and ODM (GE Healthcare) for a commercial CT scanner (Revolution, GE Healthcare) using a typical clinical thoracic CT protocol. Both organ dose and [Formula: see text]-to-organ dose conversion coefficients ([Formula: see text] factors) were compared between TCM and ODM. ODM significantly reduced all radiosensitive organ doses ([Formula: see text]). The breast dose was reduced by [Formula: see text]. For [Formula: see text] factors, organs in the anterior region (e.g., thyroid and stomach) exhibited substantial decreases, and the medial, distributed, and posterior region saw either an increase of less than 5% or no significant change. ODM significantly reduced organ doses especially for radiosensitive superficial anterior organs such as the breasts.

Characterization of radiation dose from tube current modulated CT examinations with considerations of both patient size and variable tube current

PURPOSE

The volume CT dose index (CTDI_vol ) and the size-specific dose estimate (SSDE) are widely used for monitoring patient dose from CT examinations. Both metrics may represent the average dose over the central scan plane of the CTDI phantom or the patient under constant tube current (mA), but they are not intended for the tube current modulation (TCM)-enabled CT examinations, in which the peak dose across the scanned range may not be at the scan range center. To overcome the limitation, this paper illustrates an alternative approach, its implementation, and the relationship between longitudinal dose distribution D_L (z) in water cylinder and mA line shape, scan length, as well as phantom diameter.

METHODS

A dose calculation algorithm and the published data by Li et al. [Med. Phys. 40, 031903 (10pp.) (2013); 41, 111910 (5pp.) (2014)] were used to calculate D_L (z) for the central and peripheral axes of 10- to 50-cm diameter water phantoms undergoing CT scans of one constant and three variable mA distributions, each of which in three scan lengths of 10, 28.6, and 50 cm. All scans had an identical average tube current over the scan ranges. The results in the scanned ranges were used to assess the D_L (z) to mA(z) ratios, and their coefficients of variation (CV = stdev/mean) were used to compare the line shapes of D_L (z) and mA(z) for congruence: identical line shapes would result in CV = 0, but largely different line shapes would result in high CV.

RESULTS

In 30-cm diameter water phantom, the line shape of D_L (z) was largely different from that of mA(z). CV was higher in a variable mA scan than in a constant mA scan. As the scan length of variable mA scan increased, CV mostly decreased, and the line shape of D_L (z) more closely resembled that of mA(z). When two phantom axes were compared, CV was smaller and the line shape of D_L (z) more closely resembled that of mA(z) on the peripheral axis than on the central axis. In 41 water phantoms included in this study, CV mostly increased with phantom diameter, and approached the limiting levels on the peripheral axes of large phantoms. In constant mA scans, CV ranged from 5.5% to 14.0% on the phantom central axes and from 4.6% to 6.4% on the phantom peripheral axes. However, in variable tube current scans, CV ranged from 7.4% to 70.0% on the phantom central axes and from 5.1% to 35.9% on the phantom peripheral axes.

CONCLUSION

D_L (z) (water) may be advantageous over current CT dose metrics in characterizing the dose dependences on both patient size and mA line shape from tube current modulated examinations. Evaluating D_L (z) (water) with the water equivalent diameter and tube current curve from clinical examinations has a potential to improve CT dose monitoring program.

Estimating patient dose from CT exams that use automatic exposure control: Development and validation of methods to accurately estimate tube current values

PURPOSE

The vast majority of body CT exams are performed with automatic exposure control (AEC), which adapts the mean tube current to the patient size and modulates the tube current either angularly, longitudinally or both. However, most radiation dose estimation tools are based on fixed tube current scans. Accurate estimates of patient dose from AEC scans require knowledge of the tube current values, which is usually unavailable. The purpose of this work was to develop and validate methods to accurately estimate the tube current values prescribed by one manufacturer's AEC system to enable accurate estimates of patient dose.

METHODS

Methods were developed that took into account available patient attenuation information, user selected image quality reference parameters and x-ray system limits to estimate tube current values for patient scans. Methods consistent with AAPM Report 220 were developed that used patient attenuation data that were: (a) supplied by the manufacturer in the CT localizer radiograph and (b) based on a simulated CT localizer radiograph derived from image data. For comparison, actual tube current values were extracted from the projection data of each patient. Validation of each approach was based on data collected from 40 pediatric and adult patients who received clinically indicated chest (n = 20) and abdomen/pelvis (n = 20) scans on a 64 slice multidetector row CT (Sensation 64, Siemens Healthcare, Forchheim, Germany). For each patient dataset, the following were collected with Institutional Review Board (IRB) approval: (a) projection data containing actual tube current values at each projection view, (b) CT localizer radiograph (topogram) and (c) reconstructed image data. Tube current values were estimated based on the actual topogram (actual-topo) as well as the simulated topogram based on image data (sim-topo). Each of these was compared to the actual tube current values from the patient scan. In addition, to assess the accuracy of each method in estimating patient organ doses, Monte Carlo simulations were performed by creating voxelized models of each patient, identifying key organs and incorporating tube current values into the simulations to estimate dose to the lungs and breasts (females only) for chest scans and the liver, kidney, and spleen for abdomen/pelvis scans. Organ doses from simulations using the actual tube current values were compared to those using each of the estimated tube current values (actual-topo and sim-topo).

RESULTS

When compared to the actual tube current values, the average error for tube current values estimated from the actual topogram (actual-topo) and simulated topogram (sim-topo) was 3.9% and 5.8% respectively. For Monte Carlo simulations of chest CT exams using the actual tube current values and estimated tube current values (based on the actual-topo and sim-topo methods), the average differences for lung and breast doses ranged from 3.4% to 6.6%. For abdomen/pelvis exams, the average differences for liver, kidney, and spleen doses ranged from 4.2% to 5.3%.

CONCLUSIONS

Strong agreement between organ doses estimated using actual and estimated tube current values provides validation of both methods for estimating tube current values based on data provided in the topogram or simulated from image data.

Estimating organ doses from tube current modulated CT examinations using a generalized linear model

PURPOSE

Currently, available Computed Tomography dose metrics are mostly based on fixed tube current Monte Carlo (MC) simulations and/or physical measurements such as the size specific dose estimate (SSDE). In addition to not being able to account for Tube Current Modulation (TCM), these dose metrics do not represent actual patient dose. The purpose of this study was to generate and evaluate a dose estimation model based on the Generalized Linear Model (GLM), which extends the ability to estimate organ dose from tube current modulated examinations by incorporating regional descriptors of patient size, scanner output, and other scan-specific variables as needed.

METHODS

The collection of a total of 332 patient CT scans at four different institutions was approved by each institution's IRB and used to generate and test organ dose estimation models. The patient population consisted of pediatric and adult patients and included thoracic and abdomen/pelvis scans. The scans were performed on three different CT scanner systems. Manual segmentation of organs, depending on the examined anatomy, was performed on each patient's image series. In addition to the collected images, detailed TCM data were collected for all patients scanned on Siemens CT scanners, while for all GE and Toshiba patients, data representing z-axis-only TCM, extracted from the DICOM header of the images, were used for TCM simulations. A validated MC dosimetry package was used to perform detailed simulation of CT examinations on all 332 patient models to estimate dose to each segmented organ (lungs, breasts, liver, spleen, and kidneys), denoted as reference organ dose values. Approximately 60% of the data were used to train a dose estimation model, while the remaining 40% was used to evaluate performance. Two different methodologies were explored using GLM to generate a dose estimation model: (a) using the conventional exponential relationship between normalized organ dose and size with regional water equivalent diameter (WED) and regional CTDI_vol as variables and (b) using the same exponential relationship with the addition of categorical variables such as scanner model and organ to provide a more complete estimate of factors that may affect organ dose. Finally, estimates from generated models were compared to those obtained from SSDE and ImPACT.

RESULTS

The Generalized Linear Model yielded organ dose estimates that were significantly closer to the MC reference organ dose values than were organ doses estimated via SSDE or ImPACT. Moreover, the GLM estimates were better than those of SSDE or ImPACT irrespective of whether or not categorical variables were used in the model. While the improvement associated with a categorical variable was substantial in estimating breast dose, the improvement was minor for other organs.

CONCLUSIONS

The GLM approach extends the current CT dose estimation methods by allowing the use of additional variables to more accurately estimate organ dose from TCM scans. Thus, this approach may be able to overcome the limitations of current CT dose metrics to provide more accurate estimates of patient dose, in particular, dose to organs with considerable variability across the population.

Convolution-based estimation of organ dose in tube current modulated CT

Estimating organ dose for clinical patients requires accurate modeling of the patient anatomy and the dose field of the CT exam. The modeling of patient anatomy can be achieved using a library of representative computational phantoms (Samei et al 2014 Pediatr. Radiol. 44 460-7). The modeling of the dose field can be challenging for CT exams performed with a tube current modulation (TCM) technique. The purpose of this work was to effectively model the dose field for TCM exams using a convolution-based method. A framework was further proposed for prospective and retrospective organ dose estimation in clinical practice. The study included 60 adult patients (age range: 18-70 years, weight range: 60-180 kg). Patient-specific computational phantoms were generated based on patient CT image datasets. A previously validated Monte Carlo simulation program was used to model a clinical CT scanner (SOMATOM Definition Flash, Siemens Healthcare, Forchheim, Germany). A practical strategy was developed to achieve real-time organ dose estimation for a given clinical patient. CTDIvol-normalized organ dose coefficients ([Formula: see text]) under constant tube current were estimated and modeled as a function of patient size. Each clinical patient in the library was optimally matched to another computational phantom to obtain a representation of organ location/distribution. The patient organ distribution was convolved with a dose distribution profile to generate [Formula: see text] values that quantified the regional dose field for each organ. The organ dose was estimated by multiplying [Formula: see text] with the organ dose coefficients ([Formula: see text]). To validate the accuracy of this dose estimation technique, the organ dose of the original clinical patient was estimated using Monte Carlo program with TCM profiles explicitly modeled. The discrepancy between the estimated organ dose and dose simulated using TCM Monte Carlo program was quantified. We further compared the convolution-based organ dose estimation method with two other strategies with different approaches of quantifying the irradiation field. The proposed convolution-based estimation method showed good accuracy with the organ dose simulated using the TCM Monte Carlo simulation. The average percentage error (normalized by CTDIvol) was generally within 10% across all organs and modulation profiles, except for organs located in the pelvic and shoulder regions. This study developed an improved method that accurately quantifies the irradiation field under TCM scans. The results suggested that organ dose could be estimated in real-time both prospectively (with the localizer information only) and retrospectively (with acquired CT data).

Task-driven image acquisition and reconstruction in cone-beam CT

This work introduces a task-driven imaging framework that incorporates a mathematical definition of the imaging task, a model of the imaging system, and a patient-specific anatomical model to prospectively design image acquisition and reconstruction techniques to optimize task performance. The framework is applied to joint optimization of tube current modulation, view-dependent reconstruction kernel, and orbital tilt in cone-beam CT. The system model considers a cone-beam CT system incorporating a flat-panel detector and 3D filtered backprojection and accurately describes the spatially varying noise and resolution over a wide range of imaging parameters in the presence of a realistic anatomical model. Task-based detectability index (d') is incorporated as the objective function in a task-driven optimization of image acquisition and reconstruction techniques. The orbital tilt was optimized through an exhaustive search across tilt angles ranging ± 30°. For each tilt angle, the view-dependent tube current and reconstruction kernel (i.e. the modulation profiles) that maximized detectability were identified via an alternating optimization. The task-driven approach was compared with conventional unmodulated and automatic exposure control (AEC) strategies for a variety of imaging tasks and anthropomorphic phantoms. The task-driven strategy outperformed the unmodulated and AEC cases for all tasks. For example, d' for a sphere detection task in a head phantom was improved by 30% compared to the unmodulated case by using smoother kernels for noisy views and distributing mAs across less noisy views (at fixed total mAs) in a manner that was beneficial to task performance. Similarly for detection of a line-pair pattern, the task-driven approach increased d' by 80% compared to no modulation by means of view-dependent mA and kernel selection that yields modulation transfer function and noise-power spectrum optimal to the task. Optimization of orbital tilt identified the tilt angle that reduced quantum noise in the region of the stimulus by avoiding highly attenuating anatomical structures. The task-driven imaging framework offers a potentially valuable paradigm for prospective definition of acquisition and reconstruction protocols that improve task performance without increase in dose.

Methods for CT automatic exposure control protocol translation between scanner platforms

PURPOSE

An imaging facility with a diverse fleet of CT scanners faces considerable challenges when propagating CT protocols with consistent image quality and patient dose across scanner makes and models. Although some protocol parameters can comfortably remain constant among scanners (eg, tube voltage, gantry rotation time), the automatic exposure control (AEC) parameter, which selects the overall mA level during tube current modulation, is difficult to match among scanners, especially from different CT manufacturers.

METHODS

Objective methods for converting tube current modulation protocols among CT scanners were developed. Three CT scanners were investigated, a GE LightSpeed 16 scanner, a GE VCT scanner, and a Siemens Definition AS+ scanner. Translation of the AEC parameters such as noise index and quality reference mAs across CT scanners was specifically investigated. A variable-diameter poly(methyl methacrylate) phantom was imaged on the 3 scanners using a range of AEC parameters for each scanner. The phantom consisted of 5 cylindrical sections with diameters of 13, 16, 20, 25, and 32 cm. The protocol translation scheme was based on matching either the volumetric CT dose index or image noise (in Hounsfield units) between two different CT scanners. A series of analytic fit functions, corresponding to different patient sizes (phantom diameters), were developed from the measured CT data. These functions relate the AEC metric of the reference scanner, the GE LightSpeed 16 in this case, to the AEC metric of a secondary scanner.

RESULTS

When translating protocols between different models of CT scanners (from the GE LightSpeed 16 reference scanner to the GE VCT system), the translation functions were linear. However, a power-law function was necessary to convert the AEC functions of the GE LightSpeed 16 reference scanner to the Siemens Definition AS+ secondary scanner, because of differences in the AEC functionality designed by these two companies.

CONCLUSIONS

Protocol translation on the basis of quantitative metrics (volumetric CT dose index or measured image noise) is feasible. Protocol translation has a dependency on patient size, especially between the GE and Siemens systems. Translation schemes that preserve dose levels may not produce identical image quality.

Radiation dose reduction in thoracic and abdomen-pelvic CT using tube current modulation: a phantom study

This phantom study was designed to compare the radiation dose in thoracic and abdomen-pelvic CT scans with and without use of tube current modulation (TCM). Effective dose (ED) and size-specific dose estimation (SSDE) were calculated with the absorbed doses measured at selective radiosensitive organs using a thermoluminescence dosimeter-100 (TLD-100). When compared to protocols without TCM, the ED and SSDE were reduced significantly with use of TCM for both the thoracic and abdomen-pelvic CT. With use of TCM, the ED was 6.50 ± 0.29 mSv for thoracic and 6.01 ± 0.20 mSv for the abdomen-pelvic CT protocols. However without use of TCM, the ED was 20.07 ± 0.24 mSv and 17.30 ± 0.41 mSv for the thoracic and abdomen-pelvic CT protocols, respectively. The corresponding SSDE was 10.18 ± 0.48 mGy and 11.96 ± 0.27 mGy for the thoracic and abdomen-pelvic CT protocols with TCM, and 31.56 ± 0.43 mGy and 33.23 ± 0.05 mGy for thoracic and abdomen-pelvic CT protocols without TCM, respectively. The highest absorbed dose was measured at the breast with 8.58 ± 0.12 mGy in the TCM protocols and 51.52 ± 14.72 mGy in the protocols without TCM during thoracic CT. In the abdomen-pelvic CT, the absorbed dose was highest at the skin with 9.30 ± 1.28mGy and 29.99 ± 2.23 mGy in protocols with and without use of TCM, respectively. In conclusion, the TCM technique results in significant dose reduction; thus it is to be highly recommended in routine thoracic and abdomen-pelvic CT.

The feasibility of a regional CTDIvol to estimate organ dose from tube current modulated CT exams

PURPOSE

In AAPM Task Group 204, the size-specific dose estimate (SSDE) was developed by providing size adjustment factors which are applied to the Computed Tomography (CT) standardized dose metric, CTDI(vol). However, that work focused on fixed tube current scans and did not specifically address tube current modulation (TCM) scans, which are currently the majority of clinical scans performed. The purpose of this study was to extend the SSDE concept to account for TCM by investigating the feasibility of using anatomic and organ specific regions of scanner output to improve accuracy of dose estimates.

METHODS

Thirty-nine adult abdomen/pelvis and 32 chest scans from clinically indicated CT exams acquired on a multidetector CT using TCM were obtained with Institutional Review Board approval for generating voxelized models. Along with image data, raw projection data were obtained to extract TCM functions for use in Monte Carlo simulations. Patient size was calculated using the effective diameter described in TG 204. In addition, the scanner-reported CTDI(vo)l (CTDI(vol),global) was obtained for each patient, which is based on the average tube current across the entire scan. For the abdomen/pelvis scans, liver, spleen, and kidneys were manually segmented from the patient datasets; for the chest scans, lungs and for female models only, glandular breast tissue were segmented. For each patient organ doses were estimated using Monte Carlo Methods. To investigate the utility of regional measures of scanner output, regional and organ anatomic boundaries were identified from image data and used to calculate regional and organ-specific average tube current values. From these regional and organ-specific averages, CTDI(vol) values, referred to as regional and organ-specific CTDI(vol), were calculated for each patient. Using an approach similar to TG 204, all CTDI(vol) values were used to normalize simulated organ doses; and the ability of each normalized dose to correlate with patient size was investigated.

RESULTS

For all five organs, the correlations with patient size increased when organ doses were normalized by regional and organ-specific CTDI(vol) values. For example, when estimating dose to the liver, CTDI(vol),global yielded a R(2) value of 0.26, which improved to 0.77 and 0.86, when using the regional and organ-specific CTDI(vol) for abdomen and liver, respectively. For breast dose, the global CTDI(vol) yielded a R(2) value of 0.08, which improved to 0.58 and 0.83, when using the regional and organ-specific CTDI(vol) for chest and breasts, respectively. The R(2) values also increased once the thoracic models were separated for the analysis into females and males, indicating differences between genders in this region not explained by a simple measure of effective diameter.

CONCLUSIONS

This work demonstrated the utility of regional and organ-specific CTDI(vol) as normalization factors when using TCM. It was demonstrated that CTDI(vol),global is not an effective normalization factor in TCM exams where attenuation (and therefore tube current) varies considerably throughout the scan, such as abdomen/pelvis and even thorax. These exams can be more accurately assessed for dose using regional CTDI(vol) descriptors that account for local variations in scanner output present when TCM is employed.

Dynamic bowtie for fan-beam CT

A bowtie is a filter used to shape an x-ray beam and equalize its flux reaching different detector channels. For development of spectral CT with energy discriminating photon-counting (EDPC) detectors, here we propose and evaluate a dynamic bowtie for performance optimization based on a patient model or a scout scan. With a mechanical rotation of a dynamic bowtie and an adaptive adjustment of an x-ray source flux, an x-ray beam intensity profile can be modulated. First, a mathematical model for dynamic bowtie filtering is established for an elliptical section in fan-beam geometry, and the contour of the optimal bowtie is derived. Then, numerical simulation is performed to compare the performance of the dynamic bowtie in the cases of an ideal phantom and a realistic cross-section relative to the counterparts without any bowtie and with a fixed bowtie respectively. Our dynamic bowtie can equalize the expected numbers of photons in the case of an ideal phantom. In practical cases, our dynamic bowtie can effectively reduce the dynamic range of detected signals inside the field of view. Although our design is optimized for an elliptical phantom, the resultant dynamic bowtie can be applied to a real fan-beam scan if the underlying cross-section can be approximated as an ellipse. Furthermore, our design methodology can be applied to specify an optimized dynamic bowtie for any cross-section of a patient, preferably using rapid prototyping technology.