EFFECTIVE DOSE ESTIMATION FROM ORGAN DOSE MEASUREMENTS IN FAST-kV SWITCH DUAL ENERGY COMPUTED TOMOGRAPHY.

The purpose of this study was to validate a novel approach to estimating effective dose (E) in 'fast-kV switch dual energy computed tomography' using MOSFET detectors. The effective energy of the combined dual energy environment was characterized with the dual energy CT scanner and then MOSFETs were calibrated matching to the effective energy of the dual energy CT beam with a conventional CT beam. The calibration method was then experimentally validated by comparing the dose between MOSFET and an ion chamber (IC) using a standard CTDI body phantom. The measured doses of the MOSFET and IC were 17.1 mGy ± 3.8% and 17.1 mGy ± 0.4%, respectively. To measure organ doses, an adult anthropomorphic phantom loaded with 18 MOSFET detectors was scanned using a standard fast-kV switch dual energy abdomen/pelvis CT protocol. E was calculated by applying ICRP 103 tissue weighting factors as well as partial volume correction factors for organs that were not completely covered by the protocol field-of-view. E from the dual energy abdomen/pelvis CT was calculated to be 17.8 mSv ± 11.6%. This calculation was then compared to E from dose length product method, which yielded 14.62 mSv.

Volumetric quantification of lung nodules in CT with iterative reconstruction (ASiR and MBIR).

PURPOSE: Volume quantifications of lung nodules with multidetector computed tomography (CT) images provide useful information for monitoring nodule developments. The accuracy and precision of the volume quantification, however, can be impacted by imaging and reconstruction parameters. This study aimed to investigate the impact of iterative reconstruction algorithms on the accuracy and precision of volume quantification with dose and slice thickness as additional variables. METHODS: Repeated CT images were acquired from an anthropomorphic chest phantom with synthetic nodules (9.5 and 4.8 mm) at six dose levels, and reconstructed with three reconstruction algorithms [filtered backprojection (FBP), adaptive statistical iterative reconstruction (ASiR), and model based iterative reconstruction (MBIR)] into three slice thicknesses. The nodule volumes were measured with two clinical software (A: Lung VCAR, B: iNtuition), and analyzed for accuracy and precision. RESULTS: Precision was found to be generally comparable between FBP and iterative reconstruction with no statistically significant difference noted for different dose levels, slice thickness, and segmentation software. Accuracy was found to be more variable. For large nodules, the accuracy was significantly different between ASiR and FBP for all slice thicknesses with both software, and significantly different between MBIR and FBP for 0.625 mm slice thickness with Software A and for all slice thicknesses with Software B. For small nodules, the accuracy was more similar between FBP and iterative reconstruction, with the exception of ASIR vs FBP at 1.25 mm with Software A and MBIR vs FBP at 0.625 mm with Software A. CONCLUSIONS: The systematic difference between the accuracy of FBP and iterative reconstructions highlights the importance of extending current segmentation software to accommodate the image characteristics of iterative reconstructions. In addition, a calibration process may help reduce the dependency of accuracy on reconstruction algorithms, such that volumes quantified from scans of different reconstruction algorithms can be compared. The little difference found between the precision of FBP and iterative reconstructions could be a result of both iterative reconstruction's diminished noise reduction at the edge of the nodules as well as the loss of resolution at high noise levels with iterative reconstruction. The findings do not rule out potential advantage of IR that might be evident in a study that uses a larger number of nodules or repeated scans.

Clinical impact of an adaptive statistical iterative reconstruction algorithm for detection of hypervascular liver tumours using a low tube voltage, high tube current MDCT technique.

OBJECTIVES: To investigate the impact of an adaptive statistical iterative reconstruction (ASiR) algorithm on diagnostic accuracy and confidence for the diagnosis of hypervascular liver tumours, as well as the reader's perception of image quality, using a low tube voltage (80 kVp), high tube current computed tomography (CT) technique. METHODS: Forty patients (29 men, 11 women) with 65 hypervascular liver tumours underwent dual energy CT. The 80 kV set of the dual energy acquisition was reconstructed with standard filtered backprojection (FBP) and ASiR at different blending levels. Lesion contrast-to-noise ratio (CNR), reader's confidence for lesion detection and characterisation, and reader's evaluation of image quality were recorded. RESULTS: ASiR yielded significantly higher CNR values compared with FBP (P < 0.0001 for all comparisons). Reader's perception of lesion conspicuity and confidence in the diagnosis of malignancy were also higher with 60 % and 80 % ASiR, compared with FBP (P = 0.01 and < 0.001, respectively). Compared with FBP, ASiR yielded nearly significantly lower specificity for lesion detection and a substantial decrease in the reader's perception of image quality. CONCLUSIONS: Compared with the standard FBP algorithm, ASiR significantly improves conspicuity of hypervascular liver lesions. This improvement may come at the cost of decreased specificity and reader's perception of image quality.

Quantitative CT: technique dependence of volume estimation on pulmonary nodules.

Current estimation of lung nodule size typically relies on uni- or bi-dimensional techniques. While new three-dimensional volume estimation techniques using MDCT have improved size estimation of nodules with irregular shapes, the effect of acquisition and reconstruction parameters on accuracy (bias) and precision (variance) of the new techniques has not been fully investigated. To characterize the volume estimation performance dependence on these parameters, an anthropomorphic chest phantom containing synthetic nodules was scanned and reconstructed with protocols across various acquisition and reconstruction parameters. Nodule volumes were estimated by a clinical lung analysis software package, LungVCAR. Precision and accuracy of the volume assessment were calculated across the nodules and compared between protocols via a generalized estimating equation analysis. Results showed that the precision and accuracy of nodule volume quantifications were dependent on slice thickness, with different dependences for different nodule characteristics. Other parameters including kVp, pitch, and reconstruction kernel had lower impact. Determining these technique dependences enables better volume quantification via protocol optimization and highlights the importance of consistent imaging parameters in sequential examinations.

Lung nodule detection in pediatric chest CT: quantitative relationship between image quality and radiologist performance.

PURPOSE: To determine the quantitative relationship between image quality and radiologist performance in detecting small lung nodules in pediatric CT. METHODS: The study included clinical chest CT images of 30 pediatric patients (0-16 years) scanned at tube currents of 55-180 mA. Calibrated noise addition software was used to simulate cases at three nominal mA settings: 70, 35, and 17.5 mA, resulting in quantum noise of 7-32 Hounsfield Unit (HU). Using a validated nodule simulation technique, lung nodules with diameters of 3-5 mm and peak contrasts of 200-500 HU were inserted into the cases, which were then randomized and rated independently by four experienced pediatric radiologists for nodule presence on a continuous scale from 0 (definitely absent) to 100 (definitely present). The receiver operating characteristic (ROC) data were analyzed to quantify the relationship between diagnostic accuracy (area under the ROC curve, AUC) and image quality (the product of nodule peak contrast and displayed diameter to noise ratio, CDNR display). RESULTS: AUC increased rapidly from 0.70 to 0.87 when CDNR display increased from 60 to 130 mm, followed by a slow increase to 0.94 when CDNR display further increased to 257 mm. For the average nodule diameter (4 mm) and contrast (350 HU), AUC decreased from 0.93 to 0.71 with noise increased from 7 to 28 HU. CONCLUSIONS: We quantified the relationship between image quality and the performance of radiologists in detecting lung nodules in pediatric CT. The relationship can guide CT protocol design to achieve the desired diagnostic performance at the lowest radiation dose.]

Patient-specific radiation dose and cancer risk for pediatric chest CT.

PURPOSE: To estimate patient-specific radiation dose and cancer risk for pediatric chest computed tomography (CT) and to evaluate factors affecting dose and risk, including patient size, patient age, and scanning parameters. MATERIALS AND METHODS: The institutional review board approved this study and waived informed consent. This study was HIPAA compliant. The study included 30 patients (0-16 years old), for whom full-body computer models were recently created from clinical CT data. A validated Monte Carlo program was used to estimate organ dose from eight chest protocols, representing clinically relevant combinations of bow tie filter, collimation, pitch, and tube potential. Organ dose was used to calculate effective dose and risk index (an index of total cancer incidence risk). The dose and risk estimates before and after normalization by volume-weighted CT dose index (CTDI(vol)) or dose-length product (DLP) were correlated with patient size and age. The effect of each scanning parameter was studied. RESULTS: Organ dose normalized by tube current-time product or CTDI(vol) decreased exponentially with increasing average chest diameter. Effective dose normalized by tube current-time product or DLP decreased exponentially with increasing chest diameter. Chest diameter was a stronger predictor of dose than weight and total scan length. Risk index normalized by tube current-time product or DLP decreased exponentially with both chest diameter and age. When normalized by DLP, effective dose and risk index were independent of collimation, pitch, and tube potential (<10% variation). CONCLUSION: The correlations of dose and risk with patient size and age can be used to estimate patient-specific dose and risk. They can further guide the design and optimization of pediatric chest CT protocols. SUPPLEMENTAL MATERIAL: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.11101900/-/DC1.

Patient-specific radiation dose and cancer risk estimation in CT: part I. development and validation of a Monte Carlo program.

PURPOSE: Radiation-dose awareness and optimization in CT can greatly benefit from a dose-reporting system that provides dose and risk estimates specific to each patient and each CT examination. As the first step toward patient-specific dose and risk estimation, this article aimed to develop a method for accurately assessing radiation dose from CT examinations. METHODS: A Monte Carlo program was developed to model a CT system (LightSpeed VCT, GE Healthcare). The geometry of the system, the energy spectra of the x-ray source, the three-dimensional geometry of the bowtie filters, and the trajectories of source motions during axial and helical scans were explicitly modeled. To validate the accuracy of the program, a cylindrical phantom was built to enable dose measurements at seven different radial distances from its central axis. Simulated radial dose distributions in the cylindrical phantom were validated against ion chamber measurements for single axial scans at all combinations of tube potential and bowtie filter settings. The accuracy of the program was further validated using two anthropomorphic phantoms (a pediatric one-year-old phantom and an adult female phantom). Computer models of the two phantoms were created based on their CT data and were voxelized for input into the Monte Carlo program. Simulated dose at various organ locations was compared against measurements made with thermoluminescent dosimetry chips for both single axial and helical scans. RESULTS: For the cylindrical phantom, simulations differed from measurements by -4.8% to 2.2%. For the two anthropomorphic phantoms, the discrepancies between simulations and measurements ranged between (-8.1%, 8.1%) and (-17.2%, 13.0%) for the single axial scans and the helical scans, respectively. CONCLUSIONS: The authors developed an accurate Monte Carlo program for assessing radiation dose from CT examinations. When combined with computer models of actual patients, the program can provide accurate dose estimates for specific patients.

Patient-specific radiation dose and cancer risk estimation in CT: part II. Application to patients.

PURPOSE: Current methods for estimating and reporting radiation dose from CT examinations are largely patient-generic; the body size and hence dose variation from patient to patient is not reflected. Furthermore, the current protocol designs rely on dose as a surrogate for the risk of cancer incidence, neglecting the strong dependence of risk on age and gender. The purpose of this study was to develop a method for estimating patient-specific radiation dose and cancer risk from CT examinations. METHODS: The study included two patients (a 5-week-old female patient and a 12-year-old male patient), who underwent 64-slice CT examinations (LightSpeed VCT, GE Healthcare) of the chest, abdomen, and pelvis at our institution in 2006. For each patient, a nonuniform rational B-spine (NURBS) based full-body computer model was created based on the patient's clinical CT data. Large organs and structures inside the image volume were individually segmented and modeled. Other organs were created by transforming an existing adult male or female full-body computer model (developed from visible human data) to match the framework defined by the segmented organs, referencing the organ volume and anthropometry data in ICRP Publication 89. A Monte Carlo program previously developed and validated for dose simulation on the LightSpeed VCT scanner was used to estimate patient-specific organ dose, from which effective dose and risks of cancer incidence were derived. Patient-specific organ dose and effective dose were compared with patient-generic CT dose quantities in current clinical use: the volume-weighted CT dose index (CTDIvol) and the effective dose derived from the dose-length product (DLP). RESULTS: The effective dose for the CT examination of the newborn patient (5.7 mSv) was higher but comparable to that for the CT examination of the teenager patient (4.9 mSv) due to the size-based clinical CT protocols at our institution, which employ lower scan techniques for smaller patients. However, the overall risk of cancer incidence attributable to the CT examination was much higher for the newborn (2.4 in 1000) than for the teenager (0.7 in 1000). For the two pediatric-aged patients in our study, CTDIvol underestimated dose to large organs in the scan coverage by 30%-48%. The effective dose derived from DLP using published conversion coefficients differed from that calculated using patient-specific organ dose values by -57% to 13%, when the tissue weighting factors of ICRP 60 were used, and by -63% to 28%, when the tissue weighting factors of ICRP 103 were used. CONCLUSIONS: It is possible to estimate patient-specific radiation dose and cancer risk from CT examinations by combining a validated Monte Carlo program with patient-specific anatomical models that are derived from the patients' clinical CT data and supplemented by transformed models of reference adults. With the construction of a large library of patient-specific computer models encompassing patients of all ages and weight percentiles, dose and risk can be estimated for any patient prior to or after a CT examination. Such information may aid in decisions for image utilization and can further guide the design and optimization of CT technologies and scan protocols.

Pediatric MDCT: towards assessing the diagnostic influence of dose reduction on the detection of small lung nodules.

RATIONALE AND OBJECTIVES: The purpose of this study was to evaluate the effect of reduced tube current (dose) on lung nodule detection in pediatric multidetector array computed tomography (MDCT). MATERIALS AND METHODS: The study included normal clinical chest MDCT images of 13 patients (aged 1-7 years) scanned at tube currents of 70 to 180 mA. Calibrated noise addition software was used to simulate cases as they would have been acquired at 70 mA (the lowest original tube current), 35 mA (50% reduction), and 17.5 mA (75% reduction). Using a validated nodule simulation technique, small lung nodules of 3 to 5 mm in diameter were inserted into the cases, which were then randomized and rated independently by three experienced pediatric radiologists for nodule presence on a continuous scale ranging from zero (definitely absent) to 100 (definitely present). The observer data were analyzed to assess the influence of dose on detection accuracy using the Dorfman-Berbaum-Mets method for multiobserver, multitreatment receiver-operating characteristic (ROC) analysis and the Williams trend test. RESULTS: The areas under the ROC curves were 0.95, 0.91, and 0.92 at 70, 35, and 17.5 mA, respectively, with standard errors of 0.02 and interobserver variability of 0.02. The Dorfman-Berbaum-Mets method and the Williams trend test yielded P values for the effect of dose of .09 and .05, respectively. CONCLUSION: Tube current (dose) has a weak effect on the detection accuracy of small lung nodules in pediatric MDCT. The effect on detection accuracy of a 75% dose reduction was comparable to interobserver variability, suggesting a potential for dose reduction.

Quantitative effects of contrast enhanced CT attenuation correction on PET SUV measurements.

PURPOSE: The presence of contrast materials on computed tomography (CT) images can cause problems in the attenuation correction of positron emission tomography (PET) images. These are because of errors converting the CT attenuation of contrast to 511-keV attenuation and by the change in tissue enhancement over the duration of the PET emission scan. Newer CT-based attenuation correction (CTAC) algorithms have been developed to reduce these errors. METHODS: To evaluate the effectiveness of the modified CTAC technique, we performed a retrospective analysis on 20 patients, comparing PET images using unenhanced and contrast-enhanced CT scans for attenuation correction. A phantom study was performed to simulate the effects of contrast on radiotracer concentration measurements. RESULTS: There was a maximum difference in calculated radiotracer concentrations of 5.9% within the retrospective data and 7% within the phantom data. CONCLUSION: Using a CTAC algorithm that de-emphasizes high-density areas, contrast-enhanced CT can be used for attenuation mapping without significant errors in quantitation.

Patient-specific dose estimation for pediatric chest CT.

Current methods for organ and effective dose estimations in pediatric CT are largely patient generic. Physical phantoms and computer models have only been developed for standard/limited patient sizes at discrete ages (e.g., 0, 1, 5, 10, 15 years old) and do not reflect the variability of patient anatomy and body habitus within the same size/age group. In this investigation, full-body computer models of seven pediatric patients in the same size/protocol group (weight: 11.9-18.2 kg) were created based on the patients' actual multi-detector array CT (MDCT) data. Organs and structures in the scan coverage were individually segmented. Other organs and structures were created by morphing existing adult models (developed from visible human data) to match the framework defined by the segmented organs, referencing the organ volume and anthropometry data in ICRP Publication 89. Organ and effective dose of these patients from a chest MDCT scan protocol (64 slice LightSpeed VCT scanner, 120 kVp, 70 or 75 mA, 0.4 s gantry rotation period, pitch of 1.375, 20 mm beam collimation, and small body scan field-of-view) was calculated using a Monte Carlo program previously developed and validated to simulate radiation transport in the same CT system. The seven patients had normalized effective dose of 3.7-5.3 mSv/100 mAs (coefficient of variation: 10.8%). Normalized lung dose and heart dose were 10.4-12.6 mGy/100 mAs and 11.2-13.3 mGy/100 mAs, respectively. Organ dose variations across the patients were generally small for large organs in the scan coverage (<7%), but large for small organs in the scan coverage (9%-18%) and for partially or indirectly exposed organs (11%-77%). Normalized effective dose correlated weakly with body weight (correlation coefficient: r=-0.80). Normalized lung dose and heart dose correlated strongly with mid-chest equivalent diameter (lung: r=-0.99, heart: r=-0.93); these strong correlation relationships can be used to estimate patient-specific organ dose for any other patient in the same size/protocol group who undergoes the chest scan. In summary, this work reported the first assessment of dose variations across pediatric CT patients in the same size/protocol group due to the variability of patient anatomy and body habitus and provided a previously unavailable method for patient-specific organ dose estimation, which will help in assessing patient risk and optimizing dose reduction strategies, including the development of scan protocols.