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Investigation of American Association of Physicists in Medicine Report 204 Size-specific Dose Estimates for Pediatric CT Implementation

PURPOSE To compare five methodologies the American Association of Physicists in Medicine Report 204 used to calculate size-specific dose estimates (SSDEs) for pediatric computed tomography (CT). MATERIALS AND METHODS The institutional review board waived consent for this HIPAA-compliant retrospective study. The five SSDE methodologies were investigated for calculation variation based on volumetric CT dose index (CTDI), or CTDI(vol), of chest, abdominal, and pelvic CT. SSDE calculations were derived from a predominantly pediatric population of 186 patients retrospectively and consecutively analyzed from June through November 2011. Eighty (43%) of the 186 patients were female, and 106 (57%) were male. Mean patient age was 8.6 years ± 6.3 (standard deviation), the age range was 1 month to 28 years, and mean weight was 37.7 kg ± 33.1, with a range of 3.4-146.6 kg. SSDE conversion factors were derived from anteroposterior (AP) and lateral dimensions measured on the patients CT radiograph. The measurements were either used independently, or as a summation, or to calculate the patients effective diameter; additionally, SSDE was derived on the basis of the patients age (International Commission on Radiation Units Report 74 data). SSDE conversion factors were applied to CTDI(vol) data that corrected for both 16- and 32-cm-diameter CTDI phantom measurements. SSDE data were summarized by using the patients originally prescribed weight-based CT scanning protocols. Data were summarized by using descriptive statistics. RESULTS SSDEs derived from individual measurements varied 2%-12%. The combination of measurements (sum or effective diameter) varied 0.9%-2%. The age approach varied by an average of 2% (in the younger population [0-13 years]), but up to 44%, with an average of 18% (in the older population [14-18 years]). No SSDE correction was required for patients of varying size who weighed 36 kg or less when CTDI(vol) was measured by using a 16-cm CTDI phantom or for patients weighing 100-140 kg when CTDI(vol) was measured by using a 32-cm phantom. CTDI(vol) measured by using a 32-cm phantom in patients weighing between 36 and 100 kg and patients weighing more than 140 kg differed from SSDE by an average of 35%. An average difference of 1% was found between male and female SSDE-corrected values when the two sexes were compared within the same CT weight scanning categories. CONCLUSION The combination of AP and lateral measurements should be used to determine SSDE correction factors when possible. For pediatric patients, CTDI(vol) calculated with a 32-cm phantom requires SSDE conversion to more accurately estimate patient dose; CTDI(vol) calculated with a 16-cm phantom for pediatric patients weighing 36 kg or less does not require SSDE conversion.

Pediatric CT: Implementation of ASIR for Substantial Radiation Dose Reduction While Maintaining Pre-ASIR Image Noise

PURPOSE To determine a comprehensive method for the implementation of adaptive statistical iterative reconstruction (ASIR) for maximal radiation dose reduction in pediatric computed tomography (CT) without changing the magnitude of noise in the reconstructed image or the contrast-to-noise ratio (CNR) in the patient. MATERIALS AND METHODS The institutional review board waived the need to obtain informed consent for this HIPAA-compliant quality analysis. Chest and abdominopelvic CT images obtained before ASIR implementation (183 patient examinations; mean patient age, 8.8 years ± 6.2 [standard deviation]; range, 1 month to 27 years) were analyzed for image noise and CNR. These measurements were used in conjunction with noise models derived from anthropomorphic phantoms to establish new beam current-modulated CT parameters to implement 40% ASIR at 120 and 100 kVp without changing noise texture or magnitude. Image noise was assessed in images obtained after ASIR implementation (492 patient examinations; mean patient age, 7.6 years ± 5.4; range, 2 months to 28 years) the same way it was assessed in the pre-ASIR analysis. Dose reduction was determined by comparing size-specific dose estimates in the pre- and post-ASIR patient cohorts. Data were analyzed with paired t tests. RESULTS With 40% ASIR implementation, the average relative dose reduction for chest CT was 39% (2.7/4.4 mGy), with a maximum reduction of 72% (5.3/18.8 mGy). The average relative dose reduction for abdominopelvic CT was 29% (4.8/6.8 mGy), with a maximum reduction of 64% (7.6/20.9 mGy). Beam current modulation was unnecessary for patients weighing 40 kg or less. The difference between 0% and 40% ASIR noise magnitude was less than 1 HU, with statistically nonsignificant increases in patient CNR at 100 kVp of 8% (15.3/14.2; P = .41) for chest CT and 13% (7.8/6.8; P = .40) for abdominopelvic CT. CONCLUSION Radiation dose reduction at pediatric CT was achieved when 40% ASIR was implemented as a dose reduction tool only; no net change to the magnitude of noise in the reconstructed image or the patient CNR occurred.

Size-specific dose estimate (SSDE) provides a simple method to calculate organ dose for pediatric CT examinations

PURPOSE To investigate the correlation of size-specific dose estimate (SSDE) with absorbed organ dose, and to develop a simple methodology for estimating patient organ dose in a pediatric population (5-55 kg). METHODS Four physical anthropomorphic phantoms representing a range of pediatric body habitus were scanned with metal oxide semiconductor field effect transistor (MOSFET) dosimeters placed at 23 organ locations to determine absolute organ dose. Phantom absolute organ dose was divided by phantom SSDE to determine correlation between organ dose and SSDE. Organ dose correlation factors (CF(organ)(SSDE)) were then multiplied by patient-specific SSDE to estimate patient organ dose. The [CF(organ)(SSDE)) were used to retrospectively estimate individual organ doses from 352 chest and 241 abdominopelvic pediatric CT examinations, where mean patient weight was 22 kg ± 15 (range 5-55 kg), and mean patient age was 6 yrs ± 5 (range 4 months to 23 yrs). Patient organ dose estimates were compared to published pediatric Monte Carlo study results. RESULTS Phantom effective diameters were matched with patient population effective diameters to within 4 cm; thus, showing appropriate scalability of the phantoms across the entire pediatric population in this study. Individual CF(organ)(SSDE) were determined for a total of 23 organs in the chest and abdominopelvic region across nine weight subcategories. For organs fully covered by the scan volume, correlation in the chest (average 1.1; range 0.7-1.4) and abdominopelvic region (average 0.9; range 0.7-1.3) was near unity. For organ/tissue that extended beyond the scan volume (i.e., skin, bone marrow, and bone surface), correlation was determined to be poor (average 0.3; range: 0.1-0.4) for both the chest and abdominopelvic regions, respectively. A means to estimate patient organ dose was demonstrated. Calculated patient organ dose, using patient SSDE and CF(organ)(SSDE), was compared to previously published pediatric patient doses that accounted for patient size in their dose calculation, and was found to agree in the chest to better than an average of 5% (27.6/26.2) and in the abdominopelvic region to better than 2% (73.4/75.0). CONCLUSIONS For organs fully covered within the scan volume, the average correlation of SSDE and organ absolute dose was found to be better than ± 10%. In addition, this study provides a complete list of organ dose correlation factors (CF(organ)(SSDE)) for the chest and abdominopelvic regions, and describes a simple methodology to estimate individual pediatric patient organ dose based on patient SSDE.

How to Appropriately Calculate Effective Dose for CT Using Either Size-Specific Dose Estimates or Dose-Length Product

OBJECTIVE The purpose of this study is to show how to calculate effective dose in CT using size-specific dose estimates and to correct the current method using dose-length product (DLP). MATERIALS AND METHODS Data were analyzed from 352 chest and 241 abdominopelvic CT images. Size-specific dose estimate was used as a surrogate for organ dose in the chest and abdominopelvic regions. Organ doses were averaged by patient weight-based populations and were used to calculate effective dose by the International Commission on Radiological Protection (ICRP) report 103 method using tissue-weighting factors (EICRP). In addition, effective dose was calculated using population-averaged CT examination DLP for the chest and abdominopelvic region using published k-coefficients (EDLP = k × DLP). RESULTS EDLP differed from EICRP by an average of 21% (1.4 vs 1.1) in the chest and 42% (2.4 vs 3.4) in the abdominopelvic region. The differences occurred because the published kcoefficients did not account for pitch factor other than unity, were derived using a 32-cm diameter CT dose index (CTDI) phantom for CT examinations of the pediatric body, and used ICRP 60 tissue-weighting factors. Once it was corrected for pitch factor, the appropriate size of CTDI phantom, and ICRP 103 tissue-weighting factors, EDLP improved in agreement with EICRP to better than 7% (1.4 vs 1.3) and 4% (2.4 vs 2.5) for chest and abdominopelvic regions, respectively. CONCLUSION Current use of DLP to calculate effective dose was shown to be deficient because of the outdated means by which the k-coefficients were derived. This study shows a means to calculate EICRP using patient size-specific dose estimate and how to appropriately correct EDLP.

Establishing a standard calibration methodology for MOSFET detectors in computed tomography dosimetry

PURPOSE The use of metal-oxide-semiconductor field-effect transistor (MOSFET) detectors for patient dosimetry has increased by ~25% since 2005. Despite this increase, no standard calibration methodology has been identified nor calibration uncertainty quantified for the use of MOSFET dosimetry in CT. This work compares three MOSFET calibration methodologies proposed in the literature, and additionally investigates questions relating to optimal time for signal equilibration and exposure levels for maximum calibration precision. METHODS The calibration methodologies tested were (1) free in-air (FIA) with radiographic x-ray tube, (2) FIA with stationary CT x-ray tube, and (3) within scatter phantom with rotational CT x-ray tube. Each calibration was performed at absorbed dose levels of 10, 23, and 35 mGy. Times of 0 min or 5 min were investigated for signal equilibration before or after signal read out. RESULTS Calibration precision was measured to be better than 5%-7%, 3%-5%, and 2%-4% for the 10, 23, and 35 mGy respective dose levels, and independent of calibration methodology. No correlation was demonstrated for precision and signal equilibration time when allowing 5 min before or after signal read out. Differences in average calibration coefficients were demonstrated between the FIA with CT calibration methodology 26.7 ± 1.1 mV cGy(-1) versus the CT scatter phantom 29.2 ± 1.0 mV cGy(-1) and FIA with x-ray 29.9 ± 1.1 mV cGy(-1) methodologies. A decrease in MOSFET sensitivity was seen at an average change in read out voltage of ~3000 mV. CONCLUSIONS The best measured calibration precision was obtained by exposing the MOSFET detectors to 23 mGy. No signal equilibration time is necessary to improve calibration precision. A significant difference between calibration outcomes was demonstrated for FIA with CT compared to the other two methodologies. If the FIA with a CT calibration methodology was used to create calibration coefficients for the eventual use for phantom dosimetry, a measurement error ~12% will be reflected in the dosimetry results. The calibration process must emulate the eventual CT dosimetry process by matching or excluding scatter when calibrating the MOSFETs. Finally, the authors recommend that the MOSFETs are energy calibrated approximately every 2500-3000 mV.

Tissue segmentation of computed tomography images using a Random Forest algorithm: a feasibility study

There is a need for robust, fully automated whole body organ segmentation for diagnostic CT. This study investigates and optimizes a Random Forest algorithm for automated organ segmentation; explores the limitations of a Random Forest algorithm applied to the CT environment; and demonstrates segmentation accuracy in a feasibility study of pediatric and adult patients. To the best of our knowledge, this is the first study to investigate a trainable Weka segmentation (TWS) implementation using Random Forest machine-learning as a means to develop a fully automated tissue segmentation tool developed specifically for pediatric and adult examinations in a diagnostic CT environment. Current innovation in computed tomography (CT) is focused on radiomics, patient-specific radiation dose calculation, and image quality improvement using iterative reconstruction, all of which require specific knowledge of tissue and organ systems within a CT image. The purpose of this study was to develop a fully automated Random Forest classifier algorithm for segmentation of neck-chest-abdomen-pelvis CT examinations based on pediatric and adult CT protocols. Seven materials were classified: background, lung/internal air or gas, fat, muscle, solid organ parenchyma, blood/contrast enhanced fluid, and bone tissue using Matlab and the TWS plugin of FIJI. The following classifier feature filters of TWS were investigated: minimum, maximum, mean, and variance evaluated over a voxel radius of 2 (n) , (n from 0 to 4), along with noise reduction and edge preserving filters: Gaussian, bilateral, Kuwahara, and anisotropic diffusion. The Random Forest algorithm used 200 trees with 2 features randomly selected per node. The optimized auto-segmentation algorithm resulted in 16 image features including features derived from maximum, mean, variance Gaussian and Kuwahara filters. Dice similarity coefficient (DSC) calculations between manually segmented and Random Forest algorithm segmented images from 21 patient image sections, were analyzed. The automated algorithm produced segmentation of seven material classes with a median DSC of 0.86  ±  0.03 for pediatric patient protocols, and 0.85  ±  0.04 for adult patient protocols. Additionally, 100 randomly selected patient examinations were segmented and analyzed, and a mean sensitivity of 0.91 (range: 0.82-0.98), specificity of 0.89 (range: 0.70-0.98), and accuracy of 0.90 (range: 0.76-0.98) were demonstrated. In this study, we demonstrate that this fully automated segmentation tool was able to produce fast and accurate segmentation of the neck and trunk of the body over a wide range of patient habitus and scan parameters.

Is Routine Pelvic Surveillance Imaging Necessary in Patients with Wilms’ Tumor?

It is unclear whether routine pelvic imaging is needed in patients with Wilms tumor. Thus, the primary objective of the current study was to examine the role of routine pelvic computed tomography (CT) in a cohort of pediatric patients with Wilms tumor.

Ultralow dose computed tomography attenuation correction for pediatric PET CT using adaptive statistical iterative reconstruction

PURPOSE To develop ultralow dose computed tomography (CT) attenuation correction (CTAC) acquisition protocols for pediatric positron emission tomography CT (PET CT). METHODS A GE Discovery 690 PET CT hybrid scanner was used to investigate the change to quantitative PET and CT measurements when operated at ultralow doses (10-35 mA s). CT quantitation: noise, low-contrast resolution, and CT numbers for 11 tissue substitutes were analyzed in-phantom. CT quantitation was analyzed to a reduction of 90% volume computed tomography dose index (0.39/3.64; mGy) from baseline. To minimize noise infiltration, 100% adaptive statistical iterative reconstruction (ASiR) was used for CT reconstruction. PET images were reconstructed with the lower-dose CTAC iterations and analyzed for: maximum body weight standardized uptake value (SUVbw) of various diameter targets (range 8-37 mm), background uniformity, and spatial resolution. Radiation dose and CTAC noise magnitude were compared for 140 patient examinations (76 post-ASiR implementation) to determine relative dose reduction and noise control. RESULTS CT numbers were constant to within 10% from the nondose reduced CTAC image for 90% dose reduction. No change in SUVbw, background percent uniformity, or spatial resolution for PET images reconstructed with CTAC protocols was found down to 90% dose reduction. Patient population effective dose analysis demonstrated relative CTAC dose reductions between 62% and 86% (3.2/8.3-0.9/6.2). Noise magnitude in dose-reduced patient images increased but was not statistically different from predose-reduced patient images. CONCLUSIONS Using ASiR allowed for aggressive reduction in CT dose with no change in PET reconstructed images while maintaining sufficient image quality for colocalization of hybrid CT anatomy and PET radioisotope uptake.

The role of chest computed tomography (CT) as a surveillance tool in children with high-risk neuroblastoma.

Standardization of imaging obtained in children with neuroblastoma is not well established. This study examines chest CT in pediatric patients with high‐risk neuroblastoma.

A Comprehensive Risk Assessment Method for Pediatric Patients Undergoing Research Examinations Using Ionizing Radiation: How We Answered the Institutional Review Board.

OBJECTIVE The objectives of this study are to establish a comprehensive method for radiation dose estimates for the most common imaging examinations performed for research, for internal use of institutional review board (IRB) and radiation safety committees; to provide investigators with relative examination doses so that they may better assess the potential radiation effects and risks for research subjects; and to provide simplified language that investigators can use in consent documents. MATERIALS AND METHODS Nineteen common radiation-based examinations used in clinical research at our institution were identified. For each modality (CT, digital radiography, dual-energy x-ray absorptiometry, PET/CT, and nuclear medicine), a comprehensive patient-specific dosimetry method was established. Effective dose was calculated according to average population calculated doses for the following age groups: 0-1, 2-8, 9-13, 14-15, and older than 15 years. RESULTS Estimated effective dose values were tabulated and posted on our institutional IRB intranet site for use by IRB and radiation safety committee members and institutional investigators. Relative examination dose levels were compared for all ages and for all examinations. A three-tiered approach to establish consent language for radiation exposure was established for research subjects receiving an effective dose less than 3 mSv, a dose between 3 and 50 mSv, and a dose greater than 50 mSv. CONCLUSION The method to estimate effective dose was tabulated for 19 of the most common ionizing radiation examinations at our institute. These results will act as a resource to help investigators better understand the implications of radiation exposure in research and can assist investigators in protocol development and correct categorization of radiation exposure risk.