Patient-specific radiation dose and cancer risk for pediatric chest CT.
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ABSTRACT:
SUBMITTER: Li X
PROVIDER: S-EPMC3099041 | biostudies-other | 2011 Jun
REPOSITORIES: biostudies-other
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Project description: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.
| S-EPMC3910243 | biostudies-other
Project description:ObjectiveFew studies have explored the clinical feasibility of using deep-learning reconstruction to reduce the radiation dose of CT. We aimed to compare the image quality and lung nodule detectability between chest CT using a quarter of the low dose (QLD) reconstructed with vendor-agnostic deep-learning image reconstruction (DLIR) and conventional low-dose (LD) CT reconstructed with iterative reconstruction (IR).Materials and methodsWe retrospectively collected 100 patients (median age, 61 years [IQR, 53-70 years]) who received LDCT using a dual-source scanner, where total radiation was split into a 1:3 ratio. QLD CT was generated using a quarter dose and reconstructed with DLIR (QLD-DLIR), while LDCT images were generated using a full dose and reconstructed with IR (LD-IR). Three thoracic radiologists reviewed subjective noise, spatial resolution, and overall image quality, and image noise was measured in five areas. The radiologists were also asked to detect all Lung-RADS category 3 or 4 nodules, and their performance was evaluated using area under the jackknife free-response receiver operating characteristic curve (AUFROC).ResultsThe median effective dose was 0.16 (IQR, 0.14-0.18) mSv for QLD CT and 0.65 (IQR, 0.57-0.71) mSv for LDCT. The radiologists' evaluations showed no significant differences in subjective noise (QLD-DLIR vs. LD-IR, lung-window setting; 3.23 ± 0.19 vs. 3.27 ± 0.22; P = .11), spatial resolution (3.14 ± 0.28 vs. 3.16 ± 0.27; P = .12), and overall image quality (3.14 ± 0.21 vs. 3.17 ± 0.17; P = .15). QLD-DLIR demonstrated lower measured noise than LD-IR in most areas (P < .001 for all). No significant difference was found between QLD-DLIR and LD-IR for the sensitivity (76.4% vs. 72.2%; P = .35) or the AUFROCs (0.77 vs. 0.78; P = .68) in detecting Lung-RADS category 3 or 4 nodules. Under a noninferiority limit of -0.1, QLD-DLIR showed noninferior detection performance (95% CI for AUFROC difference, -0.04 to 0.06).ConclusionQLD-DLIR images showed comparable image quality and noninferior nodule detectability relative to LD-IR images.
| S-EPMC10494344 | biostudies-literature
Project description:To retrospectively compare image quality and radiation dose between a reduced-dose computed tomographic (CT) protocol that uses model-based iterative reconstruction (MBIR) and a standard-dose CT protocol that uses 30% adaptive statistical iterative reconstruction (ASIR) with filtered back projection.Institutional review board approval was obtained. Clinical CT images of the chest, abdomen, and pelvis obtained with a reduced-dose protocol were identified. Images were reconstructed with two algorithms: MBIR and 100% ASIR. All subjects had undergone standard-dose CT within the prior year, and the images were reconstructed with 30% ASIR. Reduced- and standard-dose images were evaluated objectively and subjectively. Reduced-dose images were evaluated for lesion detectability. Spatial resolution was assessed in a phantom. Radiation dose was estimated by using volumetric CT dose index (CTDI(vol)) and calculated size-specific dose estimates (SSDE). A combination of descriptive statistics, analysis of variance, and t tests was used for statistical analysis.In the 25 patients who underwent the reduced-dose protocol, mean decrease in CTDI(vol) was 46% (range, 19%-65%) and mean decrease in SSDE was 44% (range, 19%-64%). Reduced-dose MBIR images had less noise (P > .004). Spatial resolution was superior for reduced-dose MBIR images. Reduced-dose MBIR images were equivalent to standard-dose images for lungs and soft tissues (P > .05) but were inferior for bones (P = .004). Reduced-dose 100% ASIR images were inferior for soft tissues (P < .002), lungs (P < .001), and bones (P < .001). By using the same reduced-dose acquisition, lesion detectability was better (38% [32 of 84 rated lesions]) or the same (62% [52 of 84 rated lesions]) with MBIR as compared with 100% ASIR.CT performed with a reduced-dose protocol and MBIR is feasible in the pediatric population, and it maintains diagnostic quality.
| S-EPMC4228752 | biostudies-literature
Project description:BackgroundComputed tomography (CT) emphysema quantification is affected by both radiation dose (i.e. image noise) and reconstruction technique. At reduced dose, filtered back projection (FBP) results in an overestimation of the amount of emphysema due to higher noise levels, while the use of iterative reconstruction (IR) can result in an underestimation due to reduced noise. The objective of this study was to determine the influence of dose reduction and hybrid IR (HIR) or model-based IR (MIR) on CT emphysema quantification.MethodsTwenty-two patients underwent inspiratory chest CT scan at routine radiation dose and at 45%, 60% and 75% reduced radiation dose. Acquisitions were reconstructed with FBP, HIR and MIR. Emphysema was quantified using the 15th percentile of the attenuation curve and the percentage of voxels below -950 HU. To determine whether the use of a different percentile or HU threshold is more accurate at reduced dose levels and with IR, additional measurements were performed using different percentiles and HU thresholds to determine the optimal combination.ResultsDose reduction resulted in a significant overestimation of emphysema, while HIR and MIR resulted in an underestimation. Lower HU thresholds with FBP at reduced dose and higher HU thresholds with HIR and MIR resulted in emphysema percentages comparable to the reference. The 15th percentile quantification method showed similar results as the HU threshold method.ConclusionsThis within-patients study showed that CT emphysema quantification is significantly affected by dose reduction and IR. This can potentially be solved by adapting commonly used thresholds.
| S-EPMC6220000 | biostudies-literature
Project description:BACKGROUND: During interventional neuroradiology procedures, patients can be exposed to moderate to high levels of radiation. Special considerations are required to protect children, who are generally more sensitive to the short- and long-term detrimental effects of radiation exposure. Estimates of dose to the skin of children from certain interventional procedures have been published elsewhere, but we are not aware of data on dose to the brain or on the long-term risk of cancer from brain radiation. OBJECTIVES: Our goals were to estimate radiation doses to the brain in 50 pediatric patients who had undergone cerebral embolization and to assess their lifetime risks of developing radiation-related brain cancer. MATERIALS AND METHODS: Entrance-peak skin dose and various assumptions on conditions of exposure were used as input for dosimetric calculations to estimate the spatial pattern of dose within the brain and the average dose to the whole brain for each child. The average dose and the age of the child at time of exposure were used to estimate the lifetime risk of developing radiation-related brain cancer. RESULTS: Among the 50 patients, average radiation doses to the brain were estimated to vary from 100 mGy to 1,300 mGy if exposed to non-collimated fields and from 20 mGy to 160 mGy for collimated, moving fields. The lifetime risk of developing brain cancer was estimated to be increased by 2% to 80% as a result of the exposure. Given the very small lifetime background risk of brain tumor, the excess number of cases will be small even though the relative increase might be as high as 80%. CONCLUSION: ALARA principles of collimation and dose optimization are the most effective means to minimize the risk of future radiation-related cancer.
| S-EPMC2663652 | biostudies-other
Project description:BackgroundComputed tomography (CT), a strong diagnostic tool, delivers higher radiation doses than most imaging modalities. As CT use has increased rapidly, radiation protection is important, particularly among children. We evaluate leukemia and brain tumor risk following exposure to low-dose ionizing radiation from CT scans in childhood.MethodsFor a nationwide retrospective cohort of 168 394 children who received one or more CT scans in a Dutch hospital between 1979 and 2012 who were younger than age 18 years, we obtained cancer incidence, vital status, and confounder information by record linkage with external registries. Standardized incidence ratios were calculated using cancer incidence rates from the general Dutch population. Excess relative risks (ERRs) per 100 mGy organ dose were calculated with Poisson regression. All statistical tests were two-sided.ResultsStandardized incidence ratios were elevated for all cancer sites. Mean cumulative bone marrow doses were 9.5 mGy at the end of follow-up, and leukemia risk (excluding myelodysplastic syndrome) was not associated with cumulative bone marrow dose (44 cases). Cumulative brain dose was on average 38.5 mGy and was statistically significantly associated with risk for malignant and nonmalignant brain tumors combined (ERR/100 mGy: 0.86, 95% confidence interval = 0.20 to 2.22, P = .002, 84 cases). Excluding tuberous sclerosis complex patients did not substantially change the risk.ConclusionsWe found evidence that CT-related radiation exposure increases brain tumor risk. No association was observed for leukemia. Compared with the general population, incidence of brain tumors was higher in the cohort of children with CT scans, requiring cautious interpretation of the findings.
| S-EPMC6657440 | biostudies-literature
Project description:BACKGROUND:Given the rising utilization of medical imaging and the risks of radiation, there is increased interest in reducing radiation exposure. The objective of this study was to evaluate, as a proof of principle, CT scans performed at radiation doses equivalent to that of a posteroanterior and lateral chest radiograph series in the cystic lung disease lymphangioleiomyomatosis (LAM). METHODS:From November 2016 to May 2018, 105 consecutive subjects with LAM received chest CT scans at standard and ultra-low radiation doses. Standard and ultra-low-dose images, respectively, were reconstructed with routine iterative and newer model-based iterative reconstruction. LAM severity can be quantified as cyst score (percentage of lung occupied by cysts), an ideal benchmark for validating CT scans performed at a reduced dose compared with a standard dose. Cyst scores were quantified using semi-automated software and evaluated by linear correlation and Bland-Altman analysis. RESULTS:Overall, ultra-low-dose CT scans represented a 96% dose reduction, with a median dose equivalent to 1 vs 22 posteroanterior and lateral chest radiograph series (0.14 mSv; 5th-95th percentile, 0.10-0.20 vs standard dose 3.4 mSv; 5th-95th percentile, 1.5-7.4; P < .0001). The mean difference in cyst scores between ultra-low- and standard-dose CT scans was 1.1% ± 2.0%, with a relative difference in cyst score of 11%. Linear correlation coefficient was excellent at 0.97 (P < .0001). CONCLUSIONS:In LAM chest CT scan at substantial radiation reduction to doses equivalent to that of a posteroanterior and lateral chest radiograph series provides cyst score quantification similar to that of standard-dose CT scan. TRIAL REGISTRY:ClinicalTrials.gov; Nos.: NCT00001465 and NCT00001532; URL: www.clinicaltrials.gov.
| S-EPMC6414786 | biostudies-literature
Project description:Given the radiation concerns inherent to the x-ray modalities, accurately estimating the radiation doses that patients receive during different imaging modalities is crucial. This study estimated organ doses, effective doses, and risk indices for the three clinical chest x-ray imaging techniques (chest radiography, tomosynthesis, and CT) using 59 anatomically variable voxelized phantoms and Monte Carlo simulation methods.A total of 59 computational anthropomorphic male and female extended cardiac-torso (XCAT) adult phantoms were used in this study. Organ doses and effective doses were estimated for a clinical radiography system with the capability of conducting chest radiography and tomosynthesis (Definium 8000, VolumeRAD, GE Healthcare) and a clinical CT system (LightSpeed VCT, GE Healthcare). A Monte Carlo dose simulation program (PENELOPE, version 2006, Universitat de Barcelona, Spain) was used to mimic these two clinical systems. The Duke University (Durham, NC) technique charts were used to determine the clinical techniques for the radiographic modalities. An exponential relationship between CTDIvol and patient diameter was used to determine the absolute dose values for CT. The simulations of the two clinical systems compute organ and tissue doses, which were then used to calculate effective dose and risk index. The calculation of the two dose metrics used the tissue weighting factors from ICRP Publication 103 and BEIR VII report.The average effective dose of the chest posteroanterior examination was found to be 0.04 mSv, which was 1.3% that of the chest CT examination. The average effective dose of the chest tomosynthesis examination was found to be about ten times that of the chest posteroanterior examination and about 12% that of the chest CT examination. With increasing patient average chest diameter, both the effective dose and risk index for CT increased considerably in an exponential fashion, while these two dose metrics only increased slightly for radiographic modalities and for chest tomosynthesis. Effective and organ doses normalized to mAs all illustrated an exponential decrease with increasing patient size. As a surface organ, breast doses had less correlation with body size than that of lungs or liver.Patient body size has a much greater impact on radiation dose of chest CT examinations than chest radiography and tomosynthesis. The size of a patient should be considered when choosing the best thoracic imaging modality.
| S-EPMC3985882 | biostudies-other
Project description:PURPOSE:We aimed to evaluate the quality of chest computed tomography (CT) images obtained with low-dose CT using three iterative reconstruction (IR) algorithms. METHODS:Two 64-detector spiral CT scanners (HDCT and iCT) were used to scan a chest phantom containing 6 ground-glass nodules (GGNs) at 11 radiation dose levels. CT images were reconstructed by filtered back projection or three IR algorithms. Reconstructed images were analyzed for CT values, average noise, contrast-to-noise ratio (CNR) values, subjective image noise, and diagnostic acceptability of the GGNs. Repeated-measures analysis of variance was used for statistical analyses. RESULTS:Average noise decreased and CNR increased with increasing radiation dose when the same reconstruction algorithm was applied. Average image noise was significantly lower when reconstructed with MBIR than with iDOSE4 at the same low radiation doses. The two radiologists showed good interobserver consistency in image quality with kappa 0.83. A significant relationship was found between image noise and diagnostic acceptability of the GGNs. CONCLUSION:Three IR algorithms are able to reduce the image noise and improve the image quality of low-dose CT. In the same radiation dose, the low-dose CT image quality reconstructed with MBIR algorithms is better than that of other IR algorithms.
| S-EPMC6837298 | biostudies-literature
Project description:Background Results of recent phantom studies show that variation in CT acquisition parameters and reconstruction techniques may make radiomic features largely nonreproduceable and of limited use for prognostic clinical studies. Purpose To investigate the effect of CT radiation dose and reconstruction settings on the reproducibility of radiomic features, as well as to identify correction factors for mitigating these sources of variability. Materials and Methods This was a secondary analysis of a prospective study of metastatic liver lesions in patients who underwent staging with single-energy dual-source contrast material-enhanced staging CT between September 2011 and April 2012. Technique parameters were altered, resulting in 28 CT data sets per patient that included different dose levels, section thicknesses, kernels, and reconstruction algorithm settings. By using a training data set (n = 76), reproducible intensity, shape, and texture radiomic features (reproducibility threshold, R2 ≥ 0.95) were selected and correction factors were calculated by using a linear model to convert each radiomic feature to its estimated value in a reference technique. By using a test data set (n = 75), the reproducibility of hierarchical clustering based on 106 radiomic features measured with different CT techniques was assessed. Results Data in 78 patients (mean age, 60 years ± 10; 33 women) with 151 liver lesions were included. The percentage of radiomic features deemed reproducible for any variation of the different technical parameters was 11% (12 of 106). Of all technical parameters, reconstructed section thickness had the largest impact on the reproducibility of radiomic features (12.3% [13 of 106]) if only one technical parameter was changed while all other technical parameters were kept constant. The results of the hierarchical cluster analysis showed improved clustering reproducibility when reproducible radiomic features with dedicated correction factors were used (ρ = 0.39-0.71 vs ρ = 0.14-0.47). Conclusion Most radiomic features are highly affected by CT acquisition and reconstruction settings, to the point of being nonreproducible. Selecting reproducible radiomic features along with study-specific correction factors offers improved clustering reproducibility. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Sosna in this issue.
| S-EPMC10860741 | biostudies-literature