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1.
J Comput Assist Tomogr ; 46(4): 576-583, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35405727

RESUMO

METHODS: This study used the Personalized Rapid Estimation of Dose in CT (PREDICT) tool to estimate patient-specific organ doses from CT image data. The PREDICT is a research tool that combines a linear Boltzmann transport equation solver for radiation dose map generation with deep learning algorithms for organ contouring. Computed tomography images from 74 subjects in the Medical Imaging Data Resource Center-RSNA International COVID-19 Open Radiology Database data set (chest CT of adult patients positive for COVID-19), which included expert annotations including "infectious opacities," were analyzed. First, the full z-scan length of the CT image data set was evaluated. Next, the z-scan length was reduced from the left hemidiaphragm to the top of the aortic arch. Generic dose reduction based on dose length product (DLP) and patient-specific organ dose reductions were calculated. The percentage of infectious opacities excluded from the reduced z-scan length was used to quantify the effect on diagnostic utility. RESULTS: Generic dose reduction, based on DLP, was 69%. The organ dose reduction ranged from approximately equal to 18% (breasts) to approximately equal to 64% (bone surface and bone marrow). On average, 12.4% of the infectious opacities were not included in the reduced z-coverage, per patient, of which 5.1% were above the top of the arch and 7.5% below the left hemidiaphragm. CONCLUSIONS: Limiting z-scan length of chest CTs reduced radiation dose without significantly compromising diagnostic utility in COVID-19 patients. The PREDICT demonstrated that patient-specific organ dose reductions varied from generic dose reduction based on DLP.


Assuntos
COVID-19 , Redução da Medicação , Adulto , Humanos , Doses de Radiação , Tórax , Tomografia Computadorizada por Raios X/métodos
2.
Med Phys ; 49(4): 2342-2354, 2022 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-35128672

RESUMO

PURPOSE: This study developed and evaluated a fully convolutional network (FCN) for pediatric CT organ segmentation and investigated the generalizability of the FCN across image heterogeneities such as CT scanner model protocols and patient age. We also evaluated the autosegmentation models as part of a software tool for patient-specific CT dose estimation. METHODS: A collection of 359 pediatric CT datasets with expert organ contours were used for model development and evaluation. Autosegmentation models were trained for each organ using a modified FCN 3D V-Net. An independent test set of 60 patients was withheld for testing. To evaluate the impact of CT scanner model protocol and patient age heterogeneities, separate models were trained using a subset of scanner model protocols and pediatric age groups. Train and test sets were split to answer questions about the generalizability of pediatric FCN autosegmentation models to unseen age groups and scanner model protocols, as well as the merit of scanner model protocol or age-group-specific models. Finally, the organ contours resulting from the autosegmentation models were applied to patient-specific dose maps to evaluate the impact of segmentation errors on organ dose estimation. RESULTS: Results demonstrate that the autosegmentation models generalize to CT scanner acquisition and reconstruction methods which were not present in the training dataset. While models are not equally generalizable across age groups, age-group-specific models do not hold any advantage over combining heterogeneous age groups into a single training set. Dice similarity coefficient (DSC) and mean surface distance results are presented for 19 organ structures, for example, median DSC of 0.52 (duodenum), 0.74 (pancreas), 0.92 (stomach), and 0.96 (heart). The FCN models achieve a mean dose error within 5% of expert segmentations for all 19 organs except for the spinal canal, where the mean error was 6.31%. CONCLUSIONS: Overall, these results are promising for the adoption of FCN autosegmentation models for pediatric CT, including applications for patient-specific CT dose estimation.


Assuntos
Processamento de Imagem Assistida por Computador , Tomografia Computadorizada por Raios X , Algoritmos , Criança , Humanos , Processamento de Imagem Assistida por Computador/métodos , Radiometria , Tórax
3.
Med Phys ; 49(5): 3523-3528, 2022 May.
Artigo em Inglês | MEDLINE | ID: mdl-35067940

RESUMO

PURPOSE: Organ autosegmentation efforts to date have largely been focused on adult populations, due to limited availability of pediatric training data. Pediatric patients may present additional challenges for organ segmentation. This paper describes a dataset of 359 pediatric chest-abdomen-pelvis and abdomen-pelvis Computed Tomography (CT) images with expert contours of up to 29 anatomical organ structures to aid in the evaluation and development of autosegmentation algorithms for pediatric CT imaging. ACQUISITION AND VALIDATION METHODS: The dataset collection consists of axial CT images in Digital Imaging and Communications in Medicine (DICOM) format of 180 male and 179 female pediatric chest-abdomen-pelvis or abdomen-pelvis exams acquired from one of three CT scanners at Children's Wisconsin. The datasets represent random pediatric cases based upon routine clinical indications. Subjects ranged in age from 5 days to 16 years, with a mean age of 7 years. The CT acquisition, contrast, and reconstruction protocols varied across the scanner models and patients, with specifications available in the DICOM headers. Expert contours were manually labeled for up to 29 organ structures per subject. Not all contours are available for all subjects, due to limited field of view or unreliable contouring due to high noise. DATA FORMAT AND USAGE NOTES: The data are available on The Cancer Imaging Archive (TCIA_ (https://www.cancerimagingarchive.net/) under the collection Pediatric-CT-SEG. The axial CT image slices for each subject are available in DICOM format. The expert contours are stored in a single DICOM RTSTRUCT file for each subject. The contour names are listed in Table 2. POTENTIAL APPLICATIONS: This dataset will enable the evaluation and development of organ autosegmentation algorithms for pediatric populations, which exhibit variations in organ shape and size across age. Automated organ segmentation from CT images has numerous applications including radiation therapy, diagnostic tasks, surgical planning, and patient-specific organ dose estimation.


Assuntos
Abdome , Tomografia Computadorizada por Raios X , Abdome/diagnóstico por imagem , Adulto , Algoritmos , Criança , Feminino , Humanos , Masculino , Pelve/diagnóstico por imagem , Tomógrafos Computadorizados , Tomografia Computadorizada por Raios X/métodos
4.
Med Phys ; 48(12): 8075-8088, 2021 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-34669975

RESUMO

PURPOSE: The risk of inducing cancer to patients undergoing CT examinations has motivated efforts for CT dose estimation, monitoring, and reduction, especially among pediatric population. The method investigated in this study is Acuros CTD (Varian Medical Systems, Palo Alto, CA), a deterministic linear Boltzmann transport equation (LBTE) solver aimed at generating rapid and reliable dose maps of CT exams. By applying organ contours, organ doses can also be obtained, thus patient-specific organ dose estimates can be provided. This study experimentally validated Acuros against measurements performed on a clinical CT system using a range of physical pediatric anthropomorphic phantoms and acquisition protocols. METHODS: The study consisted of (1) the acquisition of dose measurements on a clinical CT scanner through thermoluminescent dosimeters (TLDs), and (2) the modeling in the Acuros platform of the measurement set up, which includes the modeling of the CT scanner and of the anthropomorphic phantoms. For the measurements, 1-year-old, 5-year-old, and 10-year-old anthropomorphic phantoms of the CIRS ATOM family were used. TLDs were placed in selected organ locations such as stomach, liver, lungs, and heart. The pediatric phantoms were scanned helically with the GE Discovery 750 HD clinical scanner for several examination protocols. For the simulations in Acuros, scanner-specific input, such as bowtie filters, overrange collimation, and tube current modulation schemes, were modeled. These scanner complexities were implemented by defining discretized X-ray beams whose spectral distribution, defined in Acuros by only six energy bins, varied across fan angle, cone angle, and slice position. The images generated during the CT acquisitions were used to create the geometrical models, by applying thresholding algorithms and assigning materials to the HU values. The TLDs were contoured in the phantom models as sensitive cylindrical volumes at the locations selected for dosimeters placement, to provide dose estimates, in terms of dose per unit photon. To compare measured doses with dose estimates, a calibration factor was derived from the CTDIvol displayed by the scanner, to account for the number of photons emitted by the X-ray tube during the procedure. RESULTS: The differences of the measured and estimated doses, in terms of absolute % errors, were within 13% for 153 TLD locations, with an error of 17% at the stomach for one study with the 10-year-old phantom. Root-mean-squared-errors (RMSE) across all TLD locations for all configurations were in the range of 3%-8%, with Acuros providing dose estimates in a time range of a few seconds up to 2 min. CONCLUSIONS: An overall good agreement between measurements and simulations was achieved, with average RMSE of 6% across all cases. The results demonstrate that Acuros can model a specific clinical scanner despite the required discretization in spatial and energy domains. The proposed deterministic tool has the potential to be part of a near real-time individualized dosimetry monitoring system for CT applications, providing patient-specific organ dose estimates.


Assuntos
Radiometria , Tomografia Computadorizada por Raios X , Criança , Pré-Escolar , Humanos , Lactente , Método de Monte Carlo , Imagens de Fantasmas , Fótons , Doses de Radiação
5.
Phys Med ; 82: 64-71, 2021 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-33588229

RESUMO

INTRODUCTION: Interventional procedures are associated with potentially high radiation doses to the skin. The 2013/59/EURATOM Directive establishes that the equipment used for interventional radiology must have a device or a feature informing the practitioner of relevant parameters for assessing patient dose at the end of the procedure. Monte Carlo codes of radiation transport are considered to be one of the most reliable tools available to assess doses. However, they are usually too time consuming for use in clinical practice. This work presents the validation of the fast Monte Carlo code MC-GPU for application in interventional radiology. METHODOLOGIES: MC-GPU calculations were compared against the well-validated Monte Carlo simulation code PENELOPE/penEasy by simulating the organ dose distribution in a voxelized anthropomorphic phantom. In a second phase, the code was compared against thermoluminescent measurements performed on slab phantoms, both in a calibration laboratory and at a hospital. RESULTS: The results obtained from the two simulation codes show very good agreement, differences in the output were within 1%, whereas the calculation time on the MC-GPU was 2500 times shorter. Comparison with measurements is of the order of 10%, within the associated uncertainty. CONCLUSIONS: It has been verified that MC-GPU provides good estimates of the dose when compared to PENELOPE program. It is also shown that it presents very good performance when assessing organ doses in very short times, less than one minute, in real clinical set-ups. Future steps would be to simulate complex procedures with several projections.


Assuntos
Benchmarking , Cardiologia , Humanos , Método de Monte Carlo , Imagens de Fantasmas , Radiologia Intervencionista
6.
Med Phys ; 47(12): 6470-6483, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-32981038

RESUMO

PURPOSE: Epidemiological evidence suggests an increased risk of cancer related to computed tomography (CT) scans, with children exposed to greater risk. The purpose of this work is to test the reliability of a linear Boltzmann transport equation (LBTE) solver for rapid and patient-specific CT dose estimation. This includes building a flexible LBTE framework for modeling modern clinical CT scanners and to validate the resulting dose maps across a range of realistic scanner configurations and patient models. METHODS: In this study, computational tools were developed for modeling CT scanners, including a bowtie filter, overrange collimation, and tube current modulation. The LBTE solver requires discretization in the spatial, angular, and spectral dimensions, which may affect the accuracy of scanner modeling. To investigate these effects, this study evaluated the LBTE dose accuracy for different discretization parameters, scanner configurations, and patient models (male, female, adults, pediatric). The method used to validate the LBTE dose maps was the Monte Carlo code Geant4, which provided ground truth dose maps. LBTE simulations were implemented on a GeForce GTX 1080 graphic unit, while Geant4 was implemented on a distributed cluster of CPUs. RESULTS: The agreement between Geant4 and the LBTE solver quantifies the accuracy of the LBTE, which was similar across the different protocols and phantoms. The results suggest that 18 views per rotation provides sufficient accuracy, as no significant improvement in the accuracy was observed by increasing the number of projection views. Considering this discretization, the LBTE solver average simulation time was approximately 30 s. However, in the LBTE solver the phantom model was implemented with a lower voxel resolution with respect to Geant4, as it is limited by the memory of the GPU. Despite this discretization, the results showed a good agreement between the LBTE and Geant4, with root mean square error of the dose in organs of approximately 3.5% for most of the studied configurations. CONCLUSIONS: The LBTE solver is proposed as an alternative to Monte Carlo for patient-specific organ dose estimation. This study demonstrated accurate organ dose estimates for the rapid LBTE solver when considering realistic aspects of CT scanners and a range of phantom models. Future plans will combine the LBTE framework with deep learning autosegmentation algorithms to provide near real-time patient-specific organ dose estimation.


Assuntos
Benchmarking , Tomografia Computadorizada por Raios X , Adulto , Criança , Feminino , Humanos , Masculino , Método de Monte Carlo , Imagens de Fantasmas , Doses de Radiação , Reprodutibilidade dos Testes
7.
Phys Med ; 76: 177-181, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-32693354

RESUMO

In order to address the recent concerns over a possible increasing in brain tumour mortality among interventional radiologists and cardiologist, this work evaluated the exposure conditions of the operator's brain during interventional procedures using Monte Carlo simulations with anthropomorphic phantoms. The absorbed doses in several predefined segments of the operator's brain were estimated in a typical interventional radiology irradiation scenario. The doses were normalized to the KAP values simulated for ten X-ray beam qualities and four projections (PA, RAO 25°, LAO 25° and CRA 25°). For the interventional radiology scenario, because of the position of the operator, no difference was found in the exposure between the left and right regions of the brain for the first operator. However, for the second operator standing at a farer distance from the tube, the exposure of the left part of the brain is up to two times higher than that of the right part. The results are in agreement with dose measurements reported in the literature. The conversion factors, obtained as the absorbed dose per KAP, can be used to obtain a first estimate of the exposure of the brain of the operators during interventional procedures.


Assuntos
Exposição Ocupacional , Radiologia Intervencionista , Encéfalo/diagnóstico por imagem , Método de Monte Carlo , Exposição Ocupacional/análise , Imagens de Fantasmas , Doses de Radiação
8.
J Radiol Prot ; 39(1): 97-112, 2019 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-30523896

RESUMO

In fluoroscopy guided interventional procedures, workers use protective garments and often two personal dosemeters, the readings of which are used for the estimation of the effective dose; whereas the dosemeter above the protection can be used for the estimation of the equivalent dose of the lens of the eye. When a protective apron is worn the scattered field that reaches the dosemeter is different from the case where no protection is used; this study analyses the changes in the response of seven passive and eight active personal dosemeters (APDs) when they are placed above a lead or lead equivalent garment for S-Cs and x-ray diagnostic qualities. Monte Carlo simulations are used to support the experimental results. It is found that for passive dosemeters, the influence on the dosemeter's response to the lead or lead equivalent was within the range 15%-38% for the x-ray qualities. This effect is smaller, of the order of 10%, when lead-free garments are used, and much smaller, within 1%-10%, for most of the APDs used in the study. From these results it is concluded that when comparing passive and active dosemeter measurements worn above the protection, a difference of 20%-40% is expected. The effect is small when deriving the effective dose from double dosimetry algorithms, but it can be of major importance when eye lens monitoring is based on the use of the dosemeter worn above the protection.


Assuntos
Cateterismo Cardíaco , Roupa de Proteção , Dosímetros de Radiação , Proteção Radiológica/métodos , Radiografia Intervencionista , Humanos
9.
J Radiol Prot ; 36(4): 902-921, 2016 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-27861170

RESUMO

Interventional radiology and cardiology guarantee high benefits for patients, but are known to be associated with a high level of radiation exposure of medical staff. The recently suggested decrease of the annual dose limit for the eye lens, from 150 to 20 mSv, caused a need for a reconsideration of practices ensuring sufficient protection for the lens of the eyes of medical staff. In such context the study of the scattered radiation around the operator's head could help in finding the best solutions to be adopted for the ceiling-suspended shield and lead glasses in the most common situations in interventional practices. MCNPX Monte Carlo code was employed with anthropomorphic mathematical phantoms to simulate interventional practice projections. For each projection the effect of changing selected parameters on the evaluated scattered radiation towards the operator's head has been calculated. The variety of modelled situations provides plentiful material regarding the spatial distribution of the scattered radiation, useful to improve eye lens radiation protection, such as the following:  (a) Glasses, which provide shielding from both lateral and bottom-up scattered radiation, can reduce by ten times the exposure to the most exposed eyes;  (b) The ceiling-suspended shield offers valuable protection, but such effectiveness can diminish by 90% if the shielding is not correctly positioned;  (c) The transition from femoral to radial access usually intensifies the scattered radiation toward the operator head (a factor of 1.5 for AP projection), but for RAO projections, a reduction of the order by two to three times, in the case of radial access, can be seen, due to the protection provided by the image receptor. The detailed fluence outcomes show that there is a preferential direction of the impinging scattered radiation that should be considered when radiation protection options are evaluated or when a dedicated eye lens dosemeter is used for monitoring.


Assuntos
Cristalino/efeitos da radiação , Corpo Clínico Hospitalar , Proteção Radiológica/métodos , Radiologia Intervencionista , Radiometria/métodos , Dispositivos de Proteção dos Olhos , Humanos , Método de Monte Carlo , Exposição Ocupacional/prevenção & controle , Imagens de Fantasmas , Exposição à Radiação , Lesões por Radiação/prevenção & controle , Espalhamento de Radiação
10.
Radiat Prot Dosimetry ; 164(1-2): 79-83, 2015 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-25514919

RESUMO

The equivalent dose limit for the eye lens for occupational exposure recommended by the ICRP has been reduced to 20 mSv y(-1) averaged over defined periods of 5 y, with no single year exceeding 50 mSv. The compliance with this new requirement could not be easy in some workplace such as interventional radiology and cardiology. The aim of this study is to evaluate different possible approaches in order to have a good estimate of the eye lens dose during interventional procedures. Measurements were performed with an X-ray system Philips Allura FD-10, using a PMMA phantom to simulate the patient scattered radiation and a Rando phantom to simulate the cardiologist. Thermoluminescence (TL) whole-body and TL eye lens dosemeters together with Philips DoseAware active dosemeters were located on different positions of the Rando phantom to estimate the eye lens dose in typical cardiology procedures. The results show that, for the studied conditions, any of the analysed dosemeter positions are suitable for eye lens dose assessment. However, the centre of the thyroid collar and the left ear position provide a better estimate. Furthermore, in practice, improper use of the ceiling-suspended screen can produce partial protection of some parts of the body, and thus large differences between the measured doses and the actual exposure of the eye could arise if the dosemeter is not situated close to the eye.


Assuntos
Cateterismo Cardíaco/métodos , Cristalino/efeitos da radiação , Proteção Radiológica/métodos , Radiografia Intervencionista/métodos , Radiometria/métodos , Cateterismo Cardíaco/efeitos adversos , Desenho de Equipamento , Análise de Falha de Equipamento , Humanos , Cristalino/lesões , Doses de Radiação , Proteção Radiológica/instrumentação , Radiografia Intervencionista/efeitos adversos , Radiometria/instrumentação , Reprodutibilidade dos Testes , Sensibilidade e Especificidade
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