The role of Size-Specific Dose Estimate (SSDE) in patient-specific organ dose and cancer risk estimation in paediatric chest and abdominopelvic CT examinations

2015 ◽  
Vol 26 (8) ◽  
pp. 2646-2655 ◽  
Author(s):  
Caro Franck ◽  
Charlot Vandevoorde ◽  
Ingeborg Goethals ◽  
Peter Smeets ◽  
Eric Achten ◽  
...  
2010 ◽  
Vol 38 (1) ◽  
pp. 408-419 ◽  
Author(s):  
Xiang Li ◽  
Ehsan Samei ◽  
W. Paul Segars ◽  
Gregory M. Sturgeon ◽  
James G. Colsher ◽  
...  

2010 ◽  
Author(s):  
Xiang Li ◽  
Ehsan Samei ◽  
W. Paul Segars ◽  
Gregory M. Sturgeon ◽  
James G. Colsher ◽  
...  

2016 ◽  
Vol 3 (4) ◽  
pp. 043502 ◽  
Author(s):  
Taly Gilat Schmidt ◽  
Adam S. Wang ◽  
Thomas Coradi ◽  
Benjamin Haas ◽  
Josh Star-Lack

Author(s):  
Wanyi Fu ◽  
William P. Segars ◽  
Ehsan Abadi ◽  
Shobhit Sharma ◽  
Anuj J. Kapadia ◽  
...  

2020 ◽  
Vol 191 (1) ◽  
pp. 1-8
Author(s):  
W J Garzón ◽  
D F A Aldana ◽  
V F Cassola

Abstract The aim of this work was to estimate patient’s organ absorbed doses from pediatric helical head computed tomography (CT) examinations using the Size-Specific Dose Estimate (SSDE) methodology and to determine organ dose to SSDE conversion coefficients for clinical routine. Patient-specific organ and tissue absorbed doses from 139 Head CT scans performed in pediatric patients from 0 to 15 years old in a Public Hospital in Tunja, Colombia were estimated. The calculations were made through Monte Carlo simulations, based on patient-specific information, dosimetric CT quantities (CTDIvol, DLP) and age-specific computational human phantoms matched to patients on the basis of gender and size. SSDE showed to be a good quantity for estimate patient-specific organ doses from pediatric head CT examinations when appropriate phantom’s attenuation-based size metrics are chosen to match for any patient size. Strong correlations between absorbed dose and SSDE were found for skin (R2 = 0.99), brain (R2 = 0.98) and eyes (R2 = 0.97), respectively. Besides, a good correlation between SSDE and absorbed dose to the red bone marrow (tissue extended outside the scan coverage) was observed (R2 = 0.94). SSDE-to-organ-dose conversion coefficients obtained in this study provide a practical way to estimate patient-specific organ head CT doses.


2020 ◽  
Author(s):  
Ying Huang ◽  
Yang Yang ◽  
Xin Chen ◽  
Yiming Gao ◽  
Weihai Zhuo ◽  
...  

BACKGROUND CT imaging is one of the most important contributors to medical radiation exposure(1). The frequency of CT scans and radiation doses accepted by patients attracted serious concerns for health physics researchers. The utilization of advanced technology ATCM has the potentials to reduce CT radiation doses while diagnostic image quality is maintained (2-7). As ATCM adjusted tube currents slice by slice it brought challenges to organ dose estimation using conversion factors derived from fixed tube current. Cross-system communication with hospital Picture Archive and Communication System (PACS),made it possible to read massive data automatically like the scanning parameters of each slice in each case. Monte Carlo simulations are probably the most reliable techniques which could be used for accurate dose assessment. [8-11]. However, specific patient model development and specific patient dose simulations are computationally demanding and may require dedicated hardware resources, this limitation constrained its application in large scale investigation. As an alternative method, patient specific organ doses could be calculated using the patient specific scan parameters and the Monte Carlo simulated organ doses with reference human phantom, and then correct the results with patient size factors. Dw is referred as the preferred patient size metric that determined the patient group and affected organ dose. The distance of the pathway traversed by the X-ray beam could provide the best approximation of tissue length traversed during the examination (12, 13),as CT image is a cross-sectional map normalized to the linear attenuation of water (14). The purpose of current study was to establish a method to access patient-specific organ dose associated with ATCM in chest computed tomography (CT) scans by combining Monte Carlo simulation with parameters contracted from clinical CT images of each patient underwent chest CT scan with ATCM. OBJECTIVE To explore a method to access patient-specific organ dose associated with automatic tube current modulation (ATCM) in chest computed tomography (CT) scans based on the information extracted from PACS automatically. METHODS 176cases of chest CT scans were read through cross-system communication with hospital PACS. A total of 8468 images were collected and analyzed automatically using in-house software. The scanning parameters (kVp, tube current, collimation width, etc.) of each CT examination were collected in real time, and a middle CT image of each case was collected for patient size(water equivalent diameter, Dw) calculation. Based on the reference human phantom, organ doses were simulated slice by slice using Monte Carlo method. The patient specific organ doses were calculated by combining tube currents of each patient slice with the simulated results, and doses were revised by correction factors that related to patient size. RESULTS A sum of 8468 slice of tube currents were extracted and analyzed in this study, the average mAs for large size patient group was about 1.6 times to the small size patient group. For organs that covered in the scan range like lung, breast, heart, the dose values were 18.30±2.91mGy, 15.13 ±2.75mGy and 17.87±2.96mGy in small size patients(Dw smaller than 22cm).The dose values of lung, breast, heart, in medium-sized patients (Dw from 22cm to 25cm) were 21.89±4.60mGy, 18.16 ±4.13mGy and 21.46±4.60mGy, while the values were 24.98±4.40mGy, 20.81±3.66mGy and 24.77±4.46mGy respectively in large size patients(Dw larger than 25cm). The organ doses increase with the patient size due to the increase of mAs. CONCLUSIONS The PACS-based method of large batch organ dose calculation to patients undergoing chest CT with ATCM was established. The methods and results may provide guidance to the design and optimization of chest CT protocols with ATCM.


2018 ◽  
Vol 56 ◽  
pp. 96
Author(s):  
E. Gallio ◽  
F.R. Giglioli ◽  
V. Rossetti ◽  
C. Fiandra ◽  
R. Ropolo ◽  
...  

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