Literature DB >> 28477342

Estimating patient dose from CT exams that use automatic exposure control: Development and validation of methods to accurately estimate tube current values.

Kyle McMillan1,2, Maryam Bostani1,3, Christopher H Cagnon1,3, Lifeng Yu2, Shuai Leng2, Cynthia H McCollough2, Michael F McNitt-Gray1,3.   

Abstract

PURPOSE: The vast majority of body CT exams are performed with automatic exposure control (AEC), which adapts the mean tube current to the patient size and modulates the tube current either angularly, longitudinally or both. However, most radiation dose estimation tools are based on fixed tube current scans. Accurate estimates of patient dose from AEC scans require knowledge of the tube current values, which is usually unavailable. The purpose of this work was to develop and validate methods to accurately estimate the tube current values prescribed by one manufacturer's AEC system to enable accurate estimates of patient dose.
METHODS: Methods were developed that took into account available patient attenuation information, user selected image quality reference parameters and x-ray system limits to estimate tube current values for patient scans. Methods consistent with AAPM Report 220 were developed that used patient attenuation data that were: (a) supplied by the manufacturer in the CT localizer radiograph and (b) based on a simulated CT localizer radiograph derived from image data. For comparison, actual tube current values were extracted from the projection data of each patient. Validation of each approach was based on data collected from 40 pediatric and adult patients who received clinically indicated chest (n = 20) and abdomen/pelvis (n = 20) scans on a 64 slice multidetector row CT (Sensation 64, Siemens Healthcare, Forchheim, Germany). For each patient dataset, the following were collected with Institutional Review Board (IRB) approval: (a) projection data containing actual tube current values at each projection view, (b) CT localizer radiograph (topogram) and (c) reconstructed image data. Tube current values were estimated based on the actual topogram (actual-topo) as well as the simulated topogram based on image data (sim-topo). Each of these was compared to the actual tube current values from the patient scan. In addition, to assess the accuracy of each method in estimating patient organ doses, Monte Carlo simulations were performed by creating voxelized models of each patient, identifying key organs and incorporating tube current values into the simulations to estimate dose to the lungs and breasts (females only) for chest scans and the liver, kidney, and spleen for abdomen/pelvis scans. Organ doses from simulations using the actual tube current values were compared to those using each of the estimated tube current values (actual-topo and sim-topo).
RESULTS: When compared to the actual tube current values, the average error for tube current values estimated from the actual topogram (actual-topo) and simulated topogram (sim-topo) was 3.9% and 5.8% respectively. For Monte Carlo simulations of chest CT exams using the actual tube current values and estimated tube current values (based on the actual-topo and sim-topo methods), the average differences for lung and breast doses ranged from 3.4% to 6.6%. For abdomen/pelvis exams, the average differences for liver, kidney, and spleen doses ranged from 4.2% to 5.3%.
CONCLUSIONS: Strong agreement between organ doses estimated using actual and estimated tube current values provides validation of both methods for estimating tube current values based on data provided in the topogram or simulated from image data.
© 2017 American Association of Physicists in Medicine.

Entities:  

Keywords:  Monte Carlo simulations; computed tomography; organ dose; radiation dose; tube current modulation

Mesh:

Year:  2017        PMID: 28477342      PMCID: PMC5553684          DOI: 10.1002/mp.12314

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  19 in total

1.  Dose reduction in CT by anatomically adapted tube current modulation. I. Simulation studies.

Authors:  M Gies; W A Kalender; H Wolf; C Suess
Journal:  Med Phys       Date:  1999-11       Impact factor: 4.071

2.  Comparison of Z-axis automatic tube current modulation technique with fixed tube current CT scanning of abdomen and pelvis.

Authors:  Mannudeep K Kalra; Michael M Maher; Thomas L Toth; Ravi S Kamath; Elkan F Halpern; Sanjay Saini
Journal:  Radiology       Date:  2004-08       Impact factor: 11.105

3.  Dose conversion coefficients for CT examinations of adults with automatic tube current modulation.

Authors:  H Schlattl; M Zankl; J Becker; C Hoeschen
Journal:  Phys Med Biol       Date:  2010-09-30       Impact factor: 3.609

4.  A comparison of methods to estimate organ doses in CT when utilizing approximations to the tube current modulation function.

Authors:  Maryam Khatonabadi; Di Zhang; Kelsey Mathieu; Hyun J Kim; Peiyun Lu; Dianna Cody; John J Demarco; Chris H Cagnon; Michael F McNitt-Gray
Journal:  Med Phys       Date:  2012-08       Impact factor: 4.071

5.  A method to generate equivalent energy spectra and filtration models based on measurement for multidetector CT Monte Carlo dosimetry simulations.

Authors:  Adam C Turner; Di Zhang; Hyun J Kim; John J DeMarco; Chris H Cagnon; Erin Angel; Dianna D Cody; Donna M Stevens; Andrew N Primak; Cynthia H McCollough; Michael F McNitt-Gray
Journal:  Med Phys       Date:  2009-06       Impact factor: 4.071

6.  Prospective estimation of organ dose in CT under tube current modulation.

Authors:  Xiaoyu Tian; Xiang Li; W Paul Segars; Donald P Frush; Ehsan Samei
Journal:  Med Phys       Date:  2015-04       Impact factor: 4.071

7.  Dose reduction in CT by anatomically adapted tube current modulation. II. Phantom measurements.

Authors:  W A Kalender; H Wolf; C Suess
Journal:  Med Phys       Date:  1999-11       Impact factor: 4.071

Review 8.  Techniques and applications of automatic tube current modulation for CT.

Authors:  Mannudeep K Kalra; Michael M Maher; Thomas L Toth; Bernhard Schmidt; Bryan L Westerman; Hugh T Morgan; Sanjay Saini
Journal:  Radiology       Date:  2004-10-21       Impact factor: 11.105

9.  Dose to radiosensitive organs during routine chest CT: effects of tube current modulation.

Authors:  Erin Angel; Nazanin Yaghmai; Cecilia Matilda Jude; John J DeMarco; Christopher H Cagnon; Jonathan G Goldin; Cynthia H McCollough; Andrew N Primak; Dianna D Cody; Donna M Stevens; Michael F McNitt-Gray
Journal:  AJR Am J Roentgenol       Date:  2009-11       Impact factor: 3.959

10.  Monte Carlo simulations to assess the effects of tube current modulation on breast dose for multidetector CT.

Authors:  Erin Angel; Nazanin Yaghmai; Cecilia Matilda Jude; John J Demarco; Christopher H Cagnon; Jonathan G Goldin; Andrew N Primak; Donna M Stevens; Dianna D Cody; Cynthia H McCollough; Michael F McNitt-Gray
Journal:  Phys Med Biol       Date:  2009-01-06       Impact factor: 3.609

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  11 in total

1.  Estimating fetal dose from tube current-modulated (TCM) and fixed tube current (FTC) abdominal/pelvis CT examinations.

Authors:  Anthony J Hardy; Erin Angel; Maryam Bostani; Chris Cagnon; Michael McNitt-Gray
Journal:  Med Phys       Date:  2019-04-24       Impact factor: 4.071

2.  Estimating lung, breast, and effective dose from low-dose lung cancer screening CT exams with tube current modulation across a range of patient sizes.

Authors:  Anthony J Hardy; Maryam Bostani; Kyle McMillan; Maria Zankl; Cynthia McCollough; Chris Cagnon; Michael McNitt-Gray
Journal:  Med Phys       Date:  2018-09-24       Impact factor: 4.071

3.  A scanner-specific framework for simulating CT images with tube current modulation.

Authors:  Giavanna Jadick; Ehsan Abadi; Brian Harrawood; Shobhit Sharma; W Paul Segars; Ehsan Samei
Journal:  Phys Med Biol       Date:  2021-09-13       Impact factor: 3.609

4.  Reconstruction of three-dimensional tomographic patient models for radiation dose modulation in CT from two scout views using deep learning.

Authors:  Juan C Montoya; Chengzhu Zhang; Yinsheng Li; Ke Li; Guang-Hong Chen
Journal:  Med Phys       Date:  2022-01-06       Impact factor: 4.506

5.  Reference dataset for benchmarking fetal doses derived from Monte Carlo simulations of CT exams.

Authors:  Anthony J Hardy; Maryam Bostani; Erin Angel; Chris Cagnon; Ioannis Sechopoulos; Michael F McNitt-Gray
Journal:  Med Phys       Date:  2020-11-28       Impact factor: 4.071

6.  Evaluation of AAPM Reports 204 and 220: Estimation of effective diameter, water-equivalent diameter, and ellipticity ratios for chest, abdomen, pelvis, and head CT scans.

Authors:  Christiane S Burton; Timothy P Szczykutowicz
Journal:  J Appl Clin Med Phys       Date:  2017-11-27       Impact factor: 2.102

7.  Detection of unwarranted CT radiation exposure from patient and imaging protocol meta-data using regularized regression.

Authors:  Ruidi Chen; Ioannis Ch Paschalidis; Hiroto Hatabu; Vladimir I Valtchinov; Jenifer Siegelman
Journal:  Eur J Radiol Open       Date:  2019-06-05

8.  Method of determining geometric patient size surrogates using localizer images in CT.

Authors:  Christiane S Burton
Journal:  J Appl Clin Med Phys       Date:  2020-01-28       Impact factor: 2.102

9.  A comparison of breast and lung doses from chest CT scans using organ-based tube current modulation (OBTCM) vs. Automatic tube current modulation (ATCM).

Authors:  Rick R Layman; Anthony J Hardy; Hyun J Kim; Ei Ne Chou; Maryam Bostani; Chris Cagnon; Dianna Cody; Michael McNitt-Gray
Journal:  J Appl Clin Med Phys       Date:  2021-05-03       Impact factor: 2.102

10.  Accuracy of automated patient positioning in CT using a 3D camera for body contour detection.

Authors:  Ronald Booij; Ricardo P J Budde; Marcel L Dijkshoorn; Marcel van Straten
Journal:  Eur Radiol       Date:  2018-10-10       Impact factor: 5.315

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