Literature DB >> 26546568

Knowledge-based iterative model reconstruction: comparative image quality and radiation dose with a pediatric computed tomography phantom.

Young Jin Ryu1,2, Young Hun Choi3,4, Jung-Eun Cheon1,2,5, Seongmin Ha6, Woo Sun Kim1,2,5, In-One Kim1,2,5.   

Abstract

BACKGROUND: CT of pediatric phantoms can provide useful guidance to the optimization of knowledge-based iterative reconstruction CT.
OBJECTIVE: To compare radiation dose and image quality of CT images obtained at different radiation doses reconstructed with knowledge-based iterative reconstruction, hybrid iterative reconstruction and filtered back-projection.
MATERIALS AND METHODS: We scanned a 5-year anthropomorphic phantom at seven levels of radiation. We then reconstructed CT data with knowledge-based iterative reconstruction (iterative model reconstruction [IMR] levels 1, 2 and 3; Philips Healthcare, Andover, MA), hybrid iterative reconstruction (iDose(4), levels 3 and 7; Philips Healthcare, Andover, MA) and filtered back-projection. The noise, signal-to-noise ratio and contrast-to-noise ratio were calculated. We evaluated low-contrast resolutions and detectability by low-contrast targets and subjective and objective spatial resolutions by the line pairs and wire.
RESULTS: With radiation at 100 peak kVp and 100 mAs (3.64 mSv), the relative doses ranged from 5% (0.19 mSv) to 150% (5.46 mSv). Lower noise and higher signal-to-noise, contrast-to-noise and objective spatial resolution were generally achieved in ascending order of filtered back-projection, iDose(4) levels 3 and 7, and IMR levels 1, 2 and 3, at all radiation dose levels. Compared with filtered back-projection at 100% dose, similar noise levels were obtained on IMR level 2 images at 24% dose and iDose(4) level 3 images at 50% dose, respectively. Regarding low-contrast resolution, low-contrast detectability and objective spatial resolution, IMR level 2 images at 24% dose showed comparable image quality with filtered back-projection at 100% dose. Subjective spatial resolution was not greatly affected by reconstruction algorithm.
CONCLUSION: Reduced-dose IMR obtained at 0.92 mSv (24%) showed similar image quality to routine-dose filtered back-projection obtained at 3.64 mSv (100%), and half-dose iDose(4) obtained at 1.81 mSv.

Keywords:  Children; Computed tomography; Infants; Iterative model reconstruction; Iterative reconstruction; Knowledge-based iterative reconstruction; Pediatric; Radiation

Mesh:

Year:  2015        PMID: 26546568     DOI: 10.1007/s00247-015-3486-6

Source DB:  PubMed          Journal:  Pediatr Radiol        ISSN: 0301-0449


  35 in total

1.  Comparison of hybrid and pure iterative reconstruction techniques with conventional filtered back projection: dose reduction potential in the abdomen.

Authors:  Sarabjeet Singh; Mannudeep K Kalra; Synho Do; Jean Baptiste Thibault; Homer Pien; Owen J O'Connor; Owen O J Connor; Michael A Blake
Journal:  J Comput Assist Tomogr       Date:  2012 May-Jun       Impact factor: 1.826

Review 2.  Computed tomography--an increasing source of radiation exposure.

Authors:  David J Brenner; Eric J Hall
Journal:  N Engl J Med       Date:  2007-11-29       Impact factor: 91.245

3.  Six iterative reconstruction algorithms in brain CT: a phantom study on image quality at different radiation dose levels.

Authors:  A Löve; M-L Olsson; R Siemund; F Stålhammar; I M Björkman-Burtscher; M Söderberg
Journal:  Br J Radiol       Date:  2013-09-18       Impact factor: 3.039

4.  Model-based iterative reconstruction for improvement of low-contrast detectability in liver CT at reduced radiation dose: ex-vivo experience.

Authors:  D B Husarik; H Alkadhi; G D Puippe; C S Reiner; N C Chuck; F Morsbach; Z Szucs-Farkas; S T Schindera
Journal:  Clin Radiol       Date:  2014-12-29       Impact factor: 2.350

5.  A quantitative comparison of noise reduction across five commercial (hybrid and model-based) iterative reconstruction techniques: an anthropomorphic phantom study.

Authors:  Manuel Patino; Jorge M Fuentes; Koichi Hayano; Avinash R Kambadakone; Jennifer W Uyeda; Dushyant V Sahani
Journal:  AJR Am J Roentgenol       Date:  2015-02       Impact factor: 3.959

6.  Assessment of image quality on effects of varying tube voltage and automatic tube current modulation with hybrid and pure iterative reconstruction techniques in abdominal/pelvic CT: a phantom study.

Authors:  Varut Vardhanabhuti; Robert Loader; Carl A Roobottom
Journal:  Invest Radiol       Date:  2013-03       Impact factor: 6.016

7.  Abdominal CT: comparison of adaptive statistical iterative and filtered back projection reconstruction techniques.

Authors:  Sarabjeet Singh; Mannudeep K Kalra; Jiang Hsieh; Paul E Licato; Synho Do; Homer H Pien; Michael A Blake
Journal:  Radiology       Date:  2010-09-09       Impact factor: 11.105

8.  Evaluation of low-dose CT angiography with model-based iterative reconstruction after endovascular aneurysm repair of a thoracic or abdominal aortic aneurysm.

Authors:  Neil J Hansen; Ravi K Kaza; Katherine E Maturen; Peter S Liu; Joel F Platt
Journal:  AJR Am J Roentgenol       Date:  2014-03       Impact factor: 3.959

9.  Diagnostic reference ranges for pediatric abdominal CT.

Authors:  Marilyn J Goske; Keith J Strauss; Laura P Coombs; Keith E Mandel; Alexander J Towbin; David B Larson; Michael J Callahan; Kassa Darge; Daniel J Podberesky; Donald P Frush; Sjirk J Westra; Jeffrey S Prince
Journal:  Radiology       Date:  2013-03-19       Impact factor: 11.105

10.  Cancer risk in 680,000 people exposed to computed tomography scans in childhood or adolescence: data linkage study of 11 million Australians.

Authors:  John D Mathews; Anna V Forsythe; Zoe Brady; Martin W Butler; Stacy K Goergen; Graham B Byrnes; Graham G Giles; Anthony B Wallace; Philip R Anderson; Tenniel A Guiver; Paul McGale; Timothy M Cain; James G Dowty; Adrian C Bickerstaffe; Sarah C Darby
Journal:  BMJ       Date:  2013-05-21
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1.  Impact of knowledge-based iterative model reconstruction on myocardial late iodine enhancement in computed tomography and comparison with cardiac magnetic resonance.

Authors:  Yuki Tanabe; Teruhito Kido; Akira Kurata; Naoki Fukuyama; Takahiro Yokoi; Tomoyuki Kido; Teruyoshi Uetani; Mani Vembar; Amar Dhanantwari; Shinichi Tokuyasu; Natsumi Yamashita; Teruhito Mochizuki
Journal:  Int J Cardiovasc Imaging       Date:  2017-04-13       Impact factor: 2.357

Review 2.  3D printing from cardiovascular CT: a practical guide and review.

Authors:  James M Otton; Nicolette S Birbara; Tarique Hussain; Gerald Greil; Thomas A Foley; Nalini Pather
Journal:  Cardiovasc Diagn Ther       Date:  2017-10

3.  Evaluation of low-contrast detectability for iterative reconstruction in pediatric abdominal computed tomography: a phantom study.

Authors:  Nicholas Rubert; Richard Southard; Susan M Hamman; Ryan Robison
Journal:  Pediatr Radiol       Date:  2019-11-09

4.  Deep learning versus iterative image reconstruction algorithm for head CT in trauma.

Authors:  Zlatan Alagic; Jacqueline Diaz Cardenas; Kolbeinn Halldorsson; Vitali Grozman; Stig Wallgren; Chikako Suzuki; Johan Helmenkamp; Seppo K Koskinen
Journal:  Emerg Radiol       Date:  2022-01-05

5.  Low-dose CT imaging of a total hip arthroplasty phantom using model-based iterative reconstruction and orthopedic metal artifact reduction.

Authors:  R H H Wellenberg; M F Boomsma; J A C van Osch; A Vlassenbroek; J Milles; M A Edens; G J Streekstra; C H Slump; M Maas
Journal:  Skeletal Radiol       Date:  2017-02-15       Impact factor: 2.199

6.  Contrast-Enhanced CT with Knowledge-Based Iterative Model Reconstruction for the Evaluation of Parotid Gland Tumors: A Feasibility Study.

Authors:  Chae Jung Park; Ki Wook Kim; Ho-Joon Lee; Myeong-Jin Kim; Jinna Kim
Journal:  Korean J Radiol       Date:  2018-08-06       Impact factor: 3.500

7.  Application of Vendor-Neutral Iterative Reconstruction Technique to Pediatric Abdominal Computed Tomography.

Authors:  Woo Hyeon Lim; Young Hun Choi; Ji Eun Park; Yeon Jin Cho; Seunghyun Lee; Jung Eun Cheon; Woo Sun Kim; In One Kim; Jong Hyo Kim
Journal:  Korean J Radiol       Date:  2019-09       Impact factor: 3.500

  7 in total

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