Literature DB >> 30975652

Comparison of Iterative Model Reconstruction versus Filtered Back-Projection in Pediatric Emergency Head CT: Dose, Image Quality, and Image-Reconstruction Times.

R N Southard1, D M E Bardo2, M H Temkit3, M A Thorkelson2, R A Augustyn2, C A Martinot2.   

Abstract

BACKGROUND AND
PURPOSE: Noncontrast CT of the head is the initial imaging test for traumatic brain injury, stroke, or suspected nonaccidental trauma. Low-dose head CT protocols using filtered back-projection are susceptible to increased noise and decreased image quality. Iterative reconstruction noise suppression allows the use of lower-dose techniques with maintained image quality. We review our experience with children undergoing emergency head CT examinations reconstructed using knowledge-based iterative model reconstruction versus standard filtered back-projection, comparing reconstruction times, radiation dose, and objective and subjective image quality.
MATERIALS AND METHODS: This was a retrospective study comparing 173 children scanned using standard age-based noncontrast head CT protocols reconstructed with filtered back-projection with 190 children scanned using low-dose protocols reconstructed with iterative model reconstruction. ROIs placed on the frontal white matter and thalamus yielded signal-to-noise and contrast-to-noise ratios. Volume CT dose index and study reconstruction times were recorded. Random subgroups of patients were selected for subjective image-quality review.
RESULTS: The volume CT dose index was significantly reduced in studies reconstructed with iterative model reconstruction compared with filtered back-projection, (mean, 24.4 ± 3.1 mGy versus 31.1 ± 6.0 mGy, P < .001), while the SNR and contrast-to-noise ratios improved 2-fold (P < .001). Radiologists graded iterative model reconstruction images as superior to filtered back-projection images for gray-white matter differentiation and anatomic detail (P < .001). The average reconstruction time of the filtered back-projection studies was 101 seconds, and with iterative model reconstruction, it was 147 seconds (P < .001), without a practical effect on work flow.
CONCLUSIONS: In children referred for emergency noncontrast head CT, optimized low-dose protocols with iterative model reconstruction allowed us to significantly reduce the relative dose, on average, 22% compared with filtered back-projection, with significantly improved objective and subjective image quality.
© 2019 by American Journal of Neuroradiology.

Entities:  

Mesh:

Year:  2019        PMID: 30975652      PMCID: PMC7053890          DOI: 10.3174/ajnr.A6034

Source DB:  PubMed          Journal:  AJNR Am J Neuroradiol        ISSN: 0195-6108            Impact factor:   3.825


  25 in total

1.  The use of adaptive statistical iterative reconstruction in pediatric head CT: a feasibility study.

Authors:  G A Vorona; G Zuccoli; T Sutcavage; B L Clayton; R C Ceschin; A Panigrahy
Journal:  AJNR Am J Neuroradiol       Date:  2012-05-24       Impact factor: 3.825

2.  Improved image quality of helical computed tomography of the head in children by iterative reconstruction.

Authors:  Shun Ono; Tetsu Niwa; Noriharu Yanagimachi; Tomohiro Yamashita; Takashi Okazaki; Takakiyo Nomura; Jun Hashimoto; Yutaka Imai
Journal:  J Neuroradiol       Date:  2015-10-28       Impact factor: 3.447

Review 3.  Radiation dose-reduction strategies for neuroradiology CT protocols.

Authors:  A B Smith; W P Dillon; R Gould; M Wintermark
Journal:  AJNR Am J Neuroradiol       Date:  2007-09-24       Impact factor: 3.825

Review 4.  CT radiation dose: what can you do right now in your practice?

Authors:  Fergus V Coakley; Robert Gould; Benjamin M Yeh; Ronald L Arenson
Journal:  AJR Am J Roentgenol       Date:  2011-03       Impact factor: 3.959

5.  Quantitative and qualitative comparison of standard-dose and low-dose pediatric head computed tomography: a retrospective study assessing the effect of adaptive statistical iterative reconstruction.

Authors:  Koray Kilic; Gonca Erbas; Melike Guryildirim; Oznur Leman Konus; Mehmet Arac; Erhan Ilgit; Sedat Isik
Journal:  J Comput Assist Tomogr       Date:  2013 May-Jun       Impact factor: 1.826

6.  Comparison of image quality in pediatric head computed tomography reconstructed using blended iterative reconstruction versus filtered back projection.

Authors:  Chang Ho; Robert Oberle; Isaac Wu; Eugene Kim
Journal:  Clin Imaging       Date:  2013-12-21       Impact factor: 1.605

7.  Radiation dose reduction with hybrid iterative reconstruction for pediatric CT.

Authors:  Sarabjeet Singh; Mannudeep K Kalra; Anuradha S Shenoy-Bhangle; Aashna Saini; Debra A Gervais; Sjirk J Westra; James H Thrall
Journal:  Radiology       Date:  2012-05       Impact factor: 11.105

8.  ACR Appropriateness Criteria head trauma--child.

Authors:  Maura E Ryan; Susan Palasis; Gaurav Saigal; Adam D Singer; Boaz Karmazyn; Molly E Dempsey; Jonathan R Dillman; Christopher E Dory; Matthew Garber; Laura L Hayes; Ramesh S Iyer; Catherine A Mazzola; Molly E Raske; Henry E Rice; Cynthia K Rigsby; Paul R Sierzenski; Peter J Strouse; Sjirk J Westra; Sandra L Wootton-Gorges; Brian D Coley
Journal:  J Am Coll Radiol       Date:  2014-08-20       Impact factor: 5.532

9.  Impact of iterative model reconstruction combined with dose reduction on the image quality of head and neck CTA in children.

Authors:  Bochao Cheng; Haoyang Xing; Du Lei; Yingkun Guo; Gang Ning; Qiyong Gong; Wu Cai
Journal:  Sci Rep       Date:  2018-08-22       Impact factor: 4.379

10.  Thin-slice brain CT with iterative model reconstruction algorithm for small lacunar lesions detection: Image quality and diagnostic accuracy evaluation.

Authors:  Xiaoyi Liu; Lei Chen; Weiwei Qi; Yan Jiang; Ying Liu; Miao Zhang; Nan Hong
Journal:  Medicine (Baltimore)       Date:  2017-12       Impact factor: 1.817

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  8 in total

1.  Iterative reconstruction with multifrequency signal recognition technology to improve low-contrast detectability: A phantom study.

Authors:  Yoshinori Funama; Takashi Shirasaka; Taiga Goto; Yuko Aoki; Kana Tanaka; Ryo Yoshida
Journal:  Acta Radiol Open       Date:  2022-06-17

2.  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

3.  Accuracy of thin-slice model-based iterative reconstruction designed for brain CT to diagnose acute ischemic stroke in the middle cerebral artery territory: a multicenter study.

Authors:  Hidenori Mitani; Fuminari Tatsugami; Toru Higaki; Yoko Kaichi; Yuko Nakamura; Ewoud Smit; Mathias Prokop; Chiaki Ono; Ken Ono; Yukunori Korogi; Kazuo Awai
Journal:  Neuroradiology       Date:  2021-06-30       Impact factor: 2.804

4.  A Preliminary Study of Personalized Head CT Scan in Pediatric Patients.

Authors:  Bian Bingyang; Wang Gang; Shao Zhiqing; Nan Li; BoXu Zhou; ShuJia Xu; Dan Li
Journal:  Dose Response       Date:  2021-03-04       Impact factor: 2.658

5.  Simulated Annealing-Based Image Reconstruction for Patients With COVID-19 as a Model for Ultralow-Dose Computed Tomography.

Authors:  Shahzad Ahmad Qureshi; Aziz Ul Rehman; Adil Aslam Mir; Muhammad Rafique; Wazir Muhammad
Journal:  Front Physiol       Date:  2022-01-14       Impact factor: 4.566

6.  Chest Computed Tomography Images in Neonatal Bronchial Pneumonia under the Adaptive Statistical Iterative Reconstruction Algorithm.

Authors:  Ying Sun; Liao Wu; Zhaofang Tian; Tianping Bao
Journal:  J Healthc Eng       Date:  2021-10-27       Impact factor: 2.682

7.  Efficacy Evaluation of 64-Slice Spiral Computed Tomography Images in Laparoscopic-Assisted Distal Gastrectomy for Gastric Cancer under the Reconstruction Algorithm.

Authors:  Weiguang Yu; Xing Li; Hongbo Zhou; Yang Zhang; Zhiguo Sun
Journal:  Contrast Media Mol Imaging       Date:  2022-05-31       Impact factor: 3.009

8.  Application of a deep learning image reconstruction (DLIR) algorithm in head CT imaging for children to improve image quality and lesion detection.

Authors:  Jihang Sun; Haoyan Li; Bei Wang; Jianying Li; Michelle Li; Zuofu Zhou; Yun Peng
Journal:  BMC Med Imaging       Date:  2021-07-08       Impact factor: 1.930

  8 in total

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