PMID- 27348057
OWN - NLM
STAT- MEDLINE
DCOM- 20161213
LR  - 20181202
IS  - 1873-4499 (Electronic)
IS  - 0899-7071 (Linking)
VI  - 40
IP  - 5
DP  - 2016 Sep-Oct
TI  - Model-based iterative reconstruction in ultra-low-dose pediatric chest CT: 
      comparison with adaptive statistical iterative reconstruction.
PG  - 1018-22
LID - S0899-7071(16)30068-7 [pii]
LID - 10.1016/j.clinimag.2016.06.006 [doi]
AB  - PURPOSE: To evaluate image quality and dose reduction of ultra-low-dose pediatric 
      chest CT reconstructed with model-based iterative reconstruction (MBIR), as 
      compared with adaptive statistical iterative reconstruction (ASIR). MATERIALS AND 
      METHODS: Fifty-seven patients (mean age 14 years, M:F=31:26) who underwent 
      ultra-low-dose chest CT reconstructed with both MBIR and ASIR were enrolled in 
      the study. The subjective and objective image qualities of both reconstruction 
      techniques were assessed by 3 radiologists, and compared using statistical 
      analysis. We also evaluated radiation dose of ultra-low-dose chest CT as well as 
      degree of dose reduction in comparison to the prior CT (either standard dose or 
      reduced dose protocol) available in 36 patients. RESULTS: The image quality of 
      MBIR was superior to ASIR both subjectively and objectively. While MBIR showed 
      preserved diagnostic acceptability in 100%, ASIR showed 92% at mean 0.31 mSv 
      (range, 0.13-0.57 mSv) ultra-low-dose CT. In the 36 patients who underwent the 
      prior CT, mean decrease in size-specific dose estimate (SSDE) and dose length 
      product (DLP) at ultra-low-dose CT was 88% (range, 34% - 98%) and 86% (range,42% 
      - 99%), respectively. CONCLUSIONS: MBIR significantly improves image quality, as 
      compared to ASIR. Furthermore, MBIR facilitates diagnostically acceptable 
      ultra-low-dose chest CT with nearly 90% less radiation.
CI  - Copyright (c) 2016 Elsevier Inc. All rights reserved.
FAU - Kim, Hae Jin
AU  - Kim HJ
AD  - Department of Radiology and Center for Imaging Science, Samsung Medical Center, 
      Sungkyunkwan University School of Medicine, Seoul, Korea.
FAU - Yoo, So-Young
AU  - Yoo SY
AD  - Department of Radiology and Center for Imaging Science, Samsung Medical Center, 
      Sungkyunkwan University School of Medicine, Seoul, Korea. Electronic address: 
      somatom25@hanmail.net.
FAU - Jeon, Tae Yeon
AU  - Jeon TY
AD  - Department of Radiology and Center for Imaging Science, Samsung Medical Center, 
      Sungkyunkwan University School of Medicine, Seoul, Korea.
FAU - Kim, Ji Hye
AU  - Kim JH
AD  - Department of Radiology and Center for Imaging Science, Samsung Medical Center, 
      Sungkyunkwan University School of Medicine, Seoul, Korea.
LA  - eng
PT  - Comparative Study
PT  - Journal Article
DEP - 20160616
PL  - United States
TA  - Clin Imaging
JT  - Clinical imaging
JID - 8911831
SB  - IM
MH  - Adolescent
MH  - Algorithms
MH  - Child
MH  - Female
MH  - Humans
MH  - Lung/*diagnostic imaging
MH  - Male
MH  - Models, Theoretical
MH  - *Radiation Dosage
MH  - Radiographic Image Interpretation, Computer-Assisted/*methods
MH  - Retrospective Studies
MH  - Tomography, X-Ray Computed/*methods
MH  - Young Adult
OTO - NOTNLM
OT  - CT dose reduction
OT  - Iterative reconstruction
OT  - Model-based iterative reconstruction
OT  - Pediatric chest CT
EDAT- 2016/06/28 06:00
MHDA- 2016/12/15 06:00
CRDT- 2016/06/28 06:00
PHST- 2016/02/16 00:00 [received]
PHST- 2016/05/03 00:00 [revised]
PHST- 2016/06/13 00:00 [accepted]
PHST- 2016/06/28 06:00 [entrez]
PHST- 2016/06/28 06:00 [pubmed]
PHST- 2016/12/15 06:00 [medline]
AID - S0899-7071(16)30068-7 [pii]
AID - 10.1016/j.clinimag.2016.06.006 [doi]
PST - ppublish
SO  - Clin Imaging. 2016 Sep-Oct;40(5):1018-22. doi: 10.1016/j.clinimag.2016.06.006. 
      Epub 2016 Jun 16.