Literature DB >> 26001256

CT Dose Reduction for Visceral Adipose Tissue Measurement: Effects of Model-Based and Adaptive Statistical Iterative Reconstructions and Filtered Back Projection.

Yoshitake Yamada1, Masahiro Jinzaki, Yuki Niijima, Masahiro Hashimoto, Minoru Yamada, Takayuki Abe, Sachio Kuribayashi.   

Abstract

OBJECTIVE: The objective of our study was to evaluate the effects of radiation dose reduction and the reconstruction algorithm used--filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR), or model-based iterative reconstruction (MBIR)--on the measurement of abdominal visceral fat using CT. SUBJECTS AND METHODS: Standard-dose and low-dose abdominal CT examinations were performed simultaneously with automatic exposure control in 59 patients; the noise index for a 5-mm slice thickness was 12 for routine-dose CT and 24 for low-dose CT. The routine-dose CT images were reconstructed using FBP (reference standard), and the low-dose CT images were reconstructed using FBP, ASIR (so-called hybrid iterative reconstruction [IR]), and MBIR (so-called pure IR). In the 236 image series obtained, the visceral fat area was measured. Data were analyzed by the Pearson correlation coefficient test and a Bland-Altman difference analysis.
RESULTS: The radiation dose of the low-dose abdominal CT examinations was 73.0% (mean) lower than that of routine-dose CT examinations. Excellent correlations were observed between the visceral fat areas measured on the routine-dose FBP images and those measured on the low-dose FBP, low-dose ASIR, and low-dose MBIR images (r = 0.998, 0.998, and 0.998, respectively; p < 0.001). A Bland-Altman difference analysis revealed excellent agreements, with mean biases of -0.47, -0.41, and 0.18 cm(2) for the visceral fat area between the routine-dose FBP images and the low-dose FBP, low-dose ASIR, and low-dose MBIR images, respectively.
CONCLUSION: A 73.0% reduction of the radiation dose would be possible in CT for the measurement of the abdominal visceral fat regardless of which reconstruction algorithm is used (i.e., FBP, hybrid IR, or pure IR).

Entities:  

Keywords:  MDCT; abdomen; intraabdominal fat; radiation dose

Mesh:

Year:  2015        PMID: 26001256     DOI: 10.2214/AJR.14.13411

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  5 in total

1.  Anthropometer3D: Automatic Multi-Slice Segmentation Software for the Measurement of Anthropometric Parameters from CT of PET/CT.

Authors:  Pierre Decazes; David Tonnelet; Pierre Vera; Isabelle Gardin
Journal:  J Digit Imaging       Date:  2019-04       Impact factor: 4.056

2.  Low-dose MDCT: evaluation of the impact of systematic tube current reduction and sparse sampling on quantitative paraspinal muscle assessment.

Authors:  Egon Burian; Nico Sollmann; Kai Mei; Michael Dieckmeyer; Daniela Juncker; Maximilian Löffler; Tobias Greve; Claus Zimmer; Jan S Kirschke; Thomas Baum; Peter B Noël
Journal:  Quant Imaging Med Surg       Date:  2021-07

3.  Comparison study of image quality at various radiation doses for CT venography using advanced modeled iterative reconstruction.

Authors:  Jung Han Hwang; Jin Mo Kang; So Hyun Park; Suyoung Park; Jeong Ho Kim; Sang Tae Choi
Journal:  PLoS One       Date:  2021-08-31       Impact factor: 3.240

4.  Body composition determinants of radiation dose during abdominopelvic CT.

Authors:  Patrick D McLaughlin; Liam Chawke; Maria Twomey; Kevin P Murphy; Siobhán B O'Neill; Sebastian R McWilliams; Karl James; Richard G Kavanagh; Charles Sullivan; Faimee E Chan; Niamh Moore; Owen J O'Connor; Joseph A Eustace; Michael M Maher
Journal:  Insights Imaging       Date:  2017-10-23

5.  Comparison of inspiratory and expiratory lung and lobe volumes among supine, standing, and sitting positions using conventional and upright CT.

Authors:  Yoshitake Yamada; Minoru Yamada; Shotaro Chubachi; Yoichi Yokoyama; Shiho Matsuoka; Akiko Tanabe; Yuki Niijima; Mitsuru Murata; Koichi Fukunaga; Masahiro Jinzaki
Journal:  Sci Rep       Date:  2020-10-01       Impact factor: 4.379

  5 in total

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