PMID- 28133756
OWN - NLM
STAT- MEDLINE
DCOM- 20170320
LR  - 20191210
IS  - 2473-4209 (Electronic)
IS  - 0094-2405 (Linking)
VI  - 44
IP  - 2
DP  - 2017 Feb
TI  - Converting computed tomography images into photon interaction coefficients by 
      using stoichiometric calibration and parametric fit models.
PG  - 510-521
LID - 10.1002/mp.12055 [doi]
AB  - PURPOSE: X ray and gamma-ray are widely applied in radiology, radiotherapy, and 
      nuclear medicine. Linear attenuation coefficients and linear energy absorption 
      coefficients are essential for dose calculation and image correction. In this 
      study, a method that entails combining the stoichiometric calibration and 
      parametric physical models was developed to convert computed tomography (CT) 
      images into the linear attenuation coefficients and linear energy absorption 
      coefficients. METHODS: A calibration scan was performed using standard 
      tissue-equivalent materials to obtain the characteristics of the x-ray energy 
      spectrum. Subsequently, relationships between CT numbers and tissue parameters 
      were established using standard soft tissue and bone tissue data adopted from the 
      literature. The linear attenuation coefficient and linear energy absorption 
      coefficient were calculated using the parametric fit model. RESULTS: The results 
      showed a linear relationship between CT numbers and tissue parameters. The 
      tissue-equivalent materials differed from real human tissues, leading to 
      considerable errors in estimation of mass attenuation coefficients when the 
      photon energy was lower than 50 keV. Mass attenuation coefficients and mass 
      energy transfer coefficients of five tissues were calculated and validated using 
      clinical CT images. The error was less than +/- 5% and +/- 8%, compared with the 
      values of the International Commission on Radiation Units (ICRU) 46 report. 
      CONCLUSIONS: The probability of photon interaction with tissues and physical 
      characteristics of tissues can be accurately evaluated by using the proposed 
      method and applied in various clinical applications.
CI  - (c) 2016 American Association of Physicists in Medicine.
FAU - Shih, Cheng-Ting
AU  - Shih CT
AD  - 3D Printing Medical Research Center, China Medical University Hospital, China 
      Medical University, Taichung, 40402, Taiwan.
FAU - Wu, Jay
AU  - Wu J
AD  - Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming 
      University, Taipei, 11221, Taiwan.
LA  - eng
PT  - Journal Article
PT  - Validation Study
DEP - 20170130
PL  - United States
TA  - Med Phys
JT  - Medical physics
JID - 0425746
SB  - IM
MH  - Adipose Tissue/diagnostic imaging
MH  - Algorithms
MH  - Bone and Bones/diagnostic imaging
MH  - Brain/diagnostic imaging
MH  - Calibration
MH  - Humans
MH  - Liver/diagnostic imaging
MH  - Lung/diagnostic imaging
MH  - *Models, Theoretical
MH  - Muscles/diagnostic imaging
MH  - Pelvis/diagnostic imaging
MH  - *Photons
MH  - Probability
MH  - Tomography, X-Ray Computed/*methods
OTO - NOTNLM
OT  - computed tomography
OT  - photon attenuation coefficients
OT  - physical parameters
EDAT- 2017/01/31 06:00
MHDA- 2017/03/21 06:00
CRDT- 2017/01/31 06:00
PHST- 2016/03/23 00:00 [received]
PHST- 2016/11/29 00:00 [revised]
PHST- 2016/12/05 00:00 [accepted]
PHST- 2017/01/31 06:00 [pubmed]
PHST- 2017/03/21 06:00 [medline]
PHST- 2017/01/31 06:00 [entrez]
AID - 10.1002/mp.12055 [doi]
PST - ppublish
SO  - Med Phys. 2017 Feb;44(2):510-521. doi: 10.1002/mp.12055. Epub 2017 Jan 30.