Converting computed tomography images into photon interaction coefficients by using stoichiometric calibration and parametric fit models. Issue 2 (30th January 2017)

• Record Type: Journal Article
• Authors: Shih, Cheng‐Ting; Wu, Jay
• Is Part Of: Medical physics. Volume 44:Issue 2(2017)
• Page Start: 510
• Page End: 521
• Publication Date: 2017-01-30
• Subjects: computed tomography -- photon attenuation coefficients -- physical parameters; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1002/mp.12055
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: X ray and γ‐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.