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TU‐C‐BRC‐03: AAPM Initiatives in Quantitative Imaging
Author(s) -
Boone JM
Publication year - 2009
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3182337
Subject(s) - standardization , computer science , medical imaging , consistency (knowledge bases) , medical physics , software , calibration , data science , medicine , artificial intelligence , mathematics , statistics , programming language , operating system
The Science Council (SC) of the AAPM has initiated the Quantitative Imaging (QI) Initiative, which is an effort focused on moving the field of diagnostic imaging towards a more quantitative footing. While much of the quantitative content of the radiologist report will be generated by the radiologist with perhaps the help of user‐friendly and robust software capable of generating quantitative metrics off of a patient's images, there is an important role for physicists to play in assuring the quantitative integrity of the image data. The QI Initiative currently has three task groups, on PET/CT, on dynamic contrast enhanced MRI, and on CT. The methods and activity of these groups towards achieving their objectives will be discussed. The activity of these three groups has overlap with similar efforts of other societies such as the SNM, ISMRM, and the RSNA, and the interconnections will also be described. The parallel, integrated efforts towards creating a more quantitative future for medical imaging assessment is being driven by the needs of clinical research trials, as well as other payer initiatives such as pay for performance. Long term, the QI Initiative will include a comprehensive array of procedures to reduce variance in the imaging process, by standardization of the acquisition protocols, calibration of the spatial and gray scale output of scanners, incorporation of structured reporting tools to improve accuracy and format consistency, and the development of scientific software capable of extracting accurate QI data from image data.