Performance evaluation of computed tomography systems: Summary of AAPM Task Group 233. Issue 11 (11th September 2019)

• Record Type: Journal Article
• Authors: Samei, Ehsan; Bakalyar, Donovan; Boedeker, Kirsten L.; Brady, Samuel; Fan, Jiahua; Leng, Shuai; Myers, Kyle J.; Popescu, Lucretiu M.; Ramirez Giraldo, Juan Carlos; Ranallo, Frank; Solomon, Justin; Vaishnav, Jay; Wang, Jia
• Is Part Of: Medical physics. Volume 46:Issue 11(2019)
• Page Start: e735
• Page End: e756
• Publication Date: 2019-09-11
• Subjects: acceptance testing -- computed tomography -- detectability -- noise -- quality control -- resolution; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1002/mp.13763
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Background: The rapid development and complexity of new x‐ray computed tomography (CT) technologies and the need for evidence‐based optimization of image quality with respect to radiation and contrast media dose call for an updated approach towards CT performance evaluation. Aims: This report offers updated testing guidelines for testing CT systems with an enhanced focus on the operational performance including iterative reconstructions and automatic exposure control (AEC) techniques. Materials and Methods: The report was developed based on a comprehensive review of best methods and practices in the scientific literature. The detailed methods include the assessment of 1) CT noise (magnitude, texture, nonuniformity, inhomogeneity), 2) resolution (task transfer function under varying conditions and its scalar reflections), 3) task‐based performance (detectability, estimability), and 4) AEC performance (spatial, noise, and mA concordance of attenuation and exposure modulation). The methods include varying reconstruction and tube current modulation conditions, standardized testing protocols, and standardized quantities and metrology to facilitate tracking, benchmarking, and quantitative comparisons. Results: The methods, implemented in cited publications, are robust to provide a representative reflection of CT system performance as used operationally in a clinical facility. The methods include recommendations for phantoms and phantom image analysis. Discussion: In line with the current professional trajectory of the field toward quantitation and operational engagement, the stated methods offer quantitation that is more predictive of clinical performance than specification‐based approaches. They can pave the way to approach performance testing of new CT systems not only in terms of acceptance testing (i.e., verifying a device meets predefined specifications), but also system commissioning (i.e., determining how the system can be used most effectively in clinical practice). Conclusion: We offer a set of common testing procedures that can be utilized towards the optimal clinical utilization of CT imaging devices, benchmarking across varying systems and times, and a basis to develop future performance‐based criteria for CT imaging.