David W. Jordan

Introduction: In 2020, the American Association of Physicists in Medicine (AAPM) conducted a comprehensive imaging physics workforce survey (2020 Survey) to evaluate staffing needs, validate prior time and effort estimates, and explore workforce satisfaction. This report summarizes key findings, highlighting gaps between training and professional demands, challenges in recruitment, and shifts in workforce demographics and employment patterns. Methods: The 2020 Survey, administered by the American Institute of Physics (AIP) Statistical Research Center (SRC) to AAPM and Health Physics Society members, had 953 responses from participants who were primarily diagnostic and nuclear medical physicists. The data were analyzed across four key areas: professional task workloads, workforce demographics and retirement outlook, lifestyle factors, and skill gaps. Results and Discussion: The AIP SRC analyzed the results of the 2020 Survey (results archived on the AAPM members‐only website). The 2020 Survey validated the relative time required for equipment performance evaluations and the wide range of Level 2 services performed by the imaging physics workforce relative to AAPM Report 301. The 2020 Survey showed that the imaging physics workforce is aging (30% of respondents providing their age stated they were 66 years or older) and that many of these individuals could retire within 5 years of completing the survey. Finally, the 2020 Survey demonstrated that there were gaps between the skills and knowledge employers look for when hiring compared to the same self‐identified qualities of the imaging physics workforce. Conclusions: The 2020 Survey provided insights into the imaging physics workforce that validated prior publications estimating imaging physics workforce activities. The 2020 Survey indicates the imaging physics workforce is aging, with a wave of retirements on the horizon, and that individuals entering the workforce may not possess the skills and knowledge desired by employers. The data from this survey can be used to guide analyses and address future trends of the imaging physics field and workforce.

Today's diagnostic medical physicist finds a broad variety of instruments available to make the numerous quality control (QC) measurements needed for routine equipment evaluations. One of the distinguishing features of different options is the availability of multi‐purpose solid‐state detectors (SSD) and application‐specific ion chambers (IC) that can be used for measurements of the various modality equipment types. Since these measurements are the “bread and butter” of diagnostic physics work and the foundation of quality and safety for patients, the choice will have profound implications for many aspects of the physicist's work. In this debate, we explore the roles of SSD and IC instruments through the insights and perspectives of two highly experienced and accomplished diagnostic medical physicists.

Purpose: The purpose of this study was to assess the parameters and performance of CT protocols collected in numerous annual medical physics CT equipment performance evaluations (EPEs), develop clinically relevant performance targets for select phantom tests, and provide guidance for medical physicists about appropriate CT imaging parameters. Background: The results of CT scanner annual physics testing depend on the clinical protocols used at the facility, with a key image quality parameter dependent on the associated radiation dose. The American College of Radiology (ACR) accreditation process and quality control manual impose criteria on these parameters, but these minimum criteria are not meaningful performance targets for clinically acceptable protocols. Methods: A mathematical relationship between dose and contrast‐to‐noise ratio (CNR) was developed to evaluate test results and guide protocol adjustments. Historical testing results, including CNR and measured CTDI _vol were collected from 111 completed annual EPEs, and the results were compared to ACR criteria and published guidance on scanning parameters. Results: The average and 75th percentile CDTI _vol values were markedly lower than the ACR reference values, while the average and 25th percentile CNR values were markedly higher than the ACR minimum reference values. Scanners where iterative reconstruction (IR) was used did not show lower CTDI _vol values than scanners using filtered backprojection. Protocol parameters in routine clinical use showed high rates of deviation from published reference protocols and clinical imaging guidelines. Conclusions: Modern CT scanners likely can exceed ACR accreditation targets for image quality at radiation dose levels well below the ACR limits. Clinical medical physicists can use the approach described in this study to recommend clinical protocol improvements when performing physics testing. Medical physicists can engage with radiologists and technologists to determine whether published protocol guidelines are appropriate for clinical needs and can use the simple mathematical relationship described in this paper to translate protocols for modifications such as reduced slice thickness.

Background: Published reference CT protocols for lung cancer screening are not optimized to produce uniform image appearance across different scanner manufacturers and models or to conform to quantitative imaging profiles for robust small lung nodule size and volume measurements, which are important in clinical management of screen‐detected nodules. Purpose: This study used widely available phantoms and software to identify lung cancer screening CT reconstructions that enable accurate and reproducible nodule size measurements and to match reconstructions across scanner manufacturers and models to provide a consistent image appearance to interpreting physicians. Methods: ACR CT accreditation phantom scans were used to measure the modulation transfer function (MTF) and noise power spectrum (NPS) for various reconstruction kernels for six CT scanner models from three manufacturers. A reference kernel was chosen, and other kernels were matched based on agreement between MTF and NPS for each candidate kernel. Kernels were validated for conformance to the Quantitative Imaging Biomarkers Alliance (QIBA) Small Lung Nodule profile using a commercial phantom and conformance testing software. Results: Medium sharp kernels with similar MTF and NPS curves and QIBA‐compliant imaging performance were identified for the six scanner models. One medium smooth kernel with iterative reconstruction and one common lung kernel did not conform to the QIBA profile. Conclusions: MTF and NPS comparisons to a validated reference CT protocol can be used to identify candidate scanner‐specific reconstructions appropriate for lung cancer screening that conform to the QIBA protocol, thus producing accurate and reproducible nodule size measurements, and that should provide uniform image appearance to the interpreting radiologist.

There is no current authoritative accounting of the number of clinical imaging physicists practicing in the United States. Information about the workforce is needed to inform future efforts to secure training pathways and opportunities. In this study, the AAPM Diagnostic Demand and Supply Projection Working Group collected lists of medical physicists from several state registration and licensure programs and the Conference of Radiation Control Program Directors (CRCPD) registry. By cross‐referencing individuals among these lists, we were able to estimate the current imaging physics workforce in the United States by extrapolating based on population. The imaging physics workforce in the United States in 2019 consisted of approximately 1794 physicists supporting diagnostic X‐ray (1073 board‐certified) and 934 physicists supporting nuclear medicine (460 board‐certified), with a number of individuals practicing in both subfields. There were an estimated 235 physicists supporting nuclear medicine exclusively (150 board‐certified). The estimated total workforce, accounting for overlap, was 2029 medical physicists. These estimates are in approximate agreement with other published studies of segments of the workforce.