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Purpose To validate the SpekPy software toolkit that has been developed to estimate the spectra emitted from tungsten anode X-ray tubes. The model underlying the toolkit introduces improvements upon a well-known semi-empirical model of X-ray emission. Materials and methods Using the same theoretical framework as the widely-used SpekCalc software, new electron penetration data was simulated using the Monte Carlo (MC) method, alternative bremsstrahlung cross-sections were applied, L-line characteristic emissions were included, and improvements to numerical methods implemented. The SpekPy toolkit was developed with the Python programming language. The toolkit was validated against other popular X-ray spectrum models (50 to 120 kVp), X-ray spectra estimated with MC (30 to 150 kVp) as well as reference half value layers (HVL) associated with numerous radiation qualities from standard laboratories (20 to 300 kVp). Results The toolkit can be used to estimate X-ray spectra that agree with other popular X-ray spectrum models for typical configurations in diagnostic radiology as well as with MC spectra over a wider range of conditions. The improvements over SpekCalc are most evident at lower incident electron energies for lightly and moderately filtered radiation qualities. Using the toolkit, estimations of the HVL over a large range of standard radiation qualities closely match reference values. Conclusions A toolkit to estimate X-ray spectra has been developed and extensively validated for central-axis spectra. This toolkit can provide those working in Medical Physics and beyond with a powerful and user-friendly way of estimating spectra from X-ray tubes.

To investigate if the conventional localizer radiograph (LR) can be replaced by a synthetic LR (SLR), generated from a low-dose spiral CT scan, for CT scan planning with minimal changes to current clinical workflows.A dosimetric comparison of SLRs and LRs was made using Monte Carlo methods. Water equivalent diameters (WEDs) of a centered and mis-centered phantom were estimated from low-dose spiral CT scans and LRs acquired at different angles. Body sizes, in the form of two lengths and two diameters obtained from SLRs and LRs, were compared for 10 patients (4 men and 6 women with a mean age of 74.8 and 76.2 years respectively) undergoing CT of thorax and abdomen. The image quality of SLRs for CT scan planning relative to LRs was rated using a 5-grade scale by four radiologists and two CT radiographers.An SLR can be obtained at a comparable effective dose to that of traditionally acquired LRs: 0.14 mSv. WEDs from LRs were more affected by mis-centering than WEDs calculated from low-dose spiral scans. One significant discrepancy of estimated body sizes was observed, the broadest part of the patient that on lateral localizers showed a mean deviation of 17.7 mm (range: 7.3-28.7 mm, p 0.001). The anteroposterior/posteroanterior SLR image quality was assessed as better compared to an LR while the same could not be shown for lateral localizers.SLRs based on low-dose spiral scans can replace LRs for CT planning.

Purpose To investigate two methods of approximating the Modulation Transfer Function (MTF) and Noise Power Spectrum (NPS) in computed tomography (CT) for a range of scan parameters, from limited image acquisitions. Methods The two methods consist of 1) using a linear systems approach to approximate the NPS for different filtered backprojection (FBP) kernels with a filter function derived from the kernel ratio of determined MTFs and 2) using an empirical fitted model to approximate the MTF and NPS. In both cases a scaling function accounts for variations in mAs and kV. The two methods of approximating the MTF/NPS are further investigated by comparing image quality figure of merits (FOM) d′ and AUC calculated using approximations of the MTF/NPS and MTF/NPS that have been determined for different mAs/kV levels and reconstruction kernels. Results The greatest RMSE for NPS approximated for a range of mAs/kVp/convolution kernels using both methods and compared to determined NPS was 0.05 of the peak value. The RMSE for FOM with the kernel ratio method were at most 0.1 for d′ and 0.01 for the AUC. Using the empirical model method, the RMSE for FOM were at most 0.02 for d′ and 0.001 for the AUC. Conclusions The two methods proposed in this paper can provide a convenient way of approximating the MTF and NPS for use in, among other things, mathematical observer studies. Both methods require a relatively small number of direct determinations of NPS from scan acquisitions to model the NPS/MTF for arbitrary mAs and kV.

Purpose One of the major applications of Dual-Energy Computed Tomography (DECT) technology is virtual monochromatic imaging, which are representations of an object as if the source of a CT used single energy photons (keV). The advantages with virtual monochromatic imaging is that the user can manipulate image quality by freely selecting the monochromatic energy. The aim of this work was to study the image quality of virtual monochromatic images generated by two different algorithms, one of which includes a noise-reduction feature (Mono and Mono+). Methods A modified commercial image quality phantom was scanned using a dual-source CT scanner (80/140 Sn kVp). Virtual monochromatic images were generated over a range of 40–170 keV in 10 keV increments using both algorithms. Uniformity, noise, the CT number of water, the CT number of iodine, the contrast-to-noise ratio (CNR) and linearity were evaluated in both image stacks using open-source image processing software. Results In general, the Mono+ images resulted in better image quality. A significant noise reduction was found at low keV using this technique, with a maximum reduction of 50% at 40 keV, compared to the Mono images. The Mono+ images also provided an increased iodine CNR at lower keVs, moving the optimum CNR from 60 keV to 40 keV. Conclusions The Mono+ algorithm for creation of virtual monoenergetic images was shown to be superior to the Mono algorithm, especially for low keVs.

Purpose Automatic Tube Current Modulation (ATCM) adapts the tube current during a CT scan to provide a target image quality throughout the scan as well as for patients of varying sizes. However, the misapplication of ATCM can result in excessive radiation doses or images of non-diagnostic quality. Furthermore, it is not always intuitive to know which scan settings can affect the resulting ATCM and the ATCM functionality between vendors differs. The purpose of this work was to investigate which variable scan settings can impact the ATCM on CT scanners from the four major vendors. Methods The investigation was categorized into scan setting variations in CT localizer radiographs, exposure parameters, reconstruction parameters, and miscentering. A phantom dedicated to ATCM testing was designed and manufactured. A baseline scan was first made by scanning the ATCM phantom using reference scan settings. The ATCM phantom was subsequently scanned by systematically varying the settings in the four categories of setting variations. The scans with varied settings were compared to baseline and evaluated in terms of differences in applied tube current and image noise. The evaluation included both quantitative and qualitive metrics. Results The impact of scan settings on the applied ATCM will differ greatly between vendors, as each vendor has their own unique ATCM implementation. The impact on ATCM can either be apparent or subtle, depending on which scan setting has been varied. Comprehensive tables, corresponding to the different categories of setting variations, has been compiled highlighting the results. 1 . Conclusions A method (including the design of a phantom) has been developed to systematically evaluate how the choice of scan settings can affect the applied ATCM. The methodology was used to investigate the ATCM from four major CT vendors, highlighting similarities and differences among them.

Purpose A new healthcare reform centered around Value-based healthcare has recently been implemented in our region. To pursue this reform, drastic changes have been made to our hospital’s organizational structure and our hospital will serve as a tertiary and quaternary healthcare provider. The Unit of X-ray Physics is therefore in the process of implementing a new operational model to provide relevant Medical Physics support to the new clinical organization at our hospital. Methods To better understand the clinical demand for Medical Physicists, interviews were conducted with Lead Section Radiologists. These interviews indicated that there was a demand for highly specialized Medical Physics support, however the integration between Medical Physicists and the clinic was in many cases unsatisfactory. The operational model at the Unit of X-ray Physics has therefore been structured around Quality-Optimization-Methodology (QOM) groups, providing more continuous and specialized Medical Physics support to the clinic. The QOM groups are multidisciplinary (consisting of Lead Radiologists, Lead Radiographers and Medical Physicists) and they are placed at the intersection of an imaging modality and a clinical sub-specialization to best match with our hospital’s new structure (e.g., Pediatric Computed Tomography). Results The QOM group based operational model, where implemented in the still emerging new clinical structure, enables members of the Unit of X-ray Physics to become highly specialized in one or more combinations of modality and clinical sub-specialization. The new operational model also provides the Unit of X-ray Physics a clear understanding of how resources should be allocated among the identified QOM groups to best meet clinical demands. Conclusions A new operational model centered around QOM groups has been implemented at the Unit of X-ray Physics to provide continuous and specialized Medical Physics support in the new clinical structure at our hospital. In this structure, Medical Physicists become highly specialized on both a modality and clinical sub-specialty level. Furthermore, the new QOM group based operational model provides an important tool when allocating Medical Physics resources in the clinic. The model is planned to be evaluated after being fully implemented and tested.

Purpose Due to the lack of a sufficient CT Protocol Management System (CT-PMS) at our facility, adverse incidents directly affecting patient safety have occurred. The aim of this work is to mitigate adverse incidents in the future and to ensure the quality of our facility’s CT examinations by developing a CT-PMS. Methods A multidisciplinary optimization team (Lead Radiologists, Lead Radiographers, a Medical Physicist specialized in CT and vendor representatives) in direct need of a sufficient CT-PMS to support their clinical efforts initiated this project. Components of a CT-PMS were identified through a literature study as well as a site visit at a facility employing a comprehensive CT-PMS [1] . Sixteen components of a CT-PMS relevant to our facility were identified including team member roles and responsibilities, implementation and review of CT protocols, protocol naming conventions, requirements for documentation as well as dose and image quality management procedures. Where applicable, it is our goal to implement processes and methods in accordance with applicable ISO 9001:2015 clauses [2] . A project manager was recruited to organize the development of the different CT-PMS components. Results Since this is an ongoing project, only a subset of the CT-PMS components has been fully developed. These developed components include team member roles and a process for updating CT scanners with approved protocol changes. However, the completed components of the CT-PMS have been implemented and have already had a positive clinical impact. When fully completed, the CT-PMS is scheduled to be tested and evaluated in a controlled environment (one CT optimization group) before wider roll-out and adoption. Conclusions A comprehensive CT-PMS is needed to manage the quality and safety of CT examinations. As no sufficient CT-PMS existed at our institution, we are in the process of developing one. Although not yet fully developed, we have already started to see a positive clinical impact.