QAMaster: A new software framework for phantom-based computed tomography quality assurance.

The regular evaluation of imaging performance of computed tomography (CT) scanners is essential for CT quality assurance. For automation of this process, the software QAMaster was developed at the Universitätsklinikum Erlangen, which provides based on CT scans of the CatPhan® 504 (The Phantom Laboratory, Salem, USA) automated image quality analysis and documentation by evaluating CT number accuracy, spatial linearity, uniformity, contrast-noise-ratio, spatial resolution, noise, and slice thickness. Dose assessment is supported by calculations of the weighted computed tomography dose index (CTDIw ) and weighted cone beam dose index (CBDIw ). QAMaster was tested with CatPhan® 504 scans and compared to manual evaluations of these scans, whereby high consistency of the respective results was observed. The CT numbers, spatial linearity, uniformity, contrast-noise-ratio, noise, and slice thickness deviated by only (0.13 ± 0.25) HU, (0.02 ± 0.05) mm, (-0.01 ± 0.03)%, 0.8 ± 1.8, (0.131 ± 0.05) HU, and (0.004 ± 0.005) mm between both evaluations, respectively. The QAMaster results for spatial resolution did not differ significantly (p = 0.34) from the CatPhan® 504 based manual resolution assessment. Dose computations were fully consistent between QAMaster and manual calculations. Thus, QAMaster proved to be a comprehensive and functional software for performing an automated CT quality assurance routine. QAMaster will be open-source after its release.

A step closer to automation: kilovoltage and Megavoltage Planar Imaging Quality Assurance, baseline, tolerance and action levels definition and exploration.

PURPOSE: To establish automated quality assurance (QA) procedures for the kilovoltage (kV) and the Megavoltage (MV) imagers of two linear accelerators (LINACS) using a commercial software. METHODS: SNC Machine™ phantoms and software were used and the baseline values, tolerance and action levels for various image quality parameters were defined. Scaling, spatial resolution, contrast, uniformity and noise were considered, explored and evaluated utilizing the appropriate phantoms and the accompanying software. kV and MV planar radiographic images, for 6MV and 10MV beams were obtained for each LINAC. For both kV and MV QA tasks, the baseline values for spatial resolution, contrast, uniformity and noise were defined. RESULTS: Subsequent measurements performed were highly reproducible and within tolerance and action levels, while noise showed variations. The calculated tolerance and action levels for noise were looser compared to the other image quality metrics. CONCLUSIONS: An automated QA workflow of the kV and MV planar radiographic mode of LINAC imagers' was established and appears to be time effective.

A multicentre simulation study of planar whole-body bone scintigraphy in Sweden.

BACKGROUND: Whole-body bone scintigraphy is a clinically useful non-invasive and highly sensitive imaging method enabling detection of metabolic changes at an early stage of disease, often earlier than with conventional radiologic procedures. Bone scintigraphy is one of the most common nuclear medicine methods used worldwide. Therefore, it is important that the examination is implemented and performed in an optimal manner giving the patient added value in the subsequent care process. The aim of this national multicentre survey was to investigate Swedish nuclear medicine departments compliance with European practice guidelines for bone scintigraphy. In addition, the effect of image acquisition parameters on the ability to detect metabolic lesions was investigated. METHODS: Twenty-five hospital sites participated in the study. The SIMIND Monte Carlo (MC) simulation and the XCAT phantom were used to simulate ten fictive patient cases with increased metabolic activity distributed at ten different locations in the skeleton. The intensity of the metabolic activity was set into six different levels. Individual simulations were performed for each site, corresponding to their specific camera system and acquisition parameters. Simulated image data sets were then sent to each site and were visually evaluated in terms of if there was one or several locations with increased metabolic activity relative to normal activity. RESULT: There is a high compliance in Sweden with the EANM guidelines regarding image acquisition parameters for whole-body bone scintigraphy. However, up to 40% of the participating sites acquire lower count density in the images than recommended. Despite this, the image quality was adequate to maintain a stable detection level. None of the hospital sites or individual responders deviated according to the statistical analysis. There is a need for at least 2.5 times metabolic activity compared to normal for a lesion to be detected. CONCLUSION: The imaging process is well harmonized throughout the country and there is a high compliance with the EANM guidelines. There is a need for at least 2.5 times the normal metabolic activity for a lesion to be detected as abnormal.

Informatics Opportunities and Challenges in Medical Imaging: A Journey.

The role of the field of informatics in medical imaging is vital; novel or adapted informatics' core methods can be employed to realise innovative information processing and engineering of medical images. As such, imaging informatics can assist in the interpretation of image-based, clinically recorded evidence. This, in turn, leads to the generation of associated actionable knowledge to achieve precision medicine practice. The discipline of informatics has the power to transform data to useful clinical information patterns of observable evidence and, subsequently to generate actionable knowledge in terms of diagnosis, prognosis, and disease management. This paper presents the author's personal viewpoint and distinct contributions to innovations in the acquisition and collection of imaging data; storage, retrieval, and management of imaging information objects; quantitative analysis, classification, and dissemination of imaging observable evidence.