Application of newly developed Fluoro-QC software for image quality evaluation in cardiac X-ray systems. Issue 2 (May 2018)

• Record Type: Journal Article
• Authors: Oliveira, M.; Lopez, G.; Geambastiani, P.; Ubeda, C.
• Is Part Of: Radiography. Volume 24:Issue 2(2018)
• Page Start: e44
• Page End: e47
• Publication Date: 2018-05
• Subjects: Image quality -- Fluoroscopy -- Image metrics -- Quality control; Diagnostic imaging -- Periodicals; Radiotherapy -- Periodicals; Cancer -- Radiotherapy -- Periodicals; Diagnostic Imaging -- Periodicals; Neoplasms -- Periodicals; Radiotherapy -- Periodicals; Imagerie pour le diagnostic -- Périodiques; Radiothérapie -- Périodiques; Cancer -- Radiothérapie -- Périodiques; Electronic journals; 616.0757
• DOI: 10.1016/j.radi.2017.12.006
• Languages: English
• ISSNs: 1078-8174

Abstract

Abstract: Introduction: A quality assurance (QA) program is a valuable tool for the continuous production of optimal quality images. The aim of this paper is to assess a newly developed automatic computer software for image quality (IR) evaluation in fluoroscopy X-ray systems. Methods: Test object images were acquired using one fluoroscopy system, Siemens Axiom Artis model (Siemens AG, Medical Solutions Erlangen, Germany). The software was developed as an ImageJ plugin. Two image quality parameters were assessed: high-contrast spatial resolution (HCSR) and signal-to-noise ratio (SNR). The time between manual and automatic image quality assessment procedures were compared. The paired t-test was used to assess the data. p Values of less than 0.05 were considered significant. Results: The Fluoro-QC software generated faster IQ evaluation results (mean = 0.31 ± 0.08 min) than manual procedure (mean = 4.68 ± 0.09 min). The mean difference between techniques was 4.36 min. Discrepancies were identified in the region of interest (ROI) areas drawn manually with evidence of user dependence. The new software presented the results of two tests (HCSR = 3.06, SNR = 5.17) and also collected information from the DICOM header. Significant differences were not identified between manual and automatic measures of SNR (p value = 0.22) and HCRS (p value = 0.46). Conclusion: The Fluoro-QC software is a feasible, fast and free to use method for evaluating imaging quality parameters on fluoroscopy systems. Highlights: A low cost and reproducible method for fluoroscopy QC is proposed. Performance of automatic tests is faster than manual. Hospitals and clinics will be able to investigate image degradation over time using the new computer software.