Evaluation of automatic image quality assessment in chest CT – A human cadaver study. (April 2017)

• Record Type: Journal Article
• Authors: Franck, Caro; De Crop, An; De Roo, Bieke; Smeets, Peter; Vergauwen, Merel; Dewaele, Tom; Van Borsel, Mathias; Achten, Eric; Van Hoof, Tom; Bacher, Klaus
• Is Part Of: Physica medica. Volume 36(2017)
• Page Start: 32
• Page End: 37
• Publication Date: 2017-04
• Subjects: Chest CT -- Image quality -- Automatic IQ assessment -- Human cadaver study; Medical physics -- Periodicals; Biophysics -- Periodicals; Biophysics -- Periodicals; Imagerie médicale -- Périodiques; Radiothérapie -- Périodiques; Rayons X -- Sécurité -- Mesures -- Périodiques; Physique -- Périodiques; Médecine -- Périodiques; 610.153
• DOI: 10.1016/j.ejmp.2017.03.003
• Languages: English
• ISSNs: 1120-1797

Abstract

Highlights: This study uses Thiel cadavers to evaluate automatic IQ assessment in chest CT. Correlations between the IQs algorithm and the physical-technical IQ were high. The IQs algorithm correlates highly with the observed clinical IQ. The IQs values may be stored in a database and used to monitor IQ performance. Abstract: Purpose: The evaluation of clinical image quality (IQ) is important to optimize CT protocols and to keep patient doses as low as reasonably achievable. Considering the significant amount of effort needed for human observer studies, automatic IQ tools are a promising alternative. The purpose of this study was to evaluate automatic IQ assessment in chest CT using Thiel embalmed cadavers. Methods: Chest CT's of Thiel embalmed cadavers were acquired at different exposures. Clinical IQ was determined by performing a visual grading analysis. Physical-technical IQ (noise, contrast-to-noise and contrast-detail) was assessed in a Catphan phantom. Soft and sharp reconstructions were made with filtered back projection and two strengths of iterative reconstruction. In addition to the classical IQ metrics, an automatic algorithm was used to calculate image quality scores (IQs). To be able to compare datasets reconstructed with different kernels, the IQs values were normalized. Results: Good correlations were found between IQs and the measured physical-technical image quality: noise (ρ = −1.00), contrast-to-noise (ρ = 1.00) and contrast-detail (ρ = 0.96). The correlation coefficients between IQs and the observed clinical image quality of soft and sharp reconstructions were 0.88 and 0.93, respectively. Conclusions: The automatic scoring algorithm is a promising tool for the evaluation of thoracic CT scans in daily clinical practice. It allows monitoring of the image quality of a chest protocol over time, without human intervention. Different reconstruction kernels can be compared after normalization of the IQs.