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A Pilot Study to Estimate the Impact of High Matrix Image Reconstruction on Chest Computed Tomography

Akitoshi Inoue, , Benjamin A. Voss, Yong S. Lee, Shuai Leng, Chi Wan Koo, Brian D. McCollough, Jayse M. Weaver, Hao Gong, Rickey E. Carter,
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Published: 30 September 2021

Abstract: Objectives: The objectives of the study were to estimate the impact of high matrix image reconstruction on chest computed tomography (CT) compared to standard image reconstruction. Material and Methods: This retrospective study included patients with interstitial or parenchymal lung disease, airway disease, and pulmonary nodules who underwent chest CT. Chest CT images were reconstructed using high matrix (1024 × 1024) or standard matrix (512 × 512), with all other parameters matched. Two radiologists, blinded to reconstruction technique, independently examined each lung, viewing image sets side by side and rating the conspicuity of imaging findings using a 5-point relative conspicuity scale. The presence of pulmonary nodules and confidence in classification of internal attenuation was also graded. Overall image quality and subjective noise/artifacts were assessed. Results: Thirty-four patients with 68 lungs were evaluated. Relative conspicuity scores were significantly higher using high matrix image reconstruction for all imaging findings indicative of idiopathic lung fibrosis (peripheral airway visualization, interlobular septal thickening, intralobular reticular opacity, and end-stage fibrotic change; P ≤ 0.001) along with emphysema, mosaic attenuation, and fourth order bronchi for both readers (P ≤ 0.001). High matrix reconstruction did not improve confidence in the presence or classification of internal nodule attenuation for either reader. Overall image quality was increased but not subjective noise/artifacts with high matrix image reconstruction for both readers (P < 0.001). Conclusion: High matrix image reconstruction significantly improves the conspicuity of imaging findings reflecting interstitial lung disease and may be useful for diagnosis or treatment response assessment.
Keywords: high matrix / image reconstruction / matrix image / readers / subjective noise/artifacts / image quality / using high

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