Influence of CT Image Matrix Size and Kernel Type on the Assessment of HRCT in Patients with SSC-ILD

Abstract

Background: Interstitial lung disease (ILD) is a frequent complication of systemic sclerosis (SSc), and its early detection and treatment may prevent deterioration of lung function. Different vendors have recently made larger image matrices available as a post-processing option for computed tomography (CT), which could facilitate the diagnosis of SSc-ILD. Therefore, the objective of this study was to assess the effect of matrix size on lung image quality in patients with SSc by comparing a 1024-pixel matrix to a standard 512-pixel matrix and applying different reconstruction kernels. Methods: Lung scans of 50 patients (mean age 54 years, range 23–85 years) with SSc were reconstructed with these two different matrix sizes, after determining the most appropriate kernel in a first step. Four observers scored the images on a five-point Likert scale regarding image quality and detectability of clinically relevant findings. Results: Among the eight tested kernels, the Br59-kernel (sharp) reached the highest score (19.48 ± 3.99), although differences did not reach statistical significance. The 1024-pixel matrix scored higher than the 512-pixel matrix HRCT overall (p = 0.01) and in the subcategories sharpness (p < 0.01), depiction of bronchiole (p < 0.01) and overall image impression (p < 0.01), and lower for the detection of ground-glass opacities (GGO) (p = 0.04). No significant differences were found for detection of extent of reticulations/bronchiectasis/fibrosis (p = 0.50) and image noise (p = 0.09). Conclusions: Our results show that with the use of a sharp kernel, the 1024-pixel matrix HRCT, provides a slightly better subjective image quality in terms of assessing interstitial lung changes, whereby GGO are more visible on the 512-pixel matrix. However, it remains to be answered to what extent this is related to the improved representation of the smallest structures.

Assessment of Image Quality in Chest CT With Precision Matrix and Increased Framing Rate Using Single Source CT: A Phantom Study

“…At a given number of pixels, the volumetric image pixel is increasing with larger fields of view (3). If the kernel is sufficiently hard and the FOV is large enough, the volumetric image pixel will be smaller with a higher matrix which results in a visually sharper image but also increases the image noise (19). The effect of increasing image noise in larger image matrices has been evaluated before (20).…”

“…We used vendor given recommendations to harmonize the kernels used and to correlate the same sharpness of kernels available. Effects on image quality as given by closely adjacent kernel variance have shown to have minor effects on objective assessments (19).…”

Utility of fluorescence-guided biopsy in suspected lung cancer patients with bronchial mucosal lesions

“…Routine imaging examinations, such as chest X-ray (CXR) and chest tomography (CT), are useful for lung cancer diagnosis, as they can nip malignancy in the bud by prompting a timely surgical procedure [6][7] .…”

“…Lung cancer is a substantial challenge; it has high incidence and mortality rates, and it accounted for 12 to 13% of new cancer cases and approximately 22% of cancer-related deaths in the United States in 2021 [1] . Methods for diagnosing lung cancer have progressed due to medical research [2][3][4][5][6][7][8][9][10] .…”