Effect of Model-Based Iterative Reconstruction on Image Quality of Chest Computed Tomography for COVID-19 Pneumonia.

PURPOSE: This study aimed to compare the image quality of chest computed tomography (CT) scans for COVID-19 pneumonia using forward-projected model-based iterative reconstruction solution-LUNG (FIRST-LUNG) with filtered back projection (FBP) and hybrid iterative reconstruction (HIR). METHOD: The CT images of 44 inpatients diagnosed with COVID-19 pneumonia between December 2022 and June 2023 were retrospectively analyzed. The CT images were reconstructed using FBP, HIR, and FIRST-LUNG-MILD/STANDARD/STRONG. The CT values and noise of the lumen of the main trachea and erector spine muscle were measured for each group. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. Subjective evaluations included overall image quality, noise, streak artifact, visualization of normal lung structures, and abnormal CT features. One-way analysis of variance was used to compare the objective and subjective indicators among the five groups. The task-based transfer function was derived for three distinct contrasts representing anatomical structures, lower-contrast lesion, and higher-contrast lesion. RESULTS: The results of the study demonstrated significant differences in image noise, SNR, and CNR among the five groups (P < 0.001). The FBP images exhibited the highest levels of noise and the lowest SNR and CNR among the five groups (P < 0.001). When compared to the FBP and HIR groups, the noise was lower in the FIRST-LUNG-MILD/STANDARD/STRONG group, while the SNR and CNR were higher (P < 0.001). The subjective overall image quality score of FIRST-LUNG-MILD/STANDARD was significantly better than FBP and FIRST-LUNG-STRONG (P < 0.001). FIRST-LUNG-MILD was superior to FBP, HIR, FIRST-LUNG-STANDARD, and FIRST-LUNG-STRONG in visualizing proximal and peripheral bronchovascular and subpleural vessels (P < 0.05). Additionally, FIRST-LUNG-MILD achieved the best scores in evaluating abnormal lung structure (P < 0.001). The overall interobserver agreement was substantial (intraclass correlation coefficient = 0.891). The task-based transfer function 50% values of FIRST reconstructions are consistently higher compared to FBP and HIR. CONCLUSIONS: The FIRST-LUNG-MILD/STANDARD algorithm can enhance the image quality of chest CT in patients with COVID-19 pneumonia, while preserving important details of the lesions, better than the FBP and HIR algorithms. After evaluating various COVID-19 pneumonia lesions and considering the improvement in image quality, we recommend using the FIRST-LUNG-MILD reconstruction for diagnosing COVID-19 pneumonia.

Glia maturation factor beta deficiency protects against diabetic osteoporosis by suppressing osteoclast hyperactivity.

Excessive osteoclast activation, which depends on dramatic changes in actin dynamics, causes osteoporosis (OP). The molecular mechanism of osteoclast activation in OP related to type 1 diabetes (T1D) remains unclear. Glia maturation factor beta (GMFB) is considered a growth and differentiation factor for both glia and neurons. Here, we demonstrated that Gmfb deficiency effectively ameliorated the phenotype of T1D-OP in rats by inhibiting osteoclast hyperactivity. In vitro assays showed that GMFB participated in osteoclast activation rather than proliferation. Gmfb deficiency did not affect osteoclast sealing zone (SZ) formation but effectively decreased the SZ area by decreasing actin depolymerization. When GMFB was overexpressed in Gmfb-deficient osteoclasts, the size of the SZ area was enlarged in a dose-dependent manner. Moreover, decreased actin depolymerization led to a decrease in nuclear G-actin, which activated MKL1/SRF-dependent gene transcription. We found that pro-osteoclastogenic factors (Mmp9 and Mmp14) were downregulated, while anti-osteoclastogenic factors (Cftr and Fhl2) were upregulated in Gmfb KO osteoclasts. A GMFB inhibitor, DS-30, targeting the binding site of GMFB and Arp2/3, was obtained. Biocore analysis revealed a high affinity between DS-30 and GMFB in a dose-dependent manner. As expected, DS-30 strongly suppressed osteoclast hyperactivity in vivo and in vitro. In conclusion, our work identified a new therapeutic strategy for T1D-OP treatment. The discovery of GMFB inhibitors will contribute to translational research on T1D-OP.

An Exploratory Study on the Stable Radiomics Features of Metastatic Small Pulmonary Nodules in Colorectal Cancer Patients.

OBJECTIVES: To identify the relatively invariable radiomics features as essential characteristics during the growth process of metastatic pulmonary nodules with a diameter of 1 cm or smaller from colorectal cancer (CRC). METHODS: Three hundred and twenty lung nodules were enrolled in this study (200 CRC metastatic nodules in the training cohort, 60 benign nodules in the verification cohort 1, 60 CRC metastatic nodules in the verification cohort 2). All the nodules were divided into four groups according to the maximum diameter: 0 to 0.25 cm, 0.26 to 0.50 cm, 0.51 to 0.75 cm, 0.76 to 1.0 cm. These pulmonary nodules were manually outlined in computed tomography (CT) images with ITK-SNAP software, and 1724 radiomics features were extracted. Kruskal-Wallis test was performed to compare the four different levels of nodules. Cross-validation was used to verify the results. The Spearman rank correlation coefficient is calculated to evaluate the correlation between features. RESULTS: In training cohort, 90 features remained stable during the growth process of metastasis nodules. In verification cohort 1, 293 features remained stable during the growth process of benign nodules. In verification cohort 2, 118 features remained stable during the growth process of metastasis nodules. It is concluded that 20 features remained stable in metastatic nodules (training cohort and verification cohort 2) but not stable in benign nodules (verification cohort 1). Through the cross-validation (n=100), 11 features remained stable more than 90 times. CONCLUSIONS: This study suggests that a small number of radiomics features from CRC metastatic pulmonary nodules remain relatively stable from small to large, and they do not remain stable in benign nodules. These stable features may reflect the essential characteristics of metastatic nodules and become a valuable point for identifying metastatic pulmonary nodules from benign nodules.