• Title/Summary/Keyword: enhanced degradation

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Usefulness of Deep Learning Image Reconstruction in Pediatric Chest CT (소아 흉부 CT 검사 시 딥러닝 영상 재구성의 유용성)

  • Do-Hun Kim;Hyo-Yeong Lee
    • Journal of the Korean Society of Radiology
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    • v.17 no.3
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    • pp.297-303
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    • 2023
  • Pediatric Computed Tomography (CT) examinations can often result in exam failures or the need for frequent retests due to the difficulty of cooperation from young patients. Deep Learning Image Reconstruction (DLIR) methods offer the potential to obtain diagnostically valuable images while reducing the retest rate in CT examinations of pediatric patients with high radiation sensitivity. In this study, we investigated the possibility of applying DLIR to reduce artifacts caused by respiration or motion and obtain clinically useful images in pediatric chest CT examinations. Retrospective analysis was conducted on chest CT examination data of 43 children under the age of 7 from P Hospital in Gyeongsangnam-do. The images reconstructed using Filtered Back Projection (FBP), Adaptive Statistical Iterative Reconstruction (ASIR-50), and the deep learning algorithm TrueFidelity-Middle (TF-M) were compared. Regions of interest (ROI) were drawn on the right ascending aorta (AA) and back muscle (BM) in contrast-enhanced chest images, and noise (standard deviation, SD) was measured using Hounsfield units (HU) in each image. Statistical analysis was performed using SPSS (ver. 22.0), analyzing the mean values of the three measurements with one-way analysis of variance (ANOVA). The results showed that the SD values for AA were FBP=25.65±3.75, ASIR-50=19.08±3.93, and TF-M=17.05±4.45 (F=66.72, p=0.00), while the SD values for BM were FBP=26.64±3.81, ASIR-50=19.19±3.37, and TF-M=19.87±4.25 (F=49.54, p=0.00). Post-hoc tests revealed significant differences among the three groups. DLIR using TF-M demonstrated significantly lower noise values compared to conventional reconstruction methods. Therefore, the application of the deep learning algorithm TrueFidelity-Middle (TF-M) is expected to be clinically valuable in pediatric chest CT examinations by reducing the degradation of image quality caused by respiration or motion.

The Effects of Proinflammatory Cytokines and TGF-beta, on The Fibroblast Proliferation (Proinflammatory Cytokines과 TGF-beta가 섬유모세포의 증식에 미치는 영향)

  • Kim, Chul;Park, Choon-Sik;Kim, Mi-Ho;Chang, Hun-Soo;Chung, Il-Yup;Ki, Shin-Young;Uh, Soo-Taek;Moon, Seung-Hyuk;Kim, Yong-Hoon;Lee, Hi-Bal
    • Tuberculosis and Respiratory Diseases
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    • v.45 no.4
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    • pp.861-869
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    • 1998
  • Backgrounds: The injury of a tissue results in the infalmmation, and the imflammed tissue is replaced by the normal parenchymal cells during the process of repair. But, constitutional or repetitive damage of a tissue causes the deposition of collagen resulting in the loss of its function. These lesions are found in the lung of patients with idiopathic pulmonary fibrosis, complicated fibrosis after diffuse alveolar damage (DAD) and inorganic dust-induced lung fibrosis. The tissue from lungs of patients undergoing episodes of active and/or end-stage pulmonary fibrosis shows the accumulation of inflammatory cells, such as mononuclear cells, neutrophils, mast cells and eosinophils, and fibroblast hyperplasia. In this regard, it appears that the inflammation triggers fibroblast activation and proliferation with enhanced matrix synthesis, stimulated by inflammatory mediators such as interleukin-1 (IL-1) and/or tumor necrosis factor (TNF). It has been well known that TGF-$\beta$ enhance the proliferation of fibroblasts and the production of collagen and fibronectin, and inhibit the degradation of collagen. In this regard, It is likely that TGF-$\beta$ undergoes important roles in the pathogenesis of pulmonary fibrosis. Nevertheless, this single cytokine is not the sole regulator of the pulmonary fibrotic response. It is likely that the balance of many cytokines including TGF-$\beta$, IL-1, IL-6 and TNF-$\alpha$ regulates the pathogenesis of pulmonary fibrosis. In this study, we investigate the interaction of TGF-$\beta$, IL-1$\beta$, IL-6 and TNF-$\alpha$ and their effect on the proliferation of fibroblasts. Methods: We used a human fibroblast cell line, MRC-5 (ATCC). The culture of MRC-5 was confirmed by immunofluorecent staining. First, we determined the concentration of serum in cuture medium, in which the proliferation of MRC-5 is supressed but the survival of MRC-5 is retained. Second, we measured optical density after staining the cytokine-stimulated cells with 0.5% naphthol blue black in order to detect the effect of cytokines on the proliferation of MRC-5. Result: In the medium containing 0.5% fetal calf serum, the proliferation of MRC-5 increased by 50%, and it was maintained for 6 days. IL-1$\beta$, TNF-$\alpha$ and IL-6 induced the proliferation of MRC-5 by 45%, 160% and 120%, respectively. IL-1$\beta$ and TNF-$\alpha$ enhanced TGF-$\beta$-induced proliferation of MRC-5 by 64% and 159%, but IL-6 did not affect the TGF-$\beta$-induced proliferation. And lNF-$\alpha$-induced proliferation of MRC-5 was reduced by IL-1$\beta$ in 50%. TGF-$\beta$, TNF-$\alpha$ and both induced the proliferation of MRC-5 to 89%, 135% and 222%, respectively. Conclusions: TNF-$\alpha$, TGF-$\beta$ and IL-1$\beta$, in the order of the effectiveness, showed the induction of MRC-5 proliferation of MRC-5. TNF-$\alpha$ and IL-1$\beta$ enhance the TGF-$\beta$-induced proliferation of MRC-5, but IL-6 did not have any effect TNF-$\alpha$-induced proliferation of MRC-5 is diminished by IL-1, and TNF-$\alpha$ and TGF-$\beta$ showed a additive effect.

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