75% radiation dose reduction using deep learning reconstruction on low-dose chest CT.

OBJECTIVE: Few studies have explored the clinical feasibility of using deep-learning reconstruction to reduce the radiation dose of CT. We aimed to compare the image quality and lung nodule detectability between chest CT using a quarter of the low dose (QLD) reconstructed with vendor-agnostic deep-learning image reconstruction (DLIR) and conventional low-dose (LD) CT reconstructed with iterative reconstruction (IR). MATERIALS AND METHODS: We retrospectively collected 100 patients (median age, 61 years [IQR, 53-70 years]) who received LDCT using a dual-source scanner, where total radiation was split into a 1:3 ratio. QLD CT was generated using a quarter dose and reconstructed with DLIR (QLD-DLIR), while LDCT images were generated using a full dose and reconstructed with IR (LD-IR). Three thoracic radiologists reviewed subjective noise, spatial resolution, and overall image quality, and image noise was measured in five areas. The radiologists were also asked to detect all Lung-RADS category 3 or 4 nodules, and their performance was evaluated using area under the jackknife free-response receiver operating characteristic curve (AUFROC). RESULTS: The median effective dose was 0.16 (IQR, 0.14-0.18) mSv for QLD CT and 0.65 (IQR, 0.57-0.71) mSv for LDCT. The radiologists' evaluations showed no significant differences in subjective noise (QLD-DLIR vs. LD-IR, lung-window setting; 3.23 ± 0.19 vs. 3.27 ± 0.22; P = .11), spatial resolution (3.14 ± 0.28 vs. 3.16 ± 0.27; P = .12), and overall image quality (3.14 ± 0.21 vs. 3.17 ± 0.17; P = .15). QLD-DLIR demonstrated lower measured noise than LD-IR in most areas (P < .001 for all). No significant difference was found between QLD-DLIR and LD-IR for the sensitivity (76.4% vs. 72.2%; P = .35) or the AUFROCs (0.77 vs. 0.78; P = .68) in detecting Lung-RADS category 3 or 4 nodules. Under a noninferiority limit of -0.1, QLD-DLIR showed noninferior detection performance (95% CI for AUFROC difference, -0.04 to 0.06). CONCLUSION: QLD-DLIR images showed comparable image quality and noninferior nodule detectability relative to LD-IR images.

Assessment of the Suitability of the Fleischner Society Imaging Guidelines in Evaluating Chest Radiographs of COVID-19 Patients.

BACKGROUND: The Fleischner Society established consensus guidelines for imaging in patients with coronavirus disease 2019 (COVID-19). We investigated the prevalence of pneumonia and the adverse outcomes by dividing groups according to the symptoms and risk factors of patients and assessed the suitability of the Fleischner society imaging guidelines in evaluating chest radiographs of COVID-19 patients. METHODS: From February 2020 to May 2020, 685 patients (204 males, mean 58 ± 17.9 years) who were diagnosed with COVID-19 and hospitalized were included. We divided patients into four groups according to the severity of symptoms and presence of risk factors (age > 65 years and presence of comorbidities). The patient groups were defined as follows: group 1 (asymptomatic patients), group 2 (patients with mild symptoms without risk factors), group 3 (patients with mild symptoms and risk factors), and group 4 (patients with moderate to severe symptoms). According to the Fleischner society, chest imaging is not indicated for groups 1-2 but is indicated for groups 3-4. We compared the prevalence and score of pneumonia on chest radiographs and compare the adverse outcomes (progress to severe pneumonia, intensive care unit admission, and death) between groups. RESULTS: Among the 685 COVID-19 patients, 138 (20.1%), 396 (57.8%), 102 (14.9%), and 49 (7.1%) patients corresponded to groups 1 to 4, respectively. Patients in groups 3-4 were significantly older and showed significantly higher prevalence rates of pneumonia (group 1-4: 37.7%, 51.3%, 71.6%, and 98%, respectively, P < 0.001) than those in groups 1-2. Adverse outcomes were also higher in groups 3-4 than in groups 1-2 (group 1-4: 8.0%, 3.5%, 6.9%, and 51%, respectively, P < 0.001). Patients with adverse outcomes in group 1 were initially asymptomatic but symptoms developed during follow-up. They were older (mean age, 80 years) and most of them had comorbidities (81.8%). Consistently asymptomatic patients had no adverse events. CONCLUSION: The prevalence of pneumonia and adverse outcomes were different according to the symptoms and risk factors in COVID-19 patients. Therefore, as the Fleischner Society recommended, evaluation and monitoring of COVID-19 pneumonia using chest radiographs is necessary for old symptomatic patients with comorbidities.

Development and validation of a deep learning algorithm detecting 10 common abnormalities on chest radiographs.

We aimed to develop a deep learning algorithm detecting 10 common abnormalities (DLAD-10) on chest radiographs, and to evaluate its impact in diagnostic accuracy, timeliness of reporting and workflow efficacy.DLAD-10 was trained with 146 717 radiographs from 108 053 patients using a ResNet34-based neural network with lesion-specific channels for 10 common radiological abnormalities (pneumothorax, mediastinal widening, pneumoperitoneum, nodule/mass, consolidation, pleural effusion, linear atelectasis, fibrosis, calcification and cardiomegaly). For external validation, the performance of DLAD-10 on a same-day computed tomography (CT)-confirmed dataset (normal:abnormal 53:147) and an open-source dataset (PadChest; normal:abnormal 339:334) was compared with that of three radiologists. Separate simulated reading tests were conducted on another dataset adjusted to real-world disease prevalence in the emergency department, consisting of four critical, 52 urgent and 146 nonurgent cases. Six radiologists participated in the simulated reading sessions with and without DLAD-10.DLAD-10 exhibited area under the receiver operating characteristic curve values of 0.895-1.00 in the CT-confirmed dataset and 0.913-0.997 in the PadChest dataset. DLAD-10 correctly classified significantly more critical abnormalities (95.0% (57/60)) than pooled radiologists (84.4% (152/180); p=0.01). In simulated reading tests for emergency department patients, pooled readers detected significantly more critical (70.8% (17/24) versus 29.2% (7/24); p=0.006) and urgent (82.7% (258/312) versus 78.2% (244/312); p=0.04) abnormalities when aided by DLAD-10. DLAD-10 assistance shortened the mean±sd time-to-report critical and urgent radiographs (640.5±466.3 versus 3371.0±1352.5 s and 1840.3±1141.1 versus 2127.1±1468.2 s, respectively; all p<0.01) and reduced the mean±sd interpretation time (20.5±22.8 versus 23.5±23.7 s; p<0.001).DLAD-10 showed excellent performance, improving radiologists' performance and shortening the reporting time for critical and urgent cases.

Deep learning reconstruction for contrast-enhanced CT of the upper abdomen: similar image quality with lower radiation dose in direct comparison with iterative reconstruction.

OBJECTIVE: To evaluate the effect of a commercial deep learning algorithm on the image quality of chest CT, focusing on the upper abdomen. METHODS: One hundred consecutive patients who simultaneously underwent contrast-enhanced chest and abdominal CT were collected. The radiation dose was optimized for each scan (mean CTDIvol: chest CT, 3.19 ± 1.53 mGy; abdominal CT, 7.10 ± 1.88 mGy). Three image sets were collected: chest CT reconstructed with an adaptive statistical iterative reconstruction (ASiR-CHT; 50% blending), chest CT with a deep learning algorithm (DLIR-CHT), and abdominal CT with ASiR (ASiR-ABD; 40% blending). Afterwards, the images covering the upper abdomen were extracted, and image noise, the signal-to-noise ratio (SNR), and the contrast-to-noise ratio (CNR) were measured. For subjective evaluation, three radiologists independently assessed noise, spatial resolution, presence of artifacts, and overall image quality. Additionally, readers selected the most preferable reconstruction technique among three image sets for each case. RESULTS: The average measured noise for DLIR-CHT, ASiR-CHT, and ASiR-ABD was 8.01 ± 2.81, 14.8 ± 2.56, and 12.3 ± 2.28, respectively (p < .001). Deep learning-based image reconstruction (DLIR) also showed the best SNR and CNR (p < .001). However, in the subjective analysis, ASiR-ABD showed less subjective noise than DLIR (2.94 ± 0.23 vs. 2.87 ± 0.26; p < .001), while DLIR showed better spatial resolution (2.60 ± 0.34 vs. 2.44 ± 0.31; p = .02). ASiR-ABD showed a better overall image quality (p = .001), but two of the three readers preferred DLIR more frequently. CONCLUSION: With < 50% of the radiation dose, DLIR chest CT showed comparable image quality in the upper abdomen to that of dedicated abdominal CT and was preferred by most readers. KEY POINTS: • With < 50% radiation dose, a deep learning algorithm applied to contrast-enhanced chest CT exhibited better image noise and signal-to-noise ratio than standard abdominal CT with the ASiR technique. • Pooled readers mostly preferred deep learning algorithm-reconstructed contrast-enhanced chest CT reconstructed using a standard ASiR-reconstructed abdominal CT. • Reconstruction algorithm-induced distortion artifacts were more frequently observed on deep learning algorithm-reconstructed images, but diagnostic difficulty was reported in only 0.3% of cases.

Cryptotympana pustulata Extract and Its Main Active Component, Oleic Acid, Inhibit Ovalbumin-Induced Allergic Airway Inflammation through Inhibition of Th2/GATA-3 and Interleukin-17/RORγt Signaling Pathways in Asthmatic Mice.

Cicadae Periostracum (CP), derived from the slough of Cryptotympana pustulata, has been used as traditional medicine in Korea and China because of its diaphoretic, antipyretic, anti-inflammatory, antioxidant, and antianaphylactic activities. The major bioactive compounds include oleic acid (OA), palmitic acid, and linoleic acid. However, the precise therapeutic mechanisms underlying its action in asthma remain unclear. The objective of this study was to determine the antiasthmatic effects of CP in an ovalbumin (OVA)-induced asthmatic mouse model. CP and OA inhibited the inflammatory cell infiltration, airway hyperresponsiveness (AHR), and production of interleukin (IL)7 and Th2 cytokines (IL-5) in the bronchoalveolar lavage fluid and OVA-specific imunoglobin E (IgE) in the serum. The gene expression of IL-5, IL-13, CCR3, MUC5AC, and COX-2 was attenuated in lung tissues. CP and OA might inhibit the nuclear translocation of GATA-binding protein 3 (GATA-3) and retinoic acid receptor-related orphan receptor γt (RORγt) via the upregulation of forkhead box p3 (Foxp3), thereby preventing the activation of GATA-3 and RORγt. In the in vitro experiment, a similar result was observed for Th2 and GATA-3. These results suggest that CP has the potential for the treatment of asthma via the inhibition of the GATA-3/Th2 and IL-17/RORγt signaling pathways.

Growth and Clinical Impact of 6-mm or Larger Subsolid Nodules after 5 Years of Stability at Chest CT.

Background It remains unclear whether 5 years of stability is sufficient to establish the benign behavior of subsolid nodules (SSNs) of the lung. There are no guidelines for the length of follow-up needed for these SSNs. Purpose To investigate the incidence of interval growth of pulmonary SSNs 6 mm or greater in diameter after 5 years of stability and their clinical outcome. Materials and Methods This retrospective study assessed SSNs 6 mm or greater that were stable for 5 years after detection (January 2002 to December 2018). The incidence of interval growth after 5 years of stability and the clinical and radiologic features of these SSNs were investigated. Clinical stage shifts of growing SSNs, presence of metastasis, and overall survival were assessed during the follow-up period. Subgroup analysis was performed in patients with nonenhanced thin-section (section thickness ≤1.5 mm) CT for interval growth after 5 years of stability. Results A total of 235 SSNs in 235 patients (mean age, 64 years ± 10 [standard deviation]; 132 women) were evaluated. There were 212 pure ground-glass nodules and 24 part-solid nodules. During follow-up (median, 112 months; range, 84-208 months), five of the 235 SSNs (2%; three primary ground-glass nodules and two part-solid nodules) showed interval growth. Three of these five growing SSNs were 10 mm or greater. Three of the five SSNs with interval growth had clinical stage shifts after growth (from Tis [in situ] to T1mi [minimally invasive] in one lesion; from T1mi to T1a in two lesions). There were no deaths or metastases from lung cancer during follow-up. Of 160 SSNs imaged with section thickness of 1.5 mm or less, two (1%) grew; both lesions were 10 mm or greater. Conclusion Only 2% of subsolid pulmonary nodules greater than or equal to 6 mm that had been stable for 5 years showed subsequent growth. At median follow-up of 9 years (after the initial 5-year period of stability), growth of those lung nodules had no clinical effect. © RSNA, 2020 See also the editorial by Naidich and Azour in this issue.

Deep learning algorithm for surveillance of pneumothorax after lung biopsy: a multicenter diagnostic cohort study.

OBJECTIVES: Pneumothorax is the most common and potentially life-threatening complication arising from percutaneous lung biopsy. We evaluated the performance of a deep learning algorithm for detection of post-biopsy pneumothorax in chest radiographs (CRs), in consecutive cohorts reflecting actual clinical situation. METHODS: We retrospectively included post-biopsy CRs of 1757 consecutive patients (1055 men, 702 women; mean age of 65.1 years) undergoing percutaneous lung biopsies from three institutions. A commercially available deep learning algorithm analyzed each CR to identify pneumothorax. We compared the performance of the algorithm with that of radiology reports made in the actual clinical practice. We also conducted a reader study, in which the performance of the algorithm was compared with those of four radiologists. Performances of the algorithm and radiologists were evaluated by area under receiver operating characteristic curves (AUROCs), sensitivity, and specificity, with reference standards defined by thoracic radiologists. RESULTS: Pneumothorax occurred in 17.5% (308/1757) of cases, out of which 16.6% (51/308) required catheter drainage. The AUROC, sensitivity, and specificity of the algorithm were 0.937, 70.5%, and 97.7%, respectively, for identification of pneumothorax. The algorithm exhibited higher sensitivity (70.2% vs. 55.5%, p < 0.001) and lower specificity (97.7% vs. 99.8%, p < 0.001), compared with those of radiology reports. In the reader study, the algorithm exhibited lower sensitivity (77.3% vs. 81.8-97.7%) and higher specificity (97.6% vs. 81.7-96.0%) than the radiologists. CONCLUSION: The deep learning algorithm appropriately identified pneumothorax in post-biopsy CRs in consecutive diagnostic cohorts. It may assist in accurate and timely diagnosis of post-biopsy pneumothorax in clinical practice. KEY POINTS: • A deep learning algorithm can identify chest radiographs with post-biopsy pneumothorax in multicenter consecutive cohorts reflecting actual clinical situation. • The deep learning algorithm has a potential role as a surveillance tool for accurate and timely diagnosis of post-biopsy pneumothorax.

The Ethanol Extract of Holotrichia diomphalia Larvae, Containing Fatty acids and Amino acids, Exerts Anti-Asthmatic Effects through Inhibition of the GATA-3/Th2 Signaling Pathway in Asthmatic Mice.

Holotrichia diomphalia larvae (HD), a natural product from an insect resource, possesses many pharmacological properties, including anticoagulant, antitumor, anti-inflammatory, and analgesic activity. The major bioactive ingredients include oleic acid, palmitic acid, palmitoleic acid, linoleic acid, proline, and glutamic acid. Although HD is associated with immunoregulatory activities in allergic diseases, the therapeutic mechanisms of the action of HD in allergic diseases have not been investigated. The aim of this study was to evaluate the anti-asthmatic potential of HD in an ovalbumin (OVA)-induced mouse model of allergic asthma. Moreover, the anti-inflammatory potential of HD was examined to identify a plausible mechanism of action of HD in vitro. HD strongly reduced goblet cell hyperplasia, eosinophil infiltration, and reactive oxygen species (ROS), which reduced airway hyperresponsiveness (AHR), inflammation, and the expression of Th2 cytokines (IL-5 and IL-13) in bronchoalveolar lavage fluid (BALF). The expression of IL-5, IL-4, eotaxin-2, lysyl oxidase-like 2 (loxl2), and GATA-binding protein 3 (GATA-3) was attenuated in the lungs. In an in vitro assay, HD exerted immunomodulatory effects through the suppression of Th2 cytokines (IL-5, IL-13), IL-17, and tumor necrosis factor (TNF)-α production through downregulation of GATA-3 expression in EL-4 T cells. These findings suggest that the anti-asthmatic activity of HD may occur through the suppression of Th2 cytokines and total Immunoglobulin E (IgE) production by inhibition of the GATA-3 transcription pathway. Our results suggest that HD may be a potential alternative therapy, or a novel therapeutic traditional medicine, for the treatment of allergic asthma.

Internal carotid artery agenesis associated with a rare collateral pathway: supraclinoid-supraclinoid anastomosis. A case report.

Internal carotid artery (ICA) agenesis is an infrequent vascular anomaly, less than 0.01% of the population. Here we report a case of internal carotid agenesis with a rare collateral pathway, via supraclinoid ICA anastomosis to the contralateral supraclinoid ICA.

Association between total body muscle percentage and prevalence of non-alcoholic fatty liver disease in Korean adults findings from an 18-year follow-up: a prospective cohort study.

BACKGROUND: This study aimed to elucidate the association between total lean muscle mass and the incidence of non-alcoholic fatty liver disease (NAFLD) in the adult Korean population. METHODS: Utilizing data derived from the 18-year prospective cohort of the Korean Genome and Epidemiology Study, NAFLD was diagnosed via the hepatic steatosis index with an established cutoff value of 36. Lean muscle mass was assessed via bioelectrical impedance analysis and subsequently divided into tertiles. A generalized mixed model with a logit link was employed for repeated measures data analysis, accounting for potential confounders. RESULTS: Analysis encompassed 7,794 participants yielding 49,177 measurements. The findings revealed a markedly increased incidence of NAFLD in the lower tertiles of muscle mass, specifically, tertile 1 (odds ratio [OR], 20.65; 95% confidence interval [CI], 9.66-44.11) and tertile 2 (OR, 4.57; 95% CI, 2.11-9.91), in comparison to tertile 3. Age-dependent decreases in the OR were observed within the tertile 1 group, with ORs of 10.12 at age of 40 years and 4.96 at age of 80 years. Moreover, each 1%-point increment in total muscle mass corresponded with an estimated OR of 0.87 (95% CI, 0.82-0.93) for NAFLD resolution. CONCLUSIONS: The study demonstrates a significant association between total muscle mass and NAFLD prevalence among Korean adults. Given the potential endocrine role of muscle mass in NAFLD pathogenesis, interventions aimed at enhancing muscle mass might serve as an effective public health strategy for mitigating NAFLD prevalence.

[Pulmonary Artery Intimal Sarcoma Involving the Peripheral Pulmonary Artery, Initially Misdiagnosed as Pulmonary Artery Thromboembolism and Vasculitis: A Case Report]. / 폐동맥 í˜ˆì „ìƒ‰ì „ì¦ê³¼ 혈관염으로 오진된 주변부 폐동맥에서 발생한 폐동맥 ë‚´ë§‰ìœ¡ì¢ : 증례 ë³´ê³ .

Pulmonary artery sarcomas are rare, high-grade malignancies, primarily affecting the proximal elastic pulmonary artery and usually manifesting as tumoral impaction on imaging. Due to similar clinical and imaging findings, pulmonary artery sarcomas are frequently misdiagnosed as pulmonary thromboembolism or, occasionally, as vasculitis. Herein, we reported a case of pulmonary artery intimal sarcoma initially misdiagnosed as pulmonary thromboembolism and vasculitis due to its relatively atypical location and morphology, along with a literature review.

CT analysis of thoracolumbar body composition for estimating whole-body composition.

BACKGROUND: To evaluate the correlation between single- and multi-slice cross-sectional thoracolumbar and whole-body compositions. METHODS: We retrospectively included patients who underwent whole-body PET-CT scans from January 2016 to December 2019 at multiple institutions. A priori-developed, deep learning-based commercially available 3D U-Net segmentation provided whole-body 3D reference volumes and 2D areas of muscle, visceral fat, and subcutaneous fat at the upper, middle, and lower endplate of the individual T1-L5 vertebrae. In the derivation set, we analyzed the Pearson correlation coefficients of single-slice and multi-slice averaged 2D areas (waist and T12-L1) with the reference values. We then built prediction models using the top three correlated levels and tested the models in the validation set. RESULTS: The derivation and validation datasets included 203 (mean age 58.2 years; 101 men) and 239 patients (mean age 57.8 years; 80 men). The coefficients were distributed bimodally, with the first peak at T4 (coefficient, 0.78) and the second peak at L2-3 (coefficient 0.90). The top three correlations in the abdominal scan range were found for multi-slice waist averaging (0.92) and single-slice L3 and L2 (0.90, each), while those in the chest scan range were multi-slice T12-L1 averaging (0.89), single-slice L1 (0.89), and T12 (0.86). The model performance at the top three levels for estimating whole-body composition was similar in the derivation and validation datasets. CONCLUSIONS: Single-slice L2-3 (abdominal CT range) and L1 (chest CT range) analysis best correlated with whole-body composition around 0.90 (coefficient). Multi-slice waist averaging provided a slightly higher correlation of 0.92.

Mycobacterial cavity on chest computed tomography: clinical implications and deep learning-based automatic detection with quantification.

Background: This study aimed (I) to investigate the clinical implication of computed tomography (CT) cavity volume in tuberculosis (TB) and non-tuberculous mycobacterial pulmonary disease (NTM-PD), and (II) to develop a three-dimensional (3D) nnU-Net model to automatically detect and quantify cavity volume on CT images. Methods: We retrospectively included conveniently sampled 206 TB and 186 NTM-PD patients in a tertiary referral hospital, who underwent thin-section chest CT scans from 2012 through 2019. TB was microbiologically confirmed, and NTM-PD was diagnosed by 2007 Infectious Diseases Society of America/American Thoracic Society guideline. The reference cavities were semi-automatically segmented on CT images and a 3D nnU-Net model was built with 298 cases (240 cases for training, 20 for tuning, and 38 for internal validation). Receiver operating characteristic curves were used to evaluate the accuracy of the CT cavity volume for two clinically relevant parameters: sputum smear positivity in TB and treatment in NTM-PD. The sensitivity and false-positive rate were calculated to assess the cavity detection of nnU-Net using radiologist-detected cavities as references, and the intraclass correlation coefficient (ICC) between the reference and the U-Net-derived cavity volumes was analyzed. Results: The mean CT cavity volumes in TB and NTM-PD patients were 11.3 and 16.4 cm3, respectively, and were significantly greater in smear-positive TB (P<0.001) and NTM-PD necessitating treatment (P=0.020). The CT cavity volume provided areas under the curve of 0.701 [95% confidence interval (CI): 0.620-0.782] for TB sputum positivity and 0.834 (95% CI: 0.773-0.894) for necessity of NTM-PD treatment. The nnU-Net provided per-patient sensitivity of 100% (19/19) and per-lesion sensitivity of 83.7% (41/49) in the validation dataset, with an average of 0.47 false-positive small cavities per patient (median volume, 0.26 cm3). The mean Dice similarity coefficient between the manually segmented cavities and the U-Net-derived cavities was 78.9. The ICCs between the reference and U-Net-derived volumes were 0.991 (95% CI: 0.983-0.995) and 0.933 (95% CI: 0.897-0.957) on a per-patient and per-lesion basis, respectively. Conclusions: CT cavity volume was associated with sputum positivity in TB and necessity of treatment in NTM-PD. The 3D nnU-Net model could automatically detect and quantify mycobacterial cavities on chest CT, helping assess TB infectivity and initiate NTM-TB treatment.

Anti-Inflammatory Effects of Cicadidae Periostracum Extract and Oleic Acid through Inhibiting Inflammatory Chemokines Using PCR Arrays in LPS-Induced Lung inflammation In Vitro.

In this study, we aimed to evaluate the anti-inflammatory effects and mechanisms of CP and OA treatments in LPS-stimulated lung epithelial cells on overall chemokines and their receptors using PCR arrays. In addition, we aimed to confirm those effects and mechanisms in LPS-stimulated lung macrophages on some chemokines and cytokines. In our study, CP treatments significantly inhibited the inflammatory mediators CCL2, CCL3, CCL4, CCL5, CCL6, CCL9, CCL11, CCL17, CCL20, CXCL1, CXCL2, CXCL3, CXCL5, CXCL7, CXCL10, TNF-α, and IL-6, while markedly suppressing NF-κB p65 nuclear translocation and the phosphorylations of PI3K p55, Akt, Erk1/2, p38, and NF-κB p65 in LPS-stimulated lung epithelial cells. CP treatments also significantly decreased the inflammatory mediators CCL2, CCL5, CCL17, CXCL1, and CXCL2, while markedly inhibiting phospho-PI3K p55 and iNOS expression in LPS-stimulated lung macrophages. Likewise, OA treatments significantly suppressed the inflammatory mediators CCL2, CCL3, CCL4, CCL5, CCL8, CCL11, CXCL1, CXCL3, CXCL5, CXCL7, CXCL10, CCRL2, TNF-α, and IL-6, while markedly reducing the phosphorylations of PI3K p85, PI3K p55, p38, JNK, and NF-κB p65 in LPS-stimulated lung epithelial cells. Finally, OA treatments significantly inhibited the inflammatory mediators CCL2, CCL5, CCL17, CXCL1, CXCL2, TNF-α, and IL-6, while markedly suppressing phospho-PI3K p55, iNOS, and Cox-2 in LPS-stimulated lung macrophages. These results prove that CP and OA treatments have anti-inflammatory effects on the inflammatory chemokines and cytokines by inhibiting pro-inflammatory mediators, including PI3K, Akt, MAPKs, NF-κB, iNOS, and Cox-2. These findings suggest that CP and OA are potential chemokine-based therapeutic substances for treating the lung and airway inflammation seen in allergic disorders.

Study of Infraorbital Foramen Using 3-Dimensional Facial Bone Computed Tomography Scans.

BACKGROUND: Previous studies of variations of the infraorbital foramen (IOF) demonstrated conflicting results regarding to the side and gender in which specific variations occur. Significant differences in some measurement points between genders have been found, whereas, other studies did not report such differences. The presence of an accessory IOF (AIOF) can result in incomplete anesthesia or treatment failure. Previous studies have demonstrated variable results regarding the prevalence of an AIOF ranging from 16.9% to 47.6%. OBJECTIVES: The purpose of this study was to perform a morphological and morphometric study of the IOF and AIOF based on images of 3-dimensional (3D) facial bone computed tomography (CT) scans. STUDY DESIGN: Retrospective study. METHODS: Identification and analysis of patients who have undergone facial bone 3D CT were performed using Clinical Data Warehouse v 2.5 (CDW, Planit Healthcare, Seoul, Korea). The search term that we used with the CDW for analysis was "facial bone 3D CT."First, the region below the infraorbital rim was examined to determine the presence of the IOF and AIOF. Second, the shape of the IOF was determined and categorized as circular or oval. Third, the vertical (VD) and horizontal (HD) diameters of the IOF were determined. Lastly, the distances between important anatomic landmarks and the IOF were measured. RESULTS: A single IOF with a circular shape was most common. The HD and VD of the IOF were significantly larger in men than in women. The distance between the IOF and the infraorbital margin was similar between men and women. The distances measured from the lateral nasal aperture (LNA) to the IOF and the anterior nasal spine (ANS) to the IOF, at both sides, were significantly shorter in women than in men. The prevalence of the AIOF on the right and left side was 7.3% and 8.9%, respectively. The most commonly observed position of the AIOF was on the inferior medial side of the IOF. LIMITATIONS: This study had an imbalance in the number of male and female patients. CONCLUSIONS: The size of the IOF was larger in men than in women. The distance of the IOF from the infraorbital margin was similar for men and women, whereas, the distances between the IOF and the ANS and the IOF and LNA were shorter in women than in men.

Prospective evaluation of thoracic diseases using a compact flat-panel detector spiral computed tomographic scanner.

Objective: To prospectively evaluate the image quality and diagnostic performance of a compact flat-panel detector (FD) scanner for thoracic diseases compared to a clinical CT scanner. Materials and methods: The institutional review board approved this single-center prospective study, and all participants provided informed consent. From December 2020 to May 2021, 30 patients (mean age, 67.1 ± 8.3 years) underwent two same-day low-dose chest CT scans using clinical state-of-art and compact FDCT scanners. Image quality was assessed visually and quantitatively. Two readers evaluated the diagnostic performance for nodules, parenchymal opacifications, bronchiectasis, linear opacities, and pleural abnormalities in 40 paired CT scans. The other 20 paired CT scans were used to examine the agreement of semi-quantitative CT scoring regarding bronchiectasis, bronchiolitis, nodules, airspace consolidations, and cavities. Results: FDCT images had significantly lower visual image quality than clinical CT images (all p < 0.001). The two CT image sets showed no significant differences in signal-to-noise and contrast-to-noise ratios (56.8 ± 12.5 vs. 57.3 ± 15.2; p = 0.985 and 62.9 ± 11.7 vs. 60.7 ± 16.9; p = 0.615). The pooled sensitivity was comparable for nodules, parenchymal opacifications, linear opacities, and pleural abnormalities (p = 0.065-0.625), whereas the sensitivity was significantly lower in FDCT images than in clinical CT images for micronodules (p = 0.007) and bronchiectasis (p = 0.004). The specificity was mostly 1.0. Semi-quantitative CT scores were similar between the CT image sets (p > 0.05), and intraclass correlation coefficients were around 0.950 or higher, except for bronchiectasis (0.869). Conclusion: Compact FDCT images provided lower image quality but comparable diagnostic performance to clinical CT images for nodules, parenchymal opacifications, linear opacities, and pleural abnormalities.

Carnitine Orotate Complex Ameliorates Insulin Resistance and Hepatic Steatosis Through Carnitine Acetyltransferase Pathway.

BACKGROUND: Carnitine orotate complex (Godex) has been shown to decrease glycated hemoglobin levels and improve steatosis in patients with type 2 diabetes mellitus with non-alcoholic fatty liver disease. However, the mechanisms of Godex in glucose metabolism remain unclear. METHODS: Male C57BL/6J mice were divided into four groups: normal-fat diet, high-fat diet, a high-fat diet supplemented with intraperitoneal injection of (500 mg or 2,000 mg/kg/day) Godex for 8 weeks. Computed tomography, indirect calorimetry, and histological analyses including electron microscopy of the liver were performed, and biochemical profiles and oral glucose tolerance test and insulin tolerance test were undertaken. Expressions of genes in the lipid and glucose metabolism, activities of oxidative phosphorylation enzymes, carnitine acetyltransferase, pyruvate dehydrogenase, and acetyl-coenzyme A (CoA)/CoA ratio were evaluated. RESULTS: Godex improved insulin sensitivity and significantly decreased fasting plasma glucose, homeostatic model assessment for insulin resistance, steatosis, and gluconeogenesis, with a marked increase in fatty acid oxidation as well as better use of glucose in high-fat diet-fed mice. It preserved mitochondrial function and ultrastructure, restored oxidative phosphorylation enzyme activities, decreased acetyl-CoA/CoA ratio, and increased carnitine acetyltransferase content and pyruvate dehydrogenase activity. Carnitine acetyltransferase knockdown partially reversed the effects of Godex in liver and in vitro. CONCLUSION: Godex improved insulin resistance and steatosis by regulating carnitine acetyltransferase in liver in high-fat diet-fed mice.

Glucolipotoxicity and GLP-1 secretion.

INTRODUCTION: The concept of glucolipotoxicity refers to the combined, deleterious effects of elevated glucose and/or fatty acid levels. RESEARCH DESIGN AND METHODS: To investigate the effects of chronic glucolipotoxicity on glucagon-like peptide-1-(7-36) amide (GLP-1) secretion, we generated glucolipotoxic conditions in human NCI-H716 enteroendocrine cells using either 5 or 25 mM glucose with or without 500 µM palmitate for 72 hours. For in vivo study, we have established a chronic nutrient infusion model in the rat. Serial blood samples were collected for 2 hours after the consumption of a mixed meal to evaluate insulin sensitivity and ß-cell function. RESULTS: Chronic glucolipotoxic conditions decreased GLP-1 secretion and the expressions of pCREB, pGSK3ß, ß-catenin, and TCF7L2 in NCI-H716 cells. Glucolipotoxicity conditions reduced glucose transporter expression, glucose uptake, and nicotinamide-adenine dinucleotide phosphate (NADPH) levels in L-cells, and increased triglyceride accumulation. In contrast, PPARα and ATP levels were reduced, which correlated well with decreased levels of SUR1 and Kir6.2, cAMP contents and expressions of pCAMK2, EPAC and PKA. We also observed an increase in reactive oxygen species production, UCP2 expression and Complex I activity. Simultaneous treatment with insulin restored the GLP-1 secretion. Glucolipotoxic conditions decreased insulin secretion in a time-dependent manner in INS-1 cells, which was recovered with exendin-4 cotreatment. Glucose and SMOFlipid infusion for 6 hours decreased GLP-1 secretion and proglucagon mRNA levels as well as impaired the glucose tolerance, insulin and C-peptide secretion in rats. CONCLUSION: These results provide evidence for the first time that glucolipotoxicity could affect GLP-1 secretion through changes in glucose and lipid metabolism, gene expressions, and proglucagon biosynthesis and suggest the interrelationship between glucolipotoxicities of L-cells and ß-cells which develops earlier than that of L-cells.

Volume and Mass Doubling Time of Lung Adenocarcinoma according to WHO Histologic Classification.

OBJECTIVE: This study aimed to evaluate the tumor doubling time of invasive lung adenocarcinoma according to the International Association of the Study for Lung Cancer (IASLC)/American Thoracic Society (ATS)/European Respiratory Society (ERS) histologic classification. MATERIALS AND METHODS: Among the 2905 patients with surgically resected lung adenocarcinoma, we retrospectively included 172 patients (mean age, 65.6 ± 9.0 years) who had paired thin-section non-contrast chest computed tomography (CT) scans at least 84 days apart with the same CT parameters, along with 10 patients with squamous cell carcinoma (mean age, 70.9 ± 7.4 years) for comparison. Three-dimensional semiautomatic segmentation of nodules was performed to calculate the volume doubling time (VDT), mass doubling time (MDT), and specific growth rate (SGR) of volume and mass. Multivariate linear regression, one-way analysis of variance, and receiver operating characteristic curve analyses were performed. RESULTS: The median VDT and MDT of lung cancers were as follows: acinar, 603.2 and 639.5 days; lepidic, 1140.6 and 970.1 days; solid/micropapillary, 232.7 and 221.8 days; papillary, 599.0 and 624.3 days; invasive mucinous, 440.7 and 438.2 days; and squamous cell carcinoma, 149.1 and 146.1 days, respectively. The adjusted SGR of volume and mass of the solid-/micropapillary-predominant subtypes were significantly shorter than those of the acinar-, lepidic-, and papillary-predominant subtypes. The histologic subtype was independently associated with tumor doubling time. A VDT of 465.2 days and an MDT of 437.5 days yielded areas under the curve of 0.791 and 0.795, respectively, for distinguishing solid-/micropapillary-predominant subtypes from other subtypes of lung adenocarcinoma. CONCLUSION: The tumor doubling time of invasive lung adenocarcinoma differed according to the IASCL/ATS/ERS histologic classification.

Usefulness of staging chest-CT in patients with operable breast cancer.

OBJECTIVE: The aim of this study was to investigate the usefulness of staging chest-CT in terms of diagnostic yield and false-referral rate in patients with operable breast cancer. MATERIALS AND METHODS: This study was approved by the institutional review border. In this retrospective study, we reviewed patients who underwent staging chest-CT between January 2014 and June 2016. Reference standard was defined as a combination of pathology and radiologic tumor changes in accordance with primary tumor or metastatic lesions and stability during the 12-month follow-up period. We calculated diagnostic yield and false-referral rates stratified by pathologic stage. The important ancillary findings of staging chest-CT were also recorded. RESULTS: A total of 1,342 patients were included in this study. Of these, four patients (0.3%; 4/1342) had true pulmonary metastasis. Diagnostic yields of stage I, II, III disease were 0.0% (0/521), 0.3% (2/693), and 1.6% (2/128), respectively. The overall false-referral rate was 4.6% (62/1342); false-referral rates of stage I, II, and III disease were 5.0% (26/521), 3.8% (26/693), and 7.8% (10/128), respectively. No occult thoracic metastasis occurred within 12 months of staging chest-CT. Nineteen patients showed significant ancillary findings besides lung metastasis, including primary lung cancer (n = 9). The overall diagnostic yield of ancillary findings was 1.7% (23 of 1342). CONCLUSIONS: The incidence of pulmonary metastasis was near zero for pathologic stages I/II and slightly higher (although still low; 1.6%). for stage III. Considering its low diagnostic yield and substantial false-referral rates, staging chest-CT might not be useful in patients with operable breast cancer.