Perioperative urinary ketosis and metabolic acidosis in patients fasted for undergoing gynecologic surgery.

BACKGROUND: Our bodies have adaptive mechanisms to fasting, in which glycogen stored in the liver and muscle protein are broken down, but also lipid mobilisation is triggered. As a result, glycerol and fatty acids are released into the bloodstream, increasing the production of ketone bodies in liver. However, there are limited studies on the incidence of perioperative urinary ketosis, the intraoperative blood glucose changes and metabolic acidosis after fasting for surgery in non-diabetic adult patients. METHODS: We conducted a retrospective cohort study involving 1831 patients undergoing gynecologic surgery under general anesthesia from January to December 2022. Ketosis was assessed using a postoperative urine test, while blood glucose levels and acid-base status were collected from intraoperative arterial blood gas analyses. RESULTS: Of 1535 patients who underwent postoperative urinalysis, 912 (59.4%) patients had ketonuria. Patients with ketonuria were younger, had lower body mass index, and had fewer comorbidities than those without ketonuria. After adjustments, younger age, higher body mass index and surgery starting late afternoon were significant risk factors for postoperative ketonuria. Of the 929 patients assessed with intraoperative arterial blood gas analyses, 29.0% showed metabolic acidosis. Multivariable logistic regression revealed that perioperative ketonuria and prolonged surgery significantly increased the risk for moderate-to-severe metabolic acidosis. CONCLUSION: Perioperative urinary ketosis and intraoperative metabolic acidosis are common in patients undergoing gynecologic surgery, even with short-term preoperative fasting. The risks are notably higher in younger patients with lower body mass index. Optimization of preoperative fasting strategies including implementation of oral carbohydrate loading should be considered for reducing perioperative metabolic derangement due to ketosis.

Study protocol for prospective multi-institutional phase III trial of standard of care therapy with or without stereotactic ablative radiation therapy for recurrent ovarian cancer (SABR-ROC).

BACKGROUND: Efforts have been made to investigate the role of salvage radiotherapy (RT) in treating recurrent ovarian cancer (ROC). Stereotactic ablative radiation therapy (SABR) is a state-of-the-art therapy that uses intensity modulation to increase the fractional dose, decrease the number of fractions, and target tumors with high precision. METHODS: The SABR-ROC trial is a phase 3, multicenter, randomized, prospective study to evaluate whether the addition of SABR to the standard of care significantly improves the 3-year overall survival (OS) of patients with ROC. Patients who have completed the standard treatment for primary epithelial ovarian cancer are eligible. In addition, patients with number of metastases ≤ 10 and maximum diameter of each metastatic site of gross tumor ≤ 5 cm are allowed. Randomization will be stratified by (1) No. of the following clinical factors met, platinum sensitivity, absence of ascites, normal level of CA125, and ECOG performance status of 0-1; 0-3 vs. 4; (2) site of recurrence; with vs. without lymph nodes; and (3) PARP inhibitor; use vs. non-use. The target number of patients to be enrolled in this study is 270. Participants will be randomized in a 1:2 ratio. Participants in Arm 2 will receive SABR for recurrent lesions clearly identified in imaging tests as well as the standard of care (Arm 1) based on treatment guidelines and decisions made in multidisciplinary discussions. The RT fraction number can range from 1 to 10, and the accepted dose range is 16-45 Gy. The RT Quality Assurance (QA) program consists of a three-tiered system: general credentialing, trial-specific credentialing, and individual case reviews. DISCUSSION: SABR appears to be preferable as it does not interfere with the schedule of systemic treatment by minimizing the elapsed days of RT. The synergistic effect between systemic treatment and SABR is expected to reduce the tumor burden by eradicating gross tumors identified through imaging with SABR and controlling microscopic cancer with systemic treatment. It might also be beneficial for quality-of-life preservation in older adults or heavily treated patients. TRIAL REGISTRATION: This trial was registered at ClinicalTrials.gov (NCT05444270) on June 29th, 2022.

Fully Automated MRI Segmentation and Volumetric Measurement of Intracranial Meningioma Using Deep Learning.

BACKGROUND: Accurate and rapid measurement of the MRI volume of meningiomas is essential in clinical practice to determine the growth rate of the tumor. Imperfect automation and disappointing performance for small meningiomas of previous automated volumetric tools limit their use in routine clinical practice. PURPOSE: To develop and validate a computational model for fully automated meningioma segmentation and volume measurement on contrast-enhanced MRI scans using deep learning. STUDY TYPE: Retrospective. POPULATION: A total of 659 intracranial meningioma patients (median age, 59.0 years; interquartile range: 53.0-66.0 years) including 554 women and 105 men. FIELD STRENGTH/SEQUENCE: The 1.0 T, 1.5 T, and 3.0 T; three-dimensional, T1 -weighted gradient-echo imaging with contrast enhancement. ASSESSMENT: The tumors were manually segmented by two neurosurgeons, H.K. and C.-K.P., with 10 and 26 years of clinical experience, respectively, for use as the ground truth. Deep learning models based on U-Net and nnU-Net were trained using 459 subjects and tested for 100 patients from a single institution (internal validation set [IVS]) and 100 patients from other 24 institutions (external validation set [EVS]), respectively. The performance of each model was evaluated with the Sørensen-Dice similarity coefficient (DSC) compared with the ground truth. STATISTICAL TESTS: According to the normality of the data distribution verified by the Shapiro-Wilk test, variables with three or more categories were compared by the Kruskal-Wallis test with Dunn's post hoc analysis. RESULTS: A two-dimensional (2D) nnU-Net showed the highest median DSCs of 0.922 and 0.893 for the IVS and EVS, respectively. The nnU-Nets achieved superior performance in meningioma segmentation than the U-Nets. The DSCs of the 2D nnU-Net for small meningiomas less than 1 cm3 were 0.769 and 0.780 with the IVS and EVS, respectively. DATA CONCLUSION: A fully automated and accurate volumetric measurement tool for meningioma with clinically applicable performance for small meningioma using nnU-Net was developed. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Association between iodine intake and metabolic syndrome in euthyroid adult in an iodine-replete area: a nationwide population-based study.

Metabolic syndrome (MetS) is considered very important because of the increased risk for cardiovascular diseases. Identifying modifiable factors may help prevent MetS. We aimed to investigate the relationship between iodine intake as a dietary factor and MetS in euthyroid adult in an iodine-replete area. A total of 4,277 adult aged ≥19 years from the Korea National Health and Nutrition Examination Survey VI (2013-2015) with urinary iodine concentration (UIC) results and normal thyroid function were included. Participants were grouped according to their iodine nutrition status based on the WHO recommendations and modifications: insufficient (<100 µg/L), adequate (100-299 µg/L), and excessive (≥300 µg/L) iodine intake. We estimated the odds ratios (ORs) for MetS according to the UIC groups using logistic regression models. Of the study participants, 27.2% men and 23.9% women had MetS. Men with excessive iodine intake had a significantly lower risk of elevated triglycerides [OR 0.733, 95% confidence interval (CI) 0.603-0.890, p = 0.010], as compared to those with adequate iodine intake. Women with insufficient iodine intake had a significantly greater risk of elevated blood glucose (OR 1.519, 95% CI 1.011-2.282, p = 0.044), as compared to those with adequate iodine intake. In women, insufficient iodine intake was a significant risk factor for MetS compared to adequate iodine intake, even after adjusting for confounding variables including age, smoking, alcohol consumption, walking activity, serum thyroid-stimulating hormone, free thyroxine, and anti-thyroid peroxidase antibody (OR 1.544, 95% CI 1.031-2.311, p = 0.035). There was no association between iodine intake and risk of MetS in men. In conclusion, insufficient iodine intake was associated with an increased risk of MetS only in euthyroid adult women. Our data support that sex differences may influence the relationship between iodine intake as a dietary pattern and MetS.

Subclinical thyroid dysfunction and chronic kidney disease: a nationwide population-based study.

BACKGROUND: Chronic kidney disease (CKD) has a significant impact on global health. Studies have shown that subclinical thyroid dysfunction may be related to CKD, but the association between subclinical thyroid dysfunction and CKD in the general population is unclear. We aimed to evaluate the risk of CKD according to thyroid function status in a large cohort. METHODS: We analyzed data from a nationwide, population-based, cross-sectional survey (KNHANES VI). A total of 3,257 participants aged ≥ 19 years who underwent thyroid and kidney function assessments were included in this study. CKD was defined as an estimated glomerular filtration rate < 60 mL/min/1.73 m2 and/or urine albumin-creatinine ratio ≥ 30 mg/g. The risk of CKD according to thyroid function status was assessed using logistic regression, adjusted for potential confounders. RESULTS: Overall, 6.7% of the participants had CKD. There were no significant differences in thyroid-stimulating hormone and free thyroxine levels between the groups with and without CKD. The proportion of participants with CKD was significantly different among the thyroid function status groups (p = 0.012) and tended to increase significantly in the following order: subclinical hyperthyroidism (1.5%), euthyroidism (6.6%), and subclinical hypothyroidism (12.6%) (p for trend < 0.001). Subclinical hypothyroidism was a significant risk factor for CKD, even after adjusting for sex, age, household income, education, smoking, alcohol consumption, walking activity, abdominal obesity, hypertension, low high-density lipoprotein cholesterol, elevated triglycerides, hyperglycemia, free thyroxine, and thyroid-peroxidase anibody (odds ratio 2.161, 95% confidence interval 1.032-4.527, p = 0.041). CONCLUSION: Subclinical hypothyroidism is an independent predictor of CKD in the general population.

Development of a deep learning-based auto-segmentation algorithm for hepatocellular carcinoma (HCC) and application to predict microvascular invasion of HCC using CT texture analysis: preliminary results.

BACKGROUND: Automatic segmentation has recently been developed to yield objective data. Prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC) using radiomics has been reported. PURPOSE: To develop a deep learning-based auto-segmentation algorithm (DL-AS) for the detection of HCC and to predict MVI using computed tomography (CT) texture analysis. MATERIAL AND METHODS: We retrospectively collected training data from 249 patients with HCC and validation set from 35 patients. Lesions of the training set were manually drawn by radiologist, in the delayed phase. 2D U-Net was selected as the DL architecture. Using the validation set, one radiologist manually drew 2D and 3D regions of interest twice, and the developed DL-AS was performed twice with a one-month time interval. The reproducibility was calculated using intraclass correlation coefficients (ICC). Logistic regression was performed to predict MVI. RESULTS: ICC was in the range of 0.190-0.998/0.341-0.997 in the manual 3D/2D segmentation. In contrast, it was perfect in 3D/2D using DL-AS, with a success rate of 88.6% for the detection of HCC. For predicting MVI, sphericity was a significant parameter (odds ratio <0.001; 95% confidence interval <0.001-0.206; P = 0.020) for predicting MVI using 2D DL-AS. However, 3D DL-AS segmentation did not yield a predictive parameter. CONCLUSION: The auto-segmentation of HCC using DL-AS provides perfect reproducibility, although it failed to detect 11.4% (4/35). However, the extracted parameters yielded different important predictors of MVI in HCC. Sphericity was a significant predictor in 2D DL-AS and 3D manual segmentation, while discrete compactness was a significant predictor in 2D manual segmentation.

Disrupted intestinal mucosal barrier mediated by alcohol consumption aggravates systemic microplastic accumulation.

Waste plastics are degraded into microplastics (MPs), which are easily accumulated in the human body through digestive tracts, via the food chain. Alcohol is a widely consumed chemical throughout the world with the ability to alter the intestinal barrier. For this reason, this study was aimed to investigate exact relevance between alcohol consumption and organ distributions of MPs in an ethanol feeding animal model characterized by disrupted intestinal mucosal barriers. In this study, C57BL/6 mice were separated into control, control + MP, ethanol (EtOH), and EtOH + MP groups. Mice in the EtOH group ingested a Lieber-DeCarli diet containing EtOH. Mice in the MP groups ingested 0.1 mg/kg fluorophore polymerized polystyrene microplastics via oral gavage polystyrene MPs via oral gavage. The EtOH + MP group showed higher MP accumulation in the liver than the control + MP group. The same pattern was observed in the intestines, spleen, and brain. This pattern was more prominent in the intestines, with the EtOH + MP group showing the most severe damage due to EtOH ingestion. This result suggests that the intestinal mucosa disruption caused by EtOH ingestion exacerbates MP accumulation in the organs. Moreover, hepatic steatosis was more severe in the EtOH + MP group than in the EtOH group, suggesting the secondary manifestation mediated by MP accumulation. This study reports a novel MP accumulation pattern in the body by providing novel insights into alcohol-induced gut permeability and microplastics toxicity from the perspective of gut-liver axis.

Properties of Pleural Mesothelial Cells in Idiopathic Pulmonary Fibrosis and Cryptogenic Organizing Pneumonia.

BACKGROUND: Profibrotic properties of pleural mesothelial cells may play an important role in the fibrosis activity in idiopathic pulmonary fibrosis (IPF). The purpose of this study was to compare the expression of pleural mesothelial cell markers in IPF and cryptogenic organizing pneumonia (COP), with an assumption that increased expression implies increase in fibrosis. METHODS: Twenty IPF lung samples were stained by immunohistochemistry for the pleural mesothelial cell markers: leucine rich repeat neuronal 4 (LRRN4), uroplakin 3B, CC-chemokine ligand 18, and laminin-5. Nine COP lung samples were used as controls. A semi-quantitative analysis was performed to compare markers expression in IPF and COP. RESULTS: LRRN4 expression was found in epithelial lining cells along the honeycombing and fibroblastic foci in IPF, but not in the fibrotic interstitial lesion and airspace filling fibrous tufts in COP. We found a significant decrease in baseline forced vital capacity when LRRN4 expression was increased in honeycombing epithelial cells and fibroblastic foci. CONCLUSION: LRRN4 expression patterns in IPF are distinct from those in COP. Our findings suggest that mesothelial cell profibrotic property may be an important player in IPF pathogenesis and may be a clue in the irreversibility of fibrosis in IPF.

Apocrine cystomatosis: From the aspect of epithelial-mesenchymal transition.

Apocrine cystomatosis, also called epitrichial sweat gland cystomatosis, is a non-neoplastic condition characterised by multiple dilated cysts of sweat gland origin. Histopathologically, these cysts comprise two layers of cells: an inner layer of glandular epithelial cells and an outer layer of myoepithelial cells. A case of apocrine cystomatosis was admitted to a local hospital. The microscopic investigation revealed that some enlarged cysts showed the transition of glandular epithelial cells into a spindle, mesenchymal cell-like morphology. The epithelial-to-mesenchymal transition (EMT) has long been studied as a pathway for embryogenesis, organ development, and carcinogenesis. While various molecular factors, including cytokines and growth factors, are known to induce EMT, mechanical forces have also been proposed to initiate EMT. The present case describes a possible relationship between EMT occurring in a cystic condition and further pathological inspection.

Vitamin C Deficiency Inhibits Nonalcoholic Fatty Liver Disease Progression through Impaired de Novo Lipogenesis.

Despite the increasing clinical importance of nonalcoholic fatty liver disease (NAFLD), little is known about its underlying pathogenesis or specific treatment. The senescence marker protein 30 (SMP30), which regulates the biosynthesis of vitamin C (VC) in many mammals, except primates and humans, was recently recognized as a gluconolactonase. However, the precise relation between VC and lipid metabolism in NAFLD is not completely understood. Therefore, this study aimed to clearly reveal the role of VC in NAFLD progression. SMP30 knockout (KO) mice were used as a VC-deficient mouse model. To investigate the precise role of VC on lipid metabolism, 13- to 15-week-old SMP30 KO mice and wild-type mice fed a 60% high-fat diet were exposed to tap water or VC-containing water (1.5 g/L) ad libitum for 11 weeks. Primary mouse hepatocytes isolated from the SMP30 KO and wild-type mice were used to demonstrate the relation between VC and lipid metabolism in hepatocytes. Long-term VC deficiency significantly suppressed the progression of simple steatosis. The high-fat diet-fed VC-deficient SMP30 KO mice exhibited impaired sterol regulatory element-binding protein-1c activation because of excessive cholesterol accumulation in hepatocytes. Long-term VC deficiency inhibits de novo lipogenesis through impaired sterol regulatory element-binding protein-1c activation.

Association of thyroid autoimmunity with nonalcoholic fatty liver disease in euthyroid middle-aged subjects: A population-based study.

BACKGROUND AND AIM: The association between thyroid autoimmunity and nonalcoholic fatty liver disease (NAFLD) remains unclear. In this study, we aimed to investigate the relationship between thyroid autoimmunity and NAFLD in a large cohort of euthyroid subjects. METHODS: We analyzed clinical and biochemical data from a nationwide, population-based, cross-sectional survey (KNHANES VI). A total of 1589 middle-aged participants aged 45-65 years, with normal thyroid function, were included in this study. NAFLD was defined as a hepatic steatosis index of > 36. We estimated the odds ratios (ORs) for NAFLD according to anti-thyroid peroxidase antibody (TPOAb) positivity by using logistic regression models, and adjusted for potential confounders. RESULTS: Overall, 24% (n = 378) of the subjects had NAFLD. Subjects with NAFLD showed a higher positivity for TPOAb (11% vs 7%, P = 0.014) compared with those without NAFLD. TPOAb positivity was a significant risk factor for NAFLD [OR 1.668, 95% confidence interval (CI) 1.019-2.730, P = 0.042] even after adjusting for confounding variables, including age, sex, household income, education, smoking, alcohol consumption, walking activity, abdominal obesity, elevated blood pressure, dyslipidemia and hyperglycemia. In addition, TPOAb positivity predicted the risk of advanced liver fibrosis (OR 3.112, 95% CI 1.256-7.713, P = 0.014) in subjects with NAFLD, independent of the confounding variables. CONCLUSION: In euthyroid subjects, thyroid autoimmunity is associated with NAFLD and advanced liver fibrosis, independent of known metabolic risk factors. Large longitudinal studies in the future will help clarify the causality.

Single-Step Fast Tissue Clearing of Thick Mouse Brain Tissue for Multi-Dimensional High-Resolution Imaging.

Recent advances in optical clearing techniques have dramatically improved deep tissue imaging by reducing the obscuring effects of light scattering and absorption. However, these optical clearing methods require specialized equipment or a lengthy undertaking with complex protocols that can lead to sample volume changes and distortion. In addition, the imaging of cleared tissues has limitations, such as fluorescence bleaching, harmful and foul-smelling solutions, and the difficulty of handling samples in high-viscosity refractive index (RI) matching solutions. To address the various limitations of thick tissue imaging, we developed an Aqueous high refractive Index matching and tissue Clearing solution for Imaging (termed AICI) with a one-step tissue clearing protocol that was easily made at a reasonable price in our own laboratory without any equipment. AICI can rapidly clear a 1 mm thick brain slice within 90 min with simultaneous RI matching, low viscosity, and a high refractive index (RI = 1.466), allowing the imaging of the sample without additional processing. We compared AICI with commercially available RI matching solutions, including optical clear agents (OCAs), for tissue clearing. The viscosity of AICI is closer to that of water compared with other RI matching solutions, and there was a less than 2.3% expansion in the tissue linear morphology during 24 h exposure to AICI. Moreover, AICI remained fluid over 30 days of air exposure, and the EGFP fluorescence signal was only reduced to ~65% after 10 days. AICI showed a limited clearing of brain tissue >3 mm thick. However, fine neuronal structures, such as dendritic spines and axonal boutons, could still be imaged in thick brain slices treated with AICI. Therefore, AICI is useful not only for the three-dimensional (3D) high-resolution identification of neuronal structures, but also for the examination of multiple structural imaging by neuronal distribution, projection, and gene expression in deep brain tissue. AICI is applicable beyond the imaging of fluorescent antibodies and dyes, and can clear a variety of tissue types, making it broadly useful to researchers for optical imaging applications.

Molecular Detection and Genetic Diversity of Blastocystis in Korean Dogs.

Blastocystis is a genus of unicellular heterokont parasites belonging to a group of organisms known as Stramenopiles, which includes algae, diatoms, and water molds. Blastocystis includes several species that habitat in the gastrointestinal tracts of organisms as diverse as humans, farm animals, birds, rodents, reptiles, amphibians, fish, and cockroaches. It is important to public health and distributed globally, but its prevalence in dogs in Korea has not been reported to date. Here, we collected 787 canine fecal samples and assessed Blastocystis infection by age, sex, region, season, and diarrhea symptoms. We determined Blastocystis subtypes using phylogenetic analyses based on 18S rRNA gene sequences. We identified, 10 Blastocystis positive samples (1.3%). A higher proportion of infected dogs was asymptomatic; however, infection rates did not significantly differ according to region, age, sex, and season. Phylogenetic analysis showed that the Blastocystis sp. identified belonged to 4 subtypes (STs), ST1, ST5, ST10, and ST14, thus revealed the genetic diversity of Blastocystis sp. in dogs Korean. This is first report on the presence of Blastocystis sp. in dogs Korean. This study revealed a lower infection rate than expected and differed from previous studies in STs. Further studies are warranted to observe the national infection status of Blastocystis in dogs and the genetic characteristics of this genus.

Assessment of malignant potential in intraductal papillary mucinous neoplasms of the pancreas using MR findings and texture analysis.

OBJECTIVES: To investigate the utility of MR findings and texture analysis for predicting the malignant potential of pancreatic intraductal papillary mucinous neoplasms (IPMNs). METHODS: Two hundred forty-eight patients with surgically confirmed IPMNs (106 malignant [invasive carcinoma/high-grade dysplasia] and 142 benign [low/intermediate-grade dysplasia]) and who underwent magnetic resonance imaging (MRI) with MR cholangiopancreatography (MRCP) were included. Two reviewers independently analyzed MR findings as proposed by the 2017 international consensus guidelines. Texture analysis of MRCP was also performed. A multivariate logistic regression analysis was used to identify predictors for malignant IPMNs. Diagnostic performance was also analyzed using receiver operating curve analysis. RESULTS: Among MR findings, enhancing mural nodule size ≥ 5 mm, main pancreatic duct (MPD) ≥ 10 mm or MPD of 5 to 9 mm, and abrupt change of MPD were significant predictors for malignant IPMNs (p < 0.05). Among texture variables, significant predictors were effective diameter, surface area, sphericity, compactness, entropy, and gray-level co-occurrence matrix entropy (p < 0.05). At multivariate analysis, enhancing mural nodule ≥ 5 mm (odds ratios (ORs), 6.697 and 6.968, for reviewers 1 and 2, respectively), MPD ≥ 10 mm or MPD of 5 to 9 mm (ORs, 4.098 and 4.215, and 2.517 and 3.055, respectively), larger entropy (ORs, 1.485 and 1.515), and smaller compactness (ORs, 0.981 and 0.977) were significant predictors for malignant IPMNs (p < 0.05). When adding texture variable to MR findings, diagnostic performance for predicting malignant IPMNs improved from 0.80 and 0.78 to 0.85 and 0.85 in both reviewers (p < 0.05), respectively. CONCLUSIONS: MRCP-derived texture features are useful for predicting malignant IPMNs, and the addition of texture analysis to MR features may improve diagnostic performance for predicting malignant IPMNs. KEY POINTS: • Among the MR imaging findings, an enhancing mural nodule size ≥ 5 mm and dilated main pancreatic ducts are independent predictors for malignant IPMNs. • Greater entropy and smaller compactness on MR texture analysis are independent predictors for malignant IPMNs. • The addition of MR texture analysis improved the diagnostic performance for predicting malignant IPMNs from 0.80 and 0.78 to 0.85 and 0.85, respectively.

Automatic pulmonary vessel segmentation on noncontrast chest CT: deep learning algorithm developed using spatiotemporally matched virtual noncontrast images and low-keV contrast-enhanced vessel maps.

OBJECTIVES: To develop a deep learning-based pulmonary vessel segmentation algorithm (DLVS) from noncontrast chest CT and to investigate its clinical implications in assessing vascular remodeling of chronic obstructive lung disease (COPD) patients. METHODS: For development, 104 pulmonary CT angiography scans (49,054 slices) using a dual-source CT were collected, and spatiotemporally matched virtual noncontrast and 50-keV images were generated. Vessel maps were extracted from the 50-keV images. The 3-dimensional U-Net-based DLVS was trained to segment pulmonary vessels (with a vessel map as the output) from virtual noncontrast images (as the input). For external validation, vendor-independent noncontrast CT images (n = 14) and the VESSEL 12 challenge open dataset (n = 3) were used. For each case, 200 points were selected including 20 intra-lesional points, and the probability value for each point was extracted. For clinical validation, we included 281 COPD patients with low-dose noncontrast CTs. The DLVS-calculated volume of vessels with a cross-sectional area < 5 mm2 (PVV5) and the PVV5 divided by total vessel volume (%PVV5) were measured. RESULTS: DLVS correctly segmented 99.1% of the intravascular points (1,387/1,400) and 93.1% of the extravascular points (1,309/1,400). The areas-under-the receiver-operating characteristic curve (AUROCs) were 0.977 and 0.969 for the two external validation datasets. For the COPD patients, both PPV5 and %PPV5 successfully differentiated severe patients whose FEV1 < 50 (AUROCs; 0.715 and 0.804) and were significantly correlated with the emphysema index (Ps < .05). CONCLUSIONS: DLVS successfully segmented pulmonary vessels on noncontrast chest CT by utilizing spatiotemporally matched 50-keV images from a dual-source CT scanner and showed promising clinical applicability in COPD. KEY POINTS: • We developed a deep learning pulmonary vessel segmentation algorithm using virtual noncontrast images and 50-keV enhanced images produced by a dual-source CT scanner. • Our algorithm successfully segmented vessels on diseased lungs. • Our algorithm showed promising results in assessing the loss of small vessel density in COPD patients.

Differentiation of left atrial appendage thrombus from circulatory stasis using cardiac CT radiomics in patients with valvular heart disease.

OBJECTIVES: To determine whether quantitative radiomic features from cardiac CT could differentiate the left atrial appendage (LAA) thrombus from circulatory stasis in patients with valvular heart disease. METHODS: Ninety-five consecutive patients with valvular heart disease and filling defects in LAA on two-phase cardiac CT from March 2016 to August 2018 were retrospectively enrolled and classified as having thrombus or stasis by transesophageal echocardiography or cardiac surgery. The ratio of Hounsfield units in the filling defects to those in the ascending aorta (AA) was calculated on early- and late-phase CT (LAA/AAE and LAA/AAL, respectively). Radiomic features were extracted from semi-automated three-dimensional segmentation of the filling defect on early-phase CT. The diagnostic ability of radiomic features for differentiating thrombus from stasis was assessed and compared to LAA/AAE and LAA/AAL by comparing the AUC of ROC curves. Diagnostic performances of CT attenuation ratios and radiomic features were validated with an independent validation set. RESULTS: Thrombus was diagnosed in 25 cases and stasis in 70. Sixty-eight radiomic features were extracted. Values of 8 wavelet-transformed features were lower in thrombus than in stasis (p < 0.001). The AUC value of a radiomic feature, wavelet_LHL, for diagnosing thrombus was 0.78, which was higher than that of LAA/AAE (AUC = 0.54, p = 0.025) and similar to that of LAA/AAL (AUC = 0.76, p = 0.773). In the validation set, the AUC of wavelet_LHL was 0.71, which was higher than that of LAA/AAE (AUC = 0.57, p = 0.391) and similar to that of LAA/AAL (AUC = 0.75, p = 0.707). CONCLUSIONS: Quantitative radiomic features from the early phase of cardiac CT may help diagnose LAA thrombus in patients with valvular heart disease. KEY POINTS: • Wavelet-transformed grey-level non-uniformity values from radiomic analysis are significantly lower for LAA thrombus than for circulatory stasis. • Radiomic features may have an additional value for differentiating LAA thrombus from circulatory stasis when interpreting single-phase cardiac CT. • Radiomic features extracted from single-phase images may show similar diagnostic ability as conventional quantitative analysis from two-phase images.

Development of an inside-out augmented reality technique for neurosurgical navigation.

OBJECTIVE: With the advancement of 3D modeling techniques and visualization devices, augmented reality (AR)-based navigation (AR navigation) is being developed actively. The authors developed a pilot model of their newly developed inside-out tracking AR navigation system. METHODS: The inside-out AR navigation technique was developed based on the visual inertial odometry (VIO) algorithm. The Quick Response (QR) marker was created and used for the image feature-detection algorithm. Inside-out AR navigation works through the steps of visualization device recognition, marker recognition, AR implementation, and registration within the running environment. A virtual 3D patient model for AR rendering and a 3D-printed patient model for validating registration accuracy were created. Inside-out tracking was used for the registration. The registration accuracy was validated by using intuitive, visualization, and quantitative methods for identifying coordinates by matching errors. Fine-tuning and opacity-adjustment functions were developed. RESULTS: ARKit-based inside-out AR navigation was developed. The fiducial marker of the AR model and those of the 3D-printed patient model were correctly overlapped at all locations without errors. The tumor and anatomical structures of AR navigation and the tumors and structures placed in the intracranial space of the 3D-printed patient model precisely overlapped. The registration accuracy was quantified using coordinates, and the average moving errors of the x-axis and y-axis were 0.52 ± 0.35 and 0.05 ± 0.16 mm, respectively. The gradients from the x-axis and y-axis were 0.35° and 1.02°, respectively. Application of the fine-tuning and opacity-adjustment functions was proven by the videos. CONCLUSIONS: The authors developed a novel inside-out tracking-based AR navigation system and validated its registration accuracy. This technical system could be applied in the novel navigation system for patient-specific neurosurgery.

Simply Fabricated Inexpensive Dual-Polymer-Coated Fabry-Perot Interferometer-Based Temperature Sensors with High Sensitivity.

We designed simply fabricated, highly sensitive, and cost-effective dual-polymer-coated Fabry-Perot interferometer (DFPI)-based temperature sensors by employing thermosensitive polymers and non-thermosensitive polymers, as well as different two successive dip-coating techniques (stepwise dip coating and polymer mixture coating). Seven sensors were fabricated using different polymer combinations for performance optimization. The experiments demonstrated that the stepwise dip-coated dual thermosensitive polymer sensors exhibited the highest sensitivity (2142.5 pm °C-1 for poly(methyl methacrylate)-polycarbonate (PMMA_PC) and 785.5 pm °C-1 for poly(methyl methacrylate)- polystyrene (PMMA_PS)). Conversely, the polymer-mixture-coated sensors yielded low sensitivities (339.5 pm °C-1 for the poly(methyl methacrylate)-polycarbonate mixture (PMMA_PC mixture) and 233.5 pm °C-1 for the poly(methyl methacrylate)-polystyrene mixture (PMMA_PS mixture). Thus, the coating method, polymer selection, and thin air-bubble-free coating are crucial for high-sensitivity DFPI-based sensors. Furthermore, the DFPI-based sensors yielded stable readouts, based on three measurements. Our comprehensive results confirm the effectiveness, reproducibility, stability, fast response, feasibility, and accuracy of temperature measurements using the proposed sensors. The excellent performance and simplicity of our proposed sensors are promising for biomedical, biochemical, and physical applications.

"Turn on" Fluorescence Sensor of Glutathione Based on Inner Filter Effect of Co-Doped Carbon Dot/Gold Nanoparticle Composites.

Glutathione (GSH) is a thiol that plays a significant role in nutrient metabolism, antioxidant defense and the regulation of cellular events. GSH deficiency is related to variety of diseases, so it is useful to develop novel approaches for GSH evaluation and detection. In this study we used nitrogen and phosphorus co-doped carbon dot-gold nanoparticle (NPCD-AuNP) composites to fabricate a simple and selective fluorescence sensor for GSH detection. We employed the reductant potential of the nitrogen and phosphorus co-doped carbon dots (NPCDs) themselves to form AuNPs, and subsequently NPCD-AuNP composites from Au3+. The composites were characterized by using a range of spectroscopic and electron microscopic techniques, including electrophoretic light scattering and X-ray diffraction. The overlap of the fluorescence emission spectrum of NPCDs and the absorption spectrum of AuNPs resulted in an effective inner filter effect (IFE) in the composite material, leading to a quenching of the fluorescence intensity. In the presence of GSH, the fluorescence intensity of the composite was recovered, which increased proportionally to increasing the GSH concentration. In addition, our GSH sensing method showed good selectivity and sensing potential in human serum with a limit of detection of 0.1 µM and acceptable results.

Isolation and Characterization of Compounds from Glycyrrhiza uralensis as Therapeutic Agents for the Muscle Disorders.

Skeletal muscle is the most abundant tissue and constitutes about 40% of total body mass. Herein, we report that crude water extract (CWE) of G. uralensis enhanced myoblast proliferation and differentiation. Pretreatment of mice with the CWE of G. uralensis prior to cardiotoxin-induced muscle injury was found to enhance muscle regeneration by inducing myogenic gene expression and downregulating myostatin expression. Furthermore, this extract reduced nitrotyrosine protein levels and atrophy-related gene expression. Of the five different fractions of the CWE of G. uralensis obtained, the ethyl acetate (EtOAc) fraction more significantly enhanced myoblast proliferation and differentiation than the other fractions. Ten bioactive compounds were isolated from the EtOAc fraction and characterized by GC-MS and NMR. Of these compounds (4-hydroxybenzoic acid, liquiritigenin, (R)-(-)-vestitol, isoliquiritigenin, medicarpin, tetrahydroxymethoxychalcone, licochalcone B, liquiritin, liquiritinapioside, and ononin), liquiritigenin, tetrahydroxymethoxychalcone, and licochalcone B were found to enhance myoblast proliferation and differentiation, and myofiber diameters in injured muscles were wider with the liquiritigenin than the non-treated one. Computational analysis showed these compounds are non-toxic and possess good drug-likeness properties. These findings suggest that G. uralensis-extracted components might be useful therapeutic agents for the management of muscle-associated diseases.