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BACKGROUND: Digital dementia is a term that describes a possible decline in cognitive abilities, especially memory, attributed to the excessive use of digital technology such as smartphones, computers, and tablets. This concept has gained popularity in public discourse and media lately. With the increasing use of social media platforms such as Twitter (subsequently rebranded as X), discussions about digital dementia have become more widespread, which offer a rich source of information to understand public perceptions, concerns, and sentiments regarding this phenomenon. OBJECTIVE: The aim of this research was to delve into a comprehensive content and sentiment analysis of Twitter discussions regarding digital dementia using the hashtag #digitaldementia. METHODS: Retrospectively, publicly available English-language tweets with hashtag combinations related to the topic of digital dementia were extracted from Twitter. The tweets were collected over a period of 15 years, from January 1, 2008, to December 31, 2022. Content analysis was used to identify major themes within the tweets, and sentiment analysis was conducted to understand the positive and negative emotions associated with these themes in order to gain a better understanding of the issues surrounding digital dementia. A one-way ANOVA was performed to gather detailed statistical insights regarding the selected tweets from influencers within each theme. RESULTS: This study was conducted on 26,290 tweets over 15 years by 5123 Twitter users, mostly female users in the United States. The influencers had followers ranging from 20,000 to 1,195,000 and an average of 214,878 subscribers. The study identified four themes regarding digital dementia after analyzing tweet content: (1) cognitive decline, (2) digital dependency, (3) technology overload, and (4) coping strategies. Categorized according to Glaser and Strauss's classifications, most tweets (14,492/26,290, 55.12%) fell under the categories of wretched (purely negative) or bad (mostly negative). However, only a small proportion of tweets (3122/26,290, 11.86%) were classified as great (purely positive) or swell sentiment (mostly positive). The ANOVA results showed significant differences in mean sentiment scores among the themes (F3,3581=29.03; P<.001). The mean sentiment score was -0.1072 (SD 0.4276). CONCLUSIONS: Various negative tweets have raised concerns about the link between excessive use of digital devices and cognitive decline, often known as digital dementia. Of particular concern is the rapid increase in digital device use. However, some positive tweets have suggested coping strategies. Engaging in digital detox activities, such as increasing physical exercise and participating in yoga and meditation, could potentially help prevent cognitive decline.
Subject(s)
Dementia , Social Media , Social Media/statistics & numerical data , Humans , Dementia/psychology , Retrospective Studies , EmotionsABSTRACT
This research group (FROM) aimed to develop biomarkers for exposure to environmental hazards and diseases, assess environmental diseases, and apply and verify these biomarkers in environmentally vulnerable areas. Environmentally vulnerable areasincluding refineries, abandoned metal mines, coal-fired power plants, waste incinerators, cement factories, and areas with high exposure to particulate matteralong with control areas, were selected for epidemiological investigations. A total of 1,157 adults, who had resided in these areas for over 10 years, were recruited between June 2021 and September 2023. Personal characteristics of the study participants were gathered through a survey. Biological samples, specifically blood and urine, were collected during the field investigations, separated under refrigerated conditions, and then transported to the laboratory for biomarker analysis. Analyses of heavy metals, environmental hazards, and adducts were conducted on these blood and urine samples. Additionally, omics analyses of epigenomes, proteomes, and metabolomes were performed using the blood samples. The biomarkers identified in this study will be utilized to assess the risk of environmental disease occurrence and to evaluate the impact on the health of residents in environmentally vulnerable areas, following the validation of diagnostic accuracy for these diseases.
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(1) Background: it is challenging to determine the accurate grades of cartilaginous bone tumors. Using bone single photon emission computed tomography (SPECT)/computed tomography (CT), maximum standardized uptake value (SUVmax) was found to be significantly associated with different grades of cartilaginous bone tumor. The inquiry focused on the effect of the tumor matrix on SUVmax. (2) Methods: a total of 65 patients from 2017 to 2022 with central cartilaginous bone tumors, including enchondromas and low-to-intermediate grade chondrosarcomas, who had undergone bone SPECT/CT were retrospectively enrolled. The SUVmax was recorded and any aggressive CT findings of cartilaginous bone tumor and Hounsfield units (HU) of the chondroid matrix as mean, minimum, maximum, and standard deviation (SD) were reviewed on CT scans. Pearson's correlation analysis was performed to determine the relationship between CT features and SUVmax. Subgroup analysis was also performed between the benign group (enchondroma) and the malignant group (grade 1 and 2 chondrosarcoma) for comparison of HU values and SUVmax. (3) Results: a significant negative correlation between SUVmax and HU measurements, including HUmax, HUmean, and HUSD, was found. The subgroup analysis showed significantly higher SUVmax in the malignant group, with more frequent CT aggressive features, and significantly lower HUSD in the malignant group than in the benign group. (4) Conclusions: it was observed that higher SUVmax and lower HUSD were associated with a higher probability of having a low-to-intermediate chondrosarcoma with aggressive features and a less calcified tumor matrix.
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Background: Application of visual scoring scales for regional atrophy in Alzheimer's disease (AD) in clinical settings is limited by their high time cost and low intra/inter-rater agreement. Objective: To provide automated atrophy scoring using objective volume driven from deep-learning segmentation methods for AD subtype classification using magnetic resonance imaging (MRI). Methods: We enrolled 3,959 participants (1,732 cognitively normal [CN], 1594 with mild cognitive impairment [MCI], and 633 with AD). The occupancy indices for each regional volume were calculated by dividing each volume by the size of the lateral and inferior ventricular volumes. MR images from 355 participants (119 CN, 119 MCI, and 117 AD) from three different centers were used for validation. Two neuroradiologists performed visual assessments of the medial temporal, posterior, and global cortical atrophy scores in the frontal lobe using T1-weighted MR images. Images were also analyzed using the deep learning-based segmentation software, Neurophet AQUA. Cutoff values for the three scores were determined using the data distribution according to age. The scoring results were compared for consistency and reliability. Results: Four volumetric-driven scoring results showed a high correlation with the visual scoring results for AD, MCI, and CN. The overall agreement with human raters was weak-to-moderate for atrophy scoring in CN participants, and good-to-almost perfect in AD and MCI participants. AD subtyping by automated scores also showed usefulness as a research tool. Conclusions: Determining AD subtypes using automated atrophy scoring for late-MCI and AD could be useful in clinical settings or multicenter studies with large datasets.
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Heavy metals are commonly released into the environment through industrial processes such as mining and refining. The rapid industrialization that occurred in South Korea during the 1960s and 1970s contributed significantly to the economy of the country; however, the associated mining and refining led to considerable environmental pollution, and although mining is now in decline in South Korea, the detrimental effects on residents inhabiting the surrounding areas remain. The bioaccumulation of toxic heavy metals leads to metabolic alterations in human homeostasis, with disruptions in this balance leading to various health issues. This study used metabolomics to explore metabolomic alterations in the plasma samples of residents living in mining and refining areas. The results showed significant increases in metabolites involved in glycolysis and the surrounding metabolic pathways, such as glucose-6-phosphate, phosphoenolpyruvate, lactate, and inosine monophosphate, in those inhabiting polluted areas. An investigation of the associations between metabolites and blood clinical parameters through meet-in-the-middle analysis indicated that female residents were more affected by heavy metal exposure, resulting in more metabolomic alterations. For women, inhabiting the abandoned mine area, metabolites in the glycolysis and pentose phosphate pathways, such as ribose-5-phosphate and 3-phosphoglycerate, have shown a negative correlation with albumin and calcium. Finally, Mendelian randomization(MR) was used to determine the causal effects of these heavy metal exposure-related metabolites on heavy metal exposure-related clinical parameters. Metabolite biomarkers could provide insights into altered metabolic pathways related to exposure to toxic heavy metals and improve our understanding of the molecular mechanisms underlying the health effects of toxic heavy metal exposure.
Subject(s)
Environmental Exposure , Metals, Heavy , Humans , Metals, Heavy/blood , Female , Republic of Korea , Male , Adult , Metabolomics , Mining , Middle Aged , Environmental Pollution/statistics & numerical data , Environmental Pollutants/bloodABSTRACT
Residents in areas with abandoned mines risk significant exposure to abundant heavy metals in the environment. However, current clinical indicators cannot fully reflect the health changes associated with abandoned mine exposure. The aim of this study was to identify biological changes in the residents of abandoned mine areas via proteomic analysis of their blood. Blood samples were collected from abandoned mine and control areas, and mass spectrometry was used for protein profiling. A total of 138 unique or common proteins that were differentially expressed in low-exposure abandoned mine area (LoAMA) or high-exposure abandoned mine area (HiAMA) compared to non-exposure control area (NEA) were analyzed, and identified 4 clusters based on functional similarity. Among the 10 proteins that showed specific change in LoAMA, 4 proteins(Apolipoprotein M, Apolipoprotein E, Apolipoprotein L1, and Cholesteryl ester transfer protein) were cluded in cluster 1(plasma lipoprotein remodeling), and linked to proteins that showed specific change in protein expression in HiAMA. Therefore, it is suggested that 4 proteins are changed at low exposure to an abandoned mine (or initial exposure), and then at high exposure, changes in various proteins involved in linked plasma lipoprotein remodeling are induced, which might triggered by the 4 proteins. Interestingly, in addition to plasma lipoprotein remodeling, proteins involved in other functional networks were changed in the high exposure group. These were all directly or indirectly linked to the 4 biomarkers(Apolipoprotein M, Apolipoprotein E, Apolipoprotein L1, and Cholesteryl ester transfer protein) that changed during low exposure. This suggests their potential utility in identifying areas impacted by abandoned mines. Especially, proteins involved in lipid metabolism and renal function-related diseases in individuals exposed to heavy metals in abandoned mine areas were correlated. Chronic kidney disease is predominantly instigated by cardiovascular disease and is commonly accompanied by dyslipidemia.
Subject(s)
Environmental Exposure , Mining , Proteomics , Humans , Male , Middle Aged , Adult , Metals, Heavy/toxicity , Female , Blood Proteins/analysisABSTRACT
BACKGROUND: While indirect comparison of infliximab (IFX) and vedolizumab (VDZ) in adults with Crohn's disease (CD) or ulcerative colitis (UC) shows that IFX has better effectiveness during induction, and comparable efficacy during maintenance treatment, comparative data specific to subcutaneous (SC) IFX (i.e., CT-P13 SC) versus VDZ are limited. AIM: Pooled analysis of randomised studies to compare efficacy and safety with IFX SC and VDZ in moderate-to-severe inflammatory bowel disease. METHODS: Parallel-group, randomised studies evaluating IFX SC and VDZ in patients with moderate-to-severe CD or UC were identified. Eligible studies reported ≥ 1 prespecified outcome of interest at Week 6 (reflecting treatment during the induction phase) and/or at 1 year (Weeks 50-54; reflecting treatment during the maintenance phase). Prespecified efficacy and safety outcomes considered in this pooled analysis included the proportions of patients achieving disease-specific clinical responses, clinical remission, or discontinuing due to lack of efficacy, and the proportions of patients experiencing adverse events (AEs), serious AEs, infections, serious infections, or discontinuing due to AEs. Data from multiple studies or study arms were extracted and pooled using a random-effect model; comparative analyses were performed separately for patients with CD and UC. RESULTS: We identified three eligible CD trials and four eligible UC trials that assigned over 1200 participants per disease cohort to either IFX SC or VDZ. In patients with CD, intravenous induction therapy with IFX demonstrated better efficacy (non-overlapping 95% confidence intervals [CIs]) compared with VDZ; during the maintenance phase, IFX SC showed numerically better efficacy (overlapping 95% CIs) than VDZ. A lower proportion of IFX SC-treated patients discontinued therapy due to lack of efficacy over 1 year. In patients with UC, efficacy profiles were similar with IFX SC and VDZ during the induction and maintenance phases, and a lower proportion of IFX SC-treated patients discontinued therapy due to lack of efficacy over 1 year. In both cohorts, safety profiles for IFX SC and VDZ were generally comparable during 1 year. CONCLUSION: IFX SC demonstrated better efficacy than VDZ in patients with CD, and similar efficacy to VDZ in patients with UC; 1-year safety was comparable with IFX SC and VDZ.
Subject(s)
Antibodies, Monoclonal, Humanized , Colitis, Ulcerative , Crohn Disease , Gastrointestinal Agents , Infliximab , Randomized Controlled Trials as Topic , Humans , Crohn Disease/drug therapy , Colitis, Ulcerative/drug therapy , Antibodies, Monoclonal, Humanized/therapeutic use , Antibodies, Monoclonal, Humanized/adverse effects , Antibodies, Monoclonal, Humanized/administration & dosage , Gastrointestinal Agents/therapeutic use , Gastrointestinal Agents/adverse effects , Gastrointestinal Agents/administration & dosage , Infliximab/therapeutic use , Infliximab/administration & dosage , Infliximab/adverse effects , Injections, Subcutaneous , Treatment Outcome , Adult , Remission Induction , Induction Chemotherapy/methodsABSTRACT
Epithelioid angiosarcoma is a rare variant of angiosarcoma characterized by an epithelioid morphology that mimics carcinoma. Therefore, multicentric epithelioid angiosarcoma is easily misdiagnosed as bone metastasis from carcinoma and has an aggressive clinical course. Here, we present a rare case of a 61-year-old male with multicentric epithelioid angiosarcoma of the bone. Plain radiography, CT, and MRI revealed multiple osteolytic lesions in both femurs; some lesions showed soft tissue extension with cortical bone destruction. Interestingly, PET-CT revealed that the lesions were only distributed along the bones of the lower extremities, including the pelvic bones, femurs, and tibiae. Despite histological analysis initially suggesting metastatic carcinoma, after additional immunohistological staining, including that for vascular markers (CD31 and ERG), the final diagnosis was epithelioid angiosarcoma. A better understanding of the clinicoradiological features of this disease may help eliminate diagnostic confusion and provide better management.
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Cadmium (Cd), a serious environmental contaminant, is associated with adverse health effects. However, the specific changes that the human body experiences in response to exposure to varying concentrations of cadmium remain unknown. The high levels of heavy metal contamination, especially Cd, in abandoned mines and smelter sites make them ideal locations to investigate the physiological manifestations of Cd exposure. This study found that individuals inhabiting abandoned mine and smelter areas had higher concentrations of Cd in their urine and blood compared to those living outside these areas (i.e., the controls). Furthermore, proteomic profiling of blood samples from all study groups was performed to identify proteomic biomarkers associated with chronic and severe Cd exposure. This analysis showed statistically significant correlations between urine Cd levels and sixteen proteins. Among these proteins, seven exhibited significantly altered expressions in samples from contaminated areas compared with those from control areas. Therefore, these proteins were selected as potential markers representing Cd-related protein alterations. Multiple reaction monitoring analysis was performed to validate the expression patterns of the proteins and four proteins were found to exhibit consistent trends. The findings show that Cd exposure significantly affects the expression of certain proteins in the human body. Understanding the underlying mechanisms and diseases associated with Cd-induced protein alterations can aid in the development of effective preventive and therapeutic strategies for individuals exposed to Cd-linked pollution.
Subject(s)
Drug-Related Side Effects and Adverse Reactions , Metals, Heavy , Humans , Cadmium/analysis , Proteomics , Metals, Heavy/analysis , Environmental Pollution/analysis , Mining , Environmental Monitoring , Environmental Exposure/analysisABSTRACT
Recent advances in contrastive learning have significantly improved the performance of deep learning models. In contrastive learning of medical images, dealing with positive representation is sometimes difficult because some strong augmentation techniques can disrupt contrastive learning owing to the subtle differences between other standardized CXRs compared to augmented positive pairs; therefore, additional efforts are required. In this study, we propose intermediate feature approximation (IFA) loss, which improves the performance of contrastive convolutional neural networks by focusing more on positive representations of CXRs without additional augmentations. The IFA loss encourages the feature maps of a query image and its positive pair to resemble each other by maximizing the cosine similarity between the intermediate feature outputs of the original data and the positive pairs. Therefore, we used the InfoNCE loss, which is commonly used loss to address negative representations, and the IFA loss, which addresses positive representations, together to improve the contrastive network. We evaluated the performance of the network using various downstream tasks, including classification, object detection, and a generative adversarial network (GAN) inversion task. The downstream task results demonstrated that IFA loss can improve the performance of effectively overcoming data imbalance and data scarcity; furthermore, it can serve as a perceptual loss encoder for GAN inversion. In addition, we have made our model publicly available to facilitate access and encourage further research and collaboration in the field.
Subject(s)
Deep Learning , Neural Networks, Computer , Humans , Radiography, ThoracicABSTRACT
Tenosynovial giant cell tumor (TSGCT) is a rare soft tissue tumor that involves the synovial lining of joints, bursae, and tendon sheaths, primarily affecting young patients (usually in the fourth decade of life). The tumor comprises two subtypes: the localized type (L-TSGCT) and the diffuse type (D-TSGCT). Although these subtypes share histological and genetic similarities, they present a different prognosis. D-TSGCT tends to exhibit local aggressiveness and a higher recurrence rate compared to L-TSGCT. Magnetic resonance imaging (MRI) is the preferred diagnostic tool for both the initial diagnosis and for treatment planning. When interpreting the initial MRI of a suspected TSGCT, it is essential to consider: (i) the characteristic findings of TSGCT-evident as low to intermediate signal intensity on both T1- and T2-weighted images, with a blooming artifact on gradient-echo sequences due to hemosiderin deposition; (ii) the possibility of D-TSGCT-extensive involvement of the synovial membrane with infiltrative margin; and (iii) the resectability and extent-if resectable, synovectomy is performed; if not, a novel systemic therapy involving colony-stimulating factor 1 receptor inhibitors is administered. In the interpretation of follow-up MRIs of D-TSGCTs after treatment, it is crucial to consider both tumor recurrence and potential complications such as osteoarthritis after surgery as well as the treatment response after systemic treatment. Given its prevalence in young adult patents and significant impact on patients' quality of life, clinical trials exploring new agents targeting D-TSGCT are currently underway. Consequently, understanding the characteristic MRI findings of D-TSGCT before and after treatment is imperative.
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Exposure to heavy metals such as lead, cadmium, and mercury poses serious health risks to pregnant women because of their high toxicity. In this study, we investigated the associations of heavy metal exposure with birth outcomes of Korean infants. Data of 5,215 women between 2015 and 2019 were analyzed. This study was part of the Korean Children's Environmental Health (Ko-CHENS) study. Linear regression and logistic regression analyses were used to examine effects of concentrations of lead, cadmium, and mercury on birth weight, small for gestational age, and large for gestational age after adjusting for maternal age groups, parity, infant sex, education, income, smoking, drinking, body mass index, stillbirth, premature birth, diabetes, hypertension, and gestational diabetes. Besides adjusting for these covariates, each metal was mutually adjusted to estimate birth weight and large for gestational age status. Maternal cadmium concentrations during early pregnancy (ß = - 39.96; 95% confidence interval (CI): - 63.76, - 16.17) and late pregnancy (ß = - 37.24; 95% CI - 61.63, - 12.84) were significantly associated with birth weight. Cadmium levels during early pregnancy (adjusted OR = 0.637; 95% CI 0.444, 0.912) were also associated with large for gestational age status. Our findings suggest that prenatal cadmium exposure, even at a low level of exposure, is significantly associated with low birth weight.
Subject(s)
Mercury , Metals, Heavy , Premature Birth , Infant, Newborn , Infant , Child , Pregnancy , Humans , Female , Birth Weight , Cadmium/toxicity , Maternal Exposure/adverse effects , Metals, Heavy/toxicity , Mercury/toxicity , Premature Birth/epidemiology , StillbirthABSTRACT
OBJECTIVE: To develop a postmenstrual age (PMA) prediction model based on segmentation volume and to evaluate the brain maturation index using the proposed model. METHODS: Neonatal brain MRIs without clinical illness or structural abnormalities were collected from four datasets from the Developing Human Connectome Project, the Catholic University of Korea, Hammersmith Hospital (HS), and Dankook University Hospital (DU). T1- and T2-weighted images were used to train a brain segmentation model. Another model to predict the PMA of neonates based on segmentation data was developed. Accuracy was assessed using mean absolute error (MAE), root mean square error (RMSE), and mean error (ME). The brain maturation index was calculated as the difference between the PMA predicted by the model and the true PMA, and its correlation with postnatal age was analyzed. RESULTS: A total of 247 neonates (mean gestation age 37 ± 4 weeks; range 24-42 weeks) were included. Thirty-one features were extracted from each neonate and the three most contributing features for PMA prediction were the right lateral ventricle, left caudate, and corpus callosum. The predicted and true PMA were positively correlated (coefficient = 0.88, p < .001). MAE, RMSE, and ME of the external dataset of HS and DU were 1.57 and 1.33, 1.79 and 1.37, and 0.37 and 0.06 weeks, respectively. The brain maturation index negatively correlated with postnatal age (coefficient = - 0.24, p < .001). CONCLUSION: A model that calculates the regional brain volume can predict the PMA of neonates, which can then be utilized to show the brain maturation degree. CLINICAL RELEVANCE STATEMENT: A brain maturity index based on regional volume of neonate's brain can be used to measure brain maturation degree, which can help identify the status of early brain development. KEY POINTS: ⢠Neonatal brain MRI segmentation model could be used to assess neonatal brain maturation status. ⢠A postmenstrual age (PMA) prediction model was developed based on a neonatal brain MRI segmentation model. ⢠The brain maturation index, derived from the PMA prediction model, enabled the estimation of the neonatal brain maturation status.
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Synovial sarcomas are rare and highly aggressive soft-tissue sarcomas, primarily affecting adolescents and young adults aged 15-40 years. These tumors typically arise in the deep soft tissues, often near the large joints of the extremities. While the radiological features of these tumors are not definitely indicative, the presence of calcification in a soft-tissue mass (occurring in 30% of cases), adjacent to a joint, strongly suggests the diagnosis. Cross-sectional imaging characteristics play a crucial role in diagnosing synovial sarcomas. They often reveal significant characteristics such as multilobulation and pronounced heterogeneity (forming the "triple sign"), in addition to features like hemorrhage and fluid-fluid levels with septa (resulting in the "bowl of grapes" appearance). Nevertheless, the existence of non-aggressive features, such as gradual growth (with an average time to diagnosis of 2-4 years) and small size (initially measuring < 5 cm) with well-defined margins, can lead to an initial misclassification as a benign lesion. Larger size, older age, and higher tumor grade have been established as adverse predictive indicators for both local disease recurrence and the occurrence of metastasis. Recently, the prognostic importance of CT and MRI characteristics for synovial sarcomas was elucidated. These include factors like the absence of calcification, the presence of cystic components, hemorrhage, the bowl of grape sign, the triple sign, and intercompartmental extension. Wide surgical excision remains the established approach for definitive treatment. Gaining insight into and identifying the diverse range of presentations of synovial sarcomas, which correlate with the prognosis, might be helpful in achieving the optimal patient management.
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OBJECTIVE: To investigate the potential benefits of using massage chairs for improving health. DATA SOURCES: A rapid scoping review was conducted using PubMed, Embase, Cochrane Library, and Google Scholar from inception to November 1, 2022. STUDY SELECTION: Using the keyword strategy ("massage chair*" OR "massage-chair*"), only studies in English were selected. Two reviewers independently screened the studies, and conflicts were resolved by consensus. Studies involving physical massage therapy were excluded. DATA EXTRACTION: A total of 59 articles were identified, and 18 were included in the final analysis. Quality assessment was performed, following STROBE, CONSORT and CASP guidelines. The following data were extracted: authors, year, country, study design, study objective, age, gender, participants, measures, and main findings. DATA SYNTHESIS: The results of the present review indication that the utilization of massage chairs may positively affect both physical and mental health concerns. This review especially found a more significant number of studies showing benefits in mental health. However, two case reports indicated complications when using massage chairs. CONCLUSIONS: The use of massage chairs could have benefits on cognitive function improvement, stress reduction and mental fatigue decline, muscle stiffness improvement, pain reduction, and potential benefits for quality of life.
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PURPOSE: The aim of the study is to evaluate the stage 3 findings of the 2019 revision of the Association Research Circulation Osseous (ARCO) staging system for osteonecrosis of the femoral head between 3A and 3B and the relationship with bone resorption area. MATERIALS AND METHODS: We retrospectively enrolled 87 patients with ARCO stage 3 osteonecrosis of the femoral head, divided into stage 3A (n = 73) and 3B (n = 14). The revised stage 3 findings included subchondral fracture, fracture in necrotic portion, and flattening of the femoral head and were compared between stage 3A and 3B. The association between these findings and the causative features of bone resorption area was also evaluated. RESULTS: All stage 3 cases had subchondral fractures. In stage 3A, these fractures were generated by crescent sign (41.1%) and by fibrovascular reparative zone in 58.9%; however, in stage 3B, fibrovascular reparative zone generated 92.9% of these fractures and crescent sign only 7.1% with statistical significance ( P = 0.034). Necrotic portion fracture was noted in 36.7% and femoral head flattening was observed in 14.9% of all stage 3. Necrotic portion fracture (92.9% vs 26.0%) and femoral head flattening (71.4% vs 4.1%) were observed more frequently in stage 3B than 3A ( P < 0.001). Almost all subchondral fractures by fibrovascular reparative zone (96.4%) and necrotic portion fracture (96.9%), and all femoral head flattening was presented with bone resorption area with expanding areas. CONCLUSIONS: The ARCO stage 3 descriptions reflect severity in this order: subchondral fracture, necrotic portion fracture, and femoral head flattening. More severe findings are usually associated with expanding bone resorption areas.
Subject(s)
Bone Resorption , Femur Head Necrosis , Fractures, Bone , Humans , Femur Head Necrosis/diagnostic imaging , Femur Head Necrosis/complications , Femur Head/diagnostic imaging , Retrospective Studies , Bone Resorption/diagnostic imaging , Bone Resorption/complicationsABSTRACT
PURPOSE: The purpose of the study was to investigate the effects of 4 weeks of lactate intake immediately after endurance exercise on maximal oxygen uptake (VO2max) in exercise performance. METHODS: Seven-week-old mice from the Institute of Cancer Research (ICR) were randomly divided into four groups: vehicle intake (SE/CON), lactate intake (SE/LAC), endurance exercise with vehicle intake (EX/ CON), and lactate intake with endurance exercise (EX/ LAC). Mice were subjected to 60-70% VO2max endurance exercise with or without oral lactate intake 5 days/ week for 4 weeks. VO2max measurements (VO2max, time to exhaustion (TTE), respiratory exchange rate, fat oxidation, and carbohydrate oxidation) were recorded at the end of the study period. After 48 h of VO2max measurement, the mice were sacrificed, and three different abdominal fat samples (epididymal, perirenal, and mesenteric) were collected. RESULTS: Body weight and abdominal fat mass did not differ between the groups. When measuring VO2max, endurance exercise raised VO2max, and lactate intake after endurance exercise increased TTE. The change in energy substrate utilization during VO2max measurement demonstrated that although the respiratory exchange rate and fat oxidation were enhanced by lactate intake, there were no synergistic effects of lactate intake and endurance exercise. CONCLUSION: Lactate intake immediately after endurance exercises can improve exercise performance, indicating the benefit of long-term exogenous lactate intake as an exercise supplement.
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A major responsibility of radiologists in routine clinical practice is to read follow-up chest radiographs (CXRs) to identify changes in a patient's condition. Diagnosing meaningful changes in follow-up CXRs is challenging because radiologists must differentiate disease changes from natural or benign variations. Here, we suggest using a multi-task Siamese convolutional vision transformer (MuSiC-ViT) with an anatomy-matching module (AMM) to mimic the radiologist's cognitive process for differentiating baseline change from no-change. MuSiC-ViT uses the convolutional neural networks (CNNs) meet vision transformers model that combines CNN and transformer architecture. It has three major components: a Siamese network architecture, an AMM, and multi-task learning. Because the input is a pair of CXRs, a Siamese network was adopted for the encoder. The AMM is an attention module that focuses on related regions in the CXR pairs. To mimic a radiologist's cognitive process, MuSiC-ViT was trained using multi-task learning, normal/abnormal and change/no-change classification, and anatomy-matching. Among 406 K CXRs studied, 88 K change and 115 K no-change pairs were acquired for the training dataset. The internal validation dataset consisted of 1,620 pairs. To demonstrate the robustness of MuSiC-ViT, we verified the results with two other validation datasets. MuSiC-ViT respectively achieved accuracies and area under the receiver operating characteristic curves of 0.728 and 0.797 on the internal validation dataset, 0.614 and 0.784 on the first external validation dataset, and 0.745 and 0.858 on a second temporally separated validation dataset. All code is available at https://github.com/chokyungjin/MuSiC-ViT.
Subject(s)
Music , Humans , Follow-Up Studies , Learning , Neural Networks, Computer , ROC CurveABSTRACT
OBJECTIVE: Tenosynovial giant cell tumors (TSGCTs) of the knee differ in their clinical outcome according to disease subtypes and severity. The aim of this study was to determine the predictive MRI features related to local recurrence in TSGCT of the knee regarding disease subtypes and severity. METHODS: This retrospective study included 20 patients with pathology-proven TSGCT of the knee who underwent preoperative MRI and surgery from Jan. 2007 to Jan. 2022. The anatomical point of the lesion was determined with a knee mapping. And then MRI features related to disease subtype including nodularity (single vs. multinodular); margin (circumscribed vs. infiltrative); peripheral hypointenseity (present vs. absent); internal hypointensity reflecting hemosiderin deposition (speckled vs. granular) were assessed. Third, MRI features related to disease severity including involvement of bone, cartilage, and tendon were evaluated. MRI features for predicting local recurrence of TSGCT were tested using chi-square test and logistic regression analysis. RESULTS: Ten patients with diffuse-type TSGCT (D-TSGCT) and 10 patients with localized-type TSGCT (L-TSGCT) were included. There were six cases of local recurrence and all of them were D-TSGCT and none for L-TSGCT with statistical difference (P = 0.015). D-TSGCT that was direct risk factor for local recurrence showed more multinodular (80.0% vs. 10.0%; P = 0.007), infiltrative margin (90.0% vs. 10.0%; P = 0.002), and absent peripheral hypointensity (100.0% vs. 20.0%; P = 0.001) than L-TSGCT. Multivariate analysis showed infiltrative margin (odds ratio [OR], 81.0; P = 0.003) was independent MRI factor for D-TSGCT. Disease severity for risk of local recurrence included cartilage (66.7% vs. 7.1%; P = 0.024) and tendon (100.0% vs. 28.6%; P = 0.015) involvement compared to no local recurrence. Multivariate analysis showed tendon involvement (OR, 12.5; P = 0.042) was predictive MRI parameter for local recurrence. By combining tumor margin and tendon involvement, local recurrence was predicted sensitively on preoperative MRI (sensitivity, 100%; specificity, 50%; accuracy, 65%). CONCLUSION: D-TSGCTs was associated with local recurrence and showed multinodularity infiltrative margin, and absent peripheral hypointensity. Disease severity including cartilage and tendon involvement was associated with local recurrence. Preoperative MRI evaluation by combining disease subtypes and severity can predict local recurrence sensitively.
Subject(s)
Giant Cell Tumor of Tendon Sheath , Knee Joint , Humans , Retrospective Studies , Knee Joint/diagnostic imaging , Knee Joint/surgery , Tendons/diagnostic imaging , Magnetic Resonance ImagingABSTRACT
Diffusion-weighted imaging (DWI) with an apparent diffusion coefficient (ADC) value is a relatively new magnetic resonance imaging (MRI) sequence that provides functional information on the lesion by measuring the microscopic movement of water molecules. While numerous studies have evaluated the promising role of DWI in musculoskeletal radiology, most have focused on tumorous diseases related to cellularity. This review article aims to summarize DWI-acquisition techniques, considering pitfalls such as T2 shine-through and T2 black-out, and their usefulness in interpreting musculoskeletal diseases with imaging. DWI is based on the Brownian motion of water molecules within the tissue, achieved by applying diffusion-sensitizing gradients. Regardless of the cellularity of the lesion, several pitfalls must be considered when interpreting DWI with ADC values in musculoskeletal radiology. This review discusses the application of DWI in musculoskeletal diseases, including tumor and tumor mimickers, as well as non-tumorous diseases, with a focus on lesions demonstrating T2 shine-through and T2 black-out effects. Understanding these pitfalls of DWI can provide clinically useful information, increase diagnostic accuracy, and improve patient management when added to conventional MRI in musculoskeletal diseases.