scholarly journals Association of Quantified Costal Cartilage Calcification and Long-Term Cumulative Blood Glucose Exposure: The Multi-Ethnic Study of Atherosclerosis

2021 ◽  
Vol 12 ◽  
Author(s):  
Mahsima Shabani ◽  
Farhad Pishgar ◽  
Sepehr Akhtarkhavari ◽  
Thiago Quinaglia ◽  
Matthew J. Budoff ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Blood Glucose ◽  
Costal Cartilage ◽  
Ct Images ◽  
Cumulative Exposure ◽  
High Blood Glucose ◽  
Ethnic Study ◽  
Cartilage Calcification ◽  
Glucose Exposure

AimsAnecdotal reports have suggested increased soft tissue calcification in individuals with long-term exposures to high blood glucose. The association of costal cartilage calcification (CCC), a reliably quantifiable marker obtainable from non-contrast cardiac computed tomography (CT) with cumulative fasting blood glucose (FBG) exposure, is unknown. In this study, we aimed to determine the association between quantified CCC and cumulative glucose exposure using non-contrast coronary artery calcium (CAC) scoring computed tomography (CT) images in the Multi-Ethnic Study of Atherosclerosis (MESA).MethodsThe volume of bilateral CCC was quantified in high-density pixels (threshold of Hounsfield Unit>180) using the CAC scoring CT images acquired in the 5th MESA exam. Prior long-term cumulative exposure to FBG was calculated by area under the FBG-time curve over ten years before the time of the CT exam.ResultsA total of 2,305 participants (mean age: 69, female/male: 1.3) were included in this study. The median CCC volume was lower in females than males (1158 mm3 [IQR: 1751] vs. 3054 mm3 [3851], p<0.001). In cross-sectional analysis, quantified CCC was associated with FBG (9% increase per SD) and HbA1c (7% increase per SD) at the CT exam only in female participants after adjustment for age, race, BMI, and glomerular filtration rate. Only in female participants, quantified CCC was also associated with prior cumulative FBG (3% increase per decile change). In the subgroup of females with zero CAC scores, the adjusted CCC was still associated with FBG (13% increase per SD) at the time of CT exam and with prior cumulative FBG exposure (4% increase per decile change) before the CT exam.ConclusionsThe CCC, a reliably quantified marker in non-contrast cardiac CT, is associated with 10-year cumulative FBG exposure only in female participants, even those with zero CAC.

scholarly journals Thin-section Computed Tomography Detects Long-term Pulmonary Sequelae 3 Years after Novel Influenza A Virus-associated Pneumonia

2015 ◽  
Vol 128 (7) ◽  
pp. 902-908 ◽  
Author(s):  
Zhi-Heng Xing ◽  
Xin Sun ◽  
Long Xu ◽  
Qi Wu ◽  
Li Li ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Influenza A Virus ◽  
Thin Section ◽  
Influenza A ◽  
Novel Influenza A

scholarly journals Blood glucose dynamics during sleep in patients with obstructive sleep apnea and normal glucose tolerance: effects of CPAP therapy

2021 ◽  
Author(s):  
Kimimasa Saito ◽  
Yosuke Okada ◽  
Keiichi Torimoto ◽  
Yoko Takamatsu ◽  
Yoshiya Tanaka
Keyword(s):  
Obstructive Sleep Apnea ◽  
Blood Glucose ◽  
Standard Deviation ◽  
Sleep Apnea ◽  
Sleep Time ◽  
Normal Glucose Tolerance ◽  
High Blood Glucose ◽  
Obstructive Sleep ◽  
Normal Glucose ◽  
Glucose Dynamics

Abstract Purpose Glycemic variability (GV) and hypoglycemia during nighttime are presumed to be associated with fatal bradycardia. The aim of this prospective study was to evaluate blood glucose dynamics during sleep in patients with obstructive sleep apnea syndrome (OSA) and normal glucose tolerance. Methods Patients with OSA and no diabetes who underwent type 1 overnight polysomnography from December 2018 to May 2020 participated in this study. GV was evaluated in all participants for 14 days using a flash glucose monitoring device. Correlations were examined between GV indexes and indexes related to sleep breathing disorders, the effects of treatment with continuous positive airway pressure (CPAP) on these GV indexes, and the characteristics of glucose dynamics in different OSA subtypes classified by sleep stage. Results Among 42 patients with OSA and no diabetes, the standard deviation of GV during sleep correlated significantly with sleep time spent with oxygen saturation <90% (r=0.591, p=0.008). High blood glucose index during sleep correlated significantly with stage N1% (r=0.491, p=0.032) and negatively with stage N2% (r=−0.479, p=0.038). High blood glucose index correlated significantly with sleep time spent with oxygen saturation <90% (r=0.640, p=0.003). The rapid eye movement–related OSA group had a higher incidence of hypoglycemia. One-week with CPAP treatment significantly improved GV during sleep, standard deviation of GV (from 12.1 to 9.0 mg/dL, p<0.001), and high blood glucose index (from 0.7 to 0.4, p=0.006). Conclusions To evaluate GV during sleep in patients with OSA may be useful for clinical risk management. CPAP treatment for 1 week may have an improving GV and high blood glucose index. Clinical trial registration UMIN000038489 2019/11/04, UMIN 000025433 2016/12/27

Dilatation of Vascular Prostheses in Ascending Aortic Position: A Long-Term Follow-Up Computed Tomography Study with Comparison of Different Measurement Methods

2016 ◽  
Vol 66 (03) ◽  
pp. 206-214
Author(s):  
Matthias Endlich ◽  
Christian Krämer ◽  
Chris Probst ◽  
Armin Welz ◽  
Kai Wilhelm ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Measurement Methods ◽  
Point Of View ◽  
Cross Sectional ◽  
Vascular Prostheses ◽  
Aortic Replacement ◽  
Ascending Aortic Replacement ◽  
Long Term Follow Up ◽  
Methods Of Measurement

Background The aim of this study was to evaluate long-term dilatation of Hemashield Gold and Hemashield Platinum vascular prostheses in ascending aortic position using different measurement methods to obtain precise results. Methods Between 1999 and 2007, 73 patients with Stanford type A dissection received ascending aortic replacement with Hemashield Gold and Hemashield Platinum prostheses. Measurements were performed using multiplanar reconstruction mode of electrocardiogram (ECG)-gated, multislice spiral computed tomography (MSCT) in strictly orthogonal cross-sectional planes. Different methods of measurement were compared and maximum dilatation was estimated for different time spans. Results Diameters calculated from the measured circumference showed a significant (p = 0.037) but clinically not relevant difference (0.1 mm) to the mean between the largest and the shortest cross-sectional diameter of the prosthesis. Dilatation after 24.2 ± 10.2 months was 8.5 ± 4.5%. Long-term dilatation after 91.8 ± 34 months amounted to 11.8 ± 4.2%. Conclusion Based on ECG-gated MSCT images, the presented methods of measurement provided reliable results. Long-term analysis shows low dilatation rates for Hemashield prostheses, which therefore can be considered as safe from this point of view. Nevertheless, a maximal dilatation of 20% could be relevant in valve sparing root replacement. It remains unclear if a dilatation like this contributes to the formation of suture aneurysms.

scholarly journals Assisting scalable diagnosis automatically via CT images in the combat against COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bohan Liu ◽  
Pan Liu ◽  
Lutao Dai ◽  
Yanlin Yang ◽  
Peng Xie ◽  
...  
Keyword(s):  
Large Scale ◽  
Area Under The Curve ◽  
Independent Set ◽  
Reference Method ◽  
Ct Images ◽  
Loss Of Life ◽  
Case Identification ◽  
Reverse Transcription Pcr ◽  
Using Data

AbstractThe pandemic of Coronavirus Disease 2019 (COVID-19) is causing enormous loss of life globally. Prompt case identification is critical. The reference method is the real-time reverse transcription PCR (RT-PCR) assay, whose limitations may curb its prompt large-scale application. COVID-19 manifests with chest computed tomography (CT) abnormalities, some even before the onset of symptoms. We tested the hypothesis that the application of deep learning (DL) to 3D CT images could help identify COVID-19 infections. Using data from 920 COVID-19 and 1,073 non-COVID-19 pneumonia patients, we developed a modified DenseNet-264 model, COVIDNet, to classify CT images to either class. When tested on an independent set of 233 COVID-19 and 289 non-COVID-19 pneumonia patients, COVIDNet achieved an accuracy rate of 94.3% and an area under the curve of 0.98. As of March 23, 2020, the COVIDNet system had been used 11,966 times with a sensitivity of 91.12% and a specificity of 88.50% in six hospitals with PCR confirmation. Application of DL to CT images may improve both efficiency and capacity of case detection and long-term surveillance.

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