Artificial intelligence based automatic quantification of epicardial adipose tissue suitable for large scale population studies

To develop a fully automatic model capable of reliably quantifying epicardial adipose tissue (EAT) volumes and attenuation in large scale population studies to investigate their relation to markers of cardiometabolic risk. Non-contrast cardiac CT images from the SCAPIS study were used to train and test a convolutional neural network based model to quantify EAT by: segmenting the pericardium, suppressing noise-induced artifacts in the heart chambers, and, if image sets were incomplete, imputing missing EAT volumes. The model achieved a mean Dice coefficient of 0.90 when tested against expert manual segmentations on 25 image sets. Tested on 1400 image sets, the model successfully segmented 99.4% of the cases. Automatic imputation of missing EAT volumes had an error of less than 3.1% with up to 20% of the slices in image sets missing. The most important predictors of EAT volumes were weight and waist, while EAT attenuation was predicted mainly by EAT volume. A model with excellent performance, capable of fully automatic handling of the most common challenges in large scale EAT quantification has been developed. In studies of the importance of EAT in disease development, the strong co-variation with anthropometric measures needs to be carefully considered

Risk perception after genetic counseling in patients with increased risk of cancer

<p>Abstract</p> <p>Background</p> <p>Counselees are more aware of genetics and seek information, reassurance, screening and genetic testing. Risk counseling is a key component of genetic counseling process helping patients to achieve a realistic view for their own personal risk and therefore adapt to the medical, psychological and familial implications of disease and to encourage the patient to make informed choices <abbrgrp><abbr bid="B1">1</abbr><abbr bid="B2">2</abbr></abbrgrp>.</p> <p>The aim of this study was to conceptualize risk perception and anxiety about cancer in individuals attending to genetic counseling.</p> <p>Methods</p> <p>The questionnaire study measured risk perception and anxiety about cancer at three time points: before and one week after initial genetic counseling and one year after completed genetic investigations. Eligibility criteria were designed to include only index patients without a previous genetic consultation in the family. A total of 215 individuals were included. Data was collected during three years period.</p> <p>Results</p> <p>Before genetic counseling all of the unaffected participants subjectively estimated their risk as higher than their objective risk. Participants with a similar risk as the population overestimated their risk most. All risk groups estimated the risk for children's/siblings to be lower than their own. The benefits of preventive surveillance program were well understood among unaffected participants.</p> <p>The difference in subjective risk perception before and directly after genetic counseling was statistically significantly lower in all risk groups. Difference in risk perception for children as well as for population was also statistically significant. Experienced anxiety about developing cancer in the unaffected subjects was lower after genetic counseling compared to baseline in all groups. Anxiety about cancer had clear correlation to perceived risk of cancer before and one year after genetic investigations.</p> <p>The affected participants overestimated their children's risk as well as risk for anyone in population. Difference in risk perception for children/siblings as for the general population was significant between the first and second measurement time points. Anxiety about developing cancer again among affected participants continued to be high throughout this investigation.</p> <p>Conclusion</p> <p>The participant's accuracy in risk perception was poor, especially in low risk individuals before genetic counseling. There was a general trend towards more accurate estimation in all risk groups after genetic counseling. The importance of preventive programs was well understood. Cancer anxiety was prevalent and associated with risk perception, but decreased after genetic counseling.</p> <p><abbrgrp><abbr bid="B1">1</abbr></abbrgrp> National Society of Genetic Counselors (2005), Genetic Counseling as a Profession. Available at <url>http://www.nsgc.org/about/definition.cfm</url> (accessed November 25th 2007)</p> <p><abbrgrp><abbr bid="B2">2</abbr></abbrgrp> Julian-Reynier C., Welkenhuysen M-, Hagoel L., Decruyenaere M., Hopwood P. (2003) Risk communication strategies: state of the art and effectiveness in the context of cancer genetic services. Eur J of Human Genetics 11, 725736.</p

Computed Tomography and Magnetic Resonance Imaging in Determination of Human Body Composition. Methodological and Applied Studies

Background: Computed tomography (CT) and magnetic resonance imaging (MRI) provide important research opportunities due to their unique capability of characterizing and quantifying tissues and organs. Ionizing radiation is a limitation using CT, and recent developments aiming to improve MRI for determination of body composition have not been validated. An area with special interest in body composition is obesity research. The prevalence of obesity is increasing and abdominal, in particular visceral, obesity is associated with the metabolic syndrome and type 2 diabetes. Aims: I. To evaluate if the radiation dose to the subject can be substantially reduced in assessment of body composition using CT while maintaining accurate measurements of adipose and muscle tissue areas and muscle tissue attenuation. II. To validate a T1 mapping whole-body MRI method, used for assessment of body composition, by comparing it with a whole-body CT method. III. To examine within-scanner reproducibility and between-scanner performance of CT measurements of adipose and muscle tissue areas and liver attenuation. IV. To study the effects of GH treatment on body composition and insulin sensitivity in postmenopausal women with abdominal obesity. Methods: I. Seventeen subjects, covering a wide range of body diameters, were examined using scan parameters chosen to reduce radiation dose as well as standard clinical scan parameters. Tissue areas and muscle CT-numbers were measured. II. Ten patients were examined both by MRI and CT to validate the T1 mapping whole-body MRI method. MRI and CT results were compared regarding tissue areas and volumes, slice by slice, and for the whole body, respectively. III. Reproducibility of the two CT scanners was investigated using duplicates from 50 patients. Between-scanner performance was evaluated by comparison of results from 40 patients. IV. The effects of GH treatment were studied in 40 women in a randomized, placebo-controlled 12-month trial. Changes in body composition and insulin sensitivity were evaluated using CT and clamp-technique, respectively. Results and conclusions: I. In assessment of body composition using CT, the radiation dose to the subject was reduced to 2-60 % of standard dose used for diagnostic purposes while maintaining accurate measurements of adipose and muscle tissue areas and muscle tissue attenuation,. The resulting effective dose for a single slice examination is <0.1mSv, a dose level associated with trivial risk. Therefore, CT can be justified for body composition assessment even in large populations or for repeated examinations. II. Compared with CT, the MRI method slightly overestimated subcutaneous adipose tissue volume and slightly underestimated visceral adipose tissue volume, but it can be considered sufficiently accurate for whole-body measurements of adipose tissue volumes. III. Within-scanner reproducibility and between-scanner agreement were high for measurements of adipose and muscle tissue area. For measurements of liver attenuation, within-scanner reproducibility was high while a systematic bias was revealed in comparison between scanners. Therefore, comparison of CT numbers for liver from different scanners may be unreliable. IV. GH treatment of postmenopausal women with abdominal obesity reduced visceral adipose tissue and improved insulin sensitivity. CT revealed adipose tissue changes not detectable by waist-to-hip ratio, sagittal diameter, or waist circumference

Minimal risk of contrast-induced kidney injury in a randomly selected cohort with mildly reduced GFR

Objectives: Previous large studies of contrast-induced or post-contrast acute kidney injury (CI-AKI/PC-AKI) have been observational, and mostly retrospective, often with patients undergoing non-enhanced CT as controls. This carries risk of inclusion bias that makes the true incidence of PC-AKI hard to interpret. Our aim was to determine the incidence of PC-AKI in a large, randomly selected cohort, comparing the serum creatinine (Scr) changes after contrast medium exposure with the normal intraindividual fluctuation in Scr. Methods: In this prospective study of 1009 participants (age 50–65 years, 48% females) in the Swedish CArdioPulmonary bioImage Study (SCAPIS), with estimated glomerular filtration rate (eGFR) ≥ 50 mL/min, all received standard dose intravenous iohexol at coronary CT angiography (CCTA). Two separate pre-CCTA Scr samples and a follow-up sample 2–4 days post-CCTA were obtained. Change in Scr was statistically analyzed and stratification was used in the search of possible risk factors. Results: Median increase of Scr post-CCTA was 0–2 μmol/L. PC-AKI was observed in 12/1009 individuals (1.2%) according to the old ESUR criteria (> 25% or > 44 μmol/L Scr increase) and 2 individuals (0.2%) when using the updated ESUR criteria (≥ 50% or ≥ 27 μmol/L Scr increase). Possible risk factors (e.g., diabetes, age, eGFR, NSAID use) did not show increased risk of developing PC-AKI. The mean effect of contrast media on Scr did not exceed the intraindividual Scr fluctuation. Conclusions: Iohexol administration to a randomly selected cohort with mildly reduced eGFR is safe, and PC-AKI is very rare, occurring in only 0.2% when applying the updated ESUR criteria. Key Points: • Iohexol administration to a randomly selected cohort, 50–65 years old with mildly reduced eGFR, is safe and PC-AKI is very rare. • Applying the updated ESUR PC-AKI criteria resulted in fewer cases, 0.2% compared to 1.2% using the old ESUR criteria in this cohort with predominantly mild reduction of renal function. • The mean effect of CM on Scr did not exceed the intraindividual background fluctuation of Scr, regardless of potential risk factors, such as diabetes or NSAID use in our cohort of 1009 individuals

Validity of physician-diagnosed COPD in relation to spirometric definitions of COPD in a general population aged 50â-64 years - the SCAPIS pilot study

BACKGROUND: In epidemiological studies, items about physician-diagnosed COPD are often used. There is a lack of validation and standardization of these items. MATERIALS AND METHODS: In a general population-based study, 1,050 subjects completed a questionnaire and performed spirometry, including forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC) after inhalation of 400 µg of salbutamol. COPD was defined as the ratio of FEV1/FVC &lt;0.7 after bronchodilation. Physician-diagnosed COPD was defined as an affirmative answer to the single item: "Have you ever had COPD diagnosed by a physician?", physician-diagnosed COPD/emphysema as an affirmative answer to any of the two single items; "Have you ever had COPD diagnosed by a physician?" or "Have you ever been told by a physician that you have emphysema?", physician-diagnosed chronic bronchitis as an affirmative answer to; "Have you ever been told by a physician that you have chronic bronchitis?" and physician-diagnosed COPD, emphysema or chronic bronchitis was defined as an affirmative answer to either of the three items above. RESULTS: For the single item about physician-diagnosed COPD, the sensitivity was around 0.11 and the specificity was almost 0.99 in relation to COPD. The sensitivity of the combined items about COPD/emphysema in detecting COPD was 0.11 and the specificity was high, 0.985. When the items about physician-diagnosed COPD, emphysema or chronic bronchitis were merged as one entity, the sensitivity went up (0.13) and the specificity went down (0.95). CONCLUSION: Items about physician-diagnosed COPD have low sensitivity but a very high specificity, indicating that these items will minimize the proportion of false positives. The low sensitivity will underestimate the total burden of COPD in the general population. Items about physician-diagnosed COPD may be used in studies of risk factors for COPD, but are not recommended in prevalence studies

Automated analysis of liver fat, muscle and adipose tissue distribution from CT suitable for large-scale studies.

Computed Tomography (CT) allows detailed studies of body composition and its association with metabolic and cardiovascular disease. The purpose of this work was to develop and validate automated and manual image processing techniques for detailed and efficient analysis of body composition from CT data. The study comprised 107 subjects examined in the Swedish CArdioPulmonary BioImage Study (SCAPIS) using a 3-slice CT protocol covering liver, abdomen, and thighs. Algorithms were developed for automated assessment of liver attenuation, visceral (VAT) and subcutaneous (SAT) abdominal adipose tissue, thigh muscles, subcutaneous, subfascial (SFAT) and intermuscular adipose tissue. These were validated using manual reference measurements. SFAT was studied in selected subjects were the fascia lata could be visually identified (approx. 5%). In addition, precision of manual measurements of intra- (IPAT) and retroperitoneal adipose tissue (RPAT) and deep- and superficial SAT was evaluated using repeated measurements. Automated measurements correlated strongly to manual reference measurements. The SFAT depot showed the weakest correlation (r = 0.744). Automated VAT and SAT measurements were slightly, but significantly overestimated (≤4.6%, p ≤ 0.001). Manual segmentation of abdominal sub-depots showed high repeatability (CV ≤ 8.1%, r ≥ 0.930). We conclude that the low dose CT-scanning and automated analysis makes the setup suitable for large-scale studies

Automatic pericardium segmentation and quantification of epicardial fat from computed tomography angiography

Recent findings indicate a strong correlation between the risk of future heart disease and the volume of adipose tissue inside of the pericardium. So far, large-scale studies have been hindered by the fact that manual delineation of the pericardium is extremely time-consuming and that existing methods for automatic delineation lack accuracy. An efficient and fully automatic approach to pericardium segmentation and epicardial fat volume (EFV) estimation is presented, based on a variant of multi-atlas segmentation for spatial initialization and a random forest classifier for accurate pericardium detection. Experimental validation on a set of 30 manually delineated computer tomography angiography volumes shows a significant improvement on state-of-the-art in terms of EFV estimation [mean absolute EFV difference: 3.8 ml (4.7%), Pearson correlation: 0.99] with run times suitable for large-scale studies (52 s). Further, the results compare favorably with interobserver variability measured on 10 volumes

The Hospital Anxiety and Depression Scale : a meta confirmatory factor analysis

Objective: To systematically evaluate the latent structure of the Hospital Anxiety and Depression Scale (HADS) through reanalysis of previous studies and meta confirmatory factor analysis (CFA). Method: Data from 28 samples were obtained from published studies concerning the latent structure of the HADS. Ten models were considered, including eight previously identified models and two bifactor models. The fit of each model was assessed separately in each sample and by meta CFA. Meta CFA was conducted using all samples and using subgroups consisting of community samples, cardiovascular disease samples and samples from studies administering the English language version of the HADS. Results: A bifactor model including all items loading onto a general distress factor and two orthogonal anxiety and depression group factors provided the best fit for the majority of samples. Meta CFA provided further support for the bifactor model with two group factors. This was the case using all samples, as well as all subgroup analyses. The general distress factor explained 73% of the covariance between items, with the (autonomic) anxiety and (anhedonic) depression factors explaining 11% and 16%, respectively. Conclusion: A bifactor structure provides the most acceptable empirical explanation for the HADS correlation structure. Due to the presence of a strong general factor, the HADS does not provide good separation between symptoms of anxiety and depression. We recommend it is best used as a measure of general distress.Peer reviewe