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BACKGROUND - Smokers have lower risk of obesity, which some consider a "beneficial" side effect of smoking. However, some studies suggest that smoking is simultaneously associated with higher central adiposity and, more specifically, ectopic adipose deposition. Little is known about the association of smoking with intermuscular adipose tissue (IMAT), an ectopic adipose depot associated with cardiovascular disease (CVD) risk and a key determinant of muscle quality and function. We tested the hypothesis that smokers have higher abdominal IMAT and lower lean muscle quality than never smokers.
METHODS AND FINDINGS - We measured abdominal muscle total, lean, and adipose volumes (in cubic centimeters) and attenuation (in Hounsfield units [HU]) along with subcutaneous (SAT) and visceral adipose tissue (VAT) volumes using computed tomography (CT) in 3,020 middle-aged Coronary Artery Risk Development in Young Adults (CARDIA) participants (age 42-58, 56.3% women, 52.6% white race) at the year 25 (Y25) visit. The longitudinal CARDIA study was initiated in 1985 with the recruitment of young adult participants (aged 18-30 years) equally balanced by female and male sex and black and white race at 4 field centers located in Birmingham, AL, Chicago, IL, Minneapolis, MN, and Oakland, CA. Multivariable linear models included potential confounders such as physical activity and dietary habits along with traditional CVD risk factors. Current smokers had lower BMI than never smokers. Nevertheless, in the fully adjusted multivariable model with potential confounders, including BMI and CVD risk factors, adjusted mean (95% CI) IMAT volume was 2.66 (2.55-2.76) cm3 in current smokers (n = 524), 2.36 (2.29-2.43) cm3 in former smokers (n = 944), and 2.23 (2.18-2.29) cm3 in never smokers (n = 1,552) (p = 0.007 for comparison of former versus never smoker, and p < 0.001 for comparison of current smoker versus never and former smoker). Moreover, compared to participants who never smoked throughout life (41.6 [41.3-41.9] HU), current smokers (40.4 [39.9-40.9] HU) and former smokers (40.8 [40.5-41.2] HU) had lower lean muscle attenuation suggesting lower muscle quality in the fully adjusted model (p < 0.001 for comparison of never smokers with either of the other two strata). Among participants who had ever smoked, pack-years of smoking exposure were directly associated with IMAT volume (β [95% CI]: 0.017 [0.010-0.025]) (p < 0.001). Despite having less SAT, current smokers also had higher VAT/SAT ratio than never smokers. These findings must be viewed with caution as residual confounding and/or reverse causation may contribute to these associations.
CONCLUSIONS - We found that, compared to those who never smoked, current and former smokers had abdominal muscle composition that was higher in adipose tissue volume, a finding consistent with higher CVD risk and age-related physical deconditioning. These findings challenge the belief that smoking-associated weight loss or maintenance confers a health benefit.
Background Although several deep learning (DL) calcium scoring methods have achieved excellent performance for specific CT protocols, their performance in a range of CT examination types is unknown. Purpose To evaluate the performance of a DL method for automatic calcium scoring across a wide range of CT examination types and to investigate whether the method can adapt to different types of CT examinations when representative images are added to the existing training data set. Materials and Methods The study included 7240 participants who underwent various types of nonenhanced CT examinations that included the heart: coronary artery calcium (CAC) scoring CT, diagnostic CT of the chest, PET attenuation correction CT, radiation therapy treatment planning CT, CAC screening CT, and low-dose CT of the chest. CAC and thoracic aorta calcification (TAC) were quantified using a convolutional neural network trained with 1181 low-dose chest CT examinations (baseline), a small set of examinations of the respective type supplemented to the baseline (data specific), and a combination of examinations of all available types (combined). Supplemental training sets contained 199-568 CT images depending on the calcium burden of each population. The DL algorithm performance was evaluated with intraclass correlation coefficients (ICCs) between DL and manual (Agatston) CAC and (volume) TAC scoring and with linearly weighted κ values for cardiovascular risk categories (Agatston score; cardiovascular disease risk categories: 0, 1-10, 11-100, 101-400, >400). Results At baseline, the DL algorithm yielded ICCs of 0.79-0.97 for CAC and 0.66-0.98 for TAC across the range of different types of CT examinations. ICCs improved to 0.84-0.99 (CAC) and 0.92-0.99 (TAC) for CT protocol-specific training and to 0.85-0.99 (CAC) and 0.96-0.99 (TAC) for combined training. For assignment of cardiovascular disease risk category, the κ value for all test CT scans was 0.90 (95% confidence interval [CI]: 0.89, 0.91) for the baseline training. It increased to 0.92 (95% CI: 0.91, 0.93) for both data-specific and combined training. Conclusion A deep learning calcium scoring algorithm for quantification of coronary and thoracic calcium was robust, despite substantial differences in CT protocol and variations in subject population. Augmenting the algorithm training with CT protocol-specific images further improved algorithm performance. © RSNA, 2020 See also the editorial by Vannier in this issue.
BACKGROUND - Chronic subdural hematoma evacuation can be achieved in select patients through bedside placement of the Subdural Evacuation Port System (SEPS; Medtronic, Inc., Dublin, Ireland). This procedure involves drilling a burr hole at the thickest part of the hematoma. Identifying this location is often difficult, given the variable tilt of available imaging and distant anatomic landmarks. This paper evaluates the feasibility and accuracy of a bedside navigation system that relies on visible light-based 3-dimensional (3D) scanning and image registration to a pre-procedure computed tomography scan. The information provided by this system may increase accuracy of the burr hole location.
METHODS - In Part 1, the accuracy of this system was evaluated using a rigid 3D printed phantom head with implanted fiducials. In Part 2, the navigation system was tested on 3 patients who underwent SEPS placement.
RESULTS - The error in registration of this system was less than 2.5 mm when tested on a rigid 3D printed phantom head. Fiducials located in the posterior aspect of the head were difficult to reliably capture. For the 3 patients who underwent 5 SEPS placements, the distance between anticipated SEPS burr hole location based on registration and actual burr hole location was less than 1cm.
CONCLUSIONS - A bedside cranial navigation system based on 3D scanning and image registration has been introduced. Such a system may increase the success rate of bedside procedures, such as SEPS placement. However, technical challenges such as the ability to scan hair and practical challenges such as minimization of patient movement during scans must be overcome.
Copyright © 2020 Elsevier Inc. All rights reserved.
INTRODUCTION - Double aortic arch is a rare congenital malformation of the aortic arch that most frequently presents in childhood. Early surgical intervention typically yields excellent outcomes.
OBJECTIVES - To describe aortotracheal fistula as a rare, yet serious complication of vascular ring and subsequent aortic aneurysm in an adult patient.
METHODS - Clinical history, as well as radiographic and endoscopic imaging were obtained to describe the development, diagnosis, and clinical course of this patient's aortotracheal fistula. Additionally, follow up data was obtained to document the healing of this fistula after surgical repair.
RESULTS - We describe a case of a 46-year-old male with DiGeorge Syndrome and a double aortic arch, repaired in childhood, which developed into an aortotracheal fistula after tracheostomy placement as an adult.
CONCLUSIONS - This case demonstrates that dangerous complications of a double aortic arch can persist into adulthood, even after surgical repair in infancy. Each patient's unique anatomy must be considered when thinking about airway management and prevention of complications of this rare congenital anomaly.
PURPOSE - As deep neural networks achieve more success in the wide field of computer vision, greater emphasis is being placed on the generalizations of these models for production deployment. With sufficiently large training datasets, models can typically avoid overfitting their data; however, for medical imaging it is often difficult to obtain enough data from a single site. Sharing data between institutions is also frequently nonviable or prohibited due to security measures and research compliance constraints, enforced to guard protected health information (PHI) and patient anonymity.
METHODS - In this paper, we implement cyclic weight transfer with independent datasets from multiple geographically disparate sites without compromising PHI. We compare results between single-site learning (SSL) and multisite learning (MSL) models on testing data drawn from each of the training sites as well as two other institutions.
RESULTS - The MSL model attains an average dice similarity coefficient (DSC) of 0.690 on the holdout institution datasets with a volume correlation of 0.914, respectively corresponding to a 7% and 5% statistically significant improvement over the average of both SSL models, which attained an average DSC of 0.646 and average correlation of 0.871.
CONCLUSIONS - We show that a neural network can be efficiently trained on data from two physically remote sites without consolidating patient data to a single location. The resulting network improves model generalization and achieves higher average DSCs on external datasets than neural networks trained on data from a single source.
© 2019 American Association of Physicists in Medicine.
PURPOSE - Manually tracing regions of interest (ROIs) within the liver is the de facto standard method for measuring liver attenuation on computed tomography (CT) in diagnosing nonalcoholic fatty liver disease (NAFLD). However, manual tracing is resource intensive. To address these limitations and to expand the availability of a quantitative CT measure of hepatic steatosis, we propose the automatic liver attenuation ROI-based measurement (ALARM) method for automated liver attenuation estimation.
METHODS - The ALARM method consists of two major stages: (a) deep convolutional neural network (DCNN)-based liver segmentation and (b) automated ROI extraction. First, liver segmentation was achieved using our previously developed SS-Net. Then, a single central ROI (center-ROI) and three circles ROI (periphery-ROI) were computed based on liver segmentation and morphological operations. The ALARM method is available as an open source Docker container (https://github.com/MASILab/ALARM).
RESULTS - Two hundred and forty-six subjects with 738 abdomen CT scans from the African American-Diabetes Heart Study (AA-DHS) were used for external validation (testing), independent from the training and validation cohort (100 clinically acquired CT abdominal scans). From the correlation analyses, the proposed ALARM method achieved Pearson correlations = 0.94 with manual estimation on liver attenuation estimations. When evaluating the ALARM method for detection of nonalcoholic fatty liver disease (NAFLD) using the traditional cut point of < 40 HU, the center-ROI achieved substantial agreements (Kappa = 0.79) with manual estimation, while the periphery-ROI method achieved "excellent" agreement (Kappa = 0.88) with manual estimation. The automated ALARM method had reduced variability compared to manual measurements as indicated by a smaller standard deviation.
CONCLUSIONS - We propose a fully automated liver attenuation estimation method termed ALARM by combining DCNN and morphological operations, which achieved "excellent" agreement with manual estimation for fatty liver detection. The entire pipeline is implemented as a Docker container which enables users to achieve liver attenuation estimation in five minutes per CT exam.
© 2019 American Association of Physicists in Medicine.
OBJECTIVES - To describe tracheobronchial disease in patients with granulomatosis with polyangiitis (GPA) and evaluate the utility of dynamic expiratory CT to detect large-airway disease.
METHODS - Demographic and clinical features associated with the presence of subglottic stenosis (SGS) or endobronchial involvement were assessed in a multicentre, observational cohort of patients with GPA. A subset of patients with GPA from a single-centre cohort underwent dynamic chest CT to evaluate the airways.
RESULTS - Among 962 patients with GPA, SGS and endobronchial disease were identified in 95 (10%) and 59 (6%) patients, respectively. Patients with SGS were more likely to be female (72% vs 53%, P < 0.01), younger at time of diagnosis (36 vs 49 years, P < 0.01), and have saddle-nose deformities (28% vs 10%, P < 0.01), but were less likely to have renal involvement (39% vs 62%, P < 0.01). Patients with endobronchial disease were more likely to be PR3-ANCA positive (85% vs 66%, P < 0.01), with more ENT involvement (97% vs 77%, P < 0.01) and less renal involvement (42% vs 62%, P < 0.01). Disease activity in patients with large-airway disease was commonly isolated to the subglottis/upper airway (57%) or bronchi (32%). Seven of 23 patients screened by dynamic chest CT had large-airway pathology, including four patients with chronic, unexplained cough, discovered to have tracheobronchomalacia.
CONCLUSION - SGS and endobronchial disease occur in 10% and 6% of patients with GPA, respectively, and may occur without disease activity in other organs. Dynamic expiratory chest CT is a potential non-invasive screening test for large-airway involvement in GPA.
© The Author(s) 2019. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: firstname.lastname@example.org.
Background The relationship of coronary artery calcium (CAC) with adverse cardiac remodeling is not well established. We aimed to study the association of CAC in middle age and change in CAC from early adulthood to middle age with left ventricular (LV) function. Methods CAC score was measured by computed tomography at CARDIA study (Coronary Artery Risk Development in Young Adults) year-15 examination and at year-25 examination (Y25) in 3043 and 3189 participants, respectively. CAC score was assessed as a continuous variable and log-transformed to account for nonlinearity. Change in CAC from year-15 examination to Y25 was evaluated as the absolute difference of log-transformed CAC from year-15 examination to Y25. LV structure and function were evaluated by echocardiography at Y25. Results At Y25, mean age was 50.1±3.6 years, 56.6% women, 52.4% black. In the multivariable analysis at Y25, higher CAC was related to higher LV mass (β=1.218; adjusted P=0.007), higher LV end-diastolic volume (β=0.811; adjusted P=0.007), higher LV end-systolic volume (β=0.350; adjusted P=0.048), higher left atrial volume (β=0.214; adjusted P=0.009), and higher E/e' ratio (β=0.059; adjusted P=0.014). CAC was measured at both year-15 examination and Y25 in 2449 individuals. Higher change in CAC score during follow-up was independently related to higher LV mass index in blacks (β=4.789; adjusted P<0.001), but not in whites (β=1.051; adjusted P=0.283). Conclusions Higher CAC in middle age is associated with higher LV mass and volumes and worse LV diastolic function. Being free of CAC from young adulthood to middle age correlates to better LV function at middle age. Higher change in CAC score during follow-up is independently related to higher LV mass index in blacks.
INTRODUCTION - Cross-sectional data note lower levels of testosterone and sex hormone-binding globulin (SHBG) levels in men with nonalcoholic fatty liver disease (NAFLD). Whether sex hormone levels in young men are predictive of later risk of NAFLD is not known.
METHODS - Among men in the prospective population-based multicenter Coronary Artery Risk Development in Young Adults study (mean age 50; n = 837), we assessed whether testosterone and SHBG levels measured at study year 10 (median age 35 years) were associated with prevalent NAFLD at study year 25. NAFLD was defined using noncontrast abdominal computed tomography (CT) scan after excluding other causes of hepatic steatosis. The association of testosterone and SHBG with prevalent NAFLD was assessed by logistic regression.
RESULTS - Total testosterone levels in young men were inversely associated with subsequent prevalent NAFLD on unadjusted analysis (odds ratio [OR] 0.64, 95% confidence interval 0.53-0.7, P < 0.001), although no longer significant after adjustment for year 10 metabolic covariates as well as change in metabolic covariates from years 10 to 25 (OR 0.99, 95% confidence interval 0.76-1.27). In contrast, there was a significant inverse association of SHBG with prevalent NAFLD, independent of testosterone and metabolic covariates (OR 0.68, OR 0.51-0.92, P = 0.013). On formal mediation testing, visceral adiposity was found to explain ∼41.0% (95% confidence interval 27%-73%) of the association of lower SHBG with prevalent NAFLD.
CONCLUSIONS - Lower levels of SHBG in young men are associated with increase in prevalent NAFLD in middle age, independent of comprehensive metabolic risk factors. SHBG may provide a novel marker of NAFLD risk in young men.
BACKGROUND - Colorectal liver metastases that demonstrate a complete radiographic response during chemotherapy are increasingly common with advances in chemotherapy regimens and are described as disappearing liver metastases (DLMs). However, these DLMs often continue to harbor residual viable tumor. If these tumors are found in the operating room with ultrasound (US), they should be treated. The intraoperative sonographic visualization of these lesions, however, can be hindered by chemotherapy-associated liver parenchyma changes. The objective of this study was to evaluate the use of an intraoperative image guidance system, Explorer (Analogic Corporation, Peabody, MA), to aid surgeons in the identification of DLMs initially undetected by US alone.
STUDY DESIGN - In a single-arm prospective trial, patients with colorectal liver metastases undergoing liver resection and/or ablation with one or more DLMs during neoadjuvant chemotherapy were enrolled. Intraoperatively, DLMs were localized with conventional US. Any DLM not found by conventional US was re-evaluated with the image guidance system. The primary outcome was the proportion of sonographically occult DLMs subsequently located by image-guided US.
RESULTS - Between April 2016 and November 2017, 25 patients with 61 DLMs were enrolled. Thirty-eight DLMs (62%) in 14 patients (56%) were not identified with US alone. Six (16%) DLMs in five patients (36%) were subsequently located with assistance of the image guidance system. The image guidance changed the intraoperative surgical plan in four of these patients.
CONCLUSIONS - Image guidance can aid surgeons in the identification of initially sonographically occult DLMs and facilitate the complete surgical clearance of all sites of liver disease.