Medical Imaging Convention [rescheduled] Mar 09, 2021 - Mar 10, 2021 — National Exhibition Centre, Birmingham, England
9th SINAPSE Neuro-oncology Imaging Meeting [rescheduled] Mar 11, 2021 09:30 AM - 03:30 PM — West Park Conferencing & Events, 319 Perth Road, Dundee DD2 1NN
Total Body PET 2020 conference [rescheduled] Jun 05, 2021 - Jun 07, 2021 — McEwan Hall, University of Edinburgh

eLearning

SINAPSE experts from around Scotland have developed ten online modules designed to explain medical imaging. They are freely available and are intended for non-specialists.


Edinburgh Imaging Academy at the University of Edinburgh offers the following online programmes through a virtual learning environment:

Neuroimaging for Research MSc/Dip/Cert

Imaging MSc/Dip/Cert

PET-MR Principles & Applications Cert

Applied Medical Image Analysis Cert

Online Short Courses

Quantitative computed tomography measures of pectoralis muscle area and disease severity in chronic obstructive pulmonary disease. A cross-sectional study

Author(s): M. L. McDonald, A. A. Diaz, J. C. Ross, R. San Jose Estepar, L. Zhou, E. A. Regan, E. Eckbo, N. Muralidhar, C. E. Come, M. H. Cho, C. P. Hersh, C. Lange, E. Wouters, R. H. Casaburi, H. O. Coxson, W. Macnee, S. I. Rennard, D. A. Lomas, A. Agusti, B. R. Celli, J. L. Black-Shinn, G. L. Kinney, S. M. Lutz, J. E. Hokanson, E. K. Silverman, G. R. Washko

Abstract:
RATIONALE: Muscle wasting in chronic obstructive pulmonary disease (COPD) is associated with a poor prognosis and is not readily assessed by measures of body mass index (BMI). BMI does not discriminate between relative proportions of adipose tissue and lean muscle and may be insensitive to early pathologic changes in body composition. Computed tomography (CT)-based assessments of the pectoralis muscles may provide insight into the clinical significance of skeletal muscles in smokers. OBJECTIVES: We hypothesized that objective assessment of the pectoralis muscle area on chest CT scans provides information that is clinically relevant and independent of BMI. METHODS: Data from the ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) Study (n = 73) were used to assess the relationship between pectoralis muscle area and fat-free mass. We then used data in a subset (n = 966) of a larger cohort, the COPDGene (COPD Genetic Epidemiology) Study, to explore the relationship between pectoralis muscle area and COPD-related traits. MEASUREMENTS AND MAIN RESULTS: We first investigated the correlation between pectoralis muscle area and fat-free mass, using data from a subset of participants in the ECLIPSE Study. We then further investigated pectoralis muscle area in COPDGene Study participants and found that higher pectoralis muscle area values were associated with greater height, male sex, and younger age. On subsequent clinical correlation, compared with BMI, pectoralis muscle area was more significantly associated with COPD-related traits, including spirometric measures, dyspnea, and 6-minute-walk distance (6MWD). For example, on average, each 10-cm(2) increase in pectoralis muscle area was associated with a 0.8-unit decrease in the BODE (Body mass index, Obstruction, Dyspnea, Exercise) index (95% confidence interval, -1.0 to -0.6; P < 0.001). Furthermore, statistically significant associations between pectoralis muscle area and COPD-related traits remained even after adjustment for BMI. CONCLUSIONS: CT-derived pectoralis muscle area provides relevant indices of COPD morbidity that may be more predictive of important COPD-related traits than BMI. However, the relationship with clinically relevant outcomes such as hospitalization and death requires additional investigation. Pectoralis muscle area is a convenient measure that can be collected in the clinical setting in addition to BMI.

Full version: Available here

Click the link to go to an external website with the full version of the paper


ISBN: 2325-6621 (Electronic) 2325-6621 (Linking)
Publication Year: 2014
Periodical: Ann Am Thorac Soc
Periodical Number: 3
Volume: 11
Pages: 326-34
Author Address: 1 Channing Division of Network Medicine, Harvard Medical School, Boston, Massachusetts.