From the Authors:
We thank Dr. Durhan for the interest in our study (1). We agree that the anatomical region for subcutaneous fat analysis is important and must be carefully selected to ensure validity of the measurements. Although there is rationale to consider that breast tissue could theoretically interfere with subcutaneous fat measurements at the level of the carina, this is not supported by data. Previous research conducted by our group has shown that the subcutaneous fat cross-sectional area (CSA) at the level of the carina is associated with whole-body fat, body mass index (BMI), and waist circumference in individuals with advanced lung disease (2). Notably, patients with breast tissue at the level of the carina were included in this analysis and we did not find that breast tissue interfered with our analysis of subcutaneous or muscle CSA. Furthermore, there was no difference across three slices at the level of the carina for subcutaneous fat or pectoral muscle CSA between female and male subjects. Similar associations were found with mediastinal fat CSA, where there was no interference from breast tissue, but it is important to highlight that subcutaneous and visceral adiposity stores are not interchangeable (3, 4).
Although it is true that variability exists in breast density and gynecomastia, fibrous and glandular tissue would not be captured in our CSA measurements based on the differences in attenuation (5). Given that only around 10% of women have primarily fatty breast tissue (Breast Imaging Reporting and Database System score A), this may explain why the theoretical increase in subcutaneous fat CSA in these patients has not been shown to influence the overall relationship with BMI (6). In addition, a high proportion of breast tissue in women and gynecomastia in men are only fully appreciated at a level below the carina (7).
To further confirm the validity of measuring subcutaneous fat CSA at the level of the carina, we assessed the correlation between subcutaneous fat CSA and BMI stratified by sex. A strong correlation between these variables was observed in both females (N = 61; Pearson correlation coefficient, 0.75; P < 0.0001) and males (N = 95; Pearson correlation coefficient, 0.76; P < 0.0001).
Finally, we would like to highlight the advantage of measuring CSA at the level of the carina due to high reproducibility and ease of identification. There is significant heterogeneity in anatomical regions and tissue selected for CSA analysis in the thorax (8). Our study lends support to previous literature showing that the carina is a valid and reliable site for CSA measurements as a surrogate for body composition.
Footnotes
Supported by the Clinical Frailty Network grant (M.D.E.).
Author disclosures are available with the text of this letter at www.atsjournals.org.
References
- 1. Elfassy MD, Ferreyro BL, Rozenberg D, Sklar MC, Mathur S, Detsky ME, et al. Association of thoracic computed tomographic measurements and outcomes in patients with hematologic malignancies requiring mechanical ventilation. Ann Am Thorac Soc. 2021;18:1219–1226. doi: 10.1513/AnnalsATS.202008-914OC. [DOI] [PubMed] [Google Scholar]
- 2. Mathur S, Rozenberg D, Verweel L, Orsso CE, Singer LG. Chest computed tomography is a valid measure of body composition in individuals with advanced lung disease. Clin Physiol Funct Imaging. 2020;40:360–368. doi: 10.1111/cpf.12652. [DOI] [PubMed] [Google Scholar]
- 3. Fox CS, Massaro JM, Hoffmann U, Pou KM, Maurovich-Horvat P, Liu CY, et al. Abdominal visceral and subcutaneous adipose tissue compartments: association with metabolic risk factors in the Framingham Heart Study. Circulation. 2007;116:39–48. doi: 10.1161/CIRCULATIONAHA.106.675355. [DOI] [PubMed] [Google Scholar]
- 4. Taksali SE, Caprio S, Dziura J, Dufour S, Calí AM, Goodman TR, et al. High visceral and low abdominal subcutaneous fat stores in the obese adolescent: a determinant of an adverse metabolic phenotype. Diabetes. 2008;57:367–371. doi: 10.2337/db07-0932. [DOI] [PubMed] [Google Scholar]
- 5. Harish MG, Konda SD, MacMahon H, Newstead GM. Breast lesions incidentally detected with CT: what the general radiologist needs to know. Radiographics. 2007;27:S37–S51. doi: 10.1148/rg.27si075510. [DOI] [PubMed] [Google Scholar]
- 6.Sickles EA, D’Orsi CJ, Bassett LW. ACR BI-RADS atlas, breast imaging reporting and data system. Reston, VA: American College of Radiology; 2013. ACR BI-RADS mammography. [Google Scholar]
- 7.Cahill D, Orland M, Miller G. Atlas of human cross-sectional anatomy: with CT and MR images. 3rd ed. New York, NY: Wiley Liss; 1995. [Google Scholar]
- 8. Rozenberg D, Orsso CE, Chohan K, Orchanian-Cheff A, Nourouzpour S, Nicholson JM, et al. Clinical outcomes associated with computed tomography-based body composition measures in lung transplantation: a systematic review. Transpl Int. 2020;33:1610–1625. doi: 10.1111/tri.13749. [DOI] [PubMed] [Google Scholar]
