Back to Articles

Proposal for New Diagnostic Criteria for Sarcopenia Based on CT Imaging in Saudi Population: A Novel Method in Oncology Research

Submission Type:

1 Department of Radiology, Dammam Medical Complex, Dammam, Saudi Arabia

2 Department of Radiology, King Fahad Specialist Hospital, Dammam, Saudi Arabia

3 Department of Radiology, King Fahad Specialist Hospital, Dammam, Saudi Arabia

4 Department of Radiology, King Fahad Hospital Hofuf, Alahsa, Saudi Arabia

Abstract

Purpose:
Sarcopenia is regarded as a diagnostic and prognostic marker for various diseases and health issues. Several studies have used CT to measure psoas muscle surface area (PMA) to define sarcopenia. However, the cut-off values based on CT imaging remain undetermined in Saudi population. The aim of this study is to provide sex and age-specific percentiles for PMA, psoas muscle index (PMI) and psoas muscle density (PMD) in Saudi population and to establish a formula to calculate the standard PMA based on individual anthropometric measurement.


Methods:

Pre-operative CT imaging at the third lumbar vertebra level was used to measure PMA, PMI and PMD in 400 adult donors for living donor kidney transplantation. We determined the age and sex -specific cut-off values of PMA in order to define low skeletal muscle mass. A formula was generated to calculate the standard PMA using body weight as the independent variable and further validated on a new dataset involving individuals from the general population.


Results:

Males had significantly higher measurements of PMA than females (10.7 ± 2.7 cm2 vs 5.8 ± 1.9 cm2). PMA was positively correlated with body weight in both genders. The estimated PMA using the generated formula correlated strongly with the manually traced PMA measurements. The mean differences between estimated and measured PMA values were 0.81 ± 1.70 cm2 among males and 0.17 ± 1.19 cm2 among females. These outcomes emphasize the validity of our predictive computations.

Conclusion:

Defining population specific cut-off values of PMA and PMI aids in CT based opportunistic screening for sarcopenia.

Main Subjects

Training
Radiological Education
Quality Assurance
+4

Keywords

Sarcopenia
Musculoskeletal Imaging
CT
Screening
Oncology

License

Journal License

This work is licensed under a Creative Commons Attribution 4.0 International license

issue-coversheet

3, 2nd Issue

Files

Download PDF

Article Insights

Article Views

3

PDF Downloads

0

References

  1. 1.
    [1] Janssen I. (2011). The epidemiology of sarcopenia. Clinics in geriatric medicine, 27(3), 355–363. https://doi.org/10.1016/j.cger.2011.03.004
  2. 2.
    [2] Wang, C., & Bai, L. (2012). Sarcopenia in the elderly: basic and clinical issues. Geriatrics & gerontology international, 12(3), 388–396. https://doi.org/10.1111/j.1447-0594.2012.00851.x
  3. 3.
    [3] Chen LK, Liu LK, Woo J, et al. Sarcopenia in Asia: consensus report of the Asian Working Group for Sarcopenia.J Am Med Dir Assoc. 2014;15(2):95-101. doi:10.1016/j.jamda.2013.11.025
  4. 4.
    Saudi Journal of Radiology
  5. 5.
    [4] Cruz-Jentoft AJ, Baeyens JP, Bauer JM, et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working
  6. 6.
    [5] Group on Sarcopenia in Older People. Age Ageing. 2010;39(4):412-423. doi:10.1093/ageing/afq034
  7. 7.
    [6] Beaudart C, McCloskey E, Bruyère O, et al. Sarcopenia in daily practice: assessment and management. BMC Geriatr. 2016;16(1):170. Published 2016 Oct 5. doi:10.1186/s12877-016-0349-4
  8. 8.
    [7] Dawson A, Dennison E. Measuring the musculoskeletal aging phenotype. Maturitas.2016;93:13-17.doi:10.1016/j.maturitas.2016.04.014
  9. 9.
    [8] Prado CM, Lieffers JR, McCargar LJ, et al. Prevalence and clinical implications of sarcopenic obesity in patients with solid tumours of the respiratory and gastrointestinal tracts: a population-based study. Lancet Oncol. 2008;9(7):629-635. doi:10.1016/S1470-2045(08)70153-0
  10. 10.
    [9] van Vledder MG, Levolger S, Ayez N, Verhoef C, Tran TC, Ijzermans JN. Body composition and outcome in patients undergoing resection of colorectal liver metastases. Br J Surg. 2012;99(4):550-557. doi:10.1002/bjs.7823
  11. 11.
    [10] Peng P, Hyder O, Firoozmand A, et al. Impact of sarcopenia on outcomes following resection of pancreatic adenocarcinoma. J Gastrointest Surg. 2012;16(8):1478-1486. doi:10.1007/s11605-012-1923-5
  12. 12.
    [11] Meza-Junco J, Montano-Loza AJ, Baracos VE, et al. Sarcopenia as a prognostic index of nutritional status in concurrent cirrhosis and hepatocellular carcinoma. J Clin Gastroenterol. 2013;47(10):861-870. doi:10.1097/MCG.0b013e318293a825
  13. 13.
    [12] Lee CS, Cron DC, Terjimanian MN, et al. Dorsal muscle group area and surgical outcomes in liver transplantation. Clin Transplant. 2014;28(10):1092-1098. doi:10.1111/ctr.12422
  14. 14.
    [13] DiMartini A, Cruz RJ Jr, Dew MA, et al. Muscle mass predicts outcomes following liver transplantation. Liver Transpl. 2013;19(11):1172-1180. doi:10.1002/lt.23724
  15. 15.
    [14] Montano-Loza AJ, Meza-Junco J, Baracos VE, et al. Severe muscle depletion predicts postoperative length of stay but is not associated with survival after liver transplantation. Liver Transpl. 2014;20(6):640-648. doi:10.1002/lt.23863
  16. 16.
    [15] Hasselager R, Gögenur I. Core muscle size assessed by perioperative abdominal CT scan is related to mortality, postoperative complications, and hospitalization after major abdominal surgery: a systematic review. Langenbecks Arch Surg. 2014;399(3):287-295. doi:10.1007/s00423-014-1174-x
  17. 17.
    [16] Barret M, Berthaud C, Taïeb J. La sarcopénie : un concept d'importance croissante dans la prise en charge du cancer colorectal [Sarcopenia: a concept of growing importance in the management of colorectal cancer]. Presse Med. 2014;43(6 Pt 1):628-632. doi:10.1016/j.lpm.2013.12.021
  18. 18.
    [17] Yip C, Goh V, Davies A, et al. Assessment of sarcopenia and changes in body composition after neoadjuvant chemotherapy and associations with clinical outcomes in oesophageal cancer. Eur Radiol. 2014;24(5):998- 1005. doi:10.1007/s00330-014-3110-4
  19. 19.
    [18] Janssen I, Shepard DS, Katzmarzyk PT, Roubenoff R. The healthcare costs of sarcopenia in the United States. J Am Geriatr Soc. 2004;52(1):80-85. doi:10.1111/j.1532-5415.2004.52014.x
  20. 20.
    [19] Methods for voluntary weight loss and control. NIH Technology Assessment Conference Panel. Ann Intern Med. 1992;116(11):942-949. doi:10.7326/0003-4819-116-11-942
  21. 21.
    [20] Lee RC, Wang ZM, Heymsfield SB. Skeletal muscle mass and aging: regional and whole-body measurement methods. Can J Appl Physiol. 2001;26(1):102-122. doi:10.1139/h01-008
  22. 22.
    [21] Mitsiopoulos N, Baumgartner RN, Heymsfield SB, Lyons W, Gallagher D, Ross R. Cadaver validation of skeletal muscle measurement by magnetic resonance imaging and computerized tomography.J Appl Physiol (1985). 1998;85(1):115-122. doi:10.1152/jappl.1998.85.1.115
  23. 23.
    [22] Ross R, Rissanen J, Pedwell H, Clifford J, Shragge P. Influence of diet and exercise on skeletal muscle and visceral adipose tissue in men. J Appl Physiol (1985). 1996;81(6):2445-2455. doi:10.1152/jappl.1996.81.6.2445
  24. 24.
    [23] Hamaguchi Y, Kaido T, Okumura S, et al. Proposal for new diagnostic criteria for low skeletal muscle mass based on computed tomography imaging in Asian adults. Nutrition. 2016;32(11-12):1200-1205. doi:10.1016/j.nut.2016.04.003
  25. 25.
    [24] Derstine, B.A., Holcombe, S.A., Ross, B.E. et al. Skeletal muscle cutoff values for sarcopenia diagnosis using T10 to L5 measurements in a healthy US population. Sci Rep 8, 11369 (2018). https://doi.org/10.1038/s41598- 018-29825-5
  26. 26.
    [25] van der Werf A, Langius JAE, de van der Schueren MAE, et al. Percentiles for skeletal muscle index, area and radiation attenuation based on computed tomography imaging in a healthy Caucasian population. Eur J Clin Nutr. 2018;72(2):288-296. doi:10.1038/s41430-017-0034-5
  27. 27.
    [26] G. A. F. S. (n.d.). Population Estimates in the Midyear of 2021. General Authority for Statistics Kingdom of Saudi Arabia. https://www.stats.gov.sa/sites/default/files/POP%20SEM2021E.pdf
  28. 28.
    [27] Goodpaster BH, Kelley DE, Thaete FL, He J, Ross R. Skeletal muscle attenuation determined by computed tomography is associated with skeletal muscle lipid content. J Appl Physiol (1985). 2000;89(1):104-110. doi:10.1152/jappl.2000.89.1.104
  29. 29.
    [28] Boutin RD, Yao L, Canter RJ, Lenchik L. Sarcopenia: Current Concepts and Imaging Implications. AJR Am J Roentgenol. 2015;205(3):W255- W266. doi:10.2214/AJR.15.14635
  30. 30.
    [29] Mourtzakis M, Prado CM, Lieffers JR, Reiman T, McCargar LJ, Baracos VE. A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired during routine care. Appl Physiol Nutr Metab. 2008;33(5):997- 1006. doi:10.1139/H08-075
  31. 31.
    [30] Shen W, Punyanitya M, Wang Z, et al. Total body skeletal muscle and adipose tissue volumes: estimation from a single abdominal cross- sectional image. J Appl Physiol (1985). 2004;97(6):2333-2338. doi:10.1152/japplphysiol.00744.2004
  32. 32.
    [31] Antoun S, Lanoy E, Iacovelli R, et al. Skeletal muscle density predicts prognosis in patients with metastatic renal cell carcinoma treated with targeted therapies. Cancer. 2013;119(18):3377-3384. doi:10.1002/cncr.28218
  33. 33.
    [32] Sabel MS, Lee J, Cai S, Englesbe MJ, Holcombe S, Wang S. Sarcopenia as a prognostic factor among patients with stage III melanoma. Ann Surg Oncol. 2011;18(13):3579-3585. doi:10.1245/s10434-011-1976-9
  34. 34.
    [33] Weijs PJ, Looijaard WG, Dekker IM, et al. Low skeletal muscle area is a risk factor for mortality in mechanically ventilated critically ill patients.Crit Care. 2014;18(2):R12. Published 2014 Jan 13. doi:10.1186/cc13189
  35. 35.
    [34] Martin L, Birdsell L, Macdonald N, et al. Cancer cachexia in the age of obesity: skeletal muscle depletion is a powerful prognostic factor, independent of body mass index. J Clin Oncol. 2013;31(12):1539-1547. doi:10.1200/JCO.2012.45.2722