Sacroiliac joint asymmetry regarding inflammation and bone turnover: Assessment by FDG and NaF PET/CT

Document Type : Original Article

Authors

1 Department of Radiology, Hospital of the University of Pennsylvania, PA, USA

2 Department of Nuclear Medicine, Odense University Hospital, Odense, Denmark Institute of Clinical Research, University of Southern Denmark, Odense, Denmark

Abstract

Objective(s): This study was undertaken to determine the role of computed tomography (CT)-based methodology to segment the SI joint and quantify the metabolic activity using positron emission tomography (PET). We measured tracer uptake in the right and left SI joints independently to look for differences between the two sides. Further, we correlated tracer uptake with BMI and studied the inter-observer variation with regard to estimated tracer uptake in the SI joints.
Methods: In this retrospective study, a total of 103 subjects (48 females, 55 males) from the CAMONA study database collected 2012-2016 at Odense University Hospital in Denmark were included. Mean age was 48±14.59 years, mean BMI was 26.68±4.31 kg/m2. The SI joints were segmented on fused PET/CT images using a 3D growing algorithm with adjustable upper and lower Hounsfield Units (HU) thresholds. The metabolic activities on the two sides were correlated with BMI.
Results: For FDG, we found a higher average SUVmean on the right side (right: 1.3±0.33, left: 1.13±0.30; P<0.0001). Similarly, for NaF, the uptake was higher on the right side (right: 5.9±1.29, left: 4.27±1.23; P<0.0001). Positive correlations were present between BMI and FDG uptake (P<0.01) as well as NaF uptake (P<0.01).
Conclusion: The PET-based molecular imaging probes along with the CT-based segmentation techniques revealed a significant difference in the metabolic activity between the two SI joints with higher inflammation and reactive bone formation on the right side. FDG and NaF uptakes correlated significantly and positively with BMI.

Keywords

Main Subjects

References

1. Egund N, Jurik AG, editors. Anatomy and histology of the sacroiliac joints. Seminars in musculoskeletal radiology; 2014: Thieme Medical Publishers.
2. Demir M, Mavi A, Gümüsburun E, Bayram M, Gürsoy S, Nishio H. Anatomical variations with joint space measurements on CT. Kobe J Med Sci. 2007;53(5):209-17.
3. Zheng N, Watson L, Yong-Hing K. Biomechanical modelling of the human sacroiliac joint. Medical and Biological Engineering and Computing. 1997; 35(2):77-82.
4. Shi D, Wang F, Wang D, Li X, Wang Q. 3-D finite element analysis of the influence of synovial condition in sacroiliac joint on the load transmission in human pelvic system. Medical engineering & physics. 2014;36(6):745-53.
5. Cohen SP, Chen Y, Neufeld NJ. Sacroiliac joint pain: a comprehensive review of epidemiology, diagnosis and treatment. Expert review of neurotherapeutics. 2013;13(1):99-116.
6. Sheng B, Feng C, Zhang D, Spitler H, Shi L. Associations between obesity and spinal diseases: a medical expenditure panel study analysis. International journal of environmental research and public health. 2017;14(2):183.
7. Kothekar E, Raynor WY, Al-Zaghal A, Jonnakuti VS, Werner TJ, Alavi A. Evolving Role of PET/CT-MRI in Assessing Muscle Disorders. PET Clinics. 2018.
8. Chen K, Blebea J, Laredo J-D, Chen W, Alavi A, Torigian DA. Evaluation of musculoskeletal disorders with PET, PET/CT, and PET/MR imaging. PET clinics. 2008;3(3):451-65.
9. Raynor W, Houshmand S, Gholami S, Emamzadehfard S, Rajapakse CS, Blomberg BA, et al. Evolving role of molecular imaging with 18F-sodium fluoride PET as a biomarker for calcium metabolism. Current osteoporosis reports. 2016;14(4):115-25.
10. Blomberg BA, De Jong PA, Thomassen A, Lam MG, Vach W, Olsen MH, et al. Thoracic aorta calcification but not inflammation is associated with increased cardiovascular disease risk: results of the CAMONA study. European journal of nuclear medicine and molecular imaging. 2017;44(2):249-58.
11. Blomberg BA, Thomassen A, de Jong PA, Lam MG, Diederichsen AC, Olsen MH, et al. Coronary fluorine- 18-sodium fluoride uptake is increased in healthy adults with an unfavorable cardiovascular risk profile: results from the CAMONA study. Nuclear medicine communications. 2017;38(11):1007-14.
12. D’agostino RB, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM, et al. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation. 2008;117(6):743-53.
13. Blomberg BA, Thomassen A, Takx RA, Hildebrandt MG, Simonsen JA, Buch-Olsen KM, et al. Delayed 18 F-fluorodeoxyglucose PET/CT imaging improves quantitation of atherosclerotic plaque inflammation: results from the CAMONA study. Journal of Nuclear Cardiology. 2014;21(3):588-97.
14. Blomberg BA, Thomassen A, Takx RA, Vilstrup MH, Hess S, Nielsen AL, et al. Delayed sodium 18 F-fluoride PET/CT imaging does not improve quantification of vascular calcification metabolism: Results from the CAMONA study. Journal of Nuclear Cardiology. 2014;21(2):293-304.
15. Takata Y, Higashino K, Morimoto M, Sakai T, Yamashita K, Abe M, et al. Vacuum Phenomenon of the Sacroiliac Joint: Correlation with Sacropelvic Morphology. Asian spine journal. 2016;10(4):762-6.
16. Sadeghi H, Allard P, Prince F, Labelle H. Symmetry and limb dominance in able-bodied gait: a review. Gait & posture. 2000;12(1):34-45.
17. Seeley MK, Umberger BR, Shapiro R. A test of the functional asymmetry hypothesis in walking. Gait & posture. 2008;28(1):24-8.
18. Hart S, Gabbard C. Examining the mobilizing feature of footedness. Perceptual and motor skills. 1998;86(3_suppl):1339-42.
19. Gentry V, Gabbard C. Foot-preference behavior: a developmental perspective. The Journal of General Psychology. 1995;122(1):37-45.
20. Carey DP, Smith G, Smith DT, Shepherd JW, Skriver J, Ord L, et al. Footedness in world soccer: an analysis of France’98. Journal of Sports Sciences. 2001;19(11):855-64.
21. Carpes FP, Mota CB, Faria IE. On the bilateral asymmetry during running and cycling–A review considering leg preference. Physical therapy in sport. 2010;11(4):136-42.
22. Knapik DM, Perera P, Nam J, Blazek AD, Rath B, Leblebicioglu B, et al. Mechanosignaling in bone health, trauma and inflammation. Antioxidants & redox signaling. 2014;20(6):970-85.
23. Sanchez C, Pesesse L, Gabay O, Delcour JP, Msika P, Baudouin C, et al. Regulation of subchondral bone osteoblast metabolism by cyclic compression. Arthritis & Rheumatism. 2012;64(4):1193-203.
24. Berenbaum F, Eymard F, Houard X. Osteoarthritis, inflammation and obesity. Current opinion in rheumatology. 2013;25(1):114-8.
25. Sellam J, Berenbaum F. Is osteoarthritis a metabolic disease? Joint bone spine. 2013;80(6):568-73.
26. Takeda S. Effect of obesity on bone metabolism. Clinical calcium. 2008;18(5):632-7.
27. Ehrlich P, Lanyon L. Mechanical strain and bone cell function: a review. Osteoporosis international. 2002;13(9):688-700.
28. Simopoulou T, Malizos K, Iliopoulos D, Stefanou N, Papatheodorou L, Ioannou M, et al. Differential expression of leptin and leptin’s receptor isoform (Ob-Rb) mRNA between advanced and minimally affected osteoarthritic cartilage; effect on cartilage metabolism. Osteoarthritis and Cartilage. 2007;15(8):872-83.
29. Costeas A, Woodard HQ, Laughlin JS. Depletion of 18F from blood flowing through bone. Journal of Nuclear Medicine. 1970;11(1):43.
30. Bastawrous S, Bhargava P, Behnia F, Djang DS, Haseley DR. Newer PET application with an old tracer: role of 18F-NaF skeletal PET/CT in oncologic practice. Radiographics. 2014;34(5):1295-316.
31. Lupsa BC, Insogna K. Bone health and osteoporosis. Endocrinology and Metabolism Clinics. 2015; 44(3):517-30.
Asia Oceania Journal of Nuclear Medicine and Biology
Volume 7, Issue 2
July 2019
Pages 108-114

Files

Share

How to cite

Statistics