Skip to main content
SpringerLink
Log in

Quantitative MR evaluation of the infrapatellar fat pad for knee osteoarthritis: using proton density fat fraction and T2* relaxation based on DIXON

  • Musculoskeletal
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

To investigate the efficacy of fat fraction (FF) and T2* relaxation based on DIXON in the assessment of infrapatellar fat pad (IFP) for knee osteoarthritis (KOA) progression in older adults.

Methods

Ninety volunteers (age range 51–70 years, 65 females) were enrolled in this study. Participants were grouped based on the Kellgren-Lawrence grading (KLG). The FF and T2* values were measured based on the 3D-modified DXION technique. Cartilage defects, bone marrow lesions, and synovitis were assessed based on a modified version of whole-organ magnetic resonance imaging score (WORMS). Knee pain was assessed by self-administered Western Ontario and McMaster Osteoarthritis Index (WOMAC) questionnaire. The differences of FF and T2* measurement and the correlation with WORMS and WOMAC assessments were analyzed. Diagnostic efficiency was analyzed by using receiver operating characteristic (ROC) curves.

Results

A total of 60 knees were finally included (n = 20 in each group). The values were 82.6 ± 3.7%, 74.7 ± 5.4%, and 60.5 ± 14.1% for FF is the no OA, mild OA, and advanced OA groups, and were 50.7 ± 6.6 ms, 44.1 ± 6.6 ms, and 39.1 ± 4.2 ms for T2*, respectively (all p values < 0.001). The WORMS assessment and WOMAC pain assessment showed negative correlation with FF and T2* values. The ROC showed the area under the curve (AUC), sensitivity, and specificity for diagnosing OA were 0.93, 77.5%, and 100% using FF, and were 0.86, 75.0%, and 90.0% using T2*, respectively.

Conclusions

FF and T2* alternations in IFP are associated with knee structural abnormalities and clinical symptoms cross-sectionally and may have the potential to predict the severity of KOA.

Key Points

• Fat fraction (FF) and T2* relaxation based on DIXON imaging are novel methods to quantitatively assess the infrapatellar fat pad for knee osteoarthritis (KOA) progression in older adults.

• The alterations of FF and T2* using mDIXON technique in IFP were associated with knee structural abnormalities and clinical symptoms.

• FF and T2* alternations in IFP can serve as the new imaging biomarkers for fast, simple, and noninvasive assessment in KOA.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Abbreviations

AUC:

Area under the curve

CE-MRI:

Contrast-enhanced magnetic resonance imaging

DCE-MRI:

Dynamic contrast-enhanced magnetic resonance imaging

FF:

Fat fraction

ICC:

Intraclass correlation coefficient

IFP:

Infrapatellar fat pad

IS:

Signal intensity

JSN:

Toint space narrowing

KLG:

Kellgren-Lawrence grading

KOA:

Knee osteoarthritis

PDW-SPAIR:

Proton density-weighted spectrally adiabatic inversion recovery

ROC:

Receiver operating characteristic

ROI:

Global region-of-interest

T1WI:

T1-weighted image

WOMAC:

Western Ontario and McMaster Osteoarthritis Index

WORMS:

Whole-organ magnetic resonance imaging score

References

  1. Emmert D, Rasche T, Stieber C, Conrad R, Mücke M (2018) Knee pain - symptoms, diagnosis and therapy of osteoarthritis. MMW Fortschr Med 160:58–64

    Article  Google Scholar 

  2. Carballo CB, Nakagawa Y, Sekiya I, Rodeo SA (2017) Basic science of articular cartilage. Clin Sports Med 36:413–425

    Article  Google Scholar 

  3. Dobson GP, Letson HL, Grant A et al (2018) Defining the osteoarthritis patient: back to the future. Osteoarthritis Cartilage 26:1003–1007

    Article  CAS  Google Scholar 

  4. Ioan-Facsinay A, Kloppenburg M (2013) An emerging player in knee osteoarthritis: the infrapatellar fat pad. Arthritis Res Ther 15:225

    Article  Google Scholar 

  5. Zeng N, Yan ZP, Chen XY, Ni GX (2020) Infrapatellar fat pad and knee osteoarthritis. Aging Dis 11:1317–1328

    Article  Google Scholar 

  6. Poole AR (2012) Osteoarthritis as a whole joint disease. HSS J 8:4–6

    Article  Google Scholar 

  7. Steidle-Kloc E, Culvenor AG, Dörrenberg J, Wirth W, Ruhdorfer A, Eckstein F (2018) Relationship between knee pain and infrapatellar fat pad morphology: a within- and between-person analysis from the osteoarthritis initiative. Arthritis Care Res (Hoboken) 70:550–557

    Article  CAS  Google Scholar 

  8. Teichtahl AJ, Wulidasari E, Brady SR et al (2015) A large infrapatellar fat pad protects against knee pain and lateral tibial cartilage volume loss. Arthritis Res Ther 17:318

    Article  Google Scholar 

  9. Ruan G, Xu J, Wang K et al (2018) Associations between knee structural measures, circulating inflammatory factors and MMP13 in patients with knee osteoarthritis. Osteoarthritis Cartilage 26:1063–1069

    Article  CAS  Google Scholar 

  10. Favero M, El-Hadi H, Belluzzi E et al (2017) Infrapatellar fat pad features in osteoarthritis: a histopathological and molecular study. Rheumatology (Oxford) 56:1784–1793

    Article  CAS  Google Scholar 

  11. Mathiessen A, Conaghan PG (2017) Synovitis in osteoarthritis: current understanding with therapeutic implications. Arthritis Res Ther 19:18

    Article  Google Scholar 

  12. Sae-Jung T, Leearamwat N, Chaiseema N et al (2021) The infrapatellar fat pad produces interleukin-6-secreting T cells in response to a proteoglycan aggrecan peptide and provides dominant soluble mediators different from that present in synovial fluid. Int J Rheum Dis 24:834–846

    Article  CAS  Google Scholar 

  13. Eymard F, Pigenet A, Citadelle D et al (2014) Induction of an inflammatory and prodegradative phenotype in autologous fibroblast-like synoviocytes by the infrapatellar fat pad from patients with knee osteoarthritis. Arthritis Rheumatol 66:2165–2174

    Article  CAS  Google Scholar 

  14. Chang J, Liao Z, Lu M, Meng T, Han W, Ding C (2018) Systemic and local adipose tissue in knee osteoarthritis. Osteoarthritis Cartilage 26:864–871

    Article  CAS  Google Scholar 

  15. An JS, Tsuji K, Onuma H et al (2021) Inhibition of fibrotic changes in infrapatellar fat pad alleviates persistent pain and articular cartilage degeneration in monoiodoacetic acid-induced rat arthritis model. Osteoarthritis Cartilage 29:380–388

    Article  Google Scholar 

  16. van der Heijden RA, de Vries BA, Poot DHJ et al (2021) Quantitative volume and dynamic contrast-enhanced MRI derived perfusion of the infrapatellar fat pad in patellofemoral pain. Quant Imaging Med Surg 11:133–142

    Article  Google Scholar 

  17. de Vries BA, van der Heijden RA, Poot DHJ et al (2020) Quantitative DCE-MRI demonstrates increased blood perfusion in Hoffa’s fat pad signal abnormalities in knee osteoarthritis, but not in patellofemoral pain. Eur Radiol 30:3401–3408

    Article  Google Scholar 

  18. Crema MD, Felson DT, Roemer FW et al (2013) Peripatellar synovitis: comparison between non-contrast-enhanced and contrast-enhanced MRI and association with pain. The MOST study. Osteoarthritis Cartilage 21:413–418

    Article  CAS  Google Scholar 

  19. Wang K, Ding C, Hannon MJ, Chen Z, Kwoh CK, Hunter DJ (2019) Quantitative signal intensity alteration in infrapatellar fat pad predicts incident radiographic osteoarthritis: the osteoarthritis initiative. Arthritis Care Res (Hoboken) 71:30–38

    Article  Google Scholar 

  20. Han W, Aitken D, Zheng S et al (2019) Association between quantitatively measured infrapatellar fat pad high signal-intensity alteration and magnetic resonance imaging-assessed progression of knee osteoarthritis. Arthritis Care Res (Hoboken) 71:638–646

    Article  Google Scholar 

  21. Lu M, Chen Z, Han W et al (2016) A novel method for assessing signal intensity within infrapatellar fat pad on MR images in patients with knee osteoarthritis. Osteoarthritis Cartilage 24:1883–1889

    Article  CAS  Google Scholar 

  22. Han W, Aitken D, Zhu Z et al (2016) Signal intensity alteration in the infrapatellar fat pad at baseline for the prediction of knee symptoms and structure in older adults: a cohort study. Ann Rheum Dis 75:1783–1788

    Article  Google Scholar 

  23. Pezeshk P, Alian A, Chhabra A (2017) Role of chemical shift and Dixon based techniques in musculoskeletal MR imaging. Eur J Radiol 94:93–100

    Article  Google Scholar 

  24. Kim D, Kim SK, Lee SJ, Choo HJ, Park JW, Kim KY (2019) Simultaneous estimation of the fat fraction and R2(*) via T2(*)-corrected 6-echo Dixon volumetric interpolated breath-hold examination imaging for osteopenia and osteoporosis detection: correlations with sex, age, and menopause. Korean J Radiol 20:916–930

    Article  Google Scholar 

  25. Netaji A, Jain V, Gupta AK, Kumar U, Jana M (2020) Utility of MR proton density fat fraction and its correlation with ultrasonography and biochemical markers in nonalcoholic fatty liver disease in overweight adolescents. J Pediatr Endocrinol Metab 33:473–479

    Article  CAS  Google Scholar 

  26. Guo Y, Chen Y, Zhang X et al (2019) Magnetic susceptibility and fat content in the lumbar spine of postmenopausal women with varying bone mineral density. J Magn Reson Imaging 49:1020–1028

    Article  Google Scholar 

  27. Cunha GM, Thai TT, Hamilton G et al (2020) Accuracy of common proton density fat fraction thresholds for magnitude- and complex-based chemical shift-encoded MRI for assessing hepatic steatosis in patients with obesity. Abdom Radiol (NY) 45:661–671

    Article  Google Scholar 

  28. Obmann VC, Marx C, Berzigotti A et al (2019) Liver MRI susceptibility-weighted imaging (SWI) compared to T2* mapping in the presence of steatosis and fibrosis. Eur J Radiol 118:66–74

    Article  Google Scholar 

  29. Tao H, Qiao Y, Hu Y et al (2018) Quantitative T2-mapping and T2(⁎)-mapping evaluation of changes in cartilage matrix after acute anterior cruciate ligament rupture and the correlation between the results of both methods. Biomed Res Int 2018:7985672

    PubMed  PubMed Central  Google Scholar 

  30. Altman RD, Gold GE (2007) Atlas of individual radiographic features in osteoarthritis, revised. Osteoarthritis Cartilage 15 Suppl a:A1-56.

  31. Pietrosimone B, Luc BA, Duncan A, Saliba SA, Hart JM, Ingersoll CD (2017) Association between the single assessment numeric evaluation and the Western Ontario and McMaster universities osteoarthritis index. J Athl Train 52:526–533

    Article  Google Scholar 

  32. Bainbridge A, Bray TJP, Sengupta R, Hall-Craggs MA (2020) Practical approaches to bone marrow fat fraction quantification across magnetic resonance imaging platforms. J Magn Reson Imaging 52:298–306

    Article  Google Scholar 

  33. Peterfy CG, Guermazi A, Zaim S et al (2004) Whole-organ magnetic resonance imaging score (WORMS) of the knee in osteoarthritis. Osteoarthritis Cartilage 12:177–190

    Article  CAS  Google Scholar 

  34. Fontanella CG, Belluzzi E, Rossato M et al (2019) Quantitative MRI analysis of infrapatellar and suprapatellar fat pads in normal controls, moderate and end-stage osteoarthritis. Ann Anat 221:108–114

    Article  Google Scholar 

  35. Reeder SB, Bice EK, Yu H, Hernando D, Pineda AR (2012) On the performance of T2* correction methods for quantification of hepatic fat content. Magn Reson Med 67:389–404

    Article  Google Scholar 

  36. Fukuzawa K, Hayashi T, Takahashi J et al (2017) Evaluation of six-point modified Dixon and magnetic resonance spectroscopy for fat quantification: a fat-water-iron phantom study. Radiol Phys Technol 10:349–358

    Article  Google Scholar 

Download references

Acknowledgements

We would like to thank Professor Yanqiu Feng from Southern Medical University for his technical support and all necessary help to the research institute.

Funding

This study has received funding by the National Natural Science Foundation of China (81801653), and General project of President’s Foundation of the Third Affiliated Hospital of Southern Medical University (YM2021012).

Author information

Author notes

  1. Yanjun Chen and Xintao Zhang contributed equally to this work.

Authors and Affiliations

  1. School of Basic Medical Sciences, Southern Medical University, No.1023, Shatai Road South, Baiyun District, Guangzhou, 510515, Guangdong, China

    Yanjun Chen, Yaru Zhang, Wenhua Huang & Shizhen Zhong

  2. The Third Affiliated Hospital of Southern Medical University, No.183, Zhongshan Avenue West, Tianhe District, Guangzhou, 510630, Guangdong, China

    Yanjun Chen, Xintao Zhang, Mianwen Li, Lijie Zhong, Yukun Ding, Xianfu Mo, Jialing Chen, Qianmin Chen & Xiaodong Zhang

  3. Department of Radiology, Affiliated Hospital of Guangdong Medical University, Guangzhou, Guangdong, China

    Xueting Du

Authors
  1. Yanjun Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xintao Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mianwen Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lijie Zhong
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yukun Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yaru Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Xueting Du
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Xianfu Mo
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Jialing Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Qianmin Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Wenhua Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Shizhen Zhong
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Xiaodong Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Shizhen Zhong or Xiaodong Zhang.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Yanqiu, Feng, the Southern Medical University, and his e-mail address is foree@163.com.

Conflict of interest

The authors declare no competing interests.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was obtained from all subjects in this study.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• prospective

• cross-sectional study

• performed at one institution

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, Y., Zhang, X., Li, M. et al. Quantitative MR evaluation of the infrapatellar fat pad for knee osteoarthritis: using proton density fat fraction and T2* relaxation based on DIXON. Eur Radiol 32, 4718–4727 (2022). https://doi.org/10.1007/s00330-022-08561-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-022-08561-5

Keywords

Search

Navigation