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Fat suppression techniques (STIR vs. SPAIR) on diffusion-weighted imaging of breast lesions at 3.0 T: preliminary experience

  • BREAST RADIOLOGY
  • Published:
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Abstract

Purpose

The aim of this work was to perform a qualitative and quantitative comparison of the performance of two fat suppression techniques on breast diffusion-weighted imaging (DWI).

Materials and methods

Fifty-one women underwent clinical breast magnetic resonance imaging, including DWI with short TI inversion recovery (STIR) and spectral attenuated inversion recovery (SPAIR). Four were excluded from the analysis due to image artefacts. Rating of fat suppression uniformity and lesion visibility were performed. Agreement between the two sequences was evaluated. Additionally, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) values for normal gland, benign and malignant lesions were compared. Receiver operating characteristic analysis was also performed.

Results

From the 52 lesions found, 47 were detected by both sequences. DWI-STIR evidenced more homogeneous fat suppression (p = 0.03). Although these lesions were seen with both techniques, DWI-SPAIR evidenced higher score for lesion visibility in nine of them. SNR and CNR were comparable, except for SNR in benign lesions (p < 0.01), which was higher for DWI-SPAIR. Mean ADC values for lesions were similar. ADC for normal fibroglandular tissue was higher when using DWI-STIR (p = 0.006). Sensitivity, specificity, accuracy and area under the curve values were alike: 84.0 % for both; 77.3, 71.4 %; 80.9, 78.3 %; 82.5, 81.3 % for DWI-SPAIR and DWI-STIR, respectively.

Conclusion

DWI-STIR showed superior fat suppression homogeneity. No differences were found for SNR and CNR, except for SNR in benign lesions. ADCs for lesions were comparable. Findings in this study are consistent with previous studies at 1.5 T, meaning that both fat suppression techniques are appropriate for breast DWI at 3.0 T.

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References

  1. Belli P, Costantini M, Bufi E et al (2010) Diffusion-weighted imaging in breast lesion evaluation. Radiol Med 115:51–69

    Article  CAS  PubMed  Google Scholar 

  2. Jin G, An N, Jacobs MA, Li K (2010) The role of parallel diffusion-weighted imaging and apparent diffusion coefficient (ADC) map values for evaluating breast lesions: preliminary results. Acad Radiol 17:456–463

    Article  PubMed Central  PubMed  Google Scholar 

  3. Woodhams R, Ramadan S, Stanwell P et al (2011) Diffusion-weighted imaging of the breast: principles and clinical applications. Radiographics 31:1059–1084

    Article  PubMed  Google Scholar 

  4. Takahara T, Imai Y, Yamashita T et al (2004) Diffusion weighted whole body imaging with background body signal suppression (DWIBS): technical improvement using free breathing, STIR and high resolution 3D display. Radiat Med 22:275–382

    PubMed  Google Scholar 

  5. Kazama T, Nasu K, Kuroki Y et al (2009) Comparison of diffusion-weighted images using short inversion time inversion recovery or chemical shift selective pulse as fat suppression in patients with breast cancer. Jpn J Radiol 27:163–167

    Article  PubMed  Google Scholar 

  6. Bitar R, Leung G, Perng R et al (2006) MR pulse sequences: what every radiologist wants to know but is afraid to ask. Radiographics 26:513–537

    Article  PubMed  Google Scholar 

  7. Ribeiro MM, Rumor L, Oliveira M et al (2013) STIR, SPIR and SPAIR techniques in magnetic resonance of the breast: a comparative study. JBiSE 6:395–402

    Article  Google Scholar 

  8. Tannús A, Garwood M (1997) Adiabatic pulses. NMR Biomed 10:423–434

    Article  PubMed  Google Scholar 

  9. Luna A, Ribes R, Soto JA (2012) Diffusion MRI outside the brain: a case-based review and clinical applications. Springer-Verlag, Berlin, New York

    Book  Google Scholar 

  10. Woodhams R, Matsunaga K, Kan S et al (2005) ADC mapping of benign and malignant breast tumors. Magn Reson Med Sci 4:35–42

    Article  PubMed  Google Scholar 

  11. Guo Y, Cai YQ, Cai ZL et al (2002) Differentiation of clinically benign and malignant breast lesions using diffusion-weighted imaging. J Magn Reson Imaging 16:172–178

    Article  PubMed  Google Scholar 

  12. Partridge SC, McKinnon GC, Henry RG, Hylton NM (2001) Menstrual cycle variation of apparent diffusion coefficients measured in the normal breast using MRI. J Magn Reson Imaging 14:433–438

    Article  CAS  PubMed  Google Scholar 

  13. Lee J, Lustig M, Kim DH, Pauly JM (2009) Improved shim method based on the minimization of the maximum off-resonance frequency for balanced steady-state free precession (bSSFP). Magn Reson Med 61:1500–1506

    Article  PubMed Central  PubMed  Google Scholar 

  14. Agrawal G, Su MY, Nalcioglu O et al (2009) Significance of breast lesion descriptors in the ACR BI-RADS MRI lexicon. Cancer 115:1363–1380

    Article  PubMed Central  PubMed  Google Scholar 

  15. Heverhagen JT (2007) Noise measurement and estimation in MR imaging experiments. Radiology 245(3):638–639

    Article  PubMed  Google Scholar 

  16. Bogner W, Gruber S, Pinker K et al (2009) Diffusion-weighted MR for differentiation of breast lesions at 3.0 T: how does selection of diffusion protocols affect diagnosis? Radiology 253:341–351

    Article  PubMed  Google Scholar 

  17. Rahbar H, Partridge SC, Eby PR et al (2011) Characterization of ductal carcinoma in situ on diffusion weighted breast MRI. Eur Radiol 21:2011–2019

    Article  PubMed  Google Scholar 

  18. Altman DG (1991) Practical statistics for medical research. Chapman & Hall, London

    Google Scholar 

  19. Matsuoka A, Minato M, Harada M et al (2008) Comparison of 3.0-and 1.5-tesla diffusion-weighted imaging in the visibility of breast cancer. Radiat Med 26:15–20

    Article  PubMed  Google Scholar 

  20. Lourenço AP, Donegan L, Kahil H, Mainiero MB (2014) Improving outcomes of screening breast MRI with practice evolution: initial clinical experience with 3T compared to 1.5T. J Magn Reson Imaging 39:535–539

    Article  PubMed  Google Scholar 

  21. Rahbar H, Partridge SC, DeMartini WB et al (2013) Clinical and technical considerations for high quality breast MRI at 3 Tesla. J Magn Reson Imaging 37:778–790

    Article  PubMed  Google Scholar 

  22. Butler RS, Chen C, Vashi R et al (2013) 3.0 Tesla vs 1.5 Tesla breast magnetic resonance imaging in newly diagnosed breast cancer patients. World J Radiol 5:285–294

    Article  PubMed Central  PubMed  Google Scholar 

  23. Mürtz P, Kaschner M, Träber F et al (2012) Evaluation of dual-source parallel RF excitation for diffusion-weighted whole-body MR imaging with background body signal suppression at 3.0 T. Eur J Radiol 81:3614–3623

    Article  PubMed  Google Scholar 

  24. Rahbar H, Partridge SC, DeMartini WB et al (2012) Improved B1 homogeneity of 3 Tesla breast MRI using dual-source parallel radiofrequency excitation. J Magn Reson Imaging 35:1222–1226

    Article  PubMed Central  PubMed  Google Scholar 

  25. Kuroki Y, Nasu K (2008) Advances in breast MRI: diffusion-weighted imaging of the breast. Breast Cancer 15:212–217

    Article  PubMed  Google Scholar 

  26. Kuroki S, Kuroki Y, Nasu K et al (2007) Detecting breast cancer with non-contrast MR imaging: combining diffusion-weighted and STIR imaging. Magn Reson Med Sci 6:21–27

    Article  PubMed  Google Scholar 

  27. Thomassin-Naggara I, De Bazelaire C, Chopier J et al (2013) Diffusion-weighted MR imaging of the breast: advantages and pitfalls. Eur J Radiol 82:435–443

    Article  CAS  PubMed  Google Scholar 

  28. Partridge SC, Singer L, Sun R et al (2011) Diffusion-weighted MRI: influence of intravoxel fat signal and breast density on breast tumor conspicuity and apparent diffusion coefficient measurements. Magn Reson Imaging 29:1215–1221

    Article  PubMed Central  PubMed  Google Scholar 

  29. Udayasankar UK, Martin D, Lauenstein T et al (2008) Role of spectral presaturation attenuated inversion-recovery fat-suppressed T2-weighted MR imaging in active inflammatory bowel disease. J Magn Reson Imaging 28:1133–1140

    Article  PubMed  Google Scholar 

  30. Takanaga M, Hayashi N, Miyati T et al (2012) Influence of b-value on the measurement of contrast and apparent diffusion coefficient in 3.0 Tesla breast magnetic resonance imaging. Nihon Hoshasen Gijutsu Gakkai Zasshi 68:201–208

    Article  PubMed  Google Scholar 

  31. Lo GG, Ai V, Chan JK, Li KW et al (2009) Diffusion-weighted magnetic resonance imaging of breast lesions: first experiences at 3 T. J Comput Assist Tomogr 33:63–69

    Article  PubMed  Google Scholar 

  32. Sonmez G, Cuce F, Mutlu H et al (2011) Value of diffusion-weighted MRI in the differentiation of benign and malign breast lesions. Wien Klin Wochenschr 123:655–661

    Article  CAS  PubMed  Google Scholar 

  33. Tsushima Y, Takahashi-Taketomi A, Endo K (2009) Magnetic resonance (MR) differential diagnosis of breast tumors using apparent diffusion coefficient (ADC) on 1.5-T. J Magn Reson Imaging 30:249–255

    Article  PubMed  Google Scholar 

  34. Chen X, Li WL, Zhang YL et al (2010) Meta-analysis of quantitative diffusion-weighted MR imaging in the differential diagnosis of breast lesions. BMC Cancer 10:693

    Article  PubMed Central  PubMed  Google Scholar 

  35. Inoue K, Kozawa E, Mizukoshi W et al (2011) Usefulness of diffusion-weighted imaging of breast tumors: quantitative and visual assessment. Jpn J Radiol 29:429–436

    Article  PubMed  Google Scholar 

  36. Palle L, Reddy B (2009) Role of diffusion MRI in characterizing benign and malignant breast lesions. Indian J Radiol Imaging 19:287–290

    Article  PubMed Central  PubMed  Google Scholar 

  37. Woodhams R, Kakita S, Hata H et al (2009) Diffusion-weighted imaging of mucinous carcinoma of the breast: evaluation of apparent diffusion coefficient and signal intensity in correlation with histologic findings. AJR Am J Roentgenol 193:260–266

    Article  PubMed  Google Scholar 

  38. Pereira FP, Martins G, Carvalhaes de Oliveira RV (2011) Diffusion magnetic resonance imaging of the breast. Magn Reson Imaging Clin N Am 19:95–110

    Article  PubMed  Google Scholar 

  39. Baltzer PAT, Dietzal M, Vag T (2009) Diffusion weighted imaging—useful in all kinds of lesions? A systematic review. Eur Radiol 19:S765–S769

    Article  Google Scholar 

  40. Hatakenaka M, Soeda H, Yabuuchi H et al (2008) Apparent diffusion coefficients of breast tumors: clinical application. Magn Reson Med Sci 7:23–29

    Article  PubMed  Google Scholar 

  41. Iima M, Le Bihan D, Okumura R et al (2011) Apparent diffusion coefficient as an MR imaging biomarker of low-risk ductal carcinoma in situ: a pilot study. Radiology 260:364–372

    Article  PubMed  Google Scholar 

  42. Nagy Z, Weiskopf N (2008) Efficient fat suppression by slice-selection gradient reversal in twice-refocused diffusion encoding. Magn Reson Med 60:1256–1260

    Article  PubMed Central  PubMed  Google Scholar 

Download references

Acknowledgments

Grant sponsor from the Portuguese Foundation for Science and Technology; Grant Number: PEst-OE/SAU/UI0645/2011 and SFRH/BD/50027/2009.

Conflict of interest

The authors declare no conflict of interest.

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Authors and Affiliations

  1. Department of Radiology, Centro Hospitalar de São João-EPE/Faculty of Medicine, University of Porto, Alameda Prof. Hernâni Monteiro, 4200-319, Porto, Portugal

    Sofia Brandão, Joana Loureiro & Isabel Ramos

  2. Centro Hospitalar São João-EPE/Faculty of Medicine, University of Porto, Alameda Prof. Hernâni Monteiro, 4200-319, Porto, Portugal

    Luísa Nogueira

  3. School of Applied Health Sciences, Oporto Polytechnic Institute (ESTSP/IPP), Rua Valente Perfeito, 322, 4400-330, Vila Nova de Gaia, Portugal

    Luísa Nogueira

  4. Department of Health Community, Institute of Biomedical Sciences Abel Salazar of Porto University (ICBAS), Rua de Jorge Viterbo Ferreira, 228, 4050-313, Porto, Portugal

    Eduarda Matos

  5. Institute of Biophysics and Biomedical Engineering (IBEB), Faculty of Sciences, University of Lisbon, Campo Grande, 1749-016, Lisbon, Portugal

    Rita Gouveia Nunes & Hugo Alexandre Ferreira

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  1. Sofia Brandão
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  2. Luísa Nogueira
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Correspondence to Sofia Brandão.

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Brandão, S., Nogueira, L., Matos, E. et al. Fat suppression techniques (STIR vs. SPAIR) on diffusion-weighted imaging of breast lesions at 3.0 T: preliminary experience. Radiol med 120, 705–713 (2015). https://doi.org/10.1007/s11547-015-0508-2

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