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Purpose: To qualitatively and quantitatively investigate the effect of common vendor-related sequence variations in fat suppression techniques on the diagnostic performance of free-breathing DW protocols for lung imaging.
Methods: 8 patients with malignant lung lesions were scanned in free breathing using two diffusion-weighted (DW) protocols with different fat suppression techniques: DWA used short-tau inversion recovery (STIR), and DWB used Spectral Adiabatic Inversion Recovery (SPAIR). Both techniques were obtained at two time points, between 1 hour and 1 week apart. Image quality was assessed using a 5-point scoring system. The number of lesions visible within lung, mediastinum and at thoracic inlet on the DW (b=800 s/mm2) images was compared. Signal-to-noise ratios (SNR) were calculated for lesions and para-spinal muscle. Repeatability of ADC values of the lesions was estimated for both protocols together and separately.
Results: There was a signal void at the thoracic inlet in all patients with DWB but not with DWA. DWA images were rated significantly better than DWB images overall quality domains. (Cohen’s κ = 1). Although 8 more upper mediastinal/thoracic inlet lymph nodes were detected with DWA than DWB, this did not reach statistical significance (p = 0.23). Tumour ADC values were not significantly different between protocols (p=0.93), their ADC reproducibility was satisfactory (CoV=7.7%) and repeatability of each protocol separately was comparable (CoVDWA=3.7% (95% CI 2.5 – 7.1%) and CoVDWB=4.6% (95% CI 3.1 – 8.8%)).
Conclusion: In a free-breathing DW-MRI protocol for lung, STIR fat suppression produced images of better diagnostic quality than SPAIR, while maintaining comparable SNR and providing repeatable quantitative ADC acceptable for use in a multicentre trial setting.
This work is licensed under a Creative Commons Attribution 4.0 International License.
2. FDA. Critical Path Opportunities List. http://wwwfdagov/downloads/ScienceResearch/SpecialTopics/CriticalPathInitiative/CriticalPathOpportunitiesReports/UCM077258pdf. 2006.
3. Bains LJ, Zweifel M, Thoeny HC. Therapy response with diffusion MRI: an update. Cancer imaging : the official publication of the International Cancer Imaging Society. 2012;12:395-402.
4. Charles-Edwards EM. Diffusion-weighted magnetic resonance imaging and its application to cancer. Cancer imaging : the official publication of the International Cancer Imaging Society. 2006;6(1):135.
5. Reischauer C, Froehlich JM, Pless M, Binkert CA, Koh DM, Gutzeit A. Early treatment response in non-small cell lung cancer patients using diffusion-weighted imaging and functional diffusion maps--a feasibility study. PloS one. 2014;9(10):e108052.
6. Yabuuchi H, Hatakenaka M, Takayama K, Matsuo Y, Sunami S, Kamitani T, et al. Non-small cell lung cancer: detection of early response to chemotherapy by using contrast-enhanced dynamic and diffusion-weighted MR imaging. Radiology. 2011;261(2):598-604.
7. Henzler T, Schmid-Bindert G, Schoenberg SO, Fink C. Diffusion and perfusion MRI of the lung and mediastinum. European journal of radiology. 2010;76(3):329-36.
8. Bernardin L, Douglas NH, Collins DJ, Giles SL, O'Flynn EA, Orton M, et al. Diffusion-weighted magnetic resonance imaging for assessment of lung lesions: repeatability of the apparent diffusion coefficient measurement. European radiology. 2014;24(2):502-11.
9. Douglas N WJ, deSouza NM, Collins DJ, Orton MO Development of a phantom for quality assurance in multicentre clinical trials with diffusion-weighted MRI. Proceedings of the International Society of Magnetic Resonance in Medicine 2013:Presentation number 3114.
10. Winfield J, Douglas N, Collins D. Phantom for assessment of fat suppression in large field-of-view diffusion-weighted magnetic resonance imaging. Physics in medicine and biology. 2014;59(9):2235.
11. Blackledge MD, Leach MO, Collins DJ, Koh DM. Computed diffusion-weighted MR imaging may improve tumor detection. Radiology. 2011;261(2):573-81.
12. Dietrich O, Raya JG, Reeder SB, Reiser MF, Schoenberg SO. Measurement of signal‐to‐noise ratios in MR images: Influence of multichannel coils, parallel imaging, and reconstruction filters. Journal of Magnetic Resonance Imaging. 2007;26(2):375-85.
13. Lauenstein TC, Sharma P, Hughes T, Heberlein K, Tudorascu D, Martin DR. Evaluation of optimized inversion‐recovery fat‐suppression techniques for T2‐weighted abdominal MR imaging. Journal of Magnetic Resonance Imaging. 2008;27(6):1448-54.
14. Collins DJ, Blackledge M. Techniques and optimization. Diffusion-Weighted MR Imaging: Springer; 2010. p. 19-32.
15. Koh D-M, Thoeny HC. Diffusion-weighted MR imaging: applications in the body: Springer Science & Business Media; 2010.
16. Eberhardt WE, De Ruysscher D, Weder W, Le Pechoux C, De Leyn P, Hoffmann H, et al. 2nd ESMO Consensus Conference in Lung Cancer: locally advanced stage III non-small-cell lung cancer. Annals of oncology : official journal of the European Society for Medical Oncology / ESMO. 2015;26(8):1573-88.
17. Reck M, Popat S, Reinmuth N, De Ruysscher D, Kerr KM, Peters S. Metastatic non-small-cell lung cancer (NSCLC): ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Annals of oncology : official journal of the European Society for Medical Oncology / ESMO. 2014;25 Suppl 3:iii27-39.
18. Vansteenkiste J, Crino L, Dooms C, Douillard JY, Faivre-Finn C, Lim E, et al. 2nd ESMO Consensus Conference on Lung Cancer: early-stage non-small-cell lung cancer consensus on diagnosis, treatment and follow-up. Annals of oncology : official journal of the European Society for Medical Oncology / ESMO. 2014;25(8):1462-74.
19. Taouli B, Beer AJ, Chenevert T, Collins D, Lehman C, Matos C, et al. Diffusion-weighted imaging outside the brain: Consensus statement from an ISMRM-sponsored workshop. Journal of magnetic resonance imaging : JMRI. 2016.
20. Deng Y, Li X, Lei Y, Liang C, Liu Z. Use of diffusion-weighted magnetic resonance imaging to distinguish between lung cancer and focal inflammatory lesions: a comparison of intravoxel incoherent motion derived parameters and apparent diffusion coefficient. Acta radiologica (Stockholm, Sweden : 1987). 2015.
21. Jerome NP, Orton MR, d'Arcy JA, Collins DJ, Koh DM, Leach MO. Comparison of free‐breathing with navigator‐controlled acquisition regimes in abdominal diffusion‐weighted magnetic resonance images: Effect on ADC and IVIM statistics. Journal of Magnetic Resonance Imaging. 2014;39(1):235-40.
22. Jerome NP, Orton MR, d'Arcy JA, Feiweier T, Tunariu N, Koh DM, et al. Use of the temporal median and trimmed mean mitigates effects of respiratory motion in multiple-acquisition abdominal diffusion imaging. Physics in medicine and biology. 2015;60(2):N9-N20.