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Apparent diffusion coefficient measurement using thin-slice diffusion-weighted magnetic resonance imaging: assessment of measurement errors and repeatability

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Abstract

We investigated the measurement error and repeatability of the apparent diffusion coefficient (ADC) obtained using thin-slice imaging. Diffusion-weighted images of an ice-water phantom were acquired using 1.5-T and 3.0-T scanners with 1-, 3-, and 5-mm thickness. ADC maps were generated at b = 0 and 1000 mm2/s using five consecutive scans. Measurement errors were assessed with accuracy and precision. Repeatability was assessed using the within-subject coefficient of variation. The ADC accuracy of both scanners agreed with the ADC of water at 0 °C. At 1-mm, precisions were 2.9% and 8.4% for the 3.0-T and 1.5-T scanners, respectively. The repeatabilities of 1-mm thickness were 1.3% and 3.4% in the 3.0-T and 1.5-T scanners, respectively. The 3.0-T scanner showed acceptable measurement errors and moderate repeatability compared with Quantitative Imaging Biomarkers Alliance recommendation. A 3.0-T scanner can be used for reliable ADC measurement, even with a 1-mm thickness at a reasonable scan time.

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References

  1. Padhani AR, Liu G, Koh DM, Chenevert TL, Thoeny HC, Takahara T, Dzik-Jurasz A, Ross BD, Van Cauteren M, Collins D, Hammoud DA, Rustin GJ, Taouli B, Choyke PL. Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia. 2009;11:102–25.

    Article  CAS  Google Scholar 

  2. She D, Liu J, Zeng Z, Xing Z, Cao D. Diagnostic accuracy of diffusion weighted imaging for differentiation of supratentorial pilocytic astrocytoma and pleomorphic xanthoastrocytoma. Neuroradiology. 2018;60:725–33.

    Article  Google Scholar 

  3. Kim BS, Kim ST, Kim JH, Seol HJ, Nam DH, Shin HJ, Lee JI, Kong DS. Apparent diffusion coefficient as a predictive biomarker for survival in patients with treatment naive glioblastoma using quantitative multiparametric magnetic resonance profiling. World Neurosurg. 2019;122:e812–20.

    Article  Google Scholar 

  4. Malyarenko D, Galban CJ, Londy FJ, Meyer CR, Johnson TD, Rehemtulla A, Ross BD, Chenevert TL. Multi-system repeatability and reproducibility of apparent diffusion coefficient measurement using an ice-water phantom. J Magn Reson Imaging. 2013;37:1238–46.

    Article  Google Scholar 

  5. Yoshida T, Urikura A, Shirata K, Nakaya Y, Terashima S, Hosokawa Y. Image quality assessment of single-shot turbo spin echo diffusion-weighted imaging with parallel imaging technique: a phantom study. Br J Radiol. 2016;89:20160512.

    Article  Google Scholar 

  6. Yoshida T, Urikura A, Shirata K, Nakaya Y, Endo M, Terashima S, Hosokawa Y. Short tau inversion recovery in breast diffusion weighted imaging: signal-to-noise ratio and apparent diffusion coefficients using a breast phantom in comparison with spectral attenuated inversion recovery. Radiol Med (Torino). 2018;123:296–304.

    Article  Google Scholar 

  7. Saritas EU, Lee JH, Nishimura DG. SNR dependence of optimal parameters for apparent diffusion coefficient measurements. IEEE Trans Med Imaging. 2011;30:424–37.

    Article  Google Scholar 

  8. Delakis I, Moore EM, Leach MO, De Wilde JP. Developing a quality control protocol for diffusion imaging on a clinical MRI system. Phys Med Biol. 2004;49:1409–22.

    Article  Google Scholar 

  9. Paudyal R, Konar AS, Obuchowski NA, Hatzoglou V, Chenevert TL, Malyarenko DI, Swanson SD, LoCastro E, Jambawalikar S, Liu MZ, Schwartz LH, Tuttle RM, Lee N, Shukla-Dave A. Repeatability of quantitative diffusion weighted imaging metrics in phantoms, head-and-neck and thyroid cancers: preliminary findings. Tomography. 2019;5:15–25.

    Article  Google Scholar 

  10. Lavdas I, Miquel ME, McRobbie DW, Aboagye EO. Comparison between diffusion-weighted MRI (DW-MRI) at 1.5 and 3 tesla: a phantom study. J Magn Reson Imaging. 2014;40:682–90.

    Article  Google Scholar 

  11. Khalil AA, Hohenhaus M, Kunze C, Schmidt W, Brunecker P, Villringer K, Merboldt KD, Frahm J, Fiebach JB. Sensitivity of diffusion-weighted STEAM MRI and EPI-DWI to infratentorial ischemic stroke. PLoS ONE. 2016;11:e0161416.

    Article  Google Scholar 

  12. Choi S, Cunningham DT, Aguila F, Corrigan JD, Bogner J, Mysiw WJ, Knopp MV, Schmalbrock P. DTI at 7 and 3 T: systematic comparison of SNR and its influence on quantitative metrics. J Magn Reson Imaging. 2011;29:739–51.

    Article  Google Scholar 

  13. Medved M, Soylu-Boy FN, Karademir I, Sethi I, Yousuf A, Karczmar GS, Oto A. High-resolution diffusion-weighted imaging of the prostate. AJR Am J Roentgenol. 2014;203:85–90.

    Article  Google Scholar 

  14. RSNA Quantitative imaging Biomarkers Alliance (QIBA). Diffusion-weighted magnetic resonance imaging profile; 2019. https://qibawiki.rsna.org/images/7/7e/QIBADWIProfile_as_of_2019-Feb-05.pdf. Accessed 14 May 2020.

  15. Holz M, Stefan RH, Antonio S. Temperature-dependent self-diffusion coefficients of water and six selected molecular liquids for calibration in accurate 1H NMR PFG measurements. Phys Chem Chem Phys. 2000;20:4740–2.

    Article  Google Scholar 

  16. Xing D, Papadakis NG, Huang CL, Lee VM, Carpenter TA, Hall LD. Optimised diffusion-weighting for measurement of apparent diffusion coefficient (ADC) in human brain. Magn Reson Imaging. 1997;15:771–84.

    Article  CAS  Google Scholar 

  17. Grech-Sollars M, Hales PW, Miyazaki K, Raschke F, Rodriguez D, Wilson M, Gill SK, Banks T, Saunders DE, Clayden JD, Gwilliam MN, Barrick TR, Morgan PS, Davies NP, Rossiter J, Auer DP, Grundy R, Leach MO, Howe FA, Peet AC, Clark CA. Multi-centre reproducibility of diffusion MRI parameters for clinical sequences in the brain. NMR Biomed. 2015;28:468–78.

    Article  Google Scholar 

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Correspondence to Tsukasa Yoshida.

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Yoshida, T., Urikura, A., Hosokawa, Y. et al. Apparent diffusion coefficient measurement using thin-slice diffusion-weighted magnetic resonance imaging: assessment of measurement errors and repeatability. Radiol Phys Technol 14, 203–209 (2021). https://doi.org/10.1007/s12194-021-00616-4

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  • DOI: https://doi.org/10.1007/s12194-021-00616-4

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