Walk-Through

Kathryn Keenan¹

¹NIST, United States

Synopsis

This talk will present how to use and pick a phantom for specific applications, how the phantom can identify possible pitfalls or sources of error, and how to perform reproducibility and reliability studies.

Target Audience

Those who want to start performing quantitative MRI and want to learn how to use and pick a phantom for their application, how the phantom can identify possible pitfalls or sources of error, and how to perform reproducibility and reliability studies.

Purpose

Magnetic resonance (MR) biological markers (or “biomarkers”) to provide information critical to the development of novel therapeutic agents and improved clinical diagnostics has grown in recent years. Biomarkers [1-3] are objectively measured parameters that indicate biological state, biological/pathobiological processes or pharmacologic responses to treatment. While quantitative mapping of biomarkers can greatly increase the amount, reliability, and comparability of the data obtained from medical imaging, it requires careful standardization of protocols and the development of phantoms (standard reference objects or calibration structures) to validate the accuracy of these in vivo measurements as well as to assess the repeatability and reproducibility of the measurements across imaging platforms and time. Interest in biomarkers has stimulated a large number of new standards efforts to ensure accuracy and consistency across platforms. ISMRM, RSNA-QIBA [4], DoD, VA, NEMA [5], MITA [5], ACR, AAPM, PhRMA, NIH, FDA and others are interested in actively developing standards to ensure image-based biomarkers can be used reliably.

Methods

The talk will review how to select an appropriate phantom [6], reviewing some of the phantoms available [7-10], including digital reference objects [11-12], and how to use the phantom to identify sources of error in cross-platform studies.

Discussion

Discussion: Using the standardization of magnetic resonance elastography (MRE) across manufacturer platforms as a case study, the talk will emphasize the need for reproducibility papers in the path to standardization and clinical use [13-15].

Acknowledgements

The NIST Magnetic Imaging Group.

References

[1] Atkinson AJ, Colburn WA, DeGruttola VG, DeMets DL, Downing GJ, Hoth DF, Oates JA, Peck CC, Schooley RT, Spilker BA, Woodcock J, Zeger SL. Biomarkers and surrogate endpoints: Preferred definitions and conceptual framework. Clin Pharmacol Ther. 2001;69(3):89-95.

[2] Kessler LG, Barnhart HX, Buckler AJ, Choudhury KR, Kondratovich MV, Toledano A, Guimaraes AR, Filice R, Zhang Z, Sullivan DC, QIBA Terminology Working Group. The emerging science of quantitative imaging biomarkers terminology and definitions for scientific studies and regulatory submissions. Statistical methods in medical research. 2014. doi: 10.1177/0962280214537333. PubMed PMID: 24919826.

[3] Raunig DL, McShane LM, Pennello G, Gatsonis C, Carson PL, Voyvodic JT, Wahl RL, Kurland BF, Schwarz AJ, Gonen M, Zahlmann G, Kondratovich M, O’Donnell K, Petrick N, Cole PE, Garra B, Sullivan DC, QIBA Technical Performance Working Group. Quantitative imaging biomarkers: A review of statistical methods for technical performance assessment. Statistical methods in medical research. 2014. doi: 10.1177/0962280214537344. PubMed PMID: 24919831.

[4] RSNA-QIBA Profiles http://qibawiki.rsna.org/index.php/Profiles

[5] NEMA/MITA/DICOM http://dicom.nema.org/

[6] Keenan KE, Ainslie M, Barker AJ, Boss MA, Cecil KM, Charles C, Chenevert TL, Clarke L, Evelhoch JL, Finn P, Gembris D, Gunter JL, Hill DLG, Jack CR Jr, Jackson EF, Liu G, Russek SE, Sharma SD, Steckner M, Stupic KF, Trzasko JD, Yuan C, Zheng J. Quantitative magnetic resonance imaging phantoms: A review and the need for a system phantom. Magn Reson Med 20018;79(1):48-61.

[7] https://www.nist.gov/programs-projects/mri-standards

[8] Russek SE, Boss MA, Jackson EF, Jennings D, Evelhoch J, Gunter J, Sorensen A. Characterization of NIST/ISMRM MRI System Phantom. International Society for Magnetic Resonsance in Medicine; 2012; Melbourne, Australia.

[9] Boss MA, Chenevert T, Waterton J, Morris D, Ragheb H, Jackson A, deSouza N, Collins D, van Beers B, Garteiser P, Doblas S, Persigehl T, Hedderich D, Martin A, Mukherjee P, Keenan KE, Russek SE, Jackson EF, Zahlmann G. Thermally-Stabilized Isotropic Diffusion Phantom for Multisite Assessment of Apparent Diffusion Coefficient Reproducibility. Medical Physics. 2014;41(6)464.

[10] Keenan KE, WIlmes LJ, Aliu SO, Newitt DC, Jones EF, Boss MA, Stupic KF, Russek SE, Hylton NM. Design of a breast phantom for quantitative MRI. JMRI. 2016;44(3):610-9.

[11] DCE-MRI for QIBA http://qibawiki.rsna.org/index.php/Synthetic_DCE-MRI_Data

[12] Bosca RJ and Jackson EF. Creating an anthropomorphic digital MR phantom – an extensible tool for comparing and evaluating quantitative imaging algorithms. Physics in Medicine and Biology. 2016;61(2):974.

[13] Shire NJ, Yin M, Chen J, Railkar RA, Fox-Bosetti S, Johnson SM, Beals CR, Dardzinski BJ, Sanderson SO, Talwalker JA, Ehman RL. Test-retest repeatability of MR elastography for noninvasive liver fibrosis assessment in hepatitis C. JMRI. 2011;34(4):947-955.

[14] Hines CDG, Bley TA, Lindstrom MJ, Reeder SB. Repeatability of magnetic resonance elastography for quantification of hepatic stiffness. JMRI. 2010;31(3):725-731.

[15] Wang QB, Zhu H, Liu HL, Zhang B. Performance of magnetic resonance elastography and diffusion-weighted imaging for the staging of hepatic fibrosis: A meta-analysis. Hepatology. 2012. Doi: 10.1002/hep.25610

Proc. Intl. Soc. Mag. Reson. Med. 26 (2018)