Thomas M. Link1
1Radiology and Biomedical Imaging, UCSF School of Medicine, San Francisco, CA, United States
Synopsis
Keywords: Musculoskeletal: Knee, Musculoskeletal: Joints, Musculoskeletal: Cartilage
The
RSNA Quantitative Imaging Biomarker Alliance (QIBA) mechanism serves to
establish and standardize imaging biomarkers. To date there is only one
musculoskeletal QIBA committee that works on standardizing the application of
T1ρ and T2 imaging as biomarkers for the quantification of cartilage
composition. The committee has established claims for these biomarkers and
composed a profile which includes requirements and recommendations for MRI acquisition,
image analysis, participant handling, image quality assurance, and image
interpretation. Currently the QIBA MSK biomarker committee is in the process of
testing the profile to document clinical feasibility and assessing performance
at different imaging institutions.
Purpose:
To
outline the RSNA Quantitative Imaging Biomarker Alliance (QIBA) mechanism to
approve biomarkers and to report the efforts of the musculoskeletal QIBA committee
to standardize the application of T1ρ and T2 imaging as biomarkers for the
quantification of cartilage composition.
Summary:
Cartilage
loss is irreversible and up to now no effective pharmacotherapies are available
to protect or regenerate cartilage. Quantitative or compositional MR imaging
techniques have been developed to characterize the cartilage matrix quality at
a stage where degenerative disease is at an early and potentially reversible
stage, allowing prevention and life style interventions to halt disease
progression (1). Studies have shown that cartilage
quantitative imaging biomarkers allow earlier diagnosis, better prediction and
more sensitive monitoring of early osteoarthritis of the knee (2,
3). The key advantage of these biomarkers is earlier
detection before cartilage loss has happened and providing a truly
quantitative, reproducible measurement. To date T1ρ and T2
relaxation time measurements are the most frequently used cartilage
compositional imaging biomarkers with the best available reproducibility data.
To
better standardize quantitative imaging biomarkers, the Radiological Society of
North America launched the Quantitative Imaging Biomarkers Alliance (QIBA) in
2007. QIBA aims to "improve the value and practicality of quantitative
imaging biomarkers by reducing variability across devices, sites, patients, and
time" (4) and to "unite researchers,
healthcare professionals and industry to advance quantitative imaging and the
use of imaging biomarkers in clinical trials and clinical practice" (https://www.rsna.org/en/research/quantitative-imaging-biomarkers-alliance).
The
QIBA Musculoskeletal (MSK) Committee aims to standardize the application of T1ρ
and T2 imaging as biomarkers for the quantification of cartilage composition.
To implement this task, the QIBA MSK Committee has worked on requirements and
recommendations for acquisition devices, technologists, radiologists,
reconstruction software, and image analysis tools involved in study participant
handling, image acquisition, image data reconstruction, image quality
assurance, and image interpretation. The requirements are focused on achieving
sufficient reproducibility for the longitudinal evaluation of cartilage
composition by using different MRI scanners.
In
this presentation we will discuss the work of the musculoskeletal QIBA
committee to standardize the application of T1ρ and T2 imaging as biomarkers
for the quantification of cartilage composition. It should be noted that an
outline of the QIBA profile has also been published in Radiology in 2021 (5).
The
QIBA process has several steps and stages to establish an imaging biomarker which
will be outlined:
(i)
Claim: First a claim needs to be developed which can be either
cross-sectional or longitudinal. A cross-sectional claim describes the imaging
procedure’s ability to measure the imaging biomarker at one time point, while a
longitudinal claim describes the ability to measure the change in the imaging
biomarker over multiple time points. For cartilage compositional imaging the
biomarker committee has chosen a longitudinal claim focusing on reproducibility
including test-retest variability and minimum detectable change.
(ii)
Profile Development: Using the QIBA template the committee develops a profile
which centers around the claim and describes the requirements necessary to
achieve the claim. The profile also includes assessment procedures and conformance.
The MSK profile provides information on image data acquisition, analysis, and
interpretation and assessment procedures for T1ρ and T2 cartilage imaging and
test-retest conformance.
(iii)
Public Comment and Consensus: As a next step the profile is distributed to
experts in the field for review and comments. These comments are reviewed by
the committee and addressed in the profile, thus obtaining a consensus
document. The final version of the profile is reviewed and approved by the parent
MRI Biomarker Committee and the Coordinating Committee. Once approved the profile
is published.
(iv)
Clinical feasibility and confirmation: The final steps include testing
the profile to document clinical feasibility at different sites and assessing
performance at the different sites. The QIBA cartilage compositional imaging
profile is currently in these final stages.Acknowledgements
I would
like to acknowledge support through RSNA/QIBA and my QIBA Co-Chair Dr. Xiaojuan
Li as well as NIH/NIAMS funding (R01AR077452, R01AR064771, R01AR078917, OAI). References
1. Link
TM, Neumann J, Li X. Prestructural cartilage assessment using MRI. J Magn Reson
Imaging. 2017;45(4):949-65. doi: 10.1002/jmri.25554. PubMed PMID: 28019053.
2. Luke
AC, Stehling C, Stahl R, Li X, Kay T, Takamoto S, et al. High-field magnetic
resonance imaging assessment of articular cartilage before and after marathon
running: does long-distance running lead to cartilage damage? Am J Sports Med.
2010;38(11):2273-80. Epub 2010/07/16. doi: 0363546510372799 [pii]
10.1177/0363546510372799. PubMed
PMID: 20631252.
3. Razmjoo
A, Caliva F, Lee J, Liu F, Joseph GB, Link TM, et al. T2 analysis of the entire
osteoarthritis initiative dataset. J Orthop Res. 2021;39(1):74-85. Epub
2020/07/22. doi: 10.1002/jor.24811. PubMed PMID: 32691905.
4. Jackson
EF. Quantitative Imaging: The Translation from Research Tool to Clinical
Practice. Radiology. 2018;286(2):499-501. Epub 2018/01/23. doi:
10.1148/radiol.2017172258. PubMed PMID: 29356630.
5. Chalian
M, Li X, Guermazi A, Obuchowski NA, Carrino JA, Oei EH, et al. The QIBA Profile
for MRI-based Compositional Imaging of Knee Cartilage. Radiology.
2021;301(2):423-32. Epub 2021/09/08. doi: 10.1148/radiol.2021204587. PubMed
PMID: 34491127; PubMed Central PMCID: PMCPMC8574057.