Phantom-based quality assurance for multicenter quantitative MRI in locally advanced cervical cancer

Abstract

Background and purpose: A wide variation of MRI systems is a challenge in multicenter imaging biomarker studies as it adds variation in quantitative MRI values. The aim of this study was to design and test a quality assurance (QA) framework based on phantom measurements, for the quantitative MRI protocols of a multicenter imaging biomarker trial of locally advanced cervical cancer. Materials and methods: Fifteen institutes participated (five 1.5 T and ten 3 T scanners). Each institute optimized protocols for T2, diffusion-weighted imaging, T1, and dynamic contrast-enhanced (DCE-)MRI according to system possibilities, institutional preferences and study-specific constraints. Calibration phantoms with known values were used for validation. Benchmark protocols, similar on all systems, were used to investigate whether differences resulted from variations in institutional protocols or from system variations. Bias, repeatability (%RC), and reproducibility (%RDC) were determined. Ratios were used for T2 and T1 values. Results: The institutional protocols showed a range in bias of 0.88-0.98 for T2 (median %RC = 1%; % RDC = 12%), À0.007 to 0.029 Â 10 À3 mm 2 /s for the apparent diffusion coefficient (median %RC = 3%; % RDC = 18%), and 0.39-1.29 for T1 (median %RC = 1%; %RDC = 33%). For DCE a nonlinear vendor-specific relation was observed between measured and true concentrations with magnitude data, whereas the relation was linear when phase data was used. Conclusion: We designed a QA framework for quantitative MRI protocols and demonstrated for a multicenter trial for cervical cancer that measurement of consistent T2 and apparent diffusion coefficient values is feasible despite protocol differences. For DCE-MRI and T1 mapping with the variable flip angle method, this was more challenging.

Multi-site, multi-platform comparison of MRI T1 measurement using the system phantom

“…Previous studies, which found less significant variation in measured T 1 across sites, used six or fewer MRI systems and were highly controlled, in some cases programming the exact same sequence across two platforms from a single vendor rather than using a product sequence [ 11 , 12 , 32 ]. Similar to studies undertaken by Bane et al [ 17 ] and vanHoudt et al [ 19 ], our study included multiple vendor systems and multiple systems within a vendor including product or platform variation, and software variations. This study included two vendors at 1.5 T and three vendors at 3 T with more equal representation across vendors than these previous efforts.…”

“…To distinguish biological variability from technical sources that include MRI system hardware, pulse sequence design, acquisition parameters, and data reduction algorithm, a physical phantom, rather than in vivo measurements, should be used as stable reference standards for “true values” [ 13 ]. Several groups have studied T 1 across measurement methods and hardware (e.g., scanner, coils) using phantoms with known T 1 values in a range suitable for T 1 measurement of cardiac tissue [ 14 , 15 ], white matter [ 16 ], or multiple tissues [ 17 – 19 ]. Some multi-site studies had an uneven distribution of vendor systems, which can adversely impact generalization of results.…”

“…Some multi-site studies had an uneven distribution of vendor systems, which can adversely impact generalization of results. For example, Bane et al and vanHoudt et al both observed a site-specific dependence on the T 1 measurement that may be dependent on the distribution of systems included in their studies [ 17 , 19 ].…”

Quantitative Magnetic Resonance Imaging for Biological Image-Guided Adaptive Radiotherapy

“…Technical validation (124)(125)(126) of qMRI measurements on MRIgRT systems is required to ensure that the results are also relevant outside the MRIgRT domain, in particular because the MR-part of the MRIgRT systems is different from diagnostic systems. Digital and physical phantoms can be used to assess the accuracy and reproducibility of the qMRI measurements (127)(128)(129)(130)(131)(132)(133)(134). Furthermore, to know which changes in qMRI values can be attributed to the effect of the treatment, assessment of the repeatability of the measurements should be performed with test-retest studies (125).…”

Technical Challenges of Real-Time Adaptive MR-Guided Radiotherapy

“…Diffusion-weighted imaging (DWI), for example, can be implemented such that robust quantitative diffusion data can be measured with high repeatability and reproducibility ( 77 ). A major challenge for using quantitative biomarkers in observational and also interventional multi-center MR-linac studies will be the validation of imaging protocols for reproducibility of quantitative imaging in order to prove that quantitative imaging biomarkers are comparable between centers ( 78 ). Furthermore, test-retest studies to assess the level of repeatability will be prerequisites for future quantitative imaging studies in different tumor entities.…”