Development and evaluation of an arterial spin-labeling digital reference object for quality control and comparison of data analysis applications

Abstract

Longitudinal assessment of quantitative imaging biomarkers (QIBs) requires a comprehensive quality control (QC) program to minimize bias and variance in measurement results. In addition, the availability of data analysis software from multiple vendors emphasizes the need for a means of quantitatively comparing the computed QIB measures produced by the applications. The purpose of this work is to describe a digital reference object (DRO) that has been developed for the evaluation of arterial spin-labeling (ASL) measurement results. The ASL DRO is a synthetic data set consisting of 10 × 10 voxel square blocks with a range of ASL control image signal-to-noise ratio (SNRControl), blood flow (BF), and proton density (PD) image SNR values (SNRControl:1–100, BF:10–210 ml/100 g min−1, SNRPD:10–100). A pseudo-continuous ASL sequence was simulated with acquisition parameters and modeled signal intensities defined according to those typically associated with clinically-acquired ASL images. ASL parameters were estimated using the commercially-available nordicICE software package (NordicNeuroLab, Inc, Milwaukee, WI). Percent bias measures and Bland–Altman analyses demonstrated decreased bias and variance with increasing SNRControl and BF values. Excellent agreement with reference values was seen for all BF values above an SNRControl of 5 (concordance correlation coefficient greater than 0.92 for all SNRPD values). The ASL DRO developed in this work allows for the evaluation of software bias and variance across physiologically-meaningful BF and SNRControl values. Such studies are essential to the transition of quantitative ASL-based BF measurements into widespread clinical research applications, and ultimately, routine clinical care.