Retrospective Correction of ADC for Gradient Nonlinearity Errors in Multicenter Breast DWI Trials: ACRIN6698 Multiplatform Feasibility Study.

Dariya I Malyarenko,David C Newitt,Shivraman Giri,Ajit Devaraj,Luca Marinelli,Thomas L Chenevert,Johannes M Peeters,Ek T Tan,Savannah C Partridge,Lisa J Wilmes,Axel Vom Endt,Ghoncheh Amouzandeh,Nola M Hylton

doi:10.18383/j.tom.2019.00025

Abstract

The presented analysis of multisite, multiplatform clinical oncology trial data sought to enhance quantitative utility of the apparent diffusion coefficient (ADC) metric, derived from diffusion-weighted magnetic resonance imaging, by reducing technical interplatform variability owing to systematic gradient nonlinearity (GNL). This study tested the feasibility and effectiveness of a retrospective GNL correction (GNC) implementation for quantitative quality control phantom data, as well as in a representative subset of 60 subjects from the ACRIN 6698 breast cancer therapy response trial who were scanned on 6 different gradient systems. The GNL ADC correction based on a previously developed formalism was applied to trace-DWI using system-specific gradient-channel fields derived from vendor-provided spherical harmonic tables. For quantitative DWI phantom images acquired in typical breast imaging positions, the GNC improved interplatform accuracy from a median of 6% down to 0.5% and reproducibility of 11% down to 2.5%. Across studied trial subjects, GNC increased low ADC (<1 µm2/ms) tumor volume by 16% and histogram percentiles by 5%–8%, uniformly shifting percentile-dependent ADC thresholds by ∼0.06 µm2/ms. This feasibility study lays the grounds for retrospective GNC implementation in multiplatform clinical imaging trials to improve accuracy and reproducibility of ADC metrics used for breast cancer treatment response prediction.

Highlights

The American College of Radiology Imaging Network (ACRIN) 6698 multicenter breast cancer imaging trial evaluated the use of tumor apparent diffusion coefficient (ADC), measured from diffusionweighted magnetic resonance imaging (MRI) (DWI), for prediction of therapy response (1)
Figures 1 and 3 illustrate the excellent performance of GNL correction (GNC) for the quantitative DWI phantom scanned on representative ACRIN 6698 gradient platforms from 3 different vendors
Narrower histograms observed for 3 T systems compared with those for 1.5 T (Figure 3, A and B; Table 1) are consistent with random noise origin of residual intrasystem broadening of the phantom ADC, reduced at higher field strength

Summary

Introduction

The American College of Radiology Imaging Network (ACRIN) 6698 multicenter breast cancer imaging trial evaluated the use of tumor apparent diffusion coefficient (ADC), measured from diffusionweighted magnetic resonance imaging (MRI) (DWI), for prediction of therapy response (1). The predictive power of the ADC-based diagnostic metric depends on the ability to measure changes in tumor biological characteristics beyond the nonbiological (technical) measurement errors (7, 8). The confidence intervals for ADC metrics are determined (7) both by intrascan precision (repeatability) and interscan accuracy (reproducibility). While precision is typically assessed by within-subject repeatability (8, 9), accuracy is determined with respect to known ADC values, provided by a phantom (10) or a bias-free tissue reference (11)

Methods

Results

Conclusion