Abstract
BackgroundActivity of disease in patients with multiple sclerosis (MS) is monitored by detecting and delineating hyper-intense lesions on MRI scans. The Minimum Area Contour Change (MACC) algorithm has been created with two main goals: a) to improve inter-operator agreement on outlining regions of interest (ROIs) and b) to automatically propagate longitudinal ROIs from the baseline scan to a follow-up scan.MethodsThe MACC algorithm first identifies an outer bound for the solution path, forms a high number of iso-contour curves based on equally spaced contour values, and then selects the best contour value to outline the lesion. The MACC software was tested on a set of 17 FLAIR MRI images evaluated by a pair of human experts and a longitudinal dataset of 12 pairs of T2-weighted Fluid Attenuated Inversion Recovery (FLAIR) images that had lesion analysis ROIs drawn by a single expert operator.ResultsIn the tests where two human experts evaluated the same MRI images, the MACC program demonstrated that it could markedly reduce inter-operator outline error. In the longitudinal part of the study, the MACC program created ROIs on follow-up scans that were in close agreement to the original expert’s ROIs. Finally, in a post-hoc analysis of 424 follow-up scans 91% of propagated MACC were accepted by an expert and only 9% of the final accepted ROIS had to be created or edited by the expert.ConclusionWhen used with an expert operator's verification of automatically created ROIs, MACC can be used to improve inter- operator agreement and decrease analysis time, which should improve data collected and analyzed in multicenter clinical trials.
Highlights
Activity of disease in patients with multiple sclerosis (MS) is monitored by detecting and delineating hyper-intense lesions on MRI scans
Values for Detection Error (DE), Outline Error Rate (OER), and Similarity Index (SI) for the two raters’ original ROIs and the corresponding MACC ROIs from Dataset 1 (Rows 2 and 3 of Table 1) were better than those found between two raters without MACC (Row 1, Table 1)
The average DE, OER, and SI values between the original and MACC ROIs were in each case better than the corresponding values found in the comparison between the two raters (Row 1, Table 1)
Summary
Activity of disease in patients with multiple sclerosis (MS) is monitored by detecting and delineating hyper-intense lesions on MRI scans. Large agreement differences often exist between operators drawing regions of interest (ROIs) of hyperintense lesions on Fluid Attenuated Inversion Recovery (FLAIR) MRI brain scans of patients with multiple sclerosis (MS) despite training and standards designed to minimize interoperator variability [1,2,3,4]. These differences can be broken down into two categories: a) lesion outline disagreement and b) lesion detection disagreement. If a 10x10 pixel ROI increased by a half pixel in each direction, the new area would be 21% larger
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