Simon J. Francis

Review of automatic segmentation methods of multiple sclerosis white matter lesions on conventional magnetic resonance imaging

Magnetic resonance (MR) imaging is often used to characterize and quantify multiple sclerosis (MS) lesions in the brain and spinal cord. The number and volume of lesions have been used to evaluate MS disease burden, to track the progression of the disease and to evaluate the effect of new pharmaceuticals in clinical trials. Accurate identification of MS lesions in MR images is extremely difficult due to variability in lesion location, size and shape in addition to anatomical variability between subjects. Since manual segmentation requires expert knowledge, is time consuming and is subject to intra- and inter-expert variability, many methods have been proposed to automatically segment lesions. The objective of this study was to carry out a systematic review of the literature to evaluate the state of the art in automated multiple sclerosis lesion segmentation. From 1240 hits found initially with PubMed and Google scholar, our selection criteria identified 80 papers that described an automatic lesion segmentation procedure applied to MS. Only 47 of these included quantitative validation with at least one realistic image. In this paper, we describe the complexity of lesion segmentation, classify the automatic MS lesion segmentation methods found, and review the validation methods applied in each of the papers reviewed. Although many segmentation solutions have been proposed, including some with promising results using MRI data obtained on small groups of patients, no single method is widely employed due to performance issues related to the high variability of MS lesion appearance and differences in image acquisition. The challenge remains to provide segmentation techniques that work in all cases regardless of the type of MS, duration of the disease, or MRI protocol, and this within a comprehensive, standardized validation framework. MS lesion segmentation remains an open problem.

Choline is increased in pre-lesional normal appearing white matter in multiple sclerosis.

Abstract.Objective: Our aim was to determine if the resonance intensity of choline-containing compounds (Cho) measured using proton magnetic resonance spectroscopy (MRS) was increased in pre-lesional normal appearing white matter (NAWM) in patients with multiple sclerosis (MS) relative to NAWM that remained stable in subsequent scans. Background: The Cho peak in MR spectra is associated with membrane phospholipids and increases in acute MS plaques, possibly even before the appearance of MRI-visible MS lesions. Methods: Three combined proton MRI and MRS imaging examinations of the corpus callosum and adjacent periventricular white matter were performed on 12 MS patients at intervals of 6 months. Proton density (PD) images were visually matched across 3 time points and the lesion volume in each voxel of the volume of interest was determined. The voxels were subdivided into four groups based on the presence or absence of lesion at baseline and change or no change in lesion volume on the subsequent scan. Results: We found a significantly higher baseline Cho/Creatine (Cr) ratio in NAWM voxels that displayed MRI visible lesions 6 months later than NAWM voxels that remained unchanged (1.57 ± 0.30 and 1.37 ± 0.33, respectively, p < 0.001). The 12-month interval data revealed similar pre-lesional elevated Cho/Cr, (1.51 ± 0.29 versus 1.39 ± 0.32, p = 0.009). Voxels that contained lesion at baseline and increased in lesion volume at 6 months also showed a significantly higher Cho/Cr ratio than those whose lesion volume did not change (1.60 ± 0.32 and 1.49 ± 0.36, respectively, p = 0.043). Conclusions: The results of this study are consistent with focal pre-lesional myelin membrane pathology in the NAWM at least 12 months before lesions become visible on conventional MRI. This could reflect altered myelin chemistry or the presence of inflammation as seen in experimental allergic encephalomyelitis.

Magnetization transfer can predict clinical evolution in patients with multiple sclerosis

Abstract. The clinical course of multiple sclerosis (MS) is highly variable ranging from benign to aggressive, and is difficult to predict. Since magnetization transfer (MT) imaging can detect focal abnormalities in normal-appearing white matter (NAWM) before the appearance of lesions on conventional MRI, we hypothesized that changes in MT might be able to predict the clinical evolution of MS. We assessed MR data from MS patients who were subsequently followed clinically for 5 years. We computed the mean MT ratio (MTr) in gray matter, in lesions identified on T2-weighted MRI, and in NAWM, as well as in a thick central brain slice for each patient. Patients were divided into stable and worsening groups according to their change in Expanded Disability Status Scale (EDSS) scores over 5 years. We calculated the sensitivity, specificity, predictive value, and odds ratio of the baseline MTr measures in order to assess their prognostic utility. We found significant differences in baseline MTr values in NAWM (p = 0.005) and brain slice (p = 0.03) between clinically stable and worsening MS patients. When these MTr values were compared with changes in EDSS over 5 years, a strong correlation was found between the EDSS changes and MTr values in both NAWM (SRCC = −0.76, p < 0.001) and in the brain slice (SRCC = 0.59, p = 0.01). Baseline NAWM MTr correctly predicted clinical evolution in 15/18 patients (1 false positive and 2 false negatives), yielding a positive predictive value of 77.78 %, a negative predictive value of 88.89 %, and an odds ratio of 28. The relationship between 5-year changes in EDSS and MTr values in T2 weighted MRI lesions was weaker (SRCC = −0.43, p = 0.07). Our data support the notion that the quantification of MTr in the NAWM can predict the clinical evolution of MS. Lower MTr values predict poorer long-term clinical outcome. Abnormalities of MTr values in the NAWM are more relevant to the development of future patient disability than those in the T2-weighted MRI lesions.

Regional variations in normal brain shown by quantitative magnetization transfer imaging

A quantitative magnetization transfer imaging (qMTI) study, based on a two‐pool model of magnetization transfer, was performed on seven normal subjects to determine, on a regional basis, normal values for the pool sizes, exchange, and relaxation parameters that characterize the MT phenomenon. Regions were identified on high‐resolution anatomical scans using a combination of manual and automatic methods. Only voxels identified as pure tissue at the resolution of the quantitative scans were considered for analysis. While no left/right differences were observed, significant differences were found among white‐matter regions and gray‐matter regions. These regional differences were compared with existing cytoarchitectural data. In addition, the pattern and magnitude of the regional differences observed in white matter was found to be different from that reported previously for an alternative putative MRI measure of myelination, the 10–50‐ms T2 component described as myelin water. Magn Reson Med 51:299–303, 2004.

Evaluation of automated techniques for the quantification of grey matter atrophy in patients with multiple sclerosis

Several methods exist and are frequently used to quantify grey matter (GM) atrophy in multiple sclerosis (MS). Fundamental to all available techniques is the accurate segmentation of GM in the brain, a difficult task confounded even further by the pathology present in the brains of MS patients. In this paper, we examine the segmentations of six different automated techniques and compare them to a manually defined reference standard. Results demonstrate that, although the algorithms perform similarly to manual segmentations of cortical GM, severe shortcomings are present in the segmentation of deep GM structures. This deficiency is particularly relevant given the current interest in the role of GM in MS and the numerous reports of atrophy in deep GM structures.

Lesion distribution in children with clinically isolated syndromes

We evaluated the incidence, volume, and spatial distribution of T2‐weighted magnetic resonance imaging lesions in 58 children with clinically isolated syndromes at risk for multiple sclerosis compared with 58 adults with relapsing‐remitting multiple sclerosis. Pediatric patients with clinically isolated syndromes who had brain lesions had supratentorial lesion volumes similar to adult multiple sclerosis patients, but greater infratentorial lesion volumes (p < 0.009), particularly in the pons of male patients. The predilection for infratentorial lesions the pediatric patients with clinically isolated syndromes may reflect immunological differences or differences in myelin, possibly related to the caudorostral temporal gradient in myelin maturation. Ann Neurol 2008

Gradient distortions in MRI: characterizing and correcting for their effects on SIENA-generated measures of brain volume change.

Precise and accurate quantification of whole-brain atrophy based on magnetic resonance imaging (MRI) data is an important goal in understanding the natural progression of neurodegenerative disorders such as Alzheimers disease and multiple sclerosis. We found that inconsistent MRI positioning of subjects is common in typically acquired clinical trial data - particularly along the magnets long (i.e., Z) axis. We also found that, if not corrected for, the gradient distortion effects associated with such Z-shifts can significantly decrease the accuracy and precision of MRI-derived measures of whole-brain atrophy - negative effects that increase in magnitude with (i) increases in the Z-distance between the brains to be compared and (ii) increases in the Z-distance from magnet isocenter of the center of the pair of brains to be compared. These gradient distortion effects can be reduced by accurate subject positioning, and they can also be corrected post hoc with the use of appropriately-generated gradient-distortion correction fields. We used a novel DUPLO-based phantom to develop a spherical-harmonics-based gradient distortion field that was used to (i) correct for observed Z-shift-associated gradient distortion effects on SIENA-generated measures of brain atrophy and (ii) simulate the gradient distortion effects that might be expected with a greater range of Z-shifts than those that we were able to acquire. Our results suggest that consistent alignment to magnet isocenter and/or correcting for the observed effects of gradient distortion should lead to more accurate and precise estimates of brain-related changes and, as a result, to increased statistical power in studies aimed at understanding the natural progression and the effective treatment of neurodegenerative disorders.

Axonal injury in the cerebral normal-appearing white matter of patients with multiple sclerosis is related to concurrent demyelination in lesions but not to concurrent demyelination in normal-appearing white matter.

We assessed axonal injury and demyelination in the cerebral normal-appearing white matter (NAWM) of MS patients in a pilot study using proton magnetic resonance spectroscopic imaging and quantitative magnetization transfer (MT) imaging. Resonance intensities of N-acetylaspartate (NAA) relative to creatine (Cr) were measured in a large central brain volume. NAA/Cr in NAWM was estimated by regression of the NAA/Cr in each voxel against white matter fraction and extrapolation to a white matter fraction of 1. The fractional size of the semi-solid pool (F) was obtained from the binary spin bath model of MT by computing the model parameters from multiple MT-weighted and relaxometry acquisitions. F in NAWM was significantly smaller in the patients [0.109 (0.009)] relative to controls [0.123 (0.007), P = 0.011], but did not differ between RR [0.1085] and SP [0.1087] patients [P > 0.99]. NAA/Cr and F in the NAWM were not correlated (r = 0.16, P > 0.7), mainly due to a lack of variation in F among patients. This may indicate a floor to the extent of myelin pathology that can occur in NAWM before a lesion appears, or that axonal damage is not strictly related to demyelination. The correlation between NAWM NAA/Cr and T2w lesion volume was not significant (P > 0.1). However, dividing the lesion volumes by the mean F in T2w lesions resulted in a quantity that correlated well with NAWM NAA/Cr (r = -0.78, P = 0.038), possibly reflecting the association of Wallerian degeneration in the NAWM with axonal transection associated with demyelination within lesions.

The role of edema and demyelination in chronic T1 black holes: A quantitative magnetization transfer study

To use quantitative magnetization transfer imaging (qMTI) in an investigation of T1‐weighted hypointensity observed in clinical magnetic resonance imaging (MRI) scans of multiple sclerosis (MS) patients, which has previously been proposed as a more specific indicator of tissue damage than the more commonly detected T2 hyperintensity.

Evaluating intensity normalization on MRIs of human brain with multiple sclerosis

Intensity normalization is an important pre-processing step in the study and analysis of Magnetic Resonance Images (MRI) of human brains. As most parametric supervised automatic image segmentation and classification methods base their assumptions regarding the intensity distributions on a standardized intensity range, intensity normalization takes on a very significant role. One of the fast and accurate approaches proposed for intensity normalization is that of Nyul and colleagues. In this work, we present, for the first time, an extensive validation of this approach in real clinical domain where even after intensity inhomogeneity correction that accounts for scanner-specific artifacts, the MRI volumes can be affected from variations such as data heterogeneity resulting from multi-site multi-scanner acquisitions, the presence of multiple sclerosis (MS) lesions and the stage of disease progression in the brain. Using the distributional divergence criteria, we evaluate the effectiveness of the normalization in rendering, under the distributional assumptions of segmentation approaches, intensities that are more homogenous for the same tissue type while simultaneously resulting in better tissue type separation. We also demonstrate the advantage of the decile based piece-wise linear approach on the task of MS lesion segmentation against a linear normalization approach over three image segmentation algorithms: a standard Bayesian classifier, an outlier detection based approach and a Bayesian classifier with Markov Random Field (MRF) based post-processing. Finally, to demonstrate the independence of the effectiveness of normalization from the complexity of segmentation algorithm, we evaluate the Nyul method against the linear normalization on Bayesian algorithms of increasing complexity including a standard Bayesian classifier with Maximum Likelihood parameter estimation and a Bayesian classifier with integrated data priors, in addition to the above Bayesian classifier with MRF based post-processing to smooth the posteriors. In all relevant cases, the observed results are verified for statistical relevance using significance tests.