Ronald J. Killiany

Whole Brain Segmentation: Automated Labeling of Neuroanatomical Structures in the Human Brain

We present a technique for automatically assigning a neuroanatomical label to each voxel in an MRI volume based on probabilistic information automatically estimated from a manually labeled training set. In contrast to existing segmentation procedures that only label a small number of tissue classes, the current method assigns one of 37 labels to each voxel, including left and right caudate, putamen, pallidum, thalamus, lateral ventricles, hippocampus, and amygdala. The classification technique employs a registration procedure that is robust to anatomical variability, including the ventricular enlargement typically associated with neurological diseases and aging. The technique is shown to be comparable in accuracy to manual labeling, and of sufficient sensitivity to robustly detect changes in the volume of noncortical structures that presage the onset of probable Alzheimers disease.

An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.

The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI methods

The Alzheimers Disease Neuroimaging Initiative (ADNI) is a longitudinal multisite observational study of healthy elders, mild cognitive impairment (MCI), and Alzheimers disease. Magnetic resonance imaging (MRI), (18F)‐fluorodeoxyglucose positron emission tomography (FDG PET), urine serum, and cerebrospinal fluid (CSF) biomarkers, as well as clinical/psychometric assessments are acquiredat multiple time points. All data will be cross‐linked and made available to the general scientific community. The purpose of this report is to describe the MRI methods employed in ADNI. The ADNI MRI core established specifications thatguided protocol development. A major effort was devoted toevaluating 3D T1‐weighted sequences for morphometric analyses. Several options for this sequence were optimized for the relevant manufacturer platforms and then compared in a reduced‐scale clinical trial. The protocol selected for the ADNI study includes: back‐to‐back 3D magnetization prepared rapid gradient echo (MP‐RAGE) scans; B1‐calibration scans when applicable; and an axial proton density‐T2 dual contrast (i.e., echo) fast spin echo/turbo spin echo (FSE/TSE) for pathology detection. ADNI MRI methods seek to maximize scientific utility while minimizing the burden placed on participants. The approach taken in ADNI to standardization across sites and platforms of the MRI protocol, postacquisition corrections, and phantom‐based monitoring of all scanners could be used as a model for other multisite trials. J. Magn. Reson. Imaging 2008.

Reliability of MRI-derived measurements of human cerebral cortical thickness: the effects of field strength, scanner upgrade and manufacturer.

In vivo MRI-derived measurements of human cerebral cortex thickness are providing novel insights into normal and abnormal neuroanatomy, but little is known about their reliability. We investigated how the reliability of cortical thickness measurements is affected by MRI instrument-related factors, including scanner field strength, manufacturer, upgrade and pulse sequence. Several data processing factors were also studied. Two test-retest data sets were analyzed: 1) 15 healthy older subjects scanned four times at 2-week intervals on three scanners; 2) 5 subjects scanned before and after a major scanner upgrade. Within-scanner variability of global cortical thickness measurements was <0.03 mm, and the point-wise standard deviation of measurement error was approximately 0.12 mm. Variability was 0.15 mm and 0.17 mm in average, respectively, for cross-scanner (Siemens/GE) and cross-field strength (1.5 T/3 T) comparisons. Scanner upgrade did not increase variability nor introduce bias. Measurements across field strength, however, were slightly biased (thicker at 3 T). The number of (single vs. multiple averaged) acquisitions had a negligible effect on reliability, but the use of a different pulse sequence had a larger impact, as did different parameters employed in data processing. Sample size estimates indicate that regional cortical thickness difference of 0.2 mm between two different groups could be identified with as few as 7 subjects per group, and a difference of 0.1 mm could be detected with 26 subjects per group. These results demonstrate that MRI-derived cortical thickness measures are highly reliable when MRI instrument and data processing factors are controlled but that it is important to consider these factors in the design of multi-site or longitudinal studies, such as clinical drug trials.

Use of structural magnetic resonance imaging to predict who will get Alzheimer's disease

We used magnetic resonance imaging (MRI) measurements to determine whether persons in the prodromal phase of Alzheimers disease (AD) could be accurately identified before they developed clinically diagnosed dementia. Normal subjects (n = 24) and those with mild memory difficulty (n = 79) received an MRI scan at baseline and were then followed annually for 3 years to determine which individuals subsequently met clinical criteria for AD. Patients with mild AD at baseline were also evaluated (n = 16). Nineteen of the 79 subjects with mild memory difficulty “converted” to a diagnosis of probable AD after 3 years of follow‐up. Baseline MRI measures of the entorhinal cortex, the banks of the superior temporal sulcus, and the anterior cingulate were most useful in discriminating the status of the subjects on follow‐up examination. The accuracy of discrimination was related to the clinical similarity between groups. One hundred percent (100%) of normal subjects and patients with mild AD could be discriminated from one another based on these MRI measures. When the normals were compared with the individuals with memory impairments who ultimately developed AD (the converters), the accuracy of discrimination was 93%, based on the MRI measures at baseline (sensitivity = 0.95; specificity = 0.90). The discrimination of the normal subjects and the individuals with mild memory problems who did not progress to the point where they met clinical criteria for probable AD over the 3 years of follow‐up (the “questionables”) was 85% and the discrimination of the questionables and converters was 75%. The apolipoprotein E genotype did not improve the accuracy of discrimination. The specific regions selected for each of these discriminations provides information concerning the hierarchical fashion in which the pathology of AD may affect the brain during its prodromal phase. Ann Neurol 2000;47:430–439.

Medial temporal lobe function and structure in mild cognitive impairment

Functional magnetic resonance imaging (fMRI) was used to study memory‐associated activation of medial temporal lobe (MTL) regions in 32 nondemented elderly individuals with mild cognitive impairment (MCI). Subjects performed a visual encoding task during fMRI scanning and were tested for recognition of stimuli afterward. MTL regions of interest were identified from each individuals structural MRI, and activation was quantified within each region. Greater extent of activation within the hippocampal formation and parahippocampal gyrus (PHG) was correlated with better memory performance. There was, however, a paradoxical relationship between extent of activation and clinical status at both baseline and follow‐up evaluations. Subjects with greater clinical impairment, based on the Clinical Dementia Rating Sum of Boxes, recruited a larger extent of the right PHG during encoding, even after accounting for atrophy. Moreover, those who subsequently declined over the 2.5 years of clinical follow‐up (44% of the subjects) activated a significantly greater extent of the right PHG during encoding, despite equivalent memory performance. We hypothesize that increased activation in MTL regions reflects a compensatory response to accumulating AD pathology and may serve as a marker for impending clinical decline. Ann Neurol 2004;56:27–35

White matter changes with normal aging

We evaluated brain tissue compartments in 72 healthy volunteers between the ages of 18 and 81 years with quantitative MRI. The intracranial fraction of white matter was significantly lower in the age categories above 59 years. The CSF fraction increased significantly with age, consistent with previous reports. The intracranial percentage of gray matter decreased somewhat with age, but there was no significant difference between the youngest subjects and the subjects above 59. A covariance adjustment for the volume of hyperintensities did not alter the foregoing results. The intracranial percentage of white matter volume was strongly correlated with the percentage volume of CSF. The finding of a highly significant decrease with age in white matter, in the absence of a substantial decrease in gray matter, is consistent with recent neuropathologic reports in humans and nonhuman primates.

MRI-derived measurements of human subcortical, ventricular and intracranial brain volumes: Reliability effects of scan sessions, acquisition sequences, data analyses, scanner upgrade, scanner vendors and field strengths

Automated MRI-derived measurements of in-vivo human brain volumes provide novel insights into normal and abnormal neuroanatomy, but little is known about measurement reliability. Here we assess the impact of image acquisition variables (scan session, MRI sequence, scanner upgrade, vendor and field strengths), FreeSurfer segmentation pre-processing variables (image averaging, B1 field inhomogeneity correction) and segmentation analysis variables (probabilistic atlas) on resultant image segmentation volumes from older (n=15, mean age 69.5) and younger (both n=5, mean ages 34 and 36.5) healthy subjects. The variability between hippocampal, thalamic, caudate, putamen, lateral ventricular and total intracranial volume measures across sessions on the same scanner on different days is less than 4.3% for the older group and less than 2.3% for the younger group. Within-scanner measurements are remarkably reliable across scan sessions, being minimally affected by averaging of multiple acquisitions, B1 correction, acquisition sequence (MPRAGE vs. multi-echo-FLASH), major scanner upgrades (Sonata-Avanto, Trio-TrioTIM), and segmentation atlas (MPRAGE or multi-echo-FLASH). Volume measurements across platforms (Siemens Sonata vs. GE Signa) and field strengths (1.5 T vs. 3 T) result in a volume difference bias but with a comparable variance as that measured within-scanner, implying that multi-site studies may not necessarily require a much larger sample to detect a specific effect. These results suggest that volumes derived from automated segmentation of T1-weighted structural images are reliable measures within the same scanner platform, even after upgrades; however, combining data across platform and across field-strength introduces a bias that should be considered in the design of multi-site studies, such as clinical drug trials. The results derived from the young groups (scanner upgrade effects and B1 inhomogeneity correction effects) should be considered as preliminary and in need for further validation with a larger dataset.

Thalamic atrophy and cognition in multiple sclerosis

Objectives: Recent studies have indicated that brain atrophy is more closely associated with cognitive impairment in multiple sclerosis (MS) than are conventional MRI lesion measures. Enlargement of the third ventricle shows a particularly strong correlation with cognitive impairment, suggesting clinical relevance of damage to surrounding structures, such as the thalamus. Previous imaging and pathology studies have demonstrated thalamic involvement in MS. In this study, we tested the hypothesis that thalamic volume is lower in MS than in normal subjects, and that thalamic atrophy in MS correlates with cognitive function. Methods: We studied 79 patients with MS and 16 normal subjects. A subgroup of 31 MS subjects underwent cognitive testing. The thalamus was segmented in whole from three-dimensional MRI scans. We also determined whole brain atrophy (brain parenchymal fraction), third ventricular width, and whole brain T2-weighted (fluid-attenuated inversion recovery) hyperintense, T1 hypointense, and gadolinium-enhanced lesion volumes. Results: Normalized thalamic volume was 16.8% lower in the MS group (p < 0.0001) vs controls. Cognitive performance in all domains was moderately to strongly related to thalamic volume in the MS group (r = 0.506 to 0.724, p < 0.005), and thalamic volume entered and remained in all regression models predicting cognitive performance. Thalamic volume showed a weak relationship to physical disability score (r = −0.316, p = 0.005). Conclusion: These findings suggest that thalamic atrophy is a clinically relevant biomarker of the neurodegenerative disease process in multiple sclerosis.

Update on the magnetic resonance imaging core of the Alzheimer's disease neuroimaging initiative.

Functions of the Alzheimers Disease Neuroimaging Initiative (ADNI) magnetic resonance imaging (MRI) core fall into three categories: (1) those of the central MRI core laboratory at Mayo Clinic, Rochester, Minnesota, needed to generate high quality MRI data in all subjects at each time point; (2) those of the funded ADNI MRI core imaging analysis groups responsible for analyzing the MRI data; and (3) the joint function of the entire MRI core in designing and problem solving MR image acquisition, pre‐processing, and analyses methods. The primary objective of ADNI was and continues to be improving methods for clinical trials in Alzheimers disease. Our approach to the present (“ADNI‐GO”) and future (“ADNI‐2,” if funded) MRI protocol will be to maintain MRI methodological consistency in the previously enrolled “ADNI‐1” subjects who are followed up longitudinally in ADNI‐GO and ADNI‐2. We will modernize and expand the MRI protocol for all newly enrolled ADNI‐GO and ADNI‐2 subjects. All newly enrolled subjects will be scanned at 3T with a core set of three sequence types: 3D T1‐weighted volume, FLAIR, and a long TE gradient echo volumetric acquisition for micro hemorrhage detection. In addition to this core ADNI‐GO and ADNI‐2 protocol, we will perform vendor‐specific pilot sub‐studies of arterial spin‐labeling perfusion, resting state functional connectivity, and diffusion tensor imaging. One of these sequences will be added to the core protocol on systems from each MRI vendor. These experimental sub‐studies are designed to demonstrate the feasibility of acquiring useful data in a multicenter (but single vendor) setting for these three emerging MRI applications.