Metabolic brain networks in translational neurology: concepts and applications

Abstract

Over the past 2 decades, functional imaging techniques have become commonplace in the study of brain disease. Nevertheless, very few validated analytical methods have been developed specifically to identify and measure systems-level abnormalities in living patients. Network approaches are particularly relevant for translational research in the neurodegenerative disorders, which often involve stereotyped abnormalities in brain organization. In recent years, spatial covariance mapping, a multivariate analytical tool applied mainly to metabolic images acquired in the resting state, has provided a useful means of objectively assessing brain disorders at the network level. By quantifying network activity in individual subjects on a scan-by-scan basis, this technique makes it possible to objectively assess disease progression and the response to treatment on a system-wide basis. To illustrate the utility of network imaging in neurological research, we review recent applications of this approach in the study of Parkinson disease and related movement disorders. Novel uses of the technique are discussed, including the prediction of cognitive responses to dopaminergic therapy, evaluation of the effects of placebo treatment on network activity, assessment of preclinical disease progression, and the use of automated pattern-based algorithms to enhance diagnostic accuracy.

FIGURE 1

Parkinson disease (PD)-related spatial covariance pattern. (A) PD-related metabolic pattern (PDRP) identified by spatial covariance analysis of metabolic brain images from 20 PD patients and 20 age-matched healthy volunteer subjects scanned with [¹⁸F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) using the GE Advance tomograph (4.0mm, full width at half-maximum [FWHM]) at The Feinstein Institute for Medical Research (Manhasset, NY). This pattern was characterized by increased metabolic activity (red) in the globus pallidus (GP)/putamen, thalamus, pons, cerebellum, and sensorimotor cortex, associated with relative reductions (blue) in the lateral premotor cortex (PMC) and parieto-occipital association regions. In this combined group, analyzed by principal component analysis, the PDRP was represented by the first principal component pattern (PC1, accounting for 19.5% of the subject × voxel variance), which constituted the largest effect in the data. The display of the voxel weights (ie, the regional loadings) on the resulting pattern were displayed at a reliability threshold of Z = 3, (p < 0.001; bootstrap estimation) and overlaid on T1-weighted magnetic resonance template images. (B) Region weights on PD-related spatial covariance patterns identified in 4 independent cohorts of patient and healthy control subjects scanned with FDG PET. Significant disease-related topographies from the different populations are depicted by colored lines connecting the loadings on 30 standardized regions of interest (ROIs) defined using an automated atlas. The PDRP gold standard pattern (A) is represented by a red line. Additional disease-related metabolic patterns were subsequently identified by spatial covariance analysis of data from separate groups of PD patients and control subjects scanned using a Siemens Biograph PET/CT camera (4.5mm FWHM) at Huashan Hospital (Shanghai, China), the GE Discovery PET/CT camera (5.2mm FWHM) at the Institute of Nuclear Medicine and Allied Sciences (New Delhi, India), and the Siemens HR+ PET camera (4.1mm FWHM) at Groningen University Hospital (Groningen, the Netherlands). These patterns are respectively depicted by green, light blue, and dark blue lines. Voxel weights on the PDRP exhibited a close correlation with corresponding regional values on the subsequent disease-related metabolic topographies (r ≥ 0.90, p < 0.001). Spatial covariance analysis was applied separately to combined group FDG PET data from the 3 independent validation samples, which were each comprised of approximately 20 PD patients and 20 age-matched healthy subjects. Disease-related metabolic patterns were identified in each cohort according to prespecified criteria provided elsewhere. In all 3 cohorts, the resulting PD covariance topography was represented by the largest effect in the data (PC1, accounting for between 16.0 and 20.9% of the subject × voxel variance). Region weights (y-axis) of absolute value ≥0.5 (dashed lines) denote ROIs in which local glucose metabolism contributed significantly to network activity (p < 0.025). (C) Treatment-mediated changes in PDRP expression (mean ± standard error) following stereotactic surgical interventions (shaded bars) targeting the subthalamic nucleus (STN): microlesion (n = 6), subthalamotomy (n = 6), and deep brain stimulation (DBS; n = 18). Changes in network expression during L-dopa (LD) administration (n = 18; solid bar) as well as the test–retest variability of this measure (n = 14; open bar) are depicted for comparison. Significant PDRP modulation was evident following subthalamotomy, STN DBS, and L-dopa treatment but not microlesion. **p < 0.01, ***p < 0.001 for the comparison of changes in PDRP expression with each intervention with those observed during test–retest evaluation, repeated measures analysis of variance. Adapted from Asanuma K, Tang C, Ma Y, et al. Network modulation in the treatment of Parkinson’s disease. Brain 2006;129:2667–2678, by permission of Oxford University Press; Pourfar M, Tang CC, Lin T, et al. Assess the microlesion effect of subthalamic deep brain stimulation surgery with FDG PET. J Neurosurg 2009;110:1278–1282, with permission from American Association of Neurological Surgeons; Mattis P, Tang CC, Ma Y, et al. Network correlates of the cognitive response to levodopa in Parkinson’s disease. Neurology 2011;77:858–865, with permission from Elsevier.

FIGURE 2

Parkinson disease (PD) tremor-related spatial covariance pattern. (A) PD tremor-related metabolic pattern (PDTP) identified by spatial covariance analysis of [¹⁸F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) scans from 9 tremor-dominant PD patients scanned at baseline and during ventral intermediate (Vim) thalamic nucleus deep brain stimulation (DBS). This pattern was characterized by increased metabolic activity in the anterior cerebellum/dentate nucleus (DN), dorsal pons, primary sensorimotor cortex (SMC), and the caudate/putamen. The display of the covariance map was thresholded at Z = 2.70, p < 0.01 and overlaid on T1-weighted magnetic resonance template images. (B) Top: Unified Parkinson Disease Rating Scale (UPDRS) tremor ratings correlated with subject scores for the PDTP (r = 0.54, p < 0.001), but not the PD-related metabolic pattern (PDRP; r = 0.25, p = 0.16). The correlation between tremor and network activity was significantly greater for the PDTP values relative to PDRP (p < 0.05, multiple linear regression). Bottom: Although PDTP expression correlated with UPDRS tremor ratings, these values did not correlate with concurrent ratings for akinesia and rigidity from the same patients (r = 0.23, p = 0.15). Moreover, the correlation between PDTP expression and clinical disability was significantly greater for the tremor ratings relative to akinesia/rigidity (p < 0.01, multiple linear regression). (C) Top: PDTP expression (mean ± standard error [SE]) was elevated at baseline (off-stimulation) in PD patients treated with either Vim DBS (n = 9, black) or subthalamic nucleus (STN) DBS (n = 9, gray), compared with corresponding values from healthy control subjects (n = 20, white). There was a significant difference in PDTP expression across groups (p < 0.001, 1-way analysis of variance [ANOVA]), with comparable elevations in pattern expression in the 2 patient cohorts. **p < 0.005, ***p < 0.001, Student t tests relative to the healthy control subjects. Bottom: Treatment-mediated changes in PDTP expression (mean ± SE) in the Vim thalamic DBS (black), STN DBS (gray), and test–retest (white) patient groups. The degree of PDTP modulation differed across the 3 groups (p < 0.001; 1-way ANOVA), with both Vim thalamic and STN stimulation providing significant reductions in network activity (Vim DBS, ***p < 0.001; STN DBS, **p < 0.01). Of note, the change in PDTP expression during Vim thalamic DBS was larger than with STN stimulation (p < 0.05, post hoc test). Reprinted from Mure H, Hirano S, Tang CC, et al. Parkinson’s disease tremor-related metabolic network: characterization, progression, and treatment effects. Neuroimage 2011;54:1244–1253, with permission from Elsevier.

FIGURE 3

Parkinson disease (PD) related cognitive pattern (PDCP). (A) Identified by spatial covariance analysis of [¹⁸F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) scans from 15 nondemented PD patients with mild to moderate motor symptoms. This pattern was characterized by reduced metabolic activity (blue) in the rostral supplementary motor area (pre-SMA), precuneus, and posterior parietal and prefrontal regions, with relative increases (red) in the cerebellar/dentate nucleus (DN). The display of the covariance map was thresholded at Z = 2.44, p < 0.01 and overlaid on T1-weighted magnetic resonance template images. PMC = premotor cortex. Reprinted from Huang C, Mattis P, Tang C, et al. Metabolic brain networks associated with cognitive function in Parkinson’s disease. Neuroimage 2007;34:714–723, with permission from Elsevier. (B) Relationship between baseline PDCP expression and L-dopa–mediated changes in verbal learning performance. Higher baseline PDCP scores correlated with greater improvement in cognitive functioning during L-dopa treatment (r = 0.70, p < 0.005; n = 17). Patients with meaningful improvement in verbal learning performance during treatment (defined by an independently determined Reliable Change Index [RCI] for this psychometric measure) are depicted by squares; those without meaningful change are depicted by triangles. The horizontal dashed line represents the RCI cutoff of 0.44 for verbal learning test performance ; the vertical dashed line represents the estimated minimal baseline network expression value of 1.01 associated with a meaningful cognitive response to medication. The red symbols denote 2 patients who in addition to FDG PET, underwent PET imaging with [N-methyl-¹¹C]2-(4′-methylaminophenyl)-6-hydroxybenzothiazole (Pittsburgh compound B [PiB]) for the assessment of cortical protein aggregates. (C) Treatment-mediated changes in PDCP expression differed for the 8 PD patients (left) who exceeded the RCI cutoff for cognitive response to L-dopa as compared to 7 others (right) who exhibited a cognitive response of similar magnitude to placebo treatment (p = 0.02; 2 × 2 repeated measures analysis of variance). Significant PDCP modulation was observed in cognitive responders to L-dopa (**p < 0.01, post hoc test) but not to placebo (p = 0.38). B, C reprinted from Mattis P, Tang CC, Ma Y, et al. Network correlates of the cognitive response to levodopa in Parkinson’s disease. Neurology 2011;77:858–865, with permission from Elsevier. (D) Subject 1, with baseline PDCP expression of 2.19, was a cognitive responder to L-dopa by RCI criteria (B, arrow). This patient exhibited normal levels of [¹¹C]-PiB binding (1.09, specific uptake ratio relative to the cerebellum; normal: 1.09 ± 0.10) in cortical areas with significantly low metabolic activity. By contrast, Subject 2, with baseline PDCP expression of 2.01, was a cognitive nonresponder to treatment (B, arrow). This patient exhibited elevated radioligand binding (1.43) in these hypometabolic regions. Thus, despite baseline PDCP elevations of similar magnitude in the 2 patients, Subject 2 additionally exhibited abnormal levels of protein aggregate binding in key network areas (see text). Maps of [¹¹C]-PiB binding (yellow-red) from the 2 subjects were overlaid on a statistical parametric map of abnormal metabolic reductions (blue) identified by voxel-wise comparison of FDG PET scans from 14 PD patients and 15 age-matched healthy volunteer subjects (p < 0.005, uncorrected). [¹¹C]-PiB binding in hypometabolic cortical areas was quantified in the 2 patients and compared with reference values measured in the corresponding scans from the healthy control cohort.

FIGURE 4

Changes in Parkinson disease (PD)-related metabolic pattern (PDRP) activity with disease progression. (A) Time course of PDRP expression in the contralateral (squares) and ipsilateral (triangles) hemispheres of 15 early stage hemiparkinsonian patients scanned at baseline, and 2 and 4 years. On both sides, hemispheric PDRP expression was found to be abnormally elevated at each time point. Network activity increased linearly over time (p < 0.001, repeated measures analysis of variance [RMANOVA]), rising in parallel on both sides. Broken lines denote the mean value (±1 standard error) for PDRP expression measured in 15 age-matched healthy control subjects. *p < 0.05, ***p < 0.001, Student t test comparisons of hemispheric values in patients relative to control subjects. Reprinted from Tang C, Poston K, Dhawan V, et al. Abnormalities in metabolic network activity precede the onset of motor symptoms in Parkinson’s disease. J Neurosci 2010;30:1049–1056, with permission from Society for Neuroscience. (B) Schematic showing significant correlations (p < 0.01) between changes in Unified Parkinson Disease Rating Scale (UPDRS) motor ratings, PDRP network activity, and striatal dopamine transporter binding during the progression of early stage PD. The gray areas indicate overlap between pairs of measures, represented by the strength (R²) of their within-subject correlations. The black area indicates the commonality (interaction effect) of the 3 measures. FPCIT=¹⁸F-FPCIT PET Reprinted from Eckert T, Tang C, Eidelberg D. Assessment of the progression of Parkinson’s disease: a metabolic network approach. Lancet Neurol 2007;6:926–932, with permission from Elsevier. (C) Time course of PDRP expression in 23 advanced PD patients (black line, right) randomized to sham surgery and followed for 1 year as part of a blinded clinical trial of subthalamic nucleus gene therapy. A significant linear increase in whole-brain PDRP expression over time was observed in this group (p < 0.001, RMANOVA), which was in continuity (broken line) with network measurements (black line, left) obtained in a separate longitudinal study of early stage PD patients. By contrast, UPDRS motor ratings (gray line, right) declined in the sham-operated patient group (p < 0.001, RMANOVA), compatible with placebo effect, whereas this measure increased in the longitudinal cohort of early PD patients (gray line, left). The left and right y-axes denote PDRP expression and UPDRS motor ratings, respectively. The x-axis denotes disease duration. Adapted from Tang C, Poston K, Dhawan V, et al. Abnormalities in metabolic network activity precede the onset of motor symptoms in Parkinson’s disease. J Neurosci 2010;30:1049–1056, with permission from Society for Neuroscience. (D) Longitudinal changes in PDRP expression measured in 15 early stage PD patients. In this study, 8 of the subjects (circles) were drug-naive at baseline but were receiving chronic oral L-dopa/carbidopa by the 2-year time point. The remaining 7 subjects (triangles) were chronically treated with L-dopa/carbidopa for at least 3 months before the initial time point. PDRP expression for the 2 groups was similar at baseline (p = 0.86) and at the subsequent 2 time points (p > 0.85). Importantly, the rate of network progression was similar for de novo and chronically treated subjects, indicating that the estimates were not altered by the introduction of symptomatic therapy midstudy (see text).

FIGURE 5

Disease-related spatial covariance patterns for multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). (A) Top: Multiple system atrophy-related metabolic pattern (MSARP) identified by spatial covariance analysis of [¹⁸F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) scans from 10 MSA patients and 10 healthy volunteer subjects.^, This pattern was characterized by reduced metabolic activity (blue) in the putamen and the cerebellum. Bottom: Progressive supranuclear palsy-related metabolic pattern (PSPRP), identified by spatial covariance analysis of FDG PET scans from 10 PSP patients and 10 healthy volunteer subjects, was characterized by reduced metabolic activity (blue) in the medial prefrontal cortex (PFC), the frontal eye fields, the ventrolateral prefrontal cortex, the caudate nuclei, the medial thalamus, and the upper brainstem. The display of the MSARP and PSPRP covariance maps was thresholded at Z = 3.61, p < 0.001 and overlaid on T1-weighted magnetic resonance template images. Reprinted from Eckert T, Tang C, Ma Y, et al. Abnormal metabolic networks in atypical parkinsonism. Mov Disord 2008;23:727–733, with permission from John Wiley & Sons. (B) Receiver operating characteristic (ROC) curves showing accurate network-based classification of FDG PET scans from patients with parkinsonian symptoms of short duration (≤2 years) and indeterminate clinical diagnosis (see text). An ROC curve (red) from a cohort comprised of 55 short-duration patients disclosed accurate classification of the individual scans (area under the curve [AUC] = 0.93, p < 0.001; 95% confidence interval [CI], 0.86–0.99). Of these individuals, 30 were subsequently diagnosed clinically as having classical Parkinson disease (PD); the remaining 25 were diagnosed with either MSA (n = 11) or PSP (n = 14). The validity of the approach is supported by findings from a separate group of 86 patients with clinically indeterminate parkinsonism of short duration (≤2 years; M. Tripathi, personal communication). Members of this testing group were individually classified based on their FDG PET scans according to the same diagnostic algorithm in the first group. An ROC curve (blue) based on these data disclosed a similar degree of diagnostic accuracy (AUC = 0.96, p < 0.001; 95% CI, 0.91–0.99) for the second group. Of these patients, 47 were subsequently diagnosed as having PD; the remaining 39 patients were found to have either MSA (n = 18) or PSP (n = 21).

FIGURE 6

Network activity in presymptomatic patients with rapid eye movement (REM) sleep behavior disorder. (A) Parkinson disease (PD)-related metabolic pattern (PDRP) expression measured in 2 REM-sleep behavior disorder (RBD) patients without clinical signs of parkinsonism. These values were compared with corresponding measurements (mean ± standard error [SE]) from 20 PD patients (light gray) and 22 multiple system atrophy (MSA) patients (8 (dark gray) with short (≤2 year) symptom duration and 14 (black) with longer (>2 year) symptom duration). PDRP values were abnormally elevated in the PD patients (***p < 0.001, Student t test comparison with values [white] from 20 age-matched healthy control subjects), but not in their MSA counterparts. PDRP expression was higher in the first RBD subject (red square) than in the second (blue square). (B) MSA-related metabolic pattern (MSARP) expression in the 2 RBD patients compared with corresponding network values (mean ± SE) in the PD, MSA, and healthy control groups (see above). MSARP expression was abnormally elevated in the MSA patients (***p < 0.001, Student t test comparison with healthy control values), but not in their PD counterparts. MSARP expression was higher in the second RBD than in the first. (C) Bivariate scatter plot depicting individual PDRP and MSARP expression values for the PD (triangles) and MSA (circles) subjects; the 2 RBD patients are represented by red and blue squares (see above). Based on subject scores for the 2 patterns, the first RBD patient is seen to cluster with the PD group (dotted circle), whereas the second clustered with the MSA group (dotted ellipse). Of note, both RBD subjects had network values at the low end of the range for their assigned categories, consistent with their presymptomatic status (see text).