Molecular neuroimaging Most molecular imaging studies relies on analysis of values from brain regions and report descriptive statistics for these values. There are two significant difficulties when comparing molecular neuroimaging studies: 1. Regions differ between studies: E.g., some include values for “temporal cortex ” others do not. 2. Measured and reported values differ between studies and they are not comparable: Tracers and receptors; transport rates (e.g., K1), distribution volume, binding potentials; different methods to compute the values

Finn ˚arup Nielsen

Limbic Lobe

Mathematical Modelling

Nielsen, Finn Årup

Online Research Database In Technology

Databasing Molecular NeuroimagingFinn A˚rup NielsenNeurobiology Research UnitCopenhagen University Hospital RigshospitaletandInformatics and Mathematical ModellingTechnical University of DenmarkMay 24, 2005Databasing Molecular ImagingMolecular neuroimagingMost molecular imaging studies relies on analysis of values from brainregions and report descriptive statistics for these values.There are two significant difficulties when comparing molecular neuroimag-ing studies:1. Regions differ between studies: E.g., some include values for “tem-poral cortex” others do not.2. Measured and reported values differ between studies and they arenot comparable: Tracers and receptors; transport rates (e.g., K1),distribution volume, binding potentials; different methods to computethe values.Finn A˚rup Nielsen 1 May 24, 2005Databasing Molecular ImagingBrain region taxonomyWOROI: 2 Limbic lobeWOROI: 4 Cingulate gyrusWOROI: 5 Posterior cingulate gyrusWOROI: 8 Anterior cingulate gyrusWOROI: 9 Middle cingulate gyrusWOROI: 6 Left posterior cingulate gyrusWOROI: 7 Right posterior cingulate gyrusHierarchical taxonomyof brain regions recordswhich brain areas area part of other brainareas.Imputation: If “leftposterior cingulate”and “right posteriorcingulate” values areavailable in a specificstudy these are usedto define a value for“limbic lobe” — ifthis is not available.Finn A˚rup Nielsen 2 May 24, 2005Databasing Molecular ImagingBrain region taxonomy in the Brede databaseBrain region taxon-omy included in theBrede Database.Talairach coordinatesextracted where theiranatomical label cor-responds to the itemin the taxonomy.Links to NIH MeSH,BrainInfo (Neuro-Names) (Bowdenand Martin, 1995),segmented volumes,Wikipedia.Finn A˚rup Nielsen 3 May 24, 2005Databasing Molecular ImagingData matrixBrain regionsExperimentsData matrix10 20 30 40 50 60 70 8051015202530050100150200250300350X(experiments× regions).For serotonin-2A part of thedatamatrix X(32 × 80):Original matrix: ≈ 13% de-fined.“One-back” imputation: ≈17% definedFull forward/backward impu-tation: ≈ 64% definedFinn A˚rup Nielsen 4 May 24, 2005Databasing Molecular ImagingHandling different range among experimentsStudentize values across Pn = |Pn| regions with the n’th experiment:x˜ = (x− x¯n)/sn with missing valuesx¯n =1|Pn|∑p∈Pnxnp, sn =√√√√ 1|Pn| − 1∑p∈Pn(xnp − x¯n)2. (1)Conversion of data matrix to a “rank order data matrix”: X(N × P ) →X˜(N × P !2(P−2)!)x˜np˜ =1 if xnp > xnp′−1 if xnp < xnp′0 otherwise,(2)where “otherwise” is with xnp = xnp′ or if any of the values for the tworegions p or p′ is not defined.Finn A˚rup Nielsen 5 May 24, 2005Databasing Molecular ImagingData matrix(Exp x woroi)−matrix [ X(73x114) ], row Z−score scaled, Full woroi imputation, submatrix [ X(73x10) ](38, 8) = (Epidepride binding to the D2 receptor, Pu): 1.3628411 2 3 4 5 6 7 8 9 1010203040506070−3−2−1012Restriction to key regions:The 5 lobes, cerebellum, cau-date, putamen, thalamus andhippocampus: X(73× 10)After full imputation and re-striction to key regions: ≈74% defined valuesOutlying brain regions(columns in the data matrix)are: Cerebellum (blue),Caudate and Putamen (red).Finn A˚rup Nielsen 6 May 24, 2005Databasing Molecular ImagingMeasuring difference between experimentsComparison of two experiments represented in vectors xn and xm withthe cross-correlation for missing values (pairwise complete version)r˜nm =∑p∈Pnm x˜npx˜mp√∑p∈Pnm x˜2np√∑p∈Pnm x˜2mp, (3)where Pnm = Pn ∩ Pm with centered data.. . . Or just with an inner producttnm =∑p∈Pnmxnpxmp (4)Finn A˚rup Nielsen 7 May 24, 2005Databasing Molecular ImagingInformation retrieval performance0 10 20 30 40 50 60 70 800.10.20.30.40.50.60.70.80.91Area under the ROC curveSorted experimentsRaw, coffcoefRank, corrcoefOneback imputation, corrcoefFull imputation, corrcoefOneback imputation, key regionsFull imputation, key regionsRank, Full imputation, corrcoefRaw, inner productFull imputation, inner productArea under the ROCcurve as performancemeasureTask: Segregate be-tween serotonin-2Aand non-serotonin-2A studies.Full imputation withcross-correlation co-efficient is the bestmethod.Finn A˚rup Nielsen 8 May 24, 2005Databasing Molecular ImagingComparisons on serotonin-2A studies−4 −3 −2 −1 0 1 2Ada04For02She02Goe04Goe04Aud03Aud03vDy00vDy00vDy00vDy00She04She04Biv94Hal00Kay01Kay01vDy00vDy00vDy00vDy00Bae98Bae98Lip04Lip04Lip04Lip04Lip04Lip04Ros96Ros96Sad95Cg TLFL PL OLCb ThPuCdHiNormalized region valueExperimentCgTLFLPLOLCbThPuCdHi3 “clusters”: Cere-bellum (reference),Low binding (cau-date, putamen,thalamus, hippocam-pus), high binding(cerebral cortex).Little coherenceamong serotoninstudies in the cere-bral cortex, i.e.,the ordering changebetween regionschange.Finn A˚rup Nielsen 9 May 24, 2005Databasing Molecular ImagingClusteringK-means clustering capable of handling missing values in the data matrixX(experiments× regions) (Wishart, 2003).Clustering experimentsX = AC+U, (5)where A contains assignments for experiments, C the pattern across brainregions for prototypical tracers and U residuals.. . . clustering brain regionsX = CA+U (6)These kind of analyses have been made in humans and macaque withautoradiography, e.g., (Ko¨tter et al., 2001).Finn A˚rup Nielsen 10 May 24, 2005Databasing Molecular ImagingClustering of experiments1 2 3 4 5 6 71234567ComponentNumber of componentsClustered experimentsAltanserin bindAge/altanserin Vinpocetine radVinpocetine disAltanserin bindMu−opioid recepMu−opioid recepMTHA time to peAge/altanserin Vinpocetine radVinpocetine disMu−opioid recepMu−opioid recepMTHA distributiMTHA distributiFlumazenil K1 rAltanserin bindAltanserin bindMTHA time to peFluroethylflumaFluroethylflumaFlumazenil distFlumazenil bindFlumazenil distVinpocetine radVinpocetine disMu−opioid recepMu−opioid recepFlumazenil K1 rFlumazenil K1 rAge−correlationWAY−100635 bindAltanserin bindAltanserin bindMTHA time to peSetoperone bindAltanserin bind5−I−R91150 bind5−I−R91150 bind5−I−R91150 bindAge/altanserin MTHA distributiMTHA distributiFluroethylflumaFluroethylflumaFlumazenil distFlumazenil bindFlumazenil distMu−opioid recepMu−opioid recepAge−correlationWAY−100635 bindFLB 457 bindingFLB 457 bindingFLB 457 bindingFLB 457 bindingAltanserin bindMTHA time to peSetoperone bindAltanserin bind5−I−R91150 bind5−I−R91150 bind5−I−R91150 bind5−I−R91150 bindAge/altanserin Altanserin bindFluroethylflumaFluroethylflumaFlumazenil distFlumazenil bindFlumazenil distFlumazenil distVinpocetine radVinpocetine disMTHA distributiMTHA distributiFlumazenil K1 rFlumazenil K1 rChange in altanFLB 457 bindingFLB 457 bindingFLB 457 bindingFLB 457 bindingFLB 457 bindingFLB 457 bindingEpidepride bindEpidepride specAltanserin bindAltanserin bindSetoperone bindAltanserin bind5−I−R91150 bind5−I−R91150 bind5−I−R91150 bind5−I−R91150 bindAge/altanserin MTHA time to peFluroethylflumaFluroethylflumaFlumazenil distFlumazenil bindFlumazenil distFlumazenil distMTHA distributiMTHA distributiFlumazenil K1 rFlumazenil K1 rChange in altanVinpocetine radVinpocetine disMu−opioid recepMu−opioid recepAge−correlationWAY−100635 bindFLB 457 bindingFLB 457 bindingFLB 457 bindingFLB 457 bindingFLB 457 bindingFLB 457 bindingEpidepride bindEpidepride specAltanserin bindAltanserin bindSetoperone bindAltanserin bind5−I−R91150 bind5−I−R91150 bind5−I−R91150 bind5−I−R91150 bindMTHA time to peFluroethylflumaFluroethylflumaFlumazenil distFlumazenil bindFlumazenil distFlumazenil distAge/altanserin Vinpocetine radVinpocetine disFlumazenil K1 rFlumazenil K1 rAge−correlationMu−opioid recepMu−opioid recepWAY−100635 bindMTHA distributiMTHA distributiChange in altanFLB 457 bindingFLB 457 bindingFLB 457 bindingFLB 457 bindingFLB 457 bindingFLB 457 bindingEpidepride specEpidepride totaAltanserin bindSetoperone bindAltanserin bind5−I−R91150 bind5−I−R91150 bind5−I−R91150 bind5−I−R91150 bindAltanserin totaMTHA time to peFluroethylflumaFluroethylflumaFlumazenil distFlumazenil bindFlumazenil distFlumazenil distAge/altanserin Vinpocetine radVinpocetine disFlumazenil K1 rFlumazenil K1 rAge−correlationMu−opioid recepMu−opioid recepWAY−100635 bindMTHA distributiMTHA distributiChange in altanAltanserin bindEpidepride bindFinn A˚rup Nielsen 11 May 24, 2005Databasing Molecular ImagingClustering of brain regions1 2 3 4 5 6123456ComponentNumber of componentsCluster bushPosterior cinguAnterior cingulCerebral CortexTemporal lobeFrontal lobeSuperior temporPosterior cinguAnterior cingulCerebral CortexTemporal lobeFrontal lobeSuperior temporCerebellumThalamusAmygdalaPutamenCaudate nucleusHippocampusPosterior cinguAnterior cingulCerebral CortexTemporal lobeFrontal lobeSuperior temporCerebellumAmygdalaHippocampusInsulaPonsBrain stemThalamusPutamenCaudate nucleusAnterior cingulSuperior temporSubstantia NigrThalamusAmygdalaOrbital gyriPosterior cinguCerebral CortexTemporal lobeFrontal lobeParietal lobePrefrontal cortCerebellumHippocampusPonsPutamenCaudate nucleusSuperior temporSubstantia NigrThalamusAmygdalaHippocampusInsulaPosterior cinguCerebral CortexTemporal lobeFrontal lobeParietal lobePrefrontal cortCerebellum PutamenCaudate nucleusAnterior cingulPonsWhite matterSuperior temporSubstantia NigrThalamusAmygdalaHippocampusInsulaAnterior cingulCerebral CortexTemporal lobeFrontal lobeParietal lobePrefrontal cortOccipital lobe Cerebellum PutamenCaudate nucleusPosterior cinguPonsBrain stemWhite matterFinn A˚rup Nielsen 12 May 24, 2005Databasing Molecular ImagingSummaryPossible to make meta-analysis on brain region based molecular neu-roimaging.Information retrieval and clustering are dependent on key features of thetracer/receptor, e.g., altanserin has low/no binding in cerebellum.Finn A˚rup Nielsen 13 May 24, 2005ReferencesReferencesBowden, D. M. and Martin, R. F. (1995). NeuroNames brain hierarchy. NeuroImage, 2(1):63–84.PMID: 9410576. ISSN 1053-8119.Ko¨tter, R., Stephan, K. E., Palomero-Gallager, N., Geyer, S., Schleicher, A., and Zilles, K. (2001).Multimodal characterisation of cortical areas by multivariate analyses of receptor binding and connec-tivity. Anatomy and Embryology, 204(4):333–349. PMID: 11720237. DOI: 10.1007/s004290100199.ISSN 0340-2061. A study on macaque brain regions using binding characteristics from 9 different lig-ands as well as using anatomical connectivity information. Multidimensional scaling and hierarchincalclustering are used to two receptor-times-brain-regions data matrices.Wishart, D. (2003). k-means clustering with outlier detection, mixed variables and missing values. InSchwaiger, M. and Opitz, O., editors, Exploratory Data Analysis in Empirical Research. Proceedingsof the 25th Annual Conference of the Gesellschaft fu¨r Klassifikation e.V., University of Munich, March14-16, 2001, volume 16 of Studies in Classification, Data Analysis, and Knowledge Organization, pages216–226. Springer, Berlin, Germany. ISBN 3540441832.Finn A˚rup Nielsen 14 May 24, 2005

Databasing Molecular Neuroimaging

Databasing Molecular NeuroimagingFinn A˚rup NielsenNEUROBIOLOGY RESEARCH UNIT, RIGSHOSPITALET, DENMARKPositron emission tomography allows for molecular neuroimaging, e.g., for mapping human neu-rotransmitter systems. Many such studies are performed as either “voxel-based” or “region-based”.Voxel-based studies are usually reported with reference to the Talairach stereotaxic stystem [1]and appear with tables listing “hot spot” foci indicating the centers of areas with significant dif-ference between two groups of scans. The voxel-based approach is widely used in the cognitivefunctional neuroimaging literature. Databasing such studies has been advanced with the Brain-Map database (Research Imaging Center, San Antonio, TX). The newest version of this databasecontains data from over 500 studies, but the interface only allows for preprogramed access to thedata. To allow for a more flexible access we have constructed the Brede database which presentlyrecords data from 126 studies. Apart from cognitive studies the Brede database also containsdata from molecular neuroimaging studies. The experiments in the Brede database are associ-ated with items in an ontology. The ontology contains items for, e.g., cognitive functions andneuroreceptors. Some of the items are linked with corresponding MeSH terms, items from SenseLab(http://senselab.med.yale.edu/senselab/) and other biomedical databases. The items are organizedin a directed graph (a causal network) with the most general concepts (e.g., “neuroreceptor”) at theroots of the graph, while more specialized concepts (e.g., the 5-HT2A receptor) are at the leafs. Therepresentation of the hot spots centers in standardized coordinate space together with the ontologyenables the statistical modeling of the distribution of the Talairach coordinates conditioned on, e.g.,function and neuroreceptor type. So far we have implemented a line of multivariate analysis methodsas well as volume-based similarity metrics that work on these distributions [2].Only few molecular imaging studies are analyzed and reported with respect to the voxel-basedTalairach system. Most studies appear as region-based where specific variables, such as the “bindingpotential”, are reported for a series of brain regions. The regions for which variables are reportedwill typically vary between studies. To handle this variability we have constructed a second ontologyfor the description of brain regions. When results from region-based studies are entered they areannotated with items from this ontology. Current development focuses on building tools for theanalysis of region-based studies and their integration with the voxel-based studies.The published database is available as XML files in the Brain Neuroinformatics Toolbox and onthe Internet on the address http://hendrix.imm.dtu.dk/services/jerne/brede/. The Internet editionalso features results from automated web-page generation.1 J. Talairach and P. Tournoux, Co-planar Stereotaxic Atlas of the Human Brain, Thieme, NewYork (1988)2 F. . Nielsen and L. K. Hansen, Art. Intell. Med., 30 141-151 (2004)1

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Databasing Molecular Neuroimaging

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