EU Integrated Project eTUMOUR celda.pdfPCA HR-MAS PCA HR-MAS. 129. METABOLÓMICA. T=0 C (4 C interior) 4500 Hz. Aprox. 20 mgde tejido. Ro tor cilíndrico (50 µl) (PCA aprox. 2g) D.

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EU Integrated Project eTUMOUR

Project acronym:Project acronym: eTUMOUReTUMOURProject full title:Project full title:WEB ACCESSIBLE MR DECISION SUPPORT SYSTEM FOR BRAIN WEB ACCESSIBLE MR DECISION SUPPORT SYSTEM FOR BRAIN TUMOUR DIAGNOSIS AND PROGNOSIS, INCORPORATING IN TUMOUR DIAGNOSIS AND PROGNOSIS, INCORPORATING IN VIVO AND EX VIVO GENOMIC AND METABOLOMIC DATAVIVO AND EX VIVO GENOMIC AND METABOLOMIC DATA(FP6(FP6--20022002--LIFESCIHEALTH 503094)LIFESCIHEALTH 503094)

ProgrammeProgramme::SIXTH FRAMEWORK PROGRAMMESIXTH FRAMEWORK PROGRAMME PRIORITY LSHPRIORITY LSH--20022002--2.2.02.2.0--55Molecular imaging for early detection of tumours and monitoring Molecular imaging for early detection of tumours and monitoring of of treatmenttreatmentPeriodPeriod:: February February 1, 2004 1, 2004 till January till January 31 2009 (5 31 2009 (5 yearsyears))BudgetBudget:: 7.5 7.5 millionmillion € € EU EU financingfinancing; 9.633 ; 9.633 million million € € OverallOverallParticipantsParticipants:: 21 21 partners partners (14 (14 public institutions and public institutions and 7 7 companiescompanies))CoordinatorCoordinator:: Prof. Dr. Bernardo Celda, Univ. de Valencia, Prof. Dr. Bernardo Celda, Univ. de Valencia, SpainSpainWebsiteWebsite: http://: http://wwwwww.uv.es/.uv.es/etumouretumour

http://www.uv.es/etumour

http://www.uv.es/etumour

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EU Integrated Project eTUMOURAntecedentesAntecedentes

••Los tumores cerebrales afectan a una Los tumores cerebrales afectan a una ↑↑ % de la poblaci% de la poblacióón n europea aumentando al incrementarse las expectativas europea aumentando al incrementarse las expectativas de vida.de vida.••Los tumores del SNC es hoy en día la causa de Los tumores del SNC es hoy en día la causa de mortalidadmortalidadlíderlíder en niños por debajo de en niños por debajo de 15 años15 años y la segunda causay la segunda causade muerte por cáncer para edades comprendidas entre de muerte por cáncer para edades comprendidas entre 1515--34 años.34 años.••Diagnóstico y tratamiento de tumores del SNC está basadoDiagnóstico y tratamiento de tumores del SNC está basadoen la clínica, radiología y en la clínica, radiología y histopatologíahistopatología..••La respuesta a la terapia de tumores con característicasLa respuesta a la terapia de tumores con característicasHistológicas o radiológicas similares es muy variable,Histológicas o radiológicas similares es muy variable,especialmente en tumores pediátricos.especialmente en tumores pediátricos.

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EU Integrated Project eTUMOURAntecedentesAntecedentes

••El diagnóstico El diagnóstico no cruentono cruento por la imagen (RMI) sólo alcanzapor la imagen (RMI) sólo alcanza6060--90%90% de precisión en función del tipo de tumor y grado.de precisión en función del tipo de tumor y grado.••Actual “Actual “gold standardgold standard” ” →→ histopatologhistopatologíía a de biopsias implicade biopsias implicaun proceso quirúrgico “un proceso quirúrgico “invasivoinvasivo” con un riesgo 1” con un riesgo 1--2% de2% demortalidad.mortalidad.••Necesario una mejora para la clasificación y gradación noNecesario una mejora para la clasificación y gradación nocruenta para diagnóstico y pronóstico de tumores de SNCcruenta para diagnóstico y pronóstico de tumores de SNC

••Tres técnicas disponibles:Tres técnicas disponibles:1) ERM in vivo no cruenta1) ERM in vivo no cruenta2) HR2) HR--MAS ex vivo MAS ex vivo →→ METABOLMETABOLÓÓMICAMICA3) Chips ADN ex vivo 3) Chips ADN ex vivo →→ TRANSCRIPTTRANSCRIPTÓÓMICAMICA

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VOI Tumor y VOI Tumor y contralateralcontralateralGLIOMA IVGLIOMA IVNAA

Lípidos

CrComI

ContralateralContralateral

NAA(2)NAA(2)

ββ--GluGluγγ--GlnGln

LacLac

CrCr(2)(2)

αα--GlxGlx

LípidosNAA

Cr

Co

mI

TumorTumor

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Tumor in vivo 1H ERM a 1,5 TTumor in vivo Tumor in vivo 11H ERM a 1,5 TH ERM a 1,5 T

TE 31 ms

TE 136 msTE 136 ms

TE 31 ms

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CoCo

CreatinaCreatina

ColinaColina

NAANAA

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MetástasisMetástasis

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Estudio de biopsias con HR-MAS(ex vivo)

Estudio de biopsias con HR-MAS(ex vivo)

PCA

HR-MAS

PCA

HR-MAS129

METABOLÓMICAMETABOLÓMICA

T=0 C (4 C interior)

4500 Hz

Aprox. 20 mg de tejido

Rotor cilíndrico (50 µl)(PCA aprox. 2g)

D2O ajuste del campo y movilidad

[NMR in [NMR in BiomedicineBiomedicine, Martínez, Martínez--BisbalBisbal et al. 2004;17:1et al. 2004;17:1--15(2004)]15(2004)]

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GBMGlioblastomaMultiforme

Linfoma

Cr

ChomIPCr

PCho

Val

Ala

Lac

Leu

Ile

LeuLeuNAA

Glx

IleIle

NAAAsp

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4GBM PGBM P

MMAMMA

MMBMMB

CrCrCoCo

MMAMMA

MMBMMB

CrCr

CoCo

GlyGly

MMAMMAMMBMMB

NAANAA??

NAANAA??

NAANAA??CrCrCoCo

mI omI oGlyGly

In vivoIn vivoTE=31 TE=31 msms

In vivoIn vivoTE=136 TE=136 msms

ex vivoex vivo

8 GBM SGBM SCoCo

CrCr

mImI

CoCo

CrCrGlyGly

CoCoCrCr

mImI

NAANAA??

MMBMMB

MMAMMA

NAANAA??

NAANAA??

MMBMMB

MMAMMA

MMBMMB

ex vivoex vivo

5 GBM PGBM P

CrCr

CoCo

mImI

CrCr

MMAMMA

MMBMMB

NAANAA??

NAANAA??

CoCo

mImICoCo

CrCr NAANAA??

MMBMMB

MMBMMBMMAMMA

ex vivoex vivo

[NMR in [NMR in BiomedicineBiomedicine, Martínez, Martínez--BisbalBisbal et al. 2004;17:1et al. 2004;17:1--15(2004)]15(2004)]

Department of PathologyUniversity Medical Center Nijmegen

The Netherlands

Gradación de gliomas;características histopatológicas

Gradación de gliomas;características histopatológicas

•• polimorfismo nuclearpolimorfismo nuclear•• actividad mitóticaactividad mitótica•• necrosisnecrosis•• proliferación microvascular proliferación microvascular •• celularidadcelularidad

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The Netherlands

AA GBMGBM

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The Netherlands

Clasificación Histopatológica de gliomasClasificación Histopatológica de gliomas

OsOs OAsOAs AsAs

* Sensible a quimioterapia* Sensible a quimioterapia* Mejor pronóstico

OligodendroglialOligodendroglialTumorsTumors ((OTsOTs) * Mejor pronóstico)

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The Netherlands

Oligodendroglioma Maligno?O GBM con características de oligo?

Oligodendroglioma Maligno?O GBM con características de oligo?

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The Netherlands

Genética de los Tumores del SNCGenGenééticatica de de los Tumoreslos Tumores del SNCdel SNC

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Subtipos Genéticos de GBMsSubtipos Genéticos de GBMsDepartment of Pathology

University Medical Center NijmegenThe Netherlands

De novo / Primarioevolución

Progresión / Secundarioevolución

Astrocito Normal Astrocito Normal Astrocito Normal Astrocito Normal

GBMGBM GBMGBM

AstrocitomaAstrocitoma

Astrocitoma AnaplásicoAstrocitoma Anaplásico

Amplificación :

EGFR (7p12)MDM2 (12q14-15)

Deleción (LOH) o mutación :

p16 (9p21)10p and 10qRB1 (13q14)

Amplificación :

EGFR (7p12)MDM2 (12q14-15)

Deleción (LOH) o mutación :

p16 (9p21)10p and 10qRB1 (13q14)

LOH 17pP53 mutacion (17p13)

LOH 19qLOH 13qLOH 9p

LOH 10qPTEN mutacóon (10q23)

LOH 17pP53 mutacion (17p13)

LOH 19qLOH 13qLOH 9p

LOH 10qPTEN mutacóon (10q23)

LOH: pérdida de heterocigosidad

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The Netherlands

LOH 1pLOH 1p

B T

D1S1597

ID 23462ID 23462Oligoastrocitoma Oligoastrocitoma WHO Grado IIWHO Grado II

B T

D1S1182

ID 23434Anaplásico oligodendroglioma WHO Grado III

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Transcriptómica eTUMOUR

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EU Integrated Project eTUMOUReTUMOUR eTUMOUR GENERAL OBJECTIVESGENERAL OBJECTIVES

•• eTUMOUReTUMOUR aims to create a comprehensive Webaims to create a comprehensive Web--accessible accessible Decision Support System (DSS) for analysis and interpretation Decision Support System (DSS) for analysis and interpretation of in vivo Magnetic Resonance Spectroscopy and Imaging (MRS of in vivo Magnetic Resonance Spectroscopy and Imaging (MRS & MRI) data of brain tumours& MRI) data of brain tumours•• includes a database of clinical, histological, metabolic (NMR includes a database of clinical, histological, metabolic (NMR HRHR--MAS) and molecular phenotype data from brain tumour MAS) and molecular phenotype data from brain tumour patientspatients•• the DSS will facilitate evidencethe DSS will facilitate evidence--based clinical decisionbased clinical decision--making using MR and include new criteria such as genetic based making using MR and include new criteria such as genetic based tumour classificationstumour classifications••the DSS will be also designed with Agent Technology to the DSS will be also designed with Agent Technology to create a secure distributed database accessible transcreate a secure distributed database accessible trans--nationally by collaborating centresnationally by collaborating centres

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eTUMOUReTUMOUR PARTICULAR OBJECTIVES (1)PARTICULAR OBJECTIVES (1)

•• Acquire Acquire in vivo in vivo MRS/MRI and clinical (MRS/MRI and clinical (histopathologyhistopathology, treatment , treatment response and patient outcome) data from brain tumour patientsresponse and patient outcome) data from brain tumour patients

•• Acquire Acquire ex vivoex vivo HR MAS (metabolomic) and DNA microarray HR MAS (metabolomic) and DNA microarray (transcriptomic) data from tumour biopsies(transcriptomic) data from tumour biopsies

•• Correlate metabolomic with transcriptomic profiles of tumours Correlate metabolomic with transcriptomic profiles of tumours and correlate these with clinical dataand correlate these with clinical data

•• Implement pattern recognition methods for classification and Implement pattern recognition methods for classification and analysis of in vivo MRS and ex vivo HRanalysis of in vivo MRS and ex vivo HR--MAS and microarray dataMAS and microarray data

•• Develop transcriptomic based tumour classificationsDevelop transcriptomic based tumour classifications

•• Develop new microarrays specific to tumour classificationDevelop new microarrays specific to tumour classification

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EU Integrated Project eTUMOUReTUMOUReTUMOUR PARTICULAR OBJECTIVES (2)PARTICULAR OBJECTIVES (2)

•• Improve our classification of Improve our classification of in vivo in vivo molecular MRS imaging of molecular MRS imaging of tumours and understanding of tumour biology by using tumours and understanding of tumour biology by using ex vivoex vivometabolomic and transcriptomic datametabolomic and transcriptomic data•• Develop automated processing, analysis and display for Develop automated processing, analysis and display for molecular imaging by MRSmolecular imaging by MRS•• Use Agent Technology to securely integrate multiUse Agent Technology to securely integrate multi--site data for site data for access by the DSS, for pattern recognition (PR)access by the DSS, for pattern recognition (PR)•• Analysis on distributed data, for data sharing and for DSS Analysis on distributed data, for data sharing and for DSS updatingupdating•• Create a webCreate a web--based Decision Support System (DSS) with a based Decision Support System (DSS) with a distributed database that incorporates clinical, metabolomic, distributed database that incorporates clinical, metabolomic, transcriptomic data and the MRS processing and classification transcriptomic data and the MRS processing and classification prototypeprototype•• Prospectively evaluate the DSS in a clinical demonstration of Prospectively evaluate the DSS in a clinical demonstration of added value added value

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EU Integrated Project eTUMOURSCIENTIFIC OBJECTIVESSCIENTIFIC OBJECTIVES Users of the outcomes (apart Users of the outcomes (apart

from partners)from partners)

Clinical demonstration of the added Clinical demonstration of the added value of combined MRI/MRS use in value of combined MRI/MRS use in the DSS for diagnostic accuracy the DSS for diagnostic accuracy support over conventional radiology.support over conventional radiology.

Clinicians. Government Agencies. Clinicians. Government Agencies. MR companies.MR companies.

Introduction of DNA microarray Introduction of DNA microarray analysis of tumour biopsies as an analysis of tumour biopsies as an adjuvant in tumour classification.adjuvant in tumour classification.

Pathology services at major Pathology services at major hospitals. Pharmaceutical hospitals. Pharmaceutical companies.companies.

High field MRS of biopsy tissue to High field MRS of biopsy tissue to improve underimprove under--standing of tumour standing of tumour biology, classification and grading, biology, classification and grading, and to aid diagnosis and prognosis and to aid diagnosis and prognosis using new high field (using new high field (≥≥3T) whole 3T) whole body MR systems.body MR systems.

Cancer researchers. Cancer researchers. Pharmaceutical companies. HighPharmaceutical companies. High--field ex vivo MRS researchers and field ex vivo MRS researchers and users of new highusers of new high--field in vivo MR field in vivo MR systems. Developers of DSS systems. Developers of DSS upgradesupgrades

Publications and PhDPublications and PhD’’ss Scientific and industrial MR Scientific and industrial MR communitycommunity

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EU Integrated Project eTUMOURTECHNOLOGICAL OBJECTIVESTECHNOLOGICAL OBJECTIVES Users of the outcomes (apart from Users of the outcomes (apart from

partners)partners)Development of a secure distributed Development of a secure distributed database using Agent Technology with web database using Agent Technology with web server DSS accessserver DSS access

Clinical centres worldwide (Clinical centres worldwide (≈≈ 5600) with 5600) with 1.5 T (and 3T) MRI/MRS scanners1.5 T (and 3T) MRI/MRS scanners

The development of the GUI as a learning The development of the GUI as a learning tool for proper MRS use by radiologiststool for proper MRS use by radiologists

Teaching institutions. Radiology Teaching institutions. Radiology departments. Datadepartments. Data--mining groupsmining groups

Automated processing & analysis software Automated processing & analysis software for incorporation of molecular imaging by for incorporation of molecular imaging by MRS into the DSS in real time.MRS into the DSS in real time.

Future users of the DSSFuture users of the DSS

GUI guided advice on optimal MRI and MRS GUI guided advice on optimal MRI and MRS acquisition protocols for differential acquisition protocols for differential diagnosis.diagnosis.

Clinical MR centres. Companies making Clinical MR centres. Companies making MR scanners.MR scanners.

Contribution to the development of a DICOM Contribution to the development of a DICOM MRS standard.MRS standard.

Companies developing MR scanners and Companies developing MR scanners and postprocessingpostprocessing software for MRI/MRS.software for MRI/MRS.

Consensus protocols for acquisition of all Consensus protocols for acquisition of all MRS/MRI data compatible with DSS use.MRS/MRI data compatible with DSS use.

Future DSS users. Researchers into MR Future DSS users. Researchers into MR diagnosis of other abnormal brain masses diagnosis of other abnormal brain masses and and neuroneuro--degenerative diseases.degenerative diseases.

MR system and patient data quality control MR system and patient data quality control protocols for data acceptance into the DSS.protocols for data acceptance into the DSS.

MR clinical centres. Future DSS users. MR clinical centres. Future DSS users. MR Industry.MR Industry.

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EU Integrated Project eTUMOURList of ParticipantsList of Participants

COCO 11 Prof. Dr.Bernardo Celda, Prof. Dr.Bernardo Celda, Universitat de Valencia Universitat de Valencia –– EstudiEstudiGeneralGeneral

UVEGUVEG SpainSpain

CRCR 22 Prof Carles ArProf Carles Arúúss, Universitat , Universitat AutAutòònomanoma de Barcelonade Barcelona

UABUAB SpainSpain

CRCR 33 DrDr FranklynFranklyn ArronArron Howe, St Howe, St GeorgeGeorge’’s Hospital Medical Schools Hospital Medical School

SGHMSSGHMS United United KingdomKingdom

CRCR 44 Prof Prof Arend HeerschapArend Heerschap, University , University Medical Centre Medical Centre NijmegenNijmegen

UMCNUMCN The The NetherlandsNetherlands

CRCR 55 Prof Prof Lutgarde BuydensLutgarde Buydens, , Stichting Stichting Katholieke UniversiteitKatholieke Universiteit

KUNKUN The The NetherlandsNetherlands

CRCR 66 Dr Anne Ziegler, INSERM U594Dr Anne Ziegler, INSERM U594 U594U594 FranceFrance

CRCR 77 Mr Mr MagMagíí LluchLluch, MICROART, S.L., MICROART, S.L. MICROARTMICROART SpainSpain

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CRCR 88 Dr Antoni CapdevilaDr Antoni Capdevila, , Hospital San Joan de Hospital San Joan de DeuDeu

HSJDHSJD SpainSpain

CRCR 99 Dr Fernando Dr Fernando GeijoGeijo, , PharmaPharma Quality Europe, Quality Europe, s.r.l.s.r.l.

PQEPQE ItalyItaly

CRCR 1010 Dr Luigi Dr Luigi VisaniVisani, , HyperpharHyperphar Group Group SpASpA

HGHG ItalyItaly

CRCR 1111 Prof. Sabine van Prof. Sabine van HuffelHuffel, , Katholieke Universiteit Katholieke Universiteit LeuvenLeuven Research & Research & DevelopmentDevelopment

KULKUL BelgiumBelgium

CRCR 1212 Dr Dr RuudRuud de Boer, Philips de Boer, Philips Medical Systems Medical Systems Nederland B.VNederland B.V

PhilipsPhilips The The NetherlanNetherlandsds

CRCR 1313 Dr Peter Dr Peter KreislerKreisler,,SiemensSiemens AG, Medical AG, Medical SolutionsSolutions

SiemensSiemens GermanyGermany

CRCR 1414 Dr Dr Arno KlaassenArno Klaassen, , SCITO, S.A.SCITO, S.A.

SCITOSCITO FranceFrance

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CRCR 1515 Dra. Montserrat Robles, Dra. Montserrat Robles, Universidad PolitUniversidad Politéécnica cnica de Valenciade Valencia

UPVLCUPVLC SpainSpain

CRCR 1616 Prof Prof Semmler WolfhardSemmler Wolfhard, , Deutsche Deutsche KrebsforschunKrebsforschun--gszentrumgszentrum HeidelbergHeidelberg

DKFZDKFZ GermanyGermany

CRCR 1717 Dr Christian Brevard, Dr Christian Brevard, BRUKER BIOSPIN SABRUKER BIOSPIN SA

BrukerBruker FranceFrance

CRCR 1818 Dr Richard Grundy, Dr Richard Grundy, Institute of Child Institute of Child Health, University of Health, University of BirminghamBirmingham

BUBU UnitedUnitedKingdomKingdom

CRCR 1919 Dr FranDr Franççois Berger, ois Berger, INSERM U318INSERM U318

U318U318 FranceFrance

CRCR 2020 DrDr Jorge Calvar, FLENIJorge Calvar, FLENI FLENIFLENI ArgentinaArgentina

CRCR 2121 Dr Dr Witold GajewiczWitold Gajewicz, , Medical University Medical University LodzLodz

MULMUL PolandPoland

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EU Integrated Project eTUMOURWorkpackage DescriptionWorkpackage Description

Dr. Dr. Arno KlaassenArno KlaassenIndustrialization and Industrialization and CE CE MarketingMarketing

WP8WP8

MrMr. . Magí LluchMagí LluchDiffusion and Diffusion and ImplementationImplementation

WP7WP7

Dr. Dr. GildaGilda D’IncertiD’IncertiQuality AssessmentQuality AssessmentWP6WP6

Dr. Dr. Luigi VisaniLuigi VisaniClinical Demonstration Clinical Demonstration Added ValueAdded Value

WP5WP5

Dr. Dr. Anne ZieglerAnne ZieglerDSS DSS DevelopmentDevelopmentWP4WP4

Dr. Montserrat RoblesDr. Montserrat RoblesPattern RecognitionPattern RecognitionWP3WP3

Prof.Prof. Carles ArúsCarles ArúsDataDataWP2WP2

Prof. Bernardo CeldaProf. Bernardo CeldaManagementManagementWP1WP1LeaderLeaderDescriptionDescriptionWorkpackageWorkpackage

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SECURE WEB-BASED DISTRIBUTED DATABASE

DECISION SUPPORT TOOL

RVGP-2004INTERPRETINTERPRET

Astrocitoma Astrocitoma grado 3grado 3

Glioblastoma Glioblastoma ??

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HR-MASeTUMOUR

ωω2211HH

ωω11

1313CC

11HH--1313C HSQCC HSQC

NAANAA

ChoCho

CrCr

mImI LipLip++LacLac

EU Integrated Project eTUMOUR celda.pdfPCA HR-MAS PCA HR-MAS. 129. METABOLÓMICA. T=0 C (4 C interior) 4500 Hz. Aprox. 20 mgde tejido. Ro tor cilíndrico (50 µl) (PCA aprox. 2g) D.

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