lactateglx

tCr

tChomI

01234 ppm

lipids

INTERPRETInternationalNetwork for

Pattern Recognition

of Tumours

using Resonance

lactateglx

tCr

tChomI

01234 ppm

lipids

“NOSOLOGIC” IMAGES FROM CSI

FORESEEN RESULTS/PRODUCTS

1. Database of spectra, images, clinical data and CDVC-validated anatomy pathologies.

2. Combination of database structure, automated processing tools and GUI developped to store and display the MRS/MRI and clinical data.

3. The decission support tool. Incorporates 1, 2 and the classifiers developped by INTERPRET.

WP1

Project management

ProjectCo-cordinator

EU ComissionProject Officer

ProjectManagementCommittee

Clinical DataValidation

Committee

AdvisoryGroup

ProjectAdministrator

ScientificManager

QualityEvaluators(QAU-UAB)

ExternalEvaluators

WP7 - D&I

WP1 - PM

WP6 - A&E

WP4 - GUI

WP2 - DB

WP3 - PR

WP5 - IPCEWP8 - CP

Figure 3. Managing chart of the INTERPRET Consortium. Blue nodes identifyresearch related items. Light orange is used to indicate administrative items.

ProjectAdministrator

Partner 2SGHMS

Project Planning and Timetable

TASKS SCHEDULINGYear 1 Year 2 Year 3

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

T1.1T1.2 (reports after every PMC meeting (minimum 2 per year)

T2.1

T2.2

T2.3

T2.4

T2.5

T2.6

T2.7

T2.8

T2.9

T2.10

T2.11

T2.12

T2.13

T3.1

T3.2

T3.3

T3.4

T4.1

T4.2

T4.3

T4.4

T5.1

T5.2

T5.3

T6.1

T6.2

T6.3

T6.4

T6.5

T6.5

T6.7

T7.1

T7.2

T7.3

T7.4

T8.1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

Year 1 Year 2 Year 3

Completed In progress

MANAGING TASKS FOR INTERPRET.

Internal/Regular reports

Communication with EU

Cost statements

Consortium Agreement

Meetings (plenary, PMC, CDVC, technical)

Communication within Consortium (e-mail lists, web pages, newsletter)

Deliverables

REPORTS

•12-month report: SENT

•15-month report: SENT

•18-month report: SENT

•21-month report: being finalised

•Next report: 24-month report

MANAGING TASKS FOR INTERPRET.

Internal/Regular reports

Communication with EU

Cost statements

Consortium Agreement

Meetings (plenary, PMC, CDVC, technical)

Communication within Consortium (e-mail lists, web pages, newsletter)

Deliverables

Attendance to Annual Technical Reviews

Attendance to clustering meetings:Clustering Telemedicine meeting on February 18th, 20001st Health Concertation Meeting for the 5th Frame Work programme (HCM 5th FP-01), Brussels, November, 20th, 2000Next one scheduled: 2nd cluster concertation meeting (Systems and Services for the Citizen, Applications relating to Health), Brussels, November 23rd, 2001

Contract amendments: contract amendment for certification related issues submitted in June, 26th, 2001

COMMUNICATION WITH EUCOMMUNICATION WITH EU

MANAGING TASKS FOR INTERPRET.

Internal/Regular reports

Communication with EU

Cost statements

Consortium Agreement

Meetings (plenary, PMC, CDVC, technical)

Communication within Consortium (e-mail lists, web pages, newsletter)

Deliverables

COST STATEMENTSCOST STATEMENTS

• 2nd Cost Statements: sent in August, 2001; corrections sent in September, 2001

• Next Cost Statements: June, 2002

MANAGING TASKS FOR INTERPRET.

Internal/Regular reports

Communication with EU

Cost statements

Consortium Agreement

Meetings (plenary, PMC, CDVC, technical)

Communication within Consortium (e-mail lists, web pages, newsletter)

Deliverables

•The Consortium Agreement was agreed in March, 2001 and signed by all the INTERPRET partners•Based in the Unified Consortium Agreement for FP5 projects, vers:1.0 991010

CONSORTIUM AGREEMENTCONSORTIUM AGREEMENT

MANAGING TASKS FOR INTERPRET.

Internal/Regular reports

Communication with EU

Cost statements

Consortium Agreement

Meetings (plenary, PMC, CDVC, technical)

Communication within Consortium (e-mail lists, web pages, newsletter)

Deliverables

MEETINGS• 3rd PMC meeting, teleconference, 19th December, 2000

• 4th PMC meeting, Grenoble, 1st February, 2001

• 5th PMC meeting, teleconference, 20th February, 2001

• 6th PMC meeting, teleconference, 14th March, 2001

• 7th PMC meeting, Barcelona, 6th June, 2001

• 8th PMC meeting, teleconference, 17th September, 2001

• 3rd CDVC meeting, Grenoble, 1st February, 2001

• 4th CDVC meeting, Barcelona, 5th June, 2001• Technical meeting: WP 3 (Pattern Recognition) and WP 5 (Integration of

prototypes and clinical evaluation), Grenoble, 1st-2nd February, 2001

• Technical meeting: Scientific Workshop and Pattern Recognition meeting, Barcelona, 6th-7th June, 2001

• Certification meeting between INTERPRET Consortium and Pharma Quality Europe (PQE), Barcelona, 5th June, 2001

MANAGING TASKS FOR INTERPRET.

Internal/Regular reports

Communication with EU

Cost statements

Consortium Agreement

Meetings (plenary, PMC, CDVC, technical)

Communication within Consortium (e-mail lists, web pages, newsletter)

Deliverables

COMMUNICATION WITHIN CONSORTIUM

•Continuation of pre-existing e-mail lists: •interpret (general e-mail list)•interpret pm (WP 1: Project management)•interpret db (WP 2: Database development)•interpret pr (WP 3: Pattern Recognition)•interpret gui (WP4: GUI development)•interpret ae (WP 6: Assessment and evaluation)•interpret di (WP 7: Dissemination and Implementation)•interpret cp (WP 8: Certification of procedures)•interpret pmc (Project Management Committee)•interpret cdvc (Clinical Data Validation Committee)•interpret uos (Partner 8 e-mail list)•interpret user (list of people interested in helping develop the users interface)

•19 bi-weekly Newsletters edited and circulated to all members of INTERPRET.•Project websites:

http://carbon.uab.es/INTERPREThttp://cogs.susx.ac.uk/users/desw/interpret-mailhttp://www.cogs.susx.ac.uk/users/joshuau/requirements_docs

DOCUMENTS AT THE PRIVATE SITE OF THE INTERPRET WEB PAGE (http:carbon.uab.es/INTERPRET)

10 TEMPLATES

38 MEETING, PROJECT AND MANAGING REPORTS AND DOCUMENTS

36 TECHNICAL REPORTS

9 DELIVERABLES

DOCUMENTS AT THE PRIVATE SITE OF THE INTERPRET WEB PAGE (http:carbon.uab.es/INTERPRET)

10 TEMPLATES

38 MEETING, PROJECT AND MANAGING REPORTS AND DOCUMENTS

36 TECHNICAL REPORTS

9 DELIVERABLES

DOCUMENTS AT THE PRIVATE SITE OF THE INTERPRET WEB PAGE (http:carbon.uab.es/INTERPRET)

10 TEMPLATES

38 MEETING, PROJECT AND MANAGING REPORTS AND DOCUMENTS

36 TECHNICAL REPORTS

9 DELIVERABLES

DOCUMENTS AT THE PRIVATE SITE OF THE INTERPRET WEB PAGE (http:carbon.uab.es/INTERPRET)

10 TEMPLATES

38 MEETING, PROJECT AND MANAGING REPORTS AND DOCUMENTS

36 TECHNICAL REPORTS

9 DELIVERABLES

DOCUMENTS AT THE PRIVATE SITE OF THE INTERPRET WEB PAGE (http:carbon.uab.es/INTERPRET)

10 TEMPLATES

38 MEETING, PROJECT AND MANAGING REPORTS AND DOCUMENTS

36 TECHNICAL REPORTS

9 DELIVERABLES

MANAGING TASKS FOR INTERPRET.

Internal/Regular reports

Communication with EU

Cost statements

Consortium Agreement

Meetings (plenary, PMC, CDVC, technical)

Communication within Consortium (e-mail lists, web pages, newsletter)

Deliverables

DELIVERABLESDELIVERABLES

Deliverable Code & Name Planneddelivery

date

Actualdelivery

date

Comments

D01 - Data manipulationsoftware

Month 3

Month 15

Month 9

Month 15 Revised deliverable as requested by the 1st Annual Technical Review panel

D03 - Dissemination and useplan

Month 6

Month 15

Month 7

Month 16 Revised deliverable as requested by the 1st Annual Technical Review panel

D04 - Data protocols (MRS) Month 6

Month 15

Month 6

Month 15 Revised deliverable as requested by the 1st Annual Technical Review panel

D05 - Data protocols (clinical) Month 6

Month 15

Month 11

Month 15 Revised deliverable as requested by the 1st Annual Technical Review panel

D12 - TIP Month 36 Month 16 A draft of this deliverable was requested by the panel at the Annual TechnicalReview

D06 - GUI user requirementsand specifications

Month 8 Month 9 None

D07 - PR strategy Month 12 Month 13 None

D08 - DBMS and associateddocumentation

Month 18 Month 20 None

WP2

DB Development

Project Planning and Timetable

TASKS SCHEDULINGYear 1 Year 2 Year 3

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

T1.1T1.2 (reports after every PMC meeting (minimum 2 per year)

T2.1

T2.2

T2.3

T2.4

T2.5

T2.6

T2.7

T2.8

T2.9

T2.10

T2.11

T2.12

T2.13

T3.1

T3.2

T3.3

T3.4

T4.1

T4.2

T4.3

T4.4

T5.1

T5.2

T5.3

T6.1

T6.2

T6.3

T6.4

T6.5

T6.5

T6.7

T7.1

T7.2

T7.3

T7.4

T8.1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

Year 1 Year 2 Year 3

Completed In progress

34

33

2915

1

61

4

Meningiomas high gradeEmbryonalOther tumoursMeningiomas low gradeMetastatic tumoursGlial low gradeGlial high grade

TASK 2.13 Standardisation of histopathological diagnosis

Status of the validation process. 177 patients with fully validated clinical data.

Task 2.8. Data releases to INTERPRET partners during present year.

0 100 200 300 400 500 600 700 800

Number of cases

30th March

27th April

25th May

2nd July

10th August

1st October

Date of release

Patients

Spectra

DICOM images

jpg images

Semiautomated Semiautomated quality control quality control of spectraof spectra

1- PRELIMINARY DATABASE

Task 2.8. Description of final contents of the ipDB. Numbers and sources of patients. Total: 388 patients.

8

49

106

225

CDP RETROSPECTIVE

IDI RETROSPECTIVE

IDI "INTERPRET" consensus protocol

FLENI "INTERPRET" consensus protocol

Task 2.8. Description of final contents of the ipDB. Patients broken by pathologies.

75

44

10

72

1019

105

54

Abscesses EmbryonalGlial high grade Glial low gradeMeningiomas low grade Metastatic tumoursLymphomas Other tumours

ipDB INTERPRET DB

IDI

155

CDP

225

FLENI

8

SGHMS UJF FMW/AZN LODZ

VALIDATION

VALIDATION

83 11

Flow chart of patient incorporation into iDB

Project Planning and Timetable

TASKS SCHEDULINGYear 1 Year 2 Year 3

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

T1.1T1.2 (reports after every PMC meeting (minimum 2 per year)

T2.1

T2.2

T2.3

T2.4

T2.5

T2.6

T2.7

T2.8

T2.9

T2.10

T2.11

T2.12

T2.13

T3.1

T3.2

T3.3

T3.4

T4.1

T4.2

T4.3

T4.4

T5.1

T5.2

T5.3

T6.1

T6.2

T6.3

T6.4

T6.5

T6.5

T6.7

T7.1

T7.2

T7.3

T7.4

T8.1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

Year 1 Year 2 Year 3

Completed In progress

Task 2.10. Application of quality control procedures to all incoming new patient data.

ipDB

BH> 8Hz

yes no

yes/no

SNR < 5

yes no

yes/no

LPS1 LW > 34 Hz

yes

no

Discarded Good

BH: Bad homogeneitySNR: Low signal-to-noise ratioLPS1: Lipid peak due to

subcutaneous fat in voxelnear skull (Linewidth)

LPS2: Lipid peak due tosubcutaneous fat in voxelnear skull. Ratio= Lipidpeak (0.7-1.4 ppm)/Largest intensity (0-3.4ppm)

Ascii files+phasing(0 and 1st order)+offset+ normalisation to unit length

LPS2 Ratio > 0.64

no

yes

ipDB: Semiautomated quality control approach for incoming spectraipDB: Semiautomated quality control approach for incoming spectra

Semiautomated quality control approach 1

Semiautomated quality control approach 2

Semiautomated quality control approach 3

Task 2.10 Quality Control

INTERPRET PHANTOM CONTROLS

Preliminary conclusions System Quality Assurance(SQA) (these conclusions are based on the SQA ofMay 2001)

* All sites (CDPE, CDPP, IDI, SGHMS, UJF, UMCN)were able to perform the SQA measurementssuccessfully.* The shim of all spectra at all voxel positions wasgood (<4 Hz), as measured by the linewidth of thewater spectrum.* The SNR of all spectra at all voxel positions wasgood (>50), as measured by the maximum signal ofthe metabolite / the standard deviation of the noise (9-11 ppm).* No indications were found of bad volume selectionor signal contributions from outside the selected voxelby visual inspection by an expert spectroscopist.* No unacceptable spectral artifacts were observedduring visual inspection by an expert spectroscopist.

Glutamate

ppm

01234

-60000

-40000

-20000

0

20000

40000

60000

80000

Ac

2.15

2.022.323.76

Glutamine

ppm

01234

-60000

-40000

-20000

0

20000

40000

Ac

2.28

2.09

2.38

3.78

IDI-PRESS 136 ms, MENINGIOMA LOW-GRADE, n=27

ppm

01234

-0,04

-0,02

0,00

0,02

0,04

0,06

0,08

0,10

0,12

0,14

0,16

Alanine

Creatine

Choline

2.052.34

2.16

3.78

Phantom Studies

•Studies of the phase modulations of some compounds (eg. Glutamate, glutamine); try to relate these changes wiht some tumoral types.

Mean Spectra Glutamine + Glutamate

ppm

01234

-0,10

-0,08

-0,06

-0,04

-0,02

0,00

0,02

0,04

0,06

0,08

0,10

0,12

2.10

Ac

2.03

2.33

3.77 •Calculation of glutamate/glutamine mean spectra (long echo time)

•Try to coordinate the pattern recognition of some cerebral tumours with the phase modulation seen in presence of one, another or both compounds. Compare with real cases.

Project Planning and Timetable

TASKS SCHEDULINGYear 1 Year 2 Year 3

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

T1.1T1.2 (reports after every PMC meeting (minimum 2 per year)

T2.1

T2.2

T2.3

T2.4

T2.5

T2.6

T2.7

T2.8

T2.9

T2.10

T2.11

T2.12

T2.13

T3.1

T3.2

T3.3

T3.4

T4.1

T4.2

T4.3

T4.4

T5.1

T5.2

T5.3

T6.1

T6.2

T6.3

T6.4

T6.5

T6.5

T6.7

T7.1

T7.2

T7.3

T7.4

T8.1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

Year 1 Year 2 Year 3

Completed In progress

Clinical Data Input

• Access through the web, so accesible for providing centers and for validation.

• Information can be input progresively as it becomes avaliable.

2- DEFINITIVE DATABASE

Maintenance of MRS Resources

• Basic maintenance form that allows to add, edit or remove resources.

Maintenance of MRS Resources (detail 1)

• Basic set of acquisition parameters for describing the spectrum. They can be both automatically or manually entered.

Maintenance of MRS Resources (detail 2)

• Possibility of storing and retreiving other parameters recognized by the system or defined by the user for other purposes as quality control.

Maintenance of MRS Resources (detail 3)

• Possibility of storing and retreaving additional resources such as processed data.

Maintenance of MRS Resources (detail 4)

• Simple file upload through web interface for adding resources.

Data Retrieval (detail 1)

• Flexible record filter specification for selection according to clinical record attributes and later download of corresponding data.

Data Retrieval (detail 2)

• Given the cost of computing a dynamic collection, precomputed collections are available through a web form.

WP3

PATTERN

RECOGNITION

Project Planning and Timetable

TASKS SCHEDULINGYear 1 Year 2 Year 3

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

T1.1T1.2 (reports after every PMC meeting (minimum 2 per year)

T2.1

T2.2

T2.3

T2.4

T2.5

T2.6

T2.7

T2.8

T2.9

T2.10

T2.11

T2.12

T2.13

T3.1

T3.2

T3.3

T3.4

T4.1

T4.2

T4.3

T4.4

T5.1

T5.2

T5.3

T6.1

T6.2

T6.3

T6.4

T6.5

T6.5

T6.7

T7.1

T7.2

T7.3

T7.4

T8.1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

Year 1 Year 2 Year 3

Completed In progress

Task 3.2. Pattern Recognition (PR) strategy: Completed.

Partners 2, 5 and 7 have investigated the best strategies forpreprocessing, feature extraction and classification methods.Corresponding deliverable, No. 7 PR strategy, submitted.

Task 3.3. Prototype implementation. Completed.

The prototypes of the PR methods and the necessary data pre-treatment methods (such as water filtering, Eddy currentcorrection, etc.) are implemented.

Task 3.3. Prototype testing. In progress.

Test, adapt, and select the best methodology for eachprotocol/application. The different techniques, implemented intask 3.3 are tested, evaluated and adapted, and for eachprotocol/application the necessary techniques/strategies strategy

The algorithm consists of the following steps

• Pre processing of CSI and image data

• Selection of 7 spectral and 3 image features for each voxel

• Unsupervised clustering

• The found clusters can be plotted in the space of the original variables, facilitating the interpretation (Figure 1)

• Segmentation is visualized in Figure 2

Classification of short echo CSI data

University of Nijmegen, the Netherlands (P7)

Figure 1

Figure 2

• From each segment a mean spectrum is calculated (Figure 3).

• The mean spectrum from each segment is classified using a supervised classification algorithm.

Results:

• The pre processing and feature selection are ready.

• For unsupervised clustering mixture modelling is being implemented.

• Supervised classification of mean spectra is under investigation (LDA, neural networks; for limited set of tumour types).

Figure 3: mean spectra from the pink and purple segment

Tumour type XNormal

supervised classification

Training with IDI+CDP short echo; testing with SGHMS. Red: Glb, Green: LGA; Meningioma: purple.

Training with SGHMS short echo; testing with IDI+CDP. Red: Glb, Green: LGA; Meningioma: purple

Short echo time SGHMS+IDI spectra, normalized to water. Red: Glb, purple: metastasis. Var 320 & 197 are peak heights at defined spectral points.

WP4

GUI DEVELOPMENT

Project Planning and Timetable

TASKS SCHEDULINGYear 1 Year 2 Year 3

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

T1.1T1.2 (reports after every PMC meeting (minimum 2 per year)

T2.1

T2.2

T2.3

T2.4

T2.5

T2.6

T2.7

T2.8

T2.9

T2.10

T2.11

T2.12

T2.13

T3.1

T3.2

T3.3

T3.4

T4.1

T4.2

T4.3

T4.4

T5.1

T5.2

T5.3

T6.1

T6.2

T6.3

T6.4

T6.5

T6.5

T6.7

T7.1

T7.2

T7.3

T7.4

T8.1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

Year 1 Year 2 Year 3

Completed In progress

Task 4.2 User Requirements Analysis - Methodology• Literature survey (radiological) diagnostic support systems (design and

requirements)

• Observation of neuro-radiologists, radiographers at work in context

• Structured interviews (focussed on requirements) with radiologists, neurosurgeons, neurologists, (neuro) spectroscopists

• Questionnaires (for validation and prioritisation) of perceived user requirements.

• Focussed discussion groups (spectroscopists, clinicians, pattern recognition people and gui people).

• Feedback (e-mail and face-to-face) on (semi-functional) prototypes and web-based requirements specification (available at - http://www.cogs.susx.ac.uk/users/joshuau/interpret/sysdes.html)

See - Focussing User Studies: Requirements Capture for a Decision Support Tool, Joshua Underwood, et al - ICSE 2000 Workshop (WO5) Proceedings, 88-92, International Conference on Software Engineering.

Requirements Specification

Deliverable 4.1 specifies User Requirements in detail -(http://www.cogs.susx.ac.uk/users/joshuau/interpret/sysdes.html).

D4.1 consists of four sections:

• A one page system definition.

• A description of thirty functions the system should provide to end-users.

• A Use Case model which describes the actions users should be able to perform with the system (see left).

• A summary of the underpinning data used to produce the requirements. A full description user requirements would require many slides - see deliverable 4.1 for details.

DELIVERABLESDELIVERABLES

Deliverable Code & Name Planneddelivery

date

Actualdelivery

date

Comments

D01 - Data manipulationsoftware

Month 3

Month 15

Month 9

Month 15 Revised deliverable as requested by the 1st Annual Technical Review panel

D03 - Dissemination and useplan

Month 6

Month 15

Month 7

Month 16 Revised deliverable as requested by the 1st Annual Technical Review panel

D04 - Data protocols (MRS) Month 6

Month 15

Month 6

Month 15 Revised deliverable as requested by the 1st Annual Technical Review panel

D05 - Data protocols (clinical) Month 6

Month 15

Month 11

Month 15 Revised deliverable as requested by the 1st Annual Technical Review panel

D12 - TIP Month 36 Month 16 A draft of this deliverable was requested by the panel at the Annual TechnicalReview

D06 - GUI user requirementsand specifications

Month 8 Month 9 None

D07 - PR strategy Month 12 Month 13 None

D08 - DBMS and associateddocumentation

Month 18 Month 20 None

Prototype Single voxel System

Dark area on the left shows the database (red glioblastoma, white meningioma, blue low grade Ast)

Database

Prototype Single voxel System

The new case(yellow) is automatically processed and positioned in the database - it falls in the red (glioblastoma) group. Spectrum

and (DICOM) images for new case are at top right

New caseNew case spectrum and MRI

Prototype Single voxel System

The new spectrum can be compared with the typical (mean +/ SD) spectrum for glioblastoma (grey area top) and the typical

meningioma spectrum (grey area and black line bottom)

Typical meningioma

Typical meningioma

New case (black)

Typical glioblastoma

(grey)

Generate the nosologic image

WP6

ASSESSMENT AND EVALUATION

WP 6 - ASSESSMENT AND EVALUATION

• TASK 6.1 AUDIT PLANNING: COMPLETED• TASK 6.2 CHECKLISTS SENT TO EACH PARTNER• TASK 6.3 FIRST VISIT CARRIED OUT TO ALL CENTRES

EXCEPT TO SIEMENS• TASK 6.4 COLLECT AUDIT EVIDENCES: COMPLETED• TASK 6.5 QUALITY SYSTEM EVALUATION: IN PROGRESS.

INTERNAL REPORTS ABOUT THE INITIAL STATUS OF EACH CENTRE HAVE BEEN DELIVERED TO EACH PARTNER AND TO THE COORDINATOR

• TASK 6.6 SECOND SITE VISITS TO FOLLOW THE IMPLEMENTATION OF CORRECTING PROCEDURES ARE PLANNED FOR THE 2ndHALF OF THE PROJECT

WP7

DISSEMINATION

AND

IMPLEMENTATION

Dissemination / Promotional Information (1)

- Articles, communications, posters, invited conferences to meetings.

23 communications/posters/conferences related to INTERPRET. 5 publications or articles in press related to INTERPRET One local press release. One institution international bulletin release.

Handout: 1 Handout prepared for the European Congress of Radiology which took place in Vienna in March, 2nd-6th, 2001 and for MEDINFO

2001.Communications: 23

A Computer-Based System to Aid Radiologists in the Diagnosis of Brain Tumours. J. Underwood, S. J. Barton, R. Cox, J. R.Griffiths, C. Arus, A. R. Tate, The Future of Clinical Magnetic Resonance Spectroscopy, 2000, jan, British Institute of Radiology

A Decision Support Tool to help Radiologists Classify MR spectra of Brain Tumours using Automated Pattern Recognition and DataDisplay Techniques. Tate, AR, Underwood, J, Griffiths, JR, Howe, FA, Capdevila, A, & Arús, C. Communication to ISMRMworkshop on MR in Experimental and Clinical Cancer Research in the New Millennium, Norway, 10-13 August 2000.

A Decision Support Tool to Help Radiologists Use MRS, J. Underwood, R. Cox, J. R. Griffiths, C. Arus, C. Majos, A. Capdevila, A.R. Tate, Proceedings of the 17th Conference of the European Society for Magnetic Resonance in Medicine and Biology (ESMRMB),2000,Paris, sep

A Prototype Decision Support System for MR Spectroscopy-Assisted Diagnosis of Brain Tumours. J. Underwood, A. R. Tate, R.Luckin, C. Majos, A. Capdevila, F. Howe, J. Griffiths, C. Arus, Medinfo 2001 Conference, 2001,sep

Automatic classification of tumours using 1H MRSI data: assessment of several pattern recognition methods. F. Szabo, F. Estève, S.Grand, C. Rubin, C. Segebarth, M .Décorps, J.F. Lebas, C. Rémy. Brain tumour modelling workshop. International centre forMathematical Sciences, Edimbourgh, Ecosse, 27-28 June 2001.

Automatic elimination of an artefact introduced by Eddy current correction. A. Simonetti, W.J. Melssen, M. Van der Graaf,A.Heerschap and L.M.C. Buydens. .Proc Int. Soc. Mag. Reson. Med 9: 757, 2001. 21-27 April-2001, poster at ISMRM , Glasgow,Scotland,UK.

Classification of brain tumors using 1H MRSI at an echo time of 272 msec in combination with linear discrimination analysis.Strategies to improve the correct classification rate. F. Szabo, F. Estève, S. Grand, C. Rubin, C. Segebarth, M .Décorps, J.F. Lebas, C.Rémy. Proc Int. Soc. Mag. Reson., 1665, 2001.

Collection of proton MRS data of brain tumors for a European project focused on pattern recognition. Y.M. van der Meulen, M. vander Graaf, J. Schuuring and A. Heerschap. Proc SMRT & BAMRR joint meeting, presentation nr. 15, Glasgow, 20-22 April, 2001.Proc Int. Soc. Mag. Reson. Med 9: 1683, 2001.

Computer-Based MR Spectroscopy-Assisted Diagnosis of Brain Tumours. J. L. C. Underwood, R. Luckin, D. Watson, F. Howe, J. R.Griffiths, A. Capdevila, C. Majos, C. Arús, A. R. Tate, European Congress of Radiology,2001,march

Characterization of oligodendrogliomas using short echo time 2D 1H MRSI. by M. Rijpkema, J. Schuuring and A. Heerschap. ProcInt. Soc. Mag. Reson. Med 9: 2304, 2001.

Diagnosis of human brain tumours by 1-H MRS. Arús, C., Majós, C., Capdevila, A., Tate, A.R., Griffiths, J.R. XIXInternational Conference on magnetic resonance in biological systems, Florence, Italy, 20-25, August 2000

Differentiating Types of Human Brain Tumours by MRS. A Comparison of Pre-processing Methods and Echo Times.A. Rosemary Tate, John R. Griffiths, Franklyn A. Howe, Jesus Pujol, Carles Arús. Proc Int. Soc. Mag. Reson. Med 9:2284, 2001.

Espectroscopia por Resonancia Magnética de Protón en tumores gliales. Utilidad en el diagnóstico y gradacióntumoral. C. Majós, C. Aguilera, S. Coll, L. López, L.C. Pons. XXV Congreso Nacional de la Sociedad Española deRadiología Médica. Madrid 20th to 23rd May, 2000

Focussing User Studies: Requirements Capture for a Decision Support Tool.. Joshua Underwood, Rose Luckin,Richard Cox, Des Watson,Rosemary Tate, Proceedings of ICSE2000 Workshop 5, the 22nd International Conferenceon Software Engineering, 2000, J. Singer and M. Storey and S. Sim, 88--92, Limerick.

Les images nosologiques: une nouvelle méthode pour l'aide à la caractérisation des tumeurs cérébrales in vivo chezl'homme. Szabo de Edelenyi F., Rubin C., Estève F., Grand S., Rémy C., Décorps M., Le Bas J.-F. 9ème Congrès duGroupe de Recherche sur les Applications du Magnétisme en Médecine, Lille (France), 2-4 February 2000.

Linear Discriminant Analysis of Quantitative 1H MRS Data for Classification of Brain Tumors. Howe, FA, Barton, SJ,Tate, AR, Cudlip, SA, Bell, BA, & Griffiths, JR. Communication to ISMRM workshop on MR in Experimental andClinical Cancer Research in the New Millennium, Norway, 10-13 August 2000.

MRS in Routine Radiology of Brain masses. Clinical Categorical Course. Joint Annual Meeting ISMRM/ESMRMB.21-27 April 2001, Glasgow, Scotland, UK. Talk: Antoni Capdevila.

Nosologic images: a new approach for analyzing 1H magnetic resonance spectroscopic imaging of brain tumors. Szabode Edelenyi F., Rubin C., Estève F., Grand S., Décorps M., Le Bas J.-F, Rémy C.. ISMRM workshop: MR inexperimental and clinical cancer research in the new millenium, Geiranger (Norway), 10-13 August 2000.

Resultados preliminares en una serie de meningiomas intracraneales tratados con radioterapia estereotáxicafraccionada. S. Villá, D. Linero, C. Picón, S. Marín, C. Gutierrez, C. Majós, E. Ferrán, J.J. Acebes. VI Congreso de laSociedad Española de Neurocirugía. Avila 16th to 19th May, 2001

Segmentation of chemical shift images with mixture modeling. 14-17 october 2001, paper at MICCAI, Utrecht, thenetherlands.

Unsupervised Chemometric methods to automatically discriminate between 1H-MRSI spectra from patients with abrain tumor; A.W. Simonetti, W.J. Melssen, M. Rijpkema, A. Heerschap, L.M.C. Buydens. 1/7 April -2000, Poster atISMRM, Denver, Colorado,USA.

Unsupervised Chemometric methods to automatically discriminate between 1H-MRSI spectra from patients with abrain tumor; A.W. Simonetti, W.J. Melssen, M. Rijpkema, A. Heerschap, L.M.C. Buydens. 16/20 October-2000, Posterat CAC, Antwerp, Belgium.

Visualisation of Multidimensional Data for Medical Decision Support. A. Rosemary Tate, Joshua Underwood,Christophe Ladroue Rosemary Luckin, John R. Griffiths. Accepted as poster/short paper, 4 July 2001, Cascais,Portugal; AIME'01, Eighth European Conference on Artificial Intelligence in Medicine1.

Publications: 5

A new approach for analyzing proton magnetic resonance spectroscopic images of brain tumors: nosologic images. Szabo deEdelenyi F., Rubin C., Estève F., Grand S., Décorps M., Lefournier V., Le Bas J.-F, Rémy C. Nat. Med.: 6, 1287-1289, 2000

Automatic Correction for Phase Shifts, Frequency Shifts and Lineshape Distortions across a Series of Single Resonance Lines inLarge Spectral Data Sets. H. Witjes, W.J. Melssen, H.J.A. in 't Zandt, M. van der Graaf, A. Heerschap, L.M.C. Buydens. J. Magn.Reson. 144, 35-44 (2000)

Common processing of in vivo MR spectra. H.J.A. in ‘t Zandt, M. van der Graaf, A. Heerschap. NMR in Biomedicine 14, 224-232.2001.

Espectroscopia por Resonancia Magnética de Protón en tumores gliales. Utilidad en el diagnóstico y gradación tumoral.C. Majós, C.Aguilera, S. Coll, L. López, L.C. Pons. Radiología 2000; 42:97

Intraventricular Mass Lesions of the Brain. C. Majós, S.Coll, C. Aguilera, J.J. Acebes, L.C. PonsEuropean Radiology 2000; 10: 951-961

Dissemination / Promotional Information (2) Advisory Group / Potential users.

Inaugural meeting at the ISMRM 2000 in Denver (USA), April 4.

About 31 group members. Communication with them through webpage (www.cogs.susx.ac.uk/users/joshuau/interpret/index.html) andnews bulletin.

Statistics for website: around 1500 visits since July, 2000. The Department of Radiology,Medical University of Lodz (Poland)and Fundación Lucha Enfermedades Neurológicas en la Infancia(FLENI) group (Buenos Aires, Argentina) were accepted formally inthe 7th PMC meeting (Barcelona, June, 6th, 2001) as Class AAdvisory Group members. This means that the two institutions willcontribute data from patients abiding by the same QC rules andprotocols than INTERPRET partners and will have access during theduration of INTERPRET to the scientific prototypes of GUIdeveloped for participation in the testing and refining procedures. Twoother phantoms were distributed to them.

Up until now, the number of patients contributed by these 2 centers areas follows:

University of Lodz: 25 patients FLENI group: 8 patients

Ms. Margaret Hodge (Minister of Higher Education, UK) in her visit to SGHMS with Dr. Yuen-Li and Prof. John Griffiths, being shown the SV INTERPRET prototype.

Activity in relation to TIP• PRAXIM has established a relationship with SCITO

for marketing INTERPRET products• PRAXIM has decided to develop a first

INTERPRET product for 12/2002 with CE Marking.• PRAXIM suggested an open source approach. On

the 3rd year an Exploitation Plan will have to be signed and further details will be found there.

• PRAXIM/SCITO have proposed a draft of business plan

FORESEEN RESULTS/PRODUCTS

1. Database of spectra, images, clinical data and CDVC-validated anatomy pathologies.

2. Combination of database structure, automated processing tools and GUI developed to store and display the MRS/MRI and clinical data.

3. The decission support tool. Incorporates 1, 2 and the classifiers developed by INTERPRET.

MARKET OVERVIEW FOR THE DECISION SUPPORT TOOL

-12,000 clinical MRI scanners in the world.

-3,000 of them 1,5 Tesla MRI instruments.

-MRS is a reimbursable investigation in the USA.

-GE/Siemens/Philips major suppliers of 1.5 T machines.

-PRAXIM (P9) will be in charge of proposing a preliminary business model (regulatory constraints, competitiors analysis, commercial strategies).

MARKET OVERVIEW FOR THE GUI

-Workers and researchers in the field of MR spectroscopy.

-Data mining applications in Biomedicine and Biotechnology.

-Exploitation possibilities being investigated.

MARKET OVERVIEW FOR THE DATABASE

-Researchers and medical practicioners in the neuroradiology and neurooncology areas.

-Not commercially exploitable because of raw patient data content.

-Freely accessible for non-commercial purposes as european resource for medical R&D.

-Maintained and expandable through further funding (Advisory Group development) or “Decision support tool” originated revenue.

WP8

CERTIFICATION OF PROCEDURES

Project Planning and Timetable

TASKS SCHEDULINGYear 1 Year 2 Year 3

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

T1.1T1.2 (reports after every PMC meeting (minimum 2 per year)

T2.1

T2.2

T2.3

T2.4

T2.5

T2.6

T2.7

T2.8

T2.9

T2.10

T2.11

T2.12

T2.13

T3.1

T3.2

T3.3

T3.4

T4.1

T4.2

T4.3

T4.4

T5.1

T5.2

T5.3

T6.1

T6.2

T6.3

T6.4

T6.5

T6.5

T6.7

T7.1

T7.2

T7.3

T7.4

T8.1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

Year 1 Year 2 Year 3

Completed In progress

Implementation of a minimal quality system

This Quality System should be focused in generating the documentation necessary to support the INTERPRET“scientific prototype, in view of a future transformation into an “industrial prototype” and in assuring system reliability.The main areas of activity identified are:

1. Data Quality Control

2. Quality System for Software Development

1- DATA QUALITY CONTROL

If the contract amendment is accepted, assistancefrom a company specialized in QualityManagement, Pharma Quality Europe (PQE) willbe used to ensure that data collected in theINTERPRET DataBase will be useable in such aform that it will constitute an Accessory of theINTERPRET Software (Medical Device, EC 93/42Directive).

A first meeting between PQE and INTERPRETpartners took place in Barcelona in June, 5th, 2001.

A second meeting between PQE and PRAXIM(partner 9) is scheduled for October, 22nd, 2001 inBarcelona.

Description of the Database Quality Assurance and Quality Control:

Implementation through the multi-centre network involved in thedevelopment of the INTERPRET product, of a minimal quality systemfor the software prototype development activities.

The Quality System will be focused in generating the documentationnecessary to support the INTERPRET"scientific prototype", in view of afuture transformation into an “industrial prototype” and in assuringsystem reliability.

The main areas of activity identified will be: The quality of the clinical data imported in the database has to be

assessed and well documented. A review of the quality system of the 5 clinical centres involved in data

generation has to be performed and described in a specific report.Corrective actions will be eventually proposed and implemented.

2- SOFTWARE DEVELOPMENT

One of the industrial partners (PRAXIM) willdevelop a first version of a software product withthe objective to reach CE Certification of this firstProduct before the end of the EC Project

Sub-contract Assistance and Audit of CECertification to a notified body (APAVE/CPMInstitute of Research, Tests and Analysis).