All you need is a web browser.

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Overview

Overview

appMRI Hippocampus Volume Analyser:

  1. is a user-friendly, secure, web-based application for fully automated measurement of hippocampal volumes
  2. produces reliable, objective and quantitative results free of investigator-bias
  3. was calibrated to manual segmentations performed by leading experts using the Harmonized Protocol for Manual Hippocampal Segmentation (Harmonized Protocol) (Frisoni et al., 2014)
  4. is a simple yet very powerful medical device (pending certification), capable of processing T1-weighted Magnetic Resonance Images (MRI) of the human brain
  5. provides the physician with critical information on brain atrophy for diagnosing Alzheimer's disease

The device is intended to be used by trained professionals. We offer appMRI Hippocampus Volume Analyser with a pay-per-scan pricing model. No annual fee is charged. Larger volumes are handled separately. Thus, you only pay per processed image. We offer special prices for research institutions. Please have a look at our Beneficiary Industries site.

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Mission

Application

appMRI Hippocampus Volume Analyser is a user-friendly computer system used to determine the hippocampal volumes from MRI of the human brain. You only need a web browser to use it. No cumbersome software installation is needed.
After only four steps your first report is ready and available for download:

  1. Go to our service website hipp.appmri.com
  2. Register and create your personal account
  3. Upload a zipped T1­-weighted 3D MR Image of the brain 
  4. Download your report within 12 to 24 hours

Successful upload of the image is confirmed by email. The uploaded image is exposed to a validated image processing pipeline. This pipeline creates numerical output values of the left and right hippocampus together with verification images. In addition, the report contains normative values generated on MRI head scans of an age matched, healthy European control group of people using appMRI Hippocampus Volume Analyser. The scans were kindly provided by AddNeuroMed, a European collaboration for the discovery of novel biomarkers for Alzheimer’s disease (Lovestone S et al. Ann NY Acad Sci. 2009. 1180:36-46; Lovestone S, Francis P, Strandgaard K. J Nutr Health Aging. 2007. 11(4):359-61.). For securely downloading the PDF report via encrypted channels, the referring clinician will receive an email containing a secure hyperlink. A personal account is part of the service website. The reports are available there too. A sample report is ready for download here.

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Image Analaysis

 

Image Analysis 

appMRI Hippocampus Volume Analyser performs volumetric segmentation using the FreeSurfer image analysis suite, which is documented and freely available for download at surfer.nmr.mgh.harvard.edu/

The processing steps include motion correction (Reuter et al. 2010), removal of non-brain tissue using a hybrid watershed/surface deformation procedure (Segonne et al., 2004), automated Talairach transformation, segmentation of the subcortical white matter and deep grey matter volumetric structure(s) (Fischl et al., 2002; Fischl et al., 2004) and intensity normalisation (Sled et al., 1998). FreeSurfer morphometric procedures have been demonstrated to show good test-retest reliability across scanner manufacturers and across field strengths (Han et al., 2006; Reuter et al., 2012). A reference list about FreeSurfer you find here.

 

 

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QualityControll

Quality Control

Input parameter verification is performed automatically by the software before the processing pipeline is initiated. Failure to meet input parameter requirements will result in an informational email sent to the customer in the case that the image is not processed. In cases where input failure does not influence data processing ability, the image will be processed and failure is stated on the report as a warning.

Before a report is created, each processing job is subject to manual quality control by a McMRI AG expert who verifies that the processing is complete and correct. If the images pass our manual quality control, this is indicated on the report. If the scan fails to pass manual quality control, the report does not contain numerical results but a quality control failure assessment.

Applying this quality control process, we aim to guarantee that our automated volume measurements are of the highest quality. Experience shows that < 5% of processed images do not fulfil our strict quality criteria. To achieve the highest quality, please consult our technical instructions available on the service website.

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Volume assessment

appMRI Hippocampus Volume Analyser is calibrated and validated by international leading experts. For manual segmentations these tracers followed the International EADC-ADNI Harmonized Protocol for manual hippocampal segmentation on magnetic resonance (Harmonized Protocol). The Harmonized Protocol was created in order to unify the anatomical boundaries of the hippocampus for segmentation so that hippocampal volume studies become comparable between laboratories across the world.

This protocol was established as a joint project between the European Alzheimer’s Disease Consortium (EADC) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). A reference list with literature about the project you find here.

appMRI Hippocampus Volume Analyser results show a linear correlation with the Harmonized Protocol images provided by the EADC­-ADNI working Group (Bochetta et al. 2014; Frisoni et al. 2014, Boccardi et al. 2014, Boccardi et al. 2013; Boccardi et al. 2011; Frisoni and Jack 2011) whereby r>0.86, p<0.0001 (3e­8), slope = 1.04­1.09.

Img volumeAssesment

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DataManagement

Data Management

McMRI keeps track of its registered users. Each uploaded MRI sequence, processing job, intermediate and final image or numerical result and report is associated with the user who is the owner of the native MRI scan. All data is protected from unauthorised access.

Data is also protected from accidental destruction. MRI Images are stored by the appMRI Hippocampus Volume Analyser server in Switzerland for a pre­defined but limited time. After the time expires, the images are destroyed together with the results.

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Strengths

Automatic

automatic

appMRI Hippocampus Volume Analyser measures volumes by using a fully automated pipeline. Physicians do not need to calculate the volumes themselves, adjust parameters or interact with the pipeline other than to upload the files.

 

Objective

objective

appMRI Hippocampus Volume Analyser produces objective results. The result is free of investigator-bias.

 

Quantifyable

quantifiable

appMRI Hippocampus Volume Analyser produces quantitative numerical results. This allows a comparison between and follow-up of subjects.

 

Repeatable

repeatable

appMRI Hippocampus Volume Analyser produces identical results when processing the same image repeatedly. In comparison, manual tracing has inherent intrarater variability that negatively influences precision.

 

Simple

simple

appMRI Hippocampus Volume Analyser is a user-friendly, web-based application. All you need to use this service is a web browser.

 

Accurate

accurate

appMRI Hippocampus Volume Analyser produces accurate results. The results are highly correlated with the International EADC-ADNI Harmonized Protocol for manual hippocampal segmentation on magnetic resonance (Harmonized Protocol) dataset and manual tracings performed using the Harmonized Protocol. A sophisticated validation process delivered convincing results.

 

Trustworthy

trustworthy

appMRI Hippocampus Volume Analyser is a trustworthy service. The supplier, McMRI AG, follows Good Business Practice and Good Academic Practice. The company’s management processes are certified according to ISO 9001:2008 and audited at regular intervals by internal and external auditors. Software development takes place according to EN ISO 13485:2012 guidelines.

 

Certification

certified

appMRI Hippocampus Volume Analyser is a certified medical device according to the European Medical Device Directive MEDDEV 2.1/6, MEDDEV 2.7.1, MEDDEV 2.12-1, and Medical Product Guidelines 93/42/EWG with amendments RL 2007/47/EG. This enables our customers to use appMRI Hippocampus Volume Analyser in a clinical setting. In addition, McMRI AG has recieved certification for the Canadian health market in May 2015. 

 

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Offer

Offer

Our service is completely web-based. All you need is a web browser. No cumbersome installation is needed.
Equally simple is the purchasing process. Go to our service website hipp.appmri.comand register. After acceptance of the service agreement and confirmation of registration, you will get temporary, limited, free access to the service.

The first 10 MRI uploads are free of charge! This will allow you to test our service and discover the great value of appMRI Hippocampus Volume Analyser. The 10 free test scans may only be used for information and testing, however, not for commercial purposes. 

We will contact you during the test phase and issue a commercial service agreement if you are interested. The pricing mode for the clinical and commercial use of appMRI Hippocampus Volume Analyser is pay-per-scan. Thus, you only pay if you decide to use our tool for clinical and commercial use. There are no annual fees. Larger volumes of MRI scans will be handled separately. The commercial service agreement gives you access to the service website for 12 months. After that, renewal of the contract is necessary. We offer email support for commercial customers for the duration of the contract. If you have any questions, do not hesitate to contact Fabian Schönenberger, CEO. Fabian can be reached via e-mail at This email address is being protected from spambots. You need JavaScript enabled to view it. or by phone at +41 71 913 05 80.

We offer special prices for early users. Please contact us if you are interested. We are also interested in providing our service for research purposes. So please contact Fabian Schönenberger, our CEO, if you can use our service in your research project. Of course, price negotiations are possible. You can reach Fabian via e-mail at This email address is being protected from spambots. You need JavaScript enabled to view it.

 

 

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REFERENCES

FreeSurfer

Fischl, B., Salat, D.H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S., Montillo, A., Makris, N., Rosen, B., Dale, A.M., 2002. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 33, 341-355.

Fischl, B., Salat, D.H., van der Kouwe, A.J., Makris, N., Segonne, F., Quinn, B.T., Dale, A.M., 2004. Sequence-independent segmentation of magnetic resonance images. Neuroimage 23 Suppl 1, S69-84.

Han, X., Jovicich, J., Salat, D., van der Kouwe, A., Quinn, B., Czanner, S., Busa, E., Pacheco, J., Albert, M., Killiany, R., Maguire, P., Rosas, D., Makris, N., Dale, A., Dickerson, B., Fischl, B., 2006. Reliability of MRI-derived measurements of human cerebral cortical thickness: the effects of field strength, scanner upgrade and manufacturer. Neuroimage 32, 180-194.

Reuter, M., Rosas, H.D., Fischl, B., 2010. Highly Accurate Inverse Consistent Registration: A Robust Approach. Neuroimage 53 (4), 1181–1196. http://reuter.mit.edu/papers/reuter-robreg10.pdf

Reuter, M., Schmansky, N.J., Rosas, H.D., Fischl, B. 2012. Within-Subject Template Estimation for Unbiased Longitudinal Image Analysis. Neuroimage 61 (4), 1402-1418. http://reuter.mit.edu/papers/reuter-long12.pdf

Segonne, F., Dale, A.M., Busa, E., Glessner, M., Salat, D., Hahn, H.K., Fischl, B., 2004. A hybrid approach to the skull stripping problem in MRI. Neuroimage 22, 1060-1075.

Sled, J.G., Zijdenbos, A.P., Evans, A.C., 1998. A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging 17, 87-97.

 

The Harmonized Protocol for Manual Hippocampal Segmentation (HarP)

Frisoni GB, Jack CR. HarP: the EADC-ADNI Harmonized Protocol for manual hippocampal segmentation. A standard of reference from a global working group. Alzheimers Dement. 2015. 11(2):107-10.

Duchesne S, Valdivia F, Robitaille N, Mouiha A, Valdivia FA, Bocchetta M, Apostolova LG, Ganzola R, Preboske G, Wolf D, Boccardi M, Jack CR Jr, Frisoni GB; EADC-ADNI Working Group on The Harmonized Protocol for Manual Hippocampal Segmentation and for the Alzheimer's Disease Neuroimaging Initiative. Manual segmentation qualification platform for the EADC-ADNI harmonized protocol for hippocampal segmentation project. Alzheimers Dement. 2015 Feb;11(2):161-74.

Boccardi M, Bocchetta M, Morency FC, Collins DL, Nishikawa M, Ganzola R, Grothe MJ, Wolf D, Redolfi A, Pievani M, Antelmi L, Fellgiebel A, Matsuda H, Teipel S, Duchesne S, Jack CR Jr, Frisoni GB; EADC-ADNI Working Group on The Harmonized Protocol for Manual Hippocampal Segmentation and for the Alzheimer's Disease Neuroimaging Initiative. Training labels for hippocampal segmentation based on the EADC-ADNI harmonized hippocampal protocol. Alzheimers Dement. 2015 Feb;11(2):175-83.

Bocchetta M, Boccardi M, Ganzola R, Apostolova LG, Preboske G, Wolf D, Ferrari C, Pasqualetti P, Robitaille N, Duchesne S, Jack CR Jr, Frisoni GB; EADC-ADNI Working Group on The Harmonized Protocol for Manual Hippocampal Segmentation and the Alzheimer's Disease Neuroimaging Initiative; EADC-ADNI Working Group on The Harmonized Protocol for Manual Hippocampal Segmentation and the Alzheimer's Disease Neuroimaging Initiative. Harmonized benchmark labels of the hippocampus on magnetic resonance: The EADC-ADNI project. Alzheimers Dement. 2014 Sep 12. pii: S1552-5260(14)00010-7.

Frisoni GB, Jack CR, Bocchetta M, Bauer C, Frederiksen KS, Liu Y, Preboske G, Swihart T, Blair M, Cavedo E, Grothe MJ, Lanfredi M, Martinez O, Nishikawa M, Portegies M, Stoub T, Ward C, Apostolova LG, Ganzola R, Wolf D, Barkhof F, Bartzokis G, DeCarli C, Csernansky JG, deToledo-Morrell L, Geerlings MI, Kaye J, Killiany RJ, Lehéricy S, Matsuda H, O'Brien J, Silbert LC, Scheltens P, Soininen H, Teipel S, Waldemar G, Fellgiebel A, Barnes J, Firbank M, Gerritsen L, Henneman W, Malykhin N, Pruessner JC, Wang L, Watson C, Wolf H, deLeon M, Pantel J, Ferrari C, Bosco P, Pasqualetti P, Duchesne S, Duvernoy H, Boccardi M; EADC -European Alzheimer's Disease Consortium and the ADNI - Alzheimer's Disease Neuroimaging Initiative. The EADC-ADNI Harmonized Protocol for manual hippocampal segmentation on magnetic resonance: Evidence of validity. Alzheimers Dement. 2014 Sep 27. pii: S1552-5260(14)02468-6.

Boccardi M, Bocchetta M, Apostolova LG, Barnes J, Bartzokis G, Corbetta G, DeCarli C, deToledo-Morrell L, Firbank M, Ganzola R, Gerritsen L, Henneman W, Killiany RJ, Malykhin N, Pasqualetti P, Pruessner JC, Redolfi A, Robitaille N, Soininen H, Tolomeo D, Wang L, Watson C, Wolf H, Duvernoy H, Duchesne S, Jack CR Jr, Frisoni GB; for the EADC-ADNI Working Group on the Harmonized Protocol for Manual Hippocampal Segmentation. Delphi definition of the EADC-ADNI Harmonized Protocol for hippocampal segmentation on magnetic resonance. Alzheimers Dement. 2014 Aug 14. pii: S1552-5260(14)02418-2.

Boccardi M, Bocchetta M, Ganzola R, Robitaille N, Redolfi A, Duchesne S, Jack CR Jr, Frisoni GB; EADC-ADNI Working Group on The Harmonized Protocol for Hippocampal Volumetry and for the Alzheimer's Disease Neuroimaging Initiative. Operationalizing protocol differences for EADC-ADNI manual hippocampal segmentation. Alzheimers Dement. 2013 May 21. pii: S1552-5260(13)00078-2.

Boccardi M, Ganzola R, Bocchetta M, Pievani M, Redolfi A, Bartzokis G, Camicioli R, Csernansky JG, de Leon MJ, deToledo-Morrell L, Killiany RJ, Lehéricy S, Pantel J, Pruessner JC, Soininen H, Watson C, Duchesne S, Jack CR Jr, Frisoni GB. Survey of protocols for the manual segmentation of the hippocampus: preparatory steps towards a joint EADC-ADNI harmonized protocol. J Alzheimers

Dis. 2011;26 Suppl 3:61-75.

Frisoni GB, Jack CR. Harmonization of magnetic resonance-based manual hippocampal segmentation: a mandatory step for wide clinical use. Alzheimers Dement. 2011 Mar;7(2):171-4.

AddNeuroMed

Khan W, Westman E, Jones N, Wahlund LO, Mecocci P, Vellas B, Tsolaki M, Kłoszewska I, Soininen H, Spenger C, Lovestone S, Muehlboeck JS, Simmons A; for the AddNeuroMed consortium and for the Alzheimer’s Disease Neuroimaging Initiative. Automated Hippocampal Subfield Measures as Predictors of Conversion from Mild Cognitive Impairment to Alzheimer's Disease in Two Independent Cohorts. Brain Topogr. 2014 Nov 5. [Epub ahead of print]

Aguilar C, Muehlboeck JS, Mecocci P, Vellas B, Tsolaki M, Kloszewska I, Soininen H, Lovestone S, Wahlund LO, Simmons A, Westman E; AddNeuroMed Consortium. Application of a MRI based index to longitudinal atrophy change in Alzheimer disease, mild cognitive impairment and healthy older individuals in the AddNeuroMed cohort. Front Aging Neurosci. 2014 Jul 14;6:145.

Paajanen T, Hänninen T, Aitken A, Hallikainen M, Westman E, Wahlund LO, Sobow T, Mecocci P, Tsolaki M, Vellas B, Muehlboeck S, Spenger C, Lovestone S, Simmons A, Soininen H; AddNeuroMed Consortium. CERAD Neuropsychological Total Scores Reflect Cortical Thinning in Prodromal Alzheimer's Disease. Dement Geriatr Cogn Dis Extra. 2013 Nov 30;3(1):446-58.

Pereira JB, Cavallin L, Spulber G, Aguilar C, Mecocci P, Vellas B, Tsolaki M, Kłoszewska I, Soininen H, Spenger C, Aarsland D, Lovestone S, Simmons A, Wahlund LO, Westman E; AddNeuroMed consortium and for the Alzheimer's Disease Neuroimaging Initiative. Influence of age, disease onset and ApoE4 on visual medial temporal lobe atrophy cut-offs. J Intern Med. 2014 Mar;275(3):317-30.

Aguilar C, Westman E, Muehlboeck JS, Mecocci P, Vellas B, Tsolaki M, Kloszewska I, Soininen H, Lovestone S, Spenger C, Simmons A, Wahlund LO. Different multivariate techniques for automated classification of MRI data in Alzheimer's disease and mild cognitive impairment. Psychiatry Res. 2013 May 30;212(2):89-98.

Mangialasche F, Westman E, Kivipelto M, Muehlboeck JS, Cecchetti R, Baglioni M, Tarducci R, Gobbi G, Floridi P, Soininen H, Kłoszewska I, Tsolaki M, Vellas B, Spenger C, Lovestone S, Wahlund LO, Simmons A, Mecocci P; AddNeuroMed consortium. Classification and prediction of clinical diagnosis of Alzheimer's disease based on MRI and plasma measures of α-/γ-tocotrienols and γ-tocopherol. J Intern Med. 2013 Jun;273(6):602-21.

Spulber G, Simmons A, Muehlboeck JS, Mecocci P, Vellas B, Tsolaki M, Kłoszewska I, Soininen H, Spenger C, Lovestone S, Wahlund LO, Westman E; dNeuroMed consortium and for the Alzheimer Disease Neuroimaging Initiative. An MRI-based index to measure the severity of Alzheimer's disease-like structural pattern in subjects with mild cognitive impairment. J Intern Med. 2013 Apr;273(4):396-409.

Velayudhan L, Proitsi P, Westman E, Muehlboeck JS, Mecocci P, Vellas B, Tsolaki M, Kłoszewska I, Soininen H, Spenger C, Hodges A, Powell J, Lovestone S, Simmons A; dNeuroMed Consortium. Entorhinal cortex thickness predicts cognitive decline in Alzheimer's disease. J Alzheimers Dis. 2013;33(3):755-66.

Liu Y, Julkunen V, Paajanen T, Westman E, Wahlund LO, Aitken A, Sobow T, Mecocci P, Tsolaki M, Vellas B, Muehlboeck S, Spenger C, Lovestone S, Simmons A, Soininen H; AddNeuroMed Consortium. Education increases reserve against Alzheimer's disease--evidence from structural MRI analysis. Neuroradiology. 2012 Sep;54(9):929-38.

Thambisetty M, Simmons A, Hye A, Campbell J, Westman E, Zhang Y, Wahlund LO, Kinsey A, Causevic M, Killick R, Kloszewska I, Mecocci P, Soininen H, Tsolaki M, Vellas B, Spenger C, Lovestone S; AddNeuroMed Consortium. Plasma biomarkers of brain atrophy in Alzheimer's disease. PLoS One. 2011;6(12):e28527.

Westman E, Cavallin L, Muehlboeck JS, Zhang Y, Mecocci P, Vellas B, Tsolaki M, Kłoszewska I, Soininen H, Spenger C, Lovestone S, Simmons A, Wahlund LO; AddNeuroMed consortium. Sensitivity and specificity of medial temporal lobe visual ratings and multivariate regional MRI classification in Alzheimer's disease. PLoS One. 2011;6(7):e22506.

Westman E, Simmons A, Muehlboeck JS, Mecocci P, Vellas B, Tsolaki M, Kłoszewska I, Soininen H, Weiner MW, Lovestone S, Spenger C, Wahlund LO; AddNeuroMed consortium; Alzheimer's Disease Neuroimaging Initiative. AddNeuroMed and ADNI: similar patterns of Alzheimer's atrophy and automated MRI classification accuracy in Europe and North America. Neuroimage. 2011 Oct 1;58(3):818-28.

Whitehead D, Tunnard C, Hurt C, Wahlund LO, Mecocci P, Tsolaki M, Vellas B, Spenger C, Kłoszewska I, Soininen H, Cromb D, Lovestone S, Simmons A; AddNeuroMed Consortium. Frontotemporal atrophy associated with paranoid delusions in women with Alzheimer's disease. Int Psychogeriatr. 2012 Jan;24(1):99-107.

Costafreda SG, Dinov ID, Tu Z, Shi Y, Liu CY, Kloszewska I, Mecocci P, Soininen H, Tsolaki M, Vellas B, Wahlund LO, Spenger C, Toga AW, Lovestone S, Simmons A. Automated hippocampal shape analysis predicts the onset of dementia in mild cognitive impairment. Neuroimage. 2011 May 1;56(1):212-9.

Simmons A, Westman E, Muehlboeck S, Mecocci P, Vellas B, Tsolaki M, Kłoszewska I, Wahlund LO, Soininen H, Lovestone S, Evans A, Spenger C. The AddNeuroMed framework for multi-centre MRI assessment of Alzheimer's disease: experience from the first 24 months. Int J Geriatr Psychiatry. 2011
Jan;26(1):75-82.

Furney SJ, Simmons A, Breen G, Pedroso I, Lunnon K, Proitsi P, Hodges A, Powell J, Wahlund LO, Kloszewska I, Mecocci P, Soininen H, Tsolaki M, Vellas B, Spenger C, Lathrop M, Shen L, Kim S, Saykin AJ, Weiner MW, Lovestone S; Alzheimer’s Disease Neuroimaging Initiative; AddNeuroMed Consortium. Genome-wide association with MRI atrophy measures as a quantitative trait locus for Alzheimer's disease. Mol Psychiatry. 2011 Nov;16(11):1130-8.

Tunnard C, Whitehead D, Hurt C, Wahlund LO, Mecocci P, Tsolaki M, Vellas B, Spenger C, Kłoszewska I, Soininen H, Lovestone S, Simmons A; AddNeuroMed Consortium. Apathy and cortical atrophy in Alzheimer's disease. Int J Geriatr Psychiatry. 2011 Jul;26(7):741-8.

Liu Y, Paajanen T, Westman E, Zhang Y, Wahlund LO, Simmons A, Tunnard C, Sobow T, Proitsi P, Powell J, Mecocci P, Tsolaki M, Vellas B, Muehlboeck S, Evans A, Spenger C, Lovestone S, Soininen H; AddNeuroMed Consortium. APOE ε2 allele is associated with larger regional cortical thicknesses and volumes. Dement Geriatr Cogn Disord. 2010;30(3):229-37.

Westman E, Simmons A, Zhang Y, Muehlboeck JS, Tunnard C, Liu Y, Collins L, Evans A, Mecocci P, Vellas B, Tsolaki M, Kłoszewska I, Soininen H, Lovestone S, Spenger C, Wahlund LO; AddNeuroMed consortium. Multivariate analysis of MRI data for Alzheimer's disease, mild cognitive impairment and healthy controls. Neuroimage. 2011 Jan 15;54(2):1178-87.

Liu Y, Paajanen T, Westman E, Wahlund LO, Simmons A, Tunnard C, Sobow T, Proitsi P, Powell J, Mecocci P, Tsolaki M, Vellas B, Muehlboeck S, Evans A, Spenger C, Lovestone S, Soininen H; AddNeuroMed Consortium. Effect of APOE ε4 allele on cortical thicknesses and volumes: the AddNeuroMed study. J Alzheimers Dis. 2010;21(3):947-66.

Thambisetty M, Simmons A, Velayudhan L, Hye A, Campbell J, Zhang Y, Wahlund LO, Westman E, Kinsey A, Güntert A, Proitsi P, Powell J, Causevic M, Killick R, Lunnon K, Lynham S, Broadstock M, Choudhry F, Howlett DR, Williams RJ, Sharp SI, Mitchelmore C, Tunnard C, Leung R, Foy C, O'Brien D, Breen G, Furney SJ, Ward M, Kloszewska I, Mecocci P, Soininen H, Tsolaki M, Vellas B, Hodges A, Murphy DG, Parkins S, Richardson JC, Resnick SM, Ferrucci L, Wong DF, Zhou Y, Muehlboeck S,
Evans A, Francis PT, Spenger C, Lovestone S. Association of plasma clusterin concentration with severity, pathology, and progression in Alzheimer disease. Arch Gen Psychiatry. 2010 Jul;67(7):739-48.

Liu Y, Paajanen T, Zhang Y, Westman E, Wahlund LO, Simmons A, Tunnard C, Sobow T, Mecocci P, Tsolaki M, Vellas B, Muehlboeck S, Evans A, Spenger C, Lovestone S, Soininen H; AddNeuroMed Consortium. Analysis of regional MRI volumes and thicknesses as predictors of conversion from mild cognitive impairment to Alzheimer's disease. Neurobiol Aging. 2010 Aug;31(8):1375-85.

Simmons A, Westman E, Muehlboeck S, Mecocci P, Vellas B, Tsolaki M, Kłoszewska I, Wahlund LO, Soininen H, Lovestone S, Evans A, Spenger C; AddNeuroMed Consortium. MRI measures of Alzheimer's disease and the AddNeuroMed study. Ann N Y Acad Sci. 2009 Oct;1180:47-55.

Lovestone S, Francis P, Kloszewska I, Mecocci P, Simmons A, Soininen H, Spenger C, Tsolaki M, Vellas B, Wahlund LO, Ward M; AddNeuroMed Consortium. AddNeuroMed--the European collaboration for the discovery of novel biomarkers for Alzheimer's disease. Ann N Y Acad Sci. 2009 Oct;1180:36-46.

Liu Y, Paajanen T, Zhang Y, Westman E, Wahlund LO, Simmons A, Tunnard C, Sobow T, Mecocci P, Tsolaki M, Vellas B, Muehlboeck S, Evans A, Spenger C, Lovestone S, Soininen H; AddNeuroMed Consortium. Combination analysis of neuropsychological tests and structural MRI measures in differentiating AD, MCI and control groups--the AddNeuroMed study. Neurobiol Aging. 2011
Jul;32(7):1198-206.

Hooper C, Lovestone S, Sainz-Fuertes R. Alzheimer's Disease, Diagnosis and the Need for Biomarkers. Biomark Insights. 2008 May 27;3:317-323.

Lovestone S, Francis P, Strandgaard K. Biomarkers for disease modification trials--the innovative medicines initiative and AddNeuroMed. J Nutr Health Aging. 2007 Jul-Aug;11(4):359-61.

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