Giovanni B Frisoni1, Clifford R Jack2, Martina Bocchetta3, Corinna Bauer4, Kristian S Frederiksen5, Yawu Liu6, Gregory Preboske2, Tim Swihart7, Melanie Blair8, Enrica Cavedo9, Michel J Grothe10, Mariangela Lanfredi11, Oliver Martinez12, Masami Nishikawa13, Marileen Portegies14, Travis Stoub15, Chadwich Ward2, Liana G Apostolova16, Rossana Ganzola17, Dominik Wolf18, Frederik Barkhof19, George Bartzokis20, Charles DeCarli12, John G Csernansky21, Leyla deToledo-Morrell15, Mirjam I Geerlings14, Jeffrey Kaye7, Ronald J Killiany4, Stephane Lehéricy22, Hiroshi Matsuda13, John O'Brien23, Lisa C Silbert7, Philip Scheltens24, Hilkka Soininen6, Stefan Teipel25, Gunhild Waldemar5, Andreas Fellgiebel18, Josephine Barnes8, Michael Firbank23, Lotte Gerritsen26, Wouter Henneman19, Nikolai Malykhin27, Jens C Pruessner28, Lei Wang29, Craig Watson12, Henrike Wolf30, Mony deLeon31, Johannes Pantel32, Clarissa Ferrari11, Paolo Bosco9, Patrizio Pasqualetti33, Simon Duchesne17, Henri Duvernoy34, Marina Boccardi35. 1. LENITEM (Laboratory of Epidemiology, Neuroimaging and Telemedicine) IRCCS - Istituto Centro S. Giovanni di Dio - Fatebenefratelli, Brescia, Italy; Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland. 2. Department of Diagnostic Radiology, Mayo Clinic and Foundation, Rochester, MN, USA. 3. LENITEM (Laboratory of Epidemiology, Neuroimaging and Telemedicine) IRCCS - Istituto Centro S. Giovanni di Dio - Fatebenefratelli, Brescia, Italy; Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy. 4. Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA. 5. Memory Disorders Research Group, Department of Neurology, Rigshospitalet, Copenhagen, Denmark. 6. Department of Neurology, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland. 7. Department of Neurology, Oregon Health & Science University, Portland, OR, USA. 8. Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, National Hospital for Neurology and Neurosurgery, London, UK. 9. LENITEM (Laboratory of Epidemiology, Neuroimaging and Telemedicine) IRCCS - Istituto Centro S. Giovanni di Dio - Fatebenefratelli, Brescia, Italy. 10. German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany. 11. Unit of Psychiatry, IRCCS - Centro S. Giovanni di Dio - Fatebenefratelli, Brescia, Italy. 12. Department of Neurology, University of California, Davis, CA, USA. 13. Kawamura Gakuen Woman's University, Abiko-city, Japan. 14. University Medical Center Utrecht, Julius Center for Health Sciences and Primary Care, Utrecht, The Netherlands. 15. Department of Neurological Sciences, Rush University, Chicago, IL, USA. 16. Mary S. Easton Center for Alzheimer's Disease Research and Laboratory of NeuroImaging, David Geffen School of Medicine, University of California, Los Angeles, CA, USA. 17. Department of Radiology, Université Laval and Centre de Recherche de l'Institut universitaire de santé mentale de Québec, Quebec City, Canada. 18. Klinik für Psychiatrie und Psychotherapie, Johannes Gutenberg-Universität Mainz, Mainz, Germany. 19. Department of Radiology and Nuclear Medicine, Image Analysis Center, VU University Medical Center, Amsterdam, The Netherlands. 20. Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA. 21. Washington University, Northwestern University, Chicago, IL, USA. 22. Service de Neuroradiologie, Hopital de la Pitie-Salpetriere, Paris, France. 23. Institute for Ageing and Health, Newcastle University, Newcastle upon Tyne, UK. 24. Department of Neurology and Alzheimer Center, VU University Medical Cente and Neuroscience Campus Amsterdam, Amsterdam, The Netherlands. 25. German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany; Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany. 26. University Medical Center Utrecht, Julius Center for Health Sciences and Primary Care, Utrecht, The Netherlands; Department of Medical epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden. 27. Department of Biomedical Engineering, Centre for Neuroscience, University of Alberta, Edmonton, Alberta, Canada. 28. Department of Psychiatry, McGill Centre for Studies in Aging, McGill University, Montreal, Quebec, Canada. 29. Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA. 30. Department of Psychiatry Research and Geriatric Psychiatry, Psychiatric University Hospitals, University of Zurich, Zurich, Switzerland; German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany. 31. New York University School of Medicine, Center for Brain Health, New York, NY, USA. 32. Institute of General Practice, Goethe-University Frankfurt, Frankfurt, Germany. 33. SeSMIT (Service for Medical Statistics and Information Technology), AFaR (Fatebenefratelli Association for Research), Fatebenefratelli Hospital, Rome, Italy; Unit of Clinical and Molecular Epidemiology, IRCCS "San Raffaele Pisana", Rome, Italy. 34. Chemin des Relançons, Besançon, France. 35. LENITEM (Laboratory of Epidemiology, Neuroimaging and Telemedicine) IRCCS - Istituto Centro S. Giovanni di Dio - Fatebenefratelli, Brescia, Italy. Electronic address: mboccardifbf@gmail.com.
Abstract
BACKGROUND: An international Delphi panel has defined a harmonized protocol (HarP) for the manual segmentation of the hippocampus on MR. The aim of this study is to study the concurrent validity of the HarP toward local protocols, and its major sources of variance. METHODS: Fourteen tracers segmented 10 Alzheimer's Disease Neuroimaging Initiative (ADNI) cases scanned at 1.5 T and 3T following local protocols, qualified for segmentation based on the HarP through a standard web-platform and resegmented following the HarP. The five most accurate tracers followed the HarP to segment 15 ADNI cases acquired at three time points on both 1.5 T and 3T. RESULTS: The agreement among tracers was relatively low with the local protocols (absolute left/right ICC 0.44/0.43) and much higher with the HarP (absolute left/right ICC 0.88/0.89). On the larger set of 15 cases, the HarP agreement within (left/right ICC range: 0.94/0.95 to 0.99/0.99) and among tracers (left/right ICC range: 0.89/0.90) was very high. The volume variance due to different tracers was 0.9% of the total, comparing favorably to variance due to scanner manufacturer (1.2), atrophy rates (3.5), hemispheric asymmetry (3.7), field strength (4.4), and significantly smaller than the variance due to atrophy (33.5%, P < .001), and physiological variability (49.2%, P < .001). CONCLUSIONS: The HarP has high measurement stability compared with local segmentation protocols, and good reproducibility within and among human tracers. Hippocampi segmented with the HarP can be used as a reference for the qualification of human tracers and automated segmentation algorithms.
BACKGROUND: An international Delphi panel has defined a harmonized protocol (HarP) for the manual segmentation of the hippocampus on MR. The aim of this study is to study the concurrent validity of the HarP toward local protocols, and its major sources of variance. METHODS: Fourteen tracers segmented 10 Alzheimer's Disease Neuroimaging Initiative (ADNI) cases scanned at 1.5 T and 3T following local protocols, qualified for segmentation based on the HarP through a standard web-platform and resegmented following the HarP. The five most accurate tracers followed the HarP to segment 15 ADNI cases acquired at three time points on both 1.5 T and 3T. RESULTS: The agreement among tracers was relatively low with the local protocols (absolute left/right ICC 0.44/0.43) and much higher with the HarP (absolute left/right ICC 0.88/0.89). On the larger set of 15 cases, the HarP agreement within (left/right ICC range: 0.94/0.95 to 0.99/0.99) and among tracers (left/right ICC range: 0.89/0.90) was very high. The volume variance due to different tracers was 0.9% of the total, comparing favorably to variance due to scanner manufacturer (1.2), atrophy rates (3.5), hemispheric asymmetry (3.7), field strength (4.4), and significantly smaller than the variance due to atrophy (33.5%, P < .001), and physiological variability (49.2%, P < .001). CONCLUSIONS: The HarP has high measurement stability compared with local segmentation protocols, and good reproducibility within and among human tracers. Hippocampi segmented with the HarP can be used as a reference for the qualification of human tracers and automated segmentation algorithms.
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