Marina Boccardi1, Martina Bocchetta2, Rossana Ganzola1, Nicolas Robitaille3, Alberto Redolfi1, Simon Duchesne3, Clifford R Jack4, Giovanni B Frisoni5. 1. Laboratory of Epidemiology, Neuroimaging and Telemedicine, IRCCS - S. Giovanni di Dio - Fatebenefratelli, Brescia, Italy. 2. Laboratory of Epidemiology, Neuroimaging and Telemedicine, IRCCS - S. Giovanni di Dio - Fatebenefratelli, Brescia, Italy; Associazione Fatebenefratelli per la Ricerca, Rome, Italy. 3. Department of Radiology, Université Laval and Centre de Recherche de l'Institut universitaire de santé mentale de Québec, Quebec City, Canada. 4. Department of Diagnostic Radiology, Mayo Clinic and Foundation, Rochester, MN, USA. 5. Laboratory of Epidemiology, Neuroimaging and Telemedicine, IRCCS - S. Giovanni di Dio - Fatebenefratelli, Brescia, Italy; University Hospitals and University of Geneva, Geneva, Switzerland. Electronic address: gfrisoni@fatebenefratelli.it.
Abstract
BACKGROUND: Hippocampal volumetry on magnetic resonance imaging is recognized as an Alzheimer's disease (AD) biomarker, and manual segmentation is the gold standard for measurement. However, a standard procedure is lacking. We operationalize and quantitate landmark differences to help a Delphi panel converge on a set of landmarks. METHODS: One hundred percent of anatomic landmark variability across 12 different protocols for manual segmentation was reduced into four segmentation units (the minimum hippocampus, the alveus/fimbria, the tail, and the subiculum), which were segmented on magnetic resonance images by expert raters to estimate reliability and AD-related atrophy. RESULTS: Intra- and interrater reliability were more than 0.96 and 0.92, respectively, except for the alveus/fimbria, which were 0.86 and 0.77, respectively. Of all AD-related atrophy, the minimum hippocampus contributed to 67%; tail, 24%; alveus/fimbria, 4%; and the subiculum, 5%. CONCLUSIONS: Anatomic landmark variability in available protocols can be reduced to four discrete and measurable segmentation units. Their quantitative assessment will help a Delphi panel to define a set of landmarks for a harmonized protocol.
BACKGROUND: Hippocampal volumetry on magnetic resonance imaging is recognized as an Alzheimer's disease (AD) biomarker, and manual segmentation is the gold standard for measurement. However, a standard procedure is lacking. We operationalize and quantitate landmark differences to help a Delphi panel converge on a set of landmarks. METHODS: One hundred percent of anatomic landmark variability across 12 different protocols for manual segmentation was reduced into four segmentation units (the minimum hippocampus, the alveus/fimbria, the tail, and the subiculum), which were segmented on magnetic resonance images by expert raters to estimate reliability and AD-related atrophy. RESULTS: Intra- and interrater reliability were more than 0.96 and 0.92, respectively, except for the alveus/fimbria, which were 0.86 and 0.77, respectively. Of all AD-related atrophy, the minimum hippocampus contributed to 67%; tail, 24%; alveus/fimbria, 4%; and the subiculum, 5%. CONCLUSIONS: Anatomic landmark variability in available protocols can be reduced to four discrete and measurable segmentation units. Their quantitative assessment will help a Delphi panel to define a set of landmarks for a harmonized protocol.
Authors: Giovanni B Frisoni; Clifford R Jack; Martina Bocchetta; Corinna Bauer; Kristian S Frederiksen; Yawu Liu; Gregory Preboske; Tim Swihart; Melanie Blair; Enrica Cavedo; Michel J Grothe; Mariangela Lanfredi; Oliver Martinez; Masami Nishikawa; Marileen Portegies; Travis Stoub; Chadwich Ward; Liana G Apostolova; Rossana Ganzola; Dominik Wolf; Frederik Barkhof; George Bartzokis; Charles DeCarli; John G Csernansky; Leyla deToledo-Morrell; Mirjam I Geerlings; Jeffrey Kaye; Ronald J Killiany; Stephane Lehéricy; Hiroshi Matsuda; John O'Brien; Lisa C Silbert; Philip Scheltens; Hilkka Soininen; Stefan Teipel; Gunhild Waldemar; Andreas Fellgiebel; Josephine Barnes; Michael Firbank; Lotte Gerritsen; Wouter Henneman; Nikolai Malykhin; Jens C Pruessner; Lei Wang; Craig Watson; Henrike Wolf; Mony deLeon; Johannes Pantel; Clarissa Ferrari; Paolo Bosco; Patrizio Pasqualetti; Simon Duchesne; Henri Duvernoy; Marina Boccardi Journal: Alzheimers Dement Date: 2014-09-27 Impact factor: 21.566
Authors: Michael W Weiner; Dallas P Veitch; Paul S Aisen; Laurel A Beckett; Nigel J Cairns; Robert C Green; Danielle Harvey; Clifford R Jack; William Jagust; John C Morris; Ronald C Petersen; Andrew J Saykin; Leslie M Shaw; Arthur W Toga; John Q Trojanowski Journal: Alzheimers Dement Date: 2017-03-22 Impact factor: 21.566
Authors: Liana G Apostolova; Chris Zarow; Kristina Biado; Sona Hurtz; Marina Boccardi; Johanne Somme; Hedieh Honarpisheh; Anna E Blanken; Jenny Brook; Spencer Tung; Darrick Lo; Denise Ng; Jeffry R Alger; Harry V Vinters; Martina Bocchetta; Henri Duvernoy; Clifford R Jack; Giovanni B Frisoni Journal: Alzheimers Dement Date: 2015-01-22 Impact factor: 21.566
Authors: Mike F Schmidt; Judd M Storrs; Kevin B Freeman; Clifford R Jack; Stephen T Turner; Michael E Griswold; Thomas H Mosley Journal: Hum Brain Mapp Date: 2018-02-21 Impact factor: 5.038
Authors: Tejas Sankar; Min Tae M Park; Tasha Jawa; Raihaan Patel; Nikhil Bhagwat; Aristotle N Voineskos; Andres M Lozano; M Mallar Chakravarty Journal: Hum Brain Mapp Date: 2017-03-15 Impact factor: 5.038
Authors: Marina Boccardi; Martina Bocchetta; Liana G Apostolova; Josephine Barnes; George Bartzokis; Gabriele Corbetta; Charles DeCarli; Leyla deToledo-Morrell; Michael Firbank; Rossana Ganzola; Lotte Gerritsen; Wouter Henneman; Ronald J Killiany; Nikolai Malykhin; Patrizio Pasqualetti; Jens C Pruessner; Alberto Redolfi; Nicolas Robitaille; Hilkka Soininen; Daniele Tolomeo; Lei Wang; Craig Watson; Henrike Wolf; Henri Duvernoy; Simon Duchesne; Clifford R Jack; Giovanni B Frisoni Journal: Alzheimers Dement Date: 2014-08-15 Impact factor: 21.566
Authors: Victoria Sanborn; Sarah R Preis; Alvin Ang; Sherral Devine; Jesse Mez; Charles DeCarli; Rhoda Au; Michael L Alosco; John Gunstad Journal: J Alzheimers Dis Date: 2020 Impact factor: 4.472
Authors: Michel J Grothe; Christina Schuster; Florian Bauer; Helmut Heinsen; Johannes Prudlo; Stefan J Teipel Journal: J Neurol Date: 2014-07-25 Impact factor: 4.849