Operationalizing protocol differences for EADC-ADNI manual hippocampal segmentation

Marina Boccardi, Martina Bocchetta, Rossana Ganzola, Nicolas Robitaille, Alberto Redolfi, Simon Duchesne, Clifford R. Jack, Giovanni B. Frisoni, George Bartzokis, John G. Csernansky, Mony J. De Leon, Leyla Detoledo-Morrell, Ronald J. Killiany, Stephane Lehericy, Nikolai Malykhin, Johannes Pantel, Jens C. Pruessner, Hilkka Soininen, Craig Watson

Research output: Contribution to journalArticlepeer-review

37 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)184-194
Number of pages11
JournalAlzheimer's and Dementia
Issue number2
StatePublished - 2015

ASJC Scopus subject areas

  • Epidemiology
  • Health Policy
  • Developmental Neuroscience
  • Clinical Neurology
  • Geriatrics and Gerontology
  • Psychiatry and Mental health
  • Cellular and Molecular Neuroscience


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