Dataset Information

The EADC-ADNI Harmonized Protocol for manual hippocampal segmentation on magnetic resonance: evidence of validity.

ABSTRACT: 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.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.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).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.

SUBMITTER: Frisoni GB

PROVIDER: S-EPMC4422168 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature

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The EADC-ADNI Harmonized Protocol for manual hippocampal segmentation on magnetic resonance: evidence of validity.

Frisoni Giovanni B GB Frisoni Giovanni B GB Jack Clifford R CR Bocchetta Martina M Bauer Corinna C Frederiksen Kristian S KS Liu Yawu Y Preboske Gregory G Swihart Tim T Blair Melanie M Cavedo Enrica E Grothe Michel J MJ Lanfredi Mariangela M Martinez Oliver O Nishikawa Masami M Portegies Marileen M Stoub Travis T Ward Chadwich C Apostolova Liana G LG Ganzola Rossana R Wolf Dominik D Barkhof Frederik F Bartzokis George G DeCarli Charles C Csernansky John G JG deToledo-Morrell Leyla L Geerlings Mirjam I MI Kaye Jeffrey J Killiany Ronald J RJ Lehéricy Stephane S Matsuda Hiroshi H O'Brien John J Silbert Lisa C LC Scheltens Philip P Soininen Hilkka H Teipel Stefan S Waldemar Gunhild G Fellgiebel Andreas A Barnes Josephine J Firbank Michael M Gerritsen Lotte L Henneman Wouter W Malykhin Nikolai N Pruessner Jens C JC Wang Lei L Watson Craig C Wolf Henrike H deLeon Mony M Pantel Johannes J Ferrari Clarissa C Bosco Paolo P Pasqualetti Patrizio P Duchesne Simon S Duvernoy Henri H Boccardi Marina M

Alzheimer's & dementia : the journal of the Alzheimer's Association 20140927 2

<h4>Background</h4>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.<h4>Methods</h4>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-platfo ...[more]

PMID: 25267715

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Project description:PurposeThe use of magnetic resonance imaging (MRI) in radiotherapy treatment planning has rapidly increased due to its ability to evaluate patient's anatomy without the use of ionizing radiation and due to its high soft tissue contrast. For these reasons, MRI has become the modality of choice for longitudinal and adaptive treatment studies. Automatic segmentation could offer many benefits for these studies. In this work, we describe a T2-weighted MRI dataset of head and neck cancer patients that can be used to evaluate the accuracy of head and neck normal tissue auto-segmentation systems through comparisons to available expert manual segmentations.Acquisition and validation methodsT2-weighted MRI images were acquired for 55 head and neck cancer patients. These scans were collected after radiotherapy computed tomography (CT) simulation scans using a thermoplastic mask to replicate patient treatment position. All scans were acquired on a single 1.5 T Siemens MAGNETOM Aera MRI with two large four-channel flex phased-array coils. The scans covered the region encompassing the nasopharynx region cranially and supraclavicular lymph node region caudally, when possible, in the superior-inferior direction. Manual contours were created for the left/right submandibular gland, left/right parotids, left/right lymph node level II, and left/right lymph node level III. These contours underwent quality assurance to ensure adherence to predefined guidelines, and were corrected if edits were necessary.Data format and usage notesThe T2-weighted images and RTSTRUCT files are available in DICOM format. The regions of interest are named based on AAPM's Task Group 263 nomenclature recommendations (Glnd_Submand_L, Glnd_Submand_R, LN_Neck_II_L, Parotid_L, Parotid_R, LN_Neck_II_R, LN_Neck_III_L, LN_Neck_III_R). This dataset is available on The Cancer Imaging Archive (TCIA) by the National Cancer Institute under the collection "AAPM RT-MAC Grand Challenge 2019" (https://doi.org/10.7937/tcia.2019.bcfjqfqb).Potential applicationsThis dataset provides head and neck patient MRI scans to evaluate auto-segmentation systems on T2-weighted images. Additional anatomies could be provided at a later time to enhance the existing library of contours.

Dataset Information

The EADC-ADNI Harmonized Protocol for manual hippocampal segmentation on magnetic resonance: evidence of validity.

Publications

The EADC-ADNI Harmonized Protocol for manual hippocampal segmentation on magnetic resonance: evidence of validity.

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