Optimized extraction of the medial temporal lobe for postmortem MRI based on custom 3D printed molds: Neuroimaging / New imaging methods. (7th December 2020)
- Record Type:
- Journal Article
- Title:
- Optimized extraction of the medial temporal lobe for postmortem MRI based on custom 3D printed molds: Neuroimaging / New imaging methods. (7th December 2020)
- Main Title:
- Optimized extraction of the medial temporal lobe for postmortem MRI based on custom 3D printed molds
- Authors:
- Lasserve, Jade
Lim, Sydney A.
Wisse, Laura
Ittyerah, Ranjit
Ravikumar, Sadhana
Lavery, Madigan
Robinson, John L.
Schuck, Theresa
Grossman, Murray
Lee, Eddie B.
Yushkevich, Paul A.
Tisdall, Dylan M.
Prabhakaran, Karthik
Mizsei, Gabor
Artacho‐Perula, Emilio
Martin, Maria Mercedes Iniguez de Onzono
Jimenez, Maria del Mar Arroyo
Munoz, Monica
Romero, Francisco Javier Molina
Rabal, Maria del Pilar Marcos
Irwin, David J.
Trojanowski, John Q.
Wolk, David A.
Insausti, Ricardo - Abstract:
- Abstract: Background: Structural magnetic resonance imaging (MRI) biomarkers are important for early detection of Alzheimer's Disease (AD). However, atrophy measures can be confounded by changes due to aging and comorbid non‐AD neurodegenerative pathologies. Linking postmortem MRI of the medial temporal lobe (MTL) to histopathology may identify focal patterns of change associated specifically with early AD. We implemented a pipeline of high‐resolution MRI of MTL specimens and serial histopathology imaging [REF]. However, the task of extracting the intact MTL specimen such that it fits into the MRI coil requires anatomical expertise and has proven error prone. Here we present an algorithm to automatically create 3D printed molds guiding MTL extraction. Method: INPUTS: 7T MRI scan of a formalin‐fixed hemisphere in which the hemisphere, MTL ROI and optional second ROI to be spared during cutting (e.g. frontal lobe) have been segmented using ITK‐SNAP semi‐automatic segmentation tools. OUTPUTS: Two 3D printed molds with slits that guide cutting. Mold 1 holds the whole hemisphere, guiding four cuts orthogonal to the midsagittal plane (Figure 1). Mold 2 holds the extracted tissue block, guiding three subsequent longitudinal cuts that trim the tissue to fit into a 50mm cylindrical holder (Figure 2). The positioning of the cuts can be specified interactively by the user using ITK‐SNAP (translating and rotating 3D images representing cutting planes) or automatically by optimizingAbstract: Background: Structural magnetic resonance imaging (MRI) biomarkers are important for early detection of Alzheimer's Disease (AD). However, atrophy measures can be confounded by changes due to aging and comorbid non‐AD neurodegenerative pathologies. Linking postmortem MRI of the medial temporal lobe (MTL) to histopathology may identify focal patterns of change associated specifically with early AD. We implemented a pipeline of high‐resolution MRI of MTL specimens and serial histopathology imaging [REF]. However, the task of extracting the intact MTL specimen such that it fits into the MRI coil requires anatomical expertise and has proven error prone. Here we present an algorithm to automatically create 3D printed molds guiding MTL extraction. Method: INPUTS: 7T MRI scan of a formalin‐fixed hemisphere in which the hemisphere, MTL ROI and optional second ROI to be spared during cutting (e.g. frontal lobe) have been segmented using ITK‐SNAP semi‐automatic segmentation tools. OUTPUTS: Two 3D printed molds with slits that guide cutting. Mold 1 holds the whole hemisphere, guiding four cuts orthogonal to the midsagittal plane (Figure 1). Mold 2 holds the extracted tissue block, guiding three subsequent longitudinal cuts that trim the tissue to fit into a 50mm cylindrical holder (Figure 2). The positioning of the cuts can be specified interactively by the user using ITK‐SNAP (translating and rotating 3D images representing cutting planes) or automatically by optimizing (using Powell's method) energy functions that minimize the volume of the final piece of tissue under multiple constraints (see Figures 3 and 4). Result: The algorithm with interactively positioned cut planes was used in four hemispheres; the automated version in one (Figure 5). For each MRI scan, the MTL was intact. By contrast, retrospective review revealed cutting errors in 48% of manually cut specimens. Conclusion: Our image‐guided approach reduces errors and dependence on anatomical expertise; allows more tissue to be spared from each brain donation; and enables postmortem imaging at a larger scale. It is not limited to the MTL and could be of interest to brain banks and AD research centers involved in postmortem imaging. … (more)
- Is Part Of:
- Alzheimer's & dementia. Volume 16(2020)Supplement 4
- Journal:
- Alzheimer's & dementia
- Issue:
- Volume 16(2020)Supplement 4
- Issue Display:
- Volume 16, Issue 4 (2020)
- Year:
- 2020
- Volume:
- 16
- Issue:
- 4
- Issue Sort Value:
- 2020-0016-0004-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2020-12-07
- Subjects:
- Alzheimer's disease -- Periodicals
Alzheimer Disease -- Periodicals
Dementia -- Periodicals
Démence
Maladie d'Alzheimer
Périodique électronique (Descripteur de forme)
Ressource Internet (Descripteur de forme)
616.83 - Journal URLs:
- http://www.sciencedirect.com/science/journal/15525260 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1002/alz.043254 ↗
- Languages:
- English
- ISSNs:
- 1552-5260
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0806.255333
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