TY - JOUR
T1 - The status of digital pathology and associated infrastructure within Alzheimer's Disease Centers
AU - Scalco, Rebeca
AU - Hamsafar, Yamah
AU - White, Charles L.
AU - Schneider, Julie A.
AU - Reichard, Robert Ross
AU - Prokop, Stefan
AU - Perrin, Richard J.
AU - Nelson, Peter T.
AU - Mooney, Sean
AU - Lieberman, Andrew P.
AU - Kukull, Walter A.
AU - Kofler, Julia
AU - Keene, Christopher Dirk
AU - Kapasi, Alifiya
AU - Irwin, David J.
AU - Gutman, David A.
AU - Flanagan, Margaret E.
AU - Crary, John F.
AU - Chan, Kwun C.
AU - Murray, Melissa E.
AU - Dugger, Brittany N.
N1 - Publisher Copyright:
© The Author(s) 2023.
PY - 2023/3/1
Y1 - 2023/3/1
N2 - Digital pathology (DP) has transformative potential, especially for Alzheimer disease and related disorders. However, infrastructure barriers may limit adoption. To provide benchmarks and insights into implementation barriers, a survey was conducted in 2019 within National Institutes of Health's Alzheimer's Disease Centers (ADCs). Questions covered infrastructure, funding sources, and data management related to digital pathology. Of the 35 ADCs to which the survey was sent, 33 responded. Most respondents (81%) stated that their ADC had digital slide scanner access, with the most frequent brand being Aperio/Leica (62.9%). Approximately a third of respondents stated there were fees to utilize the scanner. For DP and machine learning (ML) resources, 41% of respondents stated none was supported by their ADC. For scanner purchasing and operations, 50% of respondents stated they received institutional support. Some were unsure of the file size of scanned digital images (37%) and total amount of storage space files occupied (50%). Most (76%) were aware of other departments at their institution working with ML; a similar (76%) percentage were unaware of multiuniversity or industry partnerships. These results demonstrate many ADCs have access to a digital slide scanner; additional investigations are needed to further understand hurdles to implement DP and ML workflows.
AB - Digital pathology (DP) has transformative potential, especially for Alzheimer disease and related disorders. However, infrastructure barriers may limit adoption. To provide benchmarks and insights into implementation barriers, a survey was conducted in 2019 within National Institutes of Health's Alzheimer's Disease Centers (ADCs). Questions covered infrastructure, funding sources, and data management related to digital pathology. Of the 35 ADCs to which the survey was sent, 33 responded. Most respondents (81%) stated that their ADC had digital slide scanner access, with the most frequent brand being Aperio/Leica (62.9%). Approximately a third of respondents stated there were fees to utilize the scanner. For DP and machine learning (ML) resources, 41% of respondents stated none was supported by their ADC. For scanner purchasing and operations, 50% of respondents stated they received institutional support. Some were unsure of the file size of scanned digital images (37%) and total amount of storage space files occupied (50%). Most (76%) were aware of other departments at their institution working with ML; a similar (76%) percentage were unaware of multiuniversity or industry partnerships. These results demonstrate many ADCs have access to a digital slide scanner; additional investigations are needed to further understand hurdles to implement DP and ML workflows.
KW - Alzheimer disease
KW - Computational pathology
KW - Deep Learning
KW - Digital pathology
KW - Machine Learning
KW - Quantitative pathology
KW - Slide scanner
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U2 - 10.1093/jnen/nlac127
DO - 10.1093/jnen/nlac127
M3 - Article
C2 - 36692179
AN - SCOPUS:85160264865
SN - 0022-3069
VL - 82
SP - 202
EP - 211
JO - Journal of Neuropathology and Experimental Neurology
JF - Journal of Neuropathology and Experimental Neurology
IS - 3
ER -