New objective simple evaluation methods of amyloid PET/CT using whole brain histogram and Top20%-Map Article Swipe
Chio Okuyama
,
Tatsuya Higashi
,
Koichi Ishizu
,
Naoya Oishi
,
Kuninori Kusano
,
Miki Ito
,
Shinya Kagawa
,
Tomoko Okina
,
Norio Suzuki
,
Hiroshi Hasegawa
,
Yasuhiro Nagahama
,
Hiroyuki Watanabe
,
Masahiro Ono
,
Hiroshi Yamauchi
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-4345342/v1
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-4345342/v1
Objective This study aims to assess the utility of newly developed objective methods for the evaluation of intracranial abnormal amyloid deposition using PET/CT histogram without use of cortical ROI analyses. Methods Twenty-five healthy volunteers (HV) and 38 patients with diagnosed or suspected dementia who had undergone 18F-FPYBF-2 PET/CT were retrospectively included in this study. Out of them, 11C-PiB PET/CT had been also performed in 13 subjects. In addition to the conventional methods, namely visual judgement and quantitative analyses using composed standardized uptake value ratio (comSUVR), the PET images were also evaluated by the following new parameters: the skewness and mode to mean ratio (MMR) obtained from the histogram of the brain parenchyma; Top20%-map that highlights the areas with high tracer accumulation occupying 20% volume of the total brain parenchymal on the individual’s CT images. We evaluated the utility of the new methods using histogram compared with the visual assessment and comSUVR. The results of these new methods between 18F-FPYBF-2 and 11C-PiB were also compared in 13 subjects. Results In visual analysis, 32, 9, 22 subjects showed negative, border, and positive results, and composed SUVR in each group were 1.11 ± 0.06, 1.20 ± 0.13, 1.48 ± 0.18 (p < 0.0001), respectively. Visually positive subjects showed significantly low skewness and high MMR (p < 0.0001), and the Top20%-Map showed the presence or absence of abnormal deposits clearly. In comparison between the two tracers, visual evaluation was all consistent, and the ComSUVR, skewness, MMR showed significant good correlation. The Top20%-Maps showed similar pattern. Conclusions Our new methods using the histogram of the brain parenchymal accumulation are simple and suitable for clinical practice of amyloid PET, and Top20%-Map on the individual’s brain CT can be the great help for the visual assessment.
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- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-4345342/v1
- https://www.researchsquare.com/article/rs-4345342/latest.pdf
- OA Status
- green
- Cited By
- 1
- References
- 43
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4396725851
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- OpenAlex ID
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https://openalex.org/W4396725851Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.21203/rs.3.rs-4345342/v1Digital Object Identifier
- Title
-
New objective simple evaluation methods of amyloid PET/CT using whole brain histogram and Top20%-MapWork title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-05-08Full publication date if available
- Authors
-
Chio Okuyama, Tatsuya Higashi, Koichi Ishizu, Naoya Oishi, Kuninori Kusano, Miki Ito, Shinya Kagawa, Tomoko Okina, Norio Suzuki, Hiroshi Hasegawa, Yasuhiro Nagahama, Hiroyuki Watanabe, Masahiro Ono, Hiroshi YamauchiList of authors in order
- Landing page
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https://doi.org/10.21203/rs.3.rs-4345342/v1Publisher landing page
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https://www.researchsquare.com/article/rs-4345342/latest.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.researchsquare.com/article/rs-4345342/latest.pdfDirect OA link when available
- Concepts
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Nuclear medicine, Histogram, Skewness, Medicine, Mathematics, Artificial intelligence, Computer science, Statistics, Image (mathematics)Top concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
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2024: 1Per-year citation counts (last 5 years)
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43Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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