Considerations for Performing Level-2 Centiloid Transformations for Amyloid PET SUVR values
Abstract The Centiloid Project describes a post-hoc data transformation to standardize amyloid PET measurements to enable direct data comparisons across sites and studies using differing acquisition/analysis methods. It uses linear regression that transforms values using different measurement scales...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2018-05-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-018-25459-9 |
| _version_ | 1818428238419984384 |
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| author | Christopher G. Schwarz Nirubol Tosakulwong Matthew L. Senjem Jeffrey L. Gunter Terry M. Therneau Prashanthi Vemuri Val J. Lowe Clifford R. Jack |
| author_facet | Christopher G. Schwarz Nirubol Tosakulwong Matthew L. Senjem Jeffrey L. Gunter Terry M. Therneau Prashanthi Vemuri Val J. Lowe Clifford R. Jack |
| author_sort | Christopher G. Schwarz |
| collection | DOAJ |
| description | Abstract The Centiloid Project describes a post-hoc data transformation to standardize amyloid PET measurements to enable direct data comparisons across sites and studies using differing acquisition/analysis methods. It uses linear regression that transforms values using different measurement scales to match those from a standard Centiloid unit scale. Our group’s measurement method differs from the Centiloid’s standard method in both acquisition and analysis methods. In this work we examine multiple variations for performing these transformations and compare several approaches. We hypothesized that using Deming regression, which accounts for error on both axes, would produce a more optimal transformation than the recommended standard linear regression. We also examined the effects of performing separate regressions for differences in acquisition and analysis methods, rather than a direct single-regression approach. Our results found that all transformation approaches had very similar performance and were within the recommended tolerance thresholds. |
| first_indexed | 2024-12-14T14:58:27Z |
| format | Article |
| id | doaj.art-384c32a4458e4957a1125b51825a85b5 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-14T14:58:27Z |
| publishDate | 2018-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-384c32a4458e4957a1125b51825a85b52022-12-21T22:56:56ZengNature PortfolioScientific Reports2045-23222018-05-01811610.1038/s41598-018-25459-9Considerations for Performing Level-2 Centiloid Transformations for Amyloid PET SUVR valuesChristopher G. Schwarz0Nirubol Tosakulwong1Matthew L. Senjem2Jeffrey L. Gunter3Terry M. Therneau4Prashanthi Vemuri5Val J. Lowe6Clifford R. Jack7Department of Radiology, Mayo Clinic and FoundationDepartment of Health Sciences Research, Division of Biostatistics, Mayo Clinic and FoundationDepartment of Radiology, Mayo Clinic and FoundationDepartment of Radiology, Mayo Clinic and FoundationDepartment of Health Sciences Research, Division of Biostatistics, Mayo Clinic and FoundationDepartment of Radiology, Mayo Clinic and FoundationDepartment of Radiology, Mayo Clinic and FoundationDepartment of Radiology, Mayo Clinic and FoundationAbstract The Centiloid Project describes a post-hoc data transformation to standardize amyloid PET measurements to enable direct data comparisons across sites and studies using differing acquisition/analysis methods. It uses linear regression that transforms values using different measurement scales to match those from a standard Centiloid unit scale. Our group’s measurement method differs from the Centiloid’s standard method in both acquisition and analysis methods. In this work we examine multiple variations for performing these transformations and compare several approaches. We hypothesized that using Deming regression, which accounts for error on both axes, would produce a more optimal transformation than the recommended standard linear regression. We also examined the effects of performing separate regressions for differences in acquisition and analysis methods, rather than a direct single-regression approach. Our results found that all transformation approaches had very similar performance and were within the recommended tolerance thresholds.https://doi.org/10.1038/s41598-018-25459-9 |
| spellingShingle | Christopher G. Schwarz Nirubol Tosakulwong Matthew L. Senjem Jeffrey L. Gunter Terry M. Therneau Prashanthi Vemuri Val J. Lowe Clifford R. Jack Considerations for Performing Level-2 Centiloid Transformations for Amyloid PET SUVR values Scientific Reports |
| title | Considerations for Performing Level-2 Centiloid Transformations for Amyloid PET SUVR values |
| title_full | Considerations for Performing Level-2 Centiloid Transformations for Amyloid PET SUVR values |
| title_fullStr | Considerations for Performing Level-2 Centiloid Transformations for Amyloid PET SUVR values |
| title_full_unstemmed | Considerations for Performing Level-2 Centiloid Transformations for Amyloid PET SUVR values |
| title_short | Considerations for Performing Level-2 Centiloid Transformations for Amyloid PET SUVR values |
| title_sort | considerations for performing level 2 centiloid transformations for amyloid pet suvr values |
| url | https://doi.org/10.1038/s41598-018-25459-9 |
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