Amyloid-β PET—Correlation with cerebrospinal fluid biomarkers and prediction of Alzheimer´s disease diagnosis in a memory clinic
Alzheimer's disease (AD) remains a clinical diagnosis but biomarkers from cerebrospinal fluid (CSF) and more lately amyloid imaging with positron emission tomography (PET), are important to support a diagnosis of AD. To compare amyloid-β (Aβ) PET imaging with biomarkers in CSF and evaluate the...
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| Published in | PloS one Vol. 14; no. 8; p. e0221365 |
|---|---|
| Main Authors | , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Public Library of Science
2019
PLOS Public Library of Science (PLoS) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1932-6203 1932-6203 |
| DOI | 10.1371/journal.pone.0221365 |
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| Abstract | Alzheimer's disease (AD) remains a clinical diagnosis but biomarkers from cerebrospinal fluid (CSF) and more lately amyloid imaging with positron emission tomography (PET), are important to support a diagnosis of AD.
To compare amyloid-β (Aβ) PET imaging with biomarkers in CSF and evaluate the prediction of Aβ PET on diagnosis in a memory clinic setting.
We included 64 patients who had lumbar puncture and Aβ PET with 18F-Flutemetamol performed within 190 days. PET was binary classified (Flut+ or Flut-) and logistic regression analyses for correlation to each CSF biomarker; Aβ 42 (Aβ42), total tau (T-tau) and phosphorylated tau (P-tau), were performed. Cut-off values were assessed by receiver operating characteristic (ROC) curves. Logistic regression was performed for prediction of clinical AD diagnosis. We assessed the interrater agreement of PET classification as well as for diagnoses, which were made both with and without knowledge of PET results.
Thirty-two of the 34 patients (94%) in the Flut+ group and nine of the 30 patients (30%) in the Flut- group had a clinical AD diagnosis. There were significant differences in all CSF biomarkers in the Flut+ and Flut- groups. Aβ42 showed the highest correlation with 18F-Flutemetamol PET with a cut-off value of 706.5 pg/mL, corresponding to sensitivity of 88% and specificity of 87%. 18F-Flutemetamol PET was the best predictor of a clinical AD diagnosis. We found a very high interrater agreement for both PET classification and diagnosis.
The present study showed an excellent correlation of Aβ42 in CSF and 18F-Flutemetamol PET and the presented cut-off value for Aβ42 yields high sensitivity and specificity for 18F-Flutemetamol PET. 18F-Flutemetamol PET was the best predictor of clinical AD diagnosis. |
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| AbstractList | Alzheimer's disease (AD) remains a clinical diagnosis but biomarkers from cerebrospinal fluid (CSF) and more lately amyloid imaging with positron emission tomography (PET), are important to support a diagnosis of AD.BACKGROUNDAlzheimer's disease (AD) remains a clinical diagnosis but biomarkers from cerebrospinal fluid (CSF) and more lately amyloid imaging with positron emission tomography (PET), are important to support a diagnosis of AD.To compare amyloid-β (Aβ) PET imaging with biomarkers in CSF and evaluate the prediction of Aβ PET on diagnosis in a memory clinic setting.OBJECTIVETo compare amyloid-β (Aβ) PET imaging with biomarkers in CSF and evaluate the prediction of Aβ PET on diagnosis in a memory clinic setting.We included 64 patients who had lumbar puncture and Aβ PET with 18F-Flutemetamol performed within 190 days. PET was binary classified (Flut+ or Flut-) and logistic regression analyses for correlation to each CSF biomarker; Aβ 42 (Aβ42), total tau (T-tau) and phosphorylated tau (P-tau), were performed. Cut-off values were assessed by receiver operating characteristic (ROC) curves. Logistic regression was performed for prediction of clinical AD diagnosis. We assessed the interrater agreement of PET classification as well as for diagnoses, which were made both with and without knowledge of PET results.METHODSWe included 64 patients who had lumbar puncture and Aβ PET with 18F-Flutemetamol performed within 190 days. PET was binary classified (Flut+ or Flut-) and logistic regression analyses for correlation to each CSF biomarker; Aβ 42 (Aβ42), total tau (T-tau) and phosphorylated tau (P-tau), were performed. Cut-off values were assessed by receiver operating characteristic (ROC) curves. Logistic regression was performed for prediction of clinical AD diagnosis. We assessed the interrater agreement of PET classification as well as for diagnoses, which were made both with and without knowledge of PET results.Thirty-two of the 34 patients (94%) in the Flut+ group and nine of the 30 patients (30%) in the Flut- group had a clinical AD diagnosis. There were significant differences in all CSF biomarkers in the Flut+ and Flut- groups. Aβ42 showed the highest correlation with 18F-Flutemetamol PET with a cut-off value of 706.5 pg/mL, corresponding to sensitivity of 88% and specificity of 87%. 18F-Flutemetamol PET was the best predictor of a clinical AD diagnosis. We found a very high interrater agreement for both PET classification and diagnosis.RESULTSThirty-two of the 34 patients (94%) in the Flut+ group and nine of the 30 patients (30%) in the Flut- group had a clinical AD diagnosis. There were significant differences in all CSF biomarkers in the Flut+ and Flut- groups. Aβ42 showed the highest correlation with 18F-Flutemetamol PET with a cut-off value of 706.5 pg/mL, corresponding to sensitivity of 88% and specificity of 87%. 18F-Flutemetamol PET was the best predictor of a clinical AD diagnosis. We found a very high interrater agreement for both PET classification and diagnosis.The present study showed an excellent correlation of Aβ42 in CSF and 18F-Flutemetamol PET and the presented cut-off value for Aβ42 yields high sensitivity and specificity for 18F-Flutemetamol PET. 18F-Flutemetamol PET was the best predictor of clinical AD diagnosis.CONCLUSIONSThe present study showed an excellent correlation of Aβ42 in CSF and 18F-Flutemetamol PET and the presented cut-off value for Aβ42 yields high sensitivity and specificity for 18F-Flutemetamol PET. 18F-Flutemetamol PET was the best predictor of clinical AD diagnosis. BackgroundAlzheimer's disease (AD) remains a clinical diagnosis but biomarkers from cerebrospinal fluid (CSF) and more lately amyloid imaging with positron emission tomography (PET), are important to support a diagnosis of AD.ObjectiveTo compare amyloid-β (Aβ) PET imaging with biomarkers in CSF and evaluate the prediction of Aβ PET on diagnosis in a memory clinic setting.MethodsWe included 64 patients who had lumbar puncture and Aβ PET with 18F-Flutemetamol performed within 190 days. PET was binary classified (Flut+ or Flut-) and logistic regression analyses for correlation to each CSF biomarker; Aβ 42 (Aβ42), total tau (T-tau) and phosphorylated tau (P-tau), were performed. Cut-off values were assessed by receiver operating characteristic (ROC) curves. Logistic regression was performed for prediction of clinical AD diagnosis. We assessed the interrater agreement of PET classification as well as for diagnoses, which were made both with and without knowledge of PET results.ResultsThirty-two of the 34 patients (94%) in the Flut+ group and nine of the 30 patients (30%) in the Flut- group had a clinical AD diagnosis. There were significant differences in all CSF biomarkers in the Flut+ and Flut- groups. Aβ42 showed the highest correlation with 18F-Flutemetamol PET with a cut-off value of 706.5 pg/mL, corresponding to sensitivity of 88% and specificity of 87%. 18F-Flutemetamol PET was the best predictor of a clinical AD diagnosis. We found a very high interrater agreement for both PET classification and diagnosis.ConclusionsThe present study showed an excellent correlation of Aβ42 in CSF and 18F-Flutemetamol PET and the presented cut-off value for Aβ42 yields high sensitivity and specificity for 18F-Flutemetamol PET. 18F-Flutemetamol PET was the best predictor of clinical AD diagnosis. Background Alzheimer’s disease (AD) remains a clinical diagnosis but biomarkers from cerebrospinal fluid (CSF) and more lately amyloid imaging with positron emission tomography (PET), are important to support a diagnosis of AD. Objective To compare amyloid-β (Aβ) PET imaging with biomarkers in CSF and evaluate the prediction of Aβ PET on diagnosis in a memory clinic setting. Methods We included 64 patients who had lumbar puncture and Aβ PET with 18F-Flutemetamol performed within 190 days. PET was binary classified (Flut+ or Flut-) and logistic regression analyses for correlation to each CSF biomarker; Aβ 42 (Aβ42), total tau (T-tau) and phosphorylated tau (P-tau), were performed. Cut-off values were assessed by receiver operating characteristic (ROC) curves. Logistic regression was performed for prediction of clinical AD diagnosis. We assessed the interrater agreement of PET classification as well as for diagnoses, which were made both with and without knowledge of PET results. Results Thirty-two of the 34 patients (94%) in the Flut+ group and nine of the 30 patients (30%) in the Flut- group had a clinical AD diagnosis. There were significant differences in all CSF biomarkers in the Flut+ and Flut- groups. Aβ42 showed the highest correlation with 18F-Flutemetamol PET with a cut-off value of 706.5 pg/mL, corresponding to sensitivity of 88% and specificity of 87%. 18F-Flutemetamol PET was the best predictor of a clinical AD diagnosis. We found a very high interrater agreement for both PET classification and diagnosis. Conclusions The present study showed an excellent correlation of Aβ42 in CSF and 18F-Flutemetamol PET and the presented cut-off value for Aβ42 yields high sensitivity and specificity for 18F-Flutemetamol PET. 18F-Flutemetamol PET was the best predictor of clinical AD diagnosis. Background Alzheimer’s disease (AD) remains a clinical diagnosis but biomarkers from cerebrospinal fluid (CSF) and more lately amyloid imaging with positron emission tomography (PET), are important to support a diagnosis of AD. Objective To compare amyloid-β (Aβ) PET imaging with biomarkers in CSF and evaluate the prediction of Aβ PET on diagnosis in a memory clinic setting. Methods We included 64 patients who had lumbar puncture and Aβ PET with 18F-Flutemetamol performed within 190 days. PET was binary classified (Flut+ or Flut-) and logistic regression analyses for correlation to each CSF biomarker; Aβ 42 (Aβ42), total tau (T-tau) and phosphorylated tau (P-tau), were performed. Cut-off values were assessed by receiver operating characteristic (ROC) curves. Logistic regression was performed for prediction of clinical AD diagnosis. We assessed the interrater agreement of PET classification as well as for diagnoses, which were made both with and without knowledge of PET results. Results Thirty-two of the 34 patients (94%) in the Flut+ group and nine of the 30 patients (30%) in the Flut- group had a clinical AD diagnosis. There were significant differences in all CSF biomarkers in the Flut+ and Flut- groups. Aβ42 showed the highest correlation with 18F-Flutemetamol PET with a cut-off value of 706.5 pg/mL, corresponding to sensitivity of 88% and specificity of 87%. 18F-Flutemetamol PET was the best predictor of a clinical AD diagnosis. We found a very high interrater agreement for both PET classification and diagnosis. Conclusions The present study showed an excellent correlation of Aβ42 in CSF and 18F-Flutemetamol PET and the presented cut-off value for Aβ42 yields high sensitivity and specificity for 18F-Flutemetamol PET. 18F-Flutemetamol PET was the best predictor of clinical AD diagnosis. Alzheimer's disease (AD) remains a clinical diagnosis but biomarkers from cerebrospinal fluid (CSF) and more lately amyloid imaging with positron emission tomography (PET), are important to support a diagnosis of AD. To compare amyloid-β (Aβ) PET imaging with biomarkers in CSF and evaluate the prediction of Aβ PET on diagnosis in a memory clinic setting. We included 64 patients who had lumbar puncture and Aβ PET with 18F-Flutemetamol performed within 190 days. PET was binary classified (Flut+ or Flut-) and logistic regression analyses for correlation to each CSF biomarker; Aβ 42 (Aβ42), total tau (T-tau) and phosphorylated tau (P-tau), were performed. Cut-off values were assessed by receiver operating characteristic (ROC) curves. Logistic regression was performed for prediction of clinical AD diagnosis. We assessed the interrater agreement of PET classification as well as for diagnoses, which were made both with and without knowledge of PET results. Thirty-two of the 34 patients (94%) in the Flut+ group and nine of the 30 patients (30%) in the Flut- group had a clinical AD diagnosis. There were significant differences in all CSF biomarkers in the Flut+ and Flut- groups. Aβ42 showed the highest correlation with 18F-Flutemetamol PET with a cut-off value of 706.5 pg/mL, corresponding to sensitivity of 88% and specificity of 87%. 18F-Flutemetamol PET was the best predictor of a clinical AD diagnosis. We found a very high interrater agreement for both PET classification and diagnosis. The present study showed an excellent correlation of Aβ42 in CSF and 18F-Flutemetamol PET and the presented cut-off value for Aβ42 yields high sensitivity and specificity for 18F-Flutemetamol PET. 18F-Flutemetamol PET was the best predictor of clinical AD diagnosis. |
| Author | Müller, Ebba Gløersen Edwin, Trine Holt Stokke, Caroline Babovic, Almira Knapskog, Anne Brita Navelsaker, Sigrid Stensby Revheim, Mona Elisabeth Bogdanovic, Nenad |
| AuthorAffiliation | 4 Department of Diagnostic Physics, Oslo University Hospital, Oslo, Norway 1 Department of Nuclear Medicine, Oslo University Hospital, Oslo, Norway 5 Department of Life Science and Health, Oslo Metropolitan University, Oslo, Norway Nathan S Kline Institute, UNITED STATES 3 Department of Geriatric Medicine, The Memory Clinic, Oslo University Hospital, Oslo, Norway 6 Department for Neurobiology, Caring Science and Society, Division of Clinical Geriatrics, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden 2 Institute of Clinical Medicine, University of Oslo, Oslo, Norway |
| AuthorAffiliation_xml | – name: 2 Institute of Clinical Medicine, University of Oslo, Oslo, Norway – name: 6 Department for Neurobiology, Caring Science and Society, Division of Clinical Geriatrics, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden – name: 3 Department of Geriatric Medicine, The Memory Clinic, Oslo University Hospital, Oslo, Norway – name: 4 Department of Diagnostic Physics, Oslo University Hospital, Oslo, Norway – name: Nathan S Kline Institute, UNITED STATES – name: 1 Department of Nuclear Medicine, Oslo University Hospital, Oslo, Norway – name: 5 Department of Life Science and Health, Oslo Metropolitan University, Oslo, Norway |
| Author_xml | – sequence: 1 givenname: Ebba Gløersen orcidid: 0000-0003-3964-6055 surname: Müller fullname: Müller, Ebba Gløersen – sequence: 2 givenname: Trine Holt surname: Edwin fullname: Edwin, Trine Holt – sequence: 3 givenname: Caroline orcidid: 0000-0003-4465-9635 surname: Stokke fullname: Stokke, Caroline – sequence: 4 givenname: Sigrid Stensby surname: Navelsaker fullname: Navelsaker, Sigrid Stensby – sequence: 5 givenname: Almira surname: Babovic fullname: Babovic, Almira – sequence: 6 givenname: Nenad surname: Bogdanovic fullname: Bogdanovic, Nenad – sequence: 7 givenname: Anne Brita orcidid: 0000-0003-4867-551X surname: Knapskog fullname: Knapskog, Anne Brita – sequence: 8 givenname: Mona Elisabeth surname: Revheim fullname: Revheim, Mona Elisabeth |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31430334$$D View this record in MEDLINE/PubMed |
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| Copyright | 2019 Müller et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. info:eu-repo/semantics/openAccess 2019 Müller et al 2019 Müller et al |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 ObjectType-Undefined-3 Competing Interests: I have read the journal´s policy and the authors of this manuscript have the following competing interests: ABK is the principal investigator of, and THE is a rater, in two drug trials (ROCHE BN29553 and Boehringer-Ingelheim 1346-0023) conducted at the memory clinic, Oslo University Hospital. |
| ORCID | 0000-0003-4465-9635 0000-0003-3964-6055 0000-0003-4867-551X |
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| Snippet | Alzheimer's disease (AD) remains a clinical diagnosis but biomarkers from cerebrospinal fluid (CSF) and more lately amyloid imaging with positron emission... Background Alzheimer’s disease (AD) remains a clinical diagnosis but biomarkers from cerebrospinal fluid (CSF) and more lately amyloid imaging with positron... Background Alzheimer’s disease (AD) remains a clinical diagnosis but biomarkers from cerebrospinal fluid (CSF) and more lately amyloid imaging with positron... BackgroundAlzheimer's disease (AD) remains a clinical diagnosis but biomarkers from cerebrospinal fluid (CSF) and more lately amyloid imaging with positron... |
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| SubjectTerms | Aged Alzheimer Disease - cerebrospinal fluid Alzheimer Disease - diagnosis Alzheimer's disease Amyloid Amyloid beta-Peptides - cerebrospinal fluid Aniline Compounds - administration & dosage Benzothiazoles - administration & dosage Bioindicators Biology and Life Sciences Biomarkers Biomarkers - cerebrospinal fluid Brain - diagnostic imaging Brain research Cerebrospinal fluid Classification Clinical medicine Consent Correlation Correlation analysis Cross-Sectional Studies Dementia Diagnosis Drug dosages Female Fluorine isotopes Geriatrics Hospitals Humans Imaging, Three-Dimensional - methods Male Medical diagnosis Medical imaging Medicine and Health Sciences Memory Mental Health Services Mental Status and Dementia Tests Middle Aged Neurology Neuropathology Neurosciences NMR Nuclear magnetic resonance Nuclear medicine Patients People and Places Peptide Fragments - cerebrospinal fluid Physical Sciences Positron emission Positron emission tomography Positron-Emission Tomography - methods Radiopharmaceuticals - administration & dosage Regression analysis Research and Analysis Methods Sensitivity Tau protein Tomography Values |
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| Title | Amyloid-β PET—Correlation with cerebrospinal fluid biomarkers and prediction of Alzheimer´s disease diagnosis in a memory clinic |
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