Alzheimer’s disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using SSM/PCA

Background 2-Deoxy-2-[18F]fluoroglucose (FDG) PET is an important tool for the identification of Alzheimer’s disease (AD) patients through the characteristic neurodegeneration pattern that these patients present. Regional cerebral blood flow (rCBF) images derived from dynamic 11C-labelled Pittsburgh...
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Autor*in:	Peretti, Débora E. [verfasserIn] Vállez García, David Renken, Remco J. Reesink, Fransje E. Doorduin, Janine de Jong, Bauke M. De Deyn, Peter P. Dierckx, Rudi A. J. O. Boellaard, Ronald

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Alzheimer’s disease Disease pattern Relative cerebral blood flow SSM/PCA

Anmerkung:	© The Author(s) 2022

Übergeordnetes Werk:	Enthalten in: EJNMMI Research - Berlin : Springer, 2011, 12(2022), 1 vom: 23. Juni
Übergeordnetes Werk:	volume:12 ; year:2022 ; number:1 ; day:23 ; month:06

Links:	Volltext

DOI / URN:	10.1186/s13550-022-00909-8

Katalog-ID:	SPR047387092

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520			\|a Background 2-Deoxy-2-[18F]fluoroglucose (FDG) PET is an important tool for the identification of Alzheimer’s disease (AD) patients through the characteristic neurodegeneration pattern that these patients present. Regional cerebral blood flow (rCBF) images derived from dynamic 11C-labelled Pittsburgh Compound B (PIB) have been shown to present a similar pattern as FDG. Moreover, multivariate analysis techniques, such as scaled subprofile modelling using principal component analysis (SSM/PCA), can be used to generate disease-specific patterns (DP) that may aid in the classification of subjects. Therefore, the aim of this study was to compare rCBF AD-DPs with FDG AD-DP and their respective performances. Therefore, 52 subjects were included in this study. Fifteen AD and 16 healthy control subjects were used to generate four AD-DP: one based on relative cerebral trace blood (R1), two based on time-weighted average of initial frame intervals (ePIB), and one based on FDG images. Furthermore, 21 subjects diagnosed with mild cognitive impairment were tested against these AD-DPs. Results In general, the rCBF and FDG AD-DPs were characterized by a reduction in cortical frontal, temporal, and parietal lobes. FDG and rCBF methods presented similar score distribution. Conclusion rCBF images may provide an alternative for FDG PET scans for the identification of AD patients through SSM/PCA.
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allfields	10.1186/s13550-022-00909-8 doi (DE-627)SPR047387092 (SPR)s13550-022-00909-8-e DE-627 ger DE-627 rakwb eng Peretti, Débora E. verfasserin aut Alzheimer’s disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using SSM/PCA 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Background 2-Deoxy-2-[18F]fluoroglucose (FDG) PET is an important tool for the identification of Alzheimer’s disease (AD) patients through the characteristic neurodegeneration pattern that these patients present. Regional cerebral blood flow (rCBF) images derived from dynamic 11C-labelled Pittsburgh Compound B (PIB) have been shown to present a similar pattern as FDG. Moreover, multivariate analysis techniques, such as scaled subprofile modelling using principal component analysis (SSM/PCA), can be used to generate disease-specific patterns (DP) that may aid in the classification of subjects. Therefore, the aim of this study was to compare rCBF AD-DPs with FDG AD-DP and their respective performances. Therefore, 52 subjects were included in this study. Fifteen AD and 16 healthy control subjects were used to generate four AD-DP: one based on relative cerebral trace blood (R1), two based on time-weighted average of initial frame intervals (ePIB), and one based on FDG images. Furthermore, 21 subjects diagnosed with mild cognitive impairment were tested against these AD-DPs. Results In general, the rCBF and FDG AD-DPs were characterized by a reduction in cortical frontal, temporal, and parietal lobes. FDG and rCBF methods presented similar score distribution. Conclusion rCBF images may provide an alternative for FDG PET scans for the identification of AD patients through SSM/PCA. Alzheimer’s disease (dpeaa)DE-He213 Disease pattern (dpeaa)DE-He213 Relative cerebral blood flow (dpeaa)DE-He213 SSM/PCA (dpeaa)DE-He213 Vállez García, David aut Renken, Remco J. aut Reesink, Fransje E. aut Doorduin, Janine aut de Jong, Bauke M. aut De Deyn, Peter P. aut Dierckx, Rudi A. J. O. aut Boellaard, Ronald (orcid)0000-0002-0313-5686 aut Enthalten in EJNMMI Research Berlin : Springer, 2011 12(2022), 1 vom: 23. Juni (DE-627)664970265 (DE-600)2619892-7 2191-219X nnns volume:12 year:2022 number:1 day:23 month:06 https://dx.doi.org/10.1186/s13550-022-00909-8 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2022 1 23 06
spelling	10.1186/s13550-022-00909-8 doi (DE-627)SPR047387092 (SPR)s13550-022-00909-8-e DE-627 ger DE-627 rakwb eng Peretti, Débora E. verfasserin aut Alzheimer’s disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using SSM/PCA 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Background 2-Deoxy-2-[18F]fluoroglucose (FDG) PET is an important tool for the identification of Alzheimer’s disease (AD) patients through the characteristic neurodegeneration pattern that these patients present. Regional cerebral blood flow (rCBF) images derived from dynamic 11C-labelled Pittsburgh Compound B (PIB) have been shown to present a similar pattern as FDG. Moreover, multivariate analysis techniques, such as scaled subprofile modelling using principal component analysis (SSM/PCA), can be used to generate disease-specific patterns (DP) that may aid in the classification of subjects. Therefore, the aim of this study was to compare rCBF AD-DPs with FDG AD-DP and their respective performances. Therefore, 52 subjects were included in this study. Fifteen AD and 16 healthy control subjects were used to generate four AD-DP: one based on relative cerebral trace blood (R1), two based on time-weighted average of initial frame intervals (ePIB), and one based on FDG images. Furthermore, 21 subjects diagnosed with mild cognitive impairment were tested against these AD-DPs. Results In general, the rCBF and FDG AD-DPs were characterized by a reduction in cortical frontal, temporal, and parietal lobes. FDG and rCBF methods presented similar score distribution. Conclusion rCBF images may provide an alternative for FDG PET scans for the identification of AD patients through SSM/PCA. Alzheimer’s disease (dpeaa)DE-He213 Disease pattern (dpeaa)DE-He213 Relative cerebral blood flow (dpeaa)DE-He213 SSM/PCA (dpeaa)DE-He213 Vállez García, David aut Renken, Remco J. aut Reesink, Fransje E. aut Doorduin, Janine aut de Jong, Bauke M. aut De Deyn, Peter P. aut Dierckx, Rudi A. J. O. aut Boellaard, Ronald (orcid)0000-0002-0313-5686 aut Enthalten in EJNMMI Research Berlin : Springer, 2011 12(2022), 1 vom: 23. Juni (DE-627)664970265 (DE-600)2619892-7 2191-219X nnns volume:12 year:2022 number:1 day:23 month:06 https://dx.doi.org/10.1186/s13550-022-00909-8 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2022 1 23 06
allfields_unstemmed	10.1186/s13550-022-00909-8 doi (DE-627)SPR047387092 (SPR)s13550-022-00909-8-e DE-627 ger DE-627 rakwb eng Peretti, Débora E. verfasserin aut Alzheimer’s disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using SSM/PCA 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Background 2-Deoxy-2-[18F]fluoroglucose (FDG) PET is an important tool for the identification of Alzheimer’s disease (AD) patients through the characteristic neurodegeneration pattern that these patients present. Regional cerebral blood flow (rCBF) images derived from dynamic 11C-labelled Pittsburgh Compound B (PIB) have been shown to present a similar pattern as FDG. Moreover, multivariate analysis techniques, such as scaled subprofile modelling using principal component analysis (SSM/PCA), can be used to generate disease-specific patterns (DP) that may aid in the classification of subjects. Therefore, the aim of this study was to compare rCBF AD-DPs with FDG AD-DP and their respective performances. Therefore, 52 subjects were included in this study. Fifteen AD and 16 healthy control subjects were used to generate four AD-DP: one based on relative cerebral trace blood (R1), two based on time-weighted average of initial frame intervals (ePIB), and one based on FDG images. Furthermore, 21 subjects diagnosed with mild cognitive impairment were tested against these AD-DPs. Results In general, the rCBF and FDG AD-DPs were characterized by a reduction in cortical frontal, temporal, and parietal lobes. FDG and rCBF methods presented similar score distribution. Conclusion rCBF images may provide an alternative for FDG PET scans for the identification of AD patients through SSM/PCA. Alzheimer’s disease (dpeaa)DE-He213 Disease pattern (dpeaa)DE-He213 Relative cerebral blood flow (dpeaa)DE-He213 SSM/PCA (dpeaa)DE-He213 Vállez García, David aut Renken, Remco J. aut Reesink, Fransje E. aut Doorduin, Janine aut de Jong, Bauke M. aut De Deyn, Peter P. aut Dierckx, Rudi A. J. O. aut Boellaard, Ronald (orcid)0000-0002-0313-5686 aut Enthalten in EJNMMI Research Berlin : Springer, 2011 12(2022), 1 vom: 23. Juni (DE-627)664970265 (DE-600)2619892-7 2191-219X nnns volume:12 year:2022 number:1 day:23 month:06 https://dx.doi.org/10.1186/s13550-022-00909-8 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2022 1 23 06
allfieldsGer	10.1186/s13550-022-00909-8 doi (DE-627)SPR047387092 (SPR)s13550-022-00909-8-e DE-627 ger DE-627 rakwb eng Peretti, Débora E. verfasserin aut Alzheimer’s disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using SSM/PCA 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Background 2-Deoxy-2-[18F]fluoroglucose (FDG) PET is an important tool for the identification of Alzheimer’s disease (AD) patients through the characteristic neurodegeneration pattern that these patients present. Regional cerebral blood flow (rCBF) images derived from dynamic 11C-labelled Pittsburgh Compound B (PIB) have been shown to present a similar pattern as FDG. Moreover, multivariate analysis techniques, such as scaled subprofile modelling using principal component analysis (SSM/PCA), can be used to generate disease-specific patterns (DP) that may aid in the classification of subjects. Therefore, the aim of this study was to compare rCBF AD-DPs with FDG AD-DP and their respective performances. Therefore, 52 subjects were included in this study. Fifteen AD and 16 healthy control subjects were used to generate four AD-DP: one based on relative cerebral trace blood (R1), two based on time-weighted average of initial frame intervals (ePIB), and one based on FDG images. Furthermore, 21 subjects diagnosed with mild cognitive impairment were tested against these AD-DPs. Results In general, the rCBF and FDG AD-DPs were characterized by a reduction in cortical frontal, temporal, and parietal lobes. FDG and rCBF methods presented similar score distribution. Conclusion rCBF images may provide an alternative for FDG PET scans for the identification of AD patients through SSM/PCA. Alzheimer’s disease (dpeaa)DE-He213 Disease pattern (dpeaa)DE-He213 Relative cerebral blood flow (dpeaa)DE-He213 SSM/PCA (dpeaa)DE-He213 Vállez García, David aut Renken, Remco J. aut Reesink, Fransje E. aut Doorduin, Janine aut de Jong, Bauke M. aut De Deyn, Peter P. aut Dierckx, Rudi A. J. O. aut Boellaard, Ronald (orcid)0000-0002-0313-5686 aut Enthalten in EJNMMI Research Berlin : Springer, 2011 12(2022), 1 vom: 23. Juni (DE-627)664970265 (DE-600)2619892-7 2191-219X nnns volume:12 year:2022 number:1 day:23 month:06 https://dx.doi.org/10.1186/s13550-022-00909-8 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2022 1 23 06
allfieldsSound	10.1186/s13550-022-00909-8 doi (DE-627)SPR047387092 (SPR)s13550-022-00909-8-e DE-627 ger DE-627 rakwb eng Peretti, Débora E. verfasserin aut Alzheimer’s disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using SSM/PCA 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Background 2-Deoxy-2-[18F]fluoroglucose (FDG) PET is an important tool for the identification of Alzheimer’s disease (AD) patients through the characteristic neurodegeneration pattern that these patients present. Regional cerebral blood flow (rCBF) images derived from dynamic 11C-labelled Pittsburgh Compound B (PIB) have been shown to present a similar pattern as FDG. Moreover, multivariate analysis techniques, such as scaled subprofile modelling using principal component analysis (SSM/PCA), can be used to generate disease-specific patterns (DP) that may aid in the classification of subjects. Therefore, the aim of this study was to compare rCBF AD-DPs with FDG AD-DP and their respective performances. Therefore, 52 subjects were included in this study. Fifteen AD and 16 healthy control subjects were used to generate four AD-DP: one based on relative cerebral trace blood (R1), two based on time-weighted average of initial frame intervals (ePIB), and one based on FDG images. Furthermore, 21 subjects diagnosed with mild cognitive impairment were tested against these AD-DPs. Results In general, the rCBF and FDG AD-DPs were characterized by a reduction in cortical frontal, temporal, and parietal lobes. FDG and rCBF methods presented similar score distribution. Conclusion rCBF images may provide an alternative for FDG PET scans for the identification of AD patients through SSM/PCA. Alzheimer’s disease (dpeaa)DE-He213 Disease pattern (dpeaa)DE-He213 Relative cerebral blood flow (dpeaa)DE-He213 SSM/PCA (dpeaa)DE-He213 Vállez García, David aut Renken, Remco J. aut Reesink, Fransje E. aut Doorduin, Janine aut de Jong, Bauke M. aut De Deyn, Peter P. aut Dierckx, Rudi A. J. O. aut Boellaard, Ronald (orcid)0000-0002-0313-5686 aut Enthalten in EJNMMI Research Berlin : Springer, 2011 12(2022), 1 vom: 23. Juni (DE-627)664970265 (DE-600)2619892-7 2191-219X nnns volume:12 year:2022 number:1 day:23 month:06 https://dx.doi.org/10.1186/s13550-022-00909-8 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2022 1 23 06
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source	Enthalten in EJNMMI Research 12(2022), 1 vom: 23. Juni volume:12 year:2022 number:1 day:23 month:06
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topic_facet	Alzheimer’s disease Disease pattern Relative cerebral blood flow SSM/PCA
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authorswithroles_txt_mv	Peretti, Débora E. @@aut@@ Vállez García, David @@aut@@ Renken, Remco J. @@aut@@ Reesink, Fransje E. @@aut@@ Doorduin, Janine @@aut@@ de Jong, Bauke M. @@aut@@ De Deyn, Peter P. @@aut@@ Dierckx, Rudi A. J. O. @@aut@@ Boellaard, Ronald @@aut@@
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Regional cerebral blood flow (rCBF) images derived from dynamic 11C-labelled Pittsburgh Compound B (PIB) have been shown to present a similar pattern as FDG. Moreover, multivariate analysis techniques, such as scaled subprofile modelling using principal component analysis (SSM/PCA), can be used to generate disease-specific patterns (DP) that may aid in the classification of subjects. Therefore, the aim of this study was to compare rCBF AD-DPs with FDG AD-DP and their respective performances. Therefore, 52 subjects were included in this study. Fifteen AD and 16 healthy control subjects were used to generate four AD-DP: one based on relative cerebral trace blood (R1), two based on time-weighted average of initial frame intervals (ePIB), and one based on FDG images. Furthermore, 21 subjects diagnosed with mild cognitive impairment were tested against these AD-DPs. Results In general, the rCBF and FDG AD-DPs were characterized by a reduction in cortical frontal, temporal, and parietal lobes. FDG and rCBF methods presented similar score distribution. 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author	Peretti, Débora E.
spellingShingle	Peretti, Débora E. misc Alzheimer’s disease misc Disease pattern misc Relative cerebral blood flow misc SSM/PCA Alzheimer’s disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using SSM/PCA
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topic_title	Alzheimer’s disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using SSM/PCA Alzheimer’s disease (dpeaa)DE-He213 Disease pattern (dpeaa)DE-He213 Relative cerebral blood flow (dpeaa)DE-He213 SSM/PCA (dpeaa)DE-He213
topic	misc Alzheimer’s disease misc Disease pattern misc Relative cerebral blood flow misc SSM/PCA
topic_unstemmed	misc Alzheimer’s disease misc Disease pattern misc Relative cerebral blood flow misc SSM/PCA
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title	Alzheimer’s disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using SSM/PCA
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title_full	Alzheimer’s disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using SSM/PCA
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author_browse	Peretti, Débora E. Vállez García, David Renken, Remco J. Reesink, Fransje E. Doorduin, Janine de Jong, Bauke M. De Deyn, Peter P. Dierckx, Rudi A. J. O. Boellaard, Ronald
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title_sort	alzheimer’s disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using ssm/pca
title_auth	Alzheimer’s disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using SSM/PCA
abstract	Background 2-Deoxy-2-[18F]fluoroglucose (FDG) PET is an important tool for the identification of Alzheimer’s disease (AD) patients through the characteristic neurodegeneration pattern that these patients present. Regional cerebral blood flow (rCBF) images derived from dynamic 11C-labelled Pittsburgh Compound B (PIB) have been shown to present a similar pattern as FDG. Moreover, multivariate analysis techniques, such as scaled subprofile modelling using principal component analysis (SSM/PCA), can be used to generate disease-specific patterns (DP) that may aid in the classification of subjects. Therefore, the aim of this study was to compare rCBF AD-DPs with FDG AD-DP and their respective performances. Therefore, 52 subjects were included in this study. Fifteen AD and 16 healthy control subjects were used to generate four AD-DP: one based on relative cerebral trace blood (R1), two based on time-weighted average of initial frame intervals (ePIB), and one based on FDG images. Furthermore, 21 subjects diagnosed with mild cognitive impairment were tested against these AD-DPs. Results In general, the rCBF and FDG AD-DPs were characterized by a reduction in cortical frontal, temporal, and parietal lobes. FDG and rCBF methods presented similar score distribution. Conclusion rCBF images may provide an alternative for FDG PET scans for the identification of AD patients through SSM/PCA. © The Author(s) 2022
abstractGer	Background 2-Deoxy-2-[18F]fluoroglucose (FDG) PET is an important tool for the identification of Alzheimer’s disease (AD) patients through the characteristic neurodegeneration pattern that these patients present. Regional cerebral blood flow (rCBF) images derived from dynamic 11C-labelled Pittsburgh Compound B (PIB) have been shown to present a similar pattern as FDG. Moreover, multivariate analysis techniques, such as scaled subprofile modelling using principal component analysis (SSM/PCA), can be used to generate disease-specific patterns (DP) that may aid in the classification of subjects. Therefore, the aim of this study was to compare rCBF AD-DPs with FDG AD-DP and their respective performances. Therefore, 52 subjects were included in this study. Fifteen AD and 16 healthy control subjects were used to generate four AD-DP: one based on relative cerebral trace blood (R1), two based on time-weighted average of initial frame intervals (ePIB), and one based on FDG images. Furthermore, 21 subjects diagnosed with mild cognitive impairment were tested against these AD-DPs. Results In general, the rCBF and FDG AD-DPs were characterized by a reduction in cortical frontal, temporal, and parietal lobes. FDG and rCBF methods presented similar score distribution. Conclusion rCBF images may provide an alternative for FDG PET scans for the identification of AD patients through SSM/PCA. © The Author(s) 2022
abstract_unstemmed	Background 2-Deoxy-2-[18F]fluoroglucose (FDG) PET is an important tool for the identification of Alzheimer’s disease (AD) patients through the characteristic neurodegeneration pattern that these patients present. Regional cerebral blood flow (rCBF) images derived from dynamic 11C-labelled Pittsburgh Compound B (PIB) have been shown to present a similar pattern as FDG. Moreover, multivariate analysis techniques, such as scaled subprofile modelling using principal component analysis (SSM/PCA), can be used to generate disease-specific patterns (DP) that may aid in the classification of subjects. Therefore, the aim of this study was to compare rCBF AD-DPs with FDG AD-DP and their respective performances. Therefore, 52 subjects were included in this study. Fifteen AD and 16 healthy control subjects were used to generate four AD-DP: one based on relative cerebral trace blood (R1), two based on time-weighted average of initial frame intervals (ePIB), and one based on FDG images. Furthermore, 21 subjects diagnosed with mild cognitive impairment were tested against these AD-DPs. Results In general, the rCBF and FDG AD-DPs were characterized by a reduction in cortical frontal, temporal, and parietal lobes. FDG and rCBF methods presented similar score distribution. Conclusion rCBF images may provide an alternative for FDG PET scans for the identification of AD patients through SSM/PCA. © The Author(s) 2022
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title_short	Alzheimer’s disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using SSM/PCA
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author2	Vállez García, David Renken, Remco J. Reesink, Fransje E. Doorduin, Janine de Jong, Bauke M. De Deyn, Peter P. Dierckx, Rudi A. J. O. Boellaard, Ronald
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up_date	2024-07-04T02:57:31.156Z
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Regional cerebral blood flow (rCBF) images derived from dynamic 11C-labelled Pittsburgh Compound B (PIB) have been shown to present a similar pattern as FDG. Moreover, multivariate analysis techniques, such as scaled subprofile modelling using principal component analysis (SSM/PCA), can be used to generate disease-specific patterns (DP) that may aid in the classification of subjects. Therefore, the aim of this study was to compare rCBF AD-DPs with FDG AD-DP and their respective performances. Therefore, 52 subjects were included in this study. Fifteen AD and 16 healthy control subjects were used to generate four AD-DP: one based on relative cerebral trace blood (R1), two based on time-weighted average of initial frame intervals (ePIB), and one based on FDG images. Furthermore, 21 subjects diagnosed with mild cognitive impairment were tested against these AD-DPs. Results In general, the rCBF and FDG AD-DPs were characterized by a reduction in cortical frontal, temporal, and parietal lobes. FDG and rCBF methods presented similar score distribution. 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Alzheimer’s disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using SSM/PCA

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