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Software compatibility analysis for quantitative measures of [18F]flutemetamol amyloid PET burden in mild cognitive impairment

Pemberton, Hugh G. ; Buckley, Christopher ; Battle, Mark LU ; Bollack, Ariane ; Patel, Vrajesh ; Tomova, Petya ; Cooke, David ; Balhorn, Will ; Hegedorn, Katherine and Lilja, Johan LU , et al. (2023) In EJNMMI Research 13(1).
Abstract

Rationale: Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer’s disease pathogenesis. In clinical practice, trained readers will visually categorise positron emission tomography (PET) scans as either Aβ positive or negative. However, adjunct quantitative analysis is becoming more widely available, where regulatory approved software can currently generate metrics such as standardised uptake value ratios (SUVr) and individual Z-scores. Therefore, it is of direct value to the imaging community to assess the compatibility of commercially available software packages. In this collaborative project, the compatibility of amyloid PET quantification was investigated across four regulatory approved software... (More)

Rationale: Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer’s disease pathogenesis. In clinical practice, trained readers will visually categorise positron emission tomography (PET) scans as either Aβ positive or negative. However, adjunct quantitative analysis is becoming more widely available, where regulatory approved software can currently generate metrics such as standardised uptake value ratios (SUVr) and individual Z-scores. Therefore, it is of direct value to the imaging community to assess the compatibility of commercially available software packages. In this collaborative project, the compatibility of amyloid PET quantification was investigated across four regulatory approved software packages. In doing so, the intention is to increase visibility and understanding of clinically relevant quantitative methods. Methods: Composite SUVr using the pons as the reference region was generated from [18F]flutemetamol (GE Healthcare) PET in a retrospective cohort of 80 amnestic mild cognitive impairment (aMCI) patients (40 each male/female; mean age = 73 years, SD = 8.52). Based on previous autopsy validation work, an Aβ positivity threshold of ≥ 0.6 SUVrpons was applied. Quantitative results from MIM Software’s MIMneuro, Syntermed’s NeuroQ, Hermes Medical Solutions’ BRASS and GE Healthcare’s CortexID were analysed using intraclass correlation coefficient (ICC), percentage agreement around the Aβ positivity threshold and kappa scores. Results: Using an Aβ positivity threshold of ≥ 0.6 SUVrpons, 95% agreement was achieved across the four software packages. Two patients were narrowly classed as Aβ negative by one software package but positive by the others, and two patients vice versa. All kappa scores around the same Aβ positivity threshold, both combined (Fleiss’) and individual software pairings (Cohen’s), were ≥ 0.9 signifying “almost perfect” inter-rater reliability. Excellent reliability was found between composite SUVr measurements for all four software packages, with an average measure ICC of 0.97 and 95% confidence interval of 0.957–0.979. Correlation coefficient analysis between the two software packages reporting composite z-scores was strong (r 2 = 0.98). Conclusion: Using an optimised cortical mask, regulatory approved software packages provided highly correlated and reliable quantification of [18F]flutemetamol amyloid PET with a ≥ 0.6 SUVrpons positivity threshold. In particular, this work could be of interest to physicians performing routine clinical imaging rather than researchers performing more bespoke image analysis. Similar analysis is encouraged using other reference regions as well as the Centiloid scale, when it has been implemented by more software packages.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Alzheimer’s, Amyloid PET, MCI, Quantification, SUVr, [F]flutemetamol
in
EJNMMI Research
volume
13
issue
1
article number
48
publisher
BioMed Central (BMC)
external identifiers
  • pmid:37225974
  • scopus:85160275672
ISSN
2191-219X
DOI
10.1186/s13550-023-00994-3
language
English
LU publication?
yes
id
ada592ff-d805-43a3-abd1-2e68e603cc2e
date added to LUP
2023-08-24 16:12:31
date last changed
2024-04-20 01:38:46
@article{ada592ff-d805-43a3-abd1-2e68e603cc2e,
  abstract     = {{<p>Rationale: Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer’s disease pathogenesis. In clinical practice, trained readers will visually categorise positron emission tomography (PET) scans as either Aβ positive or negative. However, adjunct quantitative analysis is becoming more widely available, where regulatory approved software can currently generate metrics such as standardised uptake value ratios (SUVr) and individual Z-scores. Therefore, it is of direct value to the imaging community to assess the compatibility of commercially available software packages. In this collaborative project, the compatibility of amyloid PET quantification was investigated across four regulatory approved software packages. In doing so, the intention is to increase visibility and understanding of clinically relevant quantitative methods. Methods: Composite SUVr using the pons as the reference region was generated from [<sup>18</sup>F]flutemetamol (GE Healthcare) PET in a retrospective cohort of 80 amnestic mild cognitive impairment (aMCI) patients (40 each male/female; mean age = 73 years, SD = 8.52). Based on previous autopsy validation work, an Aβ positivity threshold of ≥ 0.6 SUVr<sub>pons</sub> was applied. Quantitative results from MIM Software’s MIMneuro, Syntermed’s NeuroQ, Hermes Medical Solutions’ BRASS and GE Healthcare’s CortexID were analysed using intraclass correlation coefficient (ICC), percentage agreement around the Aβ positivity threshold and kappa scores. Results: Using an Aβ positivity threshold of ≥ 0.6 SUVr<sub>pons</sub>, 95% agreement was achieved across the four software packages. Two patients were narrowly classed as Aβ negative by one software package but positive by the others, and two patients vice versa. All kappa scores around the same Aβ positivity threshold, both combined (Fleiss’) and individual software pairings (Cohen’s), were ≥ 0.9 signifying “almost perfect” inter-rater reliability. Excellent reliability was found between composite SUVr measurements for all four software packages, with an average measure ICC of 0.97 and 95% confidence interval of 0.957–0.979. Correlation coefficient analysis between the two software packages reporting composite z-scores was strong (r <sup>2</sup> = 0.98). Conclusion: Using an optimised cortical mask, regulatory approved software packages provided highly correlated and reliable quantification of [<sup>18</sup>F]flutemetamol amyloid PET with a ≥ 0.6 SUVr<sub>pons</sub> positivity threshold. In particular, this work could be of interest to physicians performing routine clinical imaging rather than researchers performing more bespoke image analysis. Similar analysis is encouraged using other reference regions as well as the Centiloid scale, when it has been implemented by more software packages.</p>}},
  author       = {{Pemberton, Hugh G. and Buckley, Christopher and Battle, Mark and Bollack, Ariane and Patel, Vrajesh and Tomova, Petya and Cooke, David and Balhorn, Will and Hegedorn, Katherine and Lilja, Johan and Brand, Christine and Farrar, Gill}},
  issn         = {{2191-219X}},
  keywords     = {{Alzheimer’s; Amyloid PET; MCI; Quantification; SUVr; [F]flutemetamol}},
  language     = {{eng}},
  number       = {{1}},
  publisher    = {{BioMed Central (BMC)}},
  series       = {{EJNMMI Research}},
  title        = {{Software compatibility analysis for quantitative measures of [<sup>18</sup>F]flutemetamol amyloid PET burden in mild cognitive impairment}},
  url          = {{http://dx.doi.org/10.1186/s13550-023-00994-3}},
  doi          = {{10.1186/s13550-023-00994-3}},
  volume       = {{13}},
  year         = {{2023}},
}