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

EJNMMI Research

Original Research

Ariane Bollack¹  Christine Brand²  Vrajesh Patel²  Petya Tomova²  Christopher Buckley²  Gill Farrar²  Hugh G. Pemberton³  Mark Battle⁴  Johan Lilja⁵  Katherine Hegedorn⁶  Will Balhorn⁶  David Cooke⁷ 

[1] Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK;GE Healthcare, Pollards Wood, Chalfont St Giles, HP8 4SP, Amersham, UK;GE Healthcare, Pollards Wood, Chalfont St Giles, HP8 4SP, Amersham, UK;Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK;UCL Queen Square Institute of Neurology, University College London, London, UK;GE Healthcare, Pollards Wood, Chalfont St Giles, HP8 4SP, Amersham, UK;Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden;HERMES Medical Solutions, Stockholm, Sweden;MIM Software, Cleveland, OH, USA;Syntermed, Atlanta, GA, USA;

关键词: Amyloid PET;    SUVr;    Alzheimer’s;    MCI;    Quantification;    [F]flutemetamol;   

DOI  :  10.1186/s13550-023-00994-3

 received in 2022-09-26, accepted in 2023-05-05,  发布年份 2023

来源: Springer

【 摘 要 】

RationaleAmyloid-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.MethodsComposite 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.ResultsUsing 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 (r2 = 0.98).ConclusionUsing 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.

【 授权许可】

CC BY   
© The Author(s) 2023

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