Predicting amyloid-PET status in a memory clinic: The role of the novel antero-posterior index and visual rating scales

Visual rating scales are increasingly utilized in clinical practice to assess atrophy in crucial brain regions among patients with cognitive disorders. However, their capacity to predict Alzheimer's disease (AD)-related pathology remains unexplored, particularly within a heterogeneous memory cl...

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Veröffentlicht in:Journal of the neurological sciences 2023-12, Vol.455, p.122806-122806, Article 122806
Hauptverfasser: Zilioli, Alessandro, Misirocchi, Francesco, Pancaldi, Beatrice, Mutti, Carlotta, Ganazzoli, Chiara, Morelli, Nicola, Pellegrini, Francesca Ferrari, Messa, Giovanni, Scarlattei, Maura, Mohanty, Rosaleena, Ruffini, Livia, Westman, Eric, Spallazzi, Marco
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Sprache:eng
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Zusammenfassung:Visual rating scales are increasingly utilized in clinical practice to assess atrophy in crucial brain regions among patients with cognitive disorders. However, their capacity to predict Alzheimer's disease (AD)-related pathology remains unexplored, particularly within a heterogeneous memory clinic population. This study aims to assess the accuracy of a novel visual rating assessment, the antero-posterior index (API) scale, in predicting amyloid-PET status. Furthermore, the study seeks to determine the optimal cohort-based cutoffs for the medial temporal atrophy (MTA) and parietal atrophy (PA) scales and to integrate the main visual rating scores into a predictive model. We conducted a retrospective analysis of brain MRI and high-resolution TC scans from 153 patients with cognitive disorders who had undergone amyloid-PET assessments due to suspected AD pathology in a real-world memory clinic setting. The API scale (cutoff ≥1) exhibited the highest accuracy (AUC = 0.721) among the visual rating scales. The combination of the cohort-based MTA and PA threshold with the API yielded favorable accuracy (AUC = 0.787). Analyzing a cohort of MCI/Mild dementia patients below 75 years of age, the API scale and the predictive model improved their accuracy (AUC = 0.741 and 0.813, respectively), achieving excellent results in the early-onset population (AUC = 0.857 and 0.949, respectively). Our study emphasizes the significance of visual rating scales in predicting amyloid-PET positivity within a real-world memory clinic. Implementing the novel API scale, alongside our cohort-based MTA and PA thresholds, has the potential to substantially enhance diagnostic accuracy.
ISSN:0022-510X
1878-5883
1878-5883
DOI:10.1016/j.jns.2023.122806