European journal of nuclear medicine and molecular imaging · 2025
Comparing and combining TSPO-PET tracers in tauopathies.
СтатьяСравнительное исследованиеМногоцентровое исследованиеНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Crook Harry, Franzmeier Nicolai, Rahmouni Nesrine, Gnörich Johannes S, Fryer Tim D, Hong Young T, Roemer-Cassiano Sebastian N, Palleis Carla, Strauss Alexandra, Jones P Simon, Aigbirhio Franklin I, Hopewell Robert, Rauchmann Boris-Stephan, Massarweh Gassan, Perneczky Robert, Levin Johannes, Höglinger Günter U, Rowe James B, O'Brien John T, Rosa-Neto Pedro, Brendel Matthias, Malpetti Maura
Аннотация
PURPOSE: Neuroinflammation is a key pathological driver in neurodegenerative diseases, including Alzheimer's disease (AD) and Progressive Supranuclear Palsy (PSP). Positron emission tomography (PET) with tracers targeting the translocator protein (TSPO) enables the in vivo quantification of microgliosis. TSPO tracers have shown similar disease-specific patterns across cohorts. However, direct quantitative comparisons between commonly used TSPO-PET tracers in tauopathies have not been performed. Here, we apply a TSPO-PET standardization pipeline across clinically matched AD cohorts and PSP cohorts, to quantify, compare and combine multi-centre TSPO-PET data.
METHODS: Patients with PSP were scanned with either [11C]PK11195 or [18F]GE-180 at one of two centres, while patients with AD and control participants were scanned with either [11C]PK11195, [18F]GE-180 or [11C]PBR28 at one of three centres. A standardised pre-processing pipeline was implemented and participant standardised uptake volume ratio (SUVR) values were z-scored using tracer-specific control participant values. In a data-driven approach, dissimilarity analyses were employed to assess differences between tracers across clinically matched cohorts.
RESULTS: In PSP, dissimilarity analysis suggested that [11C]PK11195 and [18F]GE-180 binding patterns were comparable following standardisation. In AD, comparability across tracers was less robust, with [11C]PK11195 and [18F]GE-180 being most comparable, followed by [18F]GE-180 vs. [11C]PBR28, then by [11C]PK11195 vs. [11C]PBR28.
CONCLUSION: The pipeline was effective at harmonising TSPO-PET tracers and standardising the regional quantification of neuroinflammation in clinically matched cohorts of PSP, while the standardisation pipeline results were less robust across AD cohorts.
METHODS: Patients with PSP were scanned with either [11C]PK11195 or [18F]GE-180 at one of two centres, while patients with AD and control participants were scanned with either [11C]PK11195, [18F]GE-180 or [11C]PBR28 at one of three centres. A standardised pre-processing pipeline was implemented and participant standardised uptake volume ratio (SUVR) values were z-scored using tracer-specific control participant values. In a data-driven approach, dissimilarity analyses were employed to assess differences between tracers across clinically matched cohorts.
RESULTS: In PSP, dissimilarity analysis suggested that [11C]PK11195 and [18F]GE-180 binding patterns were comparable following standardisation. In AD, comparability across tracers was less robust, with [11C]PK11195 and [18F]GE-180 being most comparable, followed by [18F]GE-180 vs. [11C]PBR28, then by [11C]PK11195 vs. [11C]PBR28.
CONCLUSION: The pipeline was effective at harmonising TSPO-PET tracers and standardising the regional quantification of neuroinflammation in clinically matched cohorts of PSP, while the standardisation pipeline results were less robust across AD cohorts.