| 1. |
- Botvinik-Nezer, Rotem, et al.
(författare)
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Variability in the analysis of a single neuroimaging dataset by many teams
- 2020
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 582, s. 84-88
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Tidskriftsartikel (refereegranskat)abstract
- Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses(1). The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset(2-5). Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed. The results obtained by seventy different teams analysing the same functional magnetic resonance imaging dataset show substantial variation, highlighting the influence of analytical choices and the importance of sharing workflows publicly and performing multiple analyses.
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| 2. |
- Juffermans, Joe F., et al.
(författare)
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Multicenter Consistency Assessment of Valvular Flow Quantification With Automated Valve Tracking in 4D Flow CMR
- 2021
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Ingår i: JACC: Cardiovascular Imaging. - : Elsevier BV. - 1936-878X. ; 14:7, s. 1354-1366
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: This study determined: 1) the interobserver agreement; 2) valvular flow variation; and 3) which variables independently predicted the variation of valvular flow quantification from 4-dimensional (4D) flow cardiac magnetic resonance (CMR) with automated retrospective valve tracking at multiple sites. Background: Automated retrospective valve tracking in 4D flow CMR allows consistent assessment of valvular flow through all intracardiac valves. However, due to the variance of CMR scanners and protocols, it remains uncertain if the published consistency holds for other clinical centers. Methods: Seven sites each retrospectively or prospectively selected 20 subjects who underwent whole heart 4D flow CMR (64 patients and 76 healthy volunteers; aged 32 years [range 24 to 48 years], 47% men, from 2014 to 2020), which was acquired with locally used CMR scanners (scanners from 3 vendors; 2 1.5-T and 5 3-T scanners) and protocols. Automated retrospective valve tracking was locally performed at each site to quantify the valvular flow and repeated by 1 central site. Interobserver agreement was evaluated with intraclass correlation coefficients (ICCs). Net forward volume (NFV) consistency among the valves was evaluated by calculating the intervalvular variation. Multiple regression analysis was performed to assess the predicting effect of local CMR scanners and protocols on the intervalvular inconsistency. Results: The interobserver analysis demonstrated strong-to-excellent agreement for NFV (ICC: 0.85 to 0.96) and moderate-to-excellent agreement for regurgitation fraction (ICC: 0.53 to 0.97) for all sites and valves. In addition, all observers established a low intervalvular variation (≤10.5%) in their analysis. The availability of 2 cine images per valve for valve tracking compared with 1 cine image predicted a decreasing variation in NFV among the 4 valves (beta = −1.3; p = 0.01). Conclusions: Independently of locally used CMR scanners and protocols, valvular flow quantification can be performed consistently with automated retrospective valve tracking in 4D flow CMR.
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