Journal Article

FZJ-2020-01872

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Influence of Processing Pipeline on Cortical Thickness Measurement

Kharabian Masouleh, S. (Corresponding author)FZJ* ; Eickhoff, S. B.FZJ* ; Zeighami, Y. ; Lewis, L. B. ; Dahnke, R. ; Gaser, C. ; Chouinard-Decorte, F. ; Lepage, C. ; Scholtens, L. H. ; Hoffstaedter, F.FZJ* ; Glahn, D. C. ; Blangero, J. ; Evans, A. C. ; Genon, S.FZJ* ; Valk, S. L.FZJ*

2020
Oxford Univ. Press Oxford

This record in other databases:      

Please use a persistent id in citations: http://hdl.handle.net/2128/25679  doi:10.1093/cercor/bhaa097

Abstract: In recent years, replicability of neuroscientific findings, specifically those concerning correlates of morphological properties of gray matter (GM), have been subject of major scrutiny. Use of different processing pipelines and differences in their estimates of the macroscale GM may play an important role in this context. To address this issue, here, we investigated the cortical thickness estimates of three widely used pipelines. Based on analyses in two independent large-scale cohorts, we report high levels of within-pipeline reliability of the absolute cortical thickness-estimates and comparable spatial patterns of cortical thickness-estimates across all pipelines. Within each individual, absolute regional thickness differed between pipelines, indicating that in-vivo thickness measurements are only a proxy of actual thickness of the cortex, which shall only be compared within the same software package and thickness estimation technique. However, at group level, cortical thickness-estimates correlated strongly between pipelines, in most brain regions. The smallest between-pipeline correlations were observed in para-limbic areas and insula. These regions also demonstrated the highest interindividual variability and the lowest reliability of cortical thickness-estimates within each pipeline, suggesting that structural variations within these regions should be interpreted with caution.

Note: The Deutsche Forschungsgemeinschaft (DFG, GE 2835/1-1 and EI 816/4-1), the Helmholtz Portfolio Theme “Supercomputing and Modelling for the Human Brain,” and the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No. 720270 (HBP SGA1) and Grant Agreement No. 785907 (HBP SGA2).Notes

---

Contributing Institute(s):

1. Gehirn & Verhalten (INM-7)

Research Program(s):

1. 572 - (Dys-)function and Plasticity (POF3-572) (POF3-572)
2. SMHB - Supercomputing and Modelling for the Human Brain (HGF-SMHB-2013-2017) (HGF-SMHB-2013-2017)
3. HBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907) (785907)
4. HBP SGA1 - Human Brain Project Specific Grant Agreement 1 (720270) (720270)

Appears in the scientific report 2020

---

Database coverage:
; ; ; BIOSIS Previews ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; IF >= 5 ; JCR ; NCBI Molecular Biology Database ; Nationallizenz ; PubMed Central ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

---