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A Pipeline for ADNI Resting-State Functional MRI Processing and Quality Control
Rutherford S, Zahid Z, Welsh RC, Avena-Koenigsberger A, Hammers DB, Koppelmans V, Mejia AF, Initiative ADN.. Research Square, 2026-10-06
Topic: Brain imaging, connectivity and assessment
The Alzheimer’s Disease Neuroimaging Initiative (ADNI) provides a comprehensive multimodal neuroimaging resource for studying aging and Alzheimer’s disease (AD). However, its resting-state functional MRI (rs-fMRI) data remain underutilized, in part due to challenges with data processing driven by considerable variability in acquisition protocols, inconsistent organization, missing or incomplete imaging sessions, and frequency of data quality issues due to participant motion and aging-related factors. To facilitate widespread use of ADNI rs-fMRI data, we developed an open-source pipeline encompassing the download and organization of imaging and clinical data, conversion to Brain Imaging Data Structure (BIDS), preprocessing with fMRIPrep, and automated quality control (QC). Our QC considers acquisition parameters and 16 structural and functional MRIQC image-quality metrics, flagging scans that fall outside acceptable ranges based on expert input and robust outlier detection techniques. Processed imaging sessions are matched to temporally aligned clinical assessments to produce an analysis-ready dataset. Applying the pipeline to more than 2,800 sessions from ADNI GO, ADNI 2, and ADNI 3 yielded 2,086 quality-checked functional and structural MRI sessions from 935 unique participants. Exclusions occurred at every processing stage and were driven primarily by BIDS conversion errors, image quality flags, and preprocessing- or motion-related failures. The open-source pipeline described in this work produces one of the largest pre-processed, quality controlled, and analysis-ready functional and structural MRI datasets yet available for studying aging and AD. It lowers barriers to large-cohort and longitudinal neuroimaging research and supports large-scale neuroimaging biomarker discovery in AD.
Key findings
- Processed imaging sessions are matched to temporally aligned clinical assessments to produce an analysis-ready dataset.
- Applying the pipeline to more than 2,800 sessions from ADNI GO, ADNI 2, and ADNI 3 yielded 2,086 quality-checked functional and structural MRI sessions from 935 unique participants.
- Exclusions occurred at every processing stage and were driven primarily by BIDS conversion errors, image quality flags, and preprocessing- or motion-related failures.
- The open-source pipeline described in this work produces one of the largest pre-processed, quality controlled, and analysis-ready functional and structural MRI datasets yet available for studying aging and AD.
- It lowers barriers to large-cohort and longitudinal neuroimaging research and supports large-scale neuroimaging biomarker discovery in AD.
Study details
- Study designlongitudinal study
- Evidence strengthModerate
How this study scored 16/100
Preprint — not yet peer-reviewed. It scored 35 on the same rubric, but non-peer-reviewed sources are capped at 16, so it shows as 16. Scored zero for sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 22 of the 62 points we could judge it on, which is 35 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 2 / 10 | Tier 4 — not a peer-reviewed journal (Research Square) |
| Journal's citation record | 0 / 4 | Not a journal article, so the journal's record does not count |
| Study design | 7 / 12 | A longitudinal study following the same people over time |
| Strength of evidence | 3 / 5 | Rated “moderate” in our summary |
| Peer-review validation | 4 / 10 | Preprint — not yet peer-reviewed. Hosted on a preprint server. |
| How recent | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 22 / 62 | Scored on 12 of 20 parts. We have no data for the rest, so they are left out: 22 of the 62 points we could judge it on is 35 out of 100. |
| Total | 35 / 100 | Capped to 16 because this is not a peer-reviewed article. |
What each of these 20 components measures, and what this score is not →
Read the original
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record names 8 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
APA 7th
Rutherford, S., Zahid, Z., Welsh, R. C., Avena-Koenigsberger, A., Hammers, D. B., Koppelmans, V., et al. (2026). A Pipeline for ADNI Resting-State Functional MRI Processing and Quality Control. Research Square. https://doi.org/10.21203/rs.3.rs-11132707/v1
Vancouver
Rutherford S, Zahid Z, Welsh RC, Avena-Koenigsberger A, Hammers DB, Koppelmans V, et al. A Pipeline for ADNI Resting-State Functional MRI Processing and Quality Control. Research Square. 2026. doi:10.21203/rs.3.rs-11132707/v1.
BibTeX
@article{rutherford2026-ae90252d,
author = {Rutherford, S. and Zahid, Z. and Welsh, R. C. and Avena-Koenigsberger, A. and Hammers, D. B. and Koppelmans, V. and Mejia, A. F. and {Initiative ADN}},
title = {{A Pipeline for ADNI Resting-State Functional MRI Processing and Quality Control}},
journal = {Research Square},
year = {2026},
doi = {10.21203/rs.3.rs-11132707/v1},
url = {https://doi.org/10.21203/rs.3.rs-11132707/v1}
}
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