{"doi":"10.7554/elife.61523","title":"An interactive meta-analysis of MRI biomarkers of myelin","abstract":"Several MRI measures have been proposed as in vivo biomarkers of myelin, each with applications ranging from plasticity to pathology. Despite the availability of these myelin-sensitive modalities, specificity and sensitivity have been a matter of discussion. Debate about which MRI measure is the most suitable for quantifying myelin is still ongoing. In this study, we performed a systematic review of published quantitative validation studies to clarify how different these measures are when compared to the underlying histology. We analyzed the results from 43 studies applying meta-analysis tools, controlling for study sample size and using interactive visualization (https://neurolibre.github.io/myelin-meta-analysis). We report the overall estimates and the prediction intervals for the coefficient of determination and find that MT and relaxometry-based measures exhibit the highest correlations with myelin content. We also show which measures are, and which measures are not statistically different regarding their relationship with histology.","journal":"eLife","year":2020,"id":50956,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":173,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9563,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":252385,"name":"Agâh Karakuzu","orcid":"0000-0001-7283-271X","position":1,"is_corresponding":false},{"id":252386,"name":"Julien Cohen‐Adad","orcid":"0000-0003-3662-9532","position":2,"is_corresponding":false},{"id":237631,"name":"Mara Cercignani","orcid":"0000-0002-4550-2456","position":3,"is_corresponding":false},{"id":44930,"name":"Thomas E. Nichols","orcid":"0000-0002-4516-5103","position":4,"is_corresponding":false},{"id":252387,"name":"Nikola Stikov","orcid":"0000-0002-8480-5230","position":5,"is_corresponding":false},{"id":252384,"name":"Matteo Mancini","orcid":"0000-0001-7194-4568","position":0,"is_corresponding":true}],"reference_count":92,"raw_metadata":null,"created_at":"2026-07-18T20:39:29.006085Z","pmid":"33084576","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}