{"doi":"10.1002/mrm.30029","title":"Novel pore size‐controlled, susceptibility matched, 3D‐printed MRI phantoms","abstract":"PURPOSE: We report the design concept and fabrication of MRI phantoms, containing blocks of aligned microcapillaires that can be stacked into larger arrays to construct diameter distribution phantoms or fractured, to create a \"powder-averaged\" emulsion of randomly oriented blocks for vetting or calibrating advanced MRI methods, that is, diffusion tensor imaging, AxCaliber MRI, MAP-MRI, and multiple pulsed field gradient or double diffusion-encoded microstructure imaging methods. The goal was to create a susceptibility-matched microscopically anisotropic but macroscopically isotropic phantom with a ground truth diameter that could be used to vet advanced diffusion methods for diameter determination in fibrous tissues. METHODS: Two-photon polymerization, a novel three-dimensional printing method is used to fabricate blocks of capillaries. Double diffusion encoding methods were employed and analyzed to estimate the expected MRI diameter. RESULTS: Susceptibility-matched microcapillary blocks or modules that can be assembled into large-scale MRI phantoms have been fabricated and measured using advanced diffusion methods, resulting in microscopic anisotropy and random orientation. CONCLUSION: This phantom can vet and calibrate various advanced MRI methods and multiple pulsed field gradient or diffusion-encoded microstructure imaging methods. We demonstrated that two double diffusion encoding methods underestimated the ground truth diameter.","journal":"Magnetic Resonance in Medicine","year":2024,"id":475430,"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":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9589,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":477875,"name":"Michal E. Komlosh","orcid":null,"position":1,"is_corresponding":false},{"id":309322,"name":"Dan Benjamini","orcid":"0000-0002-9558-7056","position":2,"is_corresponding":false},{"id":271620,"name":"Evren Özarslan","orcid":"0000-0003-0859-1311","position":3,"is_corresponding":false},{"id":655564,"name":"Nickolay V. Lavrik","orcid":"0000-0002-9543-5634","position":4,"is_corresponding":false},{"id":309323,"name":"Peter J. Basser","orcid":"0000-0003-4795-6088","position":5,"is_corresponding":false},{"id":997458,"name":"Velencia J. Witherspoon","orcid":"0000-0002-2718-6605","position":0,"is_corresponding":true}],"reference_count":46,"raw_metadata":null,"created_at":"2026-07-19T02:06:16.992586Z","pmid":"38368618","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":[]}