{"doi":"10.1007/s10334-024-01186-3","title":"Improved quantitative parameter estimation for prostate T2 relaxometry using convolutional neural networks","abstract":"Abstract Objective Quantitative parameter mapping conventionally relies on curve fitting techniques to estimate parameters from magnetic resonance image series. This study compares conventional curve fitting techniques to methods using neural networks (NN) for measuring T 2 in the prostate. Materials and methods Large physics-based synthetic datasets simulating T 2 mapping acquisitions were generated for training NNs and for quantitative performance comparisons. Four combinations of different NN architectures and training corpora were implemented and compared with four different curve fitting strategies. All methods were compared quantitatively using synthetic data with known ground truth, and further compared on in vivo test data, with and without noise augmentation, to evaluate feasibility and noise robustness. Results In the evaluation on synthetic data, a convolutional neural network (CNN), trained in a supervised fashion using synthetic data generated from naturalistic images, showed the highest overall accuracy and precision amongst the methods. On in vivo data, this best performing method produced low-noise T 2 maps and showed the least deterioration with increasing input noise levels. Discussion This study showed that a CNN, trained with synthetic data in a supervised manner, may provide superior T 2 estimation performance compared to conventional curve fitting, especially in low signal-to-noise regions.","journal":"Magnetic Resonance Materials in Physics Biology and Medicine","year":2024,"id":475206,"datarank":0.32261016659662084,"base_score":1.6094379124341003,"endowment":1.6094379124341003,"self_citation_contribution":0.24141568686511508,"citation_network_contribution":0.08119447973150576,"self_endowment_contribution":0.24141568686511508,"citer_contribution":0.08119447973150576,"corpus_percentile":47.23447048812563,"corpus_rank":6822,"citation_count":4,"citer_count":3,"citers_with_citation_signal":3,"citers_with_endowment":3,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.559,"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":45.8333,"fair_percentile":59.49250993579945,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":739757,"name":"Sara L. Saunders","orcid":"0000-0001-6961-3073","position":1,"is_corresponding":false},{"id":319867,"name":"Kendrick Kay","orcid":"0000-0001-6604-9155","position":2,"is_corresponding":false},{"id":337583,"name":"Mitchell E. Gross","orcid":"0000-0002-1691-921X","position":3,"is_corresponding":false},{"id":256600,"name":"Mehmet Akçakaya","orcid":"0000-0001-6400-7736","position":4,"is_corresponding":false},{"id":393368,"name":"Gregory J. Metzger","orcid":"0000-0002-3187-6529","position":5,"is_corresponding":false},{"id":295247,"name":"Patrick J. Bolan","orcid":"0000-0002-4194-3975","position":0,"is_corresponding":true}],"reference_count":61,"raw_metadata":null,"created_at":"2026-07-19T02:06:16.992586Z","pmid":"39042205","pmcid":"PMC11417079","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":61.1111,"fair_a":25.0,"fair_i":0.0,"fair_r":33.3333,"fair_zscore":0.4506,"fair_rationale":{"fair_score":45.83,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":61.11,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"All of the de-identified in vivo data used in this study are available in the Data Repository for the University of Minnesota, at https:// conservancy.umn.edu/handle/11299/243192 [58].","grounded":false,"rationale":"The paper gives a Handle (hdl.handle.net) URL for the dataset, which is a persistent identifier scheme. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (4/5 passes agreed)]","anchors":["RDA-F1-01D — FAIR Data Maturity Model: 'Data is identified by a persistent identifier' (priorit","RDA-F1-02D — FAIR Data Maturity Model: 'Data is identified by a globally unique identifier'","FsF-F1-02D — F-UJI/FAIRsFAIR: 'Data is assigned a persistent identifier'"],"scored":true,"signal":null},{"key":"f_repository_named","label":"Named repository","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"All of the de-identified in vivo data used in this study are available in the Data Repository for the University of Minnesota","grounded":true,"rationale":"The Data Repository for the University of Minnesota is a named repository (University of Minnesota Digital Conservancy). [majority verdict 'yes' (3/5 passes agreed)]","anchors":["RDA-F4-01M — FAIR Data Maturity Model: metadata is offered so it can be harvested and indexed (","NIH DMS Policy Element 4 (NOT-OD-21-014) — name the repository where data will be archived","NSTC Desirable Characteristics of Data Repositories (2022) — 'Long-Term Sustainability', 'Reten"],"scored":true,"signal":null},{"key":"f_data_availability_statement","label":"Data-availability statement","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"All of the de-identified in vivo data used in this study are available in the Data Repository for the University of Minnesota, at https:// conservancy.umn.edu/handle/11299/243192 [58]. 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[downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (3/5 passes agreed)]","anchors":["FsF-A1-01M — F-UJI: 'Metadata contains access level and access conditions of the data'","RDA-A1-01M — metadata contains information to enable the user to get access to the data","COAR Controlled Vocabularies — Access Rights v1.0 (open / embargoed / restricted / metadata-onl"],"scored":false,"signal":null},{"key":"a_controlled_access_for_sensitive","label":"Gatekeeper for sensitive data","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":"These 118 datasets were deidentified in compliance with University of Minnesota policy, published on the University’s public data repository, and used for all analyses herein.","grounded":true,"rationale":"The data are deidentified and publicly available; no gatekeeper is named.","anchors":["NIH Genomic Data Sharing Policy (NOT-OD-14-124) — controlled-access via a Data Access Committee","RDA-A1.2-01D — 'Data is accessible through an access protocol that supports authentication and ","NIH DMS Policy Element 5 (NOT-OD-21-014) — Access, Distribution, or Reuse Considerations (conse"],"scored":false,"signal":null},{"key":"a_timeline_retention","label":"Availability timing & retention","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No sentence states how long the data will remain available or gives a retention commitment.","anchors":["NIH DMS Plan Element 4 (NOT-OD-21-014) — Data Preservation, Access, and Associated Timelines","NSTC Desirable Characteristics (2022), Organizational Infrastructure: 'Retention Policy'","RDA-A2-01M — 'Metadata is guaranteed to remain available after data is no longer available'"],"scored":false,"signal":null}]},"I":{"name":"Interoperable","score":0.0,"criteria":[{"key":"i_open_nonproprietary_format","label":"Open file format","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"The paper does not name the file format of the released data.","anchors":["FsF-R1.3-02D — F-UJI: 'Data is available in a file format recommended by the target research co","RDA-R1.3-02D — data is expressed in a machine-understandable community standard","RDA-I1-01D — data uses a knowledge representation expressed in a standardised format"],"scored":true,"signal":null},{"key":"i_community_standard_vocabulary","label":"Community standard / vocabulary","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No community standard (checklist, ontology, or schema) is named for the data.","anchors":["RDA-R1.3-01M — 'Metadata complies with a community standard' (priority Essential)","RDA-R1.3-01D — 'Data complies with a community standard'","RDA-I2-01M — '(Meta)data use vocabularies that follow FAIR principles'"],"scored":false,"signal":null},{"key":"i_qualified_references","label":"Identifiers for the resources the data depend on","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No identifier for an external resource (source dataset, database, or reference genome) is provided; the paper only uses generic references. [majority verdict 'no' (4/5 passes agreed)]","anchors":["RDA-I3-01M — '(meta)data include references to other (meta)data'","RDA-I3-03M — 'metadata includes qualified references to other metadata'","FsF-I3-01M — F-UJI: 'Metadata includes links between the data and its related entities'"],"scored":false,"signal":null}]},"R":{"name":"Reusable","score":33.33,"criteria":[{"key":"r_reuse_license","label":"Reuse licence","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No licence is stated for the data; the CC BY 4.0 licence applies only to the article.","anchors":["RDA-R1.1-01M — 'Metadata includes information about the licence under which the data can be reu","RDA-R1.1-02M — 'Metadata refers to a standard reuse licence'","RDA-R1.1-03M — 'Metadata refers to a machine-understandable reuse licence'"],"scored":true,"signal":null},{"key":"r_provenance_methods","label":"Provenance of the data","kind":"llm","weight":1.0,"fraction":1.0,"verdict":"yes","evidence":"All prostate MR imaging was acquired on a Siemens 3 T Prisma scanner with surface and endorectal receive coils.","grounded":true,"rationale":"The paper names the specific instrument (Siemens 3T Prisma) and other equipment used for data production. [majority verdict 'yes' (4/5 passes agreed)]","anchors":["RDA-R1.2-01M — 'Metadata includes provenance information according to community- specific standa","FsF-R1.2-01M — F-UJI: 'Metadata includes provenance information about data creation or generati","W3C PROV-O (W3C Recommendation, 2013) — the entity/activity/agent model of provenance"],"scored":false,"signal":null},{"key":"r_documentation_codebook","label":"Documentation / codebook","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No documentation object (README, codebook, or schema) is said to accompany the data.","anchors":["RDA-R1-01M — '(Meta)data are richly described with a plurality of accurate and relevant attribu","FsF-R1-01MD — F-UJI: 'Metadata specifies the content of the data'","NIH DMS Policy Element 3 (NOT-OD-21-014) — Standards (documentation and metadata to accompany t"],"scored":false,"signal":null},{"key":"r_versioning","label":"Snapshot identified","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"Neither a version token nor a date is provided to identify the snapshot of the data. [majority verdict 'no' (4/5 passes agreed)]","anchors":["DataCite Metadata Schema 4.6 — the 'Version' property","RDA-R1.2-01M — provenance information (which version was used is provenance)","NSTC Desirable Characteristics of Data Repositories (2022) — 'Provenance', 'Retention Policy'"],"scored":true,"signal":null},{"key":"x_code_availability","label":"Analysis code available","kind":"llm","weight":1.0,"fraction":0.5,"verdict":"partial","evidence":"The source code for training neural networks, evaluating results, and generating the figures in this manuscript, along with the trained models, are available on Github at https:// github.com/ patbolan/ prost ate_ t2map.","grounded":false,"rationale":"The paper gives a machine-resolvable code repository URL (GitHub) for its own code. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (4/5 passes agreed)]","anchors":["NIH DMS Policy Element 2 (NOT-OD-21-014) — 'Related Tools, Software and/or Code'","FAIR4RS Principles v1.0 (Chue Hong et al., 2022; RDA/FORCE11/ReSA) — FAIR Principles for Resear","FORCE11 Software Citation Principles (Smith, Katz & Niemeyer, 2016, PeerJ CS 2:e86)"],"scored":true,"signal":null},{"key":"x_funding_attribution","label":"Funder and award number","kind":"llm","weight":0.5,"fraction":1.0,"verdict":"yes","evidence":"This work was funded by the US National Institutes of Health (NIH) under grants P41 EB027061, R01 CA241159, R01 EB029985, S10 OD017974-01, R01 HL153146, and R21 EB028369.","grounded":true,"rationale":"The paper provides specific grant numbers (e.g., P41 EB027061) for the funding.","anchors":["DataCite Metadata Schema 4.6 — 'FundingReference' property (funderName, funderIdentifier, award","Crossref Funder Registry — canonical funder identifiers for funding metadata","RDA-F2-01M — rich metadata provided to allow discovery (funding is part of the descriptive reco"],"scored":true,"signal":null}]}},"actions":[{"key":"r_reuse_license","dimension":"R","label":"Reuse licence","action":"Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No licence is stated for the data; the CC BY 4.0 licence applies only to the article.","gain":16.67,"priority":"essential","scored":true},{"key":"f_dataset_pid","dimension":"F","label":"Persistent identifier for the data","action":"Mint or cite a persistent identifier for the dataset — a repository DOI or an accession from a registered repository — and print it in the paper. 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[downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (4/5 passes agreed)]","gain":8.33,"priority":"essential","scored":true},{"key":"i_open_nonproprietary_format","dimension":"I","label":"Open file format","action":"Release the data in an open, community-standard format (CSV/TSV, JSON, HDF5, NetCDF, FASTQ, VCF, NIfTI…) instead of — or alongside — any proprietary or instrument-native format, and name the format in the paper. A dataset that needs a €2,000 licence to open is not reusable.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The paper does not name the file format of the released data.","gain":8.33,"priority":"important","scored":true},{"key":"f_dataset_cited","dimension":"F","label":"Dataset formally cited","action":"Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. 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A name is not a link: it cannot be resolved, versioned, or followed by a machine.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No identifier for an external resource (source dataset, database, or reference genome) is provided; the paper only uses generic references. [majority verdict 'no' (4/5 passes agreed)]","gain":0.0,"priority":"useful","scored":false},{"key":"a_timeline_retention","dimension":"A","label":"Availability timing & retention","action":"State when the data become available AND how long they will be retained — cite the repository's preservation policy. NIH DMS Element 4 asks for both; most papers give neither.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No sentence states how long the data will remain available or gives a retention commitment.","gain":0.0,"priority":"useful","scored":false}],"suggestions":["Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","Mint or cite a persistent identifier for the dataset — a repository DOI or an accession from a registered repository — and print it in the paper. A bare URL is not persistent: it is the single most common cause of a dead data link five years after publication.","Remove the precondition or justify it. Release the data at publication with no embargo, no registration wall, and no approval step — NIH's zero-embargo public- access rule (NOT-OD-25-101) has already made 'available at publication' the federal baseline for the article; the data should not lag behind it.","Release the data in an open, community-standard format (CSV/TSV, JSON, HDF5, NetCDF, FASTQ, VCF, NIfTI…) instead of — or alongside — any proprietary or instrument-native format, and name the format in the paper. A dataset that needs a €2,000 licence to open is not reusable.","Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit."],"model":"deepseek/deepseek-v4-flash","agent_version":"fair_agent_v8","fulltext_source":"unpaywall_pdf"},"fair_model":"deepseek/deepseek-v4-flash","fair_agent_version":"fair_agent_v8","fair_fulltext_source":"unpaywall_pdf","fair_has_llm":true,"fair_computed_at":"2026-07-20T13:10:21.186184Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}