{"doi":"10.1016/j.ejrad.2025.112351","title":"Contrast-Enhanced Mammography: Bridging the research gaps and defining the future","abstract":null,"journal":"European Journal of Radiology","year":2025,"id":642252,"datarank":0.3453877639491069,"base_score":2.302585092994046,"endowment":2.302585092994046,"self_citation_contribution":0.3453877639491069,"citation_network_contribution":0.0,"self_endowment_contribution":0.3453877639491069,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":9,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1670349,"name":"Giuliana Moffa","orcid":"0000-0002-6595-1611","position":1,"is_corresponding":false},{"id":1670348,"name":"Federica Pediconi","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Contrast-Enhanced Mammography: Bridging the research gaps and defining the future","abstract":"Contrast-enhanced mammography (CEM) has emerged as a promising breast imaging technique offering morphological and functional information through the use of dual-energy mammography and intravenous iodinated contrast agents. Despite increasing clinical use, its implementation remains heterogeneous, and several technical and clinical questions stay unanswered. This review aims to highlight the major research gaps related to CEM technique, safety, interpretation, and clinical applications. We examined key areas requiring standardization, including acquisition protocols, contrast agent dosing, and interpretation of background parenchymal enhancement. Safety concerns regarding radiation exposure and contrast media reactions were addressed, along with a comparison between CEM and breast MRI in terms of diagnostic performance. New applications such as CEM-guided biopsies and supplemental screening in high-risk women were critically reviewed and the integration of artificial intelligence and radiomics into CEM interpretation was also considered and discussed. Finally, we briefly summarized the main ongoing multicenter trials investigating the clinical utility and implementation of CEM across different healthcare settings.","is_dataset_classified":null,"base_score":2.1972245773362196,"endowment":2.1972245773362196,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"40848522","pmcid":null,"openalex_id":"https://openalex.org/W4413042719","authors":[],"funders":[],"total_grants":0,"fwci":6.2073,"citation_percentile":0.97017319,"influential_citations":0,"citation_trend":[{"year":2025,"count":2},{"year":2026,"count":6}],"oa_status":"green","license":"cc-by-nc-nd","oa_locations":[{"url":"https://iris.uniroma1.it/bitstream/11573/1744615/1/EJR%20review%20CEM%202025.pdf","host_type":"repository"},{"url":"https://iris.uniroma1.it/bitstream/11573/1744615/1/EJR%20review%20CEM%202025.pdf","host_type":"GREEN"},{"url":"https://iris.uniroma1.it/bitstream/11573/1744615/1/EJR%20review%20CEM%202025.pdf","host_type":"repository"},{"url":"https://api.elsevier.com/content/article/PII:S0720048X25004371?httpAccept=text/xml","host_type":"publisher"},{"url":"https://api.elsevier.com/content/article/PII:S0720048X25004371?httpAccept=text/plain","host_type":"publisher"},{"url":"https://hdl.handle.net/11573/1744615","host_type":"repository"},{"url":"https://doi.org/10.1016/j.ejrad.2025.112351","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/40848522","host_type":"repository"}],"fields_of_study":["Digital Radiography and Breast Imaging","Radiomics and Machine Learning in Medical Imaging","AI in cancer detection","Medicine","Humans","Contrast Media","Mammography","Female","Breast Neoplasms","Forecasting","Radiographic Image Enhancement","Evidence Gaps"],"mesh_terms":["Evidence Gaps","Breast Neoplasms","Contrast Media","Female","Forecasting","Humans","Mammography","Radiographic Image Enhancement"],"keywords":["Medicine","Bridging (networking)","Mammography","Contrast (vision)","Medical physics","Radiology","Artificial intelligence","Internal medicine","Breast cancer","Standardization","Breast Imaging","Cem","Future","Iodinated Contrast Media","Research Gaps"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Climate action"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-07T22:07:13.424151Z","pmid":null,"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":[]}