{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T22:43:15Z","timestamp":1784846595504,"version":"3.55.0"},"reference-count":58,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T00:00:00Z","timestamp":1767571200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Croatian Ministry of Science, Education and Youth","award":["IP-FDMZ-2025\/2026-01"],"award-info":[{"award-number":["IP-FDMZ-2025\/2026-01"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Medicina"],"abstract":"<jats:p>Background and Objectives: Contrast-enhanced mammography (CEM) provides both morphological and functional information and may reflect breast cancer biology similarly to Magnetic Resonance Imaging (MRI). Materials and Methods: This single-center retrospective study included 399 women with Breast Imaging Reporting and Data System (BI-RADS) category 0 screening mammograms who subsequently underwent CEM. A total of 76 malignant lesions (68 invasive cancers, 8 ductal carcinoma in situ (DCIS)) with complete imaging and pathology data were analyzed. Invasive cancers were classified into luminal A, luminal B, luminal B\/Human Epidermal Growth Factor Receptor 2 (HER2)-positive, HER2-enriched, and triple-negative, and grouped as luminal (Group 1) versus HER2-positive\/triple-negative (Group 2). Results: Luminal subtypes predominated (47 of 68, 69%), while 21 of 68 (31%) were HER2-positive or triple-negative. Most cancers appeared as masses with spiculated margins and heterogeneous enhancement. Significant differences were observed in mass shape (p = 0.03) and internal enhancement (p = 0.01). Luminal tumors were more often irregular and spiculated with heterogeneous enhancement, whereas the HER2-positive\/triple-negative tumors more frequently appeared round with rim or homogeneous enhancement. Deep learning-derived malignancy scores (iCAD ProFound AI\u00ae) demonstrated good diagnostic performance (area under the curve (AUC) = 0.744, 95% confidence interval (CI) 0.654\u20130.821, p &lt; 0.001). The median AI score was significantly higher in malignant compared with benign lesions (70% [interquartile range (IQR) 47\u201393] vs. 38% [IQR 25\u201361]; Mann\u2013Whitney U test, p &lt; 0.001). Among malignant lesions, iCAD scores varied across molecular subtypes, with higher median values observed in Group 1 versus Group 2 (87% vs. 55%), although the difference was not statistically significant (Mann\u2013Whitney U test, p = 0.35). Conclusions: CEM features mirrored subtype-specific phenotypes previously described with MRI, supporting its role as a practical tool for enhanced tumor characterization. Although certain imaging and AI-derived parameters differed descriptively across subtypes, no statistically significant differences were observed. As deep-learning models continue to evolve, the integration of AI-enhanced CEM into clinical workflows holds strong potential to improve lesion characterization and risk stratification in personalized breast cancer diagnostics.<\/jats:p>","DOI":"10.3390\/medicina62010115","type":"journal-article","created":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T12:38:56Z","timestamp":1767616736000},"page":"115","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Contrast-Enhanced Mammography and Deep Learning-Derived Malignancy Scoring in Breast Cancer Molecular Subtype Assessment"],"prefix":"10.3390","volume":"62","author":[{"given":"Antonia O.","family":"Feren\u010daba","sequence":"first","affiliation":[{"name":"Department of Radiology, General Hospital Virovitica, 33000 Virovitica, Croatia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dora","family":"Gali\u0107","sequence":"additional","affiliation":[{"name":"Department of Translational Medicine, Faculty of Dental Medicine and Health Osijek, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8419-1534","authenticated-orcid":false,"given":"Gordana","family":"Ivanac","sequence":"additional","affiliation":[{"name":"School of Medicine, University of Zagreb, 10000 Zagreb, Croatia"},{"name":"Department of Diagnostic and Interventional Radiology, University Hospital Dubrava, 10000 Zagreb, Croatia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kristina","family":"Kralik","sequence":"additional","affiliation":[{"name":"Department of Medical Statistics and Medical Informatics, Faculty of Medicine Osijek, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6867-826X","authenticated-orcid":false,"given":"Martina","family":"Smoli\u0107","sequence":"additional","affiliation":[{"name":"Department of Translational Medicine, Faculty of Dental Medicine and Health Osijek, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5732-0238","authenticated-orcid":false,"given":"Justinija","family":"Steiner","sequence":"additional","affiliation":[{"name":"Health Center of Osijek-Baranja County, 31000 Osijek, Croatia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9267-988X","authenticated-orcid":false,"given":"Ivo","family":"Pedi\u0161i\u0107","sequence":"additional","affiliation":[{"name":"Radiochirurgia Zagreb, 10431 Sveta Nedelja, Croatia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4473-5706","authenticated-orcid":false,"given":"Kristina","family":"Bojanic","sequence":"additional","affiliation":[{"name":"Department of Translational Medicine, Faculty of Dental Medicine and Health Osijek, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia"},{"name":"Department of Radiology, Health Center Osijek-Baranja County, 31000 Osijek, Croatia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,5]]},"reference":[{"key":"ref_1","first-page":"209","article-title":"Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"71","author":"Sung","year":"2021","journal-title":"CA Cancer J. Clin."},{"key":"ref_2","first-page":"229","article-title":"Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"74","author":"Bray","year":"2024","journal-title":"CA Cancer J. Clin."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1154","DOI":"10.1038\/s41591-025-03502-3","article-title":"Global patterns and trends in breast cancer incidence and mortality across 185 countries","volume":"31","author":"Kim","year":"2025","journal-title":"Nat. Med."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"e36905","DOI":"10.1097\/MD.0000000000036905","article-title":"Breast cancer: A review of risk factors and diagnosis","volume":"103","author":"Obeagu","year":"2024","journal-title":"Medicine"},{"key":"ref_5","first-page":"195","article-title":"Etiology of breast cancer: A perspective from epidemiologic studies","volume":"2","author":"Luo","year":"2022","journal-title":"J. Natl. Cancer Cent."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"838","DOI":"10.3889\/oamjms.2019.171","article-title":"Application of imaging technologies in breast cancer detection: A review article","volume":"7","author":"Lima","year":"2019","journal-title":"Open Access Maced. J. Med. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Ma, M., Xu, W., Yang, J., Zheng, B., Wen, C., Wang, S., Xu, Z., Qin, G., and Chen, W. (2025). Contrast-enhanced mammography-based interpretable machine learning model for the prediction of the molecular subtype breast cancers. BMC Med. Imaging, 25.","DOI":"10.1186\/s12880-025-01765-3"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1007\/s00330-024-10951-w","article-title":"Breast density effect on the sensitivity of digital screening mammography in a UK cohort","volume":"35","author":"Payne","year":"2025","journal-title":"Eur. Radiol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1186\/s13244-025-01994-8","article-title":"Contrast-enhanced mammography for breast cancer detection and diagnosis with high concentration iodinated contrast medium","volume":"16","author":"Pediconi","year":"2025","journal-title":"Insights Imaging"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1148\/radiol.212530","article-title":"Contrast-enhanced mammography versus contrast-enhanced breast MRI: A systematic review and meta-analysis","volume":"305","author":"Vatteroni","year":"2022","journal-title":"Radiology"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"174","DOI":"10.7150\/jca.79747","article-title":"Comparing the diagnostic performance of contrast-enhanced mammography and breast MRI: A systematic review and meta-analysis","volume":"14","author":"Neeter","year":"2023","journal-title":"J. Cancer"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Luczynska, E., Piegza, T., Szpor, J., Heinze, S., Popiela, T., Kargol, J., and Rudnicki, W. (2022). Contrast-enhanced mammography (CEM) capability to distinguish molecular breast cancer subtypes. Biomedicines, 10.","DOI":"10.3390\/biomedicines10102384"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1007\/s00330-024-10896-0","article-title":"Implementing the advantages of contrast-enhanced mammography and contrast-enhanced breast MRI in breast cancer staging","volume":"35","author":"Fallenberg","year":"2025","journal-title":"Eur. Radiol."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Admoun, C., and Mayrovitz, H.N. (2022). The etiology of breast cancer. Breast Cancer, Exon Publications.","DOI":"10.36255\/exon-publications-breast-cancer-etiology"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"16","DOI":"10.4132\/jptm.2020.09.03","article-title":"Imaging features of breast cancer molecular subtypes: State of the art","volume":"55","author":"Cho","year":"2021","journal-title":"J. Pathol. Transl. Med."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.breast.2011.07.008","article-title":"Characteristics and outcomes according to molecular subtypes of breast cancer as classified by a panel of four biomarkers using immunohistochemistry","volume":"21","author":"Park","year":"2012","journal-title":"Breast"},{"key":"ref_17","first-page":"e64791","article-title":"Radiologic-pathologic correlation: Is there an association between contrast-enhanced mammography imaging features and molecular subtypes of breast cancer?","volume":"16","author":"Cheng","year":"2024","journal-title":"Cureus"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"112040","DOI":"10.1016\/j.ejrad.2025.112040","article-title":"Evaluation of a ductal carcinoma in situ component accompanying HER2-positive invasive breast cancer on contrast-enhanced mammography","volume":"186","author":"Ploumen","year":"2025","journal-title":"Eur. J. Radiol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1016\/j.crad.2019.02.006","article-title":"Artificial Intelligence in Breast Imaging","volume":"74","author":"Le","year":"2019","journal-title":"Clin. Radiol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1186\/s13058-024-01821-w","article-title":"Screening Mammography Performance According to Breast Density: A Comparison between Radiologists versus Standalone Intelligence Detection","volume":"26","author":"Kwon","year":"2024","journal-title":"Breast Cancer Res."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"100882","DOI":"10.1016\/j.landig.2025.100882","article-title":"AI as an Independent Second Reader in Detection of Clinically Relevant Breast Cancers within a Population-Based Screening Programme in the Netherlands: A Retrospective Cohort Study","volume":"7","author":"Peters","year":"2025","journal-title":"Lancet Digit. Health"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2228","DOI":"10.1016\/j.acra.2023.12.005","article-title":"Contrast-Enhanced Mammography Radiomics Analysis for Preoperative Prediction of Breast Cancer Molecular Subtypes","volume":"31","author":"Zhu","year":"2024","journal-title":"Acad. Radiol."},{"key":"ref_23","first-page":"1","article-title":"European Guidelines for the Diagnosis, Treatment and Follow-up of Breast Lesions with Uncertain Malignant Potential (B3 Lesions) Developed Jointly by EUSOMA, EUSOBI, ESP (BWG) and ESSO","volume":"50","author":"Rubio","year":"2024","journal-title":"Eur. J. Surg. Oncol."},{"key":"ref_24","unstructured":"Phillips, J. (2022). Contrast-Enhanced Mammography (CEM) Lexicon. A Supplement to ACR BI-RADS Mammography, GE Healthcare. Available online: https:\/\/www.gehealthcare.com\/-\/media\/GEHC\/US\/Files\/Products\/Mammography\/Contrast-Enhanced-Mammography-Lexicon.pdf."},{"key":"ref_25","unstructured":"American College of Radiology (2013). ACR BI-RADS\u00ae Atlas, Breast Imaging Reporting and Data System, American College of Radiology. [5th ed.]."},{"key":"ref_26","unstructured":"WHO Classification of Tumours Editorial Board (2019). Breast Tumours, International Agency for Research on Cancer. [5th ed.]."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"25","DOI":"10.32074\/1591-951X-1-20","article-title":"Histological Type and Typing of Breast Carcinomas and the WHO Classification Changes over Time","volume":"112","author":"Cserni","year":"2020","journal-title":"Pathologica"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1148\/radiol.211412","article-title":"Contrast-enhanced mammography: A systematic review and meta-analysis of diagnostic performance","volume":"302","author":"Cozzi","year":"2022","journal-title":"Radiology"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"15","DOI":"10.21037\/tbcr-24-64","article-title":"Contrast-enhanced mammography in high-dense breasts: A narrative review","volume":"6","author":"Tari","year":"2025","journal-title":"Transl. Breast Cancer Res."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"\u0141ukasiewicz, S., Czeczelewski, M., Forma, A., Baj, J., Sitarz, R., and Stanis\u0142awek, A. (2021). Breast cancer\u2014Epidemiology, risk factors, classification, prognostic markers, and current treatment strategies\u2014An updated review. Cancers, 13.","DOI":"10.3390\/cancers13174287"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Batra, H., Mouabbi, J.A., Ding, Q., Sahin, A.A., and Raso, M.G. (2023). Lobular carcinoma of the breast: A comprehensive review with translational insights. Cancers, 15.","DOI":"10.3390\/cancers15225491"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/j.breast.2019.11.002","article-title":"Mucinous breast cancer: A narrative review of the literature and a retrospective tertiary single-centre analysis","volume":"49","author":"Marrazzo","year":"2020","journal-title":"Breast"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Wang, S., Zhang, Q., and Mao, X. (2024). Invasive papillary carcinoma of the breast. Front. Oncol., 14.","DOI":"10.3389\/fonc.2024.1374091"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"e2013226","DOI":"10.1001\/jamanetworkopen.2020.13226","article-title":"Incidence trends of breast cancer molecular subtypes by age and race\/ethnicity in the US from 2010 to 2016","volume":"3","author":"Acheampong","year":"2020","journal-title":"JAMA Netw. Open"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Nicosia, L., Mariano, L., Mallardi, C., Sorce, A., Frassoni, S., Bagnardi, V., Gialain, C., Pesapane, F., Sangalli, C., and Cassano, E. (2024). Influence of breast density and menopausal status on background parenchymal enhancement in contrast-enhanced mammography: Insights from a retrospective analysis. Cancers, 17.","DOI":"10.3390\/cancers17010011"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1007\/s10549-021-06478-z","article-title":"An overview of genetic services delivery for hereditary breast cancer","volume":"191","author":"Reid","year":"2022","journal-title":"Breast Cancer Res. Treat."},{"key":"ref_37","first-page":"477","article-title":"Breast cancer statistics 2024","volume":"74","author":"Giaquinto","year":"2024","journal-title":"CA Cancer J. Clin."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1186\/s43055-024-01231-0","article-title":"Non-mass enhancement on breast MRI: Clues to a more confident diagnosis","volume":"55","author":"Mohamed","year":"2024","journal-title":"Egypt. J. Radiol. Nucl. Med."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"103595","DOI":"10.1016\/j.breast.2023.103595","article-title":"Correlation between the CEM imaging characteristics and different molecular subtypes of breast cancer","volume":"72","author":"Li","year":"2023","journal-title":"Breast"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Piccolo, C.L., Celli, I., Bandini, C., Tommasiello, M., Sammarra, M., Faggioni, L., Cioni, L., Beomonte Zobel, B., and Neri, E. (2024). The Correlation between Morpho-Dynamic Contrast-Enhanced Mammography (CEM) Features and Prognostic Factors in Breast Cancer: A Single-Center Retrospective Analysis. Cancers, 16.","DOI":"10.3390\/cancers16050870"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Marzogi, A., Baltzer, P.A.T., Kapetas, P., Milos, R.I., Bernathova, M., Helbich, T.H., and Clauser, P. (2023). Is the Level of Contrast Enhancement on Contrast-Enhanced Mammography (CEM) Associated with the Presence and Biological Aggressiveness of Breast Cancer?. Diagnostics, 13.","DOI":"10.3390\/diagnostics13040754"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Bartsch, S.J., Bro\u017eov\u00e1, K., Ehret, V., Friske, J., F\u00fcrb\u00f6ck, C., Kenner, L., Laimer-Gruber, D., Helbich, T.H., and Pinker, K. (2024). Non-Contrast-Enhanced Multiparametric MRI of the Hypoxic Tumor Microenvironment Allows Molecular Subtyping of Breast Cancer: A Pilot Study. Cancers, 16.","DOI":"10.3390\/cancers16020375"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1007\/s40134-022-00410-z","article-title":"Triple-Negative Breast Cancer: Multimodality Appearance","volume":"11","author":"Chen","year":"2023","journal-title":"Curr. Radiol. Rep."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Moffa, G., Galati, F., Collalunga, E., Rizzo, V., Kripa, E., D\u2019Amati, G., and Pediconi, F. (2020). Can MRI biomarkers predict triple-negative breast cancer?. Diagnostics, 10.","DOI":"10.3390\/diagnostics10121090"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"19305","DOI":"10.1038\/s41598-024-69778-6","article-title":"MRI features of breast cancer immunophenotypes with a focus on luminal estrogen receptor low positive invasive carcinomas","volume":"14","author":"Tajima","year":"2024","journal-title":"Sci. Rep."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Pereira, A., Siegrist, J., Lizarraga, S., and P\u00e9rez-Medina, T. (2022). Clustering molecular subtypes in breast cancer, immunohistochemical parameters and risk of axillary nodal involvement. J. Pers. Med., 12.","DOI":"10.3390\/jpm12091404"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"109883","DOI":"10.1016\/j.ejrad.2021.109883","article-title":"Contrast enhanced mammography (CEM) versus magnetic resonance imaging (MRI) for staging of breast cancer: The pro CEM perspective","volume":"142","author":"Lobbes","year":"2021","journal-title":"Eur. J. Radiol."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Bellini, C., Susini, T., Toncelli, K., Pandolfi, M., Migliaro, G., Pugliese, F., Vanzi, B., Incardona, L., Bicchierai, G., and di Naro, F. (2025). Lesion conspicuity in contrast-enhanced mammography: A retrospective analysis of tumor characteristics. Cancers, 17.","DOI":"10.3390\/cancers17030501"},{"key":"ref_49","first-page":"248","article-title":"Diagnostic Value of Qualitative and Quantitative Enhancement Parameters on Contrast-Enhanced Mammography","volume":"30","author":"Kul","year":"2024","journal-title":"Diagn. Interv. Radiol."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1148\/radiol.11102156","article-title":"Background Parenchymal Enhancement at Breast MR Imaging and Breast Cancer Risk","volume":"260","author":"King","year":"2011","journal-title":"Radiology"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"111903","DOI":"10.1016\/j.ejrad.2024.111903","article-title":"Background Parenchymal Enhancement in CEM and MRI: Is There Always a High Agreement?","volume":"183","author":"Ferrara","year":"2025","journal-title":"Eur. J. Radiol."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Vidali, S., Irmici, G., Depretto, C., Bellini, C., Pugliese, F., Incardona, L.A., Di Naro, F., De Benedetto, D., Di Filippo, G., and Ferraro, F. (2024). Performance of Contrast-Enhanced Mammography (CEM) for Monitoring Neoadjuvant Chemotherapy Response among Different Breast Cancer Subtypes. Cancers, 16.","DOI":"10.3390\/cancers16152694"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1483","DOI":"10.2214\/AJR.05.1582","article-title":"Prospective assessment of computer-aided detection in interpretation of screening mammography","volume":"187","author":"Ko","year":"2006","journal-title":"Am. J. Roentgenol."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"909","DOI":"10.2214\/AJR.12.10187","article-title":"Impact of computer-aided detection systems on radiologist accuracy with digital mammography: A multireader study","volume":"203","author":"Cole","year":"2014","journal-title":"Am. J. Roentgenol."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"431","DOI":"10.2217\/iim.13.68","article-title":"Computer-aided diagnosis in digital mammography: Comparison of two commercial systems","volume":"6","author":"Cascio","year":"2014","journal-title":"Imaging Med."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"368","DOI":"10.1007\/s11547-025-01956-6","article-title":"Superior performance in classification of breast cancer molecular subtype and histological factors by radiomics based on ultrafast MRI over standard MRI: Evidence from a prospective study","volume":"130","author":"Jeong","year":"2025","journal-title":"Radiol. Med."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Nicosia, L., Mariano, L., Gaeta, A., Raimondi, S., Pesapane, F., Corso, G., De Marco, P., Origgi, D., Sangalli, C., and Bianco, N. (2025). Preliminary evaluation of radiomics in contrast-enhanced mammography for prognostic prediction of breast cancer. Cancers, 17.","DOI":"10.3390\/cancers17121926"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Mota, A.M., Mendes, J., and Matela, N. (2024). Breast Cancer Molecular Subtype Prediction: A Mammography-Based AI Approach. Biomedicines, 12.","DOI":"10.3390\/biomedicines12061371"}],"container-title":["Medicina"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1648-9144\/62\/1\/115\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T13:11:50Z","timestamp":1767618710000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1648-9144\/62\/1\/115"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,5]]},"references-count":58,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,1]]}},"alternative-id":["medicina62010115"],"URL":"https:\/\/doi.org\/10.3390\/medicina62010115","relation":{},"ISSN":["1648-9144"],"issn-type":[{"value":"1648-9144","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,5]]}}}