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Articles published in
Radiology
    January 2026
  1. CHANG JM, Leung JWT, Heacock L, Lee SH, et al
    Breast US: State of the Art.
    Radiology. 2026;318:e233101.
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  2. MAHMOUD MA, Chen J, Edmonds CE, Fayanju OM, et al
    Black-White Racial Differences in Background Parenchymal Enhancement at Breast MRI.
    Radiology. 2026;318:e251041.
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    December 2025
  3. EOM HJ, Cha JH, Cho SM, Kim HJ, et al
    Interreader Agreement and Diagnostic Confidence in Discriminating Masses and Nonmass Lesions at Breast US.
    Radiology. 2025;317:e250783.
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  4. ZHENG J, You C, Gu Y
    Capturing Treatment Dynamics: Multi-b-Value Diffusion-weighted Imaging to Advance Response Prediction in Breast Cancer Neoadjuvant Chemotherapy.
    Radiology. 2025;317:e252601.
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    November 2025
  5. COZZI A, Bellini C, Girometti R, Alcantara Souza R, et al
    Tumor Involvement of the Nipple at Preoperative Contrast-enhanced Mammography: A Multicenter Diagnostic Accuracy Study.
    Radiology. 2025;317:e251350.
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  6. HOU R, Grimm LJ, Marks JR, King LM, et al
    Cross-National Radiomics Validation Using Mammography to Predict Occult Invasion in Ductal Carcinoma in Situ.
    Radiology. 2025;317:e243739.
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  7. YAO MM, Vy VPT, Lee CS, Chang YC, et al
    Identification of Risk Factors for Interval Breast Cancer in a Population-based Screening Program.
    Radiology. 2025;317:e243918.
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    October 2025
  8. PARK VY, Choi JS, Han K, Nahm S, et al
    Imaging Features and Diagnostic Performance of US in Nonmass Lesions with Varying Clinical Indications.
    Radiology. 2025;317:e243398.
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  9. COHEN EO, Tso HH, Shin K, Martaindale SR, et al
    Feasibility of Auditing Preoperative Breast MRI for Extent-of-Disease Evaluation Using the BI-RADS v2025 Manual.
    Radiology. 2025;317:e243803.
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  10. YOEN H, Shin HC, Yoon KH, Oh JH, et al
    Preoperative Breast MRI and Survival Outcomes in Women 50 Years or Younger with Breast Cancer.
    Radiology. 2025;317:e250439.
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  11. ROTHWELL JWD, Rogers P, Payne NR, Huang Y, et al
    Evaluation of a Mammography-based Deep Learning Model for Breast Cancer Risk Prediction in a Triennial Screening Program.
    Radiology. 2025;317:e250391.
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    September 2025
  12. KIM HJ, Chae EY, Eom HJ, Choi WJ, et al
    Node Reporting and Data System Evaluation of Axillary Nodes in Invasive Ductal and Lobular Carcinoma.
    Radiology. 2025;316:e243823.
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  13. FREITAS V
    Node Reporting and Data System in Focus: Advancing Precision in Axillary Staging for Breast Cancer.
    Radiology. 2025;316:e252033.
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  14. KO ES, Yu JH, Woo SY, Kim SW, et al
    Calcifications Affect Pathologic Complete Response and MRI Prediction after Neoadjuvant Chemotherapy in Human Epidermal Growth Factor Receptor 2-positive Breast Cancer.
    Radiology. 2025;316:e250718.
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  15. MESUROLLE B, El Khoury M
    False-Positive Recall and Biopsy Rates in Breast Cancer Screening: Insights from TOSYMA.
    Radiology. 2025;316:e252367.
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  16. WEIGEL S, Hense HW, Weyer-Elberich V, Gerss J, et al
    False-Positive Recall and False-Positive Biopsy Rates in Mammography Screening: A TOSYMA Trial Subanalysis.
    Radiology. 2025;316:e251014.
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  17. HRUSKA CB, Hunt KN, Larson NB, Miller PA, et al
    Molecular Breast Imaging and Digital Breast Tomosynthesis for Dense Breast Screening: The Density MATTERS Trial.
    Radiology. 2025;316:e243953.
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  18. KO ES, Yu JH, Woo SY, Kim SW, et al
    Erratum for: Calcifications Affect Pathologic Complete Response and MRI Prediction after Neoadjuvant Chemotherapy in Human Epidermal Growth Factor Receptor 2-positive Breast Cancer.
    Radiology. 2025;316:e259015.
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    August 2025
  19. ULANER GA
    Detection of Oligometastatic Disease in Breast Cancer: It's the Little Things That Count.
    Radiology. 2025;316:e251797.
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  20. YEH R, D'Andrea G
    In Vivo Imaging for Assessing Receptor Status in Breast Cancer.
    Radiology. 2025;316:e243832.
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  21. METSER U, Ali Mirshahvalad S, Dayes IS, Parpia S, et al
    (18)F-FDG PET/CT of Oligometastatic Disease in Locally Advanced Breast Cancer: PETABC Trial Post Hoc Analysis.
    Radiology. 2025;316:e243788.
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  22. CHEN Y, Partridge GJW, Vazirabad M, Ball RL, et al
    Performance of Algorithms Submitted in the 2023 RSNA Screening Mammography Breast Cancer Detection AI Challenge.
    Radiology. 2025;316:e241447.
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  23. VERBOOM SD, Kroes J, Pires S, Broeders MJM, et al
    AI Should Read Mammograms Only When Confident: A Hybrid Breast Cancer Screening Reading Strategy.
    Radiology. 2025;316:e242594.
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  24. WOOLDRIK SM, van de Voort EMF, Struik GM, Schouten BJM, et al
    Percutaneous Thermal Ablation for Early-Stage Breast Cancer: An Open-Label, Randomized, Phase II Trial to Select the Preferred Technique for Evaluating Thermal Ablation as a Surgical Alternative.
    Radiology. 2025;316:e243386.
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  25. HUANG Y, Song X, Chen Y, Qiu H, et al
    Intratumoral Microbiome-related MRI Model for Predicting Breast Cancer Shrinkage Pattern Following Neoadjuvant Therapy.
    Radiology. 2025;316:e243545.
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    July 2025
  26. ONISHI N
    Breast MRI for Assessing Triple-Negative Breast Cancer after Neoadjuvant Chemoimmunotherapy.
    Radiology. 2025;316:e251503.
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  27. RAMTOHUL T, Lollivier D, Spriet J, Jin M, et al
    Posttreatment MRI to Predict Pathologic Complete Response of Triple-Negative Breast Cancer to Neoadjuvant Chemoimmunotherapy.
    Radiology. 2025;316:e243824.
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  28. GOMMERS JJJ, Verboom SD, Duvivier KM, van Rooden CJ, et al
    Influence of AI Decision Support on Radiologists' Performance and Visual Search in Screening Mammography.
    Radiology. 2025;316:e243688.
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  29. OVIEDO F, Kazerouni AS, Liznerski P, Xu Y, et al
    Cancer Detection in Breast MRI Screening via Explainable AI Anomaly Detection.
    Radiology. 2025;316:e241629.
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  30. BAE MS, Ham S
    Explainable AI in MRI for Breast Cancer Detection: Another Step Forward.
    Radiology. 2025;316:e251790.
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  31. GONG X, Wang X, Wang L, Zeng X, et al
    Comparing Multi-b-Value Diffusion MRI Models for Predicting Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer.
    Radiology. 2025;316:e242969.
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  32. THAKUR SB, Bitencourt AGV
    Precision Imaging in Breast Cancer: Neoadjuvant Chemotherapy Monitoring with Advanced Diffusion MRI.
    Radiology. 2025;316:e251723.
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  33. BAHL M, Langarica S, Lamb LR, Kniss AS, et al
    AI to Reduce the Interval Cancer Rate of Screening Digital Breast Tomosynthesis.
    Radiology. 2025;316:e241050.
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  34. LEE CI, Milch HS
    Clinically Meaningful AI Detection of Interval Breast Cancer at Digital Breast Tomosynthesis Screening.
    Radiology. 2025;316:e251860.
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    June 2025
  35. ESKREIS-WINKLER S, Bhowmik A, Kelly LH, Lo Gullo R, et al
    Adaptive Breast MRI Scanning Using AI.
    Radiology. 2025;315:e242924.
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  36. HONDA M, Iima M
    Preoperative Diffusion-weighted Imaging to Reduce the Burden on Patients with Breast Cancer.
    Radiology. 2025;315:e250964.
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  37. KIM HJ, Partridge SC, Lee J, Yoen H, et al
    Preoperative Diagnosis of Ipsilateral and Contralateral Breast Cancer: Role of Diffusion-weighted MRI.
    Radiology. 2025;315:e242423.
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  38. BERG WA, Vargo A, Lu AH, Berg JM, et al
    Screening for Breast Cancer with Contrast-enhanced Mammography as an Alternative to MRI: SCEMAM Trial Results.
    Radiology. 2025;315:e242634.
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  39. KIM HJ, Partridge SC, Lee J, Yoen H, et al
    Erratum for: Preoperative Diagnosis of Ipsilateral and Contralateral Breast Cancer: Role of Diffusion-weighted MRI.
    Radiology. 2025;315:e259012.
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  40. WOO OH, Song SE, Choe SJ, Kim M, et al
    Invasive Breast Cancers Missed by AI Screening of Mammograms.
    Radiology. 2025;315:e242408.
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    May 2025
  41. BODE M, Morscheid S, Iordanishvili E, Huck LC, et al
    Intraindividual Comparison of Ultrafast versus Standard Two-dimensional Dynamic Contrast-enhanced Breast MRI.
    Radiology. 2025;315:e241371.
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  42. WINHAM SJ, McCarthy AM, Scott CG, Gastounioti A, et al
    Radiomic Parenchymal Phenotypes of Breast Texture from Mammography and Association with Risk of Breast Cancer.
    Radiology. 2025;315:e240281.
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  43. MESUROLLE B, El Khoury M
    Breast Cancer Risk Prediction with Radiomic Tissue Characterization on Mammograms Takes Shape.
    Radiology. 2025;315:e250622.
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  44. VAN GRINSVEN SEL, Mann RM, Monninkhof EM, Duvivier K, et al
    Multireader Diagnostic Accuracy of Abbreviated Breast MRI for Screening Women with Extremely Dense Breasts.
    Radiology. 2025;315:e241233.
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  45. BECHYNA S, Baltzer PAT
    Impact of Background Parenchymal Enhancement on Diagnostic Performance of Breast MRI: A Systematic Review and Meta-Analysis.
    Radiology. 2025;315:e241919.
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    April 2025
  46. SLAVKOVA KP, Kang R, Kazerouni AS, Biswas D, et al
    MRI-based Radiomic Features for Risk Stratification of Ductal Carcinoma in Situ in a Multicenter Setting (ECOG-ACRIN E4112 Trial).
    Radiology. 2025;315:e241628.
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  47. HA SM, Lee JM, Jang MJ, Kim HK, et al
    Breast Cancer Detection with Standalone AI versus Radiologist Interpretation of Unilateral Surveillance Mammography after Mastectomy.
    Radiology. 2025;315:e242955.
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  48. HUANG Y, Wang X, Cao Y, Lan X, et al
    Nomogram for Predicting Neoadjuvant Chemotherapy Response in Breast Cancer Using MRI-based Intratumoral Heterogeneity Quantification.
    Radiology. 2025;315:e241805.
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  49. AUTIER P, Burrion JB, Grivegnee A
    Artificial Intelligence System for Interval Breast Cancer Detection May Swamp Screening Programs.
    Radiology. 2025;315:e242698.
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  50. KIM HJ, Choi WJ, Eom HJ, Chae EY, et al
    Impact of Preoperative MRI on Survival Outcomes in Patients with HER2-positive and Hormone Receptor-negative Breast Cancer.
    Radiology. 2025;315:e242712.
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  51. IMBRIACO M, Ponsiglione A
    Preoperative MRI and Long-term Outcomes in Patients with HER2-positive and Hormone Receptor-negative Breast Cancer: A Matched Cohort Study.
    Radiology. 2025;315:e250532.
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    March 2025
  52. KNIP JJ, Iqbal R, Bonjer EC, Mammatas LH, et al
    The Diagnostic Accuracy of (18)F-FDG PET and (18)F-FES PET for Staging Grade 1-2 Estrogen Receptor-Positive Breast Cancer.
    Radiology. 2025;314:e241850.
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  53. FOWLER AM
    (18)F-Fluoroestradiol PET/CT for Staging Low-Grade Estrogen Receptor-Positive Breast Cancer.
    Radiology. 2025;314:e250135.
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  54. DEMBROWER KE, Crippa A, Eklund M, Strand F, et al
    Human-AI Interaction in the ScreenTrustCAD Trial: Recall Proportion and Positive Predictive Value Related to Screening Mammograms Flagged by AI CAD versus a Human Reader.
    Radiology. 2025;314:e242566.
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  55. HORVAT JV, Amir T, Watt GP, Comstock CE, et al
    Comparison of Contrast-enhanced Mammography and Low-Energy Imaging with or without Supplemental Whole-Breast US in Breast Cancer Detection.
    Radiology. 2025;314:e242006.
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    February 2025
  56. VAN WINKEL SL, Samperna R, Loehrer EA, Kroes J, et al
    Using AI to Select Women with Intermediate Breast Cancer Risk for Breast Screening with MRI.
    Radiology. 2025;314:e233067.
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  57. NISSAN N, Sevilimedu V, Gluskin J, Arita Y, et al
    Hormonal Regulation of Background Parenchymal Enhancement at Contrast-enhanced Mammography.
    Radiology. 2025;314:e241158.
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  58. LAWSON MB, Zhu W, Miglioretti DL, Onega T, et al
    Disparities in Standard-of-Care, Advanced, and Same-Day Diagnostic Services among Patients with Abnormal Screening Mammography.
    Radiology. 2025;314:e241673.
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    January 2025
  59. YOON J, Han K, Nahm S, Kim MJ, et al
    Surveillance Breast MRI in Women with a History of Breast Cancer: Association with Occurrence of Advanced Second Breast Cancer.
    Radiology. 2025;314:e240119.
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    December 2024
  60. KIM E, Moy L
    Distant-Stage Breast Cancer Incidence Is Increasing in U.S. Women across Age Groups and Race and Ethnicity Groups.
    Radiology. 2024;313:e242716.
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  61. HENDRICK RE, Monticciolo DL
    Surveillance, Epidemiology, and End Results Data Show Increasing Rates of Distant-Stage Breast Cancer at Presentation in U.S. Women.
    Radiology. 2024;313:e241397.
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    November 2024
  62. HA SM, Choi WJ, Han BK, Kim HH, et al
    Assessment of Nonmass Lesions Detected with Screening Breast US Based on Mammographic Findings.
    Radiology. 2024;313:e240043.
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  63. ABBEY CK, Bandos AI, Parthasarathy MK, Webster MA, et al
    Changes in Reader Performance During Sequential Reading of Breast Cancer Screening Digital Breast Tomosynthesis Examinations.
    Radiology. 2024;313:e232885.
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  64. HICKMAN SE, Payne NR, Black RT, Huang Y, et al
    Deep Learning Algorithms for Breast Cancer Detection in a UK Screening Cohort: As Stand-alone Readers and Combined with Human Readers.
    Radiology. 2024;313:e233147.
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    October 2024
  65. NISSAN N, Comstock CE, Sevilimedu V, Gluskin J, et al
    Diagnostic Accuracy of Screening Contrast-enhanced Mammography for Women with Extremely Dense Breasts at Increased Risk of Breast Cancer.
    Radiology. 2024;313:e232580.
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  66. LOBBES MBI
    A Decade of Contrast-enhanced Mammography: Expanding Screening to Women at Intermediate or High Risk for Breast Cancer.
    Radiology. 2024;313:e241970.
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  67. TRENTHAM-DIETZ A
    Weighing the Benefits and Risks of Mammography Screening Strategies.
    Radiology. 2024;313:e240819.
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  68. GRIMM LJ
    A New Paradigm for Reading Screening Mammograms.
    Radiology. 2024;313:e242141.
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  69. GOMMERS JJJ, Verboom SD, Duvivier KM, van Rooden JK, et al
    Enhancing Radiologist Reading Performance by Ordering Screening Mammograms Based on Characteristics That Promote Visual Adaptation.
    Radiology. 2024;313:e240237.
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  70. PARTRIDGE SC, Xu J
    Cellular Characterization of Breast Cancer Using Microstructural Diffusion MRI.
    Radiology. 2024;313:e242268.
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  71. WANG X, Ba R, Huang Y, Cao Y, et al
    Time-Dependent Diffusion MRI Helps Predict Molecular Subtypes and Treatment Response to Neoadjuvant Chemotherapy in Breast Cancer.
    Radiology. 2024;313:e240288.
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    September 2024
  72. RAMTOHUL T, Lepagney V, Bonneau C, Jin M, et al
    Use of Pretreatment Perfusion MRI-based Intratumoral Heterogeneity to Predict Pathologic Response of Triple-Negative Breast Cancer to Neoadjuvant Chemoimmunotherapy.
    Radiology. 2024;312:e240575.
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  73. RAUCH GM
    Biomarkers for Personalized Neoadjuvant Therapy in Triple-Negative Breast Cancer: Moving Forward.
    Radiology. 2024;312:e242011.
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  74. BAHL M
    Combining AI and Radiomics to Improve the Accuracy of Breast US.
    Radiology. 2024;312:e241795.
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  75. MAGNUSKA ZA, Roy R, Palmowski M, Kohlen M, et al
    Combining Radiomics and Autoencoders to Distinguish Benign and Malignant Breast Tumors on US Images.
    Radiology. 2024;312:e232554.
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  76. KIM SY, Woo OH
    Implications of Digital Breast Tomosynthesis in Breast Cancer Screening: Reducing Advanced Breast Cancers.
    Radiology. 2024;312:e242008.
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  77. PHILPOTTS LE, Grewal JK, Horvath LJ, Giwerc MY, et al
    Breast Cancers Detected during a Decade of Screening with Digital Breast Tomosynthesis: Comparison with Digital Mammography.
    Radiology. 2024;312:e232841.
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    August 2024
  78. SPRAGUE BL, Ichikawa L, Eavey J, Lowry KP, et al
    Performance of Supplemental US Screening in Women with Dense Breasts and Varying Breast Cancer Risk: Results from the Breast Cancer Surveillance Consortium.
    Radiology. 2024;312:e232380.
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  79. HELBICH TH, Kapetas P
    Gradualism: How Supplemental Breast Cancer Screening Will Become a Reality.
    Radiology. 2024;312:e241563.
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  80. ZHOU W, Franc BL, DeMartini WB, Rosen EL, et al
    Estrogen Receptor-targeted PET Imaging for Breast Cancer.
    Radiology. 2024;312:e240315.
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  81. VAN DER WAAL D, van Landsveld-Verhoeven C, Tetteroo E, van Engen RE, et al
    Pain Experience and Image Quality with Curved versus Standard Compression for Breast Cancer Screening Mammography: A Randomized Controlled Trial.
    Radiology. 2024;312:e232680.
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  82. HELBICH TH, Kapetas P
    Erratum for: Gradualism: How Supplemental Breast Cancer Screening Will Become a Reality.
    Radiology. 2024;312:e249019.
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  83. NANAA M, Gupta VO, Hickman SE, Allajbeu I, et al
    Accuracy of an Artificial Intelligence System for Interval Breast Cancer Detection at Screening Mammography.
    Radiology. 2024;312:e232303.
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    July 2024
  84. MULLER-FRANZES G, Khader F, Tayebi Arasteh S, Huck L, et al
    Intraindividual Comparison of Different Methods for Automated BPE Assessment at Breast MRI: A Call for Standardization.
    Radiology. 2024;312:e232304.
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  85. HA SM, Jang MJ, Youn I, Yoen H, et al
    Screening Outcomes of Mammography with AI in Dense Breasts: A Comparative Study with Supplemental Screening US.
    Radiology. 2024;312:e233391.
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  86. WHITMAN GJ, Destounis SV
    Screening Mammography with AI and Supplemental Breast US: Current Status.
    Radiology. 2024;312:e241362.
    >> Share

  87. LIN F, Choyke PL
    Somatostatin Radioligand Therapy of Breast Cancer: A Target of Opportunity.
    Radiology. 2024;312:e241298.
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  88. ULANER GA, VanderMolen LA, Li G, Ferreira D, et al
    Dotatate PET/CT and (225)Ac-Dotatate Therapy for Somatostatin Receptor-expressing Metastatic Breast Cancer.
    Radiology. 2024;312:e233408.
    >> Share

  89. JOGI A, Johnson K, Wittgren S, Sundgren V, et al
    Assessing Digital Breast Tomosynthesis Impact on Early Cancer Detection: Insights from Consecutive Screening.
    Radiology. 2024;312:e233417.
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    June 2024
  90. LEE AY, Friedewald SM
    Clinical Implementation of AI in Screening Mammography: The Essential Role of Prospective Evaluation.
    Radiology. 2024;311:e241124.
    >> Share

  91. LAURITZEN AD, Lillholm M, Lynge E, Nielsen M, et al
    Early Indicators of the Impact of Using AI in Mammography Screening for Breast Cancer.
    Radiology. 2024;311:e232479.
    >> Share

  92. GUO X, Zhou N, Liu J, Ding J, et al
    Comparison of an Affibody-based Molecular Probe and (18)F-FDG for Detecting HER2-Positive Breast Cancer at PET/CT.
    Radiology. 2024;311:e232209.
    >> Share

  93. MANN RM
    Breast Screening with US Transmission Imaging: A New Approach Yielding Old Results.
    Radiology. 2024;311:e241074.
    >> Share

  94. ULANER GA
    HER2-targeted PET for Patients with Breast Cancer: Scintillating Data.
    Radiology. 2024;311:e240814.
    >> Share

  95. YAMASHITA MW, Larsen LH, Perez J, Edwards AV, et al
    Comparison of Mammography and Mammography with Supplemental Whole-Breast US Tomography for Cancer Detection in Patients with Dense Breasts.
    Radiology. 2024;311:e231680.
    >> Share

    May 2024
  96. TURKBEY B
    Use of Molecular Imaging to Further Investigate PI-RADS 3 Lesions.
    Radiology. 2024;311:e240401.
    >> Share

  97. POTSCH N, Sodano C, Baltzer PAT
    Performance of Diffusion-weighted Imaging-based Noncontrast MRI Protocols for Diagnosis of Breast Cancer: A Systematic Review and Meta-Analysis.
    Radiology. 2024;311:e232508.
    >> Share

  98. KATAOKA M, Iima M
    Potential of the Diffusion-based Noncontrast Protocol for Breast Imaging: Current Status and Hints for Improvements.
    Radiology. 2024;311:e241058.
    >> Share

  99. NGUYEN DL, Ren Y, Jones TM, Thomas SM, et al
    Patient Characteristics Impact Performance of AI Algorithm in Interpreting Negative Screening Digital Breast Tomosynthesis Studies.
    Radiology. 2024;311:e232286.
    >> Share

    April 2024
  100. KIM MK, Chang JM
    AI-driven Selection of Candidates for Supplemental Breast Cancer Screening.
    Radiology. 2024;311:e240447.
    >> Share

  101. LIU Y, Sorkhei M, Dembrower K, Azizpour H, et al
    Use of an AI Score Combining Cancer Signs, Masking, and Risk to Select Patients for Supplemental Breast Cancer Screening.
    Radiology. 2024;311:e232535.
    >> Share

  102. BERG WA, Berg JM, Bandos AI, Vargo A, et al
    Addition of Contrast-enhanced Mammography to Tomosynthesis for Breast Cancer Detection in Women with a Personal History of Breast Cancer: Prospective TOCEM Trial Interim Analysis.
    Radiology. 2024;311:e231991.
    >> Share

  103. COZZI A, Pinker K, Hidber A, Zhang T, et al
    BI-RADS Category Assignments by GPT-3.5, GPT-4, and Google Bard: A Multilanguage Study.
    Radiology. 2024;311:e232133.
    >> Share

    March 2024
  104. DONNELLY J, Moffett L, Barnett AJ, Trivedi H, et al
    AsymMirai: Interpretable Mammography-based Deep Learning Model for 1-5-year Breast Cancer Risk Prediction.
    Radiology. 2024;310:e232780.
    >> Share

  105. CHEN Y, Taib AG, Darker IT, James JJ, et al
    Erratum for: Performance of a Breast Cancer Detection AI Algorithm Using the Personal Performance in Mammographic Screening Scheme.
    Radiology. 2024;310:e249007.
    >> Share

  106. ZHOU LQ, Wu XL, Huang SY, Wu GG, et al
    Erratum for: Lymph Node Metastasis Prediction from Primary Breast Cancer US Images Using Deep Learning.
    Radiology. 2024;310:e249009.
    >> Share

  107. KUHL CK
    Abbreviated Breast MRI: State of the Art.
    Radiology. 2024;310:e221822.
    >> Share


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