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Articles published in
Eur Radiol
    April 2024
  1. VEDANTHAM S
    Contrast-enhanced breast computed tomography: can lymph node metastasis be predicted from primary tumor?
    Eur Radiol. 2024;34:2574-2575.
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  2. XU Z, Lin Y, Huo J, Gao Y, et al
    A bimodal nomogram as an adjunct tool to reduce unnecessary breast biopsy following discordant ultrasonic and mammographic BI-RADS assessment.
    Eur Radiol. 2024;34:2608-2618.
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  3. MAO C, Hu L, Jiang W, Qiu Y, et al
    Discrimination between human epidermal growth factor receptor 2 (HER2)-low-expressing and HER2-overexpressing breast cancers: a comparative study of four MRI diffusion models.
    Eur Radiol. 2024;34:2546-2559.
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    March 2024
  4. CAMPS-HERRERO J, Pijnappel R, Balleyguier C
    MR-contrast enhanced mammography (CEM) for follow-up of breast cancer patients: a "pros and cons" debate.
    Eur Radiol. 2024 Mar 15. doi: 10.1007/s00330-024-10684.
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  5. LOKAJ B, Pugliese MT, Kinkel K, Lovis C, et al
    Barriers and facilitators of artificial intelligence conception and implementation for breast imaging diagnosis in clinical practice: a scoping review.
    Eur Radiol. 2024;34:2096-2109.
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  6. JING X, Dorrius MD, Zheng S, Wielema M, et al
    Localization of contrast-enhanced breast lesions in ultrafast screening MRI using deep convolutional neural networks.
    Eur Radiol. 2024;34:2084-2092.
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    February 2024
  7. KOCH HW, Larsen M, Bartsch H, Martiniussen MA, et al
    How do AI markings on screening mammograms correspond to cancer location? An informed review of 270 breast cancer cases in BreastScreen Norway.
    Eur Radiol. 2024 Feb 23. doi: 10.1007/s00330-024-10662.
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  8. SEKER ME, Koyluoglu YO, Ozaydin AN, Gurdal SO, et al
    Diagnostic capabilities of artificial intelligence as an additional reader in a breast cancer screening program.
    Eur Radiol. 2024 Feb 22. doi: 10.1007/s00330-024-10661.
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  9. ZHENG S, Yang Z, Du G, Zhang Y, et al
    Discrimination between HER2-overexpressing, -low-expressing, and -zero-expressing statuses in breast cancer using multiparametric MRI-based radiomics.
    Eur Radiol. 2024 Feb 16. doi: 10.1007/s00330-024-10641.
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  10. WANG Q, Lin Y, Ding C, Guan W, et al
    Multi-modality radiomics model predicts axillary lymph node metastasis of breast cancer using MRI and mammography.
    Eur Radiol. 2024 Feb 10. doi: 10.1007/s00330-024-10638.
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  11. ZHAO S, Li Y, Ning N, Liang H, et al
    Association of peritumoral region features assessed on breast MRI and prognosis of breast cancer: a systematic review and meta-analysis.
    Eur Radiol. 2024 Feb 9. doi: 10.1007/s00330-024-10612.
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  12. TONG Y, Hu Z, Wang H, Huang J, et al
    Anti-HER2 therapy response assessment for guiding treatment (de-)escalation in early HER2-positive breast cancer using a novel deep learning radiomics model.
    Eur Radiol. 2024 Feb 8. doi: 10.1007/s00330-024-10609.
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  13. MULLEN LA
    Can digital breast tomosynthesis decrease interval cancers in a breast cancer screening program?
    Eur Radiol. 2024 Feb 6. doi: 10.1007/s00330-024-10635.
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  14. ZHANG T, Mann RM
    Contrast-enhanced mammography: better with AI?
    Eur Radiol. 2024;34:914-916.
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  15. XU J, Zhang L, Wen W, He Y, et al
    Evaluation of standard breast ultrasonography by adding two-dimensional and three-dimensional shear wave elastography: a prospective, multicenter trial.
    Eur Radiol. 2024;34:945-956.
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  16. BARR RG
    Breast elastography: how does it works, and for what purposes?
    Eur Radiol. 2024;34:928-929.
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  17. PARTRIDGE GJW, Taib AG, Phillips P, James JJ, et al
    Take a break: should breaks be enforced during digital breast tomosynthesis reading sessions?
    Eur Radiol. 2024;34:1388-1398.
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    January 2024
  18. DENG Y, Lu Y, Li X, Zhu Y, et al
    Prediction of human epidermal growth factor receptor 2 (HER2) status in breast cancer by mammographic radiomics features and clinical characteristics: a multicenter study.
    Eur Radiol. 2024 Jan 26. doi: 10.1007/s00330-024-10607.
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  19. STEYEROVA P, Kaidar-Person O, Pinker K, Dubsky P, et al
    Breast cancer: evaluating the axilla before, during, and after therapy-new challenges.
    Eur Radiol. 2024 Jan 26. doi: 10.1007/s00330-024-10621.
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  20. AL-BAZZAZ H, Janicijevic M, Strand F
    Reader bias in breast cancer screening related to cancer prevalence and artificial intelligence decision support-a reader study.
    Eur Radiol. 2024 Jan 2. doi: 10.1007/s00330-023-10514.
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  21. ZARIC O, Hatamikia S, George G, Schwarzhans F, et al
    AI-based time-intensity-curve assessment of breast tumors on MRI.
    Eur Radiol. 2024;34:179-181.
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  22. BARUFALDI B, Acciavatti RJ, Conant EF, Maidment ADA, et al
    Impact of super-resolution and image acquisition on the detection of calcifications in digital breast tomosynthesis.
    Eur Radiol. 2024;34:193-203.
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  23. LIU Z, Yao B, Wen J, Wang M, et al
    Voxel-wise mapping of DCE-MRI time-intensity-curve profiles enables visualizing and quantifying hemodynamic heterogeneity in breast lesions.
    Eur Radiol. 2024;34:182-192.
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  24. D'ANGELO A, Scardina L, Palma S, Cicero SL, et al
    Magnetic seed versus skin tattoo localization of non-palpable breast lesions: a single institution cohort study.
    Eur Radiol. 2024;34:149-154.
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    December 2023
  25. RAYA-POVEDANO JL
    AI in breast cancer screening: a critical overview of what we know.
    Eur Radiol. 2023 Dec 21. doi: 10.1007/s00330-023-10530.
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  26. MANN RM
    Breast screening: "If you really want to see it, you just make an MRI".
    Eur Radiol. 2023;33:8410-8412.
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  27. LOBBES MBI
    Breast cancer screening in patients with intermediate risk using contrast-enhanced mammography.
    Eur Radiol. 2023;33:8407-8409.
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    November 2023
  28. ELIAS-CABOT E, Romero-Martin S, Raya-Povedano JL, Brehl AK, et al
    Impact of real-life use of artificial intelligence as support for human reading in a population-based breast cancer screening program with mammography and tomosynthesis.
    Eur Radiol. 2023 Nov 17. doi: 10.1007/s00330-023-10426.
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  29. CHAN HP
    Potential of AI-assisted analysis of mammograms for extensive intraductal component in invasive breast cancer.
    Eur Radiol. 2023 Nov 16. doi: 10.1007/s00330-023-10449.
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  30. MOSHINA N, Backmann HA, Skaane P, Hofvind S, et al
    Mammographic features and risk of breast cancer death among women with invasive screen-detected cancer in BreastScreen Norway 1996-2020.
    Eur Radiol. 2023 Nov 8. doi: 10.1007/s00330-023-10369.
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  31. COZZI A, Schiaffino S
    Preoperative breast MRI in women with dense breasts: can we keep up with a rapidly changing scenario?
    Eur Radiol. 2023;33:8077-8079.
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  32. MICHALOPOULOU E, Clauser P, Gilbert FJ, Pijnappel RM, et al
    A survey by the European Society of Breast Imaging on radiologists' preferences regarding quality assurance measures of image interpretation in screening and diagnostic mammography.
    Eur Radiol. 2023;33:8103-8111.
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  33. RANGARAJAN K, Aggarwal P, Gupta DK, Dhanakshirur R, et al
    Deep learning for detection of iso-dense, obscure masses in mammographically dense breasts.
    Eur Radiol. 2023;33:8112-8121.
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  34. JOHNSON K, Olinder J, Rosso A, Andersson I, et al
    False-positive recalls in the prospective Malmo Breast Tomosynthesis Screening Trial.
    Eur Radiol. 2023;33:8089-8099.
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    October 2023
  35. TSAI HY, Kao YW, Wang JC, Tsai TY, et al
    Multitask deep learning on mammography to predict extensive intraductal component in invasive breast cancer.
    Eur Radiol. 2023 Oct 9. doi: 10.1007/s00330-023-10254.
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  36. ZHU Y, Ma Y, Zhai Z, Liu A, et al
    Radiomics in cone-beam breast CT for the prediction of axillary lymph node metastasis in breast cancer: a multi-center multi-device study.
    Eur Radiol. 2023 Oct 2. doi: 10.1007/s00330-023-10256.
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  37. KIM H, Choi JS, Kim K, Ko ES, et al
    Effect of artificial intelligence-based computer-aided diagnosis on the screening outcomes of digital mammography: a matched cohort study.
    Eur Radiol. 2023;33:7186-7198.
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  38. SELLA T, Simor B, Adler-Levy Y, Maly B, et al
    MRI prediction of neoadjuvant chemotherapy response is equivalent in patients with or without mammographic calcifications: a step towards adapting surgical approach?
    Eur Radiol. 2023;33:7168-7177.
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    September 2023
  39. CAI L, Sidey-Gibbons C, Nees J, Riedel F, et al
    Can multi-modal radiomics using pretreatment ultrasound and tomosynthesis predict response to neoadjuvant systemic treatment in breast cancer?
    Eur Radiol. 2023 Sep 14. doi: 10.1007/s00330-023-10238.
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  40. MA J, Chen K, Li S, Zhu L, et al
    MRI-based radiomic models to predict surgical margin status and infer tumor immune microenvironment in breast cancer patients with breast-conserving surgery: a multicenter validation study.
    Eur Radiol. 2023 Sep 2. doi: 10.1007/s00330-023-10144.
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  41. COZZI A, Di Leo G, Houssami N, Gilbert FJ, et al
    Screening and diagnostic breast MRI: how do they impact surgical treatment? Insights from the MIPA study.
    Eur Radiol. 2023;33:6213-6225.
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  42. LI JK, Fu NQ, Wang B, Jiang Y, et al
    Conventional ultrasound combined with contrast-enhanced ultrasound: could it be helpful for the diagnosis of thoracic wall recurrence after mastectomy?
    Eur Radiol. 2023;33:6482-6491.
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  43. COHEN EO, Korhonen KE, Sun J, Leung JWT, et al
    Comparison of prone and upright, stereotactic, and tomosynthesis-guided biopsies with secondary analysis of ultrasound-occult architectural distortions.
    Eur Radiol. 2023;33:6189-6203.
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  44. GOODBURN R, Kousi E, Sanders C, Macdonald A, et al
    Quantitative background parenchymal enhancement and fibro-glandular density at breast MRI: Association with BRCA status.
    Eur Radiol. 2023;33:6204-6212.
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    August 2023
  45. SASSI A, Salminen A, Jukkola A, Tervo M, et al
    Breast density and the likelihood of malignant MRI-detected lesions in women diagnosed with breast cancer.
    Eur Radiol. 2023 Aug 30. doi: 10.1007/s00330-023-10072.
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  46. LI Z, Ma Q, Gao Y, Qu M, et al
    Diagnostic performance of MRI for assessing axillary lymph node status after neoadjuvant chemotherapy in breast cancer: a systematic review and meta-analysis.
    Eur Radiol. 2023 Aug 24. doi: 10.1007/s00330-023-10155.
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  47. QIAN N, Jiang W, Guo Y, Zhu J, et al
    Breast cancer diagnosis from contrast-enhanced mammography using multi-feature fusion neural network.
    Eur Radiol. 2023 Aug 23. doi: 10.1007/s00330-023-10170.
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  48. GUO Y, Xie X, Tang W, Chen S, et al
    Noninvasive identification of HER2-low-positive status by MRI-based deep learning radiomics predicts the disease-free survival of patients with breast cancer.
    Eur Radiol. 2023 Aug 19. doi: 10.1007/s00330-023-09990.
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  49. HOTTAT NA, Badr DA, Ben Ghanem M, Besse-Hammer T, et al
    Assessment of whole-body MRI including diffusion-weighted sequences in the initial staging of breast cancer patients at high risk of metastases in comparison with PET-CT: a prospective cohort study.
    Eur Radiol. 2023 Aug 9. doi: 10.1007/s00330-023-10060.
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  50. HONDA M, Iima M
    Is the breast ADC category system a useful addition to BI-RADS?
    Eur Radiol. 2023;33:5398-5399.
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  51. BICKEL H, Clauser P, Pinker K, Helbich T, et al
    Introduction of a breast apparent diffusion coefficient category system (ADC-B) derived from a large multicenter MRI database.
    Eur Radiol. 2023;33:5400-5410.
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    July 2023
  52. DU Y, Cai M, Zha H, Chen B, et al
    Ultrasound radiomics-based nomogram to predict lymphovascular invasion in invasive breast cancer: a multicenter, retrospective study.
    Eur Radiol. 2023 Jul 31. doi: 10.1007/s00330-023-09995.
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  53. SEXAUER R, Hejduk P, Borkowski K, Ruppert C, et al
    Diagnostic accuracy of automated ACR BI-RADS breast density classification using deep convolutional neural networks.
    Eur Radiol. 2023;33:4589-4596.
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    June 2023
  54. MALHAIRE C, Selhane F, Saint-Martin MJ, Cockenpot V, et al
    Exploring the added value of pretherapeutic MR descriptors in predicting breast cancer pathologic complete response to neoadjuvant chemotherapy.
    Eur Radiol. 2023 Jun 15. doi: 10.1007/s00330-023-09797.
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  55. OHASHI A, Kataoka M, Iima M, Honda M, et al
    A multiparametric approach to predict triple-negative breast cancer including parameters derived from ultrafast dynamic contrast-enhanced MRI.
    Eur Radiol. 2023 Jun 8. doi: 10.1007/s00330-023-09730.
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  56. NISSAN N, Anaby D, Mahameed G, Bauer E, et al
    Ultrafast DCE-MRI for discriminating pregnancy-associated breast cancer lesions from lactation related background parenchymal enhancement.
    Eur Radiol. 2023 Jun 6. doi: 10.1007/s00330-023-09805.
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  57. BORDE T, Wu M, Ruschke S, Boehm C, et al
    Assessing breast density using the chemical-shift encoding-based proton density fat fraction in 3-T MRI.
    Eur Radiol. 2023;33:3810-3818.
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    May 2023
  58. GIORGI ROSSI P
    Excluding specificity from research and development priorities is delaying the AI adoption in breast cancer screening.
    Eur Radiol. 2023 May 23. doi: 10.1007/s00330-023-09733.
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  59. CARMONA-BOZO JC, Manavaki R, Miller JL, Brodie C, et al
    PET/MRI of hypoxia and vascular function in ER-positive breast cancer: correlations with immunohistochemistry.
    Eur Radiol. 2023 May 11. doi: 10.1007/s00330-023-09572.
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    April 2023
  60. BA R, Wang X, Zhang Z, Li Q, et al
    Diffusion-time dependent diffusion MRI: effect of diffusion-time on microstructural mapping and prediction of prognostic features in breast cancer.
    Eur Radiol. 2023 Apr 18. doi: 10.1007/s00330-023-09623.
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  61. JANNUSCH K, Lindemann ME, Bruckmann NM, Morawitz J, et al
    Towards a fast PET/MRI protocol for breast cancer imaging: maintaining diagnostic confidence while reducing PET and MRI acquisition times.
    Eur Radiol. 2023 Apr 12. doi: 10.1007/s00330-023-09580.
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  62. PLOUMEN RAW, de Mooij CM, Gommers S, Keymeulen KBMI, et al
    Imaging findings for response evaluation of ductal carcinoma in situ in breast cancer patients treated with neoadjuvant systemic therapy: a systematic review and meta-analysis.
    Eur Radiol. 2023 Apr 5. doi: 10.1007/s00330-023-09547.
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  63. WESSLING D, Mannlin S, Schwarz R, Hagen F, et al
    Background enhancement in contrast-enhanced spectral mammography (CESM): are there qualitative and quantitative differences between imaging systems?
    Eur Radiol. 2023;33:2945-2953.
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  64. GU Y, Xu W, Liu T, An X, et al
    Ultrasound-based deep learning in the establishment of a breast lesion risk stratification system: a multicenter study.
    Eur Radiol. 2023;33:2954-2964.
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    March 2023
  65. NISSAN N, Kulpanovich A, Agassi R, Allweis T, et al
    Probing lipids relaxation times in breast cancer using magnetic resonance spectroscopic fingerprinting.
    Eur Radiol. 2023 Mar 28. doi: 10.1007/s00330-023-09560.
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  66. YU FH, Miao SM, Li CY, Hang J, et al
    Pretreatment ultrasound-based deep learning radiomics model for the early prediction of pathologic response to neoadjuvant chemotherapy in breast cancer.
    Eur Radiol. 2023 Mar 28. doi: 10.1007/s00330-023-09555.
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  67. KOCH HW, Larsen M, Bartsch H, Kurz KD, et al
    Artificial intelligence in BreastScreen Norway: a retrospective analysis of a cancer-enriched sample including 1254 breast cancer cases.
    Eur Radiol. 2023 Mar 14. doi: 10.1007/s00330-023-09461.
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  68. CLAUSER P
    Clinical value of contralateral breast cancers detected by pre-operative MRI in patients diagnosed with DCIS: a population-based cohort study-commentary.
    Eur Radiol. 2023;33:2207-2208.
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  69. JUNGMANN F, Ziegelmayer S, Lohoefer FK, Metz S, et al
    Algorithmic transparency and interpretability measures improve radiologists' performance in BI-RADS 4 classification.
    Eur Radiol. 2023;33:1844-1851.
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  70. KEYMEULEN KBIM, Geurts SME, Kooreman LFS, Duijm LEM, et al
    Clinical value of contralateral breast cancers detected by pre-operative MRI in patients diagnosed with DCIS: a population-based cohort study.
    Eur Radiol. 2023;33:2209-2217.
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    February 2023
  71. RAHIMPOUR M, Saint Martin MJ, Frouin F, Akl P, et al
    Visual ensemble selection of deep convolutional neural networks for 3D segmentation of breast tumors on dynamic contrast enhanced MRI.
    Eur Radiol. 2023;33:959-969.
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    January 2023
  72. SCHIAFFINO S, Cozzi A
    Contrast-enhanced mammography-guided biopsy: why, when, and where we need it.
    Eur Radiol. 2023;33:414-416.
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  73. ALCANTARA R, Posso M, Pitarch M, Arenas N, et al
    Contrast-enhanced mammography-guided biopsy: technical feasibility and first outcomes.
    Eur Radiol. 2023;33:417-428.
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  74. IOTTI V, Giorgi Rossi P, Canovi L, Guberti M, et al
    Patient-centred care with self-compression mammography in clinical practice: a randomized trial compared to standard compression.
    Eur Radiol. 2023;33:450-460.
    >> Share

  75. SADEGHIPOUR N, Tseng J, Anderson K, Ayalasomayajula S, et al
    Tumor volume doubling time estimated from digital breast tomosynthesis mammograms distinguishes invasive breast cancers from benign lesions.
    Eur Radiol. 2023;33:429-439.
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    December 2022
  76. DAHLBLOM V, Dustler M, Tingberg A, Zackrisson S, et al
    Breast cancer screening with digital breast tomosynthesis: comparison of different reading strategies implementing artificial intelligence.
    Eur Radiol. 2022 Dec 11. doi: 10.1007/s00330-022-09316.
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  77. GOH Y, Chou CP, Chan CW, Buhari SA, et al
    Impact of contrast-enhanced mammography in surgical management of breast cancers for women with dense breasts: a dual-center, multi-disciplinary study in Asia.
    Eur Radiol. 2022;32:8226-8237.
    >> Share

  78. LARSEN M, Aglen CF, Hoff SR, Lund-Hanssen H, et al
    Possible strategies for use of artificial intelligence in screen-reading of mammograms, based on retrospective data from 122,969 screening examinations.
    Eur Radiol. 2022;32:8238-8246.
    >> Share

  79. JING X, Wielema M, Cornelissen LJ, van Gent M, et al
    Using deep learning to safely exclude lesions with only ultrafast breast MRI to shorten acquisition and reading time.
    Eur Radiol. 2022;32:8706-8715.
    >> Share

    November 2022
  80. LIU HQ, Lin SY, Song YD, Mai SY, et al
    Machine learning on MRI radiomic features: identification of molecular subtype alteration in breast cancer after neoadjuvant therapy.
    Eur Radiol. 2022 Nov 23. doi: 10.1007/s00330-022-09264.
    >> Share

  81. NISSAN N, Massasa EEM, Bauer E, Halshtok-Neiman O, et al
    MRI can accurately diagnose breast cancer during lactation.
    Eur Radiol. 2022 Nov 8. pii: 10.1007/s00330-022-09234.
    >> Share

  82. COZZI A, Schiaffino S, Fanizza M, Magni V, et al
    Contrast-enhanced mammography for the assessment of screening recalls: a two-centre study.
    Eur Radiol. 2022;32:7388-7399.
    >> Share

  83. RONG X, Kang Y, Xue J, Han P, et al
    Value of contrast-enhanced mammography combined with the Kaiser score for clinical decision-making regarding tomosynthesis BI-RADS 4A lesions.
    Eur Radiol. 2022;32:7439-7447.
    >> Share

  84. PEREZ-LEON D, Posso M, Louro J, Ejarque B, et al
    Does the patient-assisted compression mode affect the mammography quality? A within-woman randomized controlled trial.
    Eur Radiol. 2022;32:7470-7479.
    >> Share

  85. ARENAS N, Alcantara R, Posso M, Louro J, et al
    Comparison of technical parameters and women's experience between self-compression and standard compression modes in mammography screening: a single-blind randomized clinical trial.
    Eur Radiol. 2022;32:7480-7487.
    >> Share

  86. LEE SE, Han K, Yoon JH, Youk JH, et al
    Depiction of breast cancers on digital mammograms by artificial intelligence-based computer-assisted diagnosis according to cancer characteristics.
    Eur Radiol. 2022;32:7400-7408.
    >> Share

  87. DUIJM LEM, Strobbe LJA, van Breest Smallenburg V, Vreuls W, et al
    Failure of stereotactic core needle biopsy in women recalled for suspicious calcifications at screening mammography: frequency, causes, and final outcome in a multi-institutional, observational follow-up study.
    Eur Radiol. 2022;32:7420-7429.
    >> Share

    September 2022
  88. FONG W, Tan L, Tan C, Wang H, et al
    Predicting the risk of axillary lymph node metastasis in early breast cancer patients based on ultrasonographic-clinicopathologic features and the use of nomograms: a prospective single-center observational study.
    Eur Radiol. 2022 Sep 28. pii: 10.1007/s00330-022-08855.
    >> Share

  89. NIU Z, Gao Y, Xiao M, Mao F, et al
    Contrast-enhanced lymphatic US can improve the preoperative diagnostic performance for sentinel lymph nodes in early breast cancer.
    Eur Radiol. 2022 Sep 24. pii: 10.1007/s00330-022-09139.
    >> Share

  90. XU Z, Ding Y, Zhao K, Han C, et al
    Correction to: MRI characteristics of breast edema for assessing axillary lymph node burden in early-stage breast cancer: a retrospective bicentric study.
    Eur Radiol. 2022 Sep 8. pii: 10.1007/s00330-022-09076.
    >> Share

  91. KAPSNER LA, Ohlmeyer S, Folle L, Laun FB, et al
    Automated artifact detection in abbreviated dynamic contrast-enhanced (DCE) MRI-derived maximum intensity projections (MIPs) of the breast.
    Eur Radiol. 2022;32:5997-6007.
    >> Share

  92. AN Y, Mao G, Ao W, Mao F, et al
    Can DWI provide additional value to Kaiser score in evaluation of breast lesions.
    Eur Radiol. 2022;32:5964-5973.
    >> Share

    August 2022
  93. MA Y, Liu A, Zhang Y, Zhu Y, et al
    Comparison of background parenchymal enhancement (BPE) on contrast-enhanced cone-beam breast CT (CE-CBBCT) and breast MRI.
    Eur Radiol. 2022;32:5773-5782.
    >> Share

  94. HORVAT JV, Sevilimedu V, Becker AS, Perez-Johnston R, et al
    Frequency and outcomes of MRI-detected axillary adenopathy following COVID-19 vaccination.
    Eur Radiol. 2022;32:5752-5758.
    >> Share

  95. LIU Z, Liang K, Zhang L, Lai C, et al
    Small lesion classification on abbreviated breast MRI: training can improve diagnostic performance and inter-reader agreement.
    Eur Radiol. 2022;32:5742-5751.
    >> Share

    July 2022
  96. POTSCH N, Korajac A, Stelzer P, Kapetas P, et al
    Breast MRI: does a clinical decision algorithm outweigh reader experience?
    Eur Radiol. 2022 Jul 19. pii: 10.1007/s00330-022-09015.
    >> Share

  97. HWANGBO L, Kim JY, Kim JJ, Lee NK, et al
    Changes in kinetic heterogeneity of breast cancer via computer-aided diagnosis on MRI predict the pathological response to neoadjuvant systemic therapy.
    Eur Radiol. 2022 Jul 18. pii: 10.1007/s00330-022-08998.
    >> Share

  98. GOTO M, Le Bihan D, Sakai K, Yamada K, et al
    The diffusion MRI signature index is highly correlated with immunohistochemical status and molecular subtype of invasive breast carcinoma.
    Eur Radiol. 2022;32:4879-4888.
    >> Share

  99. WANG L, Chang L, Luo R, Cui X, et al
    An artificial intelligence system using maximum intensity projection MR images facilitates classification of non-mass enhancement breast lesions.
    Eur Radiol. 2022;32:4857-4867.
    >> Share

  100. LEE M, Lee SE, Kim HR, Kim MJ, et al
    Cancer yield and imaging features of probably benign calcifications at digital magnification view.
    Eur Radiol. 2022;32:4909-4918.
    >> Share

  101. HEJDUK P, Marcon M, Unkelbach J, Ciritsis A, et al
    Fully automatic classification of automated breast ultrasound (ABUS) imaging according to BI-RADS using a deep convolutional neural network.
    Eur Radiol. 2022;32:4868-4878.
    >> Share

  102. DOMINIQUE C, Callonnec F, Berghian A, Defta D, et al
    Deep learning analysis of contrast-enhanced spectral mammography to determine histoprognostic factors of malignant breast tumours.
    Eur Radiol. 2022;32:4834-4844.
    >> Share

    June 2022
  103. SHENG DL, Shen XG, Shi ZT, Chang C, et al
    Survival outcome assessment for triple-negative breast cancer: a nomogram analysis based on integrated clinicopathological, sonographic, and mammographic characteristics.
    Eur Radiol. 2022 Jun 27. pii: 10.1007/s00330-022-08910.
    >> Share

  104. YOON J, Lee HS, Kim MJ, Park VY, et al
    AI-CAD for differentiating lesions presenting as calcifications only on mammography: outcome analysis incorporating the ACR BI-RADS descriptors for calcifications.
    Eur Radiol. 2022 Jun 24. pii: 10.1007/s00330-022-08961.
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  105. CHEN ZW, Zhao YF, Liu HR, Zhou JJ, et al
    Assessment of breast lesions by the Kaiser score for differential diagnosis on MRI: the added value of ADC and machine learning modeling.
    Eur Radiol. 2022 Jun 21. pii: 10.1007/s00330-022-08899.
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  106. XU Z, Ding Y, Zhao K, Han C, et al
    MRI characteristics of breast edema for assessing axillary lymph node burden in early-stage breast cancer: a retrospective bicentric study.
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  107. BERG WA
    Breast MRI for "the Masses".
    Eur Radiol. 2022;32:4034-4035.
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  108. PFOB A, Sidey-Gibbons C, Barr RG, Duda V, et al
    The importance of multi-modal imaging and clinical information for humans and AI-based algorithms to classify breast masses (INSPiRED 003): an international, multicenter analysis.
    Eur Radiol. 2022;32:4101-4115.
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  109. WEI Q, Yan YJ, Wu GG, Ye XR, et al
    The diagnostic performance of ultrasound computer-aided diagnosis system for distinguishing breast masses: a prospective multicenter study.
    Eur Radiol. 2022;32:4046-4055.
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  110. TSUCHIYA M, Masui T, Terauchi K, Yamada T, et al
    MRI-based radiomics analysis for differentiating phyllodes tumors of the breast from fibroadenomas.
    Eur Radiol. 2022;32:4090-4100.
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    May 2022
  111. LO GULLO R, Sevilimedu V, Baltzer P, Le Bihan D, et al
    A survey by the European Society of Breast Imaging on the implementation of breast diffusion-weighted imaging in clinical practice.
    Eur Radiol. 2022 May 4. pii: 10.1007/s00330-022-08833.
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    April 2022
  112. WANG Q, Chen H, Luo G, Li B, et al
    Performance of novel deep learning network with the incorporation of the automatic segmentation network for diagnosis of breast cancer in automated breast ultrasound.
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  113. TERNIFI R, Wang Y, Gu J, Polley EC, et al
    Ultrasound high-definition microvasculature imaging with novel quantitative biomarkers improves breast cancer detection accuracy.
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  114. SECHOPOULOS I, Abbey CK, van der Waal D, Geertse T, et al
    Evaluation of reader performance during interpretation of breast cancer screening: the Recall and detection Of breast Cancer in Screening (ROCS) trial study design.
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  115. TOLLENS F, Baltzer PAT, Dietzel M, Schnitzer ML, et al
    Economic potential of abbreviated breast MRI for screening women with dense breast tissue for breast cancer.
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  116. RIVLIN M, Anaby D, Nissan N, Zaiss M, et al
    Breast cancer imaging with glucosamine CEST (chemical exchange saturation transfer) MRI: first human experience.
    Eur Radiol. 2022 Apr 14. pii: 10.1007/s00330-022-08772.
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  117. WANG X, Tan Y, Liu D, Shen H, et al
    Chemotherapy-associated steatohepatitis was concomitant with epicardial adipose tissue volume increasing in breast cancer patients who received neoadjuvant chemotherapy.
    Eur Radiol. 2022 Apr 8. pii: 10.1007/s00330-022-08581.
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  118. EIFER M, Pinian H, Klang E, Alhoubani Y, et al
    FDG PET/CT radiomics as a tool to differentiate between reactive axillary lymphadenopathy following COVID-19 vaccination and metastatic breast cancer axillary lymphadenopathy: a pilot study.
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  119. BHALUDIN BN, Tunariu N, Koh DM, Messiou C, et al
    A review on the added value of whole-body MRI in metastatic lobular breast cancer.
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  120. HUANG JX, Lin SY, Ou Y, Shi CG, et al
    Combining conventional ultrasound and sonoelastography to predict axillary status after neoadjuvant chemotherapy for breast cancer.
    Eur Radiol. 2022 Apr 2. pii: 10.1007/s00330-022-08751.
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  121. MARTINIUSSEN MA, Sagstad S, Larsen M, Larsen ASF, et al
    Screen-detected and interval breast cancer after concordant and discordant interpretations in a population based screening program using independent double reading.
    Eur Radiol. 2022 Apr 2. pii: 10.1007/s00330-022-08711.
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  122. ZHU Y, O'Connell AM, Ma Y, Liu A, et al
    Dedicated breast CT: state of the art-Part II. Clinical application and future outlook.
    Eur Radiol. 2022;32:2286-2300.
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    March 2022
  123. DU S, Gao S, Zhao R, Liu H, et al
    Contrast-free MRI quantitative parameters for early prediction of pathological response to neoadjuvant chemotherapy in breast cancer.
    Eur Radiol. 2022 Mar 10. pii: 10.1007/s00330-022-08667.
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  124. MANN RM, Athanasiou A, Baltzer PAT, Camps-Herrero J, et al
    Breast cancer screening in women with extremely dense breasts recommendations of the European Society of Breast Imaging (EUSOBI).
    Eur Radiol. 2022 Mar 8. pii: 10.1007/s00330-022-08617.
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  125. LINCK PA, Garnier C, Depetiteville MP, MacGrogan G, et al
    Impact of the COVID-19 lockdown in France on the diagnosis and staging of breast cancers in a tertiary cancer centre.
    Eur Radiol. 2022;32:1644-1651.
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  126. YI C, Tang Y, Ouyang R, Zhang Y, et al
    The added value of an artificial intelligence system in assisting radiologists on indeterminate BI-RADS 0 mammograms.
    Eur Radiol. 2022;32:1528-1537.
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  127. LI JW, Cao YC, Zhao ZJ, Shi ZT, et al
    Prediction for pathological and immunohistochemical characteristics of triple-negative invasive breast carcinomas: the performance comparison between quantitative and qualitative sonographic feature analysis.
    Eur Radiol. 2022;32:1590-1600.
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  128. YI Z, Xie M, Shi G, Cheng Z, et al
    Assessment of quantitative dynamic contrast-enhanced MRI in distinguishing different histologic grades of breast phyllode tumor.
    Eur Radiol. 2022;32:1601-1610.
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  129. BRANCATO B, Peruzzi F, Saieva C, Schiaffino S, et al
    Mammography self-evaluation online test for screening readers: an Italian Society of Medical Radiology (SIRM) initiative.
    Eur Radiol. 2022;32:1624-1633.
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    February 2022
  130. GWEON HM, Eun NL, Youk JH, Jeong J, et al
    Added value of abbreviated breast magnetic resonance imaging for assessing suspicious microcalcification on screening mammography-a prospective study.
    Eur Radiol. 2022;32:815-821.
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  131. MACKENZIE A, Thomson EL, Mitchell M, Elangovan P, et al
    Virtual clinical trial to compare cancer detection using combinations of 2D mammography, digital breast tomosynthesis and synthetic 2D imaging.
    Eur Radiol. 2022;32:806-814.
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    January 2022
  132. KELAHAN LC, Kim D, Soliman M, Avery RJ, et al
    Role of hepatic metastatic lesion size on inter-reader reproducibility of CT-based radiomics features.
    Eur Radiol. 2022 Jan 26. pii: 10.1007/s00330-021-08526.
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  133. XU H, Liu J, Chen Z, Wang C, et al
    Intratumoral and peritumoral radiomics based on dynamic contrast-enhanced MRI for preoperative prediction of intraductal component in invasive breast cancer.
    Eur Radiol. 2022 Jan 25. pii: 10.1007/s00330-022-08539.
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  134. MAO N, Shi Y, Lian C, Wang Z, et al
    Intratumoral and peritumoral radiomics for preoperative prediction of neoadjuvant chemotherapy effect in breast cancer based on contrast-enhanced spectral mammography.
    Eur Radiol. 2022 Jan 23. pii: 10.1007/s00330-021-08414.
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  135. KIM JH, Park VY, Shin HJ, Kim MJ, et al
    Ultrafast dynamic contrast-enhanced breast MRI: association with pathologic complete response in neoadjuvant treatment of breast cancer.
    Eur Radiol. 2022 Jan 22. pii: 10.1007/s00330-021-08530.
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  136. HOTTAT NA, Badr DA, Lecomte S, Besse-Hammer T, et al
    Value of diffusion-weighted MRI in predicting early response to neoadjuvant chemotherapy of breast cancer: comparison between ROI-ADC and whole-lesion-ADC measurements.
    Eur Radiol. 2022 Jan 11. pii: 10.1007/s00330-021-08462.
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  137. CANELO-AYBAR C, Taype-Rondan A, Zafra-Tanaka JH, Rigau D, et al
    Correction to: Preoperative breast magnetic resonance imaging in patients with ductal carcinoma in situ: a systematic review for the European Commission Initiative on Breast Cancer (ECIBC).
    Eur Radiol. 2022 Jan 7. pii: 10.1007/s00330-021-08489.
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  138. HUANG F, Brezden-Masley C, Chan KKW, Barfett JJ, et al
    Evaluation of left atrial remodeling using cardiovascular magnetic resonance imaging in breast cancer patients treated with adjuvant trastuzumab.
    Eur Radiol. 2022 Jan 6. pii: 10.1007/s00330-021-08466.
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  139. KIM J, Han BK, Ko EY, Ko ES, et al
    Prediction of pathologic complete response on MRI in patients with breast cancer receiving neoadjuvant chemotherapy according to molecular subtypes.
    Eur Radiol. 2022 Jan 6. pii: 10.1007/s00330-021-08461.
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  140. CLAUSER P, Baltzer PAT, Kapetas P, Woitek R, et al
    One view or two views for wide-angle tomosynthesis with synthetic mammography in the assessment setting?
    Eur Radiol. 2022;32:661-670.
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  141. WANG S, Sun Y, Li R, Mao N, et al
    Diagnostic performance of perilesional radiomics analysis of contrast-enhanced mammography for the differentiation of benign and malignant breast lesions.
    Eur Radiol. 2022;32:639-649.
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  142. CRIVELLARO P, Tafur M, George R, Muradali D, et al
    Diagnostic interval for non-screening patients undergoing mammography during the COVID-19 pandemic.
    Eur Radiol. 2022;32:613-620.
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    December 2021
  143. PELISSIER M, Ambarki K, Salleron J, Henrot P, et al
    Maximum slope using ultrafast breast DCE-MRI at 1.5 Tesla: a potential tool for predicting breast lesion aggressiveness.
    Eur Radiol. 2021;31:9556-9566.
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  144. BACKMANN HA, Larsen M, Danielsen AS, Hofvind S, et al
    Does it matter for the radiologists' performance whether they read short or long batches in organized mammographic screening?
    Eur Radiol. 2021;31:9548-9555.
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  145. GIANNOTTI E, James JJ, Chen Y, Sun R, et al
    Effectiveness of percutaneous vacuum-assisted excision (VAE) of breast lesions of uncertain malignant potential (B3 lesions) as an alternative to open surgical biopsy.
    Eur Radiol. 2021;31:9540-9547.
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  146. MESUROLLE B, El Khoury M, Travade A, Bagard C, et al
    Is there any added value to substitute the 2D digital MLO projection for a MLO tomosynthesis projection and its synthetic view when a 2D standard digital mammography is used in a one-stop-shop immediate reading mammography screening?
    Eur Radiol. 2021;31:9529-9539.
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  147. BITENCOURT AGV, Pires BS, Calsavara VF, Negrao EMS, et al
    Prognostic value of response evaluation based on breast MRI after neoadjuvant treatment: a retrospective cohort study.
    Eur Radiol. 2021;31:9520-9528.
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    November 2021
  148. LI Y, Chen Y, Zhao R, Ji Y, et al
    Development and validation of a nomogram based on pretreatment dynamic contrast-enhanced MRI for the prediction of pathologic response after neoadjuvant chemotherapy for triple-negative breast cancer.
    Eur Radiol. 2021 Nov 12. pii: 10.1007/s00330-021-08291.
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  149. VAN WINKEL SL, Rodriguez-Ruiz A, Appelman L, Gubern-Merida A, et al
    Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study.
    Eur Radiol. 2021;31:8682-8691.
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    October 2021
  150. THOMPSON BM, Chala LF, Shimizu C, Mano MS, et al
    Pre-treatment MRI tumor features and post-treatment mammographic findings: may they contribute to refining the prediction of pathologic complete response in post-neoadjuvant breast cancer patients with radiologic complete response on MRI?
    Eur Radiol. 2021 Oct 30. pii: 10.1007/s00330-021-08290.
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  151. HEYWANG-KOBRUNNER SH, Jansch A, Hacker A, Weinand S, et al
    Digital breast tomosynthesis (DBT) plus synthesised two-dimensional mammography (s2D) in breast cancer screening is associated with higher cancer detection and lower recalls compared to digital mammography (DM) alone: results of a systematic review an
    Eur Radiol. 2021 Oct 25. pii: 10.1007/s00330-021-08308.
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  152. JIANG M, Li CL, Luo XM, Chuan ZR, et al
    Radiomics model based on shear-wave elastography in the assessment of axillary lymph node status in early-stage breast cancer.
    Eur Radiol. 2021 Oct 20. pii: 10.1007/s00330-021-08330.
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  153. GU J, Tong T, He C, Xu M, et al
    Deep learning radiomics of ultrasonography can predict response to neoadjuvant chemotherapy in breast cancer at an early stage of treatment: a prospective study.
    Eur Radiol. 2021 Oct 15. pii: 10.1007/s00330-021-08293.
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  154. SKARPING I, Larsson M, Fornvik D
    Analysis of mammograms using artificial intelligence to predict response to neoadjuvant chemotherapy in breast cancer patients: proof of concept.
    Eur Radiol. 2021 Oct 15. pii: 10.1007/s00330-021-08306.
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  155. MA M, Liu R, Wen C, Xu W, et al
    Predicting the molecular subtype of breast cancer and identifying interpretable imaging features using machine learning algorithms.
    Eur Radiol. 2021 Oct 13. pii: 10.1007/s00330-021-08271.
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  156. SARDANELLI F, Trimboli RM, Houssami N, Gilbert FJ, et al
    Magnetic resonance imaging before breast cancer surgery: results of an observational multicenter international prospective analysis (MIPA).
    Eur Radiol. 2021 Oct 13. pii: 10.1007/s00330-021-08240.
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