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Usefulness of a Combination DBT (Digital Breast Tomosynthesis) and Automated Volume Analysis of Dynamic Contrast-Enhanced Breast (DCEB) MRI in Evaluation of Response to Neoadjuvant Chemotherapy (NAC)

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Breast Imaging (IWDM 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8539))

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Abstract

We evaluated the usefulness of DBT and automated volume analysis with DCEB MRI to assess its potential role in estimating viable tumor volume in pre-and pos-t NAC images in response to treatment in comparison with FFDM and US. Twenty women having 21 lesions, in total were recruited for this study.The diagnostic procedures were performed within one month prior to surgery. FFDM, DBT, US and DCEB MRI were performed on each of the patients before and after NAC. The imaging data was analyzed by a medical workstation dedicated to breast MRI imaging. Utilizing the dynamic contrast images from 1st to 4th phase, volume statistics with VOI (volume of interest) and the volume was automatically calculated and evaluated as to the efficacy of NAC. DBT has the advantage of providing macroscopic pathological fidings in total without utitiling contrast medium. On the other hand, DCEB MRI has the advantage of providing numerical and detailed vascularity details of viable areas. In accordance with the results, a combination of DBT and automated volume analysis of DCEB MRI will contribute to more accurate diagnosis in the assessment of pathological response to NAC.

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© 2014 Springer International Publishing Switzerland

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Uchiyama, N. et al. (2014). Usefulness of a Combination DBT (Digital Breast Tomosynthesis) and Automated Volume Analysis of Dynamic Contrast-Enhanced Breast (DCEB) MRI in Evaluation of Response to Neoadjuvant Chemotherapy (NAC). In: Fujita, H., Hara, T., Muramatsu, C. (eds) Breast Imaging. IWDM 2014. Lecture Notes in Computer Science, vol 8539. Springer, Cham. https://doi.org/10.1007/978-3-319-07887-8_44

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  • DOI: https://doi.org/10.1007/978-3-319-07887-8_44

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07886-1

  • Online ISBN: 978-3-319-07887-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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