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  • Breast MRI: State of the Art and Future Directions
      • GET 20% OFF

      • The discount is only available for 'Alert of Favourite Topics' newsletter recipients.
      • Publisher's listprice EUR 140.00
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        58 065 Ft (55 300 Ft + 5% VAT)
      • Discount 20% (cc. 11 613 Ft off)
      • Discounted price 46 452 Ft (44 240 Ft + 5% VAT)

    58 065 Ft

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    printed on demand

    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Product details:

    • Publisher Elsevier Science
    • Date of Publication 22 September 2022

    • ISBN 9780128227299
    • Binding Paperback
    • No. of pages644 pages
    • Size 235x191 mm
    • Weight 1310 g
    • Language English
    • Illustrations 105 illustrations (80 in full color)
    • 298

    Categories

    Long description:

    Breast MRI: State of the Art and Future Directions provides a comprehensive overview of the current applications of breast MRI, including abbreviated MRI, as well as presenting technical recommendations, practical implementation and associated challenges in clinical routine. In addition, the book introduces novel MRI techniques, multimodality imaging, and advanced image processing coupled with AI, reviewing their potential for impeding and future clinical implementation. This book is a complete reference on state-of-the-art breast MRI methods suitable for MRI researchers, radiographers and clinicians.

    Breast cancer is one of the leading causes of death among women with early detection being the key to improved prognosis and survival. Magnetic resonance imaging (MRI) of the breast is undisputedly the most sensitive imaging method to detect cancer, with a higher detection rate than mammography, digital breast tomosynthesis, and ultrasound.

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    Table of Contents:

    Section 1. Performance and Interpretation of Breast MRI
    1. Breast Magnetic Resonance Imaging Protocols
    i.Abbreviated and Ultrafast MRI
    ii.Multiparametric MRI in clinical practice
    2. Artifacts
    3. BI-RADS
    4. The Kaiser score: an evidence-based clinical decision rule for dynamic contrast-enhanced breast MRI
    5. Background parenchymal enhancement

    Section 2. MRI Characteristics of Common Breast Lesions
    6. Benign
    7. High-risk
    8. DCIS
    9. Invasive cancers

    Section 3. Clinical Indications for Breast MRI
    10. Screening
    11. Staging and treatment planning
    12. Response assessment to neoadjuvant therapy
    13. Follow-up: Posttreatment changes and Recurrent Breast Cancer
    14. Breast Augmentation and Post-mastectomy Autologous Breast Reconstruction
    15. Problem Solving
    16. Cancer of Unknown Primary including Imaging of the Axilla

    Section 4: Breast Magnetic Resonance Imaging-guided Interventions and Therapy
    17. Biopsy including MRI-directed US and rad-path correlation
    18. Monitoring Therapy
    Future Directons

    Section 5. Advanced and Emerging Approaches
    19. Non-contrast MRI
    20. Ultra-high field magnets
    21. Pharmacokinetic modelling
    22. Diffusion MRI of the breast: standard and advanced techniques
    23. Proton Magnetic Resonance Spectroscopy
    24. Emerging MRI Techniques: CEST, BOLD, Sodium, Phospohorus MRS, Lipid MRS, HP MRI

    Section 6: Hybrid Imaging and Alternative Techniques
    25. PET/MRI hybrid imaging and targeted tracers
    26. Alternative techniques: CEM and MBI

    Section 7: Prognostic and Predictive MR imaging biomarkers
    27. MRI Radiomics and Radiogenomics for Breast Cancer
    28. Artificial Intelligence and Deep Learning

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