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Dual Energy CT

Dual Energy CT (Dual Energy Computed Tomography-DECT) is an advanced imaging technique that utilizes two different X-ray energy spectra to enhance the diagnostic capabilities of traditional computed tomography (CT). This dual-energy approach allows for improved tissue characterization, contrast resolution, and artifact reduction compared to conventional single-energy CT scans. By acquiring images at two different energy levels, DECT provides additional information about the composition of tissues, aiding in the differentiation of materials with similar X-ray attenuation values. This capability is particularly valuable in various clinical applications, including oncology, cardiovascular imaging, musculoskeletal assessments, and virtual non-contrast imaging. In oncology, dual-energy CT facilitates better characterization of lesions, helping to distinguish between benign and malignant tissues. It also allows for improved visualization of iodinated contrast agents, enhancing the assessment of vascular structures and perfusion in dynamic studies.

DECT is especially beneficial in cardiovascular imaging, where it enables accurate assessment of coronary artery disease, detection of myocardial perfusion defects, and evaluation of vascular calcifications. Furthermore, in musculoskeletal imaging, DECT aids in assessing bone composition, detecting uric acid crystals in gout, and distinguishing between various soft tissue components. The versatility of DECT extends to its application in virtual non-contrast imaging, reducing the need for multiple scans and minimizing radiation exposure in certain clinical scenarios. The ongoing evolution of dual-energy CT technology continues to refine its capabilities, with advancements in hardware and software contributing to improved image quality and diagnostic accuracy. These innovations include rapid kV switching, dual-source CT systems, and sophisticated post-processing algorithms. As DECT becomes more widely available, its integration into routine clinical practice is expected to enhance diagnostic confidence and expand its utility across a spectrum of medical specialties, ultimately contributing to more precise and comprehensive patient care.

Committee Members
Speaker at International Cancer Conference 2026 - Rajvir Dahiya

Rajvir Dahiya

University of California San Francisco, United States
Speaker at International Cancer Conference 2026 - Patricia Tai

Patricia Tai

UpToDate, Canada
Speaker at International Cancer Conference 2026 - Jose Manuel Cervera Grau

Jose Manuel Cervera Grau

Preclinical Lab and Computational Drug Discovery Program, Relayer Biotech Inc, Spain

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