New Frontiers in Oncological Imaging With Computed Tomography: From Morphology to Function.

Area of Science:

• Medical Imaging
• Radiology
• Oncology

Background:

• Computed Tomography (CT) technology has undergone significant advancements.
• These evolutions impact various applications, particularly in oncological imaging.
• Optimizing oncological imaging protocols is crucial for accurate cancer diagnosis and management.

Purpose of the Study:

• To highlight the latest technological evolutions in CT.
• To discuss their specific applications and benefits in oncological imaging.
• To explain how these innovations optimize imaging protocols.

Main Methods:

• Utilizing new powerful X-ray tube technology for low-kV acquisitions.
• Employing iterative reconstruction algorithms and artificial intelligence for image noise management.
• Leveraging spectral CT (dual-energy and photon counting CT) and perfusion CT for functional information.

Main Results:

• Low-kilovoltage (kV) acquisitions are now feasible, potentially reducing radiation dose and improving contrast enhancement.
• Iterative reconstruction and AI effectively manage image noise, leading to clearer images.
• Spectral CT and perfusion CT provide valuable functional and quantitative data beyond anatomical information.

Conclusions:

• Modern CT hardware and software innovations significantly enhance oncological imaging capabilities.
• These advancements allow for optimized imaging protocols, improved image quality, and richer diagnostic information.
• The integration of low-kV imaging, AI, and advanced spectral/perfusion techniques represents a substantial leap forward in cancer imaging.