Diagnostic Imaging in Colorectal Cancer

Dear Colleagues,

Imaging plays a crucial role in the complex approach to colorectal cancer, based on screening, diagnosis, staging, restaging and monitoring for recurrence. The push for standardized reporting systems by scientific societies is to refine the detection of small lesions and reduce report variability.

Artificial intelligence (AI), radiomics and PET/MRI are at the forefront of advances in colorectal cancer imaging. In this context, texture analysis is a groundbreaking tool that allows for software to extract additional features that are not visible to the human eye in ultrasound, CT and MRI images. This quantitative approach in colorectal cancer assays can present a new era in diagnostics, potentially augmented by AI for data management.

PET/MRI has emerged as a superior imaging modality, offering a fusion of detailed anatomical views from MRI with functional insights from PET scans. This combination has been proven to improve the accuracy of PET/CT and MRI for staging tumor spread (T and N staging), supporting its use in determining the suitability for less invasive rectal cancer treatments.

This Special Issue aims to collate state-of-the-art studies targeting advancements in colorectal cancer multimodal imaging that can lead to improved diagnostic accuracy and refine colorectal cancer assessment.

Dr. Filippo Crimì
Dr. Chiara Zanon
Guest Editors

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• colorectal cancer
• artificial intelligence
• texture analysis
• ultrasound
• magnetic resonance imaging
• PET/MRI