Advancements in colorectal cancer detection: The role of immuno-positron emission tomography, immuno-single-photon emission computed tomography, and machine learning applications

Abstract

Colorectal cancer (CRC) ranks as the world’s second most prevalent cancer and third in mortality. Detection and diagnosis are crucial in research and clinical settings. While colonoscopy and computed tomographic colonography are widely used for identifying organic lesions, positron emission tomography (PET) and single-photon emission computed tomography (SPECT) offer superior visualization of molecular changes. These immuno-PET and immuno-SPECT techniques surpass conventional [¹⁸F] Fluorodeoxyglucose PET/CT in specificity and sensitivity, improving CRC diagnostics and supporting therapeutic strategies. This review emphasizes the role of immuno-PET/SPECT in CRC diagnosis and establishing a foundation for therapeutic strategies, facilitating hierarchical management through the identification of treatment-responsive populations, prediction of therapeutic outcomes, and support for intraoperative imaging. This review introduces the preclinical and clinical utility of immunoconjugates for detecting colorectal adenomas, and primary, metastatic, or recurrent CRC, focusing on specific CRC cell targets like the epidermal growth factor receptor and carcinoembryonic antigen. The review also covers various mAb-based immunoconjugates and engineered mAb fragments, including diabodies and minibodies. Finally, it looks into the great promise of machine learning in PET or SPECT and it addresses the challenges of translating preclinical successes into clinical practice for colorectal adenoma diagnosis, proposing potential solutions and directions for future research.

Keywords

colorectal cancer / diagnosis / immuno-PET / immuno-SPECT / machine learning / radiomics

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