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Published online: 2024-04-15

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Artificial intelligence – an aid for physicians in chordoma management? A systematic review of current applications

Paweł M. Łajczak1, Kamil Jóźwik1


Introduction. Chordoma, a rare neoplasm originating from the notochord, poses diagnostic and therapeutic challenges due to its slow growth and complex anatomical locations. The advent of artificial intelligence (AI) offers promising avenues for improving chordoma management through enhanced diagnosis, prognostication, and treatment optimization. 

Methods. This systematic review adhered to the PRISMA guidelines and focused on AI applications in chordoma management. A comprehensive literature search was conducted across seven major databases, and relevant data were extracted, including publication details, study aims, AI techniques employed, validation methods, and study results. 

Results. AI techniques, including machine learning and deep learning, demonstrated efficacy in differentiating chordomas fromother neoplasms, segmenting tumor boundaries, predicting patient survival and recurrence, and guiding therapeutic strategies. Integration of radiomic features, clinical characteristics, and imagingmodalities facilitated accurate diagnosis and prognostication. Additionally, AI-driven approaches enabled drug repurposing and optimized treatment planning, particularly in radiation therapy. 

Conclusions. The findings highlight the transformative potential of AI in revolutionizing chordoma management, offering personalized and precise approaches for diagnosis, prognostication, and therapeutic intervention. Collaborative efforts between clinicians, researchers, and technologists are essential to validate AI-driven algorithms and introduce them into clinical practice. Further research is warranted to address limitations and ensure the ethical deployment of AI technologies in healthcare to improve outcomes for chordoma patients. 

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