The Response Assessment in Pediatric Neuro-Oncology (RAPNO) criteria provide an important framework for evaluating treatment efficacy and tumour progression in clinical studies of paediatric brain tumours. As artificial intelligence (AI) rapidly transforms clinical practice, integrating AI into the RAPNO framework presents a unique opportunity to enhance quantitative, data-driven approaches for response assessment. However, successful clinical implementation faces challenges, including variability…
[Policy Review] Artificial Intelligence for Response Assessment in Pediatric Neuro-Oncology (AI-RAPNO), part 2: challenges, opportunities, and recommendations for clinical translation
The Lancet Oncology | | Anahita Fathi Kazerooni, Ariana M Familiar, Mariam Aboian, Sarah C Brüningk, Arastoo Vossough, Marius George Linguraru, Raymond Y Huang, Darren Hargrave, Andrew C Peet, Adam C Resnick, Phillip B Storm, David Mirsky, Kristen W Yeom, Michael Weller, Michael Prados, Susan M Chang, Sabine Mueller, Javier E Villanueva-Meyer, Spyridon Bakas, Jason Fangusaro, Benjamin H Kann, Ali Nabavizadeh, Response Assessment in Pediatric Neuro-Oncology (RAPNO) group
Topics: blood-cancer