The text discusses the challenges in diagnosing idiopathic intracranial hypertension (IIH) and spontaneous intracranial hypotension (SIH), which can cause ongoing symptoms after Chiari malformation (CM) I surgery, and introduces the use of artificial intelligence (AI) to aid in this diagnosis through a new workflow called MaChiP 1.0.
It emphasizes the importance of utilizing both upstream and downstream MRI findings to better identify and categorize Chiari malformation subtypes and related conditions, particularly utilizing upright imaging for better assessment.
The authors outline a systematic review of relevant literature on machine learning in Chiari I malformation and propose specific MRI criteria to help differentiate between primary and secondary causes of the condition for improved diagnosis