Cranial Neuropathies—Easy to See, Hard to Diagnose: Toward an Integrated Diagnostic Framework for Rare Conditions

Purpose of Review Cranial neuropathies are a frequent reason for neurologic consultation, yet they remain diagnostically challenging because of a broad etiologic spectrum and overlapping clinical presentations. This review aims to support clinicians in achieving an accurate and timely diagnosis by classifying cranial neuropathies according to the main pathogenic mechanisms, with particular attention to rare and underrecognized entities, and by proposing a clinician-oriented diagnostic algorithm to improve diagnostic precision and efficiency.Recent Findings A comprehensive and structured synthesis of the causes of cranial neuropathies is currently lacking. Available literature is largely confined to single-cranial nerve reviews or disease-specific settings and further limited by inconsistent terminology that may blur the distinction between peripheral cranial nerve involvement and brainstem nuclear syndromes. As a result, an integrated framework to guide diagnostic reasoning in daily practice remains unavailable. Recent advances in antibody testing, neurogenetics, high-resolution neuroimaging, and targeted immunotherapies have expanded the diagnostic and therapeutic landscape, increasing the need for an updated, mechanism-based approach that can be readily applied in clinical practice.Summary We identify major etiologic categories associated with cranial neuropathies, including immune-mediated and rheumatologic diseases, paraproteinemic disorders, hereditary conditions, and infectious and compressive etiologies. For each category, we summarize representative disorders, underlying pathophysiologic mechanisms, and practical diagnostic clues, and we highlight relevant mimics that may complicate the differential diagnosis. We then propose a three-tier diagnostic algorithm integrating clinical pattern recognition with brain MRI, CSF analysis, and targeted neurophysiologic studies. By systematically combining clinical, imaging, and laboratory data, this framework is intended to increase diagnostic accuracy and support early recognition of uncommon but treatable causes of cranial neuropathy.