Cerebrospinal fluid cytology remains a cornerstone of diagnostic evaluation in infectious, autoimmune, haemorrhagic, and neoplastic disorders of the central nervous system despite advances in neuroimaging, molecular diagnostics, and digital technologies. This narrative review summarises established principles of cerebrospinal fluid cytology, highlights methodological limitations and diagnostic pitfalls, and integrates emerging developments, including automated cell counting, artificial intelligence, and telecytology. Pre-analytical factors are critical determinants of diagnostic accuracy. Delayed sample processing promotes pH-dependent autolysis and substantial cell loss, whereas rapid cytocentrifugation preserves cellular morphology and facilitates reliable assessment. Automated cell counters are increasingly implemented in routine laboratories and offer advantages in settings with limited technical staffing. However, current systems show limited precision in samples with low and slightly elevated cell counts and limited morphological evaluation. Manual chamber counting, particularly in the normal and low-cell-count range, remains the gold standard for quantitative CSF cell assessment, whereas expert microscopic examination remains the reference standard for qualitative cytomorphological assessment. Although the sensitivity of neuroimaging continues to improve, cerebrospinal fluid cytology retains a unique diagnostic role in the detection of infectious and neoplastic conditions and in the evaluation of subarachnoid haemorrhage. Cytological detection of erythrophages, siderophages, and haematoidin crystals can reveal haemorrhage and provide clues to its temporal stage. Overall, cerebrospinal fluid cytology remains a valuable diagnostic tool when integrated with clinical, laboratory, microbiological, immunological, and imaging findings. Careful recognition of common pitfalls is essential. We recommend rapid cerebrospinal fluid processing, routine preparation of cytospin-based stained slides with expert microscopic review, and the implementation of automated or digital methods only within clearly validated workflows.
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Nay et al. (2026) studied this question.
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