Feasibility of Real-Time Cellular Imaging Using a Miniaturized Epifluorescence Widefield Microscope for Intraoperative Margin Assessment in Intracranial Tumor Resection: A Pilot Study.
case_series · Level IV
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- Record sourced from PubMed, PMID 42722069.
- Also identified by DOI 10.1016/j.wneu.2026.125317.
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Abstract
Achieving maximal safe resection while balancing cytoreduction with functional preservation is a critical challenge in precision neurosurgery. The miniaturized epifluorescence widefield microscope (MEW-M) is a novel handheld device capable of real-time, cellular-level visualization. This pilot study evaluates the feasibility and diagnostic accuracy of MEW-M in guiding the surgical resection of intracranial tumors. This study enrolled 42 patients across a diverse pathological spectrum, including gliomas, meningiomas, pituitary adenomas, schwannomas, hemangioblastomas, and brain metastases. Following tumor removal, ex vivo specimens and the resection cavity were stained with 0.125% sodium fluorescein and 0.5% methylene blue for in vivo and ex vivo MEW-M imaging. A cohort of 14 cases with high-quality imaging, pathological specimens, and preoperative imaging-confirmed by joint neurosurgical, pathological, and radiological assessment-was selected for formal diagnostic analysis. Intraoperative images were interpreted using a binary classification system and validated against paraffin-embedded histopathology. In all 14 analyzed cases, MEW-M imaging demonstrated 100% concordance with final pathological diagnoses. Tumor tissue consistently exhibited hypercellularity and hyperchromatic enlarged nuclei with significant atypia, whereas normal brain tissue showed low cellular density. Staining required 30-60 seconds, with ex vivo scanning taking approximately 1 minute per specimen. An iterative "Scan-Resect-Rescan" feedback loop averaged 10 minutes (range: 8-15 minutes) per case, independent of tumor type. MEW-M provides feasible, real-time cellular-resolution intraoperative pathology. Integrating this modality into a multimodal navigational framework enables precise tumor-brain interface identification, informing surgical decision-making regarding resection extent while preserving critical neurological structures.