Objective

To assess the utility of a newly developed squash cytology (SC)-based scoring system for accurate intraoperative diagnosis of schwannoma.

Methods

We first compared SC-based diagnoses or frozen section (FS) diagnoses against final pathological diagnoses of schwannoma (16 cases), meningioma (39 cases) and low-grade astrocytoma (16 cases). Then, by logistic regression modeling, we identified features of SC preparations independently predictive of schwannoma. To develop a diagnostic scoring system, we assigned one point to each feature, and performed receiver operating characteristic analysis to determine the score cut-off value most discriminatory for differentiating schwannoma from the other tumor types. We then compared accuracy, sensitivity, and specificity of diagnosis before and after application of the scoring system.

Results

Overall diagnostic concordance between SC and FS were almost similar at 73.2% (52/71) and 77.5% (55/71 cases), respectively. Of the 16 SC features entered into the analysis, the following nine were found to independently predict schwannoma, and were thus incorporated into the scoring system: smooth cluster margins, few or no isolated tumor cells, fibrillary stroma, spindle-shaped nuclei, parallel arrangement of stroma, parallel arrangement of nuclei, presence of anisonucleosis, absence of nucleoli, and hemosiderin deposition. A cut-off score of four items yielded the best sensitivity, specificity and predictive values for prediction of schwannoma. Use of the scoring system improved accuracy of intraoperative diagnosis from 80.3% to 94.4%, sensitivity from 56.2% to 93.8%, and specificity from 87.3% to 94.5%.

Conclusion

Our proposed SC-based scoring system will increase accuracy of intraoperative diagnosis of schwannoma vs. non-schwannoma tumors.