# Investigation of the Effectiveness of an Algorithm as an Auxiliary Method in Intraoperative Consultations of Central Nervous System Tumors

## TL;DR

This study shows that using an algorithm improves diagnostic accuracy and consistency during intraoperative consultations for brain tumors.

## Contribution

The study demonstrates that a systematic algorithm can effectively aid pathologists in making more accurate and consistent intraoperative diagnoses of central nervous system tumors.

## Key findings

- Using the algorithm increased correct diagnosis rates for four out of five observers.
- The algorithm significantly reduced errors in grading glial tumors.
- The algorithm improved agreement among observers' diagnoses.

## Abstract

Objective:
One of the most difficult areas in a surgical pathology practice is intraoperative consultation. In a previous study, we proposed an algorithm that provides a systematic approach to intraoperative consultation for central nervous system tumors. Our aim was to demonstrate the effectiveness of this algorithm.

Material and Methods:
102 cases were selected from intraoperative consultation procedures performed at our institution between 2012 and 2020. The algorithm was tested by five observers. The observers examined the smears and frozen sections without the algorithm, and then with the algorithm.

Results:
The percentage change in the rate of correct diagnoses made by the four observers (O) increased after using the algorithm (O2: 8%, O3: 5%, O4: 8% and O5: 13%), but decreased for only one observer (O1) (5%). The most common error made by the four observers was “grading of glial tumors” (O1: 40%; O2: 23%; O4: 40% and O5: 27.5%), and this group of errors was mostly corrected by using the algorithm (O1: 33%; O2: 3.8%; O4: 23% and O5: 10%). For two observers (O2 and O5), a statistically significant change in diagnostic levels was observed after using the algorithm (p=0.024 and p=0.040; respectively). In addition, thanks to the use of the algorithm, a high degree of agreement was found between the observers’ diagnoses (77.7%, p<0.001).

Conclusion:
In the intraoperative consultation of central nervous system lesions, algorithms can help to increase the accuracy of the diagnosis and reduce interobserver variability. This study demonstrates that an algorithmic approach is an effective method for pathologists in intraoperative consultation procedures.