Akademik Veri Yönetim Sistemi
Turkish Journal of Pathology, cilt.40, sa.3, ss.1-7, 2024 (ESCI)
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.