Navigated ultrasound-based image guidance during resection of gliomas: practical utility in intraoperative decision-making and outcomes.

OBJECTIVE

Intraoperative imaging is increasingly being used for resection control in diffuse gliomas, in which the extent of resection (EOR) is important. Intraoperative ultrasound (iUS) has emerged as a highly effective tool in this context. Navigated ultrasound (NUS) combines the benefits of real-time imaging with the benefits of navigation guidance. In this study, the authors investigated the use of NUS as an intraoperative adjunct for resection control in gliomas.

METHODS

The authors retrospectively analyzed 210 glioma patients who underwent surgery using NUS at their center. The analysis included intraoperative decision-making, diagnostic accuracy, and operative outcomes, particularly EOR and related factors influencing this.

RESULTS

US-defined gross-total resection (GTR) was achieved in 57.6% of patients. Intermediate resection control scans were evaluable in 115 instances. These prompted a change in the operative decision in 42.5% of cases (the majority being further resection of unanticipated residual tumor). Eventual MRI-defined GTR rates were similar (58.6%), although the concordance between US and MRI was 81% (170/210 cases). There were 21 false positives and 19 false negatives with NUS, resulting in a sensitivity of 78%, specificity of 83%, positive predictive value of 77%, and negative predictive value of 84%. A large proportion of patients (13/19 patients, 68%) with false-negative results eventually had near-total resections. Tumor resectability, delineation, enhancement pattern, eloquent location, and US image resolution significantly influenced the GTR rate, though only resectability and eloquent location were significant on multivariate analysis.

CONCLUSIONS

NUS is a useful intraoperative adjunct for resection control in gliomas, detecting unanticipated tumor residues and positively influencing the course of the resection, eventually leading to higher resection rates. Nevertheless, resection is determined by the innate resectability of the tumor and its relationship to eloquent location, reinforcing the need to combine iUS with functional mapping techniques to optimize resections.