RESUMEN
BACKGROUND: Intraoperative ultrasound (IOUS) is a profitable tool for neurosurgical procedures' assistance, especially in neuro-oncology. It is a rapid, ergonomic and reproducible technique. However, its known handicap is a steep learning curve for neurosurgeons. Here, we describe an interesting postoperative analysis that provides extra feedback after surgery, accelerating the learning process. METHOD: We conducted a descriptive retrospective unicenter study including patients operated from intra-axial brain tumors using neuronavigation (Curve, Brainlab) and IOUS (BK-5000, BK medical) guidance. All patients had preoperative Magnetic Resonance Imaging (MRI) prior to tumor resection. During surgery, 3D neuronavigated IOUS studies (n3DUS) were obtained through craniotomy N13C5 transducer's integration to the neuronavigation system. At least two n3DUS studies were obtained: prior to tumor resection and at the resection conclusion. A postoperative MRI was performed within 48 h. MRI and n3DUS studies were posteriorly fused and analyzed with Elements (Brainlab) planning software, permitting two comparative analyses: preoperative MRI compared to pre-resection n3DUS and postoperative MRI to post-resection n3DUS. Cases with incomplete MRI or n3DUS studies were withdrawn from the study. RESULTS: From April 2022 to March 2024, 73 patients were operated assisted by IOUS. From them, 39 were included in the study. Analyses comparing preoperative MRI and pre-resection n3DUS showed great concordance of tumor volume (p < 0,001) between both modalities. Analysis comparing postoperative MRI and post-resection n3DUS also showed good concordance in residual tumor volume (RTV) in cases where gross total resection (GTR) was not achieved (p < 0,001). In two cases, RTV detected on MRI that was not detected intra-operatively with IOUS could be reviewed in detail to recheck its appearance. CONCLUSIONS: Post-operative comparative analyses between IOUS and MRI is a valuable tool for novel ultrasound users, as it enhances the amount of feedback provided by cases and could accelerate the learning process, flattening this technique's learning curve.