The current gold standard surgical treatment for medication-resistant essential tremor (ET) is deep brain stimulation (DBS). However, recent advances in technologies have led to the development of incisionless techniques, such as magnetic resonance-guided focused ultrasound (MRgFUS) thalamotomy. The authors perform a systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement to compare unilateral MRgFUS thalamotomy to unilateral and bilateral DBS in the treatment of ET in terms of tremor severity and quality of life improvement. PubMed, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials and SCOPUS databases were searched. 45 eligible articles, published between 1990 and 2019, were retrieved. 1202 patients were treated with DBS and 477 were treated with MRgFUS thalamotomy. Postoperative tremor improvement was greater following DBS than MRgFUS thalamotomy (p<0.001). A subgroup analysis was carried out stratifying by treatment laterality: bilateral DBS was significantly superior to both MRgFUS and unilateral DBS (p<0.001), but no significant difference was recorded between MRgFUS and unilateral DBS (p<0.198). Postoperative quality of life improvement was significantly greater following MRgFUS thalamotomy than DBS (p<0.001). Complications were differently distributed among the two groups (p<0.001). Persistent complications were significantly more common in the MRgFUS group (p=0.042). While bilateral DBS proves superior to unilateral MRgFUS thalamotomy in the treatment of ET, a subgroup analysis suggests that treatment laterality is the most significant determinant of tremor improvement, thus highlighting the importance of future investigations on bilateral staged MRgFUS thalamotomy.

Brain biopsy is the gold standard in order to establish the diagnosis of unresectable brain tumors. Few studies have investigated the long-term outcomes of biopsy patients. The aim of this single-institution-based study was to assess the concordance between radiological and histopathological diagnoses, and the long-term patient outcome. Ninety-three patients who underwent brain biopsy in the last 5 years were analyzed. We included patients treated with stereotactically guided needle, open, and neuroendoscopic biopsies. Most patients (86%) received needle biopsy. Gliomas and primary brain lymphomas comprised 88.2% of cases. The diagnostic yield was 95.7%. Serious complication and death rates were 3.2% and 2.1%, respectively. The concordance rate between radiological and histological diagnoses was 93%. Notably, the positive predictive value of radiological diagnosis of lymphoma was 100%. Biopsy allowed specific treatment in 72% of cases. Disease-related neurological worsening was the main reason that precluded adjuvant treatment. Adjuvant treatment, in turn, was the strongest prognostic factor, since the median overall survival was 11 months with vs. 2 months without treatment (p = 0.0002). Finally, advanced molecular evaluations can be obtained on glioma biopsy specimens to provide integrated diagnoses and individually tailored treatments. We conclude that, despite the huge advances in imaging techniques, biopsy is required when an adjuvant treatment is recommended, particularly in gliomas.

Background: The retrosigmoid approach represents a crucial surgical route to address different lesions in the cerebellopontine angle but cerebrospinal fluid (CSF) leak still remains the most frequent complication after this approach. Here, we analyzed the impact of different factors in CSF leak development after a retrosigmoid approach. Identifying risk factors related to a specific approach may help the surgeon to tailor the perioperative management and to appropriately counsel patients regarding their risk profile. Methods: We retrospectively reviewed the clinical, surgical, and outcome data of 103 consecutive patients (M/F, 47/56; mean follow-up 35.6 ± 23.9 months) who underwent a retrosigmoid approach for different cerebellopontine angle pathologies and studied the impact of different factors on the occurrence of a CSF leak to univariate and multivariate analysis. Results: Seventy-nine patients (76.7%) were operated for tumors growing in the cerebellopontine angle. Twenty-four patients (23.2%) underwent microvascular decompression to treat a drug-resistant trigeminal neuralgia. Sixteen patients (15.5%) developed CSF leak in the postoperative course of which six underwent surgical revision. Performing a craniectomy as surgical procedure (P = 0.0450) and performing a reopening procedure (second surgery; P = 0.0079) were significantly associated to a higher risk of developing CSF leak. Moreover, performing a reopening procedure emerged as an independent factor for CSF developing on multivariate analysis (P = 0.0156). Conclusion: Patients submitted to craniectomy and patients who underwent a second surgery showed an higher CSF leak rate. Ongoing improvement of biomaterial technology may help neurosurgeons to prevent this potentially life-threatening complication.

5-aminolevulinic acid (5-ALA)-induced PpIX fluorescence is used by neurosurgeons to identify the tumor cells of high-grade gliomas during operation. However, the issue of whether 5-ALA-induced PpIX fluorescence consistently stains all the tumor cells is still debated. Here, we assessed the cytoplasmatic signal of 5-ALA by fluorescence microscopy in a series of human gliomas. As tumor markers, we used antibodies against collapsin response-mediated protein 5 (CRMP5), alpha thalassemia/mental retardation syndrome X-linked (ATRX), and anti-isocitrate dehydrogenase 1 (IDH1). In grade III–IV gliomas, the signal induced by 5-ALA was detected in 32.7–75.5 percent of CRMP5-expressing tumor cells. In low-grade gliomas (WHO grade II), the CRMP5-expressing tumor cells did not fluoresce following 5-ALA. Immunofluorescence with antibodies that stain various components of the blood–brain barrier (BBB) suggested that 5-ALA does not cross the un-breached BBB, in spite of its small dimension. To conclude, 5-ALA-induced PpIX fluorescence has an established role in high-grade glioma surgery, but it has limited usefulness in surgery for low-grade glioma, especially when the BBB is preserved.

Purpose Transsphenoidal surgery (TSS) for pituitary adenomas can be complicated by the occurrence of intraoperative cerebrospinal fluid (CSF) leakage (IOL). IOL significantly affects the course of surgery predisposing to the development of postoperative CSF leakage, a major source of morbidity and mortality in the postoperative period. The authors trained and internally validated the Random Forest (RF) prediction model to preoperatively identify patients at high risk for IOL. A locally interpretable model-agnostic explanations (LIME) algorithm is employed to elucidate the main drivers behind each machine learning (ML) model prediction. Methods The data of 210 patients who underwent TSS were collected; first, risk factors for IOL were identified via conventional statistical methods (multivariable logistic regression). Then, the authors trained, optimized, and audited a RF prediction model. Results IOL reported in 45 patients (21.5%). The recursive feature selection algorithm identified the following variables as the most significant determinants of IOL: Knosp's grade, sellar Hardy's grade, suprasellar Hardy's grade, tumor diameter (on X, Y, and Z axes), intercarotid distance, and secreting status (nonfunctioning and growth hormone [GH] secreting). Leveraging the predictive values of these variables, the RF prediction model achieved an area under the curve (AUC) of 0.83 (95% confidence interval [CI]: 0.78; 0.86), significantly outperforming the multivariable logistic regression model (AUC = 0.63). Conclusion A RF model that reliably identifies patients at risk for IOL was successfully trained and internally validated. ML-based prediction models can predict events that were previously judged nearly unpredictable; their deployment in clinical practice may result in improved patient care and reduced postoperative morbidity and healthcare costs. Ethical approval was waived by the local Ethics Committee in view of the retrospective nature of the study and all the procedures being performed were part of the routine care. Informed consent was obtained from all individual participants included in the study. The dataset that supports the findings of this study are available from the corresponding author, M.G., on request. The source code employed to develop the herein presented machine learning model is available at the following GitHub repository: https://github.com/valerio-mc/ML-fistola-pituitary . ^* These authors contributed equally to the work. Received: 12 March 2021 Accepted: 12 November 2021 Publication Date: 16 January 2022 (online) © 2022. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany