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Luca Massimi, Giuseppe Maria Della Pepa, Gianpiero Tamburrini, and Concezio Di Rocco

Chiari malformation Type I (CM-I) is usually suspected in patients with slowly progressing neurological symptoms. However, in some instances, especially if syringomyelia is associated, an abrupt clinical onset is reported and is accompanied by an acknowledged risk of potentially severe clinical signs or even sudden death. Little is known about such a critical course in CM-I/syringomyelia complex.

The authors describe 3 challenging cases of the abrupt onset of CM-I/syringomyelia to reveal more information on the clinical presentation and pathogenetic mechanisms of this sudden and potentially severe clinical phenomenon: a 38-year-old man experienced acute respiratory failure requiring intubation following acute decompensation of hydrocephalus associated with Noonan syndrome, a 1-year-old boy had sudden hemiparesis and Horner syndrome after a minor head/neck injury, and a 2.5-year-old boy presented with quickly progressing tetraplegia and dyspnea after a mild flexion and extension neck injury a few hours before. All 3 patients showed a CM-I/syringomyelia complex at diagnosis, and all of them had a good neurological outcome after surgery despite the ominous clinical presentation.

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Grazia Menna, Alessandro Olivi, and Giuseppe Maria Della Pepa

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Giuseppe Maria Della Pepa, Quintino Giorgio D’Alessandris, Benedetta Burattini, Davide Quaranta, Carmelo Lucio Sturiale, Pier Paolo Mattogno, Roberto Pallini, and Alessandro Olivi

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Giuseppe Maria Della Pepa, Grazia Menna, Vito Stifano, Angelo Maria Pezzullo, Anna Maria Auricchio, Alessandro Rapisarda, Valerio Maria Caccavella, Giuseppe La Rocca, Giovanni Sabatino, Enrico Marchese, and Alessandro Olivi

OBJECTIVE

Providing new tools to improve surgical planning is considered a main goal in meningioma treatment. In this context, two factors are crucial in determining operating strategy: meningioma-brain interface and meningioma consistency. The use of intraoperative ultrasound (ioUS) elastosonography, a real-time imaging technique, has been introduced in general surgery to evaluate similar features in other pathological settings such as thyroid and prostate cancer. The aim of the present study was to evaluate ioUS elastosonography in the intraoperative prediction of key intracranial meningioma features and to evaluate its application in guiding surgical strategy.

METHODS

An institutional series of 36 meningiomas studied with ioUS elastosonography is reported. Elastographic data, intraoperative surgical findings, and corresponding preoperative MRI features were classified, applying a score from 0 to 2 to both meningioma consistency and meningioma-brain interface. Statistical analysis was performed to determine the degree of agreement between meningioma elastosonographic features and surgical findings, and whether intraoperative elastosonography was a better predictor than preoperative MRI in assessing meningioma consistency and slip-brain interface, using intraoperative findings as the gold standard.

RESULTS

A significantly high degree of reliability and agreement between ioUS elastographic scores and surgical finding scores was reported (intraclass correlation coefficient = 0.848, F = 12.147, p < 0.001). When analyzing both consistency and brain-tumor interface, ioUS elastography proved to have a rather elevated sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and positive (LR+) and negative likelihood ratio (LR−). This consideration was true especially for meningiomas with a hard consistency (sensitivity = 0.92, specificity = 0.96, PPV = 0.92, NPV = 0.96, LR+ = 22.00, LR− = 0.09) and for those presenting with an adherent slip-brain interface (sensitivity = 0.76, specificity = 0.95, PPV = 0.93, NPV = 0.82, LR+ = 14.3, LR− = 0.25). Furthermore, predictions derived from ioUS elastography were found to be more accurate than MRI-derived predictions, as demonstrated by McNemar’s test results in both consistency (p < 0.001) and interface (p < 0.001).

CONCLUSIONS

While external validation of the data is needed to transform ioUS elastography into a fully deployable clinical tool, this experience confirmed that it may be integrated into meningioma surgical planning, especially because of its rapidity and cost-effectiveness.

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Tamara Ius, Teresa Somma, Roberto Altieri, Filippo Flavio Angileri, Giuseppe Maria Barbagallo, Paolo Cappabianca, Francesco Certo, Fabio Cofano, Alessandro D’Elia, Giuseppe Maria Della Pepa, Vincenzo Esposito, Marco Maria Fontanella, Antonino Germanò, Diego Garbossa, Miriam Isola, Giuseppe La Rocca, Francesco Maiuri, Alessandro Olivi, Pier Paolo Panciani, Fabrizio Pignotti, Miran Skrap, Giannantonio Spena, and Giovanni Sabatino

OBJECTIVE

Approximately half of glioblastoma (GBM) cases develop in geriatric patients, and this trend is destined to increase with the aging of the population. The optimal strategy for management of GBM in elderly patients remains controversial. The aim of this study was to assess the role of surgery in the elderly (≥ 65 years old) based on clinical, molecular, and imaging data routinely available in neurosurgical departments and to assess a prognostic survival score that could be helpful in stratifying the prognosis for elderly GBM patients.

METHODS

Clinical, radiological, surgical, and molecular data were retrospectively analyzed in 322 patients with GBM from 9 neurosurgical centers. Univariate and multivariate analyses were performed to identify predictors of survival. A random forest approach (classification and regression tree [CART] analysis) was utilized to create the prognostic survival score.

RESULTS

Survival analysis showed that overall survival (OS) was influenced by age as a continuous variable (p = 0.018), MGMT (p = 0.012), extent of resection (EOR; p = 0.002), and preoperative tumor growth pattern (evaluated with the preoperative T1/T2 MRI index; p = 0.002). CART analysis was used to create the prognostic survival score, forming six different survival groups on the basis of tumor volumetric, surgical, and molecular features. Terminal nodes with similar hazard ratios were grouped together to form a final diagram composed of five classes with different OSs (p < 0.0001). EOR was the most robust influencing factor in the algorithm hierarchy, while age appeared at the third node of the CART algorithm. The ability of the prognostic survival score to predict death was determined by a Harrell’s c-index of 0.75 (95% CI 0.76–0.81).

CONCLUSIONS

The CART algorithm provided a promising, thorough, and new clinical prognostic survival score for elderly surgical patients with GBM. The prognostic survival score can be useful to stratify survival risk in elderly GBM patients with different surgical, radiological, and molecular profiles, thus assisting physicians in daily clinical management. The preliminary model, however, requires validation with future prospective investigations. Practical recommendations for clinicians/surgeons would strengthen the quality of the study; e.g., surgery can be considered as a first therapeutic option in the workflow of elderly patients with GBM, especially when the preoperative estimated EOR is greater than 80%.