Predictors of Morbidity and Cleavage Plane in Surgical Resection of Pure Convexity Meningiomas Using Cerebrospinal Fluid Sensitive Image Subtraction Magnetic Resonance Imaging

Thenier-Villa, José Luis; Campoverde, Raúl Alejandro Galárraga; Zaragoza, Adolfo Ramón De La Lama; Alonso, Cesáreo Conde

doi:10.2176/nmc.oa.2016-0169

Cited by 14 publications

(10 citation statements)

References 27 publications

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“…Considering the results of similar studies, a change in a patient’s mean age at the time of surgery could be observed over the last decades. While the average age a few decades ago was just over 50 years [ 20 , 22 ], meningioma patients who undergo surgery today are approximately 60 years old, similar to this study [ 9 , 21 , 23 , 24 ]. This is not surprising, since the ongoing advances in medicine mean that people are living longer and, consequently, also in the case of patients undergoing surgery.…”

Section: Resultssupporting

confidence: 77%

Prognostic factors of microsurgical treatment of intracranial meningiomas – A multivariate analysis

Kreßner

Arlt

Riepl³

et al. 2018

PLoS ONE

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ObjectivePeri- and postoperative time course of meningioma patients who had undergone surgical treatment was evaluated to determine prognostic factors of neurological outcome by focusing on preoperative parameters.Material and methodsA retrospective monocenter analysis was performed including patients who were operated in the Department of Neurosurgery, University Hospital Leipzig, from 2009 to 2015. Data from all patients with histologically confirmed diagnosis of intracranial meningioma treated microsurgically were included in the study. The individual characteristics of the patients, meningiomas and Karnofsky Performance scores (KPS) were analyzed by multivariate tests.ResultsTwo hundred ninety-four patients with a median age of 61 years (range: 17–89) were included. Preoperative KPS (p < 0.001), skull base as tumor origin and tumor size (p < 0.05) proved to be significantly strong prognostic factors of KPS deterioration one year postoperative by multivariate analysis. According to uni- and bivariate analysis, the following prognostic factors could also be found: preoperative mass displacement, preexisting recurrence and presence of preoperative symptoms. In this study, age had no significant influence on deterioration in patient health state, measured by KPS, one year postoperative.ConclusionPatients generally obtained an improvement in KPS score after microsurgical treatment. The knowledge of prognostic factors can be very helpful in the decision-making process for meningioma treatment of the elderly, particularly to estimate the postoperative outcome and quality of life.

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Section: Resultssupporting

confidence: 77%

Prognostic factors of microsurgical treatment of intracranial meningiomas – A multivariate analysis

Kreßner

Arlt

Riepl³

et al. 2018

PLoS ONE

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“…Arachnoidal plane constitutes also one prognosticator. Villa et al established the term cleft sign introducing a T2-FLAIR digital subtraction sequence [4]. Edema did not always correlate with the poor cleavage plane.…”

Section: Discussionmentioning

confidence: 99%

“…Edema did not always correlate with the poor cleavage plane. Absent cleft sign in the image subtraction and a minimal intraoperative cleavage plane strongly omens postoperative neurological deficits [4].…”

Section: Discussionmentioning

confidence: 99%

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Perioperative Brain Edema in Meningioma Resection Procedures: Case Series and Experience of a Single Center

Antoniades¹,

Stamatiou²,

Papadopoulou³

et al. 2020

J Neurol Exp Neurosci

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Meningiomas are the most frequent benign intracranial lesions. They arise from the arachnoidal cap cells and are extra-axially located. Gross total resection in most of the cases is the treatment of choice. Technical aspects such as the presence of perifocal edema renders the resection procedure difficult and are related to postoperative outcome. Edema is not associated with location and size alone. It constitutes actually a phenomenon of the tumor and adjacent brain parenchyma interface and also depends on the secretion of vascular proliferations factors. Herewith, we present our retrospective study concerning 57 patients, who were operated, within the last eighteen months in our tertiary neurosurgical center. In our findings we involved tumor location and histological type. The grade of resection was described according to Simpson's scale and arachoidal plane was evaluated on T2-WI and FLAIR sequences. Furthermore, we have established statistical correlations of neurological outcome utilizing modified Rankin Scale upon the first two months, based on edema index (p < 0.008), arachnoidal plane presence (p < 0.0001) and the extent of excision (p < 0.003), as well. We advocate that surgeon should thoroughly examine the preoperative radiological tools and plan safely the strategy of extirpation beginning from the arachnoidal cleft.

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“…Among MR features, tumor shape and brain invasion were significantly different between TM and AM, and based on the stepwise multivariate logistic regression analysis, they can be used as independent discrimination factors. AMs are more irregular, and TMs are mostly circular or quasicircular, which may be related to the grade of the tumor and the increased brain volume due to the peritumoral edema (26).…”

Section: Assessment Of the Clinicoradiomic Nomogram Performancementioning

confidence: 99%

A Magnetic Resonance Imaging-Based Radiomic Model for the Noninvasive Preoperative Differentiation Between Transitional and Atypical Meningiomas

Zhang

Cao

et al. 2022

Front. Oncol.

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Preoperative distinction between transitional meningioma and atypical meningioma would aid the selection of appropriate surgical techniques, as well as the prognosis prediction. Here, we aimed to differentiate between these two tumors using radiomic signatures based on preoperative, contrast-enhanced T1-weighted and T2-weighted magnetic resonance imaging. A total of 141 transitional meningioma and 101 atypical meningioma cases between January 2014 and December 2018 with a histopathologically confirmed diagnosis were retrospectively reviewed. All patients underwent magnetic resonance imaging before surgery. For each patient, 1227 radiomic features were extracted from contrast-enhanced T1-weighted and T2-weighted images each. Least absolute shrinkage and selection operator regression analysis was performed to select the most informative features of different modalities. Subsequently, stepwise multivariate logistic regression was chosen to further select strongly correlated features and build classification models that can distinguish transitional from atypical meningioma. The diagnostic abilities were evaluated by receiver operating characteristic analysis. Furthermore, a nomogram was built by incorporating clinical characteristics, radiological features, and radiomic signatures, and decision curve analysis was used to validate the clinical usefulness of the nomogram. Sex, tumor shape, brain invasion, and four radiomic features differed significantly between transitional meningioma and atypical meningioma. The clinicoradiomic model derived by fusing the above features resulted in the best discrimination ability, with areas under the curves of 0.809 (95% confidence interval, 0.743-0.874) and 0.795 (95% confidence interval, 0.692-0.899) and sensitivity values of 74.0% and 71.4% in the training and validation cohorts, respectively. The clinicoradiomic model demonstrated good performance for the differentiation between transitional and atypical meningioma. It is a quantitative tool that can potentially aid the selection of surgical techniques and the prognosis prediction and can thus be applied in patients with these two meningioma subtypes.

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Predictors of Morbidity and Cleavage Plane in Surgical Resection of Pure Convexity Meningiomas Using Cerebrospinal Fluid Sensitive Image Subtraction Magnetic Resonance Imaging

Cited by 14 publications

References 27 publications

Prognostic factors of microsurgical treatment of intracranial meningiomas – A multivariate analysis

Prognostic factors of microsurgical treatment of intracranial meningiomas – A multivariate analysis

Perioperative Brain Edema in Meningioma Resection Procedures: Case Series and Experience of a Single Center

A Magnetic Resonance Imaging-Based Radiomic Model for the Noninvasive Preoperative Differentiation Between Transitional and Atypical Meningiomas

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