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          "en" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Examples of convexity meningiomas of the three histological grades and their respective volumes&#44; surface areas and surface factors&#46; As the histological grade increases&#44; the irregularity of the tumour surface increases and its surface factor decreases&#46;</p>"
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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">The current WHO classification of brain tumours maintains differentiation by histological grade in intracerebral meningiomas&#44; with important prognostic significance in terms of choice of treatment and likelihood of recurrence after resection&#46;<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a> Overall&#44; about 75&#8211;80&#37; of meningiomas are WHO grade I&#44; 15&#8211;20&#37; are atypical or WHO grade II and 1&#8211;3&#37; are anaplastic or malignant or WHO grade III&#46;<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">2</span></a> Complete resection of a WHO I meningioma achieves cure or at least excellent local control&#44; while a high percentage of WHO grade II and all WHO grade III meningiomas require supplementary radiotherapy&#46;<a class="elsevierStyleCrossRef" href="#bib0015"><span class="elsevierStyleSup">3</span></a> The recurrence rate after excision also increases with histological grade&#44; reaching 30&#8211;50&#37; for grade II and 50&#8211;95&#37; for grade III&#46;<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1&#44;2&#44;4</span></a> The difficulty in achieving local control translates into a loss of overall survival&#44; with 10-year survival rates at around 50&#37; for WHO III&#46;<a class="elsevierStyleCrossRefs" href="#bib0020"><span class="elsevierStyleSup">4&#44;5</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Apart from histological grade&#44; the degree of resection is the most important predictor of recurrence&#46;<a class="elsevierStyleCrossRefs" href="#bib0030"><span class="elsevierStyleSup">6&#44;7</span></a> The finding of recurrence in WHO grades II and III has a worse prognosis in terms of survival than recurrence in WHO grade I meningiomas&#46;<a class="elsevierStyleCrossRefs" href="#bib0040"><span class="elsevierStyleSup">8&#8211;11</span></a> There is therefore great interest in being able to predict the histological grade prior to surgery in order to try to maximise efforts at resection in atypical and malignant meningiomas&#46;</p><p id="par0015" class="elsevierStylePara elsevierViewall">The absence of calcification&#44; location in the convexity&#44; radiological behaviour &#40;tumour hyperintensity on MRI T2-weighted sequences&#44; irregular contrast uptake and presence of perilesional oedema&#41;&#44; being male and other factors have been associated with a higher likelihood of atypical or malignant meningiomas&#46;<a class="elsevierStyleCrossRefs" href="#bib0060"><span class="elsevierStyleSup">12&#8211;14</span></a> In addition&#44; a more irregular and rougher tumour surface &#40;a feature referred to in the literature as &#34;mushroom-like&#34;&#41; seems to correlate with a worse histological grade&#46;<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a> However&#44; the degree of irregularity is a subjective and observer-dependent concept&#44; making it difficult to interpret and make comparisons&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">In 2021&#44; Popadic et al&#46;<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> introduced an objective radiological parameter for measuring the surface irregularity of meningiomas&#44; which they called the &#34;surface factor&#34;&#46; This simple parameter numerically estimates the sphericity of the tumour and appears to correlate with the histological grade&#46; This article presents a large series of operated-on meningiomas for which we calculated the surface factor &#40;SF&#41;&#44; correlating it with histological grade and defining the cut-off point of the SF above which the likelihood of tumour aggressiveness is significantly higher&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Patients and methods</span><p id="par0025" class="elsevierStylePara elsevierViewall">This was a retrospective observational study of patients with symptomatic meningiomas operated on by the neurosurgery department of a tertiary hospital between January 2015 and December 2022&#46; The study was approved by the hospital&#39;s Independent Ethics Committee &#40;IECm ref&#46;&#58; 2035&#41;&#46; All patients gave their consent to take part in the study&#46;</p><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Patient screening and inclusion and exclusion criteria</span><p id="par0030" class="elsevierStylePara elsevierViewall">We included consecutive patients over the age of 18 years who underwent surgery for intracranial meningioma in the study period&#44; who had postoperative histological confirmation and for whom a preoperative axial T1-weighted&#44; thin-slice contrast MRI scan was available &#40;at least 320 slices &#60;2&#8239;mm thick&#59; in neuronavigator sequence&#41;&#46; Meningiomas of all intracranial locations were included&#46; In patients with recurrences&#44; the preoperative MRI of the first operation was taken as the reference study&#44; as post-surgical changes sometimes make it difficult to delimit the tumour&#44; especially in parasagittal meningiomas&#44; in which dural uptakes of uncertain significance can appear&#46; In cases of worsening histological grade &#40;becoming malignant&#41;&#44; the MRI prior to the first surgical intervention was also used&#46; Patients with questionable histology&#44; meningiomas previously treated at other centres and multiple&#44; purely intraosseous or plaque meningiomas were excluded&#46; All patients were operated on in the study period by the same six neurosurgeons&#44; and histology was confirmed by the same two pathologists&#44; according to the WHO criteria in force in the study period&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Definition of variables and endpoints</span><p id="par0035" class="elsevierStylePara elsevierViewall">The primary endpoint was to determine the histological grade &#40;dependent variable&#41; using the three-grade WHO classification of intracranial meningiomas&#44; once the definitive pathology study had been carried out on fragments of the resection specimen&#46; The independent variables studied were age&#44; gender&#44; location&#44; radiological behaviour and tumour volume and surface area&#46; WHO grade II and III meningiomas were grouped together for pooled analysis&#46;</p><p id="par0040" class="elsevierStylePara elsevierViewall">Meningioma location was categorised into five groups&#58; convexity &#40;including hemispheric convexity meningiomas and intraventricular meningiomas&#41;&#44; parasagittal &#40;arising from the falx cerebri in any location&#41;&#44; skull base &#40;including olfactory groove&#44; sphenoidal&#44; clinoidal&#44; petroclival&#44; tuberculum sellae&#44; cavernous sinus and orbital roof&#41;&#44; tentorial and posterior fossa &#40;cerebellar convexity&#44; cerebellopontine angle and foramen magnum&#41;&#46;</p><p id="par0045" class="elsevierStylePara elsevierViewall">Radiologically&#44; meningiomas were categorised by their intensity on T2-weighted sequences &#40;hyperintense versus iso- or hypointense&#41;&#44; presence of perilesional oedema and presence of intra-tumour calcifications&#46; Tumour volume &#40;in cm<span class="elsevierStyleSup">3</span>&#41; and surface area &#40;in cm<span class="elsevierStyleSup">2</span>&#41; were estimated to three decimal places from semi-automated segmentation models&#44; as described in the following section&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Calculation of the surface factor</span><p id="par0050" class="elsevierStylePara elsevierViewall">Tumours with a rougher&#44; more irregular surface have proportionally more surface area in relation to their volume than smoother&#44; more regular tumours&#46; For each tumour&#44; we can quantitatively estimate its volume and surface area&#44; and compare this surface area with that of a reference sphere of equal volume&#44; which is the three-dimensional figure with the minimum surface area for a given volume&#46; By relating these two areas we obtain a ratio that quantitatively reflects the sphericity and enables comparisons between individuals&#44; regardless of tumour size &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>&#41;&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0055" class="elsevierStylePara elsevierViewall">Tumour volume and surface area were estimated on the neuronavigation sequence &#40;T1 with thin-slice contrast&#41;&#46; We used freely available segmentation software for this purpose &#40;<span class="elsevierStyleItalic">3 D Slicer</span>&#44; version 4&#46;10&#46;2&#59; available at&#58; <a href="https://www.slicer.org">https&#58;&#47;&#47;www&#46;slicer&#46;org</a>&#41;&#46; According to the previously published methodology&#44;<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> first the tumour volume and surface area are obtained by semi-automatic segmentation&#44; then a sphere with the same volume as the tumour is created&#46; The volume of this sphere is used to calculate its radius &#40;volume&#8239;&#61;&#8239;4&#47;3&#960;r<span class="elsevierStyleSup">3</span>&#41; and the radius is used to calculate its surface area &#40;surface area&#8239;&#61;&#8239;4&#960;r<span class="elsevierStyleSup">2</span>&#41;&#46; Lastly&#44; the surface areas of the sphere and the tumour are compared as a ratio &#40;surface factor&#8239;&#61;&#8239;S<span class="elsevierStyleInf">sphere</span>&#47;S<span class="elsevierStyleInf">tumour</span>&#41;&#46; This surface factor is a ratio ranging from 0 to 1&#44; with 1 being the maximum possible sphericity &#40;equivalent to a perfectly spherical tumour&#41;&#44; so the greater the irregularity&#47;roughness of the tumour&#44; the lower the ratio &#40;<a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#41;&#46; This measure is objective&#44; quantitative and enables comparison of tumours regardless of their size or location&#46; The tumour segmentations &#40;involving mixed manual and semi-automated contouring work&#41; were performed by a single investigator in order to minimise variability in the technique and to obtain as homogeneous and consistent a sample as possible&#46;</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Statistical analysis</span><p id="par0060" class="elsevierStylePara elsevierViewall">The clinical-radiological data were tabulated in Excel spreadsheets &#40;Microsoft&#44; USA&#41;&#46; Statistical analysis was performed with the SPSS software package version 24&#46;0 &#40;IBM Corp&#46;&#44; USA&#41;&#46;</p><p id="par0065" class="elsevierStylePara elsevierViewall">Parameters are described with means&#44; medians&#44; ranges and standard deviations&#46; The categorical variables are described as absolute frequency or percentages&#46; Differences between groups were assessed using Student&#39;s <span class="elsevierStyleItalic">t</span>-test or the Chi-square test&#46; The optimal cut-off value of the surface factor was estimated using the Youden index &#40;sensitivity&#8239;&#43;&#8239;specificity&#8239;&#8722;&#8239;1&#41; of the ROC curve&#46; A univariate study and a multivariate study were conducted using logistic regression that included significant variables&#46; For comparisons&#44; meningiomas were grouped into two categories&#58; WHO grade I and WHO grade II&#8211;III&#46; The limit of statistical significance was set at <span class="elsevierStyleItalic">p</span>&#8239;&#61;&#8239;0&#46;05&#46;</p></span></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Results</span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Characteristics of the sample and differences between WHO Grades I and II&#8211;III</span><p id="par0070" class="elsevierStylePara elsevierViewall">A total of 176 patients &#40;108 female&#44; 64&#46;7&#37;&#41; with a mean age of 62&#46;4 years &#40;range 35&#8722;87&#41; underwent surgery in the study period &#40;eight years&#41;&#46; The distribution of tumours by location and histological grade is shown in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#46; Of the total&#44; 120 &#40;71&#46;9&#37;&#41; were histologically confirmed as WHO grade I&#44; 43 &#40;25&#46;7&#37;&#41; as WHO grade II and four &#40;2&#46;4&#37;&#41; as WHO grade III&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0075" class="elsevierStylePara elsevierViewall">Differences in the variables according to histological grade are shown in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#46; Both groups were similar in terms of age&#44; gender&#44; radiological behaviour and tumour volume&#46; However&#44; significant differences were found in location &#40;higher prevalence of parasagittal meningiomas among WHO II&#8211;III and higher prevalence of skull base tumours in the WHO I meningioma group&#41; and tumour surface area &#40;larger surface area in WHO grade II&#8211;III meningiomas&#41;&#46;</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Differences in surface factor according to world health organization histological grade</span><p id="par0080" class="elsevierStylePara elsevierViewall">The mean SF calculated for the WHO I group was significantly higher than that of the WHO II-III group &#40;0&#46;8651&#8239;&#177;&#8239;0&#46;049 versus 0&#46;7081&#8239;&#177;&#8239;0&#46;105&#44; <span class="elsevierStyleItalic">p</span>&#8239;&#60;&#8239;0&#46;0001&#41;&#46; The differences in SF according to location are shown in <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>&#46; The mean SF values of aggressive tumours were significantly lower for all locations except for tentorial meningiomas &#40;<span class="elsevierStyleItalic">n</span>&#8239;&#61;&#8239;5&#41;&#46;</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Bivariate and multivariate analyses</span><p id="par0085" class="elsevierStylePara elsevierViewall">The variables most closely related to histological grade in the bivariate analysis were location&#44; tumour surface area and SF &#40;<a class="elsevierStyleCrossRefs" href="#tbl0010">Tables 2 and 3</a>&#41;&#46; However&#44; in the multivariate study &#40;<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>&#41; only skull base location and SF remained statistically significant&#46;</p><elsevierMultimedia ident="tbl0020"></elsevierMultimedia></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Cut-off values&#46; ROC curve</span><p id="par0090" class="elsevierStylePara elsevierViewall">The ability of the SF to correctly classify the grade of meningiomas was estimated using a ROC curve &#40;<a class="elsevierStyleCrossRef" href="#fig0015">Fig&#46; 3</a>&#41;&#44; whose area under the curve was <span class="elsevierStyleItalic">0&#46;940</span> &#40;95&#37; CI&#58; 0&#46;902&#8722;0&#46;978&#44; <span class="elsevierStyleItalic">p</span>&#8239;&#60;&#8239;0&#46;0001&#41;&#46; The sensitivity and specificity of the SF were 93&#46;3&#37; y 80&#46;9&#37;&#44; respectively&#46; The positive and negative likelihood ratios were 4&#46;88 and 0&#46;082&#44; respectively&#46; The Youden Index &#40;estimator of test accuracy&#41; was maximum &#40;0&#46;742&#41; for an SF cut-off value of <span class="elsevierStyleItalic">0&#46;7935</span>&#46; The positive and negative predictive values for this cut-off value were 82&#46;6&#37; and 92&#46;6&#37;&#44; respectively&#46;</p><elsevierMultimedia ident="fig0015"></elsevierMultimedia></span></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Discussion</span><p id="par0095" class="elsevierStylePara elsevierViewall">The results of this study on 167 patients operated on for symptomatic intracranial meningioma indicate that the SF can effectively anticipate the aggressiveness of meningiomas &#40;WHO grade I versus WHO grade II&#8211;III&#41;&#44; a parameter calculated from preoperative MRI by semi-automatic segmentation&#46; This measurement is objective and was found to be independent of tumour size or location&#46; The lower the SF&#44; the more likely it is to correspond to an aggressive meningioma &#40;WHO grades II&#8211;III&#41; with an optimal cut-off point around 0&#46;79 and a very high ability to distinguish both groups &#40;area under the ROC curve of 0&#46;940&#41;&#46; Multivariate analysis showed the SF to be an independent predictor of histological grade&#46; To date&#44; this prediction methodology has only been used once before&#46;<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> Several studies correlate the irregular shape of meningiomas with a worse histological grade&#46;<a class="elsevierStyleCrossRefs" href="#bib0060"><span class="elsevierStyleSup">12&#8211;14</span></a> Since the sphere is the figure with the smallest surface area for a given volume&#44; this surface area can be used as a comparative reference with which to construct the SF&#46;</p><p id="par0100" class="elsevierStylePara elsevierViewall">When analysed by location&#44; the differences in the SF were significant for all locations except for tentorial meningiomas&#44; probably due to the limited sample size&#46; According to the study by Popadic et al&#46;&#44;<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> the ROC curve analysis provided an optimal cut-off value for the SF of 0&#46;800&#44; almost identical to that observed in our cohort &#40;0&#46;79&#41;&#46; However&#44; the area under the curve was 0&#46;713 &#40;95&#37; CI&#58; 0&#46;62&#8722;0&#46;81&#44; <span class="elsevierStyleItalic">p</span>&#8239;&#60;&#8239;0&#46;001&#41; and the overall accuracy was modest&#59; sensitivity 52&#37;&#44; specificity 85&#46;5&#37; and positive and negative predictive values of 70&#46;3&#37; and 73&#46;3&#37;&#44; respectively&#46; In their study&#44; only the SF obtained a higher predictive value in the multivariate analysis&#46; Our data&#44; using the same methodology&#44; corroborate those of the above publication and show a higher overall accuracy of the SF as a predictor of histological grade&#44; perhaps enhanced by the larger sample size&#46;</p><p id="par0105" class="elsevierStylePara elsevierViewall">MRI image-based tumour segmentation is performed manually by contouring the lesion boundaries on each MRI slice where it is present&#46; Some programmes&#44; such as the one used here&#44; are capable of semi-automatic segmentation&#59; it requires us to define the inside of the tumour and the outside of the tumour for the programme to interpolate and segment the entire volume of the meningioma&#46; Depending on the threshold parameters specified&#44; it is almost always necessary to correct the boundaries of the three-dimensional figure provided by the system&#44; as autosegmentation is not perfect and tends to overestimate the boundaries of the tumour&#46; Programmes such as the one used include editing tools designed to perform such correction&#44; which carries with it a certain amount of subjectivity and arbitrariness&#46; For this reason&#44; we believe it is important that segmentation is always carried out by the same researcher&#44; so as to minimise variability and enhance consistency&#46; Future artificial intelligence-based autosegmentation systems<a class="elsevierStyleCrossRefs" href="#bib0080"><span class="elsevierStyleSup">16&#44;17</span></a> will probably obviate this variability and minimise the time taken for the process which&#44; with practice and in our experience&#44; requires at least 10&#8722;15&#8239;min per meningioma&#46;</p><p id="par0110" class="elsevierStylePara elsevierViewall">It is interesting to note that the location of the tumour did not affect the mean SF values and the differences by grade remained significant in the bivariate analysis&#44; although they did not reach statistical significance in the multivariate analysis&#44; except for in skull base tumours&#46; This probably reflects a higher statistical power in this subgroup&#44; which turned out to be the most prevalent&#46; Radiological behaviour &#40;tumour hyperintensity in T2&#44; peri-tumour oedema or calcifications&#41; was not able to independently predict the histological grade&#44; although greater T2 hyperintensity was found in the more aggressive tumours&#44; and more calcifications in the more benign tumours&#44; both of which have already been described in the literature&#46;<a class="elsevierStyleCrossRefs" href="#bib0065"><span class="elsevierStyleSup">13&#44;14</span></a></p><p id="par0115" class="elsevierStylePara elsevierViewall">This study provides evidence supporting the SF as an independent predictor for histological grade of meningiomas and emphasises the need for analyses stratified by location and other clinical and radiological factors&#46; As is already the case for gliomas&#44;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> it is likely that future updates of the WHO tumour classification will take molecular parameters into account when classifying meningiomas&#46; The chromosomal location and number of mutations&#44; and the tumour DNA methylation profile will probably define future classifications&#44; which will help to explain the poor clinical outcome of some WHO grade I meningiomas &#40;especially transitional and fibrous&#41; and&#44; conversely&#44; the unexpectedly good outcome of some WHO grade II meningiomas&#46;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> These potential changes open the door to studies similar to ours in which the outcome variable &#40;histological grade&#41; will presumably be more <span class="elsevierStyleItalic">realistic</span> and will allow the predictive power of the SF to be assessed more accurately&#46; In fact&#44; in our experience the SF was not perfect in predicting histological grade&#46; <a class="elsevierStyleCrossRef" href="#fig0020">Fig&#46; 4</a> shows two examples of low-grade and high-grade meningiomas which&#44; after segmentation&#44; showed a superficial appearance and SF value that clearly did not correspond with their grade&#46; These discrepancies between the SF and histological grade may be due to diagnostic errors by pathology&#44; but also to a lack of sensitivity and&#47;or specificity of the SF as a predictor&#46;</p><elsevierMultimedia ident="fig0020"></elsevierMultimedia><p id="par0120" class="elsevierStylePara elsevierViewall">One of the limitations of our study is the sample size&#44; which&#44; although large in overall terms&#44; meant we were unable to obtain results with sufficient statistical power when analysing by some subgroups&#46; Secondly&#44; this was a single-centre study&#44; so the diagnosis and management methods for meningiomas may not be generally extrapolated&#44; an aspect which makes collaboration between centres highly recommendable&#46; Thirdly&#44; the estimation of the SF is based on an exact mathematical calculation using the volume and surface area values provided by a computer programme&#44; where the irregularity of the tumour surface is slightly influenced by the observer performing the tumour segmentation&#46; In our opinion&#44; this source of potential subjectivity is greatly minimised or disappears if the same operator performs all segmentations&#46;</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Conclusions</span><p id="par0125" class="elsevierStylePara elsevierViewall">The ability to predict the histological grade of a meningioma preoperatively has prognostic and management implications both intra- and postoperatively&#46; Greater tumour surface irregularity has been correlated with worse histological grade&#46; The SF is an objective numerical parameter that quantifies this irregularity &#40;roughness&#41; and appears to be an independent predictor of histological grade&#46; The SF is a ratio that compares the area of a sphere of equivalent volume to that of the tumour to the true area of the tumour&#46; The ratio ranges from 0 to 1&#44; with 1 being the maximum possible sphericity&#44; and is lower the more aggressive the tumour is&#46; In this large series of histologically confirmed meningiomas&#44; the SF was able to distinguish high-grade meningiomas &#40;WHO II-III&#41; from low-grade meningiomas &#40;WHO I&#41; accurately in a high percentage of cases &#40;area under the curve 0&#46;940&#41;&#46; Its predictive power was highest at a cut-off value of 0&#46;79&#46; Currently available tumour segmentation software allows for rapid and reproducible estimation of the SF&#46;</p></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Funding</span><p id="par0130" class="elsevierStylePara elsevierViewall">This study has not received any funding from the public or private sector&#46;</p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Conflicts of interest</span><p id="par0135" class="elsevierStylePara elsevierViewall">The authors declare that they have no conflicts of interest with regard to the writing of the manuscript&#46; The software used for the segmentation is free to use and can be downloaded freely from <a href="https://slicer.org">https&#58;&#47;&#47;slicer&#46;org</a>&#46;</p></span></span>"
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        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Introduction</span><p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Predicting the histopathologic grade of meningioma is relevant because local recurrence is significantly greater in WHO grade II&#8211;III compared to WHO grade I tumours&#44; which would ideally benefit from a more aggressive surgical strategy&#46; It has been suggested that higher WHO grade tumours are more irregularly-shaped&#46; However&#44; irregularity is a subjective and observer-dependent feature&#46; In this study&#44; the tumour surface irregularity of a large series of meningiomas&#44; measured upon preoperative MRI&#44; is quantified and correlated with the WHO grade&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">Unicentric retrospective observational study of a cohort of symptomatic meningiomas surgically removed in the time period between January 2015 and December 2022&#46; Using specific segmentation software&#44; the Surface Factor &#40;SF&#41; was calculated for each meningioma&#46; SF is an objective parameter that compares the surface of a sphere &#40;minimum surface area for a given volume&#41; with the same volume of the tumour against the actual surface of the tumour&#46; This ratio varies from 0 to 1&#44; being 1 the maximum sphericity&#46; Since irregularly-shaped meningiomas present proportionally greater surface area&#44; the SF tends to decrease as irregularity increases&#46; SF was correlated with WHO grade and its predictive power was estimated with ROC curve analysis&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">A total of 176 patients &#40;64&#46;7&#37; females&#41; were included in the study&#59; 120 WHO grade I &#40;71&#46;9&#37;&#41;&#44; 43 WHO grade II &#40;25&#46;7&#37;&#41; and 4 WHO grade III &#40;2&#46;4&#37;&#41;&#46; A statistically significant difference was found between the mean SF of WHO grade I and WHO grade II&#8211;III tumours &#40;0&#46;8651&#8239;&#177;&#8239;0&#46;049 versus 0&#46;7081&#8239;&#177;&#8239;0&#46;105&#44; <span class="elsevierStyleItalic">p</span>&#8239;&#60;&#8239;0&#46;0001&#41;&#46; Globally&#44; the SF correctly classified more than 90&#37; of cases &#40;area under ROC curve 0&#46;940&#41; with 93&#46;3&#37; sensibility and 80&#46;9&#37; specificity&#46; A cutoff value of 0&#46;79 yielded the maximum precision&#44; with positive and negative predictive powers of 82&#46;6&#37; and 92&#46;6&#37;&#44; respectively&#46; Multivariate analysis yielded SF as an independent prognostic factor of WHO grade&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusion</span><p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">The <span class="elsevierStyleItalic">Surface Factor</span> is an objective and quantitative parameter that helps to identify aggressive meningiomas preoperatively&#46; A cutoff value of 0&#46;79 allowed differentiation between WHO grade I and WHO grade II&#8211;III with high precision&#46;</p></span>"
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        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Introducci&#243;n</span><p id="spar0095" class="elsevierStyleSimplePara elsevierViewall">Predecir el grado histol&#243;gico de los meningiomas es importante por cuanto los grados OMS II-III presentan mucha mayor tendencia a la recidiva local que los grado OMS I y&#44; por tanto&#44; pueden beneficiarse de una estrategia quir&#250;rgica m&#225;s agresiva&#46; Se ha sugerido que los meningiomas con forma m&#225;s irregular en la RM preoperatoria tienden a ser m&#225;s agresivos&#46; Sin embargo&#44; dicha irregularidad es un concepto subjetivo y observador-dependiente&#46; En este estudio se cuantifica de forma objetiva la irregularidad de una serie de meningiomas y se correlaciona con el grado histol&#243;gico de la OMS&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">M&#233;todos</span><p id="spar0100" class="elsevierStyleSimplePara elsevierViewall">Estudio observacional retrospectivo unic&#233;ntrico de una cohorte de meningiomas sintom&#225;ticos intervenidos en el per&#237;odo entre enero 2015 y diciembre 2022&#46; Mediante software de segmentaci&#243;n&#44; para cada meningioma se calcul&#243; el denominado <span class="elsevierStyleItalic">Factor de Superficie</span> &#40;FS&#41; que es un par&#225;metro objetivo que relaciona la superficie de una esfera &#40;figura con la menor &#225;rea para un volumen dado&#41; de igual volumen que el tumor con la superficie real del tumor&#46; Este cociente var&#237;a de 0 a 1&#44; siendo 1 la m&#225;xima esfericidad posible&#46; Dado que los meningiomas de forma irregular presentan una mayor superficie en relaci&#243;n a su volumen&#44; su FS tiende a ser menor cuanto m&#225;s irregular es el tumor&#46; Se correlacionaron los FS con el grado histol&#243;gico y se evalu&#243; el poder predictivo del FS mediante curva ROC&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0105" class="elsevierStyleSimplePara elsevierViewall">Se incluyeron un total de 176 pacientes &#40;64&#44;7&#37; mujeres&#41;&#59; 120 grado OMS I &#40;71&#44;9&#37;&#41;&#44; 43 grado OMS II &#40;25&#44;7&#37;&#41; y 4 grado OMS III &#40;2&#44;4&#37;&#41;&#46; Se constat&#243; una diferencia significativa en el FS entre los meningiomas grado OMS I y los OMS II-III &#40;0&#44;8651&#8239;&#177;&#8239;0&#44;049 versus 0&#44;7081&#8239;&#177;&#8239;0&#44;105&#44; p&#8239;&#60;&#8239;0&#44;0001&#41;&#46; Globalmente&#44; el FS permiti&#243; clasificar correctamente m&#225;s del 90&#37; de los pacientes &#40;&#225;rea bajo la curva ROC de 0&#44;940&#41;&#44; con una sensibilidad y especificidad del 93&#44;3&#37; y 80&#44;9&#37;&#44; respectivamente&#46; Un valor de corte de 0&#44;79 proporcion&#243; la m&#225;xima precisi&#243;n para clasificar correctamente el grado histol&#243;gico&#44; con valores predictivos positivo y negativo del 82&#44;6&#37; y 92&#44;6&#37;&#44; respectivamente&#46; El an&#225;lisis multivariante identific&#243; el FS como factor pron&#243;stico independiente del grado histol&#243;gico&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusi&#243;n</span><p id="spar0110" class="elsevierStyleSimplePara elsevierViewall">El <span class="elsevierStyleItalic">Factor de Superficie</span> es un par&#225;metro cuantitativo y objetivo que ayuda a identificar los meningiomas agresivos de forma preoperatoria&#46; Un valor de corte de 0&#44;79 permite diferenciar los meningiomas OMS I de los OMS II-III con alta precisi&#243;n&#46;</p></span>"
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        "identificador" => "fig0005"
        "etiqueta" => "Figure 1"
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          0 => array:3 [
            "identificador" => "at0005"
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          "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Method for calculating the surface factor&#46;</p>"
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        "etiqueta" => "Figure 2"
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          0 => array:4 [
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          0 => array:3 [
            "identificador" => "at0010"
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          "en" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Examples of convexity meningiomas of the three histological grades and their respective volumes&#44; surface areas and surface factors&#46; As the histological grade increases&#44; the irregularity of the tumour surface increases and its surface factor decreases&#46;</p>"
        ]
      ]
      2 => array:8 [
        "identificador" => "fig0015"
        "etiqueta" => "Figure 3"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
          0 => array:4 [
            "imagen" => "gr3.jpeg"
            "Alto" => 1688
            "Ancho" => 1649
            "Tamanyo" => 81551
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        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at0015"
            "detalle" => "Figure "
            "rol" => "short"
          ]
        ]
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          "en" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleItalic">ROC curve</span> showing the cut-off values and the ability &#40;sensitivity&#47;specificity&#41; of the surface factor to adequately classify meningiomas into WHO histological grades&#46; WHO grade I meningiomas were grouped together on one side against WHO grade II&#8211;III meningiomas on the other&#46; Area under the curve&#58; <span class="elsevierStyleItalic">0&#46;940</span> &#40;95&#37; CI&#58; 0&#46;902&#8211;0&#46;978&#44; <span class="elsevierStyleItalic">p</span>&#8239;&#60;&#8239;0&#46;0001&#41;&#46; Maximum Youden Index&#8239;&#61;&#8239;0&#46;742 for a cut-off point of SF&#8239;&#61;&#8239;0&#46;7935&#46; Sensitivity&#8239;&#61;&#8239;93&#46;3&#37;&#44; specificity&#8239;&#61;&#8239;80&#46;9&#37;&#44; positive likelihood ratio&#8239;&#61;&#8239;4&#46;8848&#44; negative likelihood ratio&#8239;&#61;&#8239;0&#46;0828&#44; positive predictive value for high grade&#8239;&#61;&#8239;82&#46;6&#37;&#44; and negative predictive value for high grade&#8239;&#61;&#8239;92&#46;6&#37;&#46;</p>"
        ]
      ]
      3 => array:8 [
        "identificador" => "fig0020"
        "etiqueta" => "Figure 4"
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        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
          0 => array:4 [
            "imagen" => "gr4.jpeg"
            "Alto" => 1764
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          0 => array:3 [
            "identificador" => "at0020"
            "detalle" => "Figure "
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          "en" => "<p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Two examples where the surface factor &#40;SF&#41; does not theoretically correspond to the histological grade&#46; The top row of images shows the segmentation of a meningioma with an irregular surface&#44; with an SF of 0&#46;753 &#40;concordant&#41;&#44; but diagnosed as WHO grade <span class="elsevierStyleSmallCaps">I</span>&#46; In contrast&#44; the images in the bottom row show the segmentation of a meningioma with a smooth surface and an SF of 0&#46;895 &#40;also concordant&#41;&#44; but which was diagnosed as WHO grade <span class="elsevierStyleSmallCaps">II</span>&#46; These discrepancies between the SF and histological grade may be due to diagnostic errors by pathology or lack of sensitivity and&#47;or specificity of the SF as a predictor&#46;</p>"
        ]
      ]
      4 => array:8 [
        "identificador" => "tbl0005"
        "etiqueta" => "Table 1"
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          0 => array:3 [
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          "leyenda" => "<p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">WHO&#58; World Health Organization&#46;</p>"
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                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Variables&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Values&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Sample size&#44; n &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">167 &#40;100&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Age&#44; mean&#8239;&#177;&#8239;standard deviation&#44; median &#40;range&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">62&#46;4&#8239;&#177;&#8239;13&#46;9&#44; 63 &#40;35&#8722;87&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Female&#44; n &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">108 &#40;64&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Location&#44; n &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Convexity&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">40 &#40;24&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Parasagittal&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">41 &#40;24&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Tentorial&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">5 &#40;3&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Skull base<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">63 &#40;37&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Posterior fossa&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">18 &#40;10&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">WHO histological grade&#44; n &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Grade I&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">120 &#40;71&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Grade II&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">43 &#40;25&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Grade III&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4 &#40;2&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
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              "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Includes sphenoidal&#44; olfactory groove&#44; clival&#44; petroclival&#44; orbital roof&#44; tuberculum sellae and cavernous sinus meningiomas&#46;</p>"
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                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
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                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="center" valign="\n
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                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="center" valign="\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">WHO II&#8211;III&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="center" valign="\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p-value&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t"><span class="elsevierStyleItalic">Patients&#44; n &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">120&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">47&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;052&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Age&#44; mean &#40;&#177; std dev&#46;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">61&#46;5 &#40;&#177; 14&#46;58&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">64&#46;7 &#40;&#177; 12&#46;06&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;181&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Female&#44; n &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">83 &#40;69&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">25 &#40;53&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;071&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">41 &#40;38&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleItalic">Tumour volume&#44; cm</span><a class="elsevierStyleCrossRef" href="#bib0015"><span class="elsevierStyleSup">3</span></a><span class="elsevierStyleItalic">&#44; mean&#8239;&#177;&#8239;std dev&#46;</span>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">33&#46;24&#8239;&#177;&#8239;31&#46;4&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">35&#46;36&#8239;&#177;&#8239;24&#46;03&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">0&#46;678&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t"><span class="elsevierStyleItalic">Tumour surface area&#44; cm</span><a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">2</span></a><span class="elsevierStyleItalic">&#44; mean&#8239;&#177;&#8239;std dev&#46;</span>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">52&#46;33&#8239;&#177;&#8239;34&#46;93&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">70&#46;93&#8239;&#177;&#8239;36&#46;59&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleBold">0&#46;003</span>&nbsp;\t\t\t\t\t\t\n
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                      "titulo" => "The 2021 WHO classification of tumors of the central nervous system&#58; A summary"
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                          "etal" => true
                          "autores" => array:6 [
                            0 => "D&#46;N&#46; Louis"
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                            3 => "D&#46;J&#46; Brat"
                            4 => "I&#46;A&#46; Cree"
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                    0 => array:2 [
                      "doi" => "10.1093/neuonc/noab106"
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                        "tituloSerie" => "Neuro Oncol"
                        "fecha" => "2021"
                        "volumen" => "23"
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                        "paginaFinal" => "1251"
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                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/34185076"
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                      "titulo" => "CBTRUS statistical report&#58; Primary brain and other central nervous system tumors diagnosed in the United States in 2012-2016"
                      "autores" => array:1 [
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                          "etal" => true
                          "autores" => array:6 [
                            0 => "Q&#46;T&#46; Ostrom"
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                            2 => "H&#46; Gittleman"
                            3 => "N&#46; Patil"
                            4 => "K&#46; Waite"
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                      "doi" => "10.1093/neuonc/noz150"
                      "Revista" => array:7 [
                        "tituloSerie" => "Neuro Oncol"
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Journal Information
Vol. 35. Issue 3.
Pages 113-121 (May - June 2024)
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Vol. 35. Issue 3.
Pages 113-121 (May - June 2024)
Clinical Research
Predicting histological grade in symptomatic meningioma by an objective estimation of the tumoral surface irregularity
Predicción del grado histológico en meningiomas sintomáticos mediante una estimación objetiva de la irregularidad de su superficie
Pedro David Delgado-López
Corresponding author
pedrodl@yahoo.com

Corresponding author.
, Antonio Montalvo-Afonso, Javier Martín-Alonso, Vicente Martín-Velasco, Rubén Diana-Martín, José Manuel Castilla-Díez
Servicio de Neurocirugía, Hospital Universitario de Burgos, Burgos, Spain
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Tables (4)
Table 1. General clinical-radiological characteristics of the sample of patients studied.
Table 2. Characteristics of patients with meningiomas classified by WHO histological grade.
Table 3. Differences in the surface factor between patients with WHO I and WHO II-III meningiomas.
Table 4. Multivariate analysis of the sample of patients with meningiomas.
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Abstract
Introduction

Predicting the histopathologic grade of meningioma is relevant because local recurrence is significantly greater in WHO grade II–III compared to WHO grade I tumours, which would ideally benefit from a more aggressive surgical strategy. It has been suggested that higher WHO grade tumours are more irregularly-shaped. However, irregularity is a subjective and observer-dependent feature. In this study, the tumour surface irregularity of a large series of meningiomas, measured upon preoperative MRI, is quantified and correlated with the WHO grade.

Methods

Unicentric retrospective observational study of a cohort of symptomatic meningiomas surgically removed in the time period between January 2015 and December 2022. Using specific segmentation software, the Surface Factor (SF) was calculated for each meningioma. SF is an objective parameter that compares the surface of a sphere (minimum surface area for a given volume) with the same volume of the tumour against the actual surface of the tumour. This ratio varies from 0 to 1, being 1 the maximum sphericity. Since irregularly-shaped meningiomas present proportionally greater surface area, the SF tends to decrease as irregularity increases. SF was correlated with WHO grade and its predictive power was estimated with ROC curve analysis.

Results

A total of 176 patients (64.7% females) were included in the study; 120 WHO grade I (71.9%), 43 WHO grade II (25.7%) and 4 WHO grade III (2.4%). A statistically significant difference was found between the mean SF of WHO grade I and WHO grade II–III tumours (0.8651 ± 0.049 versus 0.7081 ± 0.105, p < 0.0001). Globally, the SF correctly classified more than 90% of cases (area under ROC curve 0.940) with 93.3% sensibility and 80.9% specificity. A cutoff value of 0.79 yielded the maximum precision, with positive and negative predictive powers of 82.6% and 92.6%, respectively. Multivariate analysis yielded SF as an independent prognostic factor of WHO grade.

Conclusion

The Surface Factor is an objective and quantitative parameter that helps to identify aggressive meningiomas preoperatively. A cutoff value of 0.79 allowed differentiation between WHO grade I and WHO grade II–III with high precision.

Keywords:
Meningioma
Anaplastic
Histological grade
Surface
Irregularity
Resumen
Introducción

Predecir el grado histológico de los meningiomas es importante por cuanto los grados OMS II-III presentan mucha mayor tendencia a la recidiva local que los grado OMS I y, por tanto, pueden beneficiarse de una estrategia quirúrgica más agresiva. Se ha sugerido que los meningiomas con forma más irregular en la RM preoperatoria tienden a ser más agresivos. Sin embargo, dicha irregularidad es un concepto subjetivo y observador-dependiente. En este estudio se cuantifica de forma objetiva la irregularidad de una serie de meningiomas y se correlaciona con el grado histológico de la OMS.

Métodos

Estudio observacional retrospectivo unicéntrico de una cohorte de meningiomas sintomáticos intervenidos en el período entre enero 2015 y diciembre 2022. Mediante software de segmentación, para cada meningioma se calculó el denominado Factor de Superficie (FS) que es un parámetro objetivo que relaciona la superficie de una esfera (figura con la menor área para un volumen dado) de igual volumen que el tumor con la superficie real del tumor. Este cociente varía de 0 a 1, siendo 1 la máxima esfericidad posible. Dado que los meningiomas de forma irregular presentan una mayor superficie en relación a su volumen, su FS tiende a ser menor cuanto más irregular es el tumor. Se correlacionaron los FS con el grado histológico y se evaluó el poder predictivo del FS mediante curva ROC.

Resultados

Se incluyeron un total de 176 pacientes (64,7% mujeres); 120 grado OMS I (71,9%), 43 grado OMS II (25,7%) y 4 grado OMS III (2,4%). Se constató una diferencia significativa en el FS entre los meningiomas grado OMS I y los OMS II-III (0,8651 ± 0,049 versus 0,7081 ± 0,105, p < 0,0001). Globalmente, el FS permitió clasificar correctamente más del 90% de los pacientes (área bajo la curva ROC de 0,940), con una sensibilidad y especificidad del 93,3% y 80,9%, respectivamente. Un valor de corte de 0,79 proporcionó la máxima precisión para clasificar correctamente el grado histológico, con valores predictivos positivo y negativo del 82,6% y 92,6%, respectivamente. El análisis multivariante identificó el FS como factor pronóstico independiente del grado histológico.

Conclusión

El Factor de Superficie es un parámetro cuantitativo y objetivo que ayuda a identificar los meningiomas agresivos de forma preoperatoria. Un valor de corte de 0,79 permite diferenciar los meningiomas OMS I de los OMS II-III con alta precisión.

Palabras clave:
Meningioma
Anaplásico
Grado histológico
Superficie
Irregularidad

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