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Han T, Zhang J, Liu X, Zhang B, Deng L, Lin X, Jing M, Zhou J. Differentiating atypical meningioma from anaplastic meningioma using diffusion weighted imaging. Clin Imaging 2021; 82:237-243. [PMID: 34915318 DOI: 10.1016/j.clinimag.2021.12.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 11/06/2021] [Accepted: 12/06/2021] [Indexed: 12/17/2022]
Abstract
PURPOSE To explore the value of MRI conventional features and apparent diffusion coefficient (ADC) on the differential diagnosis of atypical meningioma (AtM) and anaplastic meningioma (AnM). MATERIALS AND METHODS This retrospective study analyzed the preoperative clinical data, MRI conventional features, and DWI data of 55 AtM and 25 AnM confirmed by pathology in our hospital. The clinical features, MRI conventional features, ADCmean, ADCmin, and relative ADC (rADC) values were compared between the two tumors by Chi-square test or an independent sample t-test. Receiver operating characteristic curve (ROC) and binary logistic regression analysis were used to evaluate the diagnostic efficacy of each parameter to differentiate between these tumors. RESULTS The MRI conventional features had a certain ability to distinguish AnM and AtM, with an area under the curve value (AUC) of 0.824 (95% CI, 0.723-0.900). The ADCmean, ADCmin, and rADC values were significantly higher in AtM compared to AnM (all P < 0.05). ADCmean had the best identification effect with an AUC of 0.867 (95% CI, 0.772-0.933) among them, at an cut-off of 0.817 × 10-3 mm2/s, the sensitivity and specificity of distinguishing AtM from AnM were 78.18% and 88.00%, respectively. A combination of ADCmean and MRI conventional features showed the optimum discrimination ability for the two tumors, the AUC, sensitivity, specificity, and accuracy were 0.918 (95% CI, 0.835-0.967), 80.00%, 94.55%, and 90.00%, respectively. CONCLUSION MRI conventional features combined with ADCmean, as a non-invasive method, has potential clinical value in the preoperative diagnosis of AtM and AnM.
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Affiliation(s)
- Tao Han
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730030, China; Second Clinical School, Lanzhou University, Lanzhou 730000, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou 730030, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730030, China
| | - Jing Zhang
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730030, China; Second Clinical School, Lanzhou University, Lanzhou 730000, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou 730030, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730030, China
| | - Xianwang Liu
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730030, China; Second Clinical School, Lanzhou University, Lanzhou 730000, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou 730030, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730030, China
| | - Bin Zhang
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730030, China; Second Clinical School, Lanzhou University, Lanzhou 730000, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou 730030, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730030, China
| | - Liangna Deng
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730030, China; Second Clinical School, Lanzhou University, Lanzhou 730000, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou 730030, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730030, China
| | - Xiaoqiang Lin
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730030, China; Second Clinical School, Lanzhou University, Lanzhou 730000, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou 730030, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730030, China
| | - Mengyuan Jing
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730030, China; Second Clinical School, Lanzhou University, Lanzhou 730000, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou 730030, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730030, China
| | - Junlin Zhou
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730030, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou 730030, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730030, China.
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Zhang R, Chen X, Cai J, Jiang P, Chen Y, Sun B, Song Y, Lin L, Xue Y. A Novel MRI-Based Risk Stratification Algorithm for Predicting Postoperative Recurrence of Meningioma: More Benefits to Patients. Front Oncol 2021; 11:737520. [PMID: 34737953 PMCID: PMC8560899 DOI: 10.3389/fonc.2021.737520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 10/04/2021] [Indexed: 11/19/2022] Open
Abstract
Pathological grading of meningioma is insufficient to predict recurrence after resection and to guide individualized treatment strategies. One hundred and thirty-three patients with meningiomas who underwent total resection were enrolled in this retrospective study. Univariate analyses were conducted to evaluate the association between factors and recurrence. Least absolute shrinkage and selection operator (Lasso) was used to further select variables to build a logistic model. The predictive efficiency of the model and WHO grade was compared by using receiver operating characteristic curve (ROC), decision curve analysis (DCA), and net reclassification improvement (NRI). Patients were given a new risk layer based on a nomogram. The recurrence of meningioma in different groups was observed through the Kaplan-Meier curve. Univariate analysis demonstrated that 11 risk factors were associated with prognosis (P < 0.05). The result of ROC proved that the quantified risk-scoring system (AUC = 0.853) had a higher benefit than pathological grade (AUC = 0.689, P = 0.011). The incidence of recurrence of the high risk cohort (69%) was significantly higher than that of the low risk cohort (9%) by Kaplan-Meier analysis (P < 0.001). And all patients who did not relapse in the high risk group received adjuvant radiotherapy. The novel risk stratification algorithm has a significant value for the recurrence of meningioma and can help in optimizing the individualized design of clinical therapy.
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Affiliation(s)
- Rufei Zhang
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Xiaodan Chen
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Jialing Cai
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Peirong Jiang
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China.,School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China
| | - Yilin Chen
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China.,School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China
| | - Bin Sun
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China.,School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China
| | - Yang Song
- MR Scientific Marketing, Siemens, Healthineers Ltd, Shanghai, China
| | - Lin Lin
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China.,School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China
| | - Yunjing Xue
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China.,School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China
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Meningiomas: A review of general, histopathological, clinical and molecular characteristics. Pathol Res Pract 2021; 223:153476. [PMID: 33991850 DOI: 10.1016/j.prp.2021.153476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 05/04/2021] [Accepted: 05/07/2021] [Indexed: 11/20/2022]
Abstract
OBJECTIVES In this review, the main histological and molecular characteristics of meningiomas will be addressed, as well as the aspects most related to clinical conditions, treatment, and survival of patients, enabling a better understanding of these tumors behavior. METHODS This study was conducted with the search for published studies available on NCBI, PubMed, MEDLINE, Scielo and Google Scholar. Relevant documents have been identified and 50 articles were selected. RESULTS The main points about meningiomas were characterized, as well as the histological presence of spontaneous necrosis in grade I and brain invasion as diagnostic criteria, their molecular origin related to deletion of chromosome 22 and mutations in theNF2 and TERT genes, in addition to their clinical characteristics. The preferential treatment remains the total resection of the tumor. CONCLUSION The information about meningiomas is well known and necessary, but it is expected that more work will emerge related to the behavior of these tumors, and that the scientific community will obtain more clarity about the best ways to conduct the patients treatment.
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Nakasu S, Notsu A, Na K, Nakasu Y. Malignant transformation of WHO grade I meningiomas after surgery or radiosurgery: systematic review and meta-analysis of observational studies. Neurooncol Adv 2020; 2:vdaa129. [PMID: 33305267 PMCID: PMC7712809 DOI: 10.1093/noajnl/vdaa129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Background The incidence and clinical features of the malignant transformation of benign meningiomas are poorly understood. This study examined the risk of the malignant transformation of benign meningiomas after surgery or stereotactic radiosurgery. Methods We systematically reviewed studies published between 1979 and 2019 using PubMed, Scopus, and other sources. We analyzed pooled data according to the PRISMA guideline to clarify the incidence rate of malignant transformation (IMT) and factors affecting malignant transformation in surgically or radiosurgically treated benign meningiomas. Results IMT was 2.98/1000 patient-years (95% confidence interval [CI] = 1.9–4.3) in 13 studies in a single-arm meta-analysis. Although the evidence level of the included studies was low, the heterogeneity of the incidence was mostly explained by the tumor location. In meta-regression analysis, skull base tumors had a significantly lower IMT than non-skull base tumors, but no gender association was observed. IMT after radiosurgery in 9 studies was 0.50/1000 person-years (95% CI = 0.02–1.38). However, a higher proportion of skull base tumors, lower proportion of males, and lower salvage surgery rate were observed in the radiosurgery group than in the surgery group. The median time to malignant change was 5 years (interquartile range = 2.5–8.2), and the median survival after malignant transformation was 4.7 years (95% CI = 3.7–8) in individual case data. Conclusion IMT of benign meningioma was significantly affected by the tumor location. Radiosurgery did not appear to increase IMT, but exact comparisons were difficult because of differences in study populations.
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Affiliation(s)
- Satoshi Nakasu
- Division of Neurosurgery, Kusatsu General Hospital, Kusatsu, Japan.,Department of Neurosurgery, Shiga University of Medical Science, Ohtsu, Japan
| | - Akifumi Notsu
- Clinical Research Center, Shizuoka Cancer Center, Nagaizumi, Japan
| | - Kiyong Na
- Department of Pathology, Kyung Hee University Hospital, Kyung Hee University College of Medicine, Seoul, South Korea
| | - Yoko Nakasu
- Department of Neurosurgery, Shiga University of Medical Science, Ohtsu, Japan.,Division of Neurosurgery, Shizuoka Cancer Center, Nagaizumi, Japan
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Garzon-Muvdi T, Bailey DD, Pernik MN, Pan E. Basis for Immunotherapy for Treatment of Meningiomas. Front Neurol 2020; 11:945. [PMID: 32982948 PMCID: PMC7483661 DOI: 10.3389/fneur.2020.00945] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2020] [Accepted: 07/21/2020] [Indexed: 12/15/2022] Open
Abstract
Meningiomas are common tumors that account for approximately one third of CNS tumors diagnosed every year. They are classified by the World Health Organization in grades I-III. Higher grades have an increased rate of growth, invasiveness, rate of recurrence, and worse outcomes than lower grades. Most meningiomas are grade I, while ~18% of meningiomas are grade II and III in hospital-based series. Meningiomas are typically "benign" tumors that are treated with surgery and radiation. However, when they recur or are unresectable, treatment options are very limited, especially since they are chemotherapy-resistant. Recent advances in the treatment of cancers with immunotherapy have focused on checkpoint blockade as well as other types of immunotherapy. There is emerging evidence supporting the use of immunotherapy as a potentially effective treatment strategy for meningioma patients. The immune microenvironment of meningiomas is a complex interplay of genetic alterations, immunomodulatory protein expression, and tumor-immune cell interactions. Meningiomas are known to be infiltrated by immune cells including microglia, macrophages, B-cells, and T-cells. Several mechanisms contribute to decreased an ti-tumor immune response, allowing tumor growth and evasion of the immune system. We discuss the most current knowledge on the immune micro-environment of meningiomas, preclinical findings of immunotherapy in meningiomas, meningioma immunotherapy clinical trials, and also offer insight into future prospects for immunotherapies in meningiomas.
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Affiliation(s)
- Tomas Garzon-Muvdi
- Department of Neurosurgery, UT Southwestern Medical Center, Dallas, TX, United States
| | - Destiny D. Bailey
- Department of Neurosurgery, UT Southwestern Medical Center, Dallas, TX, United States
| | - Mark N. Pernik
- Department of Neurosurgery, UT Southwestern Medical Center, Dallas, TX, United States
| | - Edward Pan
- Department of Neurology, UT Southwestern Medical Center, Dallas, TX, United States
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Bale TA, Benhamida J, Roychoudury S, Villafania L, Wrzolek MA, Bouffard JP, Bapat K, Ladanyi M, Rosenblum MK. Infarction with associated pseudosarcomatous changes mimics anaplasia in otherwise grade I meningiomas. Mod Pathol 2020; 33:1298-1306. [PMID: 32047229 PMCID: PMC8392373 DOI: 10.1038/s41379-020-0491-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Revised: 01/28/2020] [Accepted: 01/29/2020] [Indexed: 12/26/2022]
Abstract
We describe a morphologically distinct pattern of tumor infarction and associated sarcoma-like changes, mimicking focal anaplasia, in otherwise WHO grade I meningiomas. The described cases (n = 9) all demonstrated a discrete spindle-cell (pseudosarcomatous) component with brisk mitotic activity (12-14 mitoses/10 HPF), elevated Ki-67 (mean 75.5 ± 25.0%, quantified), absence of PR, SSTR2A, or EMA expression, and potential SMA expression (50%). Despite these high-grade features, all nine patients remained free of progression or recurrence post resection (follow-up mean: 49.8 months). In contrast, among a comparison (control) cohort of consecutive WHO grade II and III meningiomas (n = 16), as expected, progression rate was high (68.8%, P = 0.002, Fisher's exact, average time to progression = 25 months, follow-up mean: 39.8 months). While necrosis was a frequent feature among atypical/anaplastic meningiomas (12/16, 75%), and elevated mitoses and proliferative index were present consistent with histologic grade, a well-defined zonal pattern with pseudosarcomatous component was not present among these tumors. DNA methylation-based analysis readily distinguished meningiomas by copy number profiles and DNA-based methylation meningioma random forest classification analysis (meningioma v2.4 classifier developed at University of Heidelberg); all pseudosarcomatous cases analyzed (4/9) matched with high level calibrated classifier score to "MC benign-1", with isolated loss of chromosome 22q identified as the sole copy number alteration. In contrast, multiple chromosomal losses were detected among the comparison cohort and classifier results demonstrated good concordance with histologic grade. Our findings suggest that pseudosarcomatous alterations represent reactive changes to central meningioma infarction, rather than focal anaplasia, and further support the use of DNA methylation-based analysis as a useful adjunct for predicting meningioma behavior. These indolent tumors should be distinguished from their atypical and anaplastic counterparts.
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Affiliation(s)
- Tejus A Bale
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
| | - Jamal Benhamida
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | - Liliana Villafania
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Monika A Wrzolek
- Department of Pathology, Staten Island University Hospital, New York, NY, USA
| | | | - Kalyani Bapat
- Department of Pathology, White Plains Hospital, New York, NY, USA
| | - Marc Ladanyi
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Marc K Rosenblum
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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7
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Sarhan AM. Brain Tumor Classification in Magnetic Resonance Images Using Deep Learning and Wavelet Transform. ACTA ACUST UNITED AC 2020. [DOI: 10.4236/jbise.2020.136010] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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Salah F, Tabbarah A, ALArab y N, Asmar K, Tamim H, Makki M, Sibahi A, Hourani R. Can CT and MRI features differentiate benign from malignant meningiomas? Clin Radiol 2019; 74:898.e15-898.e23. [DOI: 10.1016/j.crad.2019.07.020] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Accepted: 07/25/2019] [Indexed: 12/01/2022]
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Proctor DT, Huang J, Lama S, Albakr A, Van Marle G, Sutherland GR. Tumor-associated macrophage infiltration in meningioma. Neurooncol Adv 2019; 1:vdz018. [PMID: 32642654 PMCID: PMC7212927 DOI: 10.1093/noajnl/vdz018] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Background Meningioma, a most common brain tumor, has a high rate of recurrence. Tumor-associated macrophages (TAMs) are the most abundant immune cell type in meningioma. TAMs display functional phenotypic diversity and may establish either an inflammatory and anti-tumoral or an immunosuppressive and pro-tumoral microenvironment. TAM subtypes present in meningioma and potential contribution to growth and recurrence is unknown. Methods Immunofluorescence staining was used to quantify M1 and M2 TAM populations in tissues obtained from 30 meningioma patients. Associations between M1 and M2 cells, M1:M2 cell ratio to tumor characteristics, WHO grade, recurrence, size, location, peri-tumoral edema, and patient demographics such as age and sex were examined. Results TAM cells accounted for ~18% of all cells in meningioma tissues. More than 80% of infiltrating TAMs were found to be of pro-tumoral M2 phenotype and correlated to tumor size (P = .0409). M1:M2 cell ratio was significantly decreased in WHO grade II, compared to grade I tumors (P = .009). Furthermore, a 2.3-fold difference in M1:M2 ratio between primary (0.14) and recurrent (0.06) tumors was observed (n = 18 and 12 respectively, P = .044). Conclusion This study is the first to confirm existence of pro-tumoral M2 TAMs in the meningioma microenvironment, emphasizing its potential role in tumor growth and recurrence.
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Affiliation(s)
- Dustin T Proctor
- Project neuroArm, Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Jordan Huang
- Project neuroArm, Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.,Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Alberta, Canada
| | - Sanju Lama
- Project neuroArm, Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.,Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Alberta, Canada
| | - Abdulrahman Albakr
- Project neuroArm, Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Department of Neurosurgery, King Saud University, Riyadh, Saudi Arabia
| | - Guido Van Marle
- Department of Microbiology, Immunology and Infectious Diseases, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Garnette R Sutherland
- Project neuroArm, Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.,Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Alberta, Canada
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Lavrador JP, Acharya S, Giamouriadis A, Vergani F, Ashkan K, Bhangoo R. Letter to the Editor. Intermediate-risk meningioma and NRG Oncology RTOG 0539. J Neurosurg 2018; 129:1651-1653. [PMID: 30265197 DOI: 10.3171/2018.4.jns18811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Barresi V, Lionti S, Caliri S, Caffo M. Histopathological features to define atypical meningioma: What does really matter for prognosis? Brain Tumor Pathol 2018; 35:168-180. [PMID: 29671247 DOI: 10.1007/s10014-018-0318-z] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Accepted: 04/12/2018] [Indexed: 12/18/2022]
Abstract
Atypical meningiomas are diagnosed in the presence of: (1) three or more of the following minor atypical criteria: increased cellularity, small cells with a high nuclear/cytoplasmic ratio, prominent nucleoli, sheeting, and foci of spontaneous or geographic necrosis; (2) mitotic count ≥ 4 mitoses per 10 HPF (high mitotic index); (3) brain invasion. The 5-year disease-free survival (DFS) is around 50%. Due to their heterogeneous behavior, the post-surgical treatment of atypical meningiomas is controversial. This study investigated the ability of histopathological features to predict recurrence risk of atypical meningiomas. Meningiomas classified as atypical only on minor atypical criteria had low recurrence risk. Brain invasion, high mitotic index and sheeting were significantly associated with shorter disease-free survival (DFS) (P = 0.001; P = 0.01; P = 0.01). The presence of brain invasion and the co-presence of sheeting and high mitotic index had the highest ability to identify recurring meningiomas (P = 0.0001) (sensitivity: 90.9%; specificity: 86.7%). Our results suggest reconsideration of classification of meningiomas as atypical based only on minor atypical criteria. The presence of brain invasion and the co-occurrence of sheeting and high mitotic count may be useful to identify high risk cases, which may benefit from adjuvant treatments.
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Affiliation(s)
- Valeria Barresi
- Dipartimento di Patologia Umana dell'Adulto e dell'Età Evolutiva "G. Barresi", AOU Policlinico G. Martino, Pad D, University of Messina, Via Consolare Valeria, 98125, Messina, Italy.
| | - Simona Lionti
- Dipartimento di Patologia Umana dell'Adulto e dell'Età Evolutiva "G. Barresi", AOU Policlinico G. Martino, Pad D, University of Messina, Via Consolare Valeria, 98125, Messina, Italy
| | - Samuel Caliri
- Dipartimento di Patologia Umana dell'Adulto e dell'Età Evolutiva "G. Barresi", AOU Policlinico G. Martino, Pad D, University of Messina, Via Consolare Valeria, 98125, Messina, Italy
| | - Maria Caffo
- Dipartimento di Scienze biomediche, odontoiatriche e delle immagini morfologiche e funzionali, University of Messina, Messina, Italy
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