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Rammeloo E, Schouten JW, Krikour K, Bos EM, Berger MS, Nahed BV, Vincent AJPE, Gerritsen JKW. Preoperative assessment of eloquence in neurosurgery: a systematic review. J Neurooncol 2023; 165:413-430. [PMID: 38095774 DOI: 10.1007/s11060-023-04509-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 11/12/2023] [Indexed: 12/29/2023]
Abstract
BACKGROUND AND OBJECTIVES Tumor location and eloquence are two crucial preoperative factors when deciding on the optimal treatment choice in glioma management. Consensus is currently lacking regarding the preoperative assessment and definition of eloquent areas. This systematic review aims to evaluate the existing definitions and assessment methods of eloquent areas that are used in current clinical practice. METHODS A computer-aided search of Embase, Medline (OvidSP), and Google Scholar was performed to identify relevant studies. This review includes articles describing preoperative definitions of eloquence in the study's Methods section. These definitions were compared and categorized by anatomical structure. Additionally, various techniques to preoperatively assess tumor eloquence were extracted, along with their benefits, drawbacks and ease of use. RESULTS This review covers 98 articles including 12,714 participants. Evaluation of these studies indicated considerable variability in defining eloquence. Categorization of these definitions yielded a list of 32 brain regions that were considered eloquent. The most commonly used methods to preoperatively determine tumor eloquence were anatomical classification systems and structural MRI, followed by DTI-FT, functional MRI and nTMS. CONCLUSIONS There were major differences in the definitions and assessment methods of eloquence, and none of them proved to be satisfactory to express eloquence as an objective, quantifiable, preoperative factor to use in glioma decision making. Therefore, we propose the development of a novel, objective, reliable, preoperative classification system to assess eloquence. This should in the future aid neurosurgeons in their preoperative decision making to facilitate personalized treatment paradigms and to improve surgical outcomes.
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Affiliation(s)
- Emma Rammeloo
- Department of Neurosurgery, Erasmus Medical Center Rotterdam, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.
| | - Joost Willem Schouten
- Department of Neurosurgery, Erasmus Medical Center Rotterdam, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | - Keghart Krikour
- Department of Neurosurgery, Erasmus Medical Center Rotterdam, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | - Eelke Marijn Bos
- Department of Neurosurgery, Erasmus Medical Center Rotterdam, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | - Mitchel Stuart Berger
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Brian Vala Nahed
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Jasper Kees Wim Gerritsen
- Department of Neurosurgery, Erasmus Medical Center Rotterdam, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
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Huckhagel T, Stadelmann C, Abboud T, Riedel C. Determining the applicability of the RSNA radiology lexicon (RadLex) in high-grade glioma MRI reporting-a preliminary study on 20 consecutive cases with newly diagnosed glioblastoma. BMC Med Imaging 2022; 22:53. [PMID: 35331160 DOI: 10.1186/s12880-022-00776-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 03/13/2022] [Indexed: 11/30/2022] Open
Abstract
Background The implementation of a collective terminology in radiological reporting such as the RSNA radiological lexicon (RadLex) yields many benefits including unambiguous communication of findings, improved education, and fostering data mining for research purposes. While some fields in general radiology have already been evaluated so far, this is the first exploratory approach to assess the applicability of the RadLex terminology to glioblastoma (GBM) MRI reporting.
Methods Preoperative brain MRI reports of 20 consecutive patients with newly diagnosed GBM (mean age 68.4 ± 10.8 years; 12 males) between January and October 2010 were retrospectively identified. All terms related to the tumor as well as their frequencies of mention were extracted from the MRI reports by two independent neuroradiologists. Every item was subsequently analyzed with respect to an equivalent RadLex representation and classified into one of four groups as follows: 1. verbatim RadLex entity, 2. synonymous/multiple equivalent(s), 3. combination of RadLex concepts, or 4. no RadLex equivalent. Additionally, verbatim entities were categorized using the hierarchical RadLex Tree Browser. Results A total of 160 radiological terms were gathered. 123/160 (76.9%) items showed literal RadLex equivalents, 9/160 (5.6%) items had synonymous (non-verbatim) or multiple counterparts, 21/160 (13.1%) items were represented by means of a combination of concepts, and 7/160 (4.4%) entities could not eventually be transferred adequately into the RadLex ontology. Conclusions Our results suggest a sufficient term coverage of the RadLex terminology for GBM MRI reporting. If applied extensively, it may improve communication of radiological findings and facilitate data mining for large-scale research purposes. Supplementary Information The online version contains supplementary material available at 10.1186/s12880-022-00776-8.
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McAleenan A, Kelly C, Spiga F, Kernohan A, Cheng HY, Dawson S, Schmidt L, Robinson T, Brandner S, Faulkner CL, Wragg C, Jefferies S, Howell A, Vale L, Higgins JPT, Kurian KM. Prognostic value of test(s) for O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation for predicting overall survival in people with glioblastoma treated with temozolomide. Cochrane Database Syst Rev 2021; 3:CD013316. [PMID: 33710615 PMCID: PMC8078495 DOI: 10.1002/14651858.cd013316.pub2] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
BACKGROUND Glioblastoma is an aggressive form of brain cancer. Approximately five in 100 people with glioblastoma survive for five years past diagnosis. Glioblastomas that have a particular modification to their DNA (called methylation) in a particular region (the O6-methylguanine-DNA methyltransferase (MGMT) promoter) respond better to treatment with chemotherapy using a drug called temozolomide. OBJECTIVES To determine which method for assessing MGMT methylation status best predicts overall survival in people diagnosed with glioblastoma who are treated with temozolomide. SEARCH METHODS We searched MEDLINE, Embase, BIOSIS, Web of Science Conference Proceedings Citation Index to December 2018, and examined reference lists. For economic evaluation studies, we additionally searched NHS Economic Evaluation Database (EED) up to December 2014. SELECTION CRITERIA Eligible studies were longitudinal (cohort) studies of adults with diagnosed glioblastoma treated with temozolomide with/without radiotherapy/surgery. Studies had to have related MGMT status in tumour tissue (assessed by one or more method) with overall survival and presented results as hazard ratios or with sufficient information (e.g. Kaplan-Meier curves) for us to estimate hazard ratios. We focused mainly on studies comparing two or more methods, and listed brief details of articles that examined a single method of measuring MGMT promoter methylation. We also sought economic evaluations conducted alongside trials, modelling studies and cost analysis. DATA COLLECTION AND ANALYSIS Two review authors independently undertook all steps of the identification and data extraction process for multiple-method studies. We assessed risk of bias and applicability using our own modified and extended version of the QUality In Prognosis Studies (QUIPS) tool. We compared different techniques, exact promoter regions (5'-cytosine-phosphate-guanine-3' (CpG) sites) and thresholds for interpretation within studies by examining hazard ratios. We performed meta-analyses for comparisons of the three most commonly examined methods (immunohistochemistry (IHC), methylation-specific polymerase chain reaction (MSP) and pyrosequencing (PSQ)), with ratios of hazard ratios (RHR), using an imputed value of the correlation between results based on the same individuals. MAIN RESULTS We included 32 independent cohorts involving 3474 people that compared two or more methods. We found evidence that MSP (CpG sites 76 to 80 and 84 to 87) is more prognostic than IHC for MGMT protein at varying thresholds (RHR 1.31, 95% confidence interval (CI) 1.01 to 1.71). We also found evidence that PSQ is more prognostic than IHC for MGMT protein at various thresholds (RHR 1.36, 95% CI 1.01 to 1.84). The data suggest that PSQ (mainly at CpG sites 74 to 78, using various thresholds) is slightly more prognostic than MSP at sites 76 to 80 and 84 to 87 (RHR 1.14, 95% CI 0.87 to 1.48). Many variants of PSQ have been compared, although we did not see any strong and consistent messages from the results. Targeting multiple CpG sites is likely to be more prognostic than targeting just one. In addition, we identified and summarised 190 articles describing a single method for measuring MGMT promoter methylation status. AUTHORS' CONCLUSIONS PSQ and MSP appear more prognostic for overall survival than IHC. Strong evidence is not available to draw conclusions with confidence about the best CpG sites or thresholds for quantitative methods. MSP has been studied mainly for CpG sites 76 to 80 and 84 to 87 and PSQ at CpG sites ranging from 72 to 95. A threshold of 9% for CpG sites 74 to 78 performed better than higher thresholds of 28% or 29% in two of three good-quality studies making such comparisons.
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Affiliation(s)
- Alexandra McAleenan
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Claire Kelly
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Francesca Spiga
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ashleigh Kernohan
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Hung-Yuan Cheng
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Sarah Dawson
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Applied Research Collaboration West (ARC West) , University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | - Lena Schmidt
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tomos Robinson
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Sebastian Brandner
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- Division of Neuropathology, The National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Claire L Faulkner
- Bristol Genetics Laboratory, Pathology Sciences, Southmead Hospital, Bristol, UK
| | - Christopher Wragg
- Bristol Genetics Laboratory, Pathology Sciences, Southmead Hospital, Bristol, UK
| | - Sarah Jefferies
- Department of Oncology, Addenbrooke's Hospital, Cambridge, UK
| | - Amy Howell
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Luke Vale
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Julian P T Higgins
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Applied Research Collaboration West (ARC West) , University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | - Kathreena M Kurian
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Bristol Medical School: Brain Tumour Research Centre, Public Health Sciences, University of Bristol, Bristol, UK
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Tanoue S, Nakaura T, Nagayama Y, Uetani H, Ikeda O, Yamashita Y. Virtual Monochromatic Image Quality from Dual-Layer Dual-Energy Computed Tomography for Detecting Brain Tumors. Korean J Radiol 2021; 22:951-958. [PMID: 33569932 PMCID: PMC8154786 DOI: 10.3348/kjr.2020.0677] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 09/13/2020] [Accepted: 10/08/2020] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To evaluate the usefulness of virtual monochromatic images (VMIs) obtained using dual-layer dual-energy CT (DL-DECT) for evaluating brain tumors. MATERIALS AND METHODS This retrospective study included 32 patients with brain tumors who had undergone non-contrast head CT using DL-DECT. Among them, 15 had glioblastoma (GBM), 7 had malignant lymphoma, 5 had high-grade glioma other than GBM, 3 had low-grade glioma, and 2 had metastatic tumors. Conventional polychromatic images and VMIs (40-200 keV at 10 keV intervals) were generated. We compared CT attenuation, image noise, contrast, and contrast-to-noise ratio (CNR) between tumor and white matter (WM) or grey matter (GM) between VMIs showing the highest CNR (optimized VMI) and conventional CT images using the paired t test. Two radiologists subjectively assessed the contrast, margin, noise, artifact, and diagnostic confidence of optimized VMIs and conventional images on a 4-point scale. RESULTS The image noise of VMIs at all energy levels tested was significantly lower than that of conventional CT images (p < 0.05). The 40-keV VMIs yielded the best CNR. Furthermore, both contrast and CNR between the tumor and WM were significantly higher in the 40 keV images than in the conventional CT images (p < 0.001); however, the contrast and CNR between tumor and GM were not significantly different (p = 0.47 and p = 0.31, respectively). The subjective scores assigned to contrast, margin, and diagnostic confidence were significantly higher for 40 keV images than for conventional CT images (p < 0.01). CONCLUSION In head CT for patients with brain tumors, compared with conventional CT images, 40 keV VMIs from DL-DECT yielded superior tumor contrast and diagnostic confidence, especially for brain tumors located in the WM.
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Affiliation(s)
- Shota Tanoue
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan.
| | - Takeshi Nakaura
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan
| | - Yasunori Nagayama
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan
| | - Hiroyuki Uetani
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan
| | - Osamu Ikeda
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan
| | - Yasuyuki Yamashita
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan
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Luo H, Tao C, Wang P, Li J, Huang K, Zhu X. Development of a prognostic index based on immunogenomic landscape analysis in glioma. Immun Inflamm Dis 2021; 9:467-479. [PMID: 33503296 PMCID: PMC8127549 DOI: 10.1002/iid3.407] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 01/05/2021] [Accepted: 01/09/2021] [Indexed: 12/21/2022]
Abstract
Background Glioma is the most common intracranial tumor. The inflammatory response actively participates in the malignancy of gliomas. There is still limited knowledge about the biological function of immune‐related genes (IRGs) and their potential involvement in the malignancy of gliomas. Methods We screened differentially expressed and survival‐associated IRGs, and explored their potential molecular characteristics. Then we developed a prognostic index derived from seven hub IRGs. A prognostic nomogram was built to indicate the prognostic value of the prognostic index and seven IRGs. We characterized the immune infiltration landscape to analyze tumor‐immune interactions. The real‐time quantitative polymerase chain reaction assay was performed to validate bioinformatics results. Results The differentially expressed IRGs are involved in cell chemotaxis, cytokine activity, and the chemokine‐mediated signaling pathway. The prognostic index derived from seven IRGs had clinical prognostic value in glioma, and positively correlated with the malignant clinicopathological characteristics. A nomogram further indicated that the prognostic index and seven hub IRGs had clinical prognostic value for gliomas. We revealed that the prognostic index could reflect the state of the glioma immune microenvironment. Conclusion This study demonstrates the importance of an IRG‐based prognostic index as a potential biomarker for predicting malignancy in gliomas.
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Affiliation(s)
- Haitao Luo
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Chuming Tao
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.,East China Institute of Digital Medical Engineering, Shangrao, Jiangxi, China
| | - Peng Wang
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Jingying Li
- Department of Comprehensive Intensive Care Unit, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Kai Huang
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.,Institute of Neuroscience, Nanchang University, Nanchang, Jiangxi, China
| | - Xingen Zhu
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.,Institute of Neuroscience, Nanchang University, Nanchang, Jiangxi, China
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Bu L, Hameed NUF, Luo C, Hong P, Zhou X, Wang S, Wu S. Germline ALK variations are associated with a poor prognosis in glioma and IDH-wildtype glioblastoma. J Neurooncol 2021; 152:27-36. [PMID: 33486679 DOI: 10.1007/s11060-020-03676-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Accepted: 12/12/2020] [Indexed: 12/21/2022]
Abstract
BACKGROUND Glioma is the most common primary brain tumor. Clear classification is crucial for accurate diagnosis and individualized treatment. Histopathological characteristics and genetic alterations have shown to be related to prognosis and treatment response. Germline variants are important components of genetic alterations. However, the distribution of germline variations in glioma patients and their association with survival remain unknown. METHODS We carried out whole-exome sequencing on 99 cases to explore germline variants in glioma. We also analyzed the association of germline variants with clinicopathological features and other prognostic indicators. RESULTS All the glioma cases harbored rare germline variants. Germline ALK variants (gALK-Mut) were identified in 12/99 (12.12%) patients. The gALK-Mut patients had significantly shorter overall survival than germline ALK wildtype (gALK-WT) patients in the all glioma group (99 cases) and the subset of patients with IDH-wildtype glioblastoma (IDH-WT-GBM, 39 cases) (P = 0.013 and 0.027, respectively). The gALK-Mut patients also had higher frequency of BIRC5, PIK3CA and RPN1 somatic mutations than the gALK-WT patients in IDH-WT-GBM. Other confounding factors appeared to contribute to patient survival. The subgroup of patients in IDH-WT-GBM with gALK-Mut/TP53-Mut had worse prognosis than the gALK-WT/TP53-Mut subgroup (P = 0.031); The gALK-Mut/TERT-WT and gALK-Mut/TERT-Mut subgroups both had a worse prognosis than the gALK-WT/TERT-Mut subgroup (P = 0.031 and 0.018, respectively). CONCLUSIONS Our study revealed ALK variation was an independent indicator of poor prognosis in glioma and IDH-WT-GBM. It could be a promising biomarker and tractable therapeutic target for this deadly disease.
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Affiliation(s)
- Linghao Bu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.,Neurosurgical Institute of Fudan University, Shanghai, China.,Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China.,Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, China
| | - N U Farrukh Hameed
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.,Neurosurgical Institute of Fudan University, Shanghai, China.,Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China.,Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, China
| | - Chen Luo
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.,Neurosurgical Institute of Fudan University, Shanghai, China.,Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China.,Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, China
| | - Pengjie Hong
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.,Neurosurgical Institute of Fudan University, Shanghai, China.,Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China.,Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, China
| | - Xiaoyu Zhou
- GenomiCare Biotechnology (Shanghai) Co. Ltd.,, Shanghai, China
| | - Shengzhou Wang
- GenomiCare Biotechnology (Shanghai) Co. Ltd.,, Shanghai, China
| | - Shuai Wu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China. .,Neurosurgical Institute of Fudan University, Shanghai, China. .,Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China. .,Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, China.
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Abstract
Whenever possible, maximal safe resection is the first intervention for management of glioblastoma. Resection offers tissue for diagnosis, decompression of the brain, cytoreduction, and has been associated with prolonged survival in numerous retrospective studies. In this review, we provide a critical overview of the literature associating glioblastoma resection with survival. We discuss techniques that enhance extent of resection, and the role of clinical and surgeon-variables. At last, we analyze the covariates and confounders that might influence the relationship between extent of resection and survival for glioblastoma, as these might ultimately also influence outcomes and other therapeutic interventions tested in trials.
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Müller DMJ, Robe PA, Ardon H, Barkhof F, Bello L, Berger MS, Bouwknegt W, Van den Brink WA, Conti Nibali M, Eijgelaar RS, Furtner J, Han SJ, Hervey-Jumper SL, Idema AJS, Kiesel B, Kloet A, De Munck JC, Rossi M, Sciortino T, Vandertop WP, Visser M, Wagemakers M, Widhalm G, Witte MG, Zwinderman AH, De Witt Hamer PC. Quantifying eloquent locations for glioblastoma surgery using resection probability maps. J Neurosurg 2020; 134:1091-1101. [PMID: 32244208 DOI: 10.3171/2020.1.jns193049] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Accepted: 01/21/2020] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Decisions in glioblastoma surgery are often guided by presumed eloquence of the tumor location. The authors introduce the "expected residual tumor volume" (eRV) and the "expected resectability index" (eRI) based on previous decisions aggregated in resection probability maps. The diagnostic accuracy of eRV and eRI to predict biopsy decisions, resectability, functional outcome, and survival was determined. METHODS Consecutive patients with first-time glioblastoma surgery in 2012-2013 were included from 12 hospitals. The eRV was calculated from the preoperative MR images of each patient using a resection probability map, and the eRI was derived from the tumor volume. As reference, Sawaya's tumor location eloquence grades (EGs) were classified. Resectability was measured as observed extent of resection (EOR) and residual volume, and functional outcome as change in Karnofsky Performance Scale score. Receiver operating characteristic curves and multivariable logistic regression were applied. RESULTS Of 915 patients, 674 (74%) underwent a resection with a median EOR of 97%, functional improvement in 71 (8%), functional decline in 78 (9%), and median survival of 12.8 months. The eRI and eRV identified biopsies and EORs of at least 80%, 90%, or 98% better than EG. The eRV and eRI predicted observed residual volumes under 10, 5, and 1 ml better than EG. The eRV, eRI, and EG had low diagnostic accuracy for functional outcome changes. Higher eRV and lower eRI were strongly associated with shorter survival, independent of known prognostic factors. CONCLUSIONS The eRV and eRI predict biopsy decisions, resectability, and survival better than eloquence grading and may be useful preoperative indices to support surgical decisions.
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Affiliation(s)
- Domenique M J Müller
- 1Brain Tumor Center & Department of Neurosurgery, Cancer Center Amsterdam, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, The Netherlands
| | - Pierre A Robe
- 2Department of Neurology & Neurosurgery, University Medical Center Utrecht, The Netherlands
| | - Hilko Ardon
- 3Department of Neurosurgery, St. Elisabeth Hospital, Tilburg, The Netherlands
| | - Frederik Barkhof
- 4Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Vrije Universiteit, University Medical Center, Amsterdam, The Netherlands.,5Institutes of Neurology and Healthcare Engineering, University College London, United Kingdom
| | - Lorenzo Bello
- 6Neurosurgical Oncology Unit, Departments of Oncology and Remato-Oncology, Università degli Studi di Milano, Humanitas Research Hospital, IRCCS, Milan, Italy
| | - Mitchel S Berger
- 7Department of Neurological Surgery, University of California, San Francisco, California
| | - Wim Bouwknegt
- 8Department of Neurosurgery, Medical Center Slotervaart, Amsterdam, The Netherlands
| | | | - Marco Conti Nibali
- 6Neurosurgical Oncology Unit, Departments of Oncology and Remato-Oncology, Università degli Studi di Milano, Humanitas Research Hospital, IRCCS, Milan, Italy
| | - Roelant S Eijgelaar
- 10Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Julia Furtner
- 11Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Austria
| | - Seunggu J Han
- 12Department of Neurological Surgery, Oregon Health and Science University, Portland, Oregon
| | - Shawn L Hervey-Jumper
- 7Department of Neurological Surgery, University of California, San Francisco, California
| | - Albert J S Idema
- 13Department of Neurosurgery, Northwest Clinics, Alkmaar, The Netherlands
| | - Barbara Kiesel
- 14Department of Neurosurgery, Medical University Vienna, Austria
| | - Alfred Kloet
- 15Department of Neurosurgery, Medical Center Haaglanden, The Hague, The Netherlands
| | - Jan C De Munck
- 4Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Vrije Universiteit, University Medical Center, Amsterdam, The Netherlands
| | - Marco Rossi
- 6Neurosurgical Oncology Unit, Departments of Oncology and Remato-Oncology, Università degli Studi di Milano, Humanitas Research Hospital, IRCCS, Milan, Italy
| | - Tommaso Sciortino
- 6Neurosurgical Oncology Unit, Departments of Oncology and Remato-Oncology, Università degli Studi di Milano, Humanitas Research Hospital, IRCCS, Milan, Italy
| | - W Peter Vandertop
- 1Brain Tumor Center & Department of Neurosurgery, Cancer Center Amsterdam, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, The Netherlands
| | - Martin Visser
- 4Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Vrije Universiteit, University Medical Center, Amsterdam, The Netherlands
| | - Michiel Wagemakers
- 16Department of Neurosurgery, University of Groningen, University Medical Center Groningen, The Netherlands; and
| | - Georg Widhalm
- 14Department of Neurosurgery, Medical University Vienna, Austria
| | - Marnix G Witte
- 10Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Aeilko H Zwinderman
- 17Department of Clinical Epidemiology and Biostatistics, Academic Medical Center, Amsterdam, The Netherlands
| | - Philip C De Witt Hamer
- 1Brain Tumor Center & Department of Neurosurgery, Cancer Center Amsterdam, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, The Netherlands
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