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Gerritsen JKW, Young JS, Chang SM, Krieg SM, Jungk C, van den Bent MJ, Satoer DD, Ille S, Schucht P, Nahed BV, Broekman MLD, Berger M, De Vleeschouwer S, Vincent AJPE. SUPRAMAX-study: supramaximal resection versus maximal resection for glioblastoma patients: study protocol for an international multicentre prospective cohort study (ENCRAM 2201). BMJ Open 2024; 14:e082274. [PMID: 38684246 PMCID: PMC11086386 DOI: 10.1136/bmjopen-2023-082274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Accepted: 02/27/2024] [Indexed: 05/02/2024] Open
Abstract
INTRODUCTION A greater extent of resection of the contrast-enhancing (CE) tumour part has been associated with improved outcomes in glioblastoma. Recent results suggest that resection of the non-contrast-enhancing (NCE) part might yield even better survival outcomes (supramaximal resection, SMR). Therefore, this study evaluates the efficacy and safety of SMR with and without mapping techniques in high-grade glioma (HGG) patients in terms of survival, functional, neurological, cognitive and quality of life outcomes. Furthermore, it evaluates which patients benefit the most from SMR, and how they could be identified preoperatively. METHODS AND ANALYSIS This study is an international, multicentre, prospective, two-arm cohort study of observational nature. Consecutive glioblastoma patients will be operated with SMR or maximal resection at a 1:1 ratio. Primary endpoints are (1) overall survival and (2) proportion of patients with National Institute of Health Stroke Scale deterioration at 6 weeks, 3 months and 6 months postoperatively. Secondary endpoints are (1) residual CE and NCE tumour volume on postoperative T1-contrast and FLAIR (Fluid-attenuated inversion recovery) MRI scans; (2) progression-free survival; (3) receipt of adjuvant therapy with chemotherapy and radiotherapy; and (4) quality of life at 6 weeks, 3 months and 6 months postoperatively. The total duration of the study is 5 years. Patient inclusion is 4 years, follow-up is 1 year. ETHICS AND DISSEMINATION The study has been approved by the Medical Ethics Committee (METC Zuid-West Holland/Erasmus Medical Center; MEC-2020-0812). The results will be published in peer-reviewed academic journals and disseminated to patient organisations and media.
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Affiliation(s)
- Jasper Kees Wim Gerritsen
- Neurosurgery, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Neurosurgery, University of California San Francisco, San Francisco, California, USA
| | - Jacob S Young
- Department of Neurosurgery, University of California San Francisco, San Francisco, California, USA
| | - Susan M Chang
- Department of Neurosurgery, University of California San Francisco, San Francisco, California, USA
| | - Sandro M Krieg
- Department of Neurosurgery, University Hospital Heidelberg, Heidelberg, Baden-Württemberg, Germany
| | - Christine Jungk
- Neuro-oncology, UniversitatsKlinikum Heidelberg, Heidelberg, Germany
| | - Martin J van den Bent
- Department of Neuro Oncology, Erasmus Medical Center, Rotterdam, Zuid-Holland, The Netherlands
| | - Djaina D Satoer
- Neurosurgery, Erasmus Medical Center, Rotterdam, Zuid-Holland, The Netherlands
| | - Sebastian Ille
- Department of Neurosurgery, Technical University of Munich, Munich, Bayern, Germany
| | - Philippe Schucht
- Neurosurgery, Inselspital Universitätsspital Bern, Bern, Switzerland
| | - Brian V Nahed
- Department of Neurosurgery, Massachusetts General Hospital, Boston, Massachusetts, USA
| | | | - Mitchel Berger
- University of California San Francisco, San Francisco, California, USA
| | | | - Arnaud J P E Vincent
- Department of Neurosurgery, Erasmus Medical Center, Rotterdam, Zuid-Holland, The Netherlands
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Nakayama N, Yamada T, Yano H, Takei H, Ohe N, Miwa K, Shinoda J, Iwama T. Prediction of nuclide accumulation spread based on the volume of enhancing magnetic resonance imaging lesion in glioblastoma patients. J Neurosurg Sci 2024; 68:164-173. [PMID: 34647709 DOI: 10.23736/s0390-5616.21.05353-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
BACKGROUND 11C-methionine-PET (MET) and Thallium-201 chloride-SPECT (TL) are useful for predictive proliferation ability and tumor invasion range identification in glioma patients, however they are not always possible in any hospital or country. Our study aimed to assess whether the range of MET and Tl accumulation could be predicted from the contrast-enhanced lesions in Gadolinium (Gd)-T1 weighted magnetic resonance image in glioblastoma multiforme (GBM) patients. METHODS In 25 cases, the MET-area, TL-area, O-area where MET and TL overlap, and all accumulation area (AA-area) were measured in the same axial cross section as the Gd enhanced maximum area (Gd-area). This tracing operation was repeated with all axial fusion slices, and each volume was also measured (Gd-V, MET-V, TL-V, O-V, AA-V). RESULTS The maximum accumulation distance of MET and TL beyond the Gd-area was limited to within 30 mm, 35 mm, respectively. Significant positive correlations were showed in all combinations with Gd-area: MET-area (r=0.851, P<0.0001), TL-area (r=0.955, P<0.0001), O-area (r=0.935, P<0.0001) and AA-area (r=0.893, P<0.0001), respectively. All combinations with Gd-V showed significant positive correlation: MET-V (r=0.867, P<0.0001), TL-V (r=0.952, P<0.0001), O-V (r=0.935, P<0.0001) and AA-V (r=0.897, P<0.0001), respectively. CONCLUSIONS Approximate tumor volume Gd-V can be calculated using the formula A * B * C / 2, where A, B, and C represent the dimensions of Gd-enhanced lesion in 3 axes perpendicular to each other. The nuclide accumulation predictive table created using the obtained linear approximation functions can be used to predict the average tumor invasion range from the Gd-V without preoperative nuclear examinations.
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Affiliation(s)
- Noriyuki Nakayama
- Department of Neurosurgery, Gifu University Graduate School of Medicine, Gifu, Japan -
| | - Tetsuya Yamada
- Department of Neurosurgery, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Hirohito Yano
- Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Kizawa Memorial Hospital, Minokamo City, Gifu, Japan
| | - Hiroaki Takei
- Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Kizawa Memorial Hospital, Minokamo City, Gifu, Japan
| | - Naoyuki Ohe
- Department of Neurosurgery, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Kazuhiro Miwa
- Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Kizawa Memorial Hospital, Minokamo City, Gifu, Japan
| | - Jun Shinoda
- Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Kizawa Memorial Hospital, Minokamo City, Gifu, Japan
| | - Toru Iwama
- Department of Neurosurgery, Gifu University Graduate School of Medicine, Gifu, Japan
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Zhang W, Yan Z, Peng J, Zhao S, Ran L, Yin H, Zhong D, Yang J, Ye J, Xu S. Magnetic resonance imaging and deoxyribonucleic acid methylation-based radiogenomic models for survival risk stratification of glioblastoma. Med Biol Eng Comput 2024; 62:853-864. [PMID: 38057447 DOI: 10.1007/s11517-023-02971-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 11/14/2023] [Indexed: 12/08/2023]
Abstract
Glioblastoma multiforme (GBM) is one of the deadliest tumours. This study aimed to construct radiogenomic prognostic models of glioblastoma overall survival (OS) based on magnetic resonance imaging (MRI) Gd-T1WI images and deoxyribonucleic acid (DNA) methylation-seq and to understand the related biological pathways. The ResNet3D-18 model was used to extract radiomic features, and Lasso-Cox regression analysis was utilized to establish the prognostic models. A nomogram was constructed by combining the radiogenomic features and clinicopathological variables. The DeLong test was performed to compare the area under the curve (AUC) of the models. We screened differentially expressed genes (DEGs) with original ribonucleic acid (RNA)-seq in risk stratification and used Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) annotations for functional enrichment analysis. For the 1-year OS models, the AUCs of the radiogenomic set, methylation set and deep learning set in the training cohort were 0.864, 0.804 and 0.787, and those in the validation cohort were 0.835, 0.768 and 0.651, respectively. The AUCs of the 0.5-, 1- and 2-year nomograms in the training cohort were 0.943, 0.861 and 0.871, and those in the validation cohort were 0.864, 0.885 and 0.805, respectively. A total of 245 DEGs were screened; functional enrichment analysis showed that these DEGs were associated with cell immunity. The survival risk-stratifying radiogenomic models for glioblastoma OS had high predictability and were associated with biological pathways related to cell immunity.
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Affiliation(s)
- Wentao Zhang
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Zikang Yan
- Department of Bioinformatics, the Basic Medical School of Chongqing Medical University, Chongqing, 400016, China
| | - Jian Peng
- The Center for Clinical Molecular Medical Detection, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Shan Zhao
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Longke Ran
- Department of Bioinformatics, the Basic Medical School of Chongqing Medical University, Chongqing, 400016, China
| | - Haoyang Yin
- Department of Neurosurgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Dong Zhong
- Department of Neurosurgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Junjun Yang
- Key Laboratory of Optoelectronic Technologyand, Systems of the Ministry of Education, Chongqing University, Chongqing, 400044, China
| | - Junyong Ye
- Key Laboratory of Optoelectronic Technologyand, Systems of the Ministry of Education, Chongqing University, Chongqing, 400044, China.
| | - Shengsheng Xu
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
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Radtke K, Schulz-Schaeffer WJ, Oertel J. Confocal laser endomicroscopy in glial tumors-a histomorphological analysis. Neurosurg Rev 2024; 47:65. [PMID: 38265724 PMCID: PMC10808457 DOI: 10.1007/s10143-024-02286-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 01/02/2024] [Accepted: 01/06/2024] [Indexed: 01/25/2024]
Abstract
OBJECTIVE The extent of resection and neurological outcome are important prognostic markers for overall survival in glioma patients. Confocal laser endomicroscopy is a tool to examine tissue without the need for fixation or staining. This study aims to analyze gliomas in confocal laser endomicroscopy and identify reliable diagnostic criteria for glial matter and glial tumors. MATERIAL AND METHODS One-hundred-and-five glioma specimens were analyzed using a 670-nm confocal laser endomicroscope and then processed into hematoxylin-eosin-stained frozen sections. All confocal images and frozen sections were evaluated for the following criteria: presence of tumor, cellularity, nuclear pleomorphism, changes of the extracellular glial matrix, microvascular proliferation, necrosis, and mitotic activity. Recurring characteristics were identified. Accuracy, sensitivity, specificity, and positive and negative predictive values were assessed for each feature. RESULTS All 125 specimens could be processed and successfully analyzed via confocal laser endomicroscopy. We found diagnostic criteria to identify white and grey matter and analyze cellularity, nuclear pleomorphism, changes in the glial matrix, vascularization, and necrosis in glial tumors. An accuracy of > 90.0 % was reached for grey matter, cellularity, and necrosis, > 80.0 % for white matter and nuclear pleomorphism, and > 70.0 % for microvascular proliferation and changes of the glial matrix. Mitotic activity could not be identified. Astroglial tumors showed significantly less nuclear pleomorphism in confocal laser endomicroscopy than oligodendroglial tumors (p < 0.001). Visualization of necrosis aids in the differentiation of low grade gliomas and high grade gliomas (p < 0.002). CONCLUSION Autofluorescence-based confocal laser endomicroscopy proved not only useful in differentiation between tumor and brain tissue but also revealed useful clues to further characterize tissue without processing in a lab. Possible applications include the improvement of extent of resection and the safe harvest of representative tissue for histopathological and molecular genetic diagnostics.
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Affiliation(s)
- Karen Radtke
- Klinik für Neurochirurgie, Medizinische Fakultät, Universität des Saarlandes, /Saar, 66421, Homburg, Germany
| | - Walter J Schulz-Schaeffer
- Institut für Neuropathologie, Medizinische Fakultät, Universität des Saarlandes, /Saar, 66421, Homburg, Germany
| | - Joachim Oertel
- Klinik für Neurochirurgie, Medizinische Fakultät, Universität des Saarlandes, /Saar, 66421, Homburg, Germany.
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Al-Gizawiy MM, Wujek RT, Alhajala HS, Cobb JM, Prah MA, Doan NB, Connelly JM, Chitambar CR, Schmainda KM. Potent in vivo efficacy of oral gallium maltolate in treatment-resistant glioblastoma. Front Oncol 2024; 13:1278157. [PMID: 38288102 PMCID: PMC10822938 DOI: 10.3389/fonc.2023.1278157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 12/26/2023] [Indexed: 01/31/2024] Open
Abstract
Background Treatment-resistant glioblastoma (trGBM) is an aggressive brain tumor with a dismal prognosis, underscoring the need for better treatment options. Emerging data indicate that trGBM iron metabolism is an attractive therapeutic target. The novel iron mimetic, gallium maltolate (GaM), inhibits mitochondrial function via iron-dependent and -independent pathways. Methods In vitro irradiated adult GBM U-87 MG cells were tested for cell viability and allowed to reach confluence prior to stereotactic implantation into the right striatum of male and female athymic rats. Advanced MRI at 9.4T was carried out weekly starting two weeks after implantation. Daily oral GaM (50mg/kg) or vehicle were provided on tumor confirmation. Longitudinal MRI parameters were processed for enhancing tumor ROIs in OsiriX 8.5.1 (lite) with Imaging Biometrics Software (Imaging Biometrics LLC). Statistical analyses included Cox proportional hazards regression models, Kaplan-Meier survival plots, linear mixed model comparisons, and t-statistic for slopes comparison as indicator of tumor growth rate. Results In this study we demonstrate non-invasively, using longitudinal MRI surveillance, the potent antineoplastic effects of GaM in a novel rat xenograft model of trGBM, as evidenced by extended suppression of tumor growth (23.56 mm3/week untreated, 5.76 mm3/week treated, P < 0.001), a blunting of tumor perfusion, and a significant survival benefit (median overall survival: 30 days untreated, 56 days treated; P < 0.001). The therapeutic effect was confirmed histologically by the presence of abundant cytotoxic cellular swelling, a significant reduction in proliferation markers (P < 0.01), and vessel normalization characterized by prominent vessel pruning, loss of branching, and uniformity of vessel lumina. Xenograft tumors in the treatment group were further characterized by an absence of an invasive edge and a significant reduction in both, MIB-1% and mitotic index (P < 0.01 each). Transferrin receptor and ferroportin expression in GaM-treated tumors illustrated cellular iron deprivation. Additionally, treatment with GaM decreased the expression of pro-angiogenic markers (von Willebrand Factor and VEGF) and increased the expression of anti-angiogenic markers, such as Angiopoietin-2. Conclusion Monotherapy with the iron-mimetic GaM profoundly inhibits trGBM growth and significantly extends disease-specific survival in vivo.
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Affiliation(s)
- Mona M. Al-Gizawiy
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Robert T. Wujek
- Department of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Hisham S. Alhajala
- Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Jonathan M. Cobb
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Melissa A. Prah
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Ninh B. Doan
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Jennifer M. Connelly
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Christopher R. Chitambar
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
- Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Kathleen M. Schmainda
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
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6
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Karschnia P, Dietrich J, Bruno F, Dono A, Juenger ST, Teske N, Young JS, Sciortino T, Häni L, van den Bent M, Weller M, Vogelbaum MA, Morshed RA, Haddad AF, Molinaro AM, Tandon N, Beck J, Schnell O, Bello L, Hervey-Jumper S, Thon N, Grau SJ, Esquenazi Y, Rudà R, Chang SM, Berger MS, Cahill DP, Tonn JC. Surgical management and outcome of newly diagnosed glioblastoma without contrast enhancement (low-grade appearance): a report of the RANO resect group. Neuro Oncol 2024; 26:166-177. [PMID: 37665776 PMCID: PMC10768992 DOI: 10.1093/neuonc/noad160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Indexed: 09/06/2023] Open
Abstract
BACKGROUND Resection of the contrast-enhancing (CE) tumor represents the standard of care in newly diagnosed glioblastoma. However, some tumors ultimately diagnosed as glioblastoma lack contrast enhancement and have a 'low-grade appearance' on imaging (non-CE glioblastoma). We aimed to (a) volumetrically define the value of non-CE tumor resection in the absence of contrast enhancement, and to (b) delineate outcome differences between glioblastoma patients with and without contrast enhancement. METHODS The RANO resect group retrospectively compiled a global, eight-center cohort of patients with newly diagnosed glioblastoma per WHO 2021 classification. The associations between postoperative tumor volumes and outcome were analyzed. Propensity score-matched analyses were constructed to compare glioblastomas with and without contrast enhancement. RESULTS Among 1323 newly diagnosed IDH-wildtype glioblastomas, we identified 98 patients (7.4%) without contrast enhancement. In such patients, smaller postoperative tumor volumes were associated with more favorable outcome. There was an exponential increase in risk for death with larger residual non-CE tumor. Accordingly, extensive resection was associated with improved survival compared to lesion biopsy. These findings were retained on a multivariable analysis adjusting for demographic and clinical markers. Compared to CE glioblastoma, patients with non-CE glioblastoma had a more favorable clinical profile and superior outcome as confirmed in propensity score analyses by matching the patients with non-CE glioblastoma to patients with CE glioblastoma using a large set of clinical variables. CONCLUSIONS The absence of contrast enhancement characterizes a less aggressive clinical phenotype of IDH-wildtype glioblastomas. Maximal resection of non-CE tumors has prognostic implications and translates into favorable outcome.
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Affiliation(s)
- Philipp Karschnia
- Department of Neurosurgery, LMU University Hospital of the Ludwig-Maximilians-University Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Germany
| | - Jorg Dietrich
- Department of Neurology, Division of Neuro-Oncology, Massachusetts General Hospital Cancer Center, Harvard Medical School, Boston, MA, USA
| | - Francesco Bruno
- Division of Neuro-Oncology, Department of Neuroscience, University of Turin, Italy
| | - Antonio Dono
- Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, TX, USA
| | | | - Nico Teske
- Department of Neurosurgery, LMU University Hospital of the Ludwig-Maximilians-University Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Germany
| | - Jacob S Young
- Department of Neurosurgery and Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Tommaso Sciortino
- Division of Neuro-Oncology, Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Levin Häni
- Department of Neurosurgery, Medical Center – University of Freiburg, Freiburg, Germany
| | - Martin van den Bent
- Department of Neurology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Michael Weller
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | | | - Ramin A Morshed
- Department of Neurosurgery and Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Alexander F Haddad
- Department of Neurosurgery and Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Annette M Molinaro
- Department of Neurosurgery and Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Nitin Tandon
- Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, TX, USA
| | - Juergen Beck
- Department of Neurosurgery, Medical Center – University of Freiburg, Freiburg, Germany
| | - Oliver Schnell
- Department of Neurosurgery, Medical Center – University of Freiburg, Freiburg, Germany
| | - Lorenzo Bello
- Division of Neuro-Oncology, Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Shawn Hervey-Jumper
- Department of Neurosurgery and Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Niklas Thon
- Department of Neurosurgery, LMU University Hospital of the Ludwig-Maximilians-University Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Germany
| | - Stefan J Grau
- Department of Neurosurgery, University of Cologne, Cologne, Germany
| | - Yoshua Esquenazi
- Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, TX, USA
| | - Roberta Rudà
- Division of Neuro-Oncology, Department of Neuroscience, University of Turin, Italy
| | - Susan M Chang
- Department of Neurosurgery and Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Mitchel S Berger
- Department of Neurosurgery and Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Daniel P Cahill
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Joerg-Christian Tonn
- Department of Neurosurgery, LMU University Hospital of the Ludwig-Maximilians-University Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Germany
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Patel KS, Yao J, Cho NS, Sanvito F, Tessema K, Alvarado A, Dudley L, Rodriguez F, Everson R, Cloughesy TF, Salamon N, Liau LM, Kornblum HI, Ellingson BM. pH-Weighted amine chemical exchange saturation transfer echo planar imaging visualizes infiltrating glioblastoma cells. Neuro Oncol 2024; 26:115-126. [PMID: 37591790 PMCID: PMC10768991 DOI: 10.1093/neuonc/noad150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Indexed: 08/19/2023] Open
Abstract
BACKGROUND Given the invasive nature of glioblastoma, tumor cells exist beyond the contrast-enhancing (CE) region targeted during treatment. However, areas of non-enhancing (NE) tumors are difficult to visualize and delineate from edematous tissue. Amine chemical exchange saturation transfer echo planar imaging (CEST-EPI) is a pH-sensitive molecular magnetic resonance imaging technique that was evaluated in its ability to identify infiltrating NE tumors and prognosticate survival. METHODS In this prospective study, CEST-EPI was obtained in 30 patients and areas with elevated CEST contrast ("CEST+" based on the asymmetry in magnetization transfer ratio: MTRasym at 3 ppm) within NE regions were quantitated. Median MTRasym at 3 ppm and volume of CEST + NE regions were correlated with progression-free survival (PFS). In 20 samples from 14 patients, image-guided biopsies of these areas were obtained to correlate MTRasym at 3 ppm to tumor and non-tumor cell burden using immunohistochemistry. RESULTS In 15 newly diagnosed and 15 recurrent glioblastoma, higher median MTRasym at 3ppm within CEST + NE regions (P = .007; P = .0326) and higher volumes of CEST + NE tumor (P = .020; P < .001) were associated with decreased PFS. CE recurrence occurred in areas of preoperative CEST + NE regions in 95.4% of patients. MTRasym at 3 ppm was correlated with presence of tumor, cell density, %Ki-67 positivity, and %CD31 positivity (P = .001; P < .001; P < .001; P = .001). CONCLUSIONS pH-weighted amine CEST-EPI allows for visualization of NE tumor, likely through surrounding acidification of the tumor microenvironment. The magnitude and volume of CEST + NE tumor correlates with tumor cell density, degree of proliferating or "active" tumor, and PFS.
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Affiliation(s)
- Kunal S Patel
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California, USA
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, California, USA
| | - Nicholas S Cho
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, California, USA
| | - Francesco Sanvito
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, California, USA
| | - Kaleab Tessema
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Medical Scientist Training Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Alvaro Alvarado
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Lindsey Dudley
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Fausto Rodriguez
- Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Richard Everson
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Timothy F Cloughesy
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, California, USA
| | - Linda M Liau
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Harley I Kornblum
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Benjamin M Ellingson
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, California, USA
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, California, USA
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8
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Patel KS, Tessema KK, Kawaguchi R, Dudley L, Alvarado AG, Muthukrishnan SD, Perryman T, Hagiwara A, Swarup V, Liau LM, Wang AC, Yong W, Geschwind DH, Nakano I, Goldman SA, Everson RG, Ellingson BM, Kornblum HI. Single-nucleus expression characterization of non-enhancing region of recurrent high-grade glioma. Neurooncol Adv 2024; 6:vdae005. [PMID: 38616896 PMCID: PMC11012612 DOI: 10.1093/noajnl/vdae005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/16/2024] Open
Abstract
Background Non-enhancing (NE) infiltrating tumor cells beyond the contrast-enhancing (CE) bulk of tumor are potential propagators of recurrence after gross total resection of high-grade glioma. Methods We leveraged single-nucleus RNA sequencing on 15 specimens from recurrent high-grade gliomas (n = 5) to compare prospectively identified biopsy specimens acquired from CE and NE regions. Additionally, 24 CE and 22 NE biopsies had immunohistochemical staining to validate RNA findings. Results Tumor cells in NE regions are enriched in neural progenitor cell-like cellular states, while CE regions are enriched in mesenchymal-like states. NE glioma cells have similar proportions of proliferative and putative glioma stem cells relative to CE regions, without significant differences in % Ki-67 staining. Tumor cells in NE regions exhibit upregulation of genes previously associated with lower grade gliomas. Our findings in recurrent GBM paralleled some of the findings in a re-analysis of a dataset from primary GBM. Cell-, gene-, and pathway-level analyses of the tumor microenvironment in the NE region reveal relative downregulation of tumor-mediated neovascularization and cell-mediated immune response, but increased glioma-to-nonpathological cell interactions. Conclusions This comprehensive analysis illustrates differing tumor and nontumor landscapes of CE and NE regions in high-grade gliomas, highlighting the NE region as an area harboring likely initiators of recurrence in a pro-tumor microenvironment and identifying possible targets for future design of NE-specific adjuvant therapy. These findings also support the aggressive approach to resection of tumor-bearing NE regions.
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Affiliation(s)
- Kunal S Patel
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Kaleab K Tessema
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Riki Kawaguchi
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Lindsey Dudley
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Alvaro G Alvarado
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Sree Deepthi Muthukrishnan
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Travis Perryman
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Akifumi Hagiwara
- UCLA Brain Tumor Imaging Laboratory (BTIL), Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Vivek Swarup
- Department of Neurobiology and Behavior, UCI School of Biological Sciences, Irvine, California, USA
| | - Linda M Liau
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Anthony C Wang
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - William Yong
- Department of Pathology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Daniel H Geschwind
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Ichiro Nakano
- Department of Neurosurgery, Hokuto Social Medical Corporation, Hokuto Hospital, Hokuto, Japan
| | - Steven A Goldman
- Center for Translational Neuromedicine, University of Rochester Medical Center, Rochester, New York, USA
- Faculty of Health and Medical Sciences, Center for Translational Neuromedicine, University of Copenhagen, Copenhagen, Denmark
| | - Richard G Everson
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
- Department of Radiation Oncology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Benjamin M Ellingson
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Harley I Kornblum
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
- Departments of Pediatrics, Psychiatry, and Molecular and Medical Pharmacology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
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Sanvito F, Kaufmann TJ, Cloughesy TF, Wen PY, Ellingson BM. Standardized brain tumor imaging protocols for clinical trials: current recommendations and tips for integration. FRONTIERS IN RADIOLOGY 2023; 3:1267615. [PMID: 38152383 PMCID: PMC10751345 DOI: 10.3389/fradi.2023.1267615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 11/24/2023] [Indexed: 12/29/2023]
Abstract
Standardized MRI acquisition protocols are crucial for reducing the measurement and interpretation variability associated with response assessment in brain tumor clinical trials. The main challenge is that standardized protocols should ensure high image quality while maximizing the number of institutions meeting the acquisition requirements. In recent years, extensive effort has been made by consensus groups to propose different "ideal" and "minimum requirements" brain tumor imaging protocols (BTIPs) for gliomas, brain metastases (BM), and primary central nervous system lymphomas (PCSNL). In clinical practice, BTIPs for clinical trials can be easily integrated with additional MRI sequences that may be desired for clinical patient management at individual sites. In this review, we summarize the general concepts behind the choice and timing of sequences included in the current recommended BTIPs, we provide a comparative overview, and discuss tips and caveats to integrate additional clinical or research sequences while preserving the recommended BTIPs. Finally, we also reflect on potential future directions for brain tumor imaging in clinical trials.
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Affiliation(s)
- Francesco Sanvito
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | | | - Timothy F. Cloughesy
- UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Patrick Y. Wen
- Center for Neuro-Oncology, Dana-Farber/Brigham and Women’s Cancer Center, Harvard Medical School, Boston, MA, United States
| | - Benjamin M. Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
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Ohmura K, Daimon T, Ikegame Y, Yano H, Yokoyama K, Kumagai M, Shinoda J, Iwama T. Resection of positive tissue on methionine-PET is associated with improved survival in glioblastomas. Brain Behav 2023; 13:e3291. [PMID: 37846176 PMCID: PMC10726771 DOI: 10.1002/brb3.3291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 10/06/2023] [Accepted: 10/10/2023] [Indexed: 10/18/2023] Open
Abstract
BACKGROUND AND PURPOSE The volume of excised tumor in contrast-enhanced areas evaluated via magnetic resonance imaging is known to have a strong influence on the survival of patients with glioblastoma (GBM). In this study, we investigated the effect of tumor resection on the survival of patients with GBM in the 11 C-methionine (MET) accumulation area using MET-positron emission tomography (MET-PET). METHODS A total of 26 patients (median age, 69 years; 15 males) who had undergone tumor resection and MET-PET before and after surgery, after being newly diagnosed with GBM, were included in the study. MET-PET before and after tumor resection were compared. The association between the decrease in the maximum standardized uptake value (SUV) of the tumor divided by the normal cortical mean SUV (%; ΔT/N), the MET extent of resection (MET-EOR) from the % reduction in the MET accumulation area (%), and residual MET accumulation area (in cm3 ; MET-residual tumor volume [RTV]), as well as the survival time of patients with GBM, were evaluated via univariate analysis. RESULTS ΔT/N were positively associated with survival (hazard ratio [HR], 0.98 [95% confidence interval (CI), 0.97-0.99], p = .02). MET-RTV revealed a negative association with survival (HR, 1.02 [95% CI, 1.01-1.04], p = .04). Additionally, MET-EOR showed a strong trend with survival (HR, 0.99 [95% CI, 0.97-1.01], p = .06). CONCLUSIONS Surgical resection of MET-accumulated areas in GBM significantly prolongs the survival of patients with GBM. However, a prospective large-scale multicenter study is needed to confirm our findings.
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Affiliation(s)
- Kazufumi Ohmura
- Chubu Medical Center for Prolonged Traumatic Brain DysfunctionMinokamoGifuJapan
- Department of NeurosurgeryGifu University Graduate School of MedicineGifuJapan
| | - Takashi Daimon
- Department of BiostatisticsHyogo College of MedicineNishinomiyaHyogoJapan
| | - Yuka Ikegame
- Chubu Medical Center for Prolonged Traumatic Brain DysfunctionMinokamoGifuJapan
- Chubu Neurorehabilitation HospitalMinokamoGifuJapan
- Department of Clinical Brain SciencesGifu University Graduate School of MedicineMinokamoGifuJapan
| | - Hirohito Yano
- Chubu Medical Center for Prolonged Traumatic Brain DysfunctionMinokamoGifuJapan
- Chubu Neurorehabilitation HospitalMinokamoGifuJapan
- Department of Clinical Brain SciencesGifu University Graduate School of MedicineMinokamoGifuJapan
| | - Kazutoshi Yokoyama
- Department of NeurosurgeryChubu International Medical CenterMinokamoGifuJapan
| | | | - Jun Shinoda
- Chubu Medical Center for Prolonged Traumatic Brain DysfunctionMinokamoGifuJapan
- Chubu Neurorehabilitation HospitalMinokamoGifuJapan
- Department of Clinical Brain SciencesGifu University Graduate School of MedicineMinokamoGifuJapan
| | - Toru Iwama
- Department of NeurosurgeryGifu University Graduate School of MedicineGifuJapan
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Teske N, Tonn JC, Karschnia P. How to evaluate extent of resection in diffuse gliomas: from standards to new methods. Curr Opin Neurol 2023; 36:564-570. [PMID: 37865849 DOI: 10.1097/wco.0000000000001212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2023]
Abstract
PURPOSE OF REVIEW Maximal safe tumor resection represents the current standard of care for patients with newly diagnosed diffuse gliomas. Recent efforts have highlighted the prognostic value of extent of resection measured as residual tumor volume in patients with isocitrate dehydrogenase (IDH)-wildtype and -mutant gliomas. Accurate assessment of such information therefore appears essential in the context of clinical trials as well as patient management. RECENT FINDINGS Current recommendations for evaluation of extent of resection rest upon standardized postoperative MRI including contrast-enhanced T1-weighted sequences, T2-weighted/fluid-attenuated-inversion-recovery sequences, and diffusion-weighted imaging to differentiate postoperative tumor volumes from ischemia and nonspecific imaging findings. In this context, correct timing of postoperative imaging within the postoperative period is of utmost importance. Advanced MRI techniques including perfusion-weighted MRI and MR-spectroscopy may add further insight when evaluating residual tumor remnants. Positron emission tomography (PET) using amino acid tracers proves beneficial in identifying metabolically active tumor beyond anatomical findings on conventional MRI. SUMMARY Future efforts will have to refine recommendations on postoperative assessment of residual tumor burden in respect to differences between IDH-wildtype and -mutant gliomas, and incorporate the emerging role of advanced imaging modalities like amino acid PET.
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Affiliation(s)
- Nico Teske
- Department of Neurosurgery, LMU University Hospital, LMU Munich
- German Cancer Consortium (DKTK), Partner Site, Munich, Germany
| | - Joerg-Christian Tonn
- Department of Neurosurgery, LMU University Hospital, LMU Munich
- German Cancer Consortium (DKTK), Partner Site, Munich, Germany
| | - Philipp Karschnia
- Department of Neurosurgery, LMU University Hospital, LMU Munich
- German Cancer Consortium (DKTK), Partner Site, Munich, Germany
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Alafandi A, van Garderen KA, Klein S, van der Voort SR, Rizopoulos D, Nabors L, Stupp R, Weller M, Gorlia T, Tonn JC, Smits M. Association of pre-radiotherapy tumour burden and overall survival in newly diagnosed glioblastoma adjusted for MGMT promoter methylation status. Eur J Cancer 2023; 188:122-130. [PMID: 37235895 DOI: 10.1016/j.ejca.2023.04.021] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/07/2023] [Accepted: 04/26/2023] [Indexed: 05/28/2023]
Abstract
PURPOSE We retrospectively evaluated the association between postoperative pre-radiotherapy tumour burden and overall survival (OS) adjusted for the prognostic value of O6-methylguanine DNA methyltransferase (MGMT) promoter methylation in patients with newly diagnosed glioblastoma treated with radio-/chemotherapy with temozolomide. MATERIALS AND METHODS Patients were included from the CENTRIC (EORTC 26071-22072) and CORE trials if postoperative magnetic resonance imaging scans were available within a timeframe of up to 4weeks before radiotherapy, including both pre- and post-contrast T1w images and at least one T2w sequence (T2w or T2w-FLAIR). Postoperative (residual) pre-radiotherapy contrast-enhanced tumour (CET) volumes and non-enhanced T2w abnormalities (NT2A) tissue volumes were obtained by three-dimensional segmentation. Cox proportional hazard models and Kaplan Meier estimates were used to assess the association of pre-radiotherapy CET/NT2A volume with OS adjusted for known prognostic factors (age, performance status, MGMT status). RESULTS 408 tumour (of which 270 MGMT methylated) segmentations were included. Median OS in patients with MGMT methylated tumours was 117 weeks versus 61weeks in MGMT unmethylated tumours (p < 0.001). When stratified for MGMT methylation status, higher CET volume (HR 1.020; 95% confidence interval CI [1.013-1.027]; p < 0.001) and older age (HR 1.664; 95% CI [1.214-2.281]; p = 0.002) were significantly associated with shorter OS while NT2A volume and performance status were not. CONCLUSION Pre-radiotherapy CET volume was strongly associated with OS in patients receiving radio-/chemotherapy for newly diagnosed glioblastoma stratified by MGMT promoter methylation status.
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Affiliation(s)
- A Alafandi
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands; Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | - K A van Garderen
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands; Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, the Netherlands; Medical Delta, Delft, the Netherlands
| | - S Klein
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands
| | - S R van der Voort
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands
| | - D Rizopoulos
- Department of Biostatistics and Department of Epidemiology, Erasmus MC, Rotterdam, the Netherlands
| | - L Nabors
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - R Stupp
- Malnati Brain Tumor Institute, Departments of Neurological Surgery and Neurology, Northwestern University, Chicago, IL, USA
| | - M Weller
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - T Gorlia
- European Organisation for Research and Treatmeant of Cancer Headquarters, Brussels, Belgium
| | - J-C Tonn
- Department of Neurosurgery, LMU University Munich, Munich, Germany
| | - M Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands; Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, the Netherlands; Medical Delta, Delft, the Netherlands.
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Quan G, Wang T, Ren JL, Xue X, Wang W, Wu Y, Li X, Yuan T. Prognostic and predictive impact of abnormal signal volume evolution early after chemoradiotherapy in glioblastoma. J Neurooncol 2023; 162:385-396. [PMID: 36991305 DOI: 10.1007/s11060-023-04299-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 03/14/2023] [Indexed: 03/31/2023]
Abstract
INTRODUCTION This study was designed to explore the feasibility of semiautomatic measurement of abnormal signal volume (ASV) in glioblastoma (GBM) patients, and the predictive value of ASV evolution for the survival prognosis after chemoradiotherapy (CRT). METHODS This retrospective trial included 110 consecutive patients with GBM. MRI metrics, including the orthogonal diameter (OD) of the abnormal signal lesions, the pre-radiation enhancement volume (PRRCE), the volume change rate of enhancement (rCE), and fluid attenuated inversion recovery (rFLAIR) before and after CRT were analyzed. Semi-automatic measurements of ASV were done through the Slicer software. RESULTS In logistic regression analysis, age (HR = 2.185, p = 0.012), PRRCE (HR = 0.373, p < 0.001), post CE volume (HR = 4.261, p = 0.001), rCE1m (HR = 0.519, p = 0.046) were the significant independent predictors of short overall survival (OS) (< 15.43 months). The areas under the receiver operating characteristic curve (AUCs) for predicting short OS with rFLAIR3m and rCE1m were 0.646 and 0.771, respectively. The AUCs of Model 1 (clinical), Model 2 (clinical + conventional MRI), Model 3 (volume parameters), Model 4 (volume parameters + conventional MRI), and Model 5 (clinical + conventional MRI + volume parameters) for predicting short OS were 0.690, 0.723, 0.877, 0.879, 0.898, respectively. CONCLUSION Semi-automatic measurement of ASV in GBM patients is feasible. The early evolution of ASV after CRT was beneficial in improving the survival evaluation after CRT. The efficacy of rCE1m was better than that of rFLAIR3m in this evaluation.
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Affiliation(s)
- Guanmin Quan
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, People's Republic of China
| | - Tianda Wang
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, People's Republic of China
| | - Jia-Liang Ren
- GE Healthcare China, Beijing, People's Republic of China
| | - Xiaoying Xue
- Department of Radiotherapy, The Second Hospital of Hebei Medical University, Shijiazhuang, People's Republic of China
| | - Wenyan Wang
- Department of Radiotherapy, The Second Hospital of Hebei Medical University, Shijiazhuang, People's Republic of China
| | - Yankai Wu
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, People's Republic of China
| | - Xiaotong Li
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, People's Republic of China
| | - Tao Yuan
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, People's Republic of China.
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, 215 Hepingxi Road, Shijiazhuang, 050000, Hebei, People's Republic of China.
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Refining the Intraoperative Identification of Suspected High-Grade Glioma Using a Surgical Fluorescence Biomarker: GALA BIDD Study Report. J Pers Med 2023; 13:jpm13030514. [PMID: 36983696 PMCID: PMC10058333 DOI: 10.3390/jpm13030514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 03/09/2023] [Accepted: 03/09/2023] [Indexed: 03/14/2023] Open
Abstract
Background. Improving intraoperative accuracy with a validated surgical biomarker is important because identifying high-grade areas within a glioma will aid neurosurgical decision-making and sampling. Methods. We designed a multicentre, prospective surgical cohort study (GALA-BIDD) to validate the presence of visible fluorescence as a pragmatic intraoperative surgical biomarker of suspected high-grade disease within a tumour mass in patients undergoing 5-aminolevulinic acid (5-ALA) fluorescence-guided cytoreductive surgery. Results. A total of 106 patients with a suspected high-grade glioma or malignant transformation of a low-grade glioma were enrolled. Among the 99 patients who received 5-ALA, 89 patients were eligible to assess the correlation of fluorescence with diagnosis as per protocol. Of these 89, 81 patients had visible fluorescence at surgery, and 8 patients had no fluorescence. A total of 80 out of 81 fluorescent patients were diagnosed as high-grade gliomas on postoperative central review with 1 low-grade glioma case. Among the eight patients given 5-ALA who did not show any visible fluorescence, none were high-grade gliomas, and all were low-grade gliomas. Of the seven patients suspected radiologically of malignant transformation of low-grade gliomas and with visible fluorescence at surgery, six were diagnosed with high-grade gliomas, and one had no tissue collected. Conclusion. In patients where there is clinical suspicion, visible 5-ALA fluorescence has clinical utility as an intraoperative surgical biomarker of high-grade gliomas and can aid surgical decision-making and sampling. Further studies assessing the use of 5-ALA to assess malignant transformation in all diffuse gliomas may be valuable.
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Hong DH, Kim JH, Won JK, Kim H, Kim C, Park KJ, Hwang K, Jeong KH, Kang SH. Clinical feasibility of miniaturized Lissajous scanning confocal laser endomicroscopy for indocyanine green-enhanced brain tumor diagnosis. Front Oncol 2023; 12:994054. [PMID: 36713547 PMCID: PMC9880156 DOI: 10.3389/fonc.2022.994054] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 12/15/2022] [Indexed: 01/15/2023] Open
Abstract
Background Intraoperative real-time confocal laser endomicroscopy (CLE) is an alternative modality for frozen tissue histology that enables visualization of the cytoarchitecture of living tissues with spatial resolution at the cellular level. We developed a new CLE with a "Lissajous scanning pattern" and conducted a study to identify its feasibility for fluorescence-guided brain tumor diagnosis. Materials and methods Conventional hematoxylin and eosin (H&E) histological images were compared with indocyanine green (ICG)-enhanced CLE images in two settings (1): experimental study with in vitro tumor cells and ex vivo glial tumors of mice, and (2) clinical evaluation with surgically resected human brain tumors. First, CLE images were obtained from cultured U87 and GL261 glioma cells. Then, U87 and GL261 tumor cells were implanted into the mouse brain, and H&E staining was compared with CLE images of normal and tumor tissues ex vivo. To determine the invasion of the normal brain, two types of patient-derived glioma cells (CSC2 and X01) were used for orthotopic intracranial tumor formation and compared using two methods (CLE vs. H&E staining). Second, in human brain tumors, tissue specimens from 69 patients were prospectively obtained after elective surgical resection and were also compared using two methods, namely, CLE and H&E staining. The comparison was performed by an experienced neuropathologist. Results When ICG was incubated in vitro, U87 and GL261 cell morphologies were well-defined in the CLE images and depended on dimethyl sulfoxide. Ex vivo examination of xenograft glioma tissues revealed dense and heterogeneous glioma cell cores and peritumoral necrosis using both methods. CLE images also detected invasive tumor cell clusters in the normal brain of the patient-derived glioma xenograft model, which corresponded to H&E staining. In human tissue specimens, CLE images effectively visualized the cytoarchitecture of the normal brain and tumors. In addition, pathognomonic microstructures according to tumor subtype were also clearly observed. Interestingly, in gliomas, the cellularity of the tumor and the density of streak-like patterns were significantly associated with tumor grade in the CLE images. Finally, panoramic view reconstruction was successfully conducted for visualizing a gross tissue morphology. Conclusion In conclusion, the newly developed CLE with Lissajous laser scanning can be a helpful intraoperative device for the diagnosis, detection of tumor-free margins, and maximal safe resection of brain tumors.
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Affiliation(s)
- Duk Hyun Hong
- Department of Neurosurgery, Korea University Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Jang Hun Kim
- Department of Neurosurgery, Korea University Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Jae-Kyung Won
- Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Hyungsin Kim
- Department of Neurosurgery, Korea University Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Chayeon Kim
- VPIX Medical Inc., Daejeon, Republic of Korea
| | - Kyung-Jae Park
- Department of Neurosurgery, Korea University Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | | | - Ki-Hun Jeong
- Department of Bio and Brain Engineering, KAIST Institute for Health Science and Technology (KIHST), Korea Advanced Institute of Science and Technology (KAIST), Seoul, Republic of Korea
| | - Shin-Hyuk Kang
- Department of Neurosurgery, Korea University Hospital, Korea University College of Medicine, Seoul, Republic of Korea
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Gamboa NT, Crabb B, Henson JC, Cole KL, Weaver BD, Karsy M, Jensen RL. High-grade glioma imaging volumes and survival: a single-institution analysis of 101 patients after resection using intraoperative MRI. J Neurooncol 2022; 160:555-565. [DOI: 10.1007/s11060-022-04159-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 10/05/2022] [Indexed: 11/19/2022]
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Pálsson S, Cerri S, Poulsen HS, Urup T, Law I, Van Leemput K. Predicting survival of glioblastoma from automatic whole-brain and tumor segmentation of MR images. Sci Rep 2022; 12:19744. [PMID: 36396681 PMCID: PMC9671967 DOI: 10.1038/s41598-022-19223-3] [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: 09/24/2021] [Accepted: 08/25/2022] [Indexed: 11/18/2022] Open
Abstract
Survival prediction models can potentially be used to guide treatment of glioblastoma patients. However, currently available MR imaging biomarkers holding prognostic information are often challenging to interpret, have difficulties generalizing across data acquisitions, or are only applicable to pre-operative MR data. In this paper we aim to address these issues by introducing novel imaging features that can be automatically computed from MR images and fed into machine learning models to predict patient survival. The features we propose have a direct anatomical-functional interpretation: They measure the deformation caused by the tumor on the surrounding brain structures, comparing the shape of various structures in the patient's brain to their expected shape in healthy individuals. To obtain the required segmentations, we use an automatic method that is contrast-adaptive and robust to missing modalities, making the features generalizable across scanners and imaging protocols. Since the features we propose do not depend on characteristics of the tumor region itself, they are also applicable to post-operative images, which have been much less studied in the context of survival prediction. Using experiments involving both pre- and post-operative data, we show that the proposed features carry prognostic value in terms of overall- and progression-free survival, over and above that of conventional non-imaging features.
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Affiliation(s)
- Sveinn Pálsson
- grid.5170.30000 0001 2181 8870Department of Health Technology, Technical University of Denmark, Lyngby, Denmark
| | - Stefano Cerri
- grid.5170.30000 0001 2181 8870Department of Health Technology, Technical University of Denmark, Lyngby, Denmark
| | - Hans Skovgaard Poulsen
- grid.475435.4Department of Oncology, The Finsen Center, Rigshospitalet, Copenhagen, Denmark
| | - Thomas Urup
- grid.475435.4Department of Oncology, The Finsen Center, Rigshospitalet, Copenhagen, Denmark
| | - Ian Law
- grid.475435.4Department of Clinical Physiology, Nuclear Medicine and PET, Center of Diagnostic Investigation, Rigshospitalet, Copenhagen, Denmark
| | - Koen Van Leemput
- grid.5170.30000 0001 2181 8870Department of Health Technology, Technical University of Denmark, Lyngby, Denmark ,grid.32224.350000 0004 0386 9924Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, USA
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Karschnia P, Young JS, Dono A, Häni L, Sciortino T, Bruno F, Juenger ST, Teske N, Morshed RA, Haddad AF, Zhang Y, Stoecklein S, Weller M, Vogelbaum MA, Beck J, Tandon N, Hervey-Jumper S, Molinaro AM, Rudà R, Bello L, Schnell O, Esquenazi Y, Ruge MI, Grau SJ, Berger MS, Chang SM, van den Bent M, Tonn JC. Prognostic validation of a new classification system for extent of resection in glioblastoma: a report of the RANO resect group. Neuro Oncol 2022; 25:940-954. [PMID: 35961053 PMCID: PMC10158281 DOI: 10.1093/neuonc/noac193] [Citation(s) in RCA: 75] [Impact Index Per Article: 37.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND Terminology to describe extent of resection in glioblastoma is inconsistent across clinical trials. A surgical classification system was previously proposed based upon residual contrast-enhancing (CE) tumor. We aimed to (I) explore the prognostic utility of the classification system and (II) define how much removed non-CE tumor translates into a survival benefit. METHODS The international RANO resect group retrospectively searched previously compiled databases from seven neuro-oncological centers in the USA and Europe for patients with newly diagnosed glioblastoma per WHO 2021 classification. Clinical and volumetric information from pre- and post-operative MRI were collected. RESULTS We collected 1008 patients with newly diagnosed IDHwt glioblastoma. 744 IDHwt glioblastomas were treated with radiochemotherapy per EORTC 26981/22981 (TMZ/RT→TMZ) following surgery. Among these homogenously treated patients, lower absolute residual tumor volumes (in cm 3) were favorably associated with outcome: patients with 'maximal CE resection' (class 2) had superior outcome compared to patients with 'submaximal CE resection' (class 3) or 'biopsy' (class 4). Extensive resection of non-CE tumor (≤5 cm 3 residual non-CE tumor) was associated with better survival among patients with complete CE resection, thus defining class 1 ('supramaximal CE resection'). The prognostic value of the resection classes was retained on multivariate analysis when adjusting for molecular and clinical markers. CONCLUSIONS The proposed "RANO categories for extent of resection in glioblastoma" are highly prognostic and may serve for stratification within clinical trials. Removal of non-CE tumor beyond the CE tumor borders may translate into additional survival benefit, providing a rationale to explicitly denominate such 'supramaximal CE resection'.
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Affiliation(s)
- Philipp Karschnia
- Department of Neurosurgery, Ludwig-Maximilians-University, Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Germany
| | - Jacob S Young
- Department of Neurosurgery & Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Antonio Dono
- Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, Texas, United States of America
| | - Levin Häni
- Department of Neurosurgery, University of Freiburg, Freiburg, Germany
| | - Tommaso Sciortino
- Division for Neuro-Oncology, Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Francesco Bruno
- Division of Neuro-Oncology, Department of Neuroscience, University of Turin, Italy
| | | | - Nico Teske
- Department of Neurosurgery, Ludwig-Maximilians-University, Munich, Germany
| | - Ramin A Morshed
- Department of Neurosurgery & Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Alexander F Haddad
- Department of Neurosurgery & Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Yalan Zhang
- Department of Neurosurgery & Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Sophia Stoecklein
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Michael Weller
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Michael A Vogelbaum
- Department of NeuroOncology, Moffitt Cancer Center, Tampa, Florida, United States of America
| | - Juergen Beck
- Department of Neurosurgery, University of Freiburg, Freiburg, Germany
| | - Nitin Tandon
- Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, Texas, United States of America
| | - Shawn Hervey-Jumper
- Department of Neurosurgery & Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Annette M Molinaro
- Department of Neurosurgery & Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Roberta Rudà
- Division of Neuro-Oncology, Department of Neuroscience, University of Turin, Italy.,Division of Neurology, Castelfranco Veneto and Treviso Hospital, Italy
| | - Lorenzo Bello
- Division for Neuro-Oncology, Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Oliver Schnell
- Department of Neurosurgery, University of Freiburg, Freiburg, Germany
| | - Yoshua Esquenazi
- Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, Texas, United States of America
| | - Maximilian I Ruge
- Department Stereotactic and Functional Neurosurgery, Centre for Neurosurgery, University Hospital Cologne, Cologne, Germany
| | - Stefan J Grau
- Department of Neurosurgery, University of Cologne, Cologne, Germany.,Klinikum Fulda, Academic Hospital of Marburg University, Fulda, Germany
| | - Mitchel S Berger
- Department of Neurosurgery & Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Susan M Chang
- Department of Neurosurgery & Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Martin van den Bent
- Department of Neurology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Joerg-Christian Tonn
- Department of Neurosurgery, Ludwig-Maximilians-University, Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Germany
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19
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Bernstock JD, Gary SE, Klinger N, Valdes PA, Ibn Essayed W, Olsen HE, Chagoya G, Elsayed G, Yamashita D, Schuss P, Gessler FA, Peruzzi PP, Bag A, Friedman GK. Standard clinical approaches and emerging modalities for glioblastoma imaging. Neurooncol Adv 2022; 4:vdac080. [PMID: 35821676 PMCID: PMC9268747 DOI: 10.1093/noajnl/vdac080] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Glioblastoma (GBM) is the most common primary adult intracranial malignancy and carries a dismal prognosis despite an aggressive multimodal treatment regimen that consists of surgical resection, radiation, and adjuvant chemotherapy. Radiographic evaluation, largely informed by magnetic resonance imaging (MRI), is a critical component of initial diagnosis, surgical planning, and post-treatment monitoring. However, conventional MRI does not provide information regarding tumor microvasculature, necrosis, or neoangiogenesis. In addition, traditional MRI imaging can be further confounded by treatment-related effects such as pseudoprogression, radiation necrosis, and/or pseudoresponse(s) that preclude clinicians from making fully informed decisions when structuring a therapeutic approach. A myriad of novel imaging modalities have been developed to address these deficits. Herein, we provide a clinically oriented review of standard techniques for imaging GBM and highlight emerging technologies utilized in disease characterization and therapeutic development.
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Affiliation(s)
- Joshua D Bernstock
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School , Boston, Massachusetts, USA
| | - Sam E Gary
- Medical Scientist Training Program, University of Alabama at Birmingham, Birmingham , AL, USA
| | - Neil Klinger
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School , Boston, Massachusetts, USA
| | - Pablo A Valdes
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School , Boston, Massachusetts, USA
| | - Walid Ibn Essayed
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School , Boston, Massachusetts, USA
| | - Hannah E Olsen
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School , Boston, Massachusetts, USA
| | - Gustavo Chagoya
- Department of Neurosurgery, University of Alabama at Birmingham, Birmingham , AL, USA
| | - Galal Elsayed
- Department of Neurosurgery, University of Alabama at Birmingham, Birmingham , AL, USA
| | - Daisuke Yamashita
- Department of Neurosurgery, University of Alabama at Birmingham, Birmingham , AL, USA
| | - Patrick Schuss
- Department of Neurosurgery, Unfallkrankenhaus Berlin , Berlin, Germany
| | | | - Pier Paolo Peruzzi
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School , Boston, Massachusetts, USA
| | - Asim Bag
- Department of Diagnostic Imaging, St. Jude Children’s Research Hospital , Memphis, TN USA
| | - Gregory K Friedman
- Department of Neurosurgery, University of Alabama at Birmingham, Birmingham , AL, USA
- Division of Pediatric Hematology and Oncology, Department of Pediatrics, University of Alabama at Birmingham , Birmingham, AL, USA
- Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham , AL, USA
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20
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Clinical measures, radiomics, and genomics offer synergistic value in AI-based prediction of overall survival in patients with glioblastoma. Sci Rep 2022; 12:8784. [PMID: 35610333 PMCID: PMC9130299 DOI: 10.1038/s41598-022-12699-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 05/06/2022] [Indexed: 02/05/2023] Open
Abstract
Multi-omic data, i.e., clinical measures, radiomic, and genetic data, capture multi-faceted tumor characteristics, contributing to a comprehensive patient risk assessment. Here, we investigate the additive value and independent reproducibility of integrated diagnostics in prediction of overall survival (OS) in isocitrate dehydrogenase (IDH)-wildtype GBM patients, by combining conventional and deep learning methods. Conventional radiomics and deep learning features were extracted from pre-operative multi-parametric MRI of 516 GBM patients. Support vector machine (SVM) classifiers were trained on the radiomic features in the discovery cohort (n = 404) to categorize patient groups of high-risk (OS < 6 months) vs all, and low-risk (OS ≥ 18 months) vs all. The trained radiomic model was independently tested in the replication cohort (n = 112) and a patient-wise survival prediction index was produced. Multivariate Cox-PH models were generated for the replication cohort, first based on clinical measures solely, and then by layering on radiomics and molecular information. Evaluation of the high-risk and low-risk classifiers in the discovery/replication cohorts revealed area under the ROC curves (AUCs) of 0.78 (95% CI 0.70-0.85)/0.75 (95% CI 0.64-0.79) and 0.75 (95% CI 0.65-0.84)/0.63 (95% CI 0.52-0.71), respectively. Cox-PH modeling showed a concordance index of 0.65 (95% CI 0.6-0.7) for clinical data improving to 0.75 (95% CI 0.72-0.79) for the combination of all omics. This study signifies the value of integrated diagnostics for improved prediction of OS in GBM.
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21
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Ben Ahmed K, Hall LO, Goldgof DB, Gatenby R. Ensembles of Convolutional Neural Networks for Survival Time Estimation of High-Grade Glioma Patients from Multimodal MRI. Diagnostics (Basel) 2022; 12:diagnostics12020345. [PMID: 35204436 PMCID: PMC8871067 DOI: 10.3390/diagnostics12020345] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 01/13/2022] [Accepted: 01/24/2022] [Indexed: 11/16/2022] Open
Abstract
Glioma is the most common type of primary malignant brain tumor. Accurate survival time prediction for glioma patients may positively impact treatment planning. In this paper, we develop an automatic survival time prediction tool for glioblastoma patients along with an effective solution to the limited availability of annotated medical imaging datasets. Ensembles of snapshots of three dimensional (3D) deep convolutional neural networks (CNN) are applied to Magnetic Resonance Image (MRI) data to predict survival time of high-grade glioma patients. Additionally, multi-sequence MRI images were used to enhance survival prediction performance. A novel way to leverage the potential of ensembles to overcome the limitation of labeled medical image availability is shown. This new classification method separates glioblastoma patients into long- and short-term survivors. The BraTS (Brain Tumor Image Segmentation) 2019 training dataset was used in this work. Each patient case consisted of three MRI sequences (T1CE, T2, and FLAIR). Our training set contained 163 cases while the test set included 46 cases. The best known prediction accuracy of 74% for this type of problem was achieved on the unseen test set.
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Affiliation(s)
- Kaoutar Ben Ahmed
- Department of Computer Science and Engineering, University of South Florida, Tampa, FL 33620, USA; (L.O.H.); (D.B.G.)
- Correspondence:
| | - Lawrence O. Hall
- Department of Computer Science and Engineering, University of South Florida, Tampa, FL 33620, USA; (L.O.H.); (D.B.G.)
| | - Dmitry B. Goldgof
- Department of Computer Science and Engineering, University of South Florida, Tampa, FL 33620, USA; (L.O.H.); (D.B.G.)
| | - Robert Gatenby
- Department of Diagnostic Imaging and Interventional Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA;
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22
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Zorman MJ, Webb P, Nixon M, Sravanam S, Honeyman S, Nandhabalan M, Apostolopoulos V, Stacey R, Hobbs C, Plaha P. Surgical and oncological score to estimate the survival benefit of resection and chemoradiotherapy in elderly (≥70 years) glioblastoma patients: a preliminary analysis. Neurooncol Adv 2022; 4:vdac007. [PMID: 35261976 PMCID: PMC8896333 DOI: 10.1093/noajnl/vdac007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Background Elderly patients with glioblastoma are perceived to face a poor prognosis with perceptions surrounding older age and a relative lack of randomized data contributing. This study evaluated survival prognosticators in elderly glioblastoma patients to more accurately guide their treatment. Methods The records of 169 elderly (≥70 years) patients with a new diagnosis of glioblastoma who had undergone neurosurgical intervention were retrospectively examined for patient sex, age, performance status, comorbidities, MGMT promoter methylation, surgical intervention, and chemoradiation regime. The adjusted survival impact of these factors was determined using Cox proportional hazards model and used to devise a two-stage scoring system to estimate patient survival at the stage of surgical (Elderly Glioblastoma Surgical Score, EGSS) and oncological management (Elderly Glioblastoma Oncological Score, EGOS). Results The median overall survival (mOS) of the cohort was 28.8 weeks. Gross-total and subtotal resection were associated with improved survival compared to biopsy alone (respective mOS 65.3 and 28.1 vs 15.7 weeks, P < .001). Hypofractionated radiotherapy (40Gy in 15 fractions) with Temozolomide was noninferior to the Stupp protocol, P = .72. Exploratory subgroup analysis revealed a significant benefit of Temozolomide-based approaches in MGMT-methylated patients as well as a trend towards improved survival in MGMT-unmethylated patients. Our EGSS and EGOS scores successfully estimated survival in this retrospective cohort with 65% and 73% accuracy. Conclusions Where appropriate and safe, elderly glioblastoma patients may benefit from surgical resection and combined chemoradiotherapy with Temozolomide. The proposed EGSS and EGOS scores take into account important prognostic factors to help guide which patients should receive such treatment.
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Affiliation(s)
- Mark J Zorman
- Department of Neurosurgery, Oxford University Hospital NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
| | - Philip Webb
- Department of Oncology, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Oxford, UK
| | | | - Sanskrithi Sravanam
- Department of Neurosurgery, Oxford University Hospital NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
| | - Susan Honeyman
- Department of Neurosurgery, Oxford University Hospital NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
| | - Meera Nandhabalan
- Department of Oncology, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Oxford, UK
| | - Vasileios Apostolopoulos
- Department of Neurosurgery, Oxford University Hospital NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
| | - Richard Stacey
- Department of Neurosurgery, Oxford University Hospital NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
| | - Claire Hobbs
- Department of Oncology, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Oxford, UK
| | - Puneet Plaha
- Department of Neurosurgery, Oxford University Hospital NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
- Nuffield Department of Surgical Sciences, University of Oxford, UK
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23
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Schoen S, Kilinc MS, Lee H, Guo Y, Degertekin FL, Woodworth GF, Arvanitis C. Towards controlled drug delivery in brain tumors with microbubble-enhanced focused ultrasound. Adv Drug Deliv Rev 2022; 180:114043. [PMID: 34801617 PMCID: PMC8724442 DOI: 10.1016/j.addr.2021.114043] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 09/27/2021] [Accepted: 11/04/2021] [Indexed: 02/06/2023]
Abstract
Brain tumors are particularly challenging malignancies, due to their location in a structurally and functionally distinct part of the human body - the central nervous system (CNS). The CNS is separated and protected by a unique system of brain and blood vessel cells which together prevent most bloodborne therapeutics from entering the brain tumor microenvironment (TME). Recently, great strides have been made through microbubble (MB) ultrasound contrast agents in conjunction with ultrasound energy to locally increase the permeability of brain vessels and modulate the brain TME. As we elaborate in this review, this physical method can effectively deliver a wide range of anticancer agents, including chemotherapeutics, antibodies, and nanoparticle drug conjugates across a range of preclinical brain tumors, including high grade glioma (glioblastoma), diffuse intrinsic pontine gliomas, and brain metastasis. Moreover, recent evidence suggests that this technology can promote the effective delivery of novel immunotherapeutic agents, including immune check-point inhibitors and chimeric antigen receptor T cells, among others. With early clinical studies demonstrating safety, and several Phase I/II trials testing the preclinical findings underway, this technology is making firm steps towards shaping the future treatments of primary and metastatic brain cancer. By elaborating on its key components, including ultrasound systems and MB technology, along with methods for closed-loop spatial and temporal control of MB activity, we highlight how this technology can be tuned to enable new, personalized treatment strategies for primary brain malignancies and brain metastases.
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Affiliation(s)
- Scott Schoen
- Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - M. Sait Kilinc
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Hohyun Lee
- Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Yutong Guo
- Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - F. Levent Degertekin
- Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Graeme F. Woodworth
- Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA,Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, College Park, MD 20742, USA,Fischell Department of Bioengineering A. James Clarke School of Engineering, University of Maryland
| | - Costas Arvanitis
- Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA,Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
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24
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Kiesel B, Wadiura LI, Mischkulnig M, Makolli J, Sperl V, Borkovec M, Freund J, Lang A, Millesi M, Berghoff AS, Furtner J, Woehrer A, Widhalm G. Efficacy, Outcome, and Safety of Elderly Patients with Glioblastoma in the 5-ALA Era: Single Center Experience of More Than 10 Years. Cancers (Basel) 2021; 13:cancers13236119. [PMID: 34885227 PMCID: PMC8657316 DOI: 10.3390/cancers13236119] [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: 10/05/2021] [Revised: 11/25/2021] [Accepted: 11/30/2021] [Indexed: 11/25/2022] Open
Abstract
Simple Summary In the next decades, the incidence of patients with glioblastoma (GBM) will markedly increase due to the growth of the elderly population. Despite the increasing incidence of GBM, elderly patients are frequently excluded from clinical studies and thus, only few data are available specifically focusing on the elderly population. In the current study, we aimed to investigate the efficacy, outcome, and safety of surgically-treated GBM including resections and biopsies in the 5-ALA era in a large elderly cohort of altogether 272 patients. Our data of this large elderly cohort demonstrate for the first time the clinical utility and safety of 5-ALA fluorescence in GBM for improved tumor visualization in both resections as well as biopsies. Therefore, we recommend the use of 5-ALA not only in resections, but also in open/stereotactic biopsies to optimize the neurosurgical management of elderly GBM patients. Abstract Background: In the next decades, the incidence of patients with glioblastoma (GBM) will increase due to the growth of the elderly population. Fluorescence-guided resection using 5-aminolevulinic acid (5-ALA) is widely applied to achieve maximal safe resection of GBM and is identified as a novel intraoperative marker for diagnostic tissue during biopsies. However, detailed analyses of the use of 5-ALA in resections as well as biopsies in a large elderly cohort are still missing. The aim of this study was thus to investigate the efficacy, outcome, and safety of surgically- treated GBM in the 5-ALA era in a large elderly cohort. Methods: All GBM patients aged 65 years or older who underwent neurosurgical intervention between 2007 and 2019 were included. Data on 5-ALA application, intraoperative fluorescence status, and 5-ALA-related side effects were derived from our databank. In the case of resection, the tumor resectability and the extent of resection were determined. Potential prognostic parameters relevant for overall survival were analyzed. Results: 272 GBM patients with a median age of 71 years were included. Intraoperative 5-ALA fluorescence was applied in most neurosurgical procedures (n = 255/272, 88%) and visible fluorescence was detected in most cases (n = 252/255, 99%). In biopsies, 5-ALA was capable of visualizing tumor tissue by visible fluorescence in all but one case (n = 91/92, 99%). 5-ALA administration did not result in any severe side effects. Regarding patient outcome, smaller preoperative tumor volume (<22.75 cm3), gross total resection, single lesions, improved postoperative neurological status, and concomitant radio-chemotherapy showed a significantly longer overall survival. Conclusions: Our data of this large elderly cohort demonstrate the clinical utility and safety of 5-ALA fluorescence in GBM for improved tumor visualization in both resections as well as biopsies. Therefore, we recommend the use of 5-ALA not only in resections, but also in open/stereotactic biopsies to optimize the neurosurgical management of elderly GBM patients.
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Affiliation(s)
- Barbara Kiesel
- Department of Neurosurgery, Medical University Vienna, 1090 Vienna, Austria; (B.K.); (L.I.W.); (M.M.); (J.M.); (V.S.); (M.B.); (J.F.); (A.L.); (M.M.)
| | - Lisa I. Wadiura
- Department of Neurosurgery, Medical University Vienna, 1090 Vienna, Austria; (B.K.); (L.I.W.); (M.M.); (J.M.); (V.S.); (M.B.); (J.F.); (A.L.); (M.M.)
| | - Mario Mischkulnig
- Department of Neurosurgery, Medical University Vienna, 1090 Vienna, Austria; (B.K.); (L.I.W.); (M.M.); (J.M.); (V.S.); (M.B.); (J.F.); (A.L.); (M.M.)
| | - Jessica Makolli
- Department of Neurosurgery, Medical University Vienna, 1090 Vienna, Austria; (B.K.); (L.I.W.); (M.M.); (J.M.); (V.S.); (M.B.); (J.F.); (A.L.); (M.M.)
| | - Veronika Sperl
- Department of Neurosurgery, Medical University Vienna, 1090 Vienna, Austria; (B.K.); (L.I.W.); (M.M.); (J.M.); (V.S.); (M.B.); (J.F.); (A.L.); (M.M.)
| | - Martin Borkovec
- Department of Neurosurgery, Medical University Vienna, 1090 Vienna, Austria; (B.K.); (L.I.W.); (M.M.); (J.M.); (V.S.); (M.B.); (J.F.); (A.L.); (M.M.)
| | - Julia Freund
- Department of Neurosurgery, Medical University Vienna, 1090 Vienna, Austria; (B.K.); (L.I.W.); (M.M.); (J.M.); (V.S.); (M.B.); (J.F.); (A.L.); (M.M.)
| | - Alexandra Lang
- Department of Neurosurgery, Medical University Vienna, 1090 Vienna, Austria; (B.K.); (L.I.W.); (M.M.); (J.M.); (V.S.); (M.B.); (J.F.); (A.L.); (M.M.)
| | - Matthias Millesi
- Department of Neurosurgery, Medical University Vienna, 1090 Vienna, Austria; (B.K.); (L.I.W.); (M.M.); (J.M.); (V.S.); (M.B.); (J.F.); (A.L.); (M.M.)
| | - Anna S. Berghoff
- Department of Medicine I, Clinical Division of Oncology, Medical University of Vienna, 1090 Vienna, Austria;
| | - Julia Furtner
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, 1090 Vienna, Austria;
| | - Adelheid Woehrer
- Department of Neurology, Institute of Neuropathology and Neurochemistry, Medical University Vienna, 1090 Vienna, Austria;
| | - Georg Widhalm
- Department of Neurosurgery, Medical University Vienna, 1090 Vienna, Austria; (B.K.); (L.I.W.); (M.M.); (J.M.); (V.S.); (M.B.); (J.F.); (A.L.); (M.M.)
- Correspondence:
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25
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Hagiwara A, Oughourlian TC, Cho NS, Schlossman J, Wang C, Yao J, Raymond C, Everson R, Patel K, Mareninov S, Rodriguez FJ, Salamon N, Pope WB, Nghiemphu PL, Liau LM, Prins RM, Cloughesy TF, Ellingson BM. Diffusion MRI is an early biomarker of overall survival benefit in IDH wild-type recurrent glioblastoma treated with immune checkpoint inhibitors. Neuro Oncol 2021; 24:1020-1028. [PMID: 34865129 DOI: 10.1093/neuonc/noab276] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Diffusion MRI estimates of the apparent diffusion coefficient (ADC) have been shown to be useful in predicting treatment response in patients with glioblastoma (GBM), with ADC elevations indicating tumor cell death. We aimed to investigate whether the ADC values measured before and after treatment with immune checkpoint inhibitors (ICIs) and the changes in these ADC values could predict overall survival (OS) in patients with recurrent IDH wild-type GBM. METHODS Forty-four patients who met the following inclusion criteria were included in this retrospective study: (i) diagnosed with recurrent IDH wild-type GBM and treated with either pembrolizumab or nivolumab and (ii) availability of diffusion data on pre- and post-ICI MRI. Tumor volume and the median relative ADC (rADC) with respect to the normal-appearing white matter within the enhancing tumor were calculated. RESULTS Median OS among all patients was 8.1 months (range, 1.0-22.5 months). Log-rank test revealed that higher post-treatment rADC was associated with a significantly longer OS (median, 10.3 months for rADC ≧ 1.63 versus 6.1 months for rADC < 1.63; P = 0.02), whereas tumor volume, pre-treatment rADC, and changes in rADC after treatment were not significantly associated with OS. Cox regression analysis revealed that post-treatment rADC significantly influenced OS (P = 0.02, univariate analysis), even after controlling for age and sex (P =0.01, multivariate analysis), and additionally controlling for surgery after ICI treatment (P = 0.045, multivariate analysis). CONCLUSIONS Elevated post-treatment rADC may be an early imaging biomarker for OS benefits in GBM patients receiving ICI treatment.
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Affiliation(s)
- Akifumi Hagiwara
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Talia C Oughourlian
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.,Neuroscience Interdepartmental PhD Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Nicholas S Cho
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA, USA.,Medical Scientist Training Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Jacob Schlossman
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Chencai Wang
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Richard Everson
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Kunal Patel
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Sergey Mareninov
- Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Fausto J Rodriguez
- Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Whitney B Pope
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Phioanh L Nghiemphu
- UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Linda M Liau
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Robert M Prins
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA, USA.,UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
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YAMASHITA S, SAITO R, OSAWA SI, NIIZUMA K, UKISHIRO K, KANAMORI M, KAKINUMA K, SUZUKI K, TOMINAGA T. A Super-selective Wada Test Successfully Detected an Artery That Supplied Broca's Area in a Case of Left Frontal Lobe Glioblastoma: Technical Case Report. Neurol Med Chir (Tokyo) 2021; 61:661-666. [PMID: 34433753 PMCID: PMC8592815 DOI: 10.2176/nmc.tn.2021-0054] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 07/15/2021] [Indexed: 11/20/2022] Open
Abstract
In cases of malignant gliomas located at language eloquent area, it is often difficult to preoperatively detect those area with functional MRI. Awake surgery is often used to spare the language eloquent area during surgery for such tumors; it is not available for a patient whose intracranial pressure is elevated due to the malignant tumor. The Wada test involves infusing anesthetic agents into the internal carotid artery to determine language dominancy before surgery for epilepsy or brain tumor. The super-selective Wada test is a technique to detect more detailed functional localization by infusing anesthetics into far distal middle cerebral artery branches. We present a 37-year-old man suffering from a left frontal lobe glioblastoma, in whom detection of an artery supplying Broca's area was attempted by a super-selective Wada test. The super-selective Wada test successfully detected the branch of middle cerebral artery supplying Broca's area. Total resection of the contrast-enhancing area was achieved without damaging the artery supplying Broca's area without any neurological sequelae. This is the first report describing the usefulness of the super-selective Wada test in glioblastoma treatment. Our findings suggest that the super-selective Wada test is a powerful and useful means to distinguish the artery that supplies the language area from the tumor feeding artery in cases of tumors in the language eloquent area.
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Affiliation(s)
- Shota YAMASHITA
- Department of Neurosurgery, Graduate School of Medicine, Tohoku University, Sendai, Miyagi, Japan
| | - Ryuta SAITO
- Department of Neurosurgery, Graduate School of Medicine, Tohoku University, Sendai, Miyagi, Japan
- Department of Neurosurgical Engineering and Translational Neuroscience, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan
| | - Shin-ichiro OSAWA
- Department of Neurosurgery, Graduate School of Medicine, Tohoku University, Sendai, Miyagi, Japan
| | - Kuniyasu NIIZUMA
- Department of Neurosurgery, Graduate School of Medicine, Tohoku University, Sendai, Miyagi, Japan
- Department of Neurosurgical Engineering and Translational Neuroscience, Graduate School of Biomedical Engineering, Tohoku University, Sendai, Miyagi, Japan
| | - Kazushi UKISHIRO
- Department of Epileptology, Graduate School of Medicine, Tohoku University, Sendai, Miyagi, Japan
| | - Masayuki KANAMORI
- Department of Neurosurgery, Graduate School of Medicine, Tohoku University, Sendai, Miyagi, Japan
| | - Kazuo KAKINUMA
- Department of Behavioral Neurology and Cognitive Neuroscience, Graduate School of Medicine, Tohoku University, Sendai, Miyagi, Japan
| | - Kyoko SUZUKI
- Department of Behavioral Neurology and Cognitive Neuroscience, Graduate School of Medicine, Tohoku University, Sendai, Miyagi, Japan
| | - Teiji TOMINAGA
- Department of Neurosurgery, Graduate School of Medicine, Tohoku University, Sendai, Miyagi, Japan
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Sudibio S, Anton J, Handoko H, Mayang Permata TB, Kodrat H, Nuryadi E, Sofyan HR, Mulyadi R, Aman RA, Gondhowiardjo S. Outcome Analysis and Prognostic Factors in Patients of Glioblastoma Multiforme: An Indonesian Single Institution Experience. Open Access Maced J Med Sci 2021. [DOI: 10.3889/oamjms.2021.7502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Aims: This study was done to assess the survival of patients with glioblastoma multiform and to identify factors that can affect patient survival.
Materials and methods: From January 2015 to December 2019, 55 patients with histopathologically confirmed glioblastoma multiform and received adjuvant radiation/chemoradiation in our department were retrospectively analyzed.
Results: The median overall survival (OS) for entire cohort was 13 months and 1-year OS and 2-year OS rate were 52.7% and 3.6% with the mean follow-up period was 12 months. In univariate analysis, age (≤50 years vs >50 years, p=0.02), performance status (≥90 vs 70-80 vs <70, p<0.001), RTOG RPA classification (class III vs class IV vs class V-VI, p<0.001), parietal lobes tumor site (vs others, p=0.02), residual tumor volume (≤20.4cm3 vs >20.4cm3, p=0.001) and time to initiate adjuvant therapy (<4 weeks vs 4-6 weeks vs >6 weeks, p=0.01) were significantly affect overall survival. In multivariate analysis, RTOG RPA classification and involvement of parietal lobes were independent prognostic factors for overall survival.
Conclusions: RTOG RPA classification that consisted of age and performance status is an independent prognostic factor for the clinical outcome of GBM. Besides this well-known factor, we also identified the involvement of parietal lobe gives a strong negative influence on survival of GBM patients.
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Kim KH, Yoo J, Kim N, Moon JH, Byun HK, Kang SG, Chang JH, Yoon HI, Suh CO. Efficacy of Whole-Ventricular Radiotherapy in Patients Undergoing Maximal Tumor Resection for Glioblastomas Involving the Ventricle. Front Oncol 2021; 11:736482. [PMID: 34621677 PMCID: PMC8490925 DOI: 10.3389/fonc.2021.736482] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 09/06/2021] [Indexed: 01/01/2023] Open
Abstract
Background and Purpose Patients with glioblastoma (GBM) involving the ventricles are at high risk of ventricle opening during surgery and potential ventricular tumor spread. We evaluated the effectiveness of whole-ventricular radiotherapy (WVRT) in reducing intraventricular seeding in patients with GBM and identified patients who could benefit from this approach. Methods and Materials We retrospectively reviewed the data of 382 patients with GBM who underwent surgical resection and temozolomide-based chemoradiotherapy. Propensity score matching was performed to compensate for imbalances in characteristics between patients who did [WVRT (+); n=59] and did not [WVRT (–); n=323] receive WVRT. Local, outfield, intraventricular, and leptomeningeal failure rates were compared. Results All patients in the WVRT (+) group had tumor ventricular involvement and ventricle opening during surgery. In the matched cohort, the WVRT (+) group exhibited a significantly lower 2-year intraventricular failure rate than the WVRT (–) group (2.1% vs. 11.8%; P=0.045), with no difference in other outcomes. Recursive partitioning analysis stratified the patients in the WVRT (–) group at higher intraventricular failure risk (2-year survival, 14.2%) due to tumor ventricular involvement, MGMT unmethylation, and ventricle opening. WVRT reduced the intraventricular failure rate only in high-risk patients (0% vs. 14.2%; P=0.054) or those with MGMT-unmethylated GBM in the matched cohort (0% vs. 17.3%; P=0.036). Conclusions WVRT reduced the intraventricular failure rate in patients with tumor ventricular involvement and ventricle opening during surgery. The MGMT-methylation status may further stratify patients who could benefit from WVRT. Further prospective evaluation of WVRT in GBM is warranted.
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Affiliation(s)
- Kyung Hwan Kim
- Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea
| | - Jihwan Yoo
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, South Korea
| | - Nalee Kim
- Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Ju Hyung Moon
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, South Korea
| | - Hwa Kyung Byun
- Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea
| | - Seok-Gu Kang
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, South Korea
| | - Jong Hee Chang
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, South Korea
| | - Hong In Yoon
- Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea
| | - Chang-Ok Suh
- Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea.,Department of Radiation Oncology, CHA Bundang Medical Center, CHA University, Seongnam, South Korea
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Fujita Y, Nagashima H, Tanaka K, Hashiguchi M, Itoh T, Sasayama T. Hyperintense signal on diffusion-weighted imaging for monitoring the acute response and local recurrence after photodynamic therapy in malignant gliomas. J Neurooncol 2021; 155:81-92. [PMID: 34550511 DOI: 10.1007/s11060-021-03845-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 09/11/2021] [Indexed: 01/22/2023]
Abstract
PURPOSE Photodynamic therapy (PDT) subsequent to surgical tumor removal is a novel localized treatment for malignant glioma that provides effective local control. The acute response of malignant glioma to PDT can be detected as linear transient hyperintense signal on diffusion-weighted imaging (DWI) and a decline in apparent diffusion coefficient values without symptoms. However, their long-term clinical significance has not yet been examined. The aim of this study was to clarify the link between hyperintense signal on DWI as an acute response and recurrence after PDT in malignant glioma. METHODS Thirty patients (16 men; median age, 60.5 years) underwent PDT for malignant glioma at our institution between 2017 and 2020. We analyzed the signal changes on DWI after PDT and the relationship between these findings and the recurrence pattern. RESULTS All patients showed linear hyperintense signal on DWI at the surface of the resected cavity from day 1 after PDT. These changes disappeared in about 30 days without any neurological deterioration. During a mean post-PDT follow-up of 14.3 months, 19 patients (63%) exhibited recurrence: 10 local, 1 distant, and 8 disseminated. All of the local recurrences arose from areas that did not show hyperintense signal on DWI obtained on day 1 after PDT. CONCLUSIONS The local recurrence in malignant glioma after PDT occurs in an area without hyperintense signal on DWI as an acute response to PDT. This characteristic finding could aid in the monitoring of local recurrence after PDT.
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Affiliation(s)
- Yuichi Fujita
- Department of Neurosurgery, Kobe University Graduate School of Medicine, 7-5-1 Kusunoki-cho, Chuo-ku, Kobe, Hyogo, 650-0017, Japan.
| | - Hiroaki Nagashima
- Department of Neurosurgery, Kobe University Graduate School of Medicine, 7-5-1 Kusunoki-cho, Chuo-ku, Kobe, Hyogo, 650-0017, Japan
| | - Kazuhiro Tanaka
- Department of Neurosurgery, Kobe University Graduate School of Medicine, 7-5-1 Kusunoki-cho, Chuo-ku, Kobe, Hyogo, 650-0017, Japan
| | - Mitsuru Hashiguchi
- Department of Neurosurgery, Kobe University Graduate School of Medicine, 7-5-1 Kusunoki-cho, Chuo-ku, Kobe, Hyogo, 650-0017, Japan
| | - Tomoo Itoh
- Department of Diagnostic Pathology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan
| | - Takashi Sasayama
- Department of Neurosurgery, Kobe University Graduate School of Medicine, 7-5-1 Kusunoki-cho, Chuo-ku, Kobe, Hyogo, 650-0017, Japan
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30
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Fyllingen EH, Bø LE, Reinertsen I, Jakola AS, Sagberg LM, Berntsen EM, Salvesen Ø, Solheim O. Survival of glioblastoma in relation to tumor location: a statistical tumor atlas of a population-based cohort. Acta Neurochir (Wien) 2021; 163:1895-1905. [PMID: 33742279 PMCID: PMC8195961 DOI: 10.1007/s00701-021-04802-6] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2019] [Accepted: 03/03/2021] [Indexed: 02/03/2023]
Abstract
Purpose Previous studies on the effect of tumor location on overall survival in glioblastoma have found conflicting results. Based on statistical maps, we sought to explore the effect of tumor location on overall survival in a population-based cohort of patients with glioblastoma and IDH wild-type astrocytoma WHO grade II–III with radiological necrosis. Methods Patients were divided into three groups based on overall survival: < 6 months, 6–24 months, and > 24 months. Statistical maps exploring differences in tumor location between these three groups were calculated from pre-treatment magnetic resonance imaging scans. Based on the results, multivariable Cox regression analyses were performed to explore the possible independent effect of centrally located tumors compared to known prognostic factors by use of distance from center of the third ventricle to contrast-enhancing tumor border in centimeters as a continuous variable. Results A total of 215 patients were included in the statistical maps. Central tumor location (corpus callosum, basal ganglia) was associated with overall survival < 6 months. There was also a reduced overall survival in patients with tumors in the left temporal lobe pole. Tumors in the dorsomedial right temporal lobe and the white matter region involving the left anterior paracentral gyrus/dorsal supplementary motor area/medial precentral gyrus were associated with overall survival > 24 months. Increased distance from center of the third ventricle to contrast-enhancing tumor border was a positive prognostic factor for survival in elderly patients, but less so in younger patients. Conclusions Central tumor location was associated with worse prognosis. Distance from center of the third ventricle to contrast-enhancing tumor border may be a pragmatic prognostic factor in elderly patients. Supplementary Information The online version contains supplementary material available at 10.1007/s00701-021-04802-6.
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31
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Ellingson BM, Patel K, Wang C, Raymond C, Brenner A, de Groot JF, Butowski NA, Zach L, Campian JL, Schlossman J, Rizvi S, Cohen YC, Lowenton-Spier N, Minei TR, Shmueli SF, Wen PY, Cloughesy TF. Validation of diffusion MRI as a biomarker for efficacy using randomized phase III trial of bevacizumab with or without VB-111 in recurrent glioblastoma. Neurooncol Adv 2021; 3:vdab082. [PMID: 34377989 PMCID: PMC8350152 DOI: 10.1093/noajnl/vdab082] [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: 11/14/2022] Open
Abstract
Background Evidence from single and multicenter phase II trials have suggested diffusion MRI is a predictive imaging biomarker for survival benefit in recurrent glioblastoma (rGBM) treated with anti-VEGF therapy. The current study confirms these findings in a large, randomized phase III clinical trial. Methods Patients with rGBM were enrolled in a phase III randomized (1:1), controlled trial (NCT02511405) to compare the efficacy and safety of bevacizumab (BV) versus BV in combination with ofranergene obadenovec (BV+VB-111), an anti-cancer viral therapy. In 170 patients with diffusion MRI available, pretreatment enhancing tumor volume and ADC histogram analysis were used to phenotype patients as having high (>1.24 µm2/ms) or low (<1.24 µm2/ms) ADCL, the mean value of the lower peak of the ADC histogram, within the contrast enhancing tumor. Results Baseline tumor volume (P = .3460) and ADCL (P = .2143) did not differ between treatment arms. Univariate analysis showed patients with high ADCL had a significant survival advantage in all patients (P = .0006), as well as BV (P = .0159) and BV+VB-111 individually (P = .0262). Multivariable Cox regression accounting for treatment arm, age, baseline tumor volume, and ADCL identified continuous measures of tumor volume (P < .0001; HR = 1.0212) and ADCL phenotypes (P = .0012; HR = 0.5574) as independent predictors of OS. Conclusion Baseline diffusion MRI and tumor volume are independent imaging biomarkers of OS in rGBM treated with BV or BV+VB-111.
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Affiliation(s)
- Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,UCLA Neuro Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Kunal Patel
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Chencai Wang
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Andrew Brenner
- University of Texas Health San Antonio Cancer Center, San Antonio, Texas, USA
| | - John F de Groot
- Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Nicholas A Butowski
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Leor Zach
- Oncology Institute, Chaim Sheba Medical Center, Tel HaShomer, Israel
| | - Jian L Campian
- Division of Medical Oncology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Jacob Schlossman
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Shan Rizvi
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | | | | | | | | | - Patrick Y Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Timothy F Cloughesy
- UCLA Neuro Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
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Deciphering the glioblastoma phenotype by computed tomography radiomics. Radiother Oncol 2021; 160:132-139. [PMID: 33984349 DOI: 10.1016/j.radonc.2021.05.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Revised: 04/19/2021] [Accepted: 05/03/2021] [Indexed: 12/23/2022]
Abstract
INTRODUCTION Glioblastoma (GBM) is the most common malignant primary brain tumour which has, despite extensive treatment, a median overall survival of 15 months. Radiomics is the high-throughput extraction of large amounts of image features from radiographic images, which allows capturing the tumour phenotype in 3D and in a non-invasive way. In this study we assess the prognostic value of CT radiomics for overall survival in patients with a GBM. MATERIALS AND METHODS Clinical data and pre-treatment CT images were obtained from 218 patients diagnosed with a GBM via biopsy who underwent radiotherapy +/- temozolomide between 2004 and 2015 treated at three independent institutes (n = 93, 62 and 63). A clinical prognostic score (CPS), a simple radiomics model consisting of volume based score (VPS), a complex radiomics prognostic score (RPS) and a combined clinical and radiomics (C + R)PS model were developed. The population was divided into three risk groups for each prognostic score and respective Kaplan-Meier curves were generated. RESULTS Patient characteristics were broadly comparable. Clinically significant differences were observed with regards to radiation dose, tumour volume and performance status between datasets. Image acquisition parameters differed between institutes. The cross-validated c-indices were moderately discriminative and for the CPS ranged from 0.63 to 0.65; the VPS c-indices ranged between 0.52 and 0.61; the RPS c-indices ranged from 0.57 to 0.64 and the combined clinical and radiomics model resulted in c-indices of 0.59-0.71. CONCLUSION In this study clinical and CT radiomics features were used to predict OS in GBM. Discrimination between low-, middle- and high-risk patients based on the combined clinical and radiomics model was comparable to previous MRI-based models.
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Cloughesy TF, Brenner A, de Groot JF, Butowski NA, Zach L, Campian JL, Ellingson BM, Freedman LS, Cohen YC, Lowenton-Spier N, Rachmilewitz Minei T, Fain Shmueli S, Wen PY. A randomized controlled phase III study of VB-111 combined with bevacizumab vs bevacizumab monotherapy in patients with recurrent glioblastoma (GLOBE). Neuro Oncol 2021; 22:705-717. [PMID: 31844890 PMCID: PMC7229248 DOI: 10.1093/neuonc/noz232] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Background Ofranergene obadenovec (VB-111) is an anticancer viral therapy that demonstrated in a phase II study a survival benefit for patients with recurrent glioblastoma (rGBM) who were primed with VB-111 monotherapy that was continued after progression with concomitant bevacizumab. Methods This pivotal phase III randomized, controlled trial compared the efficacy and safety of upfront combination of VB-111 and bevacizumab versus bevacizumab monotherapy. Patients were randomized 1:1 to receive VB-111 1013 viral particles every 8 weeks in combination with bevacizumab 10 mg/kg every 2 weeks (combination arm) or bevacizumab monotherapy (control arm). The primary endpoint was overall survival (OS), and secondary endpoints were objective response rate (ORR) by Response Assessment in Neuro-Oncology (RANO) criteria and progression-free survival (PFS). Results Enrolled were 256 patients at 57 sites. Median exposure to VB-111 was 4 months. The study did not meet its primary or secondary goals. Median OS was 6.8 versus 7.9 months in the combination versus control arm (hazard ratio, 1.20; 95% CI: 0.91–1.59; P = 0.19) and ORR was 27.3% versus 21.9% (P = 0.26). A higher rate of grades 3–5 adverse events was reported in the combination arm (67% vs 40%), mainly attributed to a higher rate of CNS and flu-like/fever events. Trends for improved survival with combination treatment were seen in the subgroup of patients with smaller tumors and in patients who had a posttreatment febrile reaction. Conclusions In this study, upfront concomitant administration of VB-111 and bevacizumab failed to improve outcomes in rGBM. Change of treatment regimen, with the lack of VB-111 monotherapy priming, may explain the differences from the favorable phase II results. Clinical trials registration NCT02511405
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Affiliation(s)
- Timothy F Cloughesy
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Andrew Brenner
- University of Texas Health San Antonio Cancer Center, San Antonio, Texas, USA
| | - John F de Groot
- Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Nicholas A Butowski
- Department of Neurological Surgery, University of California San Francisco, San Francisco, California, USA
| | - Leor Zach
- Oncology Institute, Chaim Sheba Medical Center, Tel HaShomer, Israel
| | - Jian L Campian
- Division of Medical Oncology, Washington University School of Medicine, St Louis, Missouri, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Laurence S Freedman
- Biostatistics and Biomathematics Unit, Gertner Institute for Epidemiology and Health Policy Research, Chaim Sheba Medical Center, Tel HaShomer, Israel
| | | | | | | | | | | | - Patrick Y Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
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Kitano Y, Aoki K, Ohka F, Yamazaki S, Motomura K, Tanahashi K, Hirano M, Naganawa T, Iida M, Shiraki Y, Nishikawa T, Shimizu H, Yamaguchi J, Maeda S, Suzuki H, Wakabayashi T, Baba Y, Yasui T, Natsume A. Urinary MicroRNA-Based Diagnostic Model for Central Nervous System Tumors Using Nanowire Scaffolds. ACS APPLIED MATERIALS & INTERFACES 2021; 13:17316-17329. [PMID: 33793202 DOI: 10.1021/acsami.1c01754] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
There are no accurate mass screening methods for early detection of central nervous system (CNS) tumors. Recently, liquid biopsy has received a lot of attention for less-invasive cancer screening. Unlike other cancers, CNS tumors require efforts to find biomarkers due to the blood-brain barrier, which restricts molecular exchange between the parenchyma and blood. Additionally, because a satisfactory way to collect urinary biomarkers is lacking, urine-based liquid biopsy has not been fully investigated despite the fact that it has some advantages compared to blood or cerebrospinal fluid-based biopsy. Here, we have developed a mass-producible and sterilizable nanowire-based device that can extract urinary microRNAs efficiently. Urinary microRNAs from patients with CNS tumors (n = 119) and noncancer individuals (n = 100) were analyzed using a microarray to yield comprehensive microRNA expression profiles. To clarify the origin of urinary microRNAs of patients with CNS tumors, glioblastoma organoids were generated. Glioblastoma organoid-derived differentially expressed microRNAs (DEMs) included 73.4% of the DEMs in urine of patients with parental tumors but included only 3.9% of those in urine of noncancer individuals, which suggested that many CNS tumor-derived microRNAs could be identified in urine directly. We constructed the diagnostic model based on the expression of the selected microRNAs and found that it was able to differentiate patients and noncancer individuals at a sensitivity and specificity of 100 and 97%, respectively, in an independent dataset. Our findings demonstrate that urinary microRNAs extracted with the nanowire device offer a well-fitted strategy for mass screening of CNS tumors.
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Affiliation(s)
- Yotaro Kitano
- Department of Neurosurgery, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
- Department of Neurosurgery, Graduate School of Medicine, Mie University, 2-174 Edobashi, Tsu 514-8507, Japan
| | - Kosuke Aoki
- Department of Neurosurgery, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
- Institute of Nano-Life-Systems, Institutes of Innovation for Future Society, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
| | - Fumiharu Ohka
- Department of Neurosurgery, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Shintaro Yamazaki
- Department of Neurosurgery, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Kazuya Motomura
- Department of Neurosurgery, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Kuniaki Tanahashi
- Department of Neurosurgery, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Masaki Hirano
- Department of Neurosurgery, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Tsuyoshi Naganawa
- Department of Biomolecular Engineering, Graduate School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
| | - Mikiko Iida
- Department of Biomolecular Engineering, Graduate School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
| | - Yukihiro Shiraki
- Department of Pathology, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Tomohide Nishikawa
- Department of Neurosurgery, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Hiroyuki Shimizu
- Department of Neurosurgery, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Junya Yamaguchi
- Department of Neurosurgery, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Sachi Maeda
- Department of Neurosurgery, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Hidenori Suzuki
- Department of Neurosurgery, Graduate School of Medicine, Mie University, 2-174 Edobashi, Tsu 514-8507, Japan
| | - Toshihiko Wakabayashi
- Department of Neurosurgery, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Yoshinobu Baba
- Institute of Nano-Life-Systems, Institutes of Innovation for Future Society, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
- Department of Biomolecular Engineering, Graduate School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
- Institute of Quantum Life Science, National Institutes for Quantum and Radiological Science and Technology, Anagawa 4-9-1, Inage-ku, Chiba 263-8555, Japan
| | - Takao Yasui
- Institute of Nano-Life-Systems, Institutes of Innovation for Future Society, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
- Department of Biomolecular Engineering, Graduate School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
- Japan Science and Technology Agency (JST), PRESTO, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012, Japan
| | - Atsushi Natsume
- Department of Neurosurgery, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
- Institute of Nano-Life-Systems, Institutes of Innovation for Future Society, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
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On the Prognosis of Multifocal Glioblastoma: An Evaluation Incorporating Volumetric MRI. ACTA ACUST UNITED AC 2021; 28:1437-1446. [PMID: 33917207 PMCID: PMC8167648 DOI: 10.3390/curroncol28020136] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 03/28/2021] [Accepted: 04/02/2021] [Indexed: 11/17/2022]
Abstract
Primary glioblastoma (GBM), IDH-wildtype, especially with multifocal appearance/growth (mGBM), is associated with very poor prognosis. Several clinical parameters have been identified to provide prognostic value in both unifocal GBM (uGBM) and mGBM, but information about the influence of radiological parameters on survival for mGBM cohorts is scarce. This study evaluated the prognostic value of several volumetric parameters derived from magnetic resonance imaging (MRI). Data from the Department of Neurosurgery, Leipzig University Hospital, were retrospectively analyzed. Patients treated between 2014 and 2019, aged older than 18 years and with adequate peri-operative MRI were included. Volumetric assessment was performed manually. One hundred and eighty-three patients were included. Survival of patients with mGBM was significantly shorter (p < 0.0001). Univariate analysis revealed extent of resection, adjuvant therapy regimen, residual tumor volume, tumor necrosis volume and ratio of tumor necrosis to initial volume as statistically significant for overall survival. In multivariate Cox regression, however, only EOR (for uGBM and the entire cohort) and adjuvant therapy were independently significant for survival. Decreased ratio of tumor necrosis to initial tumor volume and extent of resection were associated with prolonged survival in mGBM but failed to achieve statistical significance in multivariate analysis.
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36
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Patel KS, Everson RG, Yao J, Raymond C, Goldman J, Schlossman J, Tsung J, Tan C, Pope WB, Ji MS, Nguyen NT, Lai A, Nghiemphu PL, Liau LM, Cloughesy TF, Ellingson BM. Diffusion Magnetic Resonance Imaging Phenotypes Predict Overall Survival Benefit From Bevacizumab or Surgery in Recurrent Glioblastoma With Large Tumor Burden. Neurosurgery 2021; 87:931-938. [PMID: 32365185 DOI: 10.1093/neuros/nyaa135] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Accepted: 02/02/2020] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Diffusion magnetic resonance (MR) characteristics are a predictive imaging biomarker for survival benefit in recurrent glioblastoma treated with anti-vascular endothelial growth factor (VEGF) therapy; however, its use in large volume recurrence has not been evaluated. OBJECTIVE To determine if diffusion MR characteristics can predict survival outcomes in patients with large volume recurrent glioblastoma treated with bevacizumab or repeat resection. METHODS A total of 32 patients with large volume (>20 cc or > 3.4 cm diameter) recurrent glioblastoma treated with bevacizumab and 35 patients treated with repeat surgery were included. Pretreatment tumor volume and apparent diffusion coefficient (ADC) histogram analysis were used to phenotype patients as having high (>1.24 μm2/ms) or low (<1.24 μm2/ms) ADCL, the mean value of the lower peak in a double Gaussian model of the ADC histogram within the contrast enhancing tumor. RESULTS In bevacizumab and surgical cohorts, volume was correlated with overall survival (Bevacizumab: P = .009, HR = 1.02; Surgical: P = .006, HR = 0.96). ADCL was an independent predictor of survival in the bevacizumab cohort (P = .049, HR = 0.44), but not the surgical cohort (P = .273, HR = 0.67). There was a survival advantage of surgery over bevacizumab in patients with low ADCL (P = .036, HR = 0.43) but not in patients with high ADCL (P = .284, HR = 0.69). CONCLUSION Pretreatment diffusion MR imaging is an independent predictive biomarker for overall survival in recurrent glioblastoma with a large tumor burden. Large tumors with low ADCL have a survival benefit when treated with surgical resection, whereas large tumors with high ADCL may be best managed with bevacizumab.
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Affiliation(s)
- Kunal S Patel
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.,Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Richard G Everson
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Jodi Goldman
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Jacob Schlossman
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Joseph Tsung
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Caleb Tan
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Whitney B Pope
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Matthew S Ji
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Nhung T Nguyen
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Albert Lai
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Phioanh L Nghiemphu
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Linda M Liau
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Timothy F Cloughesy
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
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37
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Precise enhancement quantification in post-operative MRI as an indicator of residual tumor impact is associated with survival in patients with glioblastoma. Sci Rep 2021; 11:695. [PMID: 33436737 PMCID: PMC7804103 DOI: 10.1038/s41598-020-79829-3] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Accepted: 12/09/2020] [Indexed: 12/15/2022] Open
Abstract
Glioblastoma is the most common primary brain tumor. Standard therapy consists of maximum safe resection combined with adjuvant radiochemotherapy followed by chemotherapy with temozolomide, however prognosis is extremely poor. Assessment of the residual tumor after surgery and patient stratification into prognostic groups (i.e., by tumor volume) is currently hindered by the subjective evaluation of residual enhancement in medical images (magnetic resonance imaging [MRI]). Furthermore, objective evidence defining the optimal time to acquire the images is lacking. We analyzed 144 patients with glioblastoma, objectively quantified the enhancing residual tumor through computational image analysis and assessed the correlation with survival. Pathological enhancement thickness on post-surgical MRI correlated with survival (hazard ratio: 1.98, p < 0.001). The prognostic value of several imaging and clinical variables was analyzed individually and combined (radiomics AUC 0.71, p = 0.07; combined AUC 0.72, p < 0.001). Residual enhancement thickness and radiomics complemented clinical data for prognosis stratification in patients with glioblastoma. Significant results were only obtained for scans performed between 24 and 72 h after surgery, raising the possibility of confounding non-tumor enhancement in very early post-surgery MRI. Regarding the extent of resection, and in agreement with recent studies, the association between the measured tumor remnant and survival supports maximal safe resection whenever possible.
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Riva M, Lopci E, Gay LG, Nibali MC, Rossi M, Sciortino T, Castellano A, Bello L. Advancing Imaging to Enhance Surgery: From Image to Information Guidance. Neurosurg Clin N Am 2021; 32:31-46. [PMID: 33223024 DOI: 10.1016/j.nec.2020.08.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Conventional magnetic resonance imaging (cMRI) has an established role as a crucial disease parameter in the multidisciplinary management of glioblastoma, guiding diagnosis, treatment planning, assessment, and follow-up. Yet, cMRI cannot provide adequate information regarding tissue heterogeneity and the infiltrative extent beyond the contrast enhancement. Advanced magnetic resonance imaging and PET and newer analytical methods are transforming images into data (radiomics) and providing noninvasive biomarkers of molecular features (radiogenomics), conveying enhanced information for improving decision making in surgery. This review analyzes the shift from image guidance to information guidance that is relevant for the surgical treatment of glioblastoma.
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Affiliation(s)
- Marco Riva
- Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Via Festa del Perdono 7, Milan 20122, Italy; IRCCS Istituto Ortopedico Galeazzi, U.O. Neurochirurgia Oncologica, Milan, Italy.
| | - Egesta Lopci
- Unit of Nuclear Medicine, Humanitas Clinical and Research Center - IRCCS, Via Manzoni 56, Rozzano, Milan 20089, Italy. https://twitter.com/LopciEgesta
| | - Lorenzo G Gay
- IRCCS Istituto Ortopedico Galeazzi, U.O. Neurochirurgia Oncologica, Milan, Italy; Department of Oncology and Hemato-Oncology, Via Festa del Perdono 7, Milan 20122, Italy
| | - Marco Conti Nibali
- IRCCS Istituto Ortopedico Galeazzi, U.O. Neurochirurgia Oncologica, Milan, Italy; Department of Oncology and Hemato-Oncology, Via Festa del Perdono 7, Milan 20122, Italy. https://twitter.com/dr_mcn
| | - Marco Rossi
- IRCCS Istituto Ortopedico Galeazzi, U.O. Neurochirurgia Oncologica, Milan, Italy; Department of Oncology and Hemato-Oncology, Via Festa del Perdono 7, Milan 20122, Italy
| | - Tommaso Sciortino
- IRCCS Istituto Ortopedico Galeazzi, U.O. Neurochirurgia Oncologica, Milan, Italy; Department of Oncology and Hemato-Oncology, Via Festa del Perdono 7, Milan 20122, Italy
| | - Antonella Castellano
- Neuroradiology Unit and CERMAC, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, Milan 20123, Italy. https://twitter.com/antocastella
| | - Lorenzo Bello
- IRCCS Istituto Ortopedico Galeazzi, U.O. Neurochirurgia Oncologica, Milan, Italy; Department of Oncology and Hemato-Oncology, Via Festa del Perdono 7, Milan 20122, Italy
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Wan Y, Rahmat R, Price SJ. Deep learning for glioblastoma segmentation using preoperative magnetic resonance imaging identifies volumetric features associated with survival. Acta Neurochir (Wien) 2020; 162:3067-3080. [PMID: 32662042 PMCID: PMC7593295 DOI: 10.1007/s00701-020-04483-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 07/02/2020] [Indexed: 12/21/2022]
Abstract
BACKGROUND Measurement of volumetric features is challenging in glioblastoma. We investigate whether volumetric features derived from preoperative MRI using a convolutional neural network-assisted segmentation is correlated with survival. METHODS Preoperative MRI of 120 patients were scored using Visually Accessible Rembrandt Images (VASARI) features. We trained and tested a multilayer, multi-scale convolutional neural network on multimodal brain tumour segmentation challenge (BRATS) data, prior to testing on our dataset. The automated labels were manually edited to generate ground truth segmentations. Network performance for our data and BRATS data was compared. Multivariable Cox regression analysis corrected for multiple testing using the false discovery rate was performed to correlate clinical and imaging variables with overall survival. RESULTS Median Dice coefficients in our sample were (1) whole tumour 0.94 (IQR, 0.82-0.98) compared to 0.91 (IQR, 0.83-0.94 p = 0.012), (2) FLAIR region 0.84 (IQR, 0.63-0.95) compared to 0.81 (IQR, 0.69-0.8 p = 0.170), (3) contrast-enhancing region 0.91 (IQR, 0.74-0.98) compared to 0.83 (IQR, 0.78-0.89 p = 0.003) and (4) necrosis region were 0.82 (IQR, 0.47-0.97) compared to 0.67 (IQR, 0.42-0.81 p = 0.005). Contrast-enhancing region/tumour core ratio (HR 4.73 [95% CI, 1.67-13.40], corrected p = 0.017) and necrotic core/tumour core ratio (HR 8.13 [95% CI, 2.06-32.12], corrected p = 0.011) were independently associated with overall survival. CONCLUSION Semi-automated segmentation of glioblastoma using a convolutional neural network trained on independent data is robust when applied to routine clinical data. The segmented volumes have prognostic significance.
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40
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Abstract
PURPOSE OF REVIEW This article highlights important aspects of the evaluation, diagnosis, and treatment of adult gliomas, including lower-grade astrocytomas and oligodendrogliomas, glioblastomas, and ependymomas. RECENT FINDINGS The appropriate initial evaluation and accurate diagnosis of gliomas require an understanding of the spectrum of clinical and radiographic presentations. Recent advances in the understanding of distinct molecular prognostic subtypes have led to major revisions in the diagnostic classification of gliomas. Integration of these new diagnostic and molecular classifications is an important part of the modern management of gliomas and facilitates better understanding and interpretation of the efficacy of different therapies in specific glioma subtypes. SUMMARY The management of adult gliomas is a multidisciplinary endeavor. However, despite recent molecular and treatment advances, the majority of diffuse gliomas remain incurable, and efforts aimed at the development and testing of new therapies in clinical trials are ongoing.
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41
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Wirsching HG, Roelcke U, Weller J, Hundsberger T, Hottinger AF, von Moos R, Caparrotti F, Conen K, Remonda L, Roth P, Ochsenbein A, Tabatabai G, Weller M. MRI and 18FET-PET Predict Survival Benefit from Bevacizumab Plus Radiotherapy in Patients with Isocitrate Dehydrogenase Wild-type Glioblastoma: Results from the Randomized ARTE Trial. Clin Cancer Res 2020; 27:179-188. [PMID: 32967939 DOI: 10.1158/1078-0432.ccr-20-2096] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 08/09/2020] [Accepted: 09/17/2020] [Indexed: 11/16/2022]
Abstract
PURPOSE To explore a prognostic or predictive role of MRI and O-(2-18F-fluoroethyl)-L-tyrosine (18FET) PET parameters for outcome in the randomized multicenter trial ARTE that compared bevacizumab plus radiotherapy with radiotherpay alone in elderly patients with glioblastoma. PATIENTS AND METHODS Patients with isocitrate dehydrogenase wild-type glioblastoma ages 65 years or older were included in this post hoc analysis. Tumor volumetric and apparent diffusion coefficient (ADC) analyses of serial MRI scans from 67 patients and serial 18FET-PET tumor-to-brain intensity ratios (TBRs) from 31 patients were analyzed blinded for treatment arm and outcome. Multivariate Cox regression analysis was done to account for established prognostic factors and treatment arm. RESULTS Overall survival benefit from bevacizumab plus radiotherapy compared with radiotherapy alone was observed for larger pretreatment MRI contrast-enhancing tumor [HR per cm3 0.94; 95% confidence interval (CI), 0.89-0.99] and for higher ADC (HR 0.18; CI, 0.05-0.66). Higher 18FET-TBR on pretreatment PET scans was associated with inferior overall survival in both arms. Response assessed by standard MRI-based Response Assessment in Neuro-Oncology criteria was associated with overall survival in the bevacizumab plus radiotherapy arm by trend only (P = 0.09). High 18FET-TBR of noncontrast-enhancing tumor portions during bevacizumab therapy was associated with inferior overall survival on multivariate analysis (HR 5.97; CI, 1.16-30.8). CONCLUSIONS Large pretreatment contrast-enhancing tumor mass and higher ADCs identify patients who may experience a survival benefit from bevacizumab plus radiotherapy. Persistent 18FET-PET signal of no longer contrast-enhancing tumor after concomitant bevacizumab plus radiotherapy suggests pseudoresponse and predicts poor outcome.
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Affiliation(s)
- Hans-Georg Wirsching
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland.
| | - Ulrich Roelcke
- Department of Neurology, Cantonal Hospital Aarau, Aarau, Switzerland
| | - Jonathan Weller
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Thomas Hundsberger
- Department of Neurology, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - Andreas F Hottinger
- Departments of Clinical Neurosciences and Medical Oncology, University Hospital Lausanne, Lausanne, Switzerland
| | - Roger von Moos
- Department of Medical Oncology, Cantonal Hospital Graubuenden, Chur, Switzerland
| | - Francesca Caparrotti
- Department of Radiation Oncology, University Hospital Geneva, Geneva, Switzerland
| | - Katrin Conen
- Department of Medical Oncology, University Hospital Basel, Basel, Switzerland
| | - Luca Remonda
- Department of Neuroradiology, Cantonal Hospital Aarau, Aarau, Switzerland
| | - Patrick Roth
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Adrian Ochsenbein
- Department of Medical Oncology, Inselspital, Berne University Hospital, University of Berne, Berne, Switzerland
| | - Ghazaleh Tabatabai
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Michael Weller
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
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42
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Decorin expression is associated with predictive diffusion MR phenotypes of anti-VEGF efficacy in glioblastoma. Sci Rep 2020; 10:14819. [PMID: 32908231 PMCID: PMC7481206 DOI: 10.1038/s41598-020-71799-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 08/04/2020] [Indexed: 12/13/2022] Open
Abstract
Previous data suggest that apparent diffusion coefficient (ADC) imaging phenotypes predict survival response to anti-VEGF monotherapy in glioblastoma. However, the mechanism by which imaging may predict clinical response is unknown. We hypothesize that decorin (DCN), a proteoglycan implicated in the modulation of the extracellular microenvironment and sequestration of pro-angiogenic signaling, may connect ADC phenotypes to survival benefit to anti-VEGF therapy. Patients undergoing resection for glioblastoma as well as patients included in The Cancer Genome Atlas (TCGA) and IVY Glioblastoma Atlas Project (IVY GAP) databases had pre-operative imaging analyzed to calculate pre-operative ADCL values, the average ADC in the lower distribution using a double Gaussian mixed model. ADCL values were correlated to available RNA expression from these databases as well as from RNA sequencing from patient derived mouse orthotopic xenograft samples. Targeted biopsies were selected based on ADC values and prospectively collected during resection. Surgical specimens were used to evaluate for DCN RNA and protein expression by ADC value. The IVY Glioblastoma Atlas Project Database was used to evaluate DCN localization and relationship with VEGF pathway via in situ hybridization maps and RNA sequencing data. In a cohort of 35 patients with pre-operative ADC imaging and surgical specimens, DCN RNA expression levels were significantly larger in high ADCL tumors (41.6 vs. 1.5; P = 0.0081). In a cohort of 17 patients with prospectively targeted biopsies there was a positive linear correlation between ADCL levels and DCN protein expression between tumors (Pearson R2 = 0.3977; P = 0.0066) and when evaluating different targets within the same tumor (Pearson R2 = 0.3068; P = 0.0139). In situ hybridization data localized DCN expression to areas of microvascular proliferation and immunohistochemical studies localized DCN protein expression to the tunica adventitia of blood vessels within the tumor. DCN expression positively correlated with VEGFR1 & 2 expression and localized to similar areas of tumor. Increased ADCL on diffusion MR imaging is associated with high DCN expression as well as increased survival with anti-VEGF therapy in glioblastoma. DCN may play an important role linking the imaging features on diffusion MR and anti-VEGF treatment efficacy. DCN may serve as a target for further investigation and modulation of anti-angiogenic therapy in GBM.
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43
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Brem S, Henderson F. Commentary: 5-Aminolevulinic Acid and Contrast-Enhanced Ultrasound: The Combination of the 2 Techniques to Optimize the Extent of Resection in Glioblastoma Surgery. Neurosurgery 2020; 86:E541-E543. [PMID: 32186338 DOI: 10.1093/neuros/nyaa061] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Accepted: 01/30/2020] [Indexed: 12/20/2022] Open
Affiliation(s)
- Steven Brem
- Department of Neurosurgery, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Fraser Henderson
- Department of Neurological Surgery, Medical University of South Carolina, Charleston, South Carolina
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44
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Wen PY, Weller M, Lee EQ, Alexander BM, Barnholtz-Sloan JS, Barthel FP, Batchelor TT, Bindra RS, Chang SM, Chiocca EA, Cloughesy TF, DeGroot JF, Galanis E, Gilbert MR, Hegi ME, Horbinski C, Huang RY, Lassman AB, Le Rhun E, Lim M, Mehta MP, Mellinghoff IK, Minniti G, Nathanson D, Platten M, Preusser M, Roth P, Sanson M, Schiff D, Short SC, Taphoorn MJB, Tonn JC, Tsang J, Verhaak RGW, von Deimling A, Wick W, Zadeh G, Reardon DA, Aldape KD, van den Bent MJ. Glioblastoma in adults: a Society for Neuro-Oncology (SNO) and European Society of Neuro-Oncology (EANO) consensus review on current management and future directions. Neuro Oncol 2020; 22:1073-1113. [PMID: 32328653 PMCID: PMC7594557 DOI: 10.1093/neuonc/noaa106] [Citation(s) in RCA: 538] [Impact Index Per Article: 134.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Glioblastomas are the most common form of malignant primary brain tumor and an important cause of morbidity and mortality. In recent years there have been important advances in understanding the molecular pathogenesis and biology of these tumors, but this has not translated into significantly improved outcomes for patients. In this consensus review from the Society for Neuro-Oncology (SNO) and the European Association of Neuro-Oncology (EANO), the current management of isocitrate dehydrogenase wildtype (IDHwt) glioblastomas will be discussed. In addition, novel therapies such as targeted molecular therapies, agents targeting DNA damage response and metabolism, immunotherapies, and viral therapies will be reviewed, as well as the current challenges and future directions for research.
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Affiliation(s)
- Patrick Y Wen
- Dana-Farber Cancer Institute, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Michael Weller
- Department of Neurology and Brain Tumor Center, University Hospital and University of Zurich, Zurich, Switzerland
| | - Eudocia Quant Lee
- Dana-Farber Cancer Institute, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Brian M Alexander
- Dana-Farber Cancer Institute, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Jill S Barnholtz-Sloan
- Case Western Reserve University School of Medicine and University Hospitals of Cleveland, Cleveland, Ohio, USA
| | - Floris P Barthel
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, USA
| | - Tracy T Batchelor
- Department of Neurology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute and Harvard Medical School
| | - Ranjit S Bindra
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, Connecticut, USA
| | - Susan M Chang
- University of California San Francisco, San Francisco, California, USA
| | - E Antonio Chiocca
- Department of Neurosurgery, Brigham and Women’s Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA
| | - Timothy F Cloughesy
- David Geffen School of Medicine, Department of Neurology, University of California Los Angeles, Los Angeles, California, USA
| | - John F DeGroot
- Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | | | - Mark R Gilbert
- Neuro-Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Monika E Hegi
- Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Craig Horbinski
- Department of Pathology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Raymond Y Huang
- Division of Neuroradiology, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Andrew B Lassman
- Department of Neurology and Herbert Irving Comprehensive Cancer Center, NewYork-Presbyterian Hospital/Columbia University Irving Medical Center, New York, New York, USA
| | - Emilie Le Rhun
- University of Lille, Inserm, Neuro-oncology, General and Stereotaxic Neurosurgery service, University Hospital of Lille, Lille, France; Breast Cancer Department, Oscar Lambret Center, Lille, France and Department of Neurology & Brain Tumor Center, University Hospital and University of Zurich, Zurich, Switzerland
| | - Michael Lim
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | | | - Ingo K Mellinghoff
- Department of Neurology and Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Giuseppe Minniti
- Radiation Oncology Unit, Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - David Nathanson
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, USA
| | - Michael Platten
- Department of Neurology, Medical Faculty Mannheim, MCTN, Heidelberg University, Heidelberg, Germany
| | - Matthias Preusser
- Division of Oncology, Department of Medicine, Medical University of Vienna, Vienna, Austria
| | - Patrick Roth
- Department of Neurology and Brain Tumor Center, University Hospital and University of Zurich, Zurich, Switzerland
| | - Marc Sanson
- Sorbonne Université, Inserm, CNRS, UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière – Charles Foix, Service de Neurologie 2-Mazarin, Paris, France
| | - David Schiff
- University of Virginia School of Medicine, Division of Neuro-Oncology, Department of Neurology, University of Virginia, Charlottesville, Virginia, USA
| | - Susan C Short
- Leeds Institute of Medical Research at St James’s, University of Leeds, Leeds, UK
| | - Martin J B Taphoorn
- Department of Neurology, Medical Center Haaglanden, The Hague and Department of Neurology, Leiden University Medical Center, the Netherlands
| | | | - Jonathan Tsang
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, USA
| | - Roel G W Verhaak
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, USA
| | - Andreas von Deimling
- Neuropathology and Clinical Cooperation Unit Neuropathology, University Heidelberg and German Cancer Center, Heidelberg, Germany
| | - Wolfgang Wick
- Department of Neurology and Neuro-oncology Program, National Center for Tumor Diseases, Heidelberg University Hospital, Heidelberg, Germany
| | - Gelareh Zadeh
- MacFeeters Hamilton Centre for Neuro-Oncology Research, Princess Margaret Cancer Centre, Toronto, Canada
| | - David A Reardon
- Dana-Farber Cancer Institute, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Kenneth D Aldape
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA
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Kickingereder P, Brugnara G, Hansen MB, Nowosielski M, Pflüger I, Schell M, Isensee F, Foltyn M, Neuberger U, Kessler T, Sahm F, Wick A, Heiland S, Weller M, Platten M, von Deimling A, Maier-Hein KH, Østergaard L, van den Bent MJ, Gorlia T, Wick W, Bendszus M. Noninvasive Characterization of Tumor Angiogenesis and Oxygenation in Bevacizumab-treated Recurrent Glioblastoma by Using Dynamic Susceptibility MRI: Secondary Analysis of the European Organization for Research and Treatment of Cancer 26101 Trial. Radiology 2020; 297:164-175. [PMID: 32720870 DOI: 10.1148/radiol.2020200978] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Background Relevance of antiangiogenic treatment with bevacizumab in patients with glioblastoma is controversial because progression-free survival benefit did not translate into an overall survival (OS) benefit in randomized phase III trials. Purpose To perform longitudinal characterization of intratumoral angiogenesis and oxygenation by using dynamic susceptibility contrast agent-enhanced (DSC) MRI and evaluate its potential for predicting outcome from administration of bevacizumab. Materials and Methods In this secondary analysis of the prospective randomized phase II/III European Organization for Research and Treatment of Cancer 26101 trial conducted between October 2011 and December 2015 in 596 patients with first recurrence of glioblastoma, the subset of patients with availability of anatomic MRI and DSC MRI at baseline and first follow-up was analyzed. Patients were allocated into those administered bevacizumab (hereafter, the BEV group; either bevacizumab monotherapy or bevacizumab with lomustine) and those not administered bevacizumab (hereafter, the non-BEV group with lomustine monotherapy). Contrast-enhanced tumor volume, noncontrast-enhanced T2 fluid-attenuated inversion recovery (FLAIR) signal abnormality volume, Gaussian-normalized relative cerebral blood volume (nrCBV), Gaussian-normalized relative blood flow (nrCBF), and tumor metabolic rate of oxygen (nTMRO2) was quantified. The predictive ability of these imaging parameters was assessed with multivariable Cox regression and formal interaction testing. Results A total of 254 of 596 patients were evaluated (mean age, 57 years ± 11; 155 men; 161 in the BEV group and 93 in non-BEV group). Progression-free survival was longer in the BEV group (3.7 months; 95% confidence interval [CI]: 3.0, 4.2) compared with the non-BEV group (2.5 months; 95% CI: 1.5, 2.9; P = .01), whereas OS was not different (P = .15). The nrCBV decreased for the BEV group (-16.3%; interquartile range [IQR], -39.5% to 12.0%; P = .01), but not for the non-BEV group (1.2%; IQR, -17.9% to 23.3%; P = .19) between baseline and first follow-up. An identical pattern was observed for both nrCBF and nTMRO2 values. Contrast-enhanced tumor and noncontrast-enhanced T2 FLAIR signal abnormality volumes decreased for the BEV group (-66% [IQR, -83% to -35%] and -33% [IQR, -71% to -5%], respectively; P < .001 for both), whereas they increased for the non-BEV group (30% [IQR, -17% to 98%], P = .001; and 10% [IQR, -13% to 82%], P = .02, respectively) between baseline and first follow-up. None of the assessed MRI parameters were predictive for OS in the BEV group. Conclusion Bevacizumab treatment decreased tumor volumes, angiogenesis, and oxygenation, thereby reflecting its effectiveness for extending progression-free survival; however, these parameters were not predictive of overall survival (OS), which highlighted the challenges of identifying patients that derive an OS benefit from bevacizumab. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Dillon in this issue.
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Affiliation(s)
- Philipp Kickingereder
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Gianluca Brugnara
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Mikkel Bo Hansen
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Martha Nowosielski
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Irada Pflüger
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Marianne Schell
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Fabian Isensee
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Martha Foltyn
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Ulf Neuberger
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Tobias Kessler
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Felix Sahm
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Antje Wick
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Sabine Heiland
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Michael Weller
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Michael Platten
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Andreas von Deimling
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Klaus H Maier-Hein
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Leif Østergaard
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Martin J van den Bent
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Thierry Gorlia
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Wolfgang Wick
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Martin Bendszus
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
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Incekara F, Smits M, van der Voort SR, Dubbink HJ, Atmodimedjo PN, Kros JM, Vincent AJPE, van den Bent M. The Association Between the Extent of Glioblastoma Resection and Survival in Light of MGMT Promoter Methylation in 326 Patients With Newly Diagnosed IDH-Wildtype Glioblastoma. Front Oncol 2020; 10:1087. [PMID: 32766140 PMCID: PMC7381265 DOI: 10.3389/fonc.2020.01087] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Accepted: 06/01/2020] [Indexed: 12/14/2022] Open
Abstract
Background: The association between contrast enhanced (CE) and non-contrast enhanced (NCE) tumor resection and survival in patients with glioblastoma in relation to molecular subtypes is poorly understood. The aim of this study was to assess the association between CE and NCE tumor resection and survival in light of MGMT promoter methylation in newly diagnosed IDH-wildtype glioblastoma. Materials and methods: Patients with newly diagnosed IDH-wildtype glioblastoma who underwent surgery were eligible. CE and NCE tumor volumes were assessed on pre- and post-operative MRI scans and extent of resection was calculated. The association between CE and NCE tumor resection and survival was evaluated using multivariable Cox proportional hazards models and Kaplan Meier estimates. Results: Three hundred and twenty-six patients were included: 177 (54.3%) with and 149 (45.7%) without MGMT methylation. Multivariable Cox proportional hazards models stratified for MGMT methylation identified age ≤ 65y (HR 0.63; 95% CI, 0.49–0.81; p < 0.0001), chemoradiation (HR 0.13; 95% CI, 0.09–0.19; p < 0.0001), maximal CE tumor resection (HR 0.58; 95% CI, 0.39–0.87; p = 0.009), ≥ 30% NCE tumor resection (HR 0.71; 95% CI, 0.53–0.93; p = 0.014), and minimal residual CE tumor volume (HR 0.64; 95% CI, 0.46–0.88 p = 0.007) as being associated with longer overall survival. Kaplan Meier estimates showed that extensive surgery was more beneficial for patients with MGMT methylated glioblastoma. Conclusions: This study shows an association between maximal CE tumor resection, ≥30% NCE tumor resection, minimal residual CE tumor volume, and longer overall survival in patients with newly diagnosed IDH wildtype glioblastoma. Intraoperative imaging and stimulation mapping may be used to pursue safe and maximal resection. In future research, the safety aspect of maximizing tumor resection needs to be addressed.
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Affiliation(s)
- Fatih Incekara
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC-University Medical Center Rotterdam, Rotterdam, Netherlands.,Department of Radiology and Nuclear Medicine, Erasmus MC-University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC-University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Sebastian R van der Voort
- Department of Radiology and Nuclear Medicine, Erasmus MC-University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Hendrik Jan Dubbink
- Department of Pathology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Peggy N Atmodimedjo
- Department of Pathology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Johan M Kros
- Department of Pathology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Arnaud J P E Vincent
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC-University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Martin van den Bent
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
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De Barros A, Attal J, Roques M, Nicolau J, Sol JC, Charni S, Cohen-Jonathan-Moyal E, Roux FE. Glioblastoma survival is better analyzed on preradiotherapy MRI than on postoperative MRI residual volumes: A retrospective observational study. Clin Neurol Neurosurg 2020; 196:105972. [PMID: 32512407 DOI: 10.1016/j.clineuro.2020.105972] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 04/09/2020] [Accepted: 05/26/2020] [Indexed: 11/18/2022]
Abstract
OBJECTIVES Establishing an overall survival prognosis for resected glioblastoma during routine postoperative management remains a challenge. The aim of our single-center study was to assess the usefulness of basing survival analyses on preradiotherapy MRI (PRMR) rather than on postoperative MRI (POMR). PATIENTS AND METHODS A retrospective review was undertaken of 75 patients with glioblastoma treated at our institute. We collected overall survival and MRI volumetric data. We analyzed two types of volumetric data: residual tumor volume and extent of resection. Overall survival rates were compared according to these two types of volumetric data, calculated on either POMR or PRMR and according to the presence or absence of residual enhancement. RESULTS Analysis of volumetric data revealed progression of some residual tumors between POMR and PRMR. Kaplan-Meier analysis of the correlations between extent of resection, residual tumor volume, and overall survival revealed significant differences between POMR and PRMR data. Both MRI scans indicated a difference between the complete resection subgroup and the incomplete resection subgroup, as median overall survival was longer in patients with complete resection. However, differences were significant for PRMR (25.3 vs. 15.5, p = 0.012), but not for POMR (21.3 vs. 15.8 months, p = 0.145). With a residual tumor volume cut-off value of 3 cm3, Kaplan-Meier survival analysis revealed non-significant differences on POMR (p = 0.323) compared with PRMR (p = 0.007). CONCLUSION Survival in patients with resected glioblastoma was more accurately predicted by volumetric data acquired with PRMR. Differences in predicted survival between the POMR and PRMR groups can be attributed to changes in tumor behavior before adjuvant therapy.
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Affiliation(s)
- Amaury De Barros
- Pôle Neuroscience (Neurochirurgie), Toulouse University Hospital, Toulouse, France; Université Paul Sabatier, Toulouse III, 118 route de Narbonne, Toulouse, 31062, France.
| | - Justine Attal
- Université Paul Sabatier, Toulouse III, 118 route de Narbonne, Toulouse, 31062, France; Department of Radiation Oncology, Institut Universitaire du Cancer de Toulouse-Oncopôle, 1 Avenue Irène Joliot-Curie, 31059, Toulouse, France
| | - Margaux Roques
- Université Paul Sabatier, Toulouse III, 118 route de Narbonne, Toulouse, 31062, France; Neuroradiology Department, Toulouse University Hospital, Toulouse, France
| | - Julien Nicolau
- Pôle Neuroscience (Neurochirurgie), Toulouse University Hospital, Toulouse, France; Université Paul Sabatier, Toulouse III, 118 route de Narbonne, Toulouse, 31062, France
| | - Jean-Christophe Sol
- Pôle Neuroscience (Neurochirurgie), Toulouse University Hospital, Toulouse, France; Université Paul Sabatier, Toulouse III, 118 route de Narbonne, Toulouse, 31062, France
| | - Saloua Charni
- Université Paul Sabatier, Toulouse III, 118 route de Narbonne, Toulouse, 31062, France; CNRS UMR5549 Brain and Cognition (Cerco), Hôpital Purpan, Toulouse, France
| | - Elizabeth Cohen-Jonathan-Moyal
- Université Paul Sabatier, Toulouse III, 118 route de Narbonne, Toulouse, 31062, France; Department of Radiation Oncology, Institut Universitaire du Cancer de Toulouse-Oncopôle, 1 Avenue Irène Joliot-Curie, 31059, Toulouse, France; INSERM U1037, Centre de Recherche contre le Cancer de Toulouse, 1 avenue Irène Joliot-Curie, Toulouse Cedex, 31059, France
| | - Franck-Emmanuel Roux
- Pôle Neuroscience (Neurochirurgie), Toulouse University Hospital, Toulouse, France; Université Paul Sabatier, Toulouse III, 118 route de Narbonne, Toulouse, 31062, France; CNRS UMR5549 Brain and Cognition (Cerco), Hôpital Purpan, Toulouse, France
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Brenner AJ, Peters KB, Vredenburgh J, Bokstein F, Blumenthal DT, Yust-Katz S, Peretz I, Oberman B, Freedman LS, Ellingson BM, Cloughesy TF, Sher N, Cohen YC, Lowenton-Spier N, Rachmilewitz Minei T, Yakov N, Mendel I, Breitbart E, Wen PY. Safety and efficacy of VB-111, an anticancer gene therapy, in patients with recurrent glioblastoma: results of a phase I/II study. Neuro Oncol 2020; 22:694-704. [PMID: 31844886 PMCID: PMC7229257 DOI: 10.1093/neuonc/noz231] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND VB-111 is a non-replicating adenovirus carrying a Fas-chimera transgene, leading to targeted apoptosis of tumor vascular endothelium and induction of a tumor-specific immune response. This phase I/II study evaluated the safety, tolerability, and efficacy of VB-111 with and without bevacizumab in recurrent glioblastoma (rGBM). METHODS Patients with rGBM (n = 72) received VB-111 in 4 treatment groups: subtherapeutic (VB-111 dose escalation), limited exposure (LE; VB-111 monotherapy until progression), primed combination (VB-111 monotherapy continued upon progression with combination of bevacizumab), and unprimed combination (upfront combination of VB-111 and bevacizumab). The primary endpoint was median overall survival (OS). Secondary endpoints were safety, overall response rate, and progression-free survival (PFS). RESULTS VB-111 was well tolerated. The most common adverse event was transient mild-moderate fever. Median OS time was significantly longer in the primed combination group compared with both LE (414 vs 223 days; hazard ratio [HR], 0.48; P = 0.043) and unprimed combination (414 vs 141.5 days; HR, 0.24; P = 0.0056). Patients in the combination phase of the primed combination group had a median PFS time of 90 days compared with 60 in the LE group (HR, 0.36; P = 0.032), and 63 in the unprimed combination group (P = 0.72). Radiographic responders to VB-111 exhibited characteristic, expansive areas of necrosis in the areas of initial enhancing disease. CONCLUSIONS Patients with rGBM who were primed with VB-111 monotherapy that continued after progression with the addition of bevacizumab showed significant survival and PFS advantage, as well as specific imaging characteristics related to VB-111 mechanism of action. These results warrant further assessment in a randomized controlled study.
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Affiliation(s)
- Andrew J Brenner
- University of Texas Health San Antonio Mays Cancer Center, San Antonio, Texas, USA
| | - Katherine B Peters
- Preston Robert Tisch Brain Tumor Center, Duke University Medical Center, Durham, North Carolina, USA
| | - James Vredenburgh
- Saint Francis Hospital and Medical Center, Hartford, Connecticut, USA
| | - Felix Bokstein
- Tel Aviv Sourasky Medical Center and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Deborah T Blumenthal
- Tel Aviv Sourasky Medical Center and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Shlomit Yust-Katz
- Neuro-Oncology Unit, Davidoff Cancer Center at Rabin Medical Center, Petach Tikvah, Israel and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Idit Peretz
- Neuro-Oncology Unit, Davidoff Cancer Center at Rabin Medical Center, Petach Tikvah, Israel and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Bernice Oberman
- Biostatistics and Biomathematics Unit, Gertner Institute for Epidemiology and Health Policy Research, Chaim Sheba Medical Center, Tel Hashomer, Israel
| | - Laurence S Freedman
- Biostatistics and Biomathematics Unit, Gertner Institute for Epidemiology and Health Policy Research, Chaim Sheba Medical Center, Tel Hashomer, Israel
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Timothy F Cloughesy
- Department of Neurology, Ronald Reagan UCLA Medical Center, University of California Los Angeles, Los Angeles, California, USA
| | | | | | | | | | | | | | | | - Patrick Y Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
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49
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Jovčevska I. Next Generation Sequencing and Machine Learning Technologies Are Painting the Epigenetic Portrait of Glioblastoma. Front Oncol 2020; 10:798. [PMID: 32500035 PMCID: PMC7243123 DOI: 10.3389/fonc.2020.00798] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2019] [Accepted: 04/23/2020] [Indexed: 12/31/2022] Open
Abstract
Even with a rare occurrence of only 1.35% of cancer cases in the United States of America, brain tumors are considered as one of the most lethal malignancies. The most aggressive and invasive type of brain tumor, glioblastoma, accounts for 60–70% of all gliomas and presents with life expectancy of only 12–18 months. Despite trimodal treatment and advances in diagnostic and therapeutic methods, there are no significant changes in patient outcome. Our understanding of glioblastoma was significantly improved with the introduction of next generation sequencing technologies. This led to the identification of different genetic and molecular subtypes, which greatly improve glioblastoma diagnosis. Still, because of the poor life expectancy, novel diagnostic, and treatment methods are broadly explored. Epigenetic modifications like methylation and changes in histone acetylation are such examples. Recently, in addition to genetic and molecular characteristics, epigenetic profiling of glioblastomas is also used for sample classification. Further advancement of next generation sequencing technologies is expected to identify in detail the epigenetic signature of glioblastoma that can open up new therapeutic opportunities for glioblastoma patients. This should be complemented with the use of computational power i.e., machine and deep learning algorithms for objective diagnostics and design of individualized therapies. Using a combination of phenotypic, genotypic, and epigenetic parameters in glioblastoma diagnostics will bring us closer to precision medicine where therapies will be tailored to suit the genetic profile and epigenetic signature of the tumor, which will grant longer life expectancy and better quality of life. Still, a number of obstacles including potential bias, availability of data for minorities in heterogeneous populations, data protection, and validation and independent testing of the learning algorithms have to be overcome on the way.
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Affiliation(s)
- Ivana Jovčevska
- Medical Centre for Molecular Biology, Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
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50
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Henderson F, Brem S. Commentary: The Role of Laser Interstitial Thermal Therapy in Surgical Neuro-Oncology: Series of 100 Consecutive Patients. Neurosurgery 2019; 87:E101-E103. [DOI: 10.1093/neuros/nyz528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Accepted: 10/04/2019] [Indexed: 11/12/2022] Open
Affiliation(s)
- Fraser Henderson
- Department of Neurological Surgery, Medical University of South Carolina, Charleston, South Carolina
- Department of Neurosurgery, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Steven Brem
- Department of Neurosurgery, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania
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