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Lazaridis L, Moenninghoff C, Bumes E, Spille DC, Müther M, Schulz T, Heider S, Agkatsev S, Schmidt T, Blau T, Oster C, Stummer W, Kessler AF, Seidel C, Grauer O, Hau P, Ahmadipour Y, Sure U, Keyvani K, Herrlinger U, Kleinschnitz C, Stuschke M, Guberina N, Herrmann K, Deuschl C, Scheffler B, Kebir S, Glas M. Temporal Muscle Thickness as a Prognostic Marker in a Real-Life Cohort of Newly Diagnosed MGMT Promoter Methylated Glioblastoma: A Multicentric Imaging Analysis. Cancer Med 2025; 14:e70689. [PMID: 40260649 PMCID: PMC12012565 DOI: 10.1002/cam4.70689] [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: 05/22/2024] [Revised: 12/02/2024] [Accepted: 02/04/2025] [Indexed: 04/23/2025] Open
Abstract
INTRODUCTION Prior research has identified temporal muscle thickness (TMT) as a prognostic marker in glioblastoma. Nonetheless, implementation in daily clinical practice is complicated due to the heterogeneity of previous studies. We performed a multicentric analysis aiming to validate recently proposed sex-specific cutoff values using a homogeneous cohort of newly diagnosed MGMT promoter methylated glioblastoma patients; we included a balanced control cohort for comparison. MATERIALS AND METHODS TMT was measured at baseline using the initial preoperative/postoperative magnetic resonance images (MRIs) and in disease course using the first MRI after radiotherapy. Patients were divided by sex and TMT into "at risk of sarcopenia" or "normal muscle status." Kaplan-Meier and multivariable Cox regression analysis was used for survival correlation. RESULTS In total, n = 126 patients were included (n = 66 treated with CCNU/temozolomide, n = 60 with single-drug temozolomide). Patients with normal muscle mass at baseline had significantly prolonged survival (median overall survival: 44.2 months versus 16.7 months with CCNU/temozolomide, and 29.5 months versus 17.4 months with single-drug temozolomide) compared to those at risk of sarcopenia. In a multivariable Cox regression analysis, normal muscle mass and an initial age at diagnosis of < 50 years emerged as significant prognostic markers. Longitudinally, survival was longest in patients with lack of TMT decline over the disease course. DISCUSSION This analysis confirms TMT as an important prognostic marker in glioblastoma in two real-life cohorts. However, in order to establish TMT assessment as a routine marker for patient selection and therapeutic measures, further validation in prospective controlled trials is necessary.
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Affiliation(s)
- Lazaros Lazaridis
- Department of Neurology and Center for Translational Neuro‐ and Behavioral Sciences (C‐TNBS), Division of Clinical Neurooncology, University Medicine EssenUniversity Duisburg‐EssenEssenGermany
- German Cancer Consortium (DKTK)Partner Site University Medicine EssenEssenGermany
- Department of Neurology, University Hospital Knappschaftskrankenhaus BochumRuhr University BochumBochumGermany
| | - Christoph Moenninghoff
- University Institute for Radiology, Neuroradiology and Nuclear MedicineJohannes Wesling Klinikum MindenMindenGermany
| | - Elisabeth Bumes
- Department of Neurology and Wilhelm Sander‐NeuroOncology UnitUniversity Hospital RegensburgRegensburgGermany
| | | | - Michael Müther
- Department of NeurosurgeryUniversity Hospital MünsterMünsterGermany
| | - Tim Schulz
- Department of NeurosurgeryUniversity Hospital of WürzburgWürzburgGermany
| | - Sina Heider
- Department of Radiotherapy and Radiation OncologyUniversity Hospital LeipzigLeipzigGermany
| | - Sarina Agkatsev
- Department of Neurology and Center for Translational Neuro‐ and Behavioral Sciences (C‐TNBS), Division of Clinical Neurooncology, University Medicine EssenUniversity Duisburg‐EssenEssenGermany
- German Cancer Consortium (DKTK)Partner Site University Medicine EssenEssenGermany
- Department of Neurology, University Hospital Knappschaftskrankenhaus BochumRuhr University BochumBochumGermany
| | - Teresa Schmidt
- Department of Neurology and Center for Translational Neuro‐ and Behavioral Sciences (C‐TNBS), Division of Clinical Neurooncology, University Medicine EssenUniversity Duisburg‐EssenEssenGermany
- German Cancer Consortium (DKTK)Partner Site University Medicine EssenEssenGermany
| | - Tobias Blau
- German Cancer Consortium (DKTK)Partner Site University Medicine EssenEssenGermany
- Institute of Neuropathology, University Medicine EssenUniversity Duisburg‐EssenEssenGermany
- DKFZ Division Translational Neurooncology at the WTZ and German Cancer Consortium (DKTK)Partner site Essen/Düsseldorf, a partnership between DKFZ and University Hospital EssenGermany
| | - Christoph Oster
- Department of Neurology and Center for Translational Neuro‐ and Behavioral Sciences (C‐TNBS), Division of Clinical Neurooncology, University Medicine EssenUniversity Duisburg‐EssenEssenGermany
- German Cancer Consortium (DKTK)Partner Site University Medicine EssenEssenGermany
- DKFZ Division Translational Neurooncology at the WTZ and German Cancer Consortium (DKTK)Partner site Essen/Düsseldorf, a partnership between DKFZ and University Hospital EssenGermany
| | - Walter Stummer
- Department of NeurosurgeryUniversity Hospital MünsterMünsterGermany
| | | | - Clemens Seidel
- Department of Radiotherapy and Radiation OncologyUniversity Hospital LeipzigLeipzigGermany
| | - Oliver Grauer
- Department of Neurology with Institute of Translational NeurologyMünsterGermany
| | - Peter Hau
- Department of Neurology and Wilhelm Sander‐NeuroOncology UnitUniversity Hospital RegensburgRegensburgGermany
| | - Yahya Ahmadipour
- German Cancer Consortium (DKTK)Partner Site University Medicine EssenEssenGermany
- Department of Neurosurgery and Spine SurgeryUniversity Medicine Essen, University Duisburg‐EssenEssenGermany
| | - Ulrich Sure
- German Cancer Consortium (DKTK)Partner Site University Medicine EssenEssenGermany
- Department of Neurosurgery and Spine SurgeryUniversity Medicine Essen, University Duisburg‐EssenEssenGermany
| | - Kathy Keyvani
- German Cancer Consortium (DKTK)Partner Site University Medicine EssenEssenGermany
- Institute of Neuropathology, University Medicine EssenUniversity Duisburg‐EssenEssenGermany
| | - Ulrich Herrlinger
- Division of Clinical Neurooncology, Department of Neurology and Center for Integrated OncologyUniversity Hospital BonnBonnGermany
| | - Christoph Kleinschnitz
- Department of Neurology and Center for Translational Neuro‐ and Behavioral Sciences (C‐TNBS), Division of Clinical Neurooncology, University Medicine EssenUniversity Duisburg‐EssenEssenGermany
- German Cancer Consortium (DKTK)Partner Site University Medicine EssenEssenGermany
| | - Martin Stuschke
- German Cancer Consortium (DKTK)Partner Site University Medicine EssenEssenGermany
- Department of RadiotherapyUniversity Medicine EssenEssenGermany
| | - Nika Guberina
- German Cancer Consortium (DKTK)Partner Site University Medicine EssenEssenGermany
- Department of RadiotherapyUniversity Medicine EssenEssenGermany
| | - Ken Herrmann
- German Cancer Consortium (DKTK)Partner Site University Medicine EssenEssenGermany
- Department of Nuclear Medicine, University Medicine EssenUniversity Duisburg‐EssenEssenGermany
| | - Cornelius Deuschl
- German Cancer Consortium (DKTK)Partner Site University Medicine EssenEssenGermany
- Institute for Diagnostic and Interventional Radiology and Neuroradiology, University Medicine EssenUniversity Duisburg‐EssenEssenGermany
| | - Björn Scheffler
- DKFZ Division Translational Neurooncology at the WTZ and German Cancer Consortium (DKTK)Partner site Essen/Düsseldorf, a partnership between DKFZ and University Hospital EssenGermany
| | - Sied Kebir
- Department of Neurology and Center for Translational Neuro‐ and Behavioral Sciences (C‐TNBS), Division of Clinical Neurooncology, University Medicine EssenUniversity Duisburg‐EssenEssenGermany
- German Cancer Consortium (DKTK)Partner Site University Medicine EssenEssenGermany
- DKFZ Division Translational Neurooncology at the WTZ and German Cancer Consortium (DKTK)Partner site Essen/Düsseldorf, a partnership between DKFZ and University Hospital EssenGermany
| | - Martin Glas
- Department of Neurology and Center for Translational Neuro‐ and Behavioral Sciences (C‐TNBS), Division of Clinical Neurooncology, University Medicine EssenUniversity Duisburg‐EssenEssenGermany
- German Cancer Consortium (DKTK)Partner Site University Medicine EssenEssenGermany
- DKFZ Division Translational Neurooncology at the WTZ and German Cancer Consortium (DKTK)Partner site Essen/Düsseldorf, a partnership between DKFZ and University Hospital EssenGermany
- Division of Clinical Neurooncology, Department of Neurology and Center for Integrated OncologyUniversity Hospital BonnBonnGermany
- Department of Neurology and NeurooncologySt. Marien Hospital LünenLünenGermany
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2
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Imani M, Borda MG, Vogrin S, Meijering E, Aarsland D, Duque G. Using Deep Learning to Perform Automatic Quantitative Measurement of Masseter and Tongue Muscles in Persons With Dementia: Cross-Sectional Study. JMIR Aging 2025; 8:e63686. [PMID: 40106819 PMCID: PMC11999904 DOI: 10.2196/63686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2024] [Revised: 12/17/2024] [Accepted: 01/02/2025] [Indexed: 03/22/2025] Open
Abstract
Background Sarcopenia (loss of muscle mass and strength) increases adverse outcomes risk and contributes to cognitive decline in older adults. Accurate methods to quantify muscle mass and predict adverse outcomes, particularly in older persons with dementia, are still lacking. Objective This study's main objective was to assess the feasibility of using deep learning techniques for segmentation and quantification of musculoskeletal tissues in magnetic resonance imaging (MRI) scans of the head in patients with neurocognitive disorders. This study aimed to pave the way for using automated techniques for opportunistic detection of sarcopenia in patients with neurocognitive disorder. Methods In a cross-sectional analysis of 53 participants, we used 7 U-Net-like deep learning models to segment 5 different tissues in head MRI images and used the Dice similarity coefficient and average symmetric surface distance as main assessment techniques to compare results. We also analyzed the relationship between BMI and muscle and fat volumes. Results Our framework accurately quantified masseter and subcutaneous fat on the left and right sides of the head and tongue muscle (mean Dice similarity coefficient 92.4%). A significant correlation exists between the area and volume of tongue muscle, left masseter muscle, and BMI. Conclusions Our study demonstrates the successful application of a deep learning model to quantify muscle volumes in head MRI in patients with neurocognitive disorders. This is a promising first step toward clinically applicable artificial intelligence and deep learning methods for estimating masseter and tongue muscle and predicting adverse outcomes in this population.
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Affiliation(s)
- Mahdi Imani
- Department of Medicine, Melbourne Medical School, University of Melbourne, St. Albans, Australia
| | - Miguel G Borda
- Centre for Age-Related Medicine (SESAM), Stavanger University Hospital, Stavanger, Norway
- Department of Neurology, Clínica Universidad de Navarra, Pamplona, Spain
| | - Sara Vogrin
- Department of Medicine, Melbourne Medical School, University of Melbourne, St. Albans, Australia
| | - Erik Meijering
- School of Computer Science and Engineering, UNSW Sydney, Sydney, Australia
| | - Dag Aarsland
- Centre for Age-Related Medicine (SESAM), Stavanger University Hospital, Stavanger, Norway
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, United Kingdom
| | - Gustavo Duque
- Bone, Muscle & Geroscience Group, Research Institute of the McGill University Health Centre, McGill University, 1001 Decarie Blvd, Room EM1.3226, Montreal, QC, H4A 3J1, Canada, 1 514 934 1934
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Gendreau J, Mehkri Y, Kuo C, Chakravarti S, Jimenez MA, Shalom M, Kazemi F, Mukherjee D. Clinical Predictors of Overall Survival in Very Elderly Patients With Glioblastoma: A National Cancer Database Multivariable Analysis. Neurosurgery 2025; 96:373-385. [PMID: 38940573 DOI: 10.1227/neu.0000000000003072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Accepted: 05/08/2024] [Indexed: 06/29/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Surgery for the very elderly is a progressively important paradigm as life expectancy continues to rise. Patients with glioblastoma multiforme often undergo surgery, radiotherapy (RT), and chemotherapy (CT) to prolong overall survival (OS). However, the efficacy of these treatment modalities in patients aged 80 years and older has yet to be fully assessed in the literature. METHODS The National Cancer Database was used to retrospectively identify patients aged 65 years and older with glioblastoma multiforme (1989-2016). All available patient demographic characteristics, disease characteristics, and clinical outcomes were collected. To study OS, bivariable survival models were created using Kaplan-Meier estimates. A Cox proportional-hazards model was used for final adjusted analyses. RESULTS A total of 578 very elderly patients (aged 80 years and older) and 2836 elderly patients (aged 65-79 years) were identified. Compared with elderly patients, very elderly patients were more likely to have Medicare (odds ratio [OR] 1.899 [95% CI: 1.417-2.544], P < .001) while less likely to have private insurance status (OR 0.544 [95% CI: 0.401-0.739], P < .001). In addition, very elderly patients were more likely to travel the least distance for treatment and have multiple tumors ( P < .001). When controlling for demographic and disease characteristics, very elderly patients were less likely to receive gross total resection (GTR) (OR 0.822 [95% CI: 0.681-0.991], P < .041), RT (OR 0.385 [95% CI: 0.319-0.466], P < .001), or postoperative CT (OR 0.298 [95% CI: 0.219-0.359], P < .001) relative to elderly counterparts. Within very elderly patients, GTR, RT, and CT all independently and significantly predicted improved OS ( P < .001 for all). These predictive models were deployed in an online calculator ( https://spine.shinyapps.io/GBM_elderly ). CONCLUSION Very elderly patients are less likely to receive GTR, RT, or CT when compared with elderly counterparts despite use of these therapies conferring improved OS. Selected very elderly patients may benefit from more aggressive attempts at surgical and adjuvant treatment.
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Affiliation(s)
- Julian Gendreau
- Department of Neurological Surgery, Johns Hopkins University School of Medicine, Baltimore , Maryland , USA
| | - Yusuf Mehkri
- Department of Neurological Surgery, University of Florida School of Medicine, Gainesville , Florida , USA
| | - Cathleen Kuo
- Department of Neurological Surgery, University of Buffalo Jacobs School of Medicine, Buffalo , New York , USA
| | - Sachiv Chakravarti
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston , Massachusetts , USA
| | - Miguel Angel Jimenez
- Department of Neurological Surgery, University of Chicago Pritzker School of Medicine, Chicago , Illinois , USA
| | - Moshe Shalom
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv , Israel
| | - Foad Kazemi
- Department of Neurological Surgery, Johns Hopkins University School of Medicine, Baltimore , Maryland , USA
| | - Debraj Mukherjee
- Department of Neurological Surgery, Johns Hopkins University School of Medicine, Baltimore , Maryland , USA
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Rahmani F, Camps G, Mironchuk O, Atagu N, Ballard DH, Benzinger TLS, Chow VTY, Dahiya S, Evans J, Jaswal S, Hosseinzadeh Kassani S, Ma D, Naeem M, Popuri K, Raji CA, Siegel MJ, Xu Y, Liu J, Beg MF, Chicoine MR, Ippolito JE. Abdominal myosteatosis measured with computed tomography predicts poor outcomes in patients with glioblastoma. Neurooncol Adv 2025; 7:vdae209. [PMID: 39791017 PMCID: PMC11713020 DOI: 10.1093/noajnl/vdae209] [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: 01/12/2025] Open
Abstract
Background Alterations in cellular metabolism affect cancer survival and can manifest in metrics of body composition. We investigated the effects of various body composition metrics on survival in patients with glioblastoma (GBM). Methods We retrospectively analyzed patients who had an abdominal and pelvic computed tomography (CT) scan performed within 1 month of diagnosis of GBM (178 participants, 102 males, 76 females, median age: 62.1 years). Volumetric body composition metrics were derived using automated CT segmentation of adipose tissue, skeletal muscle, and aortic calcification from L1 to L5. Univariable and multivariable Cox proportional hazards models were performed separately in males and females using known predictors of GBM overall survival (OS) as covariates. A sex-specific composite score of predisposing and protective factors was constructed using the relative importance of each metric in GBM OS. Results Higher skeletal muscle volume and lower skeletal muscle fat fraction were associated with better OS in the entire dataset. A robust and independent effect on GBM OS was seen specifically for fraction of inter/intramuscular adipose tissue to total adipose tissue after correction for known survival predictors and comorbidities. Worse OS was observed with increased abdominal aortic calcification volume in both sexes. There was a significant difference in GBM OS among participants stratified into quartiles based on sex-specific composite predisposing and protective scores. Conclusion The relationship between body composition and GBM OS provides an actionable advancement toward precision medicine in GBM management, as lifestyle and dietary regimens can alter body composition and metabolism and from there GBM survival.
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Affiliation(s)
- Farzaneh Rahmani
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in Saint Louis, St. Louis, Missouri, USA
| | - Garrett Camps
- Graduate Medical Education, St. Joseph’s Medical Center, Stockton, California, USA
| | - Olesya Mironchuk
- University of Washington School of Medicine, Seattle, Washington, USA
| | - Norman Atagu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - David H Ballard
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in Saint Louis, St. Louis, Missouri, USA
| | - Tammie L S Benzinger
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in Saint Louis, St. Louis, Missouri, USA
| | - Vincent Tze Yang Chow
- School of Engineering Science, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Sonika Dahiya
- Department of Pathology, Washington University School of Medicine, Saint Louis, Missouri, USA
| | - John Evans
- Department of Neurosurgery, Washington University School of Medicine, Saint Louis, Missouri, USA
| | - Shama Jaswal
- Department of Radiology, Weill Cornell Medical Center/New York Presbyterian Hospital, New York City, New York, USA
| | - Sara Hosseinzadeh Kassani
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in Saint Louis, St. Louis, Missouri, USA
| | - Da Ma
- Department of Internal Medicine, Section of Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Muhammad Naeem
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Karteek Popuri
- Department of Computer Science, Memorial University of Newfoundland, St. John’s, Newfoundland and Labrador, Canada
| | - Cyrus A Raji
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in Saint Louis, St. Louis, Missouri, USA
| | - Marilyn J Siegel
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in Saint Louis, St. Louis, Missouri, USA
| | - Yifei Xu
- Department of Surgery, Washington University School of Medicine, Saint Louis, Missouri, USA
| | - Jingxia Liu
- Department of Surgery, Washington University School of Medicine, Saint Louis, Missouri, USA
| | - Mirza Faisal Beg
- School of Engineering Science, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Michael R Chicoine
- Department of Neurosurgery, University of Missouri, Columbia, Missouri, USA
| | - Joseph E Ippolito
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, Saint Louis, Missouri, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in Saint Louis, St. Louis, Missouri, USA
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Horowitz MA, Ghadiyaram A, Mehkri Y, Chakravarti S, Liu J, Fox K, Gendreau J, Mukherjee D. Surgical resection of glioblastoma in the very elderly: An analysis of survival outcomes using the surveillance, epidemiology, and end results database. Clin Neurol Neurosurg 2024; 245:108469. [PMID: 39079287 DOI: 10.1016/j.clineuro.2024.108469] [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: 07/20/2024] [Accepted: 07/25/2024] [Indexed: 09/10/2024]
Abstract
OBJECTIVE Patients with glioblastoma (GBM) often undergo surgery to prolong survival. However, the use of surgery, and more specifically achieving gross total resection (GTR), in patients >80 years old has yet to be fully assessed. Using the Surveillance, Epidemiology, and End Results (SEER) database, we aim to assess the efficacy of surgical resection, radiotherapy (RT) and chemotherapy (CT) on overall survival (OS) in very elderly GBM patients compared to elderly counterparts (age 65-79 years). METHODS The SEER database was queried for all patients >65 years old with GBM (2000-2020). Patients not undergoing surgery or biopsy were excluded. Patients were stratified by age, and demographic relationships were assessed with chi-squared testing for categorical variables. Bivariable models were created using Kaplan-Meier survival estimates. All significant variables from bivariable analysis were included on multivariable Cox survival regression models to determine independent associations between clinical variables and OS. RESULTS A total of 27,090 operative GBM patients were identified; 1868 patients (15.92 %) were very elderly and 10,092 patients (84.38 %) were elderly. Very elderly patients were less likely to undergo GTR (28 % vs 35 %, p<0.001), RT (59 % vs 78 %, p<0.001) and CT (40 % vs 66 %, p<0.001). In multivariable Cox regression analysis, very elderly patients who achieved GTR (HR=.696, p<0.001), received RT (HR=0.583, p<0.001) and underwent CT (HR=0.4197, p<0.001) had significantly improved OS compared to very elderly patients that did not undergo these treatment options. CONCLUSION Currently, very elderly GBM patients undergo lower rates of aggressive surgery, RT and CT. However, very elderly patients that undergo surgery, RT and CT may have a survival advantage. These treatments should be considered as potential options for this patient population.
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Affiliation(s)
| | - Ashwin Ghadiyaram
- Department of Neurological Surgery, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
| | - Yusuf Mehkri
- Department of Neurological Surgery, University of Florida College of Medicine, Gainesville, FL, USA
| | | | - Jiaqi Liu
- Department of Neurological Surgery, Georgetown University School of Medicine, Washington, DC, USA
| | - Keiko Fox
- Department of Neurological Surgery, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Julian Gendreau
- Department of Neurological Surgery, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Debraj Mukherjee
- Department of Neurological Surgery, Johns Hopkins School of Medicine, Baltimore, MD, USA.
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Korhonen TK, Arponen O, Steinruecke M, Pecorella I, Mee H, Yordanov S, Viaroli E, Guilfoyle MR, Kolias A, Timofeev I, Hutchinson P, Helmy A. Reduced temporal muscle thickness predicts shorter survival in patients undergoing chronic subdural haematoma drainage. J Cachexia Sarcopenia Muscle 2024; 15:1441-1450. [PMID: 38720242 PMCID: PMC11294050 DOI: 10.1002/jcsm.13489] [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: 10/02/2023] [Revised: 03/15/2024] [Accepted: 03/26/2024] [Indexed: 08/03/2024] Open
Abstract
BACKGROUND Chronic subdural haematoma (CSDH) drainage is a common neurosurgical procedure. CSDHs cause excess mortality, which is exacerbated by frailty. Sarcopenia contributes to frailty - its key component, low muscle mass, can be assessed using cross-sectional imaging. We aimed to examine the prognostic role of temporal muscle thickness (TMT) measured from preoperative computed tomography head scans among patients undergoing surgical CSDH drainage. METHODS We retrospectively identified all patients who underwent CSDH drainage within 1 year of February 2019. We measured their mean TMT from preoperative computed tomography scans, tested the reliability of these measurements, and evaluated their prognostic value for postoperative survival. RESULTS One hundred and eighty-eight (122, 65% males) patients (median age 78 years, IQR 70-85 years) were included. Thirty-four (18%) patients died within 2 years, and 51 (27%) died at a median follow-up of 39 months (IQR 34-42 months). Intra- and inter-observer reliability of TMT measurements was good-to-excellent (ICC 0.85-0.97, P < 0.05). TMT decreased with age (Pearson's r = -0.38, P < 0.001). Females had lower TMT than males (P < 0.001). The optimal TMT cut-off values for predicting two-year survival were 4.475 mm for males and 3.125 mm for females. TMT below these cut-offs was associated with shorter survival in both univariate (HR 3.24, 95% CI 1.85-5.67) and multivariate (HR 1.86, 95% CI 1.02-3.36) analyses adjusted for age, ASA grade and bleed size. The effect of TMT on mortality was not mediated by age. CONCLUSIONS In patients with CSDH, TMT measurements from preoperative imaging were reliable and contained prognostic information supplemental to previously known predictors of poor outcomes.
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Affiliation(s)
- Tommi K. Korhonen
- Division of Neurosurgery, Department of Clinical NeurosciencesCambridge University Hospitals NHS Foundation Trust & University of CambridgeCambridgeUK
- Department of Neurosurgery, Neurocenter OYSOulu University HospitalOuluFinland
- Department of Neurosurgery, Research Unit of Clinical NeurosciencesUniversity of OuluOuluFinland
| | - Otso Arponen
- Department of RadiologyUniversity of CambridgeCambridgeUK
- Faculty of Medicine and Health SciencesTampere UniversityTampereFinland
- Department of RadiologyTampere University HospitalTampereFinland
| | - Moritz Steinruecke
- Division of Neurosurgery, Department of Clinical NeurosciencesCambridge University Hospitals NHS Foundation Trust & University of CambridgeCambridgeUK
| | - Ilaria Pecorella
- Division of Neurosurgery, Department of Clinical NeurosciencesCambridge University Hospitals NHS Foundation Trust & University of CambridgeCambridgeUK
| | - Harry Mee
- Division of Neurosurgery, Department of Clinical NeurosciencesCambridge University Hospitals NHS Foundation Trust & University of CambridgeCambridgeUK
| | - Stefan Yordanov
- Division of Neurosurgery, Department of Clinical NeurosciencesCambridge University Hospitals NHS Foundation Trust & University of CambridgeCambridgeUK
| | - Edoardo Viaroli
- Division of Neurosurgery, Department of Clinical NeurosciencesCambridge University Hospitals NHS Foundation Trust & University of CambridgeCambridgeUK
| | - Mathew R. Guilfoyle
- Division of Neurosurgery, Department of Clinical NeurosciencesCambridge University Hospitals NHS Foundation Trust & University of CambridgeCambridgeUK
| | - Angelos Kolias
- Division of Neurosurgery, Department of Clinical NeurosciencesCambridge University Hospitals NHS Foundation Trust & University of CambridgeCambridgeUK
| | - Ivan Timofeev
- Division of Neurosurgery, Department of Clinical NeurosciencesCambridge University Hospitals NHS Foundation Trust & University of CambridgeCambridgeUK
| | - Peter Hutchinson
- Division of Neurosurgery, Department of Clinical NeurosciencesCambridge University Hospitals NHS Foundation Trust & University of CambridgeCambridgeUK
| | - Adel Helmy
- Division of Neurosurgery, Department of Clinical NeurosciencesCambridge University Hospitals NHS Foundation Trust & University of CambridgeCambridgeUK
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Olukoya O, Osunronbi T, Jesuyajolu DA, Uwaga BC, Vaughan A, Aluko O, Ayantayo TO, Daniel JO, David SO, Jagunmolu HA, Kanu A, Kayode AT, Olajide TN, Thorne L. The prognostic utility of temporalis muscle thickness measured on magnetic resonance scans in patients with intra-axial malignant brain tumours: A systematic review and meta-analysis. World Neurosurg X 2024; 22:100318. [PMID: 38440376 PMCID: PMC10911852 DOI: 10.1016/j.wnsx.2024.100318] [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: 08/25/2023] [Accepted: 02/21/2024] [Indexed: 03/06/2024] Open
Abstract
Introduction Sarcopenia is associated with worsened outcomes in solid cancers. Temporalis muscle thickness (TMT) has emerged as a measure of sarcopenia. Hence, this study aims to evaluate the relationship between TMT and outcome measures in patients with malignant intra-axial neoplasms. Method We searched Medline, Embase, Scopus and Cochrane databases for relevant studies. Event ratios with 95% confidence intervals (CI) were analysed using the RevMan 5.4 software. Where meta-analysis was impossible, vote counting was used to determine the effect of TMT on outcomes. The GRADE framework was used to determine the certainty of the evidence. Results Four outcomes were reported for three conditions across 17 studies involving 4430 patients. Glioblastoma: thicker TMT was protective for overall survival (OS) (HR 0.59; 95% CI 0.46-0.76) (GRADE low), progression free survival (PFS) (HR 0.40; 95% CI 0.26-0.62) (GRADE high), and early discontinuation of treatment (OR 0.408; 95% CI 0.168-0.989) (GRADE high); no association with complications (HR 0.82; 95% CI 0.60-1.10) (GRADE low). Brain Metastases: thicker TMT was protective for OS (HR 0.73; 95% CI 0.67-0.78) (GRADE moderate); no association with PFS (GRADE low). Primary CNS Lymphoma: TMT was protective for overall survival (HR 0.34; 95% CI 0.19-0.60) (GRADE moderate) and progression free survival (HR 0.23; 95% CI 0.09-0.56) (GRADE high). Conclusion TMT has significant prognostic potential in intra-axial malignant neoplasms, showing a moderate to high certainty for its association with outcomes following GRADE evaluation. This will enable shared decision making between patients and clinicians.
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Affiliation(s)
- Olatomiwa Olukoya
- Neurosurgery Department, Surgery Interest Group of Africa, Lagos, Nigeria
- The National Hospital for Neurology and Neurosurgery, London, United Kingdom
| | - Temidayo Osunronbi
- Neurosurgery Department, Surgery Interest Group of Africa, Lagos, Nigeria
- Department of Neurosurgery, Royal Hallamshire Hospital, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, United Kingdom
| | | | - Blossom C. Uwaga
- Neurosurgery Department, Surgery Interest Group of Africa, Lagos, Nigeria
| | - Ayomide Vaughan
- Neurosurgery Department, Surgery Interest Group of Africa, Lagos, Nigeria
| | - Oluwabusayo Aluko
- Neurosurgery Department, Surgery Interest Group of Africa, Lagos, Nigeria
| | | | | | - Samuel O. David
- Neurosurgery Department, Surgery Interest Group of Africa, Lagos, Nigeria
| | | | - Alieu Kanu
- Neurosurgery Department, Surgery Interest Group of Africa, Lagos, Nigeria
| | - Ayomide T. Kayode
- Neurosurgery Department, Surgery Interest Group of Africa, Lagos, Nigeria
| | - Tobi N. Olajide
- Neurosurgery Department, Surgery Interest Group of Africa, Lagos, Nigeria
| | - Lewis Thorne
- The National Hospital for Neurology and Neurosurgery, London, United Kingdom
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8
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Pehlivan UA, Somay E, Yilmaz B, Besen AA, Mertsoylu H, Selek U, Topkan E. Pretreatment Masseter Muscle Volume Predicts Survival in Locally Advanced Nasopharyngeal Carcinoma Patients Treated with Concurrent Chemoradiotherapy. J Clin Med 2023; 12:6863. [PMID: 37959329 PMCID: PMC10648120 DOI: 10.3390/jcm12216863] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 10/24/2023] [Accepted: 10/27/2023] [Indexed: 11/15/2023] Open
Abstract
BACKGROUND AND PURPOSE Muscle loss is a significant indicator of cancer cachexia and is associated with a poor prognosis in cancer patients. Given the absence of comparable studies, the current retrospective study sought to examine the correlation between the total masseter muscle volume (TMMV) before treatment and the survival outcomes in locally advanced nasopharyngeal cancer (LA-NPC) patients who received definitive concurrent chemoradiotherapy (CCRT). METHODS A three-dimensional segmentation model was used to determine the TMMV for each patient by analyzing pre-CCRT magnetic resonance imaging. The optimal TMMV cutoff values were searched using receiver operating characteristic (ROC) curve analyses. The primary and secondary endpoints were the relationship between the pre-CCRT TMMV measures and overall survival (OS) and progression-free survival (PFS), respectively. RESULTS Ninety-seven patients were included in this study. ROC curve analyses revealed 38.0 cc as the optimal TMMV cutoff: ≤38.00 cc (n = 42) and >38.0 cc (n = 55). Comparisons between the two groups showed that the TMMV>38.0 cc group had significantly longer PFS [Not reached (NR) vs. 28; p < 0.01] and OS (NR vs. 71; p < 0.01) times, respectively. The results of the multivariate analysis demonstrated that the T-stage, N-stage, number of concurrent chemotherapy cycles, and TMMV were independent associates of PFS (p < 0.05 for each) and OS (p < 0.05 for each) outcomes, respectively. CONCLUSION The findings of the current retrospective research suggest that pretreatment TMMV is a promising indicator for predicting survival outcomes in LA-NPC patients receiving definitive CCRT.
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Affiliation(s)
- Umur Anil Pehlivan
- Department of Radiology, Adana Dr. Turgut Noyan Application and Research Center, Faculty of Medicine, Baskent University, Adana 01120, Turkey
| | - Efsun Somay
- Department of Oral and Maxillofacial Surgery, Adana Dr. Turgut Noyan Application and Research Center, Faculty of Dentistry, Baskent University, Adana 01120, Turkey;
| | - Busra Yilmaz
- Department of Oral and Maxillofacial Radiology, School of Dental Medicine, Bahcesehir University, Istanbul 34349, Turkey;
| | - Ali Ayberk Besen
- Department of Medical Oncology, Medical Park Seyhan Hospital, Adana 07160, Turkey;
| | - Huseyin Mertsoylu
- Department of Medical Oncology, Medical Park Adana Hospital, Istinye University, Istanbul 34010, Turkey;
| | - Ugur Selek
- Department of Radiation Oncology, Koc University School of Medicine, Istanbul 34010, Turkey;
| | - Erkan Topkan
- Department of Radiation Oncology, Adana Dr. Turgut Noyan Application and Research Center, Faculty of Medicine, Baskent University, Adana 01120, Turkey;
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9
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Tolonen A, Kerminen H, Lehtomäki K, Huhtala H, Bärlund M, Österlund P, Arponen O. Association between Computed Tomography-Determined Loss of Muscle Mass and Impaired Three-Month Survival in Frail Older Adults with Cancer. Cancers (Basel) 2023; 15:3398. [PMID: 37444508 DOI: 10.3390/cancers15133398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 06/06/2023] [Accepted: 06/26/2023] [Indexed: 07/15/2023] Open
Abstract
As patients with solid (non-hematological) cancers and a life expectancy of <3 months rarely benefit from oncological treatment, we examined whether the CT-determined loss of muscle mass is associated with an impaired 3-month overall survival (OS) in frail ≥75-year-old patients with cancer. Frailty was assessed with G8-screening and comprehensive geriatric assessment in older adults at risk of frailty. The L3-level skeletal (SMI) and psoas (PMI) muscle indexes were determined from routine CT scans. Established and optimized SMI and PMI cut-offs were used. In the non-curative treatment group (n = 58), 3-month OS rates for normal and low SMI were 95% and 64% (HR 9.28; 95% CI 1.2-71) and for PMI 88%, and 60%, respectively (HR 4.10; 1.3-13). A Cox multivariable 3-month OS model showed an HR of 10.7 (1.0-110) for low SMI, 2.34 (0.6-9.8) for ECOG performance status 3-4, 2.11 (0.5-8.6) for clinical frailty scale 5-9, and 0.57 (0.1-2.8) for males. The 24-month OS rates in the curative intent group (n = 21) were 91% and 38% for the normal and low SMI groups, respectively. In conclusion, CT-determined low muscle mass is independently associated with an impaired 3-month OS and, alongside geriatric assessment, could aid in oncological versus best supportive care decision-making in frail patients with non-curable cancers.
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Affiliation(s)
- Antti Tolonen
- Department of Radiology, Tampere University Hospital, Kuntokatu 2, 33520 Tampere, Finland
- Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön Katu 34, 33520 Tampere, Finland
| | - Hanna Kerminen
- Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön Katu 34, 33520 Tampere, Finland
- Centre of Geriatrics, Tampere University Hospital, Kuntokatu 2, 33520 Tampere, Finland
- Gerontology Research Center (GEREC), Tampere University, Arvo Ylpön Katu 34, 33520 Tampere, Finland
| | - Kaisa Lehtomäki
- Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön Katu 34, 33520 Tampere, Finland
- Department of Oncology, Tays Cancer Centre, Tampere University Hospital, Teiskontie 35, 33520 Tampere, Finland
| | - Heini Huhtala
- Faculty of Social Sciences, Tampere University, Kalevantie 5, 33014 Tampere, Finland
| | - Maarit Bärlund
- Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön Katu 34, 33520 Tampere, Finland
- Department of Oncology, Tays Cancer Centre, Tampere University Hospital, Teiskontie 35, 33520 Tampere, Finland
| | - Pia Österlund
- Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön Katu 34, 33520 Tampere, Finland
- Department of Oncology, Tays Cancer Centre, Tampere University Hospital, Teiskontie 35, 33520 Tampere, Finland
- Department of Oncology, Comprehensive Cancer Center, Helsinki University Hospital, University of Helsinki, Haartmaninkatu 4, 00290 Helsinki, Finland
- Department of Gastrointestinal Oncology, Tema Cancer, Karolinska Universitetssjukhuset, Eugeniavägen 3, 17176 Solna, Sweden
- Department of Oncology-Pathology, Karolinska Institutet, Solnavägen 1, 17177 Solna, Sweden
| | - Otso Arponen
- Department of Radiology, Tampere University Hospital, Kuntokatu 2, 33520 Tampere, Finland
- Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön Katu 34, 33520 Tampere, Finland
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10
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Yang YW, Zhou YW, Xia X, Jia SL, Zhao YL, Zhou LX, Cao Y, Ge ML. Prognostic value of temporal muscle thickness, a novel radiographic marker of sarcopenia, in patients with brain tumor: A systematic review and meta-analysis. Nutrition 2023; 112:112077. [PMID: 37236042 DOI: 10.1016/j.nut.2023.112077] [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: 02/14/2023] [Revised: 04/24/2023] [Accepted: 05/08/2023] [Indexed: 05/28/2023]
Abstract
Sarcopenia has been identified as a prognostic factor among certain types of cancer. However, it is unclear whether there is prognostic value of temporalis muscle thickness (TMT), a potential surrogate for sarcopenia, in adults patients with brain tumors. Therefore, we searched the Medline, Embase, and PubMed to systematically review and meta-analyze the relationship between TMT and overall survival, progression-free survival, and complications in patients with brain tumors and the hazard ratio (HR) or odds ratios (OR), and 95% confidence interval (CI) were evaluated. The quality in prognostic studies (QUIPS) instrument was employed to evaluate study quality. Nineteen studies involving 4570 patients with brain tumors were included for qualitative and quantitative analysis. Meta-analysis revealed thinner TMT was associated with poor overall survival (HR, 1.72; 95% CI, 1.45-2.04; P < 0.01) in patients with brain tumors. Sub-analyses showed that the association existed for both primary brain tumors (HR, 2.02; 95% CI, 1.55-2.63) and brain metastases (HR, 1.39; 95% CI, 1.30-1.49). Moreover, thinner TMT also was the independent predictor of progression-free survival in patients with primary brain tumors (HR, 2.88; 95% CI, 1.85-4.46; P < 0.01). Therefore, to improve clinical decision making it is important to integrate TMT assessment into routine clinical settings in patients with brain tumors.
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Affiliation(s)
- Yan-Wu Yang
- Emergency Department, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yi-Wu Zhou
- Emergency Department, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xin Xia
- Center of Gerontology and Geriatrics (National Clinical Research Center for Geriatrics), West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Shu-Li Jia
- Center of Gerontology and Geriatrics (National Clinical Research Center for Geriatrics), West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yun-Li Zhao
- Center of Gerontology and Geriatrics (National Clinical Research Center for Geriatrics), West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Li-Xing Zhou
- Center of Gerontology and Geriatrics (National Clinical Research Center for Geriatrics), West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yu Cao
- Emergency Department, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Mei-Ling Ge
- Center of Gerontology and Geriatrics (National Clinical Research Center for Geriatrics), West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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11
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Troschel FM, Troschel BO, Kloss M, Troschel AS, Pepper NB, Wiewrodt RG, Stummer W, Wiewrodt D, Theodor Eich H. Cervical body composition on radiotherapy planning computed tomography scans predicts overall survival in glioblastoma patients. Clin Transl Radiat Oncol 2023; 40:100621. [PMID: 37008514 PMCID: PMC10063381 DOI: 10.1016/j.ctro.2023.100621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 03/20/2023] [Accepted: 03/23/2023] [Indexed: 03/29/2023] Open
Abstract
Background and purpose Glioblastoma (GBM) patients face a strongly unfavorable prognosis despite multimodal therapy regimens. However, individualized mortality prediction remains imprecise. Harnessing routine radiation planning cranial computed tomography (CT) scans, we assessed cervical body composition measures as novel biomarkers for overall survival (OS) in GBM patients. Materials and methods We performed threshold-based semi-automated quantification of muscle and subcutaneous fat cross-sectional area (CSA) at the levels of the first and second cervical vertebral body. First, we tested this method's validity by correlating cervical measures to established abdominal body composition in an open-source whole-body CT cohort. We then identified consecutive patients undergoing radiation planning for recent GBM diagnosis at our institution from 2010 to 2020 and quantified cervical body composition on radiation planning CT scans. Finally, we performed univariable and multivariable time-to-event analyses, adjusting for age, sex, body mass index, comorbidities, performance status, extent of surgical resection, extent of tumor at diagnosis, and MGMT methylation. Results Cervical body composition measurements were well-correlated with established abdominal markers (Spearman's rho greater than 0.68 in all cases). Subsequently, we included 324 GBM patients in our study cohort (median age 63 years, 60.8% male). 293 (90.4%) patients died during follow-up. Median survival time was 13 months. Patients with below-average muscle CSA or above-average fat CSA demonstrated shorter survival. In multivariable analyses, continuous cervical muscle measurements remained independently associated with OS. Conclusion This exploratory study establishes novel cervical body composition measures routinely available on cranial radiation planning CT scans and confirms their association with OS in patients diagnosed with GBM.
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Affiliation(s)
- Fabian M. Troschel
- Department of Radiation Oncology, Münster University Hospital, Albert-Schweitzer-Campus 1, 48149 Münster, Germany
- Corresponding author at: Universitätsklinikum Münster, Albert-Schweitzer-Campus 1, 48149 Münster, Germany.
| | - Benjamin O. Troschel
- Department of Radiation Oncology, Münster University Hospital, Albert-Schweitzer-Campus 1, 48149 Münster, Germany
| | - Maren Kloss
- Department of Neurosurgery, Münster University Hospital, Albert-Schweitzer-Campus 1, 48149 Münster, Germany
| | - Amelie S. Troschel
- Department of Medicine II, Klinikum Wolfsburg, Sauerbruchstraße 7, 38440 Wolfsburg, Germany
| | - Niklas B. Pepper
- Department of Radiation Oncology, Münster University Hospital, Albert-Schweitzer-Campus 1, 48149 Münster, Germany
| | - Rainer G. Wiewrodt
- Pulmonary Research Division, Münster University, Albert-Schweitzer-Campus 1, 48149 Münster, Germany
- Department of Pulmonary Medicine, Mathias Foundation, Hospitals Rheine and Ibbenbueren, Frankenburgsstrasse 31, 48431 Rheine, Germany
| | - Walter Stummer
- Department of Neurosurgery, Münster University Hospital, Albert-Schweitzer-Campus 1, 48149 Münster, Germany
| | - Dorothee Wiewrodt
- Department of Neurosurgery, Münster University Hospital, Albert-Schweitzer-Campus 1, 48149 Münster, Germany
| | - Hans Theodor Eich
- Department of Radiation Oncology, Münster University Hospital, Albert-Schweitzer-Campus 1, 48149 Münster, Germany
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