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  • Elsevier (CrossRef)  (11)
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  • 1
    Language: English
    In: Journal of Clinical Neuroscience, April 2016, Vol.26, pp.145-146
    Description: Intravenous administration of thrombolytic agents is considered to be contraindicated in patients with intracranial neoplasms. However, only a single case of thrombolysis-related intracranial tumour haemorrhage has been reported to our knowledge and several studies have suggested that systemic thrombolysis can be safely carried out in these patients. Here we report a patient who developed haemorrhage into a previously unknown intracranial tumour following intravenous thrombolysis for acute myocardial ST-elevation infarction. Identification of abnormal tissue during surgical haematoma evacuation initiated histopathological examination which revealed meningioma World Health Organization Grade I. Intracranial tumours may represent the causative pathology in cases of thrombolysis-related intracranial haemorrhage and this should be considered in the treatment of these patients.
    Keywords: Fibrinolysis ; Haemorrhage ; Intracranial Neoplasm ; Thrombolysis ; Medicine
    ISSN: 0967-5868
    E-ISSN: 1532-2653
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  • 2
    Language: English
    In: International Journal of Radiation Oncology, Biology, Physics, 01 December 2018, Vol.102(5), pp.1472-1480
    Description: Because treatment options at progression are limited for patients with glioma, accuracy in definition of progression is pivotal. Clinically asymptomatic, newly detected, nonmeasurable, speckled contrast-enhancing lesions (SCEs) without immediate relation to prior immune therapy or radiation therapy appear relatively frequently during the course of disease in patients with glioma and challenge the definition of progression based on Response Assessment in Neuro-oncology criteria. Therefore, data characterizing these SCEs are needed for recommendations of subsequent clinical management. Magnetic resonance imaging of 746 patients with glioma included in this study were retrospectively revised for appearance of newly detected SCEs during the course of disease. Associations with molecular and clinical baseline parameters and their prognostic impact were statistically analyzed, and frequency, natural course, and location of SCEs were described. SCEs occurred more frequently in World Health Organization grade 2 and 3 astrocytoma and oligodendroglial tumors and were significantly associated with isocitrate dehydrogenase mutation in World Health Organization grade 3 astrocytoma and glioblastoma. SCEs mostly remained stable or dissolved in follow-up magnetic resonance imaging, even if no new treatment was initiated. SCEs were frequently located within the tumor or tumor-associated fluid-attenuated inversion recovery abnormalities, but distant appearance also occurred. In patients with glioblastoma, SCEs were associated with a favorable prognosis, which was also observed in the subgroup of patients with glioblastoma with isocitrate dehydrogenase wildtype status. The data demonstrate a predominantly benign course of SCEs after their appearance and emphasize cautious definitions of progression and regular clinical and radiographic follow-up rather than premature initiation of new antitumor therapies until progression is confirmed.
    Keywords: Medicine
    ISSN: 0360-3016
    E-ISSN: 1879-355X
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  • 3
    Language: English
    In: Journal of Neuroimmunology, 15 October 2014, Vol.275(1-2), pp.39-39
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jneuroim.2014.08.104 Byline: Theresa Schumacher, Lukas Bunse, Stefan Pusch, Felix Sahm, Andreas von Deimling, Wolfgang Wick, Michael Platten
    Keywords: Medicine ; Anatomy & Physiology
    ISSN: 0165-5728
    E-ISSN: 1872-8421
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  • 4
    Language: English
    In: Journal of Neuroimmunology, 15 October 2014, Vol.275(1-2), pp.174-174
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jneuroim.2014.08.467 Byline: Jana Sonner, Melanie Keil, Tobias Lanz, Iris Oezen, Theresa Schumacher, Felix Sahm, Wolfgang Wick, Michael Platten
    Keywords: Medicine ; Anatomy & Physiology
    ISSN: 0165-5728
    E-ISSN: 1872-8421
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  • 5
    Language: English
    In: Journal of Neuroimmunology, 15 December 2013, Vol.265(1-2), pp.106-116
    Description: Malignant gliomas are primary brain tumors characterized by profound local immunosuppression. While the remarkable plasticity of perivascular cells – resembling mesenchymal stem cells (MSC) – in malignant gliomas and their contribution to angiogenesis is increasingly recognized, their role as potential mediators of immunosuppression is unknown. Here we demonstrate that FACS-sorted malignant glioma-derived pericytes (HMGP) were characterized by the expression of CD90, CD248, and platelet-derived growth factor receptor-β (PDGFR-β). HMGP shared this expression profile with human brain vascular pericytes (HBVP) and human MSC (HMSC) but not human cerebral microvascular endothelial cells (HCMEC). CD90 + PDGFR-β + perivascular cells distinct from CD31 + endothelial cells accumulated in human gliomas with increasing degree of malignancy and negatively correlated with the presence of blood vessel-associated leukocytes and CD8 + T cells. Cultured CD90 + PDGFR-β + HBVP were equally capable of suppressing allogeneic or mitogen-activated T cell responses as human MSC. HMGP, HBVP and HMSC expressed prostaglandin E synthase (PGES), inducible nitric oxide synthase (iNOS), human leukocyte antigen-G (HLA-G), hepatocyte growth factor (HGF) and transforming growth factor-β (TGF-β). These factors but not indoleamine 2,3-dioxygenase-mediated conversion of tryptophan to kynurenine functionally contributed to immunosuppression of immature pericytes. Our data provide evidence that human cerebral CD90 + perivascular cells possess T cell inhibitory capability comparable to human MSC and suggest that these cells, besides their critical role in tumor vascularization, also promote local immunosuppression in malignant gliomas and possibly other brain diseases.
    Keywords: Glioma ; Immunosuppression ; Pericytes ; Mesenchymal Stem Cells ; Medicine ; Anatomy & Physiology
    ISSN: 0165-5728
    E-ISSN: 1872-8421
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  • 6
    Language: English
    In: Journal of Neuroimmunology, 15 October 2014, Vol.275(1-2), pp.35-35
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jneuroim.2014.08.096 Byline: Lukas Bunse, Theresa Schumacher, Felix Sahm, Stefan Pusch, Iris Oezen, Andreas von Deimling, Wolfgang Wick, Michael Platten
    Keywords: Medicine ; Anatomy & Physiology
    ISSN: 0165-5728
    E-ISSN: 1872-8421
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  • 7
    Language: English
    In: European Journal of Radiology, March 2013, Vol.82(3), pp.552-556
    Description: Reliable differentiation between glioblastoma and primary CNS lymphoma (PCNSL) using conventional MR imaging is challenging, since both entities may show similar appearance on structural MR imaging. Here we analyzed if the appearance of intratumoural susceptibility signals (ITSS) on susceptibility weighted imaging (SWI) may differentiate between both entities. SWI and contrast enhanced T1-weighted images were acquired from 15 patients with newly diagnosed PCNSL (14 B-cell PCNSL, 1 T-cell PCNSL) and 117 patients with newly diagnosed glioblastoma with a 3 Tesla MR. Additional phase images were available in 8 patients with PCNSL and 88 patients with glioblastoma. Appearance of ITSS was assessed by two readers on SWI and the size of the enhancing lesions on contrast enhanced T1-weighted images were measured. Furthermore it was assessed if ITSS displayed more clearly on SWI or on phase images. ITSS were detected in 106 (reader 1) and 109 (reader 2) glioblastoma, respectively. Both readers identified ITSS within the T-cell PCNSL while both readers did not identify any ITSS within the 14 Bcell PCNSL. Interrarter variability as determined by Cohen was excellent for glioblastoma ( = 0.938) and for PCNSL ( = 1). The medium size of the enhancing lesion of the glioblastoma that did not harbour ITSS was significantly smaller than the size of the glioblastoma exhibiting ITSS ( 〈 0.008). All identified ITSS displayed more clearly on SWI than on phase images. Presence of ITSS differentiates reliably between glioblastoma and B-cell PCNSL and provides a fast bases for the clinical decision without causing any postprocessing work.
    Keywords: Glioblastoma ; Primary CNS Lymphoma ; Susceptibility Weighted Imaging ; Intratumoural Susceptibility Signals ; Medicine
    ISSN: 0720-048X
    E-ISSN: 1872-7727
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  • 8
    Language: English
    In: The Lancet Oncology, May 2017, Vol.18(5), pp.682-694
    Description: The WHO classification of brain tumours describes 15 subtypes of meningioma. Nine of these subtypes are allotted to WHO grade I, and three each to grade II and grade III. Grading is based solely on histology, with an absence of molecular markers. Although the existing classification and grading approach is of prognostic value, it harbours shortcomings such as ill-defined parameters for subtypes and grading criteria prone to arbitrary judgment. In this study, we aimed for a comprehensive characterisation of the entire molecular genetic landscape of meningioma to identify biologically and clinically relevant subgroups. In this multicentre, retrospective analysis, we investigated genome-wide DNA methylation patterns of meningiomas from ten European academic neuro-oncology centres to identify distinct methylation classes of meningiomas. The methylation classes were further characterised by DNA copy number analysis, mutational profiling, and RNA sequencing. Methylation classes were analysed for progression-free survival outcomes by the Kaplan-Meier method. The DNA methylation-based and WHO classification schema were compared using the Brier prediction score, analysed in an independent cohort with WHO grading, progression-free survival, and disease-specific survival data available, collected at the Medical University Vienna (Vienna, Austria), assessing methylation patterns with an alternative methylation chip. We retrospectively collected 497 meningiomas along with 309 samples of other extra-axial skull tumours that might histologically mimic meningioma variants. Unsupervised clustering of DNA methylation data clearly segregated all meningiomas from other skull tumours. We generated genome-wide DNA methylation profiles from all 497 meningioma samples. DNA methylation profiling distinguished six distinct clinically relevant methylation classes associated with typical mutational, cytogenetic, and gene expression patterns. Compared with WHO grading, classification by individual and combined methylation classes more accurately identifies patients at high risk of disease progression in tumours with WHO grade I histology, and patients at lower risk of recurrence among WHO grade II tumours (p=0·0096) from the Brier prediction test). We validated this finding in our independent cohort of 140 patients with meningioma. DNA methylation-based meningioma classification captures clinically more homogenous groups and has a higher power for predicting tumour recurrence and prognosis than the WHO classification. The approach presented here is potentially very useful for stratifying meningioma patients to observation-only or adjuvant treatment groups. We consider methylation-based tumour classification highly relevant for the future diagnosis and treatment of meningioma. German Cancer Aid, Else Kröner-Fresenius Foundation, and DKFZ/Heidelberg Institute of Personalized Oncology/Precision Oncology Program.
    Keywords: Medicine
    ISSN: 1470-2045
    E-ISSN: 1474-5488
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  • 9
    Language: English
    In: Cell, 25 February 2016, Vol.164(5), pp.1060-1072
    Description: Primitive neuroectodermal tumors of the central nervous system (CNS-PNETs) are highly aggressive, poorly differentiated embryonal tumors occurring predominantly in young children but also affecting adolescents and adults. Herein, we demonstrate that a significant proportion of institutionally diagnosed CNS-PNETs display molecular profiles indistinguishable from those of various other well-defined CNS tumor entities, facilitating diagnosis and appropriate therapy for patients with these tumors. From the remaining fraction of CNS-PNETs, we identify four new CNS tumor entities, each associated with a recurrent genetic alteration and distinct histopathological and clinical features. These new molecular entities, designated “CNS neuroblastoma with activation (CNS NB- ),” “CNS Ewing sarcoma family tumor with alteration (CNS EFT- ),” “CNS high-grade neuroepithelial tumor with alteration (CNS HGNET- ),” and “CNS high-grade neuroepithelial tumor with alteration (CNS HGNET- ),” will enable meaningful clinical trials and the development of therapeutic strategies for patients affected by poorly differentiated CNS tumors. Highly malignant primitive neuroectodermal tumors of the CNS (CNS-PNETs) have been challenging to diagnose and distinguish from other kinds of brain tumors, but molecular profiling now reveals that these cancers can be readily classified into some known tumor types and four new entities with distinct histopathological and clinical features, paving the way for meaningful clinical trials.
    Keywords: Biology
    ISSN: 0092-8674
    E-ISSN: 1097-4172
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  • 10
    Language: English
    In: The Lancet Oncology, May 2019, Vol.20(5), pp.728-740
    Description: The Response Assessment in Neuro-Oncology (RANO) criteria and requirements for a uniform protocol have been introduced to standardise assessment of MRI scans in both clinical trials and clinical practice. However, these criteria mainly rely on manual two-dimensional measurements of contrast-enhancing (CE) target lesions and thus restrict both reliability and accurate assessment of tumour burden and treatment response. We aimed to develop a framework relying on artificial neural networks (ANNs) for fully automated quantitative analysis of MRI in neuro-oncology to overcome the inherent limitations of manual assessment of tumour burden. In this retrospective study, we compiled a single-institution dataset of MRI data from patients with brain tumours being treated at Heidelberg University Hospital (Heidelberg, Germany; Heidelberg training dataset) to develop and train an ANN for automated identification and volumetric segmentation of CE tumours and non-enhancing T2-signal abnormalities (NEs) on MRI. Independent testing and large-scale application of the ANN for tumour segmentation was done in a single-institution longitudinal testing dataset from the Heidelberg University Hospital and in a multi-institutional longitudinal testing dataset from the prospective randomised phase 2 and 3 European Organisation for Research and Treatment of Cancer (EORTC)-26101 trial ( ), acquired at 38 institutions across Europe. In both longitudinal datasets, spatial and temporal tumour volume dynamics were automatically quantified to calculate time to progression, which was compared with time to progression determined by RANO, both in terms of reliability and as a surrogate endpoint for predicting overall survival. We integrated this approach for fully automated quantitative analysis of MRI in neuro-oncology within an application-ready software infrastructure and applied it in a simulated clinical environment of patients with brain tumours from the Heidelberg University Hospital (Heidelberg simulation dataset). For training of the ANN, MRI data were collected from 455 patients with brain tumours (one MRI per patient) being treated at Heidelberg hospital between July 29, 2009, and March 17, 2017 (Heidelberg training dataset). For independent testing of the ANN, an independent longitudinal dataset of 40 patients, with data from 239 MRI scans, was collected at Heidelberg University Hospital in parallel with the training dataset (Heidelberg test dataset), and 2034 MRI scans from 532 patients at 34 institutions collected between Oct 26, 2011, and Dec 3, 2015, in the EORTC-26101 study were of sufficient quality to be included in the EORTC-26101 test dataset. The ANN yielded excellent performance for accurate detection and segmentation of CE tumours and NE volumes in both longitudinal test datasets (median DICE coefficient for CE tumours 0·89 [95% CI 0·86–0·90], and for NEs 0·93 [0·92–0·94] in the Heidelberg test dataset; CE tumours 0·91 [0·90–0·92], NEs 0·93 [0·93–0·94] in the EORTC-26101 test dataset). Time to progression from quantitative ANN-based assessment of tumour response was a significantly better surrogate endpoint than central RANO assessment for predicting overall survival in the EORTC-26101 test dataset (hazard ratios ANN 2·59 [95% CI 1·86–3·60] central RANO 2·07 [1·46–2·92]; p〈0·0001) and also yielded a 36% margin over RANO (p〈0·0001) when comparing reliability values (ie, agreement in the quantitative volumetrically defined time to progression [based on radiologist ground truth automated assessment with ANN] of 87% [266 of 306 with sufficient data] compared with 51% [155 of 306] with local independent central RANO assessment). In the Heidelberg simulation dataset, which comprised 466 patients with brain tumours, with 595 MRI scans obtained between April 27, and Sept 17, 2018, automated on-demand processing of MRI scans and quantitative tumour response assessment within the simulated clinical environment required 10 min of computation time (average per scan). Overall, we found that ANN enabled objective and automated assessment of tumour response in neuro-oncology at high throughput and could ultimately serve as a blueprint for the application of ANN in radiology to improve clinical decision making. Future research should focus on prospective validation within clinical trials and application for automated high-throughput imaging biomarker discovery and extension to other diseases. Medical Faculty Heidelberg Postdoc-Program, Else Kröner-Fresenius Foundation.
    Keywords: Medicine
    ISSN: 1470-2045
    E-ISSN: 1474-5488
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