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Li Z, Xue C, Li S, Jing M, Liu S, Sun J, Ren T, Zhou J. Preoperative CT histogram analysis to predict the expression of Ki-67 in solid pseudopapillary tumours of the pancreas. Clin Radiol 2024; 79:e197-e203. [PMID: 38007336 DOI: 10.1016/j.crad.2023.10.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 10/11/2023] [Accepted: 10/22/2023] [Indexed: 11/27/2023]
Abstract
AIM To explore the value of preoperative computed tomography (CT) histogram features in predicting the expression status of Ki-67 in patients with solid pseudopapillary pancreatic tumours (SPTP). MATERIALS AND METHODS This retrospective study analysed venous phase CT images of 39 patients with SPTP confirmed at surgery and histopathology and measured using the Ki-67 proliferation index from November 2015 to February 2022. According to the Ki-67 proliferation index, they were divided into high expression (Ki-67 ≥ 4%) and low expression (Ki-67 < 4%) groups. The histogram features of quantitative parameters were extracted using MaZda software, and the quantitative parameters of CT histograms were compared between groups. The receiver operating characteristic (ROC) curves of the patients were plotted according to the parameters, with statistically significant differences. The area under the curve (AUC), sensitivity, and specificity were calculated, and the effectiveness of the histogram parameters in predicting Ki-67 expression was analysed and evaluated. RESULTS In total, 27 SPTP patients were enrolled, including 11 with high expression of Ki-67 and 16 with low expression. Comparative analysis of the Ki-67 high- and low-expression groups revealed a statistically significant in necrosis and variance (p<0.05). ROC curve analysis showed that the AUC of necrosis and variance predicting Ki-67 expression status were 0.753 and 0.841, the sensitivities were 81.8% and 81.3%, and the specificities were 68.7% and 81.8%, respectively. CONCLUSION Preoperative CT histogram features help predict Ki-67 expression status in patients with SPTP.
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Affiliation(s)
- Z Li
- Department of Imaging, Shaanxi Provincial People's Hospital, Xi'an, China
| | - C Xue
- Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No. 82, Chengguan District, Lanzhou 730030, China; Second Clinical School, Lanzhou University, Lanzhou, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
| | - S Li
- Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No. 82, Chengguan District, Lanzhou 730030, China; Second Clinical School, Lanzhou University, Lanzhou, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
| | - M Jing
- Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No. 82, Chengguan District, Lanzhou 730030, China; Second Clinical School, Lanzhou University, Lanzhou, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
| | - S Liu
- Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No. 82, Chengguan District, Lanzhou 730030, China; Second Clinical School, Lanzhou University, Lanzhou, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
| | - J Sun
- Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No. 82, Chengguan District, Lanzhou 730030, China; Second Clinical School, Lanzhou University, Lanzhou, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
| | - T Ren
- Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No. 82, Chengguan District, Lanzhou 730030, China; Second Clinical School, Lanzhou University, Lanzhou, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
| | - J Zhou
- Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No. 82, Chengguan District, Lanzhou 730030, China; Second Clinical School, Lanzhou University, Lanzhou, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China.
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Gihr G, Horvath-Rizea D, Kohlhof-Meinecke P, Ganslandt O, Henkes H, Härtig W, Donitza A, Skalej M, Schob S. Diffusion Weighted Imaging in Gliomas: A Histogram-Based Approach for Tumor Characterization. Cancers (Basel) 2022; 14:cancers14143393. [PMID: 35884457 PMCID: PMC9321540 DOI: 10.3390/cancers14143393] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/07/2022] [Accepted: 07/09/2022] [Indexed: 12/10/2022] Open
Abstract
Simple Summary Glioma represent approximately one-third of all brain tumors. Although they differ clinically, histologically and genetically, they often are not distinguishable by morphological magnetic resonance imaging (MRI) diagnostics. We therefore investigated in this retrospective study whether diffusion weighted imaging (DWI) using a radiomic approach could provide complementary information with respect to tumor differentiation and cell proliferation, as well as the underlying genetic and epigenetic tumor profile. We identified several histogram features that could facilitate presurgical tumor grading and potentially enable one to draw conclusions about tumor characteristics on a cellular and subcellular scale. Abstract (1) Background: Astrocytic gliomas present overlapping appearances in conventional MRI. Supplementary techniques are necessary to improve preoperative diagnostics. Quantitative DWI via the computation of apparent diffusion coefficient (ADC) histograms has proven valuable for tumor characterization and prognosis in this regard. Thus, this study aimed to investigate (I) the potential of ADC histogram analysis (HA) for distinguishing low-grade gliomas (LGG) and high-grade gliomas (HGG) and (II) whether those parameters are associated with Ki-67 immunolabelling, the isocitrate-dehydrogenase-1 (IDH1) mutation profile and the methylguanine-DNA-methyl-transferase (MGMT) promoter methylation profile; (2) Methods: The ADC-histograms of 82 gliomas were computed. Statistical analysis was performed to elucidate associations between histogram features and WHO grade, Ki-67 immunolabelling, IDH1 and MGMT profile; (3) Results: Minimum, lower percentiles (10th and 25th), median, modus and entropy of the ADC histogram were significantly lower in HGG. Significant differences between IDH1-mutated and IDH1-wildtype gliomas were revealed for maximum, lower percentiles, modus, standard deviation (SD), entropy and skewness. No differences were found concerning the MGMT status. Significant correlations with Ki-67 immunolabelling were demonstrated for minimum, maximum, lower percentiles, median, modus, SD and skewness; (4) Conclusions: ADC HA facilitates non-invasive prediction of the WHO grade, tumor-proliferation rate and clinically significant mutations in case of astrocytic gliomas.
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Affiliation(s)
- Georg Gihr
- Katharinenhospital Stuttgart, Clinic for Neuroradiology, 70174 Stuttgart, Germany; (D.H.-R.); (H.H.)
- Correspondence: (G.G.); (S.S.); Tel.: +49-711-2785-4454 (G.G.); +49-345-557-2342 (S.S.)
| | - Diana Horvath-Rizea
- Katharinenhospital Stuttgart, Clinic for Neuroradiology, 70174 Stuttgart, Germany; (D.H.-R.); (H.H.)
| | | | - Oliver Ganslandt
- Katharinenhospital Stuttgart, Clinic for Neurosurgery, 70174 Stuttgart, Germany;
| | - Hans Henkes
- Katharinenhospital Stuttgart, Clinic for Neuroradiology, 70174 Stuttgart, Germany; (D.H.-R.); (H.H.)
| | - Wolfgang Härtig
- Paul Flechsig Institute for Brain Research, University of Leipzig, 04103 Leipzig, Germany;
| | - Aneta Donitza
- Department for Neuroradiology, Clinic and Policlinic for Radiology, University Hospital Halle (Saale), 06120 Halle (Saale), Germany; (A.D.); (M.S.)
| | - Martin Skalej
- Department for Neuroradiology, Clinic and Policlinic for Radiology, University Hospital Halle (Saale), 06120 Halle (Saale), Germany; (A.D.); (M.S.)
| | - Stefan Schob
- Department for Neuroradiology, Clinic and Policlinic for Radiology, University Hospital Halle (Saale), 06120 Halle (Saale), Germany; (A.D.); (M.S.)
- Correspondence: (G.G.); (S.S.); Tel.: +49-711-2785-4454 (G.G.); +49-345-557-2342 (S.S.)
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Haghighi Borujeini M, Farsizaban M, Yazdi SR, Tolulope Agbele A, Ataei G, Saber K, Hosseini SM, Abedi-Firouzjah R. Grading of meningioma tumors based on analyzing tumor volumetric histograms obtained from conventional MRI and apparent diffusion coefficient images. Egypt J Radiol Nucl Med 2021. [DOI: 10.1186/s43055-021-00545-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Abstract
Background
Our purpose was to evaluate the application of volumetric histogram parameters obtained from conventional MRI and apparent diffusion coefficient (ADC) images for grading the meningioma tumors.
Results
Tumor volumetric histograms of preoperative MRI images from 45 patients with the diagnosis of meningioma at different grades were analyzed to find the histogram parameters. Kruskal-Wallis statistical test was used for comparison between the parameters obtained from different grades. Multi-parametric regression analysis was used to find the model and parameters with high predictive value for the classification of meningioma. Mode; standard deviation on post-contrast T1WI, T2-FLAIR, and ADC images; kurtosis on post-contrast T1WI and T2-FLAIR images; mean and several percentile values on ADC; and post-contrast T1WI images showed significant differences among different tumor grades (P < 0.05). The multi-parametric linear regression showed that the ADC histogram parameters model had a higher predictive value, with cutoff values of 0.212 (sensitivity = 79.6%, specificity = 84.3%) and 0.180 (sensitivity = 70.9%, specificity = 80.8%) for differentiating the grade I from II, and grade II from III, respectively.
Conclusions
The multi-parametric model of volumetric histogram parameters in some of the conventional MRI series (i.e., post-contrast T1WI and T2-FLAIR images) along with the ADC images are appropriate for predicting the meningioma tumors’ grade.
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Meyer HJ, Höhn AK, Surov A. Histogram parameters derived from T1 and T2 weighted images correlate with tumor infiltrating lymphocytes and tumor-stroma ratio in head and neck squamous cell cancer. Magn Reson Imaging 2021; 80:127-131. [PMID: 33971242 DOI: 10.1016/j.mri.2021.05.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 05/02/2021] [Accepted: 05/05/2021] [Indexed: 12/12/2022]
Abstract
PURPOSE The present study used histogram analysis values derived from T1- and T2- weighted (w) images to elucidate possible associations with Tumor-infiltrating lymphocytes (TIL) and Vimentin expression in head and neck squamous cell cancer (HNSCC). MATERIALS AND METHODS Overall, 28 patients (n = 8 female patient, 28.6%) with primary HNSCC of different localizations were involved in the study. Magnetic resonance imaging (MRI) was obtained on a 3 T MRI. The images were analyzed with a whole lesion measurement using a histogram approach. TIL- and vimentin-expression was calculated on biopsy samples before any form of treatment. RESULTS Several T1-derived parameters correlated with the expression of TIL within the stroma compartment: mean (r = 0.42, p = 0.025), p10 (r = 0.50, p = 0.007), p25 (r = 0.42, p = 0.025), median (r = 0.39, p = 0.036), and mode (r = 0.39, p = 0.04). No T2-derived parameter correlated with the TIL within the stroma compartment. Several T2-derived parameters correlated with the expression of TIL within the tumor compartment: mean (r = -0.52, p = 0.004), max (r = -0.43, p = 0.02), p10 (r = -0.38, p = 0.04), p25 (r = -0.53, p = 0.004), p75 (r = -0.52, p = 0.004), p90 (r = -0.48, p = 0.009), median (r = -0.52, p = 0.004), mode (r = -0.40, p = 0.03). Kurtosis derived from T2w images had significant higher values in tumor-rich tumors, compared to stroma-rich tumors, (mean 5.5 ± 0.5 versus 4.2 ± 1.2, p = 0.028). CONCLUSIONS Histogram analysis parameters derived from T1w and T2w images might be able to reflect tumor compartments and TIL expression in HNSCC.
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Affiliation(s)
- Hans-Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Liebigstraße 20, 04103 Leipzig, Germany.
| | - Anne Kathrin Höhn
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Liebigstraße 20, 04103 Leipzig, Germany; Department of Pathology, University of Leipzig, Liebigstraße 20, 04103 Leipzig, Germany
| | - Alexey Surov
- Department of Diagnostic and Interventional Radiology, University of Magdeburg, Leipzigerstraße 44, 39120 Magdeburg, Germany
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Gihr G, Horvath-Rizea D, Hekeler E, Ganslandt O, Henkes H, Hoffmann KT, Scherlach C, Schob S. Diffusion weighted imaging in high-grade gliomas: A histogram-based analysis of apparent diffusion coefficient profile. PLoS One 2021; 16:e0249878. [PMID: 33857203 PMCID: PMC8049265 DOI: 10.1371/journal.pone.0249878] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 03/26/2021] [Indexed: 12/15/2022] Open
Abstract
Purpose Glioblastoma and anaplastic astrocytoma represent the most commonly encountered high-grade-glioma (HGG) in adults. Although both neoplasms are very distinct entities in context of epidemiology, clinical course and prognosis, their appearance in conventional magnetic resonance imaging (MRI) is very similar. In search for additional information aiding the distinction of potentially confusable neoplasms, histogram analysis of apparent diffusion coefficient (ADC) maps recently proved to be auxiliary in a number of entities. Therefore, our present exploratory retrospective study investigated whether ADC histogram profile parameters differ significantly between anaplastic astrocytoma and glioblastoma, reflect the proliferation index Ki-67, or are associated with the prognostic relevant MGMT (methylguanine-DNA methyl-transferase) promotor methylation status. Methods Pre-surgical ADC volumes of 56 HGG patients were analyzed by histogram-profiling. Association between extracted histogram parameters and neuropathology including WHO-grade, Ki-67 expression and MGMT promotor methylation status was investigated due to comparative and correlative statistics. Results Grade IV gliomas were more heterogeneous than grade III tumors. More specifically, ADCmin and the lowest percentile ADCp10 were significantly lower, whereas ADCmax, ADC standard deviation and Skewness were significantly higher in the glioblastoma group. ADCmin, ADCmax, ADC standard deviation, Kurtosis and Entropy of ADC histogram were significantly correlated with Ki-67 expression. No significant difference could be revealed by comparison of ADC histogram parameters between MGMT promotor methylated and unmethylated HGG. Conclusions ADC histogram parameters differ significantly between glioblastoma and anaplastic astrocytoma and show distinct associations with the proliferative activity in both HGG. Our results suggest ADC histogram profiling as promising biomarker for differentiation of both, however, further studies with prospective multicenter design are wanted to confirm and further elaborate this hypothesis.
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Affiliation(s)
- Georg Gihr
- Clinic for Neuroradiology, Katharinenhospital Stuttgart, Stuttgart, Germany
- * E-mail:
| | | | - Elena Hekeler
- Department for Pathology, Katharinenhospital Stuttgart, Stuttgart, Germany
| | - Oliver Ganslandt
- Clinic for Neurosurgery, Katharinenhospital Stuttgart, Stuttgart, Germany
| | - Hans Henkes
- Clinic for Neuroradiology, Katharinenhospital Stuttgart, Stuttgart, Germany
| | - Karl-Titus Hoffmann
- Department for Neuroradiology, University Hospital Leipzig, Leipzig, Germany
| | - Cordula Scherlach
- Department for Neuroradiology, University Hospital Leipzig, Leipzig, Germany
| | - Stefan Schob
- Department for Radiology, University Hospital Halle (Saale), Halle (Saale), Germany
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Meyer HJ, Schneider I, Emmer A, Kornhuber M, Surov A. Associations between apparent diffusion coefficient values and histopathological tissue alterations in myopathies. Brain Behav 2020; 10:e01809. [PMID: 32860496 PMCID: PMC7667360 DOI: 10.1002/brb3.1809] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 08/02/2020] [Accepted: 08/04/2020] [Indexed: 12/13/2022] Open
Abstract
OBJECTIVES Diffusion-weighted imaging (DWI) can reflect histopathologic changes in muscle disorders. The present study sought to elucidate possible associations between histopathology derived from muscle biopsies and DWI in myositis and other myopathies. METHODS Nineteen patients (10 women, 52.6%) with a mean age 51.43 ± 19 years were included in this retrospective study. Apparent diffusion coefficients (ADC) were evaluated with a histogram approach of the biopsied muscle. The histopathology analysis included the scoring systems proposed by Tateyama et al., Fanin et al., Allenbach et al. and immunhistochemical stainings for MHC, CD68, CD8, and CD4. RESULTS There was a tendency that skewness was lowered with increasing Tateyama score, but it did not reach statistical significance (p = .14). No statistical differences for the other scores were identified. There was a tendency that kurtosis was higher in MHC negative stained patient compared to positive patients, but statistically significance was not reached (p = .07). ADC histogram parameters did not correlate with CD68 and CD8 positive stained cells. There was a trend for skewness to correlate with the amount of CD4-positive cells (r = .57, p = .07). CONCLUSION The present study could not identify statistical significant associations between DWI and histopathology in muscle diseases based upon a small patient sample. Presumably, the investigated histopathology scores are more specific for certain disease aspects, whereas ADC values reflect the whole cellularity of the investigated muscle, which might cause the negative results.
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Affiliation(s)
- Hans-Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
| | - Ilka Schneider
- Department of Neurology, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Alexander Emmer
- Department of Neurology, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Malte Kornhuber
- Department of Neurology, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Alexey Surov
- Department of Diagnostic and Interventional Radiology, University of Magdeburg, Magdeburg, Germany
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Gihr GA, Horvath-Rizea D, Hekeler E, Ganslandt O, Henkes H, Hoffmann KT, Scherlach C, Schob S. Histogram Analysis of Diffusion Weighted Imaging in Low-Grade Gliomas: in vivo Characterization of Tumor Architecture and Corresponding Neuropathology. Front Oncol 2020; 10:206. [PMID: 32158691 PMCID: PMC7051987 DOI: 10.3389/fonc.2020.00206] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Accepted: 02/06/2020] [Indexed: 02/01/2023] Open
Abstract
Background: Low-grade gliomas (LGG) in adults are usually slow growing and frequently asymptomatic brain tumors, originating from glial cells of the central nervous system (CNS). Although regarded formally as “benign” neoplasms, they harbor the potential of malignant transformation associated with high morbidity and mortality. Their complex and unpredictable tumor biology requires a reliable and conclusive presurgical magnetic resonance imaging (MRI). A promising and emerging MRI approach in this context is histogram based apparent diffusion coefficient (ADC) profiling, which recently proofed to be capable of providing prognostic relevant information in different tumor entities. Therefore, our study investigated whether histogram profiling of ADC distinguishes grade I from grade II glioma, reflects the proliferation index Ki-67, as well as the IDH (isocitrate dehydrogenase) mutation and MGMT (methylguanine-DNA methyl-transferase) promotor methylation status. Material and Methods: Pre-treatment ADC volumes of 26 LGG patients were used for histogram-profiling. WHO-grade, Ki-67 expression, IDH mutation, and MGMT promotor methylation status were evaluated. Comparative and correlative statistics investigating the association between histogram-profiling and neuropathology were performed. Results: Almost the entire ADC profile (p25, p75, p90, mean, median) was significantly lower in grade II vs. grade I gliomas. Entropy, as second order histogram parameter of ADC volumes, was significantly higher in grade II gliomas compared with grade I gliomas. Mean, maximum value (ADCmax) and the percentiles p10, p75, and p90 of ADC histogram were significantly correlated with Ki-67 expression. Furthermore, minimum ADC value (ADCmin) was significantly associated with MGMT promotor methylation status as well as ADC entropy with IDH-1 mutation status. Conclusions: ADC histogram-profiling is a valuable radiomic approach, which helps differentiating tumor grade, estimating growth kinetics and probably prognostic relevant genetic as well as epigenetic alterations in LGG.
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Affiliation(s)
| | | | - Elena Hekeler
- Department for Pathology, Katharinenhospital Stuttgart, Stuttgart, Germany
| | - Oliver Ganslandt
- Katharinenhospital Stuttgart, Clinic for Neurosurgery, Stuttgart, Germany
| | - Hans Henkes
- Katharinenhospital Stuttgart, Clinic for Neuroradiology, Stuttgart, Germany
| | - Karl-Titus Hoffmann
- Department for Neuroradiology, University Hospital Leipzig, Leipzig, Germany
| | - Cordula Scherlach
- Department for Neuroradiology, University Hospital Leipzig, Leipzig, Germany
| | - Stefan Schob
- Department for Neuroradiology, University Hospital Leipzig, Leipzig, Germany
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