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  1. Book ; Online ; E-Book: Robotergeführte Radiochirurgie

    Becker, Gerd / Muacevic, Alexander / Ruge, Maximilian Ingolf

    Cranielle und Spinale Indikationen

    2020  

    Author's details Gerd Becker, Alexander Muacevic, Maximilian I. Ruge (Hrsg.)
    Subject code 610
    Language German
    Size 1 Online-Ressource (X, 282 Seiten), Illustrationen, Diagramme
    Publisher De Gruyter
    Publishing place Berlin
    Publishing country Germany
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    HBZ-ID HT020615903
    ISBN 978-3-11-054059-8 ; 978-3-11-053984-4 ; 9783110539653 ; 3-11-054059-2 ; 3-11-053984-5 ; 3110539659
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Book ; Thesis: Ökonomische Analyse der robotergestützten Radiochirurgie mittels CyberKnife®

    Jonas, Patrik / Ruge, Maximilian Ingolf / Pfaff, Holger

    2021  

    Institution Klinik für Stereotaxie und Funktionelle Neurochirurgie
    Author's details vorgelegt von Patrik Jonas ; 1. Berichterstatter: Universitätsprofessor Dr. med. M.I. Ruge, 2. Berichterstatter: Universitätsprofessor Dr. phil. H. Pfaff ; aus dem Zentrum für Neurochirurgie der Universität zu Köln, Klinik und Poliklinik für Funktionelle Neurochirurgie und Stereotaxie
    Subject code 610
    Language German
    Size 113 Blätter, Diagramme
    Publishing place Köln
    Publishing country Germany
    Document type Book ; Thesis
    Thesis / German Habilitation thesis Dissertation, Universität zu Köln, 2021
    HBZ-ID HT021297964
    Database Catalogue ZB MED Medicine, Health

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    Shelf markLoan statusLocation
    2022 D 175 order for loan Magazin

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  3. Book ; Thesis: Frame-based stereotactic biopsy of deep-seated and midline structures in 511 procedures

    Minartz, Jana / Ruge, Maximilian Ingolf / Pfister, David

    feasibility, risk profile and diagnostic yield

    2020  

    Institution Klinik für Stereotaxie und Funktionelle Neurochirurgie
    Author's details vorgelegt von Jana Minartz ; 1. Gutachter: Universitätsprofessor Dr. med. M. Ruge, 2. Gutachter: Professor Dr. med. D. Pfister ; aus dem Zentrum für Neurochirurgie der Universität zu Köln, Klinik und Poliklinik für Funktionelle Neurochirurgie und Stereotaxie
    Language English ; German
    Size 48 Blätter, Illustrationen
    Publishing place Köln
    Publishing country Germany
    Document type Book ; Thesis
    Thesis / German Habilitation thesis Dissertation, Universität zu Köln, 2021
    Note Text deutsch. Enthält einen Sonderabdruck aus Zeitschrift in englischer Sprache
    HBZ-ID HT020898201
    Database Catalogue ZB MED Medicine, Health

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    Shelf markLoan statusLocation
    2021 D 228 order for loan Magazin

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  4. Book ; Thesis: Acoustic Neuroma Treated with Stereotactic Radiosurgery

    Pöhlmann, Lea / Ruge, Maximilian Ingolf / Klußmann, Jens Peter

    follow-up of 335 Patients; Veröffentlicht am 30.04.2018 im World Neurosurgery

    2019  

    Institution Klinik für Stereotaxie und Funktionelle Neurochirurgie
    Author's details vorgelegt von Lea Pöhlmann ; 1. Gutachter: Universitätsprofessor Dr. med. M.I. Ruge, 2. Gutachter: Universitätsprofessor Dr. med. J.P. Klußmann ; aus dem Zentrum für Neurochirurgie der Universität zu Köln, Klinik und Poliklinik für Funktionelle Neurochirurgie und Stereotaxie
    Subject code 610
    Language German ; English
    Size 30 Blätter, Diagramme
    Publishing place Köln
    Publishing country Germany
    Document type Book ; Thesis
    Thesis / German Habilitation thesis Dissertation, Universität zu Köln, 2019
    Note Enthält Sonderabdruck aus Zeitschrift in englischer Sprache
    HBZ-ID HT020237093
    Database Catalogue ZB MED Medicine, Health

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  5. Book ; Thesis: Stereotaktische einzeitige Radiochirurgie gutartiger Hirntumore bei älteren Patienten

    Weyer, Vera / Ruge, Maximilian Ingolf / Goldbrunner, Roland

    Retrospektive Untersuchung der Tumorkontrolle und Toxizität in einer monozentrischen Studie

    2020  

    Institution Klinik für Stereotaxie und Funktionelle Neurochirurgie
    Author's details vorgelegt von Vera Weyer ; 1. Gutachter: Universitätsprofessor Dr. med. M.I. Ruge, 2. Gutachter: Universitätsprofessor Dr. med. R.H. Goldbrunner ; aus dem Zentrum für Neurochirurgie der Universität zu Köln, Klinik und Poliklinik für Funktionelle Neurochirurgie und Stereotaxie
    Subject code 610
    Language German
    Size 59 Seiten, Diagramme
    Publishing place Köln
    Publishing country Germany
    Document type Book ; Thesis
    Thesis / German Habilitation thesis Dissertation, Universität zu Köln, 2021
    HBZ-ID HT021001505
    Database Catalogue ZB MED Medicine, Health

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    Shelf markLoan statusLocation
    2021 D 470 order for loan Magazin

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  6. Book ; Thesis: Stereotaktische Brachytherapie zur Behandlung Zerebraler Metastasen

    Ruge, Maximilian Ingolf

    = Stereotactic brachytherapy for the treatment of brain metastases

    2011  

    Title variant Stereotactic brachytherapy for the treatment of brain metastases
    Author's details vorgelegt von Maximilian I. Ruge
    Language German
    Size 89 S. : graph. Darst.
    Publishing country Germany
    Document type Book ; Thesis
    Thesis / German Habilitation thesis Köln, Univ., Habil.-Schr., 2011
    HBZ-ID HT016997912
    Database Catalogue ZB MED Medicine, Health

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  7. Article ; Online: Accuracy of robotic radiosurgery in renal cell carcinoma.

    Hofmann, Theresa / Kohlhase, Nadja / Eftimova, Dochka / Eder, Michael Martin / Staehler, Michael / Ruge, Maximilian I / Muacevic, Alexander / Fürweger, Christoph

    Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)

    2024  Volume 122, Page(s) 103372

    Abstract: Purpose: Although emerging clinical evidence supports robotic radiosurgery as a highly effective treatment option for renal cell carcinoma (RCC) less than 4 cm in diameter, delivery uncertainties and associated target volume margins have not been ... ...

    Abstract Purpose: Although emerging clinical evidence supports robotic radiosurgery as a highly effective treatment option for renal cell carcinoma (RCC) less than 4 cm in diameter, delivery uncertainties and associated target volume margins have not been studied in detail. We assess intrafraction tumor motion patterns and accuracy of robotic radiosurgery in renal tumors with real-time respiratory tracking to optimize treatment margins.
    Methods: Delivery log files from 165 consecutive treatments of RCC were retrospectively analyzed. Five components were considered for planning target volume (PTV) margin estimation: (a) The model error from the correlation model between patient breath and tumor motion, (b) the prediction error from an algorithm predicting the patient breathing pattern, (c) the targeting error from the treatment robot, (d) the inherent total accuracy of the system for respiratory motion tracking, and (e) the margin required to cover potential target rotation, simulated with PTV rotations up to 10°.
    Results: The median tumor motion was 10.5 mm, 2.4 mm and 4.4 mm in the superior-inferior, left-right, and anterior-posterior directions, respectively. The root of the sum of squares of all contributions to the system's inaccuracy results in a minimum PTV margin of 4.3 mm, 2.6 mm and 3.0 mm in the superior-inferior, left-right and anterior-posterior directions, respectively, assuming optimal fiducial position and neglecting target deformation.
    Conclusions: We have assessed kidney motion and derived PTV margins for the treatment of RCC with robotic radiosurgery, which helps to deliver renal treatments in a more consistent manner and potentially further improve outcomes.
    Language English
    Publishing date 2024-05-16
    Publishing country Italy
    Document type Journal Article
    ZDB-ID 1122650-x
    ISSN 1724-191X ; 1120-1797
    ISSN (online) 1724-191X
    ISSN 1120-1797
    DOI 10.1016/j.ejmp.2024.103372
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    Zs.B 2941: Show issues Location:
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  8. Book ; Thesis: Histo-Autoradiographie

    Ruge, Maximilian Ingolf

    Entwicklung einer Methode, Etablierung und klinische Anwendung

    (Medizin)

    1998  

    Author's details Maximilian Ingolf Ruge
    Series title Medizin
    Keywords Magenkrebs ; Epidermaler Wachstumsfaktor-Rezeptor ; Autoradiographie
    Subject Radioautographie ; Autoradiografie ; Radioautografie ; EGF-Rezeptor ; EGFR ; ErbB ; Epidermal Growth Factor Receptor ; Carcinoma ventriculi ; Magencarcinom ; Magenkarzinom
    Language German
    Size 85 S. : Ill., graph. Darst.
    Edition Als Typoskript gedr.
    Publisher Hieronymus
    Publishing place München
    Document type Book ; Thesis
    Thesis / German Habilitation thesis Bochum, Univ., Diss., 1998
    HBZ-ID HT009624682
    ISBN 3-933083-98-2 ; 978-3-933083-98-2
    Database Catalogue ZB MED Medicine, Health

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  9. Article ; Online: Quality requirements for MRI simulation in cranial stereotactic radiotherapy: a guideline from the German Taskforce "Imaging in Stereotactic Radiotherapy".

    Putz, Florian / Bock, Michael / Schmitt, Daniela / Bert, Christoph / Blanck, Oliver / Ruge, Maximilian I / Hattingen, Elke / Karger, Christian P / Fietkau, Rainer / Grigo, Johanna / Schmidt, Manuel A / Bäuerle, Tobias / Wittig, Andrea

    Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al

    2024  Volume 200, Issue 1, Page(s) 1–18

    Abstract: Accurate Magnetic Resonance Imaging (MRI) simulation is fundamental for high-precision stereotactic radiosurgery and fractionated stereotactic radiotherapy, collectively referred to as stereotactic radiotherapy (SRT), to deliver doses of high biological ... ...

    Abstract Accurate Magnetic Resonance Imaging (MRI) simulation is fundamental for high-precision stereotactic radiosurgery and fractionated stereotactic radiotherapy, collectively referred to as stereotactic radiotherapy (SRT), to deliver doses of high biological effectiveness to well-defined cranial targets. Multiple MRI hardware related factors as well as scanner configuration and sequence protocol parameters can affect the imaging accuracy and need to be optimized for the special purpose of radiotherapy treatment planning. MRI simulation for SRT is possible for different organizational environments including patient referral for imaging as well as dedicated MRI simulation in the radiotherapy department but require radiotherapy-optimized MRI protocols and defined quality standards to ensure geometrically accurate images that form an impeccable foundation for treatment planning. For this guideline, an interdisciplinary panel including experts from the working group for radiosurgery and stereotactic radiotherapy of the German Society for Radiation Oncology (DEGRO), the working group for physics and technology in stereotactic radiotherapy of the German Society for Medical Physics (DGMP), the German Society of Neurosurgery (DGNC), the German Society of Neuroradiology (DGNR) and the German Chapter of the International Society for Magnetic Resonance in Medicine (DS-ISMRM) have defined minimum MRI quality requirements as well as advanced MRI simulation options for cranial SRT.
    MeSH term(s) Humans ; Radiosurgery/methods ; Magnetic Resonance Imaging ; Radiotherapy Dosage ; Radiation Oncology ; Imaging, Three-Dimensional
    Language English
    Publishing date 2024-01-02
    Publishing country Germany
    Document type Journal Article ; Review
    ZDB-ID 84983-2
    ISSN 1439-099X ; 0179-7158 ; 0039-2073
    ISSN (online) 1439-099X
    ISSN 0179-7158 ; 0039-2073
    DOI 10.1007/s00066-023-02183-6
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  10. Article ; Online: Applications of radiomics and machine learning for radiotherapy of malignant brain tumors.

    Kocher, Martin / Ruge, Maximilian I / Galldiks, Norbert / Lohmann, Philipp

    Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al

    2020  Volume 196, Issue 10, Page(s) 856–867

    Abstract: Background: Magnetic resonance imaging (MRI) and amino acid positron-emission tomography (PET) of the brain contain a vast amount of structural and functional information that can be analyzed by machine learning algorithms and radiomics for the use of ... ...

    Abstract Background: Magnetic resonance imaging (MRI) and amino acid positron-emission tomography (PET) of the brain contain a vast amount of structural and functional information that can be analyzed by machine learning algorithms and radiomics for the use of radiotherapy in patients with malignant brain tumors.
    Methods: This study is based on comprehensive literature research on machine learning and radiomics analyses in neuroimaging and their potential application for radiotherapy in patients with malignant glioma or brain metastases.
    Results: Feature-based radiomics and deep learning-based machine learning methods can be used to improve brain tumor diagnostics and automate various steps of radiotherapy planning. In glioma patients, important applications are the determination of WHO grade and molecular markers for integrated diagnosis in patients not eligible for biopsy or resection, automatic image segmentation for target volume planning, prediction of the location of tumor recurrence, and differentiation of pseudoprogression from actual tumor progression. In patients with brain metastases, radiomics is applied for additional detection of smaller brain metastases, accurate segmentation of multiple larger metastases, prediction of local response after radiosurgery, and differentiation of radiation injury from local brain metastasis relapse. Importantly, high diagnostic accuracies of 80-90% can be achieved by most approaches, despite a large variety in terms of applied imaging techniques and computational methods.
    Conclusion: Clinical application of automated image analyses based on radiomics and artificial intelligence has a great potential for improving radiotherapy in patients with malignant brain tumors. However, a common problem associated with these techniques is the large variability and the lack of standardization of the methods applied.
    MeSH term(s) Brain Neoplasms/diagnostic imaging ; Brain Neoplasms/radiotherapy ; Brain Neoplasms/secondary ; Brain Neoplasms/surgery ; Computational Biology ; DNA Methylation ; DNA Modification Methylases/genetics ; DNA Repair Enzymes/genetics ; Deep Learning ; Diagnosis, Differential ; Glioblastoma/diagnostic imaging ; Glioblastoma/radiotherapy ; Glioma/diagnostic imaging ; Glioma/pathology ; Glioma/radiotherapy ; Humans ; Image Processing, Computer-Assisted/methods ; Imaging Genomics ; Isocitrate Dehydrogenase/genetics ; Magnetic Resonance Imaging ; Neoplasm Grading ; Neoplasm Proteins/genetics ; Neoplasm Recurrence, Local ; Neuroimaging/methods ; Positron-Emission Tomography ; Progression-Free Survival ; Promoter Regions, Genetic/genetics ; Radiation Oncology/methods ; Radiation Oncology/trends ; Radiosurgery ; Radiotherapy Planning, Computer-Assisted ; Sensitivity and Specificity ; Tumor Suppressor Proteins/genetics
    Chemical Substances Neoplasm Proteins ; Tumor Suppressor Proteins ; IDH2 protein, human (EC 1.1.1.41) ; Isocitrate Dehydrogenase (EC 1.1.1.41) ; IDH1 protein, human (EC 1.1.1.42.) ; DNA Modification Methylases (EC 2.1.1.-) ; MGMT protein, human (EC 2.1.1.63) ; DNA Repair Enzymes (EC 6.5.1.-)
    Language English
    Publishing date 2020-05-11
    Publishing country Germany
    Document type Journal Article ; Review
    ZDB-ID 84983-2
    ISSN 1439-099X ; 0179-7158 ; 0039-2073
    ISSN (online) 1439-099X
    ISSN 0179-7158 ; 0039-2073
    DOI 10.1007/s00066-020-01626-8
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