Martha Foltyn-Dumitru

• Doctor of Medicine
• Medical Doctor at University of Bonn

Background Glioblastoma (GB) heterogeneity poses substantial challenges for diagnosis and treatment. IDH-wildtype GB may lack contrast enhancement on MRI and exhibit a "low-grade radiologic appearance" (non-CE GB), a phenomenon with unclear clinical implications. This study investigates the histopathological and molecular differences and survival o...

Objectives Double-dose contrast-enhanced brain imaging improves tumor delineation and detection of occult metastases but is limited by concerns about gadolinium-based contrast agents' effects on patients and the environment. The purpose of this study was to test the benefit of a deep learning–based contrast signal amplification in true single-dose...

Background This study aimed to explore the potential of the Advanced Data Analytics (ADA) package of GPT-4 to autonomously develop Machine-Learning Models (ML) for predicting glioma molecular types using radiomics from MRI. Methods Radiomic features were extracted from preoperative MRI of n=615 newly diagnosed glioma patients to predict glioma mol...

Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive computing, posing a big barrier to their adoption in clinical practice. In this work, we organized the first international competition dedicated to promptable medical image...

Objectives Small lesions are the limiting factor for reducing gadolinium-based contrast agents in brain magnetic resonance imaging (MRI). The purpose of this study was to compare the sensitivity and precision in metastasis detection on true contrast-enhanced T1-weighted (T1w) images and artificial images synthesized by a deep learning method using...

Apart from the traditional definition of IDH-wildtype GBM based on histological characteristics, IDH-wildtype diffuse gliomas previously assigned to histological grade 2 or 3 are now defined as IDH-wildtype GBM in the presence of qualifying molecular markers (TERTp mutation, EGFR amplification, or chromosome +7/-10) (“molecular GBM”) in the 2021 WH...

BACKGROUND Artificial intelligence (AI) and machine learning (ML) are in the process of being integrated into modern healthcare, especially in imaging data-dependent fields like Radiology. Unfortunately, data shows that the acquaintance of physicians and medical students with AI is far from sufficient. Therefore, we implemented an educational chapt...

Artificial intelligence (AI) models often face performance drops after deployment to external datasets. This study evaluated the potential of a novel data augmentation framework based on generative adversarial networks (GANs) that creates synthetic patient image data for model training to improve model generalizability. Model development and extern...

The growing use of artificial neural network (ANN) tools for computed tomography angiography (CTA) data analysis underscores the necessity for elevated data protection measures. We aimed to establish an automated defacing pipeline for CTA data. In this retrospective study, CTA data from multi-institutional cohorts were utilized to annotate facemask...

Objectives This study examines clustering based on shape radiomic features and tumor volume to identify IDH-wildtype glioma phenotypes and assess their impact on overall survival (OS). Materials and methods This retrospective study included 436 consecutive patients diagnosed with IDH-wt glioma who underwent preoperative MR imaging. Alongside the t...

Background The purpose of this study was to elucidate the relationship between distinct brain regions and molecular subtypes in glioblastoma (GB), focusing on integrating modern statistical tools and molecular profiling to better understand the heterogeneity of Isocitrate Dehydrogenase wild-type (IDH-wt) gliomas. Methods This retrospective study c...

Purpose To propose a novel recursive partitioning analysis (RPA) classification model in patients with IDH-wildtype glioblastomas that incorporates the recently expanded conception of the extent of resection (EOR) in terms of both supramaximal and total resections. Experimental Design This multicenter cohort study included a developmental cohort o...

Gliomas are the most common malignant primary brain tumors in adults and one of the deadliest types of cancer. There are many challenges in treatment and monitoring due to the genetic diversity and high intrinsic heterogeneity in appearance, shape, histology, and treatment response. Treatments include surgery, radiation, and systemic therapies, wit...

Background This study investigates the influence of diffusion-weighted Magnetic Resonance Imaging (DWI-MRI) on radiomic-based prediction of glioma types according to molecular status and assesses the impact of DWI intensity normalization on model generalizability. Methods Radiomic features, compliant with image biomarker standardization initiative...

For CNS lymphomas (CNSL), there is a high need for minimally invasive and easily obtainable diagnostic markers. Intrathecal IgM synthesis can easily be determined in routine CSF diagnostics. The aim of this study was to systematically investigate the diagnostic potential of intrathecal IgM synthesis in primary and secondary CNSL (PCNSL and SCNSL)....

Background: While the association between diffusion and perfusion MRI and survival in glioblastoma is established, prognostic models for patients are lacking. This study employed clustering of functional imaging to identify distinct functional phenotypes in untreated glioblastomas, assessing their prognostic significance for overall survival. Met...

The fifth edition of the World Health Organization classification of central nervous system tumors published in 2021 reflects the current transitional state between traditional classification system based on histopathology and the state‐of‐the‐art molecular diagnostics. This Part 3 Review focuses on the molecular diagnostics and imaging findings of...

Objectives: Radiomic features have demonstrated encouraging results for non-invasive detection of molecular biomarkers, but the lack of guidelines for pre-processing MRI-data has led to poor generalizability. Here, we assessed the influence of different MRI-intensity normalization techniques on the performance of radiomics-based models for predict...

Deep learning segmentation algorithms can produce reproducible results in a matter of seconds. However, their application to more complex datasets is uncertain and may fail in the presence of severe structural abnormalities—such as those commonly seen in stroke patients. In this investigation, six recent, deep learning-based hippocampal segmentatio...

The fifth edition of the World Health Organization (WHO) classification of central nervous system tumors published in 2021 advances the role of molecular diagnostics in the classification of gliomas by emphasizing integrated diagnoses based on histopathology and molecular information and grouping tumors based on genetic alterations. Importantly, mo...

The fifth edition of the World Health Organization (WHO) classification of central nervous system tumors published in 2021 advances the role of molecular diagnostics in the classification of gliomas by emphasizing integrated diagnoses based on histopathology and molecular information and grouping tumors based on genetic alterations. This Part 2 rev...

Background Pseudoprogression (PsPD) is a major diagnostic challenge in the follow-up of patients with glioblastoma (GB) after chemo-radiotherapy (CRT). Conventional imaging signs and parameters derived from diffusion and perfusion-MRI have yet to prove their reliability in clinical practice for an accurate differential diagnosis. Here, we tested th...

Background To assess whether AI-based decision support allows more reproducible and standardized assessment of treatment response on MRI in neuro-oncology as compared to manual 2-dimensional measurements of tumor burden using the RANO criteria. Methods A series of 30 patients (15 lower-grade gliomas, 15 glioblastoma) with availability of consecuti...

Background Gadolinium-based contrast agents (GBCAs) are widely used to enhance tissue contrast during MRI scans and play a crucial role in the management of patients with cancer. However, studies have shown gadolinium deposition in the brain after repeated GBCA administration with yet unknown clinical significance. We aimed to assess the feasibilit...

Recent technological advances in molecular diagnostics through liquid biopsies hold the promise to repetitively monitor tumor evolution and treatment response of brain malignancies without the need of invasive surgical tissue accrual. Here, we implemented a mass spectrometry‐based protein analysis pipeline which identified hundreds of proteins in 2...

Background We studied the effects of endovascular treatment (EVT) and the impact of the extent of recanalization on cerebral perfusion and oxygenation parameters in patients with acute ischemic stroke (AIS) and large vessel occlusion (LVO). Methods Forty-seven patients with anterior LVO underwent computed tomography perfusion (CTP) before and imme...

Background and Purpose This study assessed the predictive performance and relative importance of clinical, multimodal imaging, and angiographic characteristics for predicting the clinical outcome of endovascular treatment for acute ischemic stroke. Methods A consecutive series of 246 patients with acute ischemic stroke and large vessel occlusion i...

Background Relevance of antiangiogenic treatment with bevacizumab in patients with glioblastoma is controversial because progression-free survival benefit did not translate into an overall survival (OS) benefit in randomized phase III trials. Purpose To perform longitudinal characterization of intratumoral angiogenesis and oxygenation by using dyna...

Background: This study validated a previously described diffusion-MRI phenotype as a potential predictive imaging biomarker in patients with recurrent glioblastoma receiving bevacizumab (BEV). Methods: A total of 396/596 patients (66%) from the prospective randomized phase II/III EORTC-26101 trial (with n=242 in the BEV and n=154 in the non-BEV...

Objective This study aimed to assess the validity and pathophysiology of the T2/FLAIR mismatch sign for non-invasive identification of IDH-mutant 1p/19q non-codeleted glioma. Methods MRI scans from 408 consecutive patients with newly diagnosed glioma (113 lower-grade glioma and 295 glioblastoma) were evaluated for the presence of T2/FLAIR-mismatch...

OBJECTIVE To assess the validity and pathophysiology of the T2/FLAIR mismatch sign for non-invasive identification of IDH-mutant 1p/19q non-codeleted glioma. METHODS MRI scans from 408 consecutive patients with newly diagnosed glioma (113 lower-grade glioma and 295 glioblastoma) were evaluated for the presence of a T2/FLAIR-mismatch sign (defined...

Background: 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 restri...

Background: Despite significant advances in the understanding of glioblastoma genetics and biology, survival is still poor. Hypoxia and nutrient depletion in the tumour microenvironment induce adaptive signalling and metabolic responses, which can influence sensitivity to therapeutic regimens. DNA damage-inducible transcript 4 (DDIT4) is a protein...

Glioblastomas are characterized by fast uncontrolled growth leading to hypoxic areas and necrosis. Signalling from EGFR via mammalian target of rapamycin complex 1 (mTORC1) is a major driver of cell growth and proliferation and one of the most commonly altered signalling pathways in glioblastomas. Therefore, epidermal growth factor receptor and mTO...

Glioblastomas (GBs) are characterized by a fast uncontrolled growth leading to hypoxic areas and necrosis. Signalling from epidermal growth factor receptor (EGFR) via mammalian target of rapamycin complex 1 (mTORC1) is one of the most commonly altered signalling pathways in GBs. Therefore, EGFR and mTORC1 signalling are plausible targets for GB the...

Glioblastoma (GB) is an incurable brain cancer with median survival of less than one year in unselected cohorts. Current treatment of recurrent tumors frequently involves the VEGF-A-targeting antibody bevacizumab that causes local therapeutic hypoxia. After initial chemotherapy activating mutations in the Akt-mTORC1 signaling pathway have been show...

Glioblastoma is an incurable brain cancer with median survival of less than 1 year in unselected cohorts. Current treatment options include surgical resection and radiotherapy, alkylating chemotherapy with temozolomide or nitrosoureas. Hypoxia and nutrient depletion in the tumor microenvironment are thought to induce alterations of signaling and me...