Article
Medicine, General & Internal
Siddhesh P. Thakur, Matthew K. Schindler, Michel Bilello, Spyridon Bakas
Summary: This article introduces a computational approach that utilizes computer-aided detection (CAD) software to play a vital role in the diagnosis and treatment monitoring of Multiple Sclerosis (MS). The software can accurately detect disease activity and determine the necessity for injecting Gadolinium Based Contract Agents (GBCAs), providing reproducible and accurate clinical assessments, reducing adverse effects, and decreasing healthcare costs.
FRONTIERS IN MEDICINE
(2022)
Review
Clinical Neurology
Christopher Martin Allen, Ellen Mowry, Mar Tintore, Nikos Evangelou
Summary: Clinically isolated syndrome (CIS) is a single attack of inflammatory demyelination of the central nervous system, which can predict the development of multiple sclerosis. MRI scanning remains the most influential prognostic investigation during diagnosis, while multiple testing methods and medical history information also contribute to the diagnosis.
JOURNAL OF NEUROLOGY NEUROSURGERY AND PSYCHIATRY
(2021)
Article
Clinical Neurology
Marco Pisa, Tommaso Croese, Gloria Dalla Costa, Simone Guerrieri, Su-Chun Huang, Annamaria Finardi, Lorena Fabbella, Francesca Sangalli, Bruno Colombo, Lucia Moiola, Vittorio Martinelli, Giancarlo Comi, Roberto Furlan, Letizia Leocani
Summary: Optical coherence tomography (OCT) is increasingly important in evaluating patients with multiple sclerosis, showing neuro-retinal changes indicative of inflammatory and disease burden. Subclinical optic nerve involvement and thinning of ganglion cell layer in eyes without acute optic neuritis are associated with greater disease burden, reflecting early disease phases.
Review
Clinical Neurology
Massimiliano Calabrese, Damiano Marastoni, Francesco Crescenzo, Antonio Scalfari
Summary: This review discusses the challenges in diagnosing patients with the first demyelinating attack or RIS, focusing on the updated diagnostic criteria, considering neuroinflammatory conditions in the differential diagnosis, and identifying factors that predict MS development. Accurate interpretation of demyelinating attacks, MRI results, and the importance of cerebrospinal fluid examination are emphasized for an early and precise MS diagnosis to start timely disease-modifying therapy and improve long-term outcomes.
CURRENT OPINION IN NEUROLOGY
(2021)
Article
Neurosciences
Giordano Gentile, Mark Jenkinson, Ludovica Griffanti, Ludovico Luchetti, Matteo Leoncini, Maira Inderyas, Marzia Mortilla, Rosa Cortese, Nicola De Stefano, Marco Battaglini
Summary: In this study, a novel tool called BIANCA-MS is presented for brain white matter lesion segmentation in multiple sclerosis (MS). BIANCA-MS is able to generalize across different MRI acquisition protocols and heterogeneity of manually labeled data. It outperformed other available tools in high- and low-resolution images and provided comparable performance across different scanning protocols, sets of modalities, and image resolutions. The findings suggest that BIANCA-MS is a robust and accurate approach for automated MS lesion segmentation.
HUMAN BRAIN MAPPING
(2023)
Article
Medicine, Research & Experimental
Victor Chavarria, Guillermo Espinosa-Ramirez, Julio Sotelo, Jose Flores-Rivera, Omar Anguiano, Ana Campos Hernandez, Edgar Daniel Guzman-Rios, Aleli Salazar, Graciela Ordonez, Benjamin Pineda
Summary: This study investigates the predictors of conversion from Clinically Isolated Syndrome (CIS) to Clinical Definite Multiple Sclerosis (CDMS) in Mexican patients. Motor symptoms, multifocal syndromes, and alterations of somatosensory evoked potentials were associated with conversion to CDMS. The presence of at least one lesion on magnetic resonance imaging was the main factor associated with an increased risk of conversion to CDMS.
ARCHIVES OF MEDICAL RESEARCH
(2023)
Article
Clinical Neurology
Lukas Haider, Ferran Prados, Karen Chung, Olivia Goodkin, Baris Kanber, Carole Sudre, Marios Yiannakas, Rebecca S. Samson, Stephanie Mangesius, Alan J. Thompson, Claudia A. M. Gandini Wheeler-Kingshott, Olga Ciccarelli, Declan T. Chard, Frederik Barkhof
Summary: The study found that after 30 years, the greatest differences in MRI measures between SPMS and RRMS were the higher number of cortical lesions in SPMS and the lower grey matter volume in SPMS. This suggests that cortical involvement, in terms of lesions and atrophy, is the main correlate of progressive disease and disability in individuals with very long follow-up, indicating it should be the target of therapeutic interventions.
Article
Neuroimaging
Barbora Rehak Buckova, Jan Mares, Antonin Skoch, Jakub Kopal, Jaroslav Tintera, Robert Dineen, Kamila Rasova, Jaroslav Hlinka
Summary: This study used statistical and machine learning techniques to analyze multimodal neuroimaging data in order to discriminate between multiple sclerosis patients and healthy controls and predict motor disability scores in the patients. The study found a relationship between white and grey matter changes and motor impairment in multiple sclerosis.
BRAIN IMAGING AND BEHAVIOR
(2023)
Review
Immunology
Faezeh Moazami, Alain Lefevre-Utile, Costas Papaloukas, Vassili Soumelis
Summary: This review highlights the main applications of Machine Learning (ML) models in the field of Multiple Sclerosis (MS) using MRI data, categorizing them into four groups: Automated diagnosis, Prediction of disease progression, Differentiation of stages, and Distinction from similar disorders.
FRONTIERS IN IMMUNOLOGY
(2021)
Article
Medicine, General & Internal
Amjad I. AlTokhis, Abrar AlAmrani, Abdulmajeed Alotaibi, Anna Podlasek, Cris S. Constantinescu
Summary: Definite imaging predictors for long-term disability in multiple sclerosis (MS) are currently lacking. However, recent findings suggest that white matter lesion (WML) counts and volumes may be able to predict long-term disability in MS. A meta-analysis of studies found that T2 brain lesion counts and volumes were associated with disability progression after 10 years, with a significant association between the presence of four or more lesions at baseline and EDSS 3 and EDSS 6. These findings suggest that lesion counts and volumes could provide additional guidance in treatment decision making.
Article
Clinical Neurology
Susana Otero-Romero, Luciana Midaglia, Pere Carbonell-Mirabent, Maria Zuluaga, Ingrid Galan, Jordi Rio, Georgina Arrambide, Marta Rodriguez-Barranco, Angela Vidal-Jordana, Joaquin Castillo, Breogan Rodriguez-Acevedo, Ana Zabalza, Carlos Nos, Manuel Comabella-Lopez, Patricia Mulero, Cristina Auger, Jaume Sastre-Garriga, Santiago Perez-Hoyos, Alex Rovira, Xavier Montalban, Mar Tintore
Summary: In this study, the effect of menopause on disability accumulation in women with clinically isolated syndrome (CIS) was evaluated. Results indicated that menopause did not increase the risk of disability in this population when considering Expanded Disability Status Scale (EDSS) trajectories along with age and disease duration. The annual increase in EDSS was higher in menopausal women compared to nonmenopausal women, but this difference disappeared when controlling for age and disease duration.
EUROPEAN JOURNAL OF NEUROLOGY
(2022)
Article
Clinical Neurology
Carlos R. Camara-Lemarroy, Claudia Silva, Luanne M. Metz, Graziela Cerchiaro, Jamie Greenfield, Reza Dowlatabadi, Hans J. Vogel, Chieh-Hsin Lee, Fabrizio Giuliani, Maryam Nakhaei-Nejad, David K. B. Li, Anthony Traboulsee, V. Wee Yong
Summary: In this study, blood levels of various biomarkers were measured in individuals with early MS and CIS, revealing differences in cytokines, MMPs, serum metabolomics, and immune cell immunophenotyping between early MS/CIS patients and healthy controls. One biomarker, MMP-1, was identified as being able to differentiate early MS from CIS and was found to correlate with lesion volume on MRI. The immunological and metabolic profiles of CIS and early MS were found to be remarkably similar, suggesting a common underlying pathophysiological process.
MULTIPLE SCLEROSIS AND RELATED DISORDERS
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Jeroen Bleker, Derya Yakar, Bram van Noort, Dennis Rouw, Igle Jan de Jong, Rudi A. J. O. Dierckx, Thomas C. Kwee, Henkjan Huisman
Summary: The study showed that a radiomics-based bpMRI model trained on a single center does not generalize to multi-center data, while a multi-center trained model performs better and shows improved performance on multi-center data.
INSIGHTS INTO IMAGING
(2021)
Article
Medicine, General & Internal
Marcela de Oliveira, Marina Piacenti-Silva, Fernando Coronetti Gomes da Rocha, Jorge Manuel Santos, Jaime dos Santos Cardoso, Paulo Noronha Lisboa-Filho
Summary: This study proposes a method for automatic segmentation and volumetric quantification of brain lesions on MRIs of MS patients using two convolutional neural networks (CNNs). The results show that the proposed algorithm achieved accurate lesion detection and segmentation, and the quantification method can be valuable for treatment monitoring and clinical evaluation of MS patients.
Article
Clinical Neurology
Sarasa Tohyama, Jiwon Oh, Makenna Timm, Joshua C. Cheng, Aisha Halawani, David J. Mikulis, Andrew J. Solomon, Mojgan Hodaie
Summary: The relationship between trigeminal neuralgia (TN) and multiple sclerosis (MS) is well established, with many MS patients with TN showing MRI evidence of demyelinating lesion. There is confusion regarding whether TN should be considered a clinically isolated syndrome for the application of McDonald criteria. This case series highlights the need for data to guide the care of patients presenting with TN and additional MRI findings suggestive of MS.
MULTIPLE SCLEROSIS JOURNAL
(2023)
Article
Neuroimaging
Chen Niu, Alexander D. Cohen, Xin Wen, Ziyi Chen, Pan Lin, Xin Liu, Bjoern H. Menze, Benedikt Wiestler, Yang Wang, Ming Zhang
Summary: Resting-state functional MRI (rs-fMRI) is an important tool for studying brain physiology and predicting individual differences in task activation. The GLM-ML approach demonstrated in this study can accurately predict task activation based on rs-fMRI data and outperforms conventional methods.
BRAIN IMAGING AND BEHAVIOR
(2021)
Article
Oncology
Anne Berberich, Frederik Bartels, Zili Tang, Maximilian Knoll, Sonja Pusch, Nanina Hucke, Tobias Kessler, Zhen Dong, Benedikt Wiestler, Frank Winkler, Michael Platten, Wolfgang Wick, Amir Abdollahi, Dieter Lemke
FRONTIERS IN ONCOLOGY
(2020)
Article
Clinical Neurology
Tom Finck, Friederike Liesche-Starnecker, Monika Probst, Stefanie Bette, Viktoria Ruf, Christina Wendl, Franziska Dorn, Klemens Angstwurm, Juergen Schlegel, Claus Zimmer, Benedikt Wiestler, Isabel Wiesinger
ANNALS OF NEUROLOGY
(2020)
Article
Oncology
Friederike Liesche-Starnecker, Karoline Mayer, Florian Kofler, Sandra Baur, Friederike Schmidt-Graf, Johanna Kempter, Georg Prokop, Nicole Pfarr, Wu Wei, Jens Gempt, Stephanie E. Combs, Claus Zimmer, Bernhard Meyer, Benedikt Wiestler, Juergen Schlegel
Review
Oncology
Peter Hau, Didier Frappaz, Elizabeth Hovey, Martin G. McCabe, Kristian W. Pajtler, Benedikt Wiestler, Clemens Seidel, Stephanie E. Combs, Linda Dirven, Martin Klein, Antoinette Anazodo, Elke Hattingen, Silvia Hofer, Stefan M. Pfister, Claus Zimmer, Rolf-Dieter Kortmann, Marie-Pierre Sunyach, Ronan Tanguy, Rachel Effeney, Andreas von Deimling, Felix Sahm, Stefan Rutkowski, Anna S. Berghoff, Enrico Franceschi, Estela Pineda, Dagmar Beier, Ellen Peeters, Thierry Gorlia, Maureen Vanlancker, Jacoline E. C. Bromberg, Julien Gautier, David S. Ziegler, Matthias Preusser, Wolfgang Wick, Michael Weller
Summary: This study focuses on medulloblastoma in post-pubertal patients, discussing its rarity, treatment options, and clinical trial design. By comparing treatment with SMO inhibitors for SHH subgroup patients, the aim is to improve treatment efficacy, reduce toxicity, and provide guidance for future clinical trials.
Article
Medicine, General & Internal
Tom Finck, Julia Moosbauer, Monika Probst, Sarah Schlaeger, Madeleine Schuberth, David Schinz, Mehmet Yigitsoy, Sebastian Byas, Claus Zimmer, Franz Pfister, Benedikt Wiestler
Summary: This study demonstrates that AI-based triage of head CT scans can improve diagnostic accuracy and accelerate reporting for both experienced and inexperienced radiologists. By rapidly identifying normal scans, the tool can guide clinicians towards patients requiring urgent attention.
Article
Oncology
Christian D. Diehl, Steffi U. Pigorsch, Jens Gempt, Sandro M. Krieg, Silvia Reitz, Maria Waltenberger, Melanie Barz, Hanno S. Meyer, Arthur Wagner, Jan Wilkens, Benedikt Wiestler, Claus Zimmer, Bernhard Meyer, Stephanie E. Combs
Summary: Advancements in systemic cancer management have led to improved survival for multiple types of solid cancer, resulting in an increasing number of patients with brain metastases (BM). Resection is recommended for patients with single brain metastases and controlled primary disease, as well as cases requiring histopathologic diagnosis for cancer management decisions. However, local recurrence rates after surgery are high, necessitating adjuvant local radiation therapy (RT) to improve outcomes. Low-energy X-ray intraoperative radiation therapy (IORT) has emerged as a potential treatment option, offering local ablative treatment with steep dose gradients. This retrospective study describes the effectiveness and safety of IORT in 18 patients with resected brain metastases, supporting previous research findings.
Article
Oncology
Michael Griessmair, Claire Delbridge, Julian Ziegenfeuter, Denise Bernhardt, Jens Gempt, Friederike Schmidt-Graf, Olivia Kertels, Marie Thomas, Hanno S. Meyer, Claus Zimmer, Bernhard Meyer, Stephanie E. Combs, Igor Yakushev, Benedikt Wiestler, Marie-Christin Metz
Summary: By using advanced imaging and AI-based image processing, this study demonstrates significant differences in biological MR imaging metrics among molecularly defined glioma subgroups. The findings contribute to the understanding that fine tumor grading is possible through visualization of tumor biology with advanced MRI.
Article
Medicine, General & Internal
Sarah Schlaeger, Katharina Drummer, Malek El Husseini, Florian Kofler, Nico Sollmann, Severin Schramm, Claus Zimmer, Jan S. Kirschke, Benedikt Wiestler
Summary: In clinical practice, additional T2-weighted fat-saturated (T2-w fs) images are often missing in spine MRI due to time constraints or motion artifacts. This study aims to evaluate the diagnostic value of synthetic T2-w fs images generated by a generative adversarial network (GAN) in the clinical routine, using a heterogenous dataset to simulate the radiological workflow.
Article
Oncology
Wei Zhang, Sebastian Ille, Maximilian Schwendner, Benedikt Wiestler, Bernhard Meyer, Sandro M. Krieg
Summary: The use of intraoperative MRI in modern neurosurgery significantly reduces residual tumor volume and helps achieve comparable progression-free survival. This is true even for patients with unexpected residual tumor after initial resection.
Article
Oncology
Julian Ziegenfeuter, Claire Delbridge, Denise Bernhardt, Jens Gempt, Friederike Schmidt-Graf, Michael Griessmair, Marie Thomas, Hanno S. Meyer, Claus Zimmer, Bernhard Meyer, Stephanie E. Combs, Igor Yakushev, Benedikt Wiestler, Marie-Christin Metz
Summary: Reliable differentiation between true tumor progression and treatment-related changes in glioma patients is challenging. This study investigated the diagnostic performance of simultaneous and sequential acquisition of PET and MRI in 38 glioblastoma patients. The results showed no significant difference in global and local image metrics, as well as the diagnostic performance, between the two acquisition methods. This suggests that sequential acquisition is clinically and scientifically acceptable, supporting further research on multi-parametric models for personalized decision-making in neuro-oncology.
Article
Health Care Sciences & Services
Dennis M. Hedderich, Matthias Keicher, Benedikt Wiestler, Martin J. Gruber, Hendrik Burwinkel, Florian Hinterwimmer, Tobias Czempiel, Judith E. Spiro, Daniel Pinto dos Santos, Dominik Heim, Claus Zimmer, Daniel Rueckert, Jan S. Kirschke, Nassir Navab
Summary: Successful adoption of artificial intelligence in medical imaging requires medical professionals to understand underlying principles and techniques. The course on AI for Doctors: Medical Imaging aimed to fill the gap in tailored educational offerings, resulting in improved self-assessed skill ratings. However, a high dropout rate was observed, mainly due to time constraints of medical professionals.
Article
Oncology
Amir Kaywan Aftahy, Melanie Barz, Philipp Krauss, Arthur Wagner, Nicole Lange, Alaa Hijazi, Benedikt Wiestler, Bernhard Meyer, Chiara Negwer, Jens Gempt
Article
Oncology
A. Kaywan Aftahy, Melanie Barz, Philipp Krauss, Friederike Liesche, Benedikt Wiestler, Stephanie E. Combs, Christoph Straube, Bernhard Meyer, Jens Gempt
Article
Neuroimaging
Richard McKinley, Rik Wepfer, Lorenz Grunder, Fabian Aschwanden, Tim Fischer, Christoph Friedli, Raphaela Muri, Christian Rummel, Rajeev Verma, Christian Weisstanner, Benedikt Wiestler, Christoph Berger, Paul Eichinger, Mark Muhlau, Mauricio Reyes, Anke Salmen, Andrew Chan, Roland Wiest, Franca Wagner
NEUROIMAGE-CLINICAL
(2020)
