4.5 Article

Voxel-based 3D MRI analysis helps to detect subtle forms of subcortical band heterotopia

Journal

EPILEPSIA
Volume 49, Issue 5, Pages 772-785

Publisher

BLACKWELL PUBLISHING
DOI: 10.1111/j.1528-1167.2007.01436.x

Keywords

subcortical band heterotopia; double cortex; cryptogenic focal epilepsy; MRI; postprocessing; cortical malformation; neuronal migration disorder

Ask authors/readers for more resources

Purpose: To evaluate the potential diagnostic value of a novel magnetic resonance image (MRI) postprocessing technique in subtle forms of subcortical band heterotopia (SBH). The method was introduced to improve the visualization of blurred gray-white matter junctions associated with focal cortical dysplasia but was found to be applicable also to SBH. Methods: In the voxel-based MRI analysis presented here, T-1-weighted MRI volume data sets are normalized and segmented using standard algorithms of SPM5. The distribution of gray and white matter is analyzed on a voxelwise basis and compared with a normal database of 150 controls. Based on this analysis, a three-dimensional feature map is created that highlights brain areas if their signal intensities fall within the range between normal gray and white matter and differ from the normal database in this respect. The method was applied to the MRI data of 378 patients with focal epilepsy in three different epilepsy centers. Results: SBH was diagnosed in seven patients with five of them showing subtle forms of SBH that had gone unrecognized in conventional visual analysis of MRI and were only detected by MRI postprocessing. In contrast to distinct double cortex syndrome, these patients had partial double cortex with SBH mostly confined to posterior brain regions. Conclusions: The results of this study suggest that a considerable part of cases with SBH might remain unrecognized by conventional MRI. Voxel-based MRI analysis may help to identify subtle forms and appears to be a valuable additional diagnostic tool in the evaluation of patients with cryptogenic epilepsy.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Clinical Neurology

Quantifying progression in primary progressive aphasia with structural neuroimaging

Jolina Lombardi, Benjamin Mayer, Elisa Semler, Sarah Anderl-Straub, Ingo Uttner, Jan Kassubek, Janine Diehl-Schmid, Adrian Danek, Johannes Levin, Klaus Fassbender, Klaus Fliessbach, Anja Schneider, Hans-Juergen Huppertz, Holger Jahn, Alexander Volk, Johannes Kornhuber, Bernhard Landwehrmeyer, Martin Lauer, Johannes Prudlo, Jens Wiltfang, Matthias L. Schroeter, Albert Ludolph, Markus Otto

Summary: PPA is a left-dominant disease with significant atrophy at baseline, primarily affecting gray matter and progressing in a variant-specific manner. The highest atrophy at baseline was found in the left frontal lobe for nfvPPA, left temporal lobe for svPPA, and (medial) temporal regions for lvPPA, with different patterns of progression within 1-year follow-up.

ALZHEIMERS & DEMENTIA (2021)

Review Clinical Neurology

Genotype-Phenotype Relations for the Atypical Parkinsonism Genes: MDSGene Systematic Review

Christina Wittke, Sonja Petkovic, Valerija Dobricic, Susen Schaake, Gesine Respondek, Anne Weissbach, Harutyun Madoev, Joanne Trinh, Eva-Juliane Vollstedt, Neele Kuhnke, Katja Lohmann, Marija Dulovic Mahlow, Connie Marras, Inke R. Koenig, Maria Stamelou, Vincenzo Bonifati, Christina M. Lill, Meike Kasten, Hans-Jurgen Huppertz, Guenter Hoeglinger, Christine Klein

Summary: This systematic review focuses on monogenic atypical parkinsonism with mutations in specific genes. An automated classification procedure was used to distinguish the different forms of monogenic atypical parkinsonism with high accuracy. Patients with monogenic atypical parkinsonism showed earlier onset and less favorable levodopa response compared to those with monogenic typical presentations.

MOVEMENT DISORDERS (2021)

Article Neurosciences

How to Arrange Follow-Up Time-Intervals for Longitudinal Brain MRI Studies in Neurodegenerative Diseases

Hans-Peter Mueller, Anna Behler, G. Bernhard Landwehrmeyer, Hans-Juergen Huppertz, Jan Kassubek

Summary: This theoretical study explores the impact of time-intervals in longitudinal imaging studies with one baseline and two follow-up visits on the results. Suggestions for analyzing longitudinal trends are provided based on simulations and analysis of atlas-based volumetry data of Huntington's disease patients.

FRONTIERS IN NEUROSCIENCE (2021)

Article Clinical Neurology

Fully automated detection of focal cortical dysplasia: Comparison of MPRAGE and MP2RAGE sequences

Theo Demerath, Christoph P. Kaller, Marcel Heers, Anke Staack, Ralf Schwarzwald, Tobias Kober, Marco Reisert, Andreas Schulze-Bonhage, Hans-Juergen Huppertz, Horst Urbach

Summary: The study showed that utilizing MP2RAGE sequences for FCD detection had higher sensitivity compared to using MPRAGE sequences. Additionally, incorporating cluster volume information helped differentiate between true and false positive results in MP2RAGE imaging.

EPILEPSIA (2022)

Article Clinical Neurology

Involvement of cortico-efferent tracts in flail arm syndrome: a tract-of-interest-based DTI study

Angela Rosenbohm, Kelly Del Tredici, Heiko Braak, Hans-Juergen Huppertz, Albert C. Ludolph, Hans-Peter Mueller, Jan Kassubek

Summary: The study utilized DTI data to investigate specific white matter alterations in flail arm syndrome patients, showing similarities in white matter integrity with 'classical' ALS patients. The results support the hypothesis that flail arm syndrome is a phenotypical variant of ALS.

JOURNAL OF NEUROLOGY (2022)

Review Clinical Neurology

Relationship of Genotype, Phenotype, and Treatment in Dopa-Responsive Dystonia: MDSGene Review

Anne Weissbach, Martje G. Pauly, Rebecca Herzog, Lisa Hahn, Sara Halmans, Feline Hamami, Christina Bolte, Sarah Camargos, Beomseok Jeon, Manju A. Kurian, Thomas Opladen, Norbert Brueggemann, Hans-Juergen Huppertz, Inke R. Koenig, Christine Klein, Katja Lohmann

Summary: By analyzing a large number of DRD patients and asymptomatic GCH1 mutation carriers, specific phenotypic and biochemical characteristics were identified, which can aid in the rapid diagnosis and initiation of treatment.

MOVEMENT DISORDERS (2022)

Article Clinical Neurology

Within a minute detection of focal cortical dysplasia

Horst Urbach, Marcel Heers, Dirk-Matthias Altenmueller, Andreas Schulze-Bonhage, Anke Maren Staack, Thomas Bast, Marco Reisert, Ralf Schwarzwald, Christoph P. Kaller, Hans-Juergen Huppertz, Theo Demerath

Summary: Automated MRI postprocessing tool was evaluated for enhanced and rapid detection of focal cortical dysplasia (FCD). The results showed effective identification of FCD within a minute, with a need for careful comparison with conventional MRI images to reduce false positives.

NEURORADIOLOGY (2022)

Article Clinical Neurology

Comparative analysis of machine learning algorithms for multi-syndrome classification of neurodegenerative syndromes

Leonie Lampe, Sebastian Niehaus, Hans-Juergen Huppertz, Alberto Merola, Janis Reinelt, Karsten Mueller, Sarah Anderl-Straub, Klaus Fassbender, Klaus Fliessbach, Holger Jahn, Johannes Kornhuber, Martin Lauer, Johannes Prudlo, Anja Schneider, Matthis Synofzik, Adrian Danek, Janine Diehl-Schmid, Markus Otto, Arno Villringer, Karl Egger, Elke Hattingen, Rudiger Hilker-Roggendorf, Alfons Schnitzler, Martin Sudmeyer, Wolfgang Oertel, Jan Kassubek, Gunter Hoeglinger, Matthias L. Schroeter

Summary: This study compared several machine learning methods for the classification of neurodegenerative diseases based on structural magnetic resonance imaging. The results showed that the neural network performed the best and most consistently, while the ensemble learning methods or support vector machine had better performance for smaller classes.

ALZHEIMERS RESEARCH & THERAPY (2022)

Article Genetics & Heredity

Large Phenotypic Variation of Individuals from a Family with a Novel ASPM Mutation Associated with Microcephaly, Epilepsy, and Behavioral and Cognitive Deficits

Randi von Wrede, Martin Schidlowski, Hans-Juergen Huppertz, Theodor Rueber, Anja Ivo, Tobias Baumgartner, Kerstin Hallmann, Gabor Zsurka, Christoph Helmstaedter, Rainer Surges, Wolfram S. Kunz

Summary: In this study, we identified a novel homozygous frame-shift mutation in ASPM gene in a consanguineous family, leading to microcephaly, epilepsy, and cognitive deficits. Our findings suggest that the severity of neurological symptoms in patients with ASPM mutations may be influenced by factors other than ASPM expression levels.

GENES (2022)

Article Clinical Neurology

Relationship of serum beta-synuclein with blood biomarkers and brain atrophy

Patrick Oeckl, Sarah Anderl-Straub, Adrian Danek, Janine Diehl-Schmid, Klaus Fassbender, Klaus Fliessbach, Steffen Halbgebauer, Hans-Juergen Huppertz, Holger Jahn, Jan Kassubek, Johannes Kornhuber, Bernhard Landwehrmeyer, Martin Lauer, Johannes Prudlo, Anja Schneider, Matthias L. Schroeter, Petra Steinacker, Alexander E. Volk, Matias Wagner, Juliane Winkelmann, Jens Wiltfang, Albert C. Ludolph, Markus Otto

Summary: Recent data support beta-synuclein as a blood biomarker for studying synaptic degeneration in Alzheimer's disease. This study compared serum beta-synuclein with established blood markers (p-tau181 and NfL) and found that beta-synuclein is increased in AD and correlated with temporal brain atrophy and cognitive impairment. The pattern of beta-synuclein changes differs from p-tau181 and NfL.

ALZHEIMERS & DEMENTIA (2023)

Review Clinical Neurology

Artificial intelligence for the detection of focal cortical dysplasia: Challenges in translating algorithms into clinical practice

Lennart Walger, Sophie Adler, Konrad Wagstyl, Leonie Henschel, Bastian David, Valeri Borger, Elke Hattingen, Hartmut Vatter, Christian E. Elger, Torsten Baldeweg, Felix Rosenow, Horst Urbach, Albert Becker, Alexander Radbruch, Rainer Surges, Martin Reuter, Fernando Cendes, Zhong Irene Wang, Hans-Juergen Huppertz, Theodor Rueber

Summary: Focal cortical dysplasias (FCDs) are common pathologies causing treatment-resistant focal epilepsy. Resective neurosurgery can be successful, but the visual assessment of magnetic resonance imaging is not always accurate in locating FCDs. Computational approaches using artificial intelligence show promise in automatic FCD detection. However, challenges remain in organizing imaging data, evaluating algorithmic output, and making research accessible and reproducible.

EPILEPSIA (2023)

Article Neuroimaging

Multiclass prediction of different dementia syndromes based on multi-centric volumetric MRI imaging

Leonie Lampe, Hans-Jurgen Huppertz, Sarah Anderl-Straub, Franziska Albrecht, Tommaso Ballarini, Sandrine Bisenius, Karsten Mueller, Sebastian Niehaus, Klaus Fassbender, Klaus Fliessbach, Holger Jahn, Johannes Kornhuber, Martin Lauer, Johannes Prudlo, Anja Schneider, Matthis Synofzik, Jan Kassubek, Adrian Danek, Arno Villringer, Janine Diehl-Schmid, Markus Otto, Matthias L. Schroeter

Summary: The study aimed to build a classifier for multiple dementia syndromes using MRI, and the results showed that the binary classification models achieved high prediction accuracies between 71% and 95%, with disease-specific atrophy patterns reflected in feature importance. The multi-syndrome model reached accuracies more than three times higher than chance level but was still far from 100%, and the performance varied across different dementia syndromes.

NEUROIMAGE-CLINICAL (2023)

Article Clinical Neurology

Diagnostic Accuracy of Epilepsy-dedicated MRI with Post-processing

Horst Urbach, Christian Scheiwe, Muskesh J. J. Shah, Julia M. M. Nakagawa, Marcel Heers, Maria Victoria San Antonio-Arce, Dirk-Matthias Altenmueller, Andreas Schulze-Bonhage, Hans-Juergen Huppertz, Theo Demerath, Soroush Doostkam

Summary: The purpose of this study was to evaluate the diagnostic accuracy of epilepsy-dedicated 3 Tesla MRI by correlating MRI, histopathology, and postsurgical seizure outcomes. The results showed that MRI and histopathology were concordant in most cases, but there were some cases where MRI missed certain lesions or showed false positives. The proposed MRI protocol was found to be highly accurate overall.

CLINICAL NEURORADIOLOGY (2023)

Article Clinical Neurology

Brain MRI in Progressive Supranuclear Palsy with Richardson's Syndrome and Variant Phenotypes

Mike Wattjes, Hans-Juergen Huppertz, Nima Mahmoudi, Sophia Stoecklein, Sophia Rogozinski, Florian Wegner, Martin Klietz, Ivayla Apostolova, Johannes Levin, Sabrina Katzdobler, Carsten Buhmann, Andrea Quattrone, Georg Berding, Matthias Brendel, Henryk Barthel, Osama Sabri, Guenter Hoeglinger, Ralph Buchert, Alzheimers Dis Neuroimaging Initiat

Summary: This study compared the value of different MRI reading strategies and automatic classification methods in the diagnosis of PSP. The results showed that the fully automatic classification method using support vector machine performed the best, especially in the diagnosis of vPSP. Therefore, it is recommended to use machine learning methods for fully automatic classification in settings with a broad phenotypic PSP spectrum.

MOVEMENT DISORDERS (2023)

Article Clinical Neurology

Automatic covariance pattern analysis outperforms visual reading of 18F-fluorodeoxyglucose-positron emission tomography (FDG-PET) in variant progressive supranuclear palsy

Ralph Buchert, Florian Wegner, Hans-Juergen Huppertz, Georg Berding, Matthias Brendel, Ivayla Apostolova, Carsten Buhmann, Alexander Dierks, Sabrina Katzdobler, Martin Klietz, Johannes Levin, Nima Mahmoudi, Andreas Rinscheid, Sophia Rogozinski, Jost-Julian Rumpf, Christine Schneider, Sophia Stoecklein, Phoebe G. Spetsieris, David Eidelberg, Mike P. Wattjes, Osama Sabri, Henryk Barthel, Guenter Hoeglinger

Summary: This study evaluated FDG-PET in a sample of 41 PSP patients and found that automatic covariance pattern analysis outperformed visual interpretation in detecting PSP-RS and provided useful sensitivity for vPSP. Pattern expression analysis is clinically useful in suspected PSP to complement visual reading and voxel-based testing.

MOVEMENT DISORDERS (2023)

No Data Available