Klinische Forschung

Im Rahmen der klinischen Forschung erforschen, entwickeln und validieren wir neue bildgestützte Biomarker.

Wir kooperieren mit universitären Zentren, Kliniken und Forschungseinrichtungen und führen für die pharmazeutische Industrie und Unternehmen der Biotechnologie und Medizintechnik Studien der Phasen IIIb und IV durch.

Wissenschaftliche Publikationen

Ausgewählte Konferenzbeiträge finden Sie weiter unten.

Originalbeiträge in Fachzeitschriften

Buddenkotte T, Apostolova I, Opfer R, Krüger J, Klutmann S, Buchert R (2023) Automated identification of uncertain cases in deep learning‑based classification of dopamine transporter SPECT to improve clinical utility and acceptance Eur J Nucl Med Mol Imaging (2023).
PubMed

Krüger J, Opfer R, Spies L, Hedderich D, Buchert R (2023) Voxel-based morphometry in single subjects without a scanner-specific normal database using a convolutional neural network Eur Radiol (2023).
PubMed

Schlaeger S, Shit S, Eichinger P, Hamann M, Opfer R, Krüger J, Dieckmeyer M, Schön S, Mühlau M, Zimmer C, Kirschke J, Wiestler B, Hedderich D (2023) AI-based detection of contrast-enhancing MRI lesions in patients with multiple sclerosis Insights Into Imaging 14:123(2023).
PubMed

Behrendt F, Bengs M, Bhattacharya D, Krüger J, Opfer R, Schlaefer A (2023) A systematic approach to deep learning-based nodule detection in chest radiographs Scientific Reports 13(1):10120(2023).
PubMed

Opfer R, Krüger J, Spies L, Ostwaldt AC, Kitzler HH, Schippling S, Buchert R (2022) Automatic segmentation of the thalamus using a massively trained 3D convolutional neural network: higher sensitivity for the detection of reduced thalamus volume by improved inter-scanner stability. European Radiology(2022).
PubMed

Opfer R, Krüger J, Spies L, Kitzler HH, Schippling S, Buchert R (2022) Single‑subject analysis of regional brain volumetric measures can be strongly influenced by the method for head size adjustment. Neuroradiology(2022).
PubMed


Krüger J, Ostwaldt AC, Spies L, Geisler B, Schlaefer A, Kitzler HH, Schippling S, Opfer R (2021) Infratentorial lesions in multiple sclerosis patients: intra and inter‑rater variability in comparison to a fully automated segmentation using 3D convolutional neural networks. European Radiology(2021).
PubMed

Pawlitzki M, Horbrügger M, Loewe K, Kaufmann J, Opfer R, Wagner M, Al-Nosairy KO, Meuth SG, Hoffmann MB, Schippling S (2020) MS optic neuritis-induced long-term structural changes within the visual pathway. Neurol Neuroimmunol Neuroinflamm. 2020 Jan 22;7(2):e665.
PubMed

Opfer R, Krüger J, Spies L, Hamann M, Wicki CA, Kitzler H, Gocke C, Silva D, Schippling S (2020) Age-dependent cut-offs for pathological deep gray matter and thalamic volume loss using Jacobian integration. NeuroImage:Clinical 28:102478.
PubMed

Krüger J, Opfer R, Gessert N, Ostwaldt AC, Manogaran P, Kitzler H, Schlaefer A, Schippling S (2020) Fully automated longitudinal segmentation of new or enlarged multiple sclerosis lesions using 3D convolutional neural networks. NeuroImage:Clinical 28:102445.
PubMed

Gessert N, Krüger J, Opfer R, Ostwaldt AC, Manogaran P, Kitzler H, Schippling S, Schlaefer A (2020) Multiple sclerosis lesion activity segmentation with attention-guided two-path CNNs. Comput Med Imaging Graph. 84:101772.
PubMed

Raji A, Opfer R, Ostwaldt AC, Suppa P, Spies, L, Winkler G (2018) MRI-based brain volumetry at a single time point complements clinical evaluation of patients with multiple sclerosis in an outpatient setting. Front Neurol. 9:545.
PubMed

Buchert R, Lange C, Suppa P, Apostolova I, Spies L, Teipel S, Dubois B, Hampel H, Grothe MJ (2018) Magnetic resonance imaging-based hippocampus volume for prediction of dementia in mild cognitive impairment: Why does the measurement method matter so little? Alzheimers Dement. 14:976–978.
PubMed

Opfer R, Ostwaldt AC, Sormani MP, Gocke C, Walker-Egger C, Panogaran M, De Stefano N, Schippling S (2018) Estimates of age-dependent cut-offs for pathological brain volume loss using SIENA/FSL – A longitudinal brain volumetry study in healthy adults. Neurobiol Aging. 65:1-6.
PubMed

Opfer R, Ostwaldt AC, Walker-Egger C, Panogaran M, Sormani MP, De Stefano N, Schippling S (2018) Within patient fluctuation of brain volume estimates from shortterm repeated MRI measurements using SIENA/FSL. J Neurol. 265:1158-1165.
PubMed

Apostolova I, Lange C, Mäurer A, Suppa P, Spies L, Grothe MJ, Nierhaus T, Fiebach JB, Steinhagen-Thiessen E, Buchert R (2018) Hypermetabolism in the hippocampal formation of cognitively impaired patients indicates detrimental maladaptation. Neurobiol Aging. 65:41-50.
PubMed

Apostolova I, Lange C, Suppa P, Spies L, Klutmann S, Adam G, Grothe MJ, Buchert R (2017) Impact of plasma glucose level on the pattern of brain FDG uptake und the predictive power of FDG PET in mild cognitive impairment. Eur J Nucl Med Mol Imaging. 45:1417-1422.
PubMed

Lange C, Suppa P, Pietrzyk U, Makowski MR, Spies L, Peters O, Buchert R (2017) Prediction of Alzheimer's Dementia in Patients with Amnestic Mild Cognitive Impairment in Clinical Routine: Incremental Value of Biomarkers of Neurodegeneration and Brain Amyloidosis Added Stepwise to Cognitive Status. J Alzheimers Dis. 61:373-388.
PubMed

Levy Nogueira M, Samri D, Epelbaum S, Lista S, Suppa P, Spies L, Hampel H, Dubois B, Teichmann M (2017) Alzheimer's Disease Diagnosis Relies on a Twofold Clinical-Biological Algorithm: Three Memory Clinic Case Reports. J Alzheimers Dis. 60:577-583.
PubMed

Cavedo E, Suppa P, Lange C, Opfer R, Lista L, Galluzzi S, Schwarz AJ, Spies L, Buchert R, Hampel H (2017) Fully automatic MRI-based hippocampus volumetry using FSL-FIRST: intra-scanner test-retest stability, inter-field strength variability, and performance as enrichment biomarker for clinical trials using prodromal target populations at risk for Alzheimer's disease. J Alzheimers Dis. 60:151-164.
PubMed

Schippling S, Ostwaldt AC, Suppa P, Spies L, Manogaran P, Gocke C, Huppertz HJ und Opfer R (2017) Global and regional annual brain volume loss rates in physiological aging. J Neurol. 264:520-528.
PubMed

Egger C, Opfer R, Wang C, Kepp T, Sormani MP, Spies L, Barnett M und Schippling S (2017) MRI FLAIR lesion segmentation in Multiple Sclerosis: Does automated segmentation hold up with manual annotation? NeuroImage: Clinical. 13:264–270.
PubMed

Lange C, Suppa P, Mäurer A, Ritter K, Pietrzyk U, Steinhagen-Thiessen E, Fiebach JB, Spies L und Buchert R (2016) Mental speed is associated with the shape irregularity of white matter MRI hyperintensity load. Brain Imaging and Behavior. 11:1720-1730.
PubMed

Ritter K, Lange C, Weygandt M, Mäurer A, Roberts A, Estrella M, Suppa P, Spies L, Prasad V, Steffen I, Apostolova I, Bittner D, Gövercin M, Brenner W, Mende C, Peters O, Seybold J, Fiebach JB, Steinhagen-Thiessen E, Hampel H, Haynes JD und Buchert R (2016) Combination of structural MRI and FDG-PET of the brain improves diagnostic accuracy in newly manifested cognitive impairment in geriatric inpatients. J Alzheimers Dis. 54:1319–1331.
PubMed

Suppa P, Hampel H, Kepp T, Lange C, Spies L, Fiebach JB, Dubois B, Buchert R (2016) Performance of hippocampus volumetry with FSL-FIRST for prediction of Alzheimer's disease dementia in at risk subjects with amnestic mild cognitive impairment. J Alzheimers Dis. 51:867-873.
PubMed

Opfer R, Suppa P, Kepp T, Spies L, Schippling S und Huppertz HJ (2016) Atlas based brain volumetry: how to distinguish regional volume changes due to biological or physiological effects from inherent noise of the methodology. Magn Reson Imaging. 34:45-461.
PubMed

Lange C, Suppa P, Frings L, Brenner W, Spies L und Buchert R (2016) Optimization of Statistical Single Subject analysis of Brain FDG PET for the Prognosis of Mild Cognitive Impairment-to-Alzheimer’s Disease Conversion. J Alzheimers Dis. 49:945-959.
PubMed

Burkhardt T, Lüdecke D, Spies L, Wittmann W, Westphal M und Flitsch J (2015) Hippocampal and cerebellar atrophy in patients with Cushing’s disease. Neurosurg Focus. 39:E5
PubMed

Suppa P, Hampel H, Spies L, Fiebach J, Dubois B und Buchert R (2015) Fully automated atlas-based hippocampal volumetry for clinical routine: validation in subjects with mild cognitive impairment from the ADNI cohort. J Alzheimers Dis. 46:199–209.
PubMed

Suppa P, Anker U, Spies L, Bopp I, Rüegger-Frey B, Klaghofer R, Gocke C, Hampel H, Beck S und Buchert R (2015) Fully automated atlas-based hippocampal volumetry for detection of Alzheimer’s disease in a memory clinic setting. J Alzheimers Dis. 44:183–193.
PubMed

Boelmans K, Spies L, Sedlacik J, Fiehler J, Jahn H, Gerloff C, Münchau A. (2014) A novel computerized algorithm to detect microstructural brainstem pathology in Parkinson's disease using standard 3 Tesla MR imaging. J Neurol. 261:1968-75
PubMed

Spies L, Tewes A, Suppa P, Buchert R, Winkler G und Raji A. (2013) Fully automatic detection of deep white matter T1 hypointense lesions in multiple sclerosis. Phys Med Biol. 58:8323–37.
PubMed

Arlt S, Buchert R, Spies L, Eichenlaub M, Lehmbeck J und Jahn H. (2013) Association between fully automated MRI based volumetry of different brain regions and neuropsychological test performance in patients with mild cognitive impairment and Alzheimer's disease. Eur Arch Psychiatry Clin Neurosci. 263:335-44.
PubMed

Ausgewählte Konferenzbeiträge

Schuh K, Opfer R, Spies L (2020) QUANTUM - Quantitative and standardized imaging in daily clinical routine of MS patients AAN, Toronto, Canada
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Krüger J, Opfer R, Gessert N, Ostwaldt AC, Walker-Egger C, Manogaran P, Schlaefer A, Schippling S (2019) Fully automated longitudinal segmentation of new or enlarging Multiple Sclerosis(MS) lesions using 3D convolution neural networks. neuroRAD, Frankfurt a.M.
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Peters O, Suppa P, Haas B, Buchert R, Spies L, Heuser I (2016) Robustness of MRI-based volumetry for the prediction of short-term conversion from mild cognitive impairment to Alzheimer´s dementia. CTAD, San Diego, USA
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Opfer R, Suppa P, Spies L, Egger C, Schippling S (2016) Consistency of longitudinal brain volume loss assessment in MS using SIENA/FSL. ECTRIMS, London, UK
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Opfer R, Kepp T, Suppa P, Spies L, Egger C, Schippling S (2015) Assessing intra- and interscanner variability of automated brain volumetry using SPM12, SIENA, SIENAX. ECTRIMS, Barcelona, Spain
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