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Norbert Galldiks

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4 papers

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YNICL Journal 2020 Journal Article

Role of the default mode resting-state network for cognitive functioning in malignant glioma patients following multimodal treatment

Martin Kocher
Christiane Jockwitz
Svenja Caspers
Jan Schreiber
Ezequiel Farrher
Gabriele Stoffels
Christian Filss
Philipp Lohmann

BACKGROUND: Progressive cognitive decline following multimodal neurooncological treatment is a common observation in patients suffering from malignant glioma. Alterations of the default-mode network (DMN) represent a possible source of impaired neurocognitive functioning and were analyzed in these patients. METHODS: F]fluoroethyl)-L-tyrosine (FET) were simultaneously acquired to rs-fMRI on a hybrid MR/PET scanner. A cohort of 80 healthy subjects matched for gender, age, and educational status served as controls. RESULTS: The connectivity pattern within the DMN (12 nodes) of the glioma patients differed significantly from that of the healthy subjects but did not depend on age, tumor grade, time since treatment initiation, presence of residual/recurrent tumor, number of chemotherapy cycles received, or anticonvulsive medication. Small changes in the connectivity pattern were observed in patients who had more than one series of radiotherapy. In contrast, structural tissue changes located at or near the tumor site (including resection cavities, white matter lesions, edema, and tumor tissue) had a strong negative impact on the functional connectivity of the adjacent DMN nodes, resulting in a marked dependence of the connectivity pattern on tumor location. In the majority of neurocognitive domains, glioma patients performed significantly worse than healthy subjects. Correlation analysis revealed that reduced connectivity in the left temporal and parietal DMN nodes was associated with low performance in language processing and verbal working memory. Furthermore, connectivity of the left parietal DMN node also correlated with processing speed, executive function, and verbal as well as visual working memory. Overall DMN connectivity loss and cognitive decline were less pronounced in patients with higher education. CONCLUSION: Personalized treatment strategies for malignant glioma patients should consider the left parietal and temporal DMN nodes as vulnerable regions concerning neurocognitive outcome.

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YNICL Journal 2018 Journal Article

Combined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasis

Philipp Lohmann
Martin Kocher
Garry Ceccon
Elena K. Bauer
Gabriele Stoffels
Shivakumar Viswanathan
Maximilian I. Ruge
Bernd Neumaier

Background: F]fluoroethyl)-L-tyrosine (FET) PET for the differentiation between local recurrent brain metastasis and radiation injury since CE-MRI often remains inconclusive. Methods: = 33), local recurrent brain metastases were diagnosed in 21 patients (40%) and radiation injury in 31 patients (60%). Forty-two textural features were calculated on both unfiltered and filtered CE-MRI and summed FET PET images (20-40 min p.i.), using the software LIFEx. After feature selection, logistic regression models using a maximum of five features to avoid overfitting were calculated for each imaging modality separately and for the combined FET PET/MRI features. The resulting models were validated using cross-validation. Diagnostic accuracies were calculated for each imaging modality separately as well as for the combined model. Results: For the differentiation between radiation injury and recurrence of brain metastasis, textural features extracted from CE-MRI had a diagnostic accuracy of 81% (sensitivity, 67%; specificity, 90%). FET PET textural features revealed a slightly higher diagnostic accuracy of 83% (sensitivity, 88%; specificity, 75%). However, the highest diagnostic accuracy was obtained when combining CE-MRI and FET PET features (accuracy, 89%; sensitivity, 85%; specificity, 96%). Conclusions: Our findings suggest that combined FET PET/CE-MRI radiomics using textural feature analysis offers a great potential to contribute significantly to the management of patients with brain metastases.

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YNICL Journal 2018 Journal Article

Evaluation of factors influencing 18F-FET uptake in the brain

Antoine Verger
Carina Stegmayr
Norbert Galldiks
Axel Van Der Gucht
Philipp Lohmann
Gabriele Stoffels
Nadim J. Shah
Gereon R. Fink

PET using the amino-acid O-(2-18F-fluoroethyl)-l-tyrosine (18F-FET) is gaining increasing interest for brain tumour management. Semi-quantitative analysis of tracer uptake in brain tumours is based on the standardized uptake value (SUV) and the tumour-to-brain ratio (TBR). The aim of this study was to explore physiological factors that might influence the relationship of SUV of 18F-FET uptake in various brain areas, and thus affect quantification of 18F-FET uptake in brain tumours. Negative 18F-FET PET scans of 107 subjects, showing an inconspicuous brain distribution of 18F-FET, were evaluated retrospectively. Whole-brain quantitative analysis with Statistical Parametric Mapping (SPM) using parametric SUV PET images, and volumes of interest (VOIs) analysis with fronto-parietal, temporal, occipital, and cerebellar SUV background areas were performed to study the effect of age, gender, height, weight, injected activity, body mass index (BMI), and body surface area (BSA). After multivariate analysis, female gender and high BMI were found to be two independent factors associated with increased SUV of 18F-FET uptake in the brain. In women, SUVmean of 18F-FET uptake in the brain was 23% higher than in men (p<0. 01). SUVmean of 18F-FET uptake in the brain was positively correlated with BMI (r=0. 29; p<0. 01). The influence of these factors on SUV of 18F-FET was similar in all brain areas. In conclusion, SUV of 18F-FET in the normal brain is influenced by gender and weakly by BMI, but changes are similar in all brain areas.

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YNICL Journal 2017 Journal Article

The use of amino acid PET and conventional MRI for monitoring of brain tumor therapy

Norbert Galldiks
Ian Law
Whitney B. Pope
Javier Arbizu
Karl-Josef Langen

Routine diagnostics and treatment monitoring of brain tumors is usually based on contrast-enhanced MRI. However, the capacity of conventional MRI to differentiate tumor tissue from posttherapeutic effects following neurosurgical resection, chemoradiation, alkylating chemotherapy, radiosurgery, and/or immunotherapy may be limited. Metabolic imaging using PET can provide relevant additional information on tumor metabolism, which allows for more accurate diagnostics especially in clinically equivocal situations. This review article focuses predominantly on the amino acid PET tracers 11C-methyl-l-methionine (MET), O-(2-[18F]fluoroethyl)-l-tyrosine (FET) and 3, 4-dihydroxy-6-[18F]-fluoro-l-phenylalanine (FDOPA) and summarizes investigations regarding monitoring of brain tumor therapy.

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