Jan Neumann

Dr. Jan Neumann

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Research Focus & Metrics

Academic Career Length

33Years (1994-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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3 April 2019 in BMC Cancer
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Journal Article
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CKCarolin Knebel
Carolin Knebel
JNJan Neumann
Jan Neumann
BSBenedikt J. Schwaiger
Benedikt J. Schwaiger
DKDimitrios Karampinos
Dimitrios Karampinos
DPDaniela Pfeiffer
Daniela Pfeiffer
AGAlexandra S. Gersing
Alexandra S. Gersing
To evaluate the diagnostic value of MR imaging for the differentiation of lipomas and atypical lipomatous tumors (ALT) in comparison with histology and MDM2 amplification status. Patients with well-differentiated lipomatous tumors (n = 113), of which 66 were diagnosed as lipoma (mean age 53 years (range, 13–82); 47% women) and 47 as atypical lipomatous tumor (ALT; mean age 60 years (range, 28–88); 64% women), were included into this study using histology and MDM2 amplification status by fluorescence in situ hybridization (FISH) as standard of reference. Preoperative MR images were retrospectively assessed by two radiologists for the following imaging features: maximum tumor diameter (mm) as well as the affected compartment (intramuscular, intermuscular or subcutaneous), septa (absent, thin (< 2 mm) or thick septa (> 2 mm) with nodular components); contrast enhancing areas within the lipomatous tumor (< 1/3 of the tumor volume, > 1/3 of the tumor volume); Of the 47 patients with ALT, 40 (85.1%) presented thick septa (> 2 mm) and this finding significantly increased the likelihood of ALT (OR 6.24, 95% CI 3.36–11.59; P < 0.001). The likelihood of ALT was increased if the tumor exceeded a maximum diameter of 130.0 mm (OR 2.74, 95% CI 1.82–4.11, P < 0.001). The presence of contrast enhancement in lipomatous tumors significantly increased the likelihood of ALT (Odds ratio (OR) 2.95, 95% confidence interval (CI) 2.01–4.31; P < 0.001). Of the lipomas, 21.1% were located subcutaneously, 63.6% intramuscularly and 15.2% intermuscularly. On the other hand, none of the ALTs were located subcutaneously, the majority was located intermuscularly (87.3%) and a small number of ALTs was located intramuscularly (12.7%). Our results suggest that using specific morphological MR imaging characteristics (maximum tumor diameter, thick septa and contrast enhancement) and the information on the localization of the lipomatous tumor, a high sensitivity and substantial specificity can be achieved for the diagnosis of lipomas and ALTs.

16 April 2021 in Cancers
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Journal Article
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JPJan Peeken
Jan Peeken
JNJan Neumann
Jan Neumann
RARebecca Asadpour
Rebecca Asadpour
YLYannik Leonhardt
Yannik Leonhardt
JMJoao R. Moreira
Joao R. Moreira
SCStephanie Combs
Stephanie Combs
Background: In patients with soft-tissue sarcomas of the extremities, the treatment decision is currently regularly based on tumor grading and size. The imaging-based analysis may pose an alternative way to stratify patients’ risk. In this work, we compared the value of MRI-based radiomics with expert-derived semantic imaging features for the prediction of overall survival (OS). Methods: Fat-saturated T2-weighted sequences (T2FS) and contrast-enhanced T1-weighted fat-saturated (T1FSGd) sequences were collected from two independent retrospective cohorts (training: 108 patients; testing: 71 patients). After preprocessing, 105 radiomic features were extracted. Semantic imaging features were determined by three independent radiologists. Three machine learning techniques (elastic net regression (ENR), least absolute shrinkage and selection operator, and random survival forest) were compared to predict OS. Results: ENR models achieved the best predictive performance. Histologies and clinical staging differed significantly between both cohorts. The semantic prognostic model achieved a predictive performance with a C-index of 0.58 within the test set. This was worse compared to a clinical staging system (C-index: 0.61) and the radiomic models (C-indices: T1FSGd: 0.64, T2FS: 0.63). Both radiomic models achieved significant patient stratification. Conclusions: T2FS and T1FSGd-based radiomic models outperformed semantic imaging features for prognostic assessment.


24 October 2018 in Skeletal Radiology
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Journal Article
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JNJan Neumann
Jan Neumann
JGJulio B. Guimaraes
Julio B. Guimaraes
UHUrsula Heilmeier
Ursula Heilmeier
GJGabby B. Joseph
Gabby B. Joseph
MNMichael C. Nevitt
Michael C. Nevitt
TLThomas M. Link
Thomas M. Link

1 March 1994 in Cartographica
Verified
Journal Article
Closed access
JNJan Neumann
Jan Neumann
This paper recalls promising attempts at the application of information theory in cartography and their denial by means of the concept of information increment generated in the course of map interpretation which is out of keeping with the principles of information theory. Critical analysis of the idea of information increment is presented, and applied information theory and topology are identified as a scientific environment facilitating explanation of this increment as an inherent attribute of a map. The paper introduces the topological information content of a map as an effective instrument for quantification of the increment mentioned and demonstrates its application in an experimental river basin map. Operation of this tool confirms that the concept of information increment is compatible with the principles of applied information theory which finds hardier usefulness in cartography.