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9. Quality and safety of coronary computed tomography angiography at academic and non-academic sites: insights from a large European registry (ESCR MR/CT Registry)

Author

Foldyna, Borek, Uhlig, Johannes, Gohmann, Robin, Lücke, Christian, Mayrhofer, Thomas, Lehmkuhl, Lukas, Natale, Luigi, Vliegenthart, Rozemarijn, Lotz, Joachim, Salgado, Rodrigo, Francone, Marco, Loewe, Christian, Nikolaou, Konstantin, Bamberg, Fabian, Maintz, David, Maurovich-Horvat, Pal, Thiele, Holger, Hoffmann, Udo, and Gutberlet, Matthias

Published
2022
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20. Sunitinib for Metastatic Renal Cell Carcinoma: Real-World Data from the STAR-TOR Registry and Detailed Literature Review.

Author

Uhlig, Annemarie, Bergmann, Lothar, Bögemann, Martin, Fischer, Thomas, Goebell, Peter J., Leitsmann, Marianne, Reichert, Mathias, Rink, Michael, Schlack, Katrin, Trojan, Lutz, Uhlig, Johannes, Woike, Michael, and Strauß, Arne

Subjects
RENAL cell carcinoma, LITERATURE reviews, SUNITINIB, KARNOFSKY Performance Status, IMMUNE checkpoint inhibitors
Abstract

Introduction: We evaluated the effectiveness and safety profile of the tyrosine kinase inhibitor sunitinib in patients with advanced or metastatic renal cell carcinoma (a/mRCC) in a real-world setting. Methods: We analyzed data of adult a/mRCC patients treated with sunitinib. Data were derived from the German non-interventional post-approval multicenter STAR-TOR registry (NCT00700258). Progression-free survival (PFS), overall survival (OS), and adverse events (AEs) were evaluated using descriptive statistics and survival analyses for the entire cohort and patient subgroups. Results: A total of 116 study sites recruited 702 patients treated with sunitinib (73.1% male; median age 68.0 years; median Karnofsky index 90%) between November 2010 and May 2020. The most frequent histological subtype was clear cell RCC (81.6%). Sunitinib was administered as first-line treatment in 83.5%, as second line in 11.7%, and as third line or beyond in 4.8% of the patients. Drug-related AEs and serious AEs were reported in 66.3% and 13.9% of the patients, respectively (most common AE: gastrointestinal disorders; 39.7% of all patients). Conclusions: This study adds further real-world evidence of the persisting relevance of sunitinib for patients with a/mRCC who cannot receive or tolerate immune checkpoint inhibitors. The study population includes a high proportion of patients with unfavorable MSKCC poor-risk score, but shows still good PFS and OS results, while the drug demonstrates a favorable safety profile. The STAR-TOR registry is also registered in the database of US library of medicine (NCT00700258). [ABSTRACT FROM AUTHOR]

Published
2024
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25. Acute adverse events in cardiac MR imaging with gadolinium-based contrast agents: results from the European Society of Cardiovascular Radiology (ESCR) MRCT Registry in 72,839 patients

Author

Uhlig, Johannes, Lücke, Christian, Vliegenthart, Rozemarijn, Loewe, Christian, Grothoff, Matthias, Schuster, Andreas, Lurz, Philipp, Jacquier, Alexis, Francone, Marco, Zapf, Antonia, Schülke, Christoph, Daniel Thomas, May, Matthias Stefan, Bremerich, Jens, Lotz, Joachim, Gutberlet, Matthias, and the ESCR MRCT Registry contributors

Published
2019
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40. Morphological Parameters of the Hip Joint and Its Relation to Gender, Joint Side and Age—A CT-Based Study.

Author

Hawellek, Thelonius, Meier, Marc-Pascal, Seitz, Mark-Tilman, Uhlig, Johannes, Hosseini, Ali Seif Amir, Beil, Frank Timo, Lehmann, Wolfgang, and Hubert, Jan

Subjects
HIP joint, ACETABULUM (Anatomy), REFERENCE values, HIP fractures, HIP osteoarthritis, FEMUR neck
Abstract

Background: Physiological reference values for morphological parameters of the hip (MPH) are of clinical importance for the treatment of painful, degenerated or fractured hip joints, as well as to detect morphological deformities, which could result in early osteoarthritis of the hip. Currently, sufficient data for MPH are lacking. Therefore, it remains unclear if age-dependent alterations in adult hip morphology are physiological and if there are side- and gender-dependent differences. The aim of the study was to analyze MPH according to gender, side and age in a large-scaled cohort by CT scans. Methods: A total of 1576 hip joints from 788 patients (female: 257, male: 531; mean age: 58.3 years (±18.9; 18–92 years)) were analyzed by CT. For all hips, acetabular anteversion (AcetAV); lateral centrum edge angle (LCE); acetabular index (AI); femoral neck version (FNV); centrum-collum-diaphyseal angle (CCD); and anterior alpha angle (AαA) were measured. Results: The mean values in this cohort were: AcetAV 20.5° (±6.9); LCE 40.8° (±8.8); AI 0.3° (±5.3); FNV 11.0° (±9.8); CCD 129.9° (±7.4); and AαA 41.2° (±7.7). There was a detectable side-specific difference for AcetAV (p = 0.001); LCE (p < 0.001); CCD (p < 0.001); and AαA (p < 0.001). All the analyzed parameters showed a significant gender-specific difference, except for AI (p = 0.37). There was a significant correlation between age and AcetAV (r = 0.17; p < 0.001); LCE (r = 0.39; p < 0.001); AI (r = −0.25; p < 0.001); CCD (r = −0.15; p < 0.001); and AαA (r = 0.09; p < 0.001), except FNV (p = 0.79). Conclusions: There are side-, gender- and age-specific alterations in hip morphology, which have to be considered in treating hip joint pathologies. [ABSTRACT FROM AUTHOR]

Published
2022
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42. Radiomic Features and Machine Learning for the Discrimination of Renal Tumor Histological Subtypes: A Pragmatic Study Using Clinical-Routine Computed Tomography

Author

Uhlig, Johannes Uhlig, Andreas Leha, Laura M. Delonge, Anna-Maria Haack, Brian Shuch, Hyun S. Kim, Felix Bremmer, Lutz Trojan, Joachim Lotz, and Annemarie

Subjects
renal cell carcinoma, computed tomography, image interpretation, computer-assisted, radiomics, machine learning
Abstract

This study evaluates the diagnostic performance of radiomic features and machine learning algorithms for renal tumor subtype assessment in venous computed tomography (CT) studies from clinical routine. Patients undergoing surgical resection and histopathological assessment of renal tumors at a tertiary referral center between 2012 and 2019 were included. Preoperative venous-phase CTs from multiple referring imaging centers were segmented, and standardized radiomic features extracted. After preprocessing, class imbalance handling, and feature selection, machine learning algorithms were used to predict renal tumor subtypes using 10-fold cross validation, assessed as multiclass area under the curve (AUC). In total, n = 201 patients were included (73.7% male; mean age 66 ± 11 years), with n = 131 clear cell renal cell carcinomas (ccRCC), n = 29 papillary RCC, n = 11 chromophobe RCC, n = 16 oncocytomas, and n = 14 angiomyolipomas (AML). An extreme gradient boosting algorithm demonstrated the highest accuracy (multiclass area under the curve (AUC) = 0.72). The worst discrimination was evident for oncocytomas vs. AML and oncocytomas vs. chromophobe RCC (AUC = 0.55 and AUC = 0.45, respectively). In sensitivity analyses excluding oncocytomas, a random forest algorithm showed the highest accuracy, with multiclass AUC = 0.78. Radiomic feature analyses from venous-phase CT acquired in clinical practice with subsequent machine learning can discriminate renal tumor subtypes with moderate accuracy. The classification of oncocytomas seems to be the most complex with the lowest accuracy.

Published
2020
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45. PD-1 targeted immunotherapy for advanced hepatocellular carcinoma: current utilization and outcomes in the USA.

Author

Uhlig, Johannes, Stein, Stacey, and Kim, Hyun S

Abstract

Objective: To evaluate the utilization and outcomes of PD-1-directed immunotherapy (PD-1 IMT) for advanced hepatocellular carcinoma. Methods: Patients with advanced hepatocellular carcinoma receiving systemic therapy and PD-1 IMT (nivolumab/pembrolizumab) were included from the Flatiron database. Overall survival (OS) was evaluated using multivariable Cox models with the following subgroup analyses: patients with data on clinical performance and liver function and patients receiving tyrosine kinase inhibitors. Results: n = 1770 patients were included (PD-1 IMT 19.3%). Overall, PD-1 IMT was associated with longer OS (hazard ratio [HR]: 0.57). This effect was robust across both subgroup analyses with HR: 0.72 (subgroup 1) and HR: 0.57 (subgroup 2). Conclusions: PD-1 IMT is increasingly used in clinical practice and associated with an OS benefit. [ABSTRACT FROM AUTHOR]

Published
2022
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46. A pragmatic radiomics and machine learning approach

Author

Uhlig, Johannes, Biggemann, Lorenz, Nietert, Manuel M., Beißbarth, Tim, Lotz, Joachim, Kim, Hyun S., Trojan, Lutz, and Uhlig, Annemarie

Subjects
carcinoma, computer-assisted, image interpretation, machine learning, multidetector computed tomography, renal cell
Abstract

The aim of this study was to discriminate malignant and benign clinical T1 renal masses on routinely acquired computed tomography (CT) images using radiomics and machine learning techniques. Adult patients undergoing surgical resection and histopathological analysis of clinical T1 renal masses were included. Preoperative CT studies in venous phase from multiple referring centers were included, without restriction to specific CT scanners, slice thickness, or degrees of artifacts. Renalmasseswere segmented and 120 standardized radiomic features extracted. Machine learning algorithms were used to predictmalignancy of renal masses using radiomics features and cross-validation. Diagnostic accuracy of machine learningmodels and assessment by independent blinded radiologists were compared based on the gold standard of histopathologic diagnosis. A total of 94 patients met inclusion criteria (benign renal masses: n=18; malignant: n=76). CT studies from 18 different scanners were assessed with median slice thickness of 2.5mm and artifacts in 15 cases (15.9%). Area under the receiver-operating-characteristics curve (AUC) of random forest (random forest [RF], AUC=0.83) was significantly higher compared to the radiologists (AUC=0.68, P=.047). Sensitivity was significantly higher for RF versus radiologists (0.88 vs 0.80, P=.045), whereas specificity was numerically higher for RF (0.67 vs 0.50, P=.083). Although limited by an overall small sample size and few benign renal tumors, a radiomic features and machine learning approach suggests a high diagnostic accuracy for discrimination of malignant and benign clinical T1 renal masses on venous phase CT. The presented algorithm robustly outperforms human readers in a real-life scenario with nonstandardized imaging studies from various referring centers. Open-Access-Publikationsfonds 2020 peerReviewed

Published
2020

48. Hardware Implementation of an OPC UA Server for Industrial Field Devices.

Author

Bauer, Heiner, Hoppner, Sebastian, Iatrou, Chris, Charania, Zohra, Hartmann, Stephan, Rehman, Saif Ur, Dixius, Andreas, Ellguth, Georg, Walter, Dennis, Uhlig, Johannes, Neumarker, Felix, Berthel, Marc, Stolba, Marco, Kelber, Florian, Urbas, Leon, and Mayr, Christian

Subjects
FACTORIES, RASPBERRY Pi, INDUSTRY 4.0, COMMUNICATION infrastructure, INTERNET of things, FOOTPRINTS
Abstract

Industrial plants suffer from a high degree of complexity and incompatibility in their communication infrastructure, caused by a wild mix of proprietary technologies. This prevents transformation toward Industry 4.0 and the Industrial Internet of Things. Open platform communications unified architecture (OPC UA) is a standardized protocol that addresses these problems with uniform and semantic communication across all levels of the hierarchy. However, its adoption in embedded field devices, such as sensors and actuators, is still lacking due to prohibitive memory and power requirements of software implementations. We have developed a dedicated hardware engine that offloads processing of the OPC UA protocol and enables the realization of compact and low-power field devices with OPC UA support. As part of a proof-of-concept embedded system, we have implemented this engine in a 22-nm FDSOI technology, representing the first ASIC implementation of an OPC UA server. We measured performance, power consumption, and memory footprint of our test chip and compared it with a software implementation based on open62541 and a Raspberry Pi 2B. Our OPC UA hardware engine is 50 times more energy efficient and only requires 36 KiB of memory. The complete system consumes only 24 mW under full load, making it suitable for low-power embedded applications. [ABSTRACT FROM AUTHOR]

Published
2021
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49. Correlation of cone-beam breast-CT, digital breast tomosynthesis and full-field digital mammography with histopathology

Author

Wienbeck, Susanne, Uhlig, Johannes, Fischer, Uwe, Hellriegel, Martin, von Fintel, Eva, Kulenkampff, Dietrich, Surov, Alexey, Lotz, Joachim, and Perske, Christina

Subjects
Breast lesion
Abstract

To compare the accuracy of breast lesion size measurement of cone-beam breast-CT (CBBCT), digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM).Patients scheduled for mastectomy due to at least 1 malignant breast lesion were included. Mastectomy specimens were examined by CBBCT, DBT, FFDM, and histopathology.A total of 94 lesions (40 patients) were included. Histopathological analyses revealed 47 malignant, 6 high-risk, and 41 benign lesions. Mean histopathological lesion size was 20.8 mm (range 2-100). Mean absolute size deviation from histopathology was largest for FFDM (5.3 ± 6.7 mm) and smallest for CBBCT 50 mA, high-resolution mode (4.3 ± 6.7 mm). Differences between imaging modalities did not reach statistical significance (P = .85).All imaging methods tend to overestimate breast lesion size compared to histopathological gold standard. No significant differences were found regarding size measurements, although in tendency CBBCT showed better lesion detection and cT classification over FFDM. peerReviewed

Published
2019

50. A STROBE compliant study

Author

Strauss, Arne, Uhlig, Johannes, Lotz, Joachim, Trojan, Lutz, and Uhlig, Annemarie

Subjects
anatomy, nephrectomy, renal cell carcinoma, risk factors, survival analysis
Abstract

To assess whether left and right-sided renal cell carcinoma (RCC) carry side-specific outcomes.Surgically treated RCC patients were included from the United States Surveillance, Epidemiology and End Results database (Surveillance, Epidemiology and End Results database [SEER]; 2013 version) and the German Centre for Cancer Registry Data (ZfKD; 2000-2014). Bilateral RCC, those with missing RCC staging, follow-up time, and survival status were excluded. Cancer-specific survival (CSS) according to RCC side was compared using multivariable Cox regression.Seventeen thousand seven hundred nine SEER patients and 41,967 ZfKD patients were included. In both datasets, patients with left-sided RCC had higher T status and more often presented with nodal positive or metastatic disease. In the SEER dataset 1258 (14.33%) patients with left-sided RCC underwent lymphadenectomy (LAD), compared to 908 (10.17%) LADs in right-sided RCC (P

Published
2019

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