Publications by authors named "J Rennert"

Background Large language models have already demonstrated potential in medical text processing. GPT-4V, a large vision-language model from OpenAI, has shown potential for medical imaging, yet a quantitative analysis is lacking. Purpose To quantitatively assess the performance of GPT-4V in interpreting radiologic images using unseen data.

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This study uses magnetic resonance imaging (MRI) to investigate the potential of the hepatospecific contrast agent gadolinium ethoxybenzyl-diethylenetriaminepentaacetic acid (Gd-EOB-DTPA) in distinguishing G1- from G2/G3-differentiated hepatocellular carcinoma (HCC). Our approach involved analyzing the dynamic behavior of the contrast agent in different phases of imaging by signal intensity (SI) and lesion contrast (C), to surrounding liver parenchyma, and comparing it across distinct groups of patients differentiated based on the histopathological grading of their HCC lesions and the presence of liver cirrhosis. Our results highlighted a significant contrast between well- and poorly-differentiated lesions regarding the lesion contrast in the arterial and late arterial phases.

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The aim of this study was to evaluate if CT findings in patients with pulmonary Post Covid syndrome represent residua after acute pneumonia or if SARS-CoV 2 induces a true ILD. Consecutive patients with status post acute Covid-19 pneumonia and persisting pulmonary symptoms were enrolled. Inclusion criteria were availability of at least one chest CT performed in the acute phase and at least one chest CT performed at least 80 days after symptom onset.

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Aim: To evaluate the effectiveness of complementary imaging of high-resolution ultrasound including CEUS with PET/CT for tissue characterization and tumor detection.

Material And Methods: 100 patients were examined with PET/CT and US/CEUS between January 2018 until February 2020. All patients underwent PET/CT followed by selective US/CEUS within 4 weeks.

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