Publications by authors named "Hannes Henry"

The increased knowledge regarding HPV-infections in head and neck squamous cell carcinoma (HNSCC) has unexpectedly contributed to several uncertainties related to i) prevalence diversities depending on tumour site and geographical origin of the patients, ii) proportion of HPV-driven tumours among HPV-DNA-positive cases, and iii) identification of patients with HPV-attributed survival benefit. To investigate this heterogeneity, we analysed 307 HNSCC cases (tonsillar, n=135; non-tonsillar, n=172) from eight health care centers mostly from Northern Germany and determined HPV-DNA/mRNA and p16INK4A-status and combined results with the patient outcome. Overall HPV-DNA prevalence rate was 23.

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It has been proposed that p16(INK4A) qualifies as a surrogate marker for viral oncogene activity in head and neck cancer (HNSCC). By analyzing 78 HNSCC we sought to validate the accuracy of p16(INK4A) as a reliable marker of active HPV infections in HNSCC. To this end we determined HPV DNA (HPVD) and E6*I mRNA (HPVR) expression status and correlated these results with p16(INK4A) staining.

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We sought to assess the possibility of using pharmacokinetic parameters as a predictor of response to benign prostatic hyperplasia (BPH) pharmacotherapy via a randomized, placebo-controlled, animal preclinical trial using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Twelve male beagles with BPH were enrolled in a preclinical experimental drug trial and divided into two randomized groups with six beagles each: one drug (finasteride) group and one placebo (control) group. Two baseline MRI examinations and three follow-ups during treatment were performed on a clinical 1.

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Objectives: We sought to evaluate the capabilities of different magnetic resonance imaging (MRI)-based methodologies for measuring prostate volume.

Materials And Methods: Twenty-four male beagles with benign prostatic hyperplasia were enrolled in a drug trial and imaged at 5 time points. A total of 120 prostate volumes were determined by MRI-based semiautomated segmentation.

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