Publications by authors named "N Bachmann"
Purpose: Radiation therapy (RT) plays a key role in the management of esophageal cancer (EC). However, toxicities caused by proximity of organs at risk (OAR) and daily target coverage caused by interfractional anatomic changes are of concern. Daily online adaptive RT (oART) addresses these concerns and has the potential to increase OAR sparing and improve target coverage.
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- The study evaluated craniospinal irradiation (CSI) treatments using protons at the Paul Scherrer Institute, focusing on local recurrences and late toxicity outcomes for 71 patients, mostly children and young adults with tumors like medulloblastoma and ependymoma.
- Data from patients treated in both prone and supine positions were analyzed, revealing that supine positioning led to lower systematic and random errors in treatment setup, resulting in more accurate dosing.
- The research concluded that local failures in treatment were not linked to inaccuracies in radiation dosing, and there was no observed correlation between treatment-related toxicities and increased radiation effects.
Neo-adjuvant chemoradiotherapy (CRT) and perioperative chemotherapy are different strategies for treating non-metastatic esophageal cancer (EC). The advantages of neo-adjuvant therapies are primarily seen in patients who achieve a pathologic complete response (pCR) and therefore show higher survival rates and better prognosis. In general, less than one-third of patients with EC experience pCR after neo-adjuvant therapies; however, patients with esophageal adenocarcinoma (AC) demonstrate lower rates of pCR compared to those with esophageal squamous cell carcinoma (SCC), respectively.
View Article and Find Full Text PDFPancreatic intraepithelial neoplasias (PanINs) are the most common precursors of pancreatic cancer, but their small size and inaccessibility in humans make them challenging to study. Critically, the number, dimensions and connectivity of human PanINs remain largely unknown, precluding important insights into early cancer development. Here, we provide a microanatomical survey of human PanINs by analysing 46 large samples of grossly normal human pancreas with a machine-learning pipeline for quantitative 3D histological reconstruction at single-cell resolution.
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