Publications by authors named "J Wiersma"
Clinical implementation of RTT-only CBCT-guided online adaptive focal radiotherapy for bladder cancer.
Clin Transl Radiat Oncol
January 2025
Purpose: The study assesses the clinical implementation of radiation therapist (RTT)-only Conebeam CT (CBCT)-guided online adaptive focal radiotherapy (oART) for bladder cancer, by describing the training program, analyzing the workflow and monitoring patient experience.
Materials And Methods: Bladder cancer patients underwent treatment (20 sessions) on a ring-based linac (Ethos, Varian, a Siemens Healthineers Company, USA). Commencing April 2021, 14 patients were treated by RTTs supervised by the Radiation Oncologist (RO) and Medical Physics Expert (MPE) in a multidisciplinary workflow.
End-use and processing traits in wheat (Triticum aestivum L.) are crucial for varietal development but are often evaluated only in the advanced stages of the breeding program due to the amount of grain needed and the labor-intensive phenotyping assays. Advances in genomic resources have provided new tools to address the selection for these complex traits earlier in the breeding process.
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- - In 2020, wheat saw significant advancements with the launch of HB4, a drought-resistant variety approved for commercial cultivation in Argentina, marking a breakthrough after years of slow genetic modification adoption due to consumer resistance and trade barriers.
- - The paper highlights a need for a new regulatory framework to promote genetic technologies in wheat, as current discussions around modern breeding could help overcome historical reluctance from consumers and boost private R&D investments.
- - It emphasizes the importance of understanding the risks and benefits of biotechnological approaches, like transgenic and genome editing, to develop climate-resilient wheat varieties essential for an increasing global population.
Purpose: Early and accurate assessment of distal radius fractures (DRFs) is crucial for optimal prognosis. Identifying fractures likely to lose threshold alignment (instability) in a cast is vital for treatment decisions, yet prediction tools' accuracy and reliability remain challenging. Artificial intelligence (AI), particularly Convolutional Neural Networks (CNNs), can evaluate radiographic images with high performance.
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