Read article: Dose tracking during radiotherapy could enable safer cancer treatments
Ionizing radiation acoustic imaging can monitor dose deposition during radiotherapy, helping to guide treatments in real time
Read article: High-energy physics devices adapted for electron FLASH dosimetry
Beam current transformers used in high-energy physics experiments prove suitable for accurate monitoring of electron FLASH beams
Read article: Patient positioning chair paves the way for upright radiotherapy
Upright radiotherapy, enabled by an effective patient positioning system, could improve treatment delivery and patient outcome for several tumour locations
Read article: THETIS phantom detects image distortions to support MR-based treatment planning
German QA specialist LAP and Siemens Healthineers have co-developed a versatile phantom to counter the effects of MR image distortion in radiotherapy treatment planning
Read article: MRI guidance reduces side effects of prostate cancer radiotherapy
First randomized trial reveals that tighter margins enabled by MRI-guided radiotherapy significantly reduce toxicity after prostate cancer treatments
Read article: A sheet of quantum dots enhances Cherenkov imaging of radiotherapy dose
A flexible, non-toxic sheet of carbon quantum dots attached to the patient improves the quality of Cherenkov images used for real-time radiotherapy verification
Read article: Will ultrahigh dose rates transform radiotherapy in a FLASH?
Researchers meet up in London to discuss the pipeline for moving FLASH radiotherapy from basic research into the clinic
Read article: Photons, protons or electrons: which will bring FLASH radiotherapy to the clinic?
A balloon debate at the FRPT 2022 conference pondered which particle offers most promise for clinical implementation of FLASH radiotherapy
Read article: Biological model reveals best way to deliver thermoradiotherapy
The cancer treatment thermoradiotherapy is most effective with high temperatures and short time intervals between heating and irradiation
Read article: Deep-learning system identifies difficult-to-detect brain metastases
A deep-learning-based computer-aided detection system reveals brain metastases that the human eye cannot reliably discern
