Integrated MRI-guided radiotherapy—opportunities and challenges
MRI can help to categorize tissues as malignant or non-malignant both anatomically and
functionally, with a high level of spatial and temporal resolution. This non-invasive imaging …
functionally, with a high level of spatial and temporal resolution. This non-invasive imaging …
Roadmap: proton therapy physics and biology
The treatment of cancer with proton radiation therapy was first suggested in 1946 followed
by the first treatments in the 1950s. As of 2020, almost 200 000 patients have been treated …
by the first treatments in the 1950s. As of 2020, almost 200 000 patients have been treated …
Medical physics challenges in clinical MR-guided radiotherapy
The integration of magnetic resonance imaging (MRI) for guidance in external beam
radiotherapy has faced significant research and development efforts in recent years. The …
radiotherapy has faced significant research and development efforts in recent years. The …
Practical clinical workflows for online and offline adaptive radiation therapy
Adaptive radiotherapy emerged over 20 years ago and is now an established clinical
practice in a number of organ sites. No one solution for adaptive therapy exists. Rather …
practice in a number of organ sites. No one solution for adaptive therapy exists. Rather …
MRI-LINAC: A transformative technology in radiation oncology
Advances in radiotherapy technologies have enabled more precise target guidance,
improved treatment verification, and greater control and versatility in radiation delivery …
improved treatment verification, and greater control and versatility in radiation delivery …
Magnetic resonance‐guided radiation therapy: a review
Magnetic resonance‐guided radiation therapy (MRgRT) is a promising approach to
improving clinical outcomes for patients treated with radiation therapy. The roles of image …
improving clinical outcomes for patients treated with radiation therapy. The roles of image …
Deep convolution neural network (DCNN) multiplane approach to synthetic CT generation from MR images—application in brain proton therapy
Purpose The first aim of this work is to present a novel deep convolution neural network
(DCNN) multiplane approach and compare it to single-plane prediction of synthetic …
(DCNN) multiplane approach and compare it to single-plane prediction of synthetic …
DeepDose: Towards a fast dose calculation engine for radiation therapy using deep learning
We present DeepDose, a deep learning framework for fast dose calculations in radiation
therapy. Given a patient anatomy and linear-accelerator IMRT multi-leaf-collimator shape or …
therapy. Given a patient anatomy and linear-accelerator IMRT multi-leaf-collimator shape or …
Patient‐specific transfer learning for auto‐segmentation in adaptive 0.35 T MRgRT of prostate cancer: a bi‐centric evaluation
Background Online adaptive radiation therapy (RT) using hybrid magnetic resonance linear
accelerators (MR‐Linacs) can administer a tailored radiation dose at each treatment fraction …
accelerators (MR‐Linacs) can administer a tailored radiation dose at each treatment fraction …
Stability of radiomics features in apparent diffusion coefficient maps from a multi-centre test-retest trial
Quantitative radiomics features, extracted from medical images, characterize tumour-
phenotypes and have been shown to provide prognostic value in predicting clinical …
phenotypes and have been shown to provide prognostic value in predicting clinical …