All Outputs (2)

Machine learning-based predictions of gamma passing rates for virtual specific-plan verification based on modulation maps, monitor unit profiles, and composite dose images (2022)
Journal Article
Quintero, P., Benoit, D., Cheng, Y., Moore, C., & Beavis, A. (2022). Machine learning-based predictions of gamma passing rates for virtual specific-plan verification based on modulation maps, monitor unit profiles, and composite dose images. Physics in Medicine and Biology, 67(24), Article 245001. https://doi.org/10.1088/1361-6560/aca38a

Machine learning (ML) methods have been implemented in radiotherapy to aid virtual specific-plan verification protocols, predicting gamma passing rates (GPR) based on calculated modulation complexity metrics because of their direct relation to dose d... Read More about Machine learning-based predictions of gamma passing rates for virtual specific-plan verification based on modulation maps, monitor unit profiles, and composite dose images.

Bn2DT3A, a Chelator for 68Ga Positron Emission Tomography: Hydroxide Coordination Increases Biological Stability of [68Ga][Ga(Bn2DT3A)(OH)]− (2022)
Journal Article
Price, T. W., Renard, I., Prior, T. J., Kubíček, V., Benoit, D. M., Archibald, S. J., …Stasiuk, G. J. (2022). Bn2DT3A, a Chelator for 68Ga Positron Emission Tomography: Hydroxide Coordination Increases Biological Stability of [68Ga][Ga(Bn2DT3A)(OH)]−. Inorganic chemistry, 61(43), 17059–17067. https://doi.org/10.1021/acs.inorgchem.2c01992

The chelator Bn2DT3A was used to produce a novel 68Ga complex for positron emission tomography (PET). Unusually, this system is stabilized by a coordinated hydroxide in aqueous solutions above pH 5, which confers sufficient stability for it to be use... Read More about Bn2DT3A, a Chelator for 68Ga Positron Emission Tomography: Hydroxide Coordination Increases Biological Stability of [68Ga][Ga(Bn2DT3A)(OH)]−.