Embedded Files
Hindocha, S., Charlton, T.G., Linton-Reid, K., Hunter, B., Chan, C., Ahmed, M., Robinson, E.J., Orton, M.R., Ahmad, S., McDonald, F., Locke, I., Power, D., Blackledge, M.D., Lee, R.W. & Aboagye, E.O. 2022. A comparison of machine learning methods for predicting recurrence and death after curative-intent radiotherapy for non-small cell lung cancer: Development and validation of multivariable clinical prediction models. EBioMedicine, 77, 103911.
Hindocha, S., Charlton, T.G., Linton-Reid, K., Hunter, B., Chan, C., Ahmed, M., Robinson, E.J., Orton, M.R., Ahmad, S., McDonald, F., Locke, I., Power, D., Blackledge, M.D., Lee, R.W. & Aboagye, E.O. 2022. Combined CT radiomics of primary tumour and metastatic lymph nodes improves prediction of recurrence following radiotherapy for non-small cell lung cancer. Lung Cancer, 165, pp.S59-S60.
Donners, R., Figueiredo, I., Tunariu, N., Blackledge, M.D., Koh, D.M., de la Maza, M.D.L.D.F., Chandran, K., de Bono, J.S. and Fotiadis, N., 2022. Multiparametric bone MRI can improve CT-guided bone biopsy target selection in cancer patients and increase diagnostic yield and feasibility of next-generation tumour sequencing. European Radiology, pp.1-10.
Kalantar, R., Messiou, C., Winfield, J.M., Renn, A., Latifoltojar, A., Downey, K., Sohaib, A., Lalondrelle, S., Koh, D.M. and Blackledge, M.D., 2021. CT-Based Pelvic T1-Weighted MR Image Synthesis Using UNet, UNet++ and Cycle-Consistent Generative Adversarial Network (Cycle-GAN). Frontiers in Oncology, p.3006.
Zormpas-Petridis, K., Tunariu, N., Curcean, A., Messiou, C., Curcean, S., Collins, D.J., Hughes, J.C., Jamin, Y., Koh, D.M. and Blackledge, M.D., 2021. Accelerating Whole-Body Diffusion-weighted MRI with Deep Learning–based Denoising Image Filters. Radiology: Artificial Intelligence, 3(5), p.e200279.
Donners, R., Yiin, R.S.Z., Blackledge, M. D. and Koh, D.M., 2021. Whole-body diffusion-weighted MRI of normal lymph nodes: prospective apparent diffusion coefficient histogram and nodal distribution analysis in a healthy cohort. Cancer Imaging, 21(1), pp.1-10.
Kalantar, R., Lin, G., Winfield, J.M., Messiou, C., Lalondrelle, S., Blackledge, M.D., and Koh, D.M., 2021. Automatic Segmentation of Pelvic Cancers Using Deep Learning: State-of-the-Art Approaches and Challenges. Diagnostics, 11(11), p.1964.
Winfield, J.M., Blackledge, M.D., Tunariu, N., Koh, D.M. and Messiou, C., 2021. Whole-body MRI: a practical guide for imaging patients with malignant bone disease. Clinical Radiology, 76(10), pp.715-727.
Shur, J., Blackledge, M.D., D’Arcy, J., Collins, D.J., Bali, M., O’Leach, M. and Koh, D.M., 2021. MRI texture feature repeatability and image acquisition factor robustness, a phantom study and in silico study. European radiology experimental, 5(1), pp.1-11.
Blackledge, M.D., Tunariu, N., Zungi, F., Holbrey, R., Orton, M.R., Ribeiro, A., Hughes, J.C., Scurr, E.D., Collins, D.J., Leach, M.O. and Koh, D.M., 2020. Noise-corrected, exponentially weighted, diffusion-weighted MRI (niceDWI) improves image signal uniformity in whole-body imaging of metastatic prostate cancer. Frontiers in Oncology, 10, p.704.
Blackledge, M.D., Winfield, J.M., Miah, A., Strauss, D., Thway, K., Morgan, V.A., Collins, D.J., Koh, D.M., Leach, M.O. and Messiou, C., 2019. Supervised machine-learning enables segmentation and evaluation of heterogeneous post-treatment changes in multi-parametric MRI of soft-tissue sarcoma. Frontiers in oncology, 9, p.941.
Zormpas-Petridis, K., Jerome, N.P., Blackledge, M.D., Carceller, F., Poon, E., Clarke, M., McErlean, C.M., Barone, G., Koers, A., Vaidya, S.J. and Marshall, L.V., 2019. MRI imaging of the hemodynamic vasculature of neuroblastoma predicts response to antiangiogenic treatment. Cancer research, 79(11), pp.2978-2991.
Messiou, C., Hillengass, J., Delorme, S., Lecouvet, F.E., Moulopoulos, L.A., Collins, D.J., Blackledge, M.D., Abildgaard, N., Østergaard, B., Schlemmer, H.P. and Landgren, O., 2019. Guidelines for acquisition, interpretation, and reporting of whole-body MRI in myeloma: myeloma response assessment and diagnosis system (MY-RADS). Radiology, 291(1), pp.5-13.
Barnes, A., Alonzi, R., Blackledge, M.D., et. al., 2018. UK quantitative WB-DWI technical workgroup: consensus meeting recommendations on optimisation, quality control, processing and analysis of quantitative whole-body diffusion-weighted imaging for cancer. The British journal of radiology, 91(1081), p.20170577.
Hill, D.K., Heindl, A., Zormpas-Petridis, K., ... and Blackledge M.D., 2017. Non-invasive prostate cancer characterization with diffusion-weighted MRI: insight from in silico studies of a transgenic mouse model. Frontiers in oncology, 7, p.290.
Perez-Lopez, R., Mateo, J., Mossop, H., Blackledge, M.D., et. al., 2017. Diffusion-weighted imaging as a treatment response biomarker for evaluating bone metastases in prostate cancer: a pilot study. Radiology, 283(1), pp.168-177.
Blackledge, M.D., Rata, M., Tunariu, N., Koh, D.M., George, A., Zivi, A., Lorente, D., Attard, G., de Bono, J.S., Leach, M.O. and Collins, D.J., 2016. Visualizing whole-body treatment response heterogeneity using multi-parametric magnetic resonance imaging. Journal of Algorithms & Computational Technology, 10(4), pp.290-301.
Cheng, L., Blackledge, M.D., Collins, D.J., Orton, M.R., Jerome, N.P., Feiweier, T., Rata, M., Morgan, V., Tunariu, N., Leach, M.O. and Koh, D.M., 2016. T2-adjusted computed diffusion-weighted imaging: A novel method to enhance tumour visualisation. Computers in biology and medicine, 79, pp.92-98.
Perez-Lopez, R., Lorente, D., Blackledge, M.D., et. al., 2016. Volume of bone metastasis assessed with whole-body diffusion-weighted imaging is associated with overall survival in metastatic castration-resistant prostate cancer. Radiology, 280(1), pp.151-160.
O'Flynn, E.A., Blackledge, M.D., Collins, D., Downey, K., Doran, S., Patel, H., Dumonteil, S., Mok, W., Leach, M.O. and Koh, D.M., 2016. Evaluating the diagnostic sensitivity of computed diffusion-weighted MR imaging in the detection of breast cancer. Journal of Magnetic Resonance Imaging, 44(1), pp.130-137.
Blackledge, M.D., Tunariu, N., Orton, M.R., Padhani, A.R., Collins, D.J., Leach, M.O. and Koh, D.M., 2016. Inter-and intra-observer repeatability of quantitative whole-body, diffusion-weighted imaging (WBDWI) in metastatic bone disease. PloS one, 11(4), p.e0153840.
Blackledge, M.D., Collins, D.J., Koh, D.M. and Leach, M.O., 2016. Rapid development of image analysis research tools: bridging the gap between researcher and clinician with pyOsiriX. Computers in biology and medicine, 69, pp.203-212.
Blackledge, M.D., Collins, D.J., Tunariu, N., Orton, M.R., Padhani, A.R., Leach, M.O. and Koh, D.M., 2014. Assessment of treatment response by total tumor volume and global apparent diffusion coefficient using diffusion-weighted MRI in patients with metastatic bone disease: a feasibility study. PloS one, 9(4), p.e91779.
Blackledge, M.D., Koh, D.M., Collins, D.J., Chua, S. and Leach, M.O., 2013. The utility of whole-body diffusion-weighted MRI for delineating regions of interest in PET. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 702, pp.148-151.
Koh, D.M., Blackledge, M.D., Burns, S., Hughes, J., Stemmer, A., Kiefer, B., Leach, M.O. and Collins, D.J., 2012. Combination of chemical suppression techniques for dual suppression of fat and silicone at diffusion-weighted MR imaging in women with breast implants. European radiology, 22(12), pp.2648-2653.
Blackledge, M.D., Leach, M.O., Collins, D.J. and Koh, D.M., 2011. Computed diffusion-weighted MR imaging may improve tumor detection. Radiology, 261(2), pp.573-581.
Koh, D.M., Blackledge, M.D., et. al., 2009. Reproducibility and changes in the apparent diffusion coefficients of solid tumours treated with combretastatin A4 phosphate and bevacizumab in a two-centre phase I clinical trial. European radiology, 19(11), pp.2728-2738.
Patents
Patents
Blackledge, M.D., Zormpas-Petridis, K., Institute of Cancer Research and Royal Marsden NHS Foundation Trust, 2021. Diffusion-weighted magnetic resonance imaging. GB2591671
Blackledge, M.D., Collins, D. and Leach, M., Institute of Cancer Research and Royal Marsden NHS Foundation Trust, 2021. Method for producing a weighted magnetic resonance image. US10885679B2
Page updated
Google Sites
Report abuse