Search

Your search keyword '"Graves, Martin J"' showing total 41 results
Start Over Author "Graves, Martin J" Publisher elsevier bv
41 results on '"Graves, Martin J"'

2. Somatostatin Receptor PET/MR Imaging of Inflammation in Patients With Large Vessel Vasculitis and Atherosclerosis

Author

Ćorović, Andrej, primary, Wall, Christopher, additional, Nus, Meritxell, additional, Gopalan, Deepa, additional, Huang, Yuan, additional, Imaz, Maria, additional, Zulcinski, Michal, additional, Peverelli, Marta, additional, Uryga, Anna, additional, Lambert, Jordi, additional, Bressan, Dario, additional, Maughan, Robert T., additional, Pericleous, Charis, additional, Dubash, Suraiya, additional, Jordan, Natasha, additional, Jayne, David R., additional, Hoole, Stephen P., additional, Calvert, Patrick A., additional, Dean, Andrew F., additional, Rassl, Doris, additional, Barwick, Tara, additional, Iles, Mark, additional, Frontini, Mattia, additional, Hannon, Greg, additional, Manavaki, Roido, additional, Fryer, Tim D., additional, Aloj, Luigi, additional, Graves, Martin J., additional, Gilbert, Fiona J., additional, Dweck, Marc R., additional, Newby, David E., additional, Fayad, Zahi A., additional, Reynolds, Gary, additional, Morgan, Ann W., additional, Aboagye, Eric O., additional, Davenport, Anthony P., additional, Jørgensen, Helle F., additional, Mallat, Ziad, additional, Bennett, Martin R., additional, Peters, James E., additional, Rudd, James H.F., additional, Mason, Justin C., additional, and Tarkin, Jason M., additional

Published
2023
Full Text
View/download PDF

3. Deuterium metabolic imaging and hyperpolarized 13C-MRI of the normal human brain at clinical field strength reveals differential cerebral metabolism

Author

Kaggie, Joshua D, primary, Khan, Alixander S, additional, Matys, Tomasz, additional, Schulte, Rolf F, additional, Locke, Matthew J, additional, Grimmer, Ashley, additional, Frary, Amy, additional, Menih, Ines Horvat, additional, Latimer, Elizabeth, additional, Graves, Martin J, additional, McLean, Mary A, additional, and Gallagher, Ferdia A, additional

Published
2022
Full Text
View/download PDF

9. Evaluation of the sensitivity of R1ρ MRI to pH and macromolecular density

Author

Ali, Syed O, Fessas, Petros, Kaggie, Joshua D, Zaccagna, Fulvio, Houston, Gavin, Reid, Scott, Graves, Martin J, Gallagher, Ferdia A, Kaggie, Joshua [0000-0001-6706-3442], Zaccagna, Fulvio [0000-0001-6838-9532], Graves, Martin [0000-0003-4327-3052], Gallagher, Ferdia [0000-0003-4784-5230], and Apollo - University of Cambridge Repository

Subjects
Male, Brain Mapping, pH, Phantoms, Imaging, Macromolecular Substances, Brain, Reproducibility of Results, Contrast Media, Gadolinium, Hydrogen-Ion Concentration, T(1)ρ, Magnetic Resonance Imaging, Sensitivity and Specificity, R(1)ρ, Healthy Volunteers, Basal Ganglia, Brain Ischemia, Stroke, Young Adult, Neoplasms, Tumor Microenvironment, Humans, Gray Matter, Neoplasm Metastasis, MRI
Abstract

The tumor microenvironment is characteristically acidic and this extracellular acidosis is known to play a role in carcinogenesis and metastasis and can affect tumor chemosensitivity and radiosensitivity. Intracellular pH has been used as a possible biomarker of salvageable tissue in ischemic stroke. A non-invasive MRI-based approach for the determination and imaging of cerebral pH would be a powerful tool in cancer diagnosis and monitoring, as well as stroke treatment planning. Several pH-based MRI imaging approaches have been proposed but for these to be useful, disentangling the effects of pH from other parameters which may affect the measured MRI signal is crucial to ensure accuracy and specificity. R1 relaxation in the rotating frame (R1ρ) is an example of a method that has been proposed to probe pH in vivo using MRI. In this study, we have investigated the relationship between R1ρ, pH, and macromolecular density in vitro using phantoms and in human volunteers. Here we show that the rate of R1ρ relaxation (=1/T1ρ) varies with pH but only in the presence of macromolecules. At constant pH, phantom macromolecular density inversely correlated with R1ρ. R1ρ imaging of the normal human brain demonstrated regional heterogeneity with significant differences between structurally distinct regions, which are likely to be independent of pH. For example, R1ρ was higher in the basal ganglia compared to grey matter and higher in grey matter compared to white matter. We conclude that R1ρ cannot be reliably used to image tissue pH without deconvolution from the effects of local tissue macromolecular composition.

Published
2019

10. Multi-site repeatability and reproducibility of MR fingerprinting of the healthy brain at 1.5 and 3.0 T

Author

Buonincontri, Guido, Biagi, Laura, Retico, Alessandra, Cecchi, Paolo, Cosottini, Mirco, Gallagher, Ferdia A, Gómez, Pedro A, Graves, Martin J, McLean, Mary A, Riemer, Frank, Schulte, Rolf F, Tosetti, Michela, Zaccagna, Fulvio, and Kaggie, Joshua D

Subjects
MR fingerprinting, Adult, Male, Brain Mapping, Adolescent, Brain, Reproducibility of Results, Middle Aged, Magnetic Resonance Imaging, Quantitation, Young Adult, Humans, Female, Relaxometry, MRI
Abstract

Fully-quantitative MR imaging methods are useful for longitudinal characterization of disease and assessment of treatment efficacy. However, current quantitative MRI protocols have not been widely adopted in the clinic, mostly due to lengthy scan times. Magnetic Resonance Fingerprinting (MRF) is a new technique that can reconstruct multiple parametric maps from a single fast acquisition in the transient state of the MR signal. Due to the relative novelty of this technique, the repeatability and reproducibility of quantitative measurements obtained using MRF has not been extensively studied. Our study acquired test/retest data from the brains of nine healthy volunteers, each scanned on five MRI systems (two at 3.0 T and three at 1.5 T, all from a single vendor) located at two different centers. The pulse sequence and reconstruction algorithm were the same for all acquisitions. After registration of the MRF-derived M0, T1 and T2 maps to an anatomical atlas, coefficients-of-variation (CVs) were computed to assess test/retest repeatability and inter-site reproducibility in each voxel, while a General Linear Model (GLM) was used to determine the voxel-wise variability between all confounders, which included test/retest, subject, field strength and site. Our analysis demonstrated an excellent repeatability (CVs of 2-3% for T1, 5-8% for T2, 3% for normalized-M0) and a good reproducibility (CVs of 3-8% for T1, 8-14% for T2, 5% for normalized-M0) in grey and white matter.

Published
2019
Full Text
View/download PDF

11. Imaging intralesional heterogeneity of sodium concentration in multiple sclerosis: Initial evidence from 23Na-MRI

Author

Grist, James T, Riemer, Frank, McLean, Mary A, Matys, Tomasz, Zaccagna, Fulvio, Hilborne, Sarah F, Mason, Jackie P, Patterson, Ilse, Slough, Rhys, Kaggie, Joshua, Deen, Surrin S, Graves, Martin J, Jones, Joanne L, Coles, Alasdair J, and Gallagher, Ferdia A

Subjects
Adult, Analysis of Variance, Multiple Sclerosis, Sodium Radioisotopes, Sodium, Brain, (23)Na, Magnetic Resonance Imaging, Intracellular sodium, Disability Evaluation, Imaging, Three-Dimensional, 3-tesla, Humans, Female, High-resolution, Extracellular sodium
Abstract

Sodium MRI (23Na-MRI) has been used to non-invasively quantify tissue sodium but has been limited by low spatial resolution. Here we demonstrate for the first time that high resolution 23Na-MRI reveals the spatial heterogeneity of sodium concentration within a multiple sclerosis (MS) lesion. A patient with treatment-naïve relapsing-remitting MS and a ring-enhancing lesion was imaged using 23Na-MRI. The periphery of the lesion demonstrated an elevated total sodium content compared to the normal appearing white and grey matter (p

Published
2018
Full Text
View/download PDF

12. Multi-site repeatability and reproducibility of MR fingerprinting of the healthy brain at 1.5 and 3.0 T

Author

Buonincontri, Guido, primary, Biagi, Laura, additional, Retico, Alessandra, additional, Cecchi, Paolo, additional, Cosottini, Mirco, additional, Gallagher, Ferdia A., additional, Gómez, Pedro A., additional, Graves, Martin J., additional, McLean, Mary A., additional, Riemer, Frank, additional, Schulte, Rolf F., additional, Tosetti, Michela, additional, Zaccagna, Fulvio, additional, and Kaggie, Joshua D., additional

Published
2019
Full Text
View/download PDF

14. Quantifying normal human brain metabolism using hyperpolarized [1–13C]pyruvate and magnetic resonance imaging

Author

Grist, James T., primary, McLean, Mary A., additional, Riemer, Frank, additional, Schulte, Rolf F., additional, Deen, Surrin S., additional, Zaccagna, Fulvio, additional, Woitek, Ramona, additional, Daniels, Charlie J., additional, Kaggie, Joshua D., additional, Matys, Tomasz, additional, Patterson, Ilse, additional, Slough, Rhys, additional, Gill, Andrew B., additional, Chhabra, Anita, additional, Eichenberger, Rose, additional, Laurent, Marie-Christine, additional, Comment, Arnaud, additional, Gillard, Jonathan H., additional, Coles, Alasdair J., additional, Tyler, Damian J., additional, Wilkinson, Ian, additional, Basu, Bristi, additional, Lomas, David J., additional, Graves, Martin J., additional, Brindle, Kevin M., additional, and Gallagher, Ferdia A., additional

Published
2019
Full Text
View/download PDF

15. The use of error-category mapping in pharmacokinetic model analysis of dynamic contrast-enhanced MRI data

Author

Gill, Andrew B., Anandappa, Gayathri, Patterson, Andrew J., Priest, Andrew N., Graves, Martin J., Janowitz, Tobias, Jodrell, Duncan I., Eisen, Tim, Lomas, David J., Gill, Andrew [0000-0002-9287-9563], Graves, Martin [0000-0003-4327-3052], Jodrell, Duncan [0000-0001-9360-1670], Eisen, Tim [0000-0001-9663-4873], Lomas, David [0000-0003-2904-8617], and Apollo - University of Cambridge Repository

Subjects
AIC, Akaike information criterion, DCE-MRI, pharamacokinetic modeling, ROI, region of interest, Biophysics, Biomedical Engineering, Contrast Media, Antibodies, Monoclonal, Humanized, PK, pharmacokinetic, DCE-MRI, dynamic contrast-enhanced magnetic resonance imaging, metastatic renal cell carcinoma, eTM, extended Tofts model, Technical Note, Image Processing, Computer-Assisted, Humans, repeatability, Neoplasm Metastasis, Carcinoma, Renal Cell, error analysis, Reproducibility of Results, Models, Theoretical, Magnetic Resonance Imaging, Kidney Neoplasms, MFA, multiple flip angles, Bevacizumab, mRCC, metastatic renal cell carcinoma, Radiology Nuclear Medicine and imaging, Area Under Curve, AIF, arterial input function, Algorithms, Software
Abstract

This study introduces the use of 'error-category mapping' in the interpretation of pharmacokinetic (PK) model parameter results derived from dynamic contrast-enhanced (DCE-) MRI data. Eleven patients with metastatic renal cell carcinoma were enrolled in a multiparametric study of the treatment effects of bevacizumab. For the purposes of the present analysis, DCE-MRI data from two identical pre-treatment examinations were analysed by application of the extended Tofts model (eTM), using in turn a model arterial input function (AIF), an individually-measured AIF and a sample-average AIF. PK model parameter maps were calculated. Errors in the signal-to-gadolinium concentration ([Gd]) conversion process and the model-fitting process itself were assigned to category codes on a voxel-by-voxel basis, thereby forming a colour-coded 'error-category map' for each imaged slice. These maps were found to be repeatable between patient visits and showed that the eTM converged adequately in the majority of voxels in all the tumours studied. However, the maps also clearly indicated sub-regions of low Gd uptake and of non-convergence of the model in nearly all tumours. The non-physical condition ve ≥ 1 was the most frequently indicated error category and appeared sensitive to the form of AIF used. This simple method for visualisation of errors in DCE-MRI could be used as a routine quality-control technique and also has the potential to reveal otherwise hidden patterns of failure in PK model applications.

Published
2015
Full Text
View/download PDF

16. Sodium MRI with 3D-cones as a measure of tumour cellularity in high grade serous ovarian cancer

Author

Deen, Surrin S., primary, Riemer, Frank, additional, McLean, Mary A., additional, Gill, Andrew B., additional, Kaggie, Joshua D., additional, Grist, James T., additional, Crawford, Robin, additional, Latimer, John, additional, Baldwin, Peter, additional, Earl, Helena M., additional, Parkinson, Christine A., additional, Smith, Sarah A., additional, Hodgkin, Charlotte, additional, Moore, Elizabeth, additional, Jimenez-Linan, Mercedes, additional, Brodie, Cara R., additional, Addley, Helen C., additional, Freeman, Susan J., additional, Moyle, Penelope L., additional, Sala, Evis, additional, Graves, Martin J., additional, Brenton, James D., additional, and Gallagher, Ferdia A., additional

Published
2019
Full Text
View/download PDF

18. Imaging intralesional heterogeneity of sodium concentration in multiple sclerosis: Initial evidence from 23 Na-MRI

Author

Grist, James T., primary, Riemer, Frank, additional, McLean, Mary A., additional, Matys, Tomasz, additional, Zaccagna, Fulvio, additional, Hilborne, Sarah F., additional, Mason, Jackie P., additional, Patterson, Ilse, additional, Slough, Rhys, additional, Kaggie, Joshua, additional, Deen, Surrin S., additional, Graves, Martin J., additional, Jones, Joanne L., additional, Coles, Alasdair J., additional, and Gallagher, Ferdia A., additional

Published
2018
Full Text
View/download PDF

19. Three-dimensional black-blood T2 mapping with compressed sensing and data-driven parallel imaging in the carotid artery

Author

Yuan, Jianmin, Usman, Ammara, Reid, Scott A, King, Kevin F, Patterson, Andrew J, Gillard, Jonathan H, Graves, Martin J, Gillard, Jonathan [0000-0003-4787-8091], Graves, Martin [0000-0003-4327-3052], and Apollo - University of Cambridge Repository

Subjects
Adult, Aged, 80 and over, Male, Phantoms, Imaging, Reproducibility of Results, Middle Aged, Magnetic Resonance Imaging, Parallel imaging, Young Adult, Carotid Arteries, Imaging, Three-Dimensional, Image Processing, Computer-Assisted, Compressed sensing, Feasibility Studies, Humans, Carotid Stenosis, Female, T(2) mapping, Carotid imaging, Aged
Abstract

PURPOSE: To develop a 3D black-blood T2 mapping sequence with a combination of compressed sensing (CS) and parallel imaging (PI) for carotid wall imaging. MATERIALS AND METHODS: A 3D black-blood fast-spin-echo (FSE) sequence for T2 mapping with CS and PI was developed and validated. Phantom experiments were performed to assess T2 accuracy using a Eurospin Test Object, with different combination of CS and PI acceleration factors. A 2D multi-echo FSE sequence was used as a reference to evaluate the accuracy. The concordance correlation coefficient and Bland-Altman statistics were calculated. Twelve volunteers were scanned twice to determine the repeatability of the sequence and the intraclass correlation coefficient (ICC) was reported. Wall-lumen sharpness was calculated for different CS and PI combinations. Six patients with carotid stenosis >50% were scanned with optimised sequence. The T2 maps were compared with multi-contrast images. RESULTS: Phantom scans showed good correlation in T2 measurement between current and reference sequence (r=0.991). No significant difference was found between different combination of CS and PI accelerations (p=0.999). Volunteer scans showed good repeatability of T2 measurement (ICC: 0.93, 95% CI 0.84-0.97). The mean T2 of the healthy wall was 48.0±9.5ms. Overall plaque T2 values from patients were 54.9±12.2ms. Recent intraplaque haemorrhage and fibrous tissue have higher T2 values than the mean plaque T2 values (88.1±6.8ms and 62.7±9.3ms, respectively). CONCLUSION: This study demonstrates the feasibility of combining CS and PI for accelerating 3D T2 mapping in the carotid artery, with accurate T2 measurements and good repeatability.

Published
2017
Full Text
View/download PDF

33. Utility of high resolution MR imaging to assess carotid plaque morphology: A comparison of acute symptomatic, recently symptomatic and asymptomatic patients with carotid artery disease

Author

Sadat, Umar, primary, Weerakkody, Ruwan A., additional, Bowden, David J., additional, Young, Victoria E., additional, Graves, Martin J., additional, Li, Zhi-Yong, additional, Tang, Tjun Y., additional, Gaunt, Michael E., additional, Hayes, Paul D., additional, and Gillard, Jonathan H., additional

Published
2009
Full Text
View/download PDF

35. The ATHEROMA (Atorvastatin Therapy: Effects on Reduction of Macrophage Activity) Study

Author

Tang, Tjun Y., primary, Howarth, Simon P.S., additional, Miller, Sam R., additional, Graves, Martin J., additional, Patterson, Andrew J., additional, U-King-Im, Jean-Marie, additional, Li, Zhi Y., additional, Walsh, Stewart R., additional, Brown, Andrew P., additional, Kirkpatrick, Peter J., additional, Warburton, Elizabeth A., additional, Hayes, Paul D., additional, Varty, Kevin, additional, Boyle, Jonathan R., additional, Gaunt, Michael E., additional, Zalewski, Andrew, additional, and Gillard, Jonathan H., additional

Published
2009
Full Text
View/download PDF

36. Atorvastatin and uptake of ultrasmall superparamagnetic iron oxide nanoparticles (Ferumoxtran-10) in human monocyte–macrophages: Implications for magnetic resonance imaging

Author

Müller, Karin, primary, Skepper, Jeremy N., additional, Tang, Tjun Y., additional, Graves, Martin J., additional, Patterson, Andrew J., additional, Corot, Claire, additional, Lancelot, Eric, additional, Thompson, Paul W., additional, Brown, Andrew P., additional, and Gillard, Jonathan H., additional

Published
2008
Full Text
View/download PDF

41. The optimisation of deep neural networks for segmenting multiple knee joint tissues from MRIs

Author

Kessler, Dimitri A, MacKay, James W, Crowe, Victoria A, Henson, Frances MD, Graves, Martin J, Gilbert, Fiona J, and Kaggie, Joshua D

Subjects
musculoskeletal diseases, Image segmentation, Knee Joint, Musculoskeletal, Convolutional neural network (CNN), Generative adversarial network (GAN), Image Processing, Computer-Assisted, Humans, Magnetic resonance imaging (MRI), Neural Networks, Computer, Magnetic Resonance Imaging, Bone and Bones, 3. Good health
Abstract

Automated semantic segmentation of multiple knee joint tissues is desirable to allow faster and more reliable analysis of large datasets and to enable further downstream processing e.g. automated diagnosis. In this work, we evaluate the use of conditional Generative Adversarial Networks (cGANs) as a robust and potentially improved method for semantic segmentation compared to other extensively used convolutional neural network, such as the U-Net. As cGANs have not yet been widely explored for semantic medical image segmentation, we analysed the effect of training with different objective functions and discriminator receptive field sizes on the segmentation performance of the cGAN. Additionally, we evaluated the possibility of using transfer learning to improve the segmentation accuracy. The networks were trained on i) the SKI10 dataset which comes from the MICCAI grand challenge "Segmentation of Knee Images 2010″, ii) the OAI ZIB dataset containing femoral and tibial bone and cartilage segmentations of the Osteoarthritis Initiative cohort and iii) a small locally acquired dataset (Advanced MRI of Osteoarthritis (AMROA) study) consisting of 3D fat-saturated spoiled gradient recalled-echo knee MRIs with manual segmentations of the femoral, tibial and patellar bone and cartilage, as well as the cruciate ligaments and selected peri-articular muscles. The Sørensen-Dice Similarity Coefficient (DSC), volumetric overlap error (VOE) and average surface distance (ASD) were calculated for segmentation performance evaluation. DSC ≥ 0.95 were achieved for all segmented bone structures, DSC ≥ 0.83 for cartilage and muscle tissues and DSC of ≈0.66 were achieved for cruciate ligament segmentations with both cGAN and U-Net on the in-house AMROA dataset. Reducing the receptive field size of the cGAN discriminator network improved the networks segmentation performance and resulted in segmentation accuracies equivalent to those of the U-Net. Pretraining not only increased segmentation accuracy of a few knee joint tissues of the fine-tuned dataset, but also increased the network's capacity to preserve segmentation capabilities for the pretrained dataset. cGAN machine learning can generate automated semantic maps of multiple tissues within the knee joint which could increase the accuracy and efficiency for evaluating joint health.

Catalog

Books, media, physical & digital resources
See catalog results