Imperial College London

Professor Paul M. Matthews

Faculty of MedicineDepartment of Medicine

Edmond and Lily Safra Chair and Head of Brain Sciences
 
 
 
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Contact

 

+44 (0)20 7594 2855p.matthews

 
 
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Assistant

 

Ms Alison Thomas +44 (0)20 7594 2855

 
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Location

 

E502Burlington DanesHammersmith Campus

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Summary

 

Publications

Publication Type
Year
to

578 results found

Gafson AR, Thorne T, McKechnie CIJ, Jimenez B, Nicholas R, Matthews PMet al., 2018, Lipoprotein markers associated with disability from multiple sclerosis, SCIENTIFIC REPORTS, Vol: 8, ISSN: 2045-2322

JOURNAL ARTICLE

Ntusi NAB, Francis JM, Sever E, Liu A, Piechnik S, Ferreira VM, Matthews PM, Robson MD, Wordsworth PB, Neubauer S, Karamitsos TDet al., 2018, Anti-TNF modulation reduces myocardial inflammation and improves cardiovascular function in systemic rheumatic diseases, INTERNATIONAL JOURNAL OF CARDIOLOGY, Vol: 270, Pages: 253-259, ISSN: 0167-5273

JOURNAL ARTICLE

Tarroni G, Oktay O, Bai W, Schuh A, Suzuki H, Passerat-Palmbach J, de Marvao A, O'Regan DP, Cook S, Glocker B, Matthews PM, Rueckert Det al., 2018, Learning-Based Quality Control for Cardiac MR Images.

The effectiveness of a cardiovascular magnetic resonance (CMR) scan depends on the ability of the operator to correctly tune the acquisition parameters to the subject being scanned and on the potential occurrence of imaging artefacts such as cardiac and respiratory motion. In the clinical practice, a quality control step is performed by visual assessment of the acquired images: however, this procedure is strongly operatordependent, cumbersome and sometimes incompatible with the time constraints in clinical settings and large-scale studies. We propose a fast, fully-automated, learning-based quality control pipeline for CMR images, specifically for short-axis image stacks. Our pipeline performs three important quality checks: 1) heart coverage estimation, 2) inter-slice motion detection, 3) image contrast estimation in the cardiac region. The pipeline uses a hybrid decision forest method - integrating both regression and structured classification models - to extract landmarks as well as probabilistic segmentation maps from both long- and short-axis images as a basis to perform the quality checks. The technique was tested on up to 3000 cases from the UK Biobank as well as on 100 cases from the UK Digital Heart Project, and validated against manual annotations and visual inspections performed by expert interpreters. The results show the capability of the proposed pipeline to correctly detect incomplete or corrupted scans (e.g. on UK Biobank, sensitivity and specificity respectively 88% and 99% for heart coverage estimation, 85% and 95% for motion detection), allowing their exclusion from the analysed dataset or the triggering of a new acquisition.

CONFERENCE PAPER

Inkster B, Simmons A, Cole JH, Schoof E, Linding R, Nichols T, Muglia P, Holsboer F, Saemann PG, McGuffin P, Fu CHY, Miskowiak K, Matthews PM, Zai G, Nicodemus Ket al., 2018, Unravelling the GSK3 beta-related genotypic interaction network influencing hippocampal volume in recurrent major depressive disorder, PSYCHIATRIC GENETICS, Vol: 28, Pages: 77-84, ISSN: 0955-8829

JOURNAL ARTICLE

LaRocca NG, Hudson LD, Rudick R, Amtmann D, Balcer L, Benedict R, Bermel R, Chang I, Chiaravalloti ND, Chin P, Cohen JA, Cutter GR, Davis MD, DeLuca J, Feys P, Francis G, Goldman MD, Hartley E, Kapoor R, Lublin F, Lundstrom G, Matthews PM, Mayo N, Meibach R, Miller DM, Motl RW, Mowry EM, Naismith R, Neville J, Panagoulias J, Panzara M, Phillips G, Robbins A, Sidovar MF, Smith KE, Sperling B, Uitdehaag BMJ, Weaver Jet al., 2018, The MSOAC approach to developing performance outcomes to measure and monitor multiple sclerosis disability, MULTIPLE SCLEROSIS JOURNAL, Vol: 24, Pages: 1469-1484, ISSN: 1352-4585

JOURNAL ARTICLE

Bai W, Sinclair M, Tarroni G, Oktay O, Rajchl M, Vaillant G, Lee AM, Aung N, Lukaschuk E, Sanghvi MM, Zemrak F, Fung K, Paiva JM, Carapella V, Kim YJ, Suzuki H, Kainz B, Matthews PM, Petersen SE, Piechnik SK, Neubauer S, Glocker B, Rueckert Det al., 2018, Automated cardiovascular magnetic resonance image analysis with fully convolutional networks, JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE, Vol: 20, ISSN: 1097-6647

JOURNAL ARTICLE

Liu Z, Zhang J, Zhang K, Zhang J, Li X, Cheng W, Li M, Zhao L, Deng W, Guo W, Ma X, Wang Q, Matthews PM, Feng J, Li Tet al., 2018, Distinguishable brain networks relate disease susceptibility to symptom expression in schizophrenia, HUMAN BRAIN MAPPING, Vol: 39, Pages: 3503-3515, ISSN: 1065-9471

JOURNAL ARTICLE

Gibson L, Littlejohns T, Adamska L, Garratt S, Doherty N, Wardlaw J, Maskell G, Parker M, Brownsword R, Matthews P, Collins R, Allen N, Sellors J, Sudlow CLM, UK Biobank Imaging Working Groupet al., 2018, Impact of detecting potentially serious incidental findings during multi-modal imaging

Background : There are limited data on the impact of feedback of incidental findings (IFs) from research imaging.  We evaluated the impact of UK Biobank’s protocol for handling potentially serious IFs in a multi-modal imaging study of 100,000 participants (radiographer ‘flagging’ with radiologist confirmation of potentially serious IFs) compared with systematic radiologist review of all images. Methods : Brain, cardiac and body magnetic resonance, and dual-energy x-ray absorptiometry scans from the first 1000 imaged UK Biobank participants were independently assessed for potentially serious IFs using both protocols. We surveyed participants with potentially serious IFs and their GPs up to six months after imaging to determine subsequent clinical assessments, final diagnoses, emotional, financial and work or activity impacts. Results : Compared to systematic radiologist review, radiographer flagging resulted in substantially fewer participants with potentially serious IFs (179/1000 [17.9%] versus 18/1000 [1.8%]) and a higher proportion with serious final diagnoses (21/179 [11.7%] versus 5/18 [27.8%]). Radiographer flagging missed 16/21 serious final diagnoses (i.e., false negatives), while systematic radiologist review generated large numbers of non-serious final diagnoses (158/179) (i.e., false positives). Almost all (90%) participants had further clinical assessment (including invasive procedures in similar numbers with serious and non-serious final diagnoses [11 and 12 respectively]), with additional impact on emotional wellbeing (16.9%), finances (8.9%), and work or activities (5.6%). Conclusions : Compared with systematic radiologist review, radiographer flagging missed some serious diagnoses, but avoided adverse impacts for many participants with non-serious diagnoses. While systematic radiologist review may benefit some participants, UK Biobank’s responsibility to avoid both unnecessary harm to larger numbers of

JOURNAL ARTICLE

Calsolaro V, Mayers J, Fan Z, Tyacke R, Venkataraman A, Femminella G, Perneczky R, Gunn R, Rabiner E, Matthews P, Nutt D, Edison Pet al., 2018, Evaluation of novel astrocyte marker [11C]BU99008 PET in Alzheimer’s disease: a Dementia Platform U.K. experimental medicine study, Alzheimer's and Dementia, Vol: 14, Pages: P842-P843, ISSN: 1552-5260

JOURNAL ARTICLE

Fan Z, Calsolaro V, Mayers J, Tyacke R, Venkataraman A, Femminella G, Perneczky R, Gunn R, Rabiner E, Matthews P, Nutt D, Edison Pet al., 2018, Relationship between astrocyte activation using [11C]BU99008 PET, glucose metabolism and amyloid in Alzheimer’s disease: a Dementia Platform UK experimental medicine study, Alzheimer's and Dementia, Vol: 14, Pages: P1640-P1640, ISSN: 1552-5260

JOURNAL ARTICLE

Supratak A, Datta G, Gafson AR, Nicholas R, Guo Y, Matthews PMet al., 2018, Remote Monitoring in the Home Validates Clinical Gait Measures for Multiple Sclerosis, FRONTIERS IN NEUROLOGY, Vol: 9, ISSN: 1664-2295

JOURNAL ARTICLE

Gafson AR, Kim K, Cencioni MT, van Hecke W, Nicholas R, Baranzini SE, Matthews PMet al., 2018, Mononuclear cell transcriptome changes associated with dimethyl fumarate in MS, NEUROLOGY-NEUROIMMUNOLOGY & NEUROINFLAMMATION, Vol: 5, ISSN: 2332-7812

JOURNAL ARTICLE

Dawes T, Serrani M, Bai W, Cai J, de Marvao A, Matthews P, Reuckert D, Cook S, Costantino M, O'Regan Det al., 2018, Myocardial trabeculae improve left ventricular function: a combined UK Biobank and computational analysis, AAGBI GAT Annual Scientific Meeting, Publisher: WILEY, Pages: 12-12, ISSN: 0003-2409

CONFERENCE PAPER

Scott G, Zetterberg H, Jolly A, Cole JH, De Simoni S, Jenkins PO, Feeney C, Owen DR, Lingford-Hughes A, Howes O, Patel MC, Goldstone AP, Gunn RN, Blennow K, Matthews PM, Sharp DJet al., 2018, Minocycline reduces chronic microglial activation after brain trauma but increases neurodegeneration, BRAIN, Vol: 141, Pages: 459-471, ISSN: 0006-8950

JOURNAL ARTICLE

Alfaro-Almagro F, Jenkinson M, Bangerter NK, Andersson JLR, Griffanti L, Douaud G, Sotiropoulos SN, Jbabdi S, Hernandez-Fernandez M, Vallee E, Vidaurre D, Webster M, McCarthy P, Rorden C, Daducci A, Alexander DC, Zhang H, Dragonu I, Matthews PM, Miller KL, Smith SMet al., 2018, Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank, NEUROIMAGE, Vol: 166, Pages: 400-424, ISSN: 1053-8119

JOURNAL ARTICLE

Dong H, Supratak A, Pan W, Wu C, Matthews PM, Guo Yet al., 2018, Mixed Neural Network Approach for Temporal Sleep Stage Classification, IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, Vol: 26, Pages: 324-333, ISSN: 1534-4320

JOURNAL ARTICLE

Ntusi NAB, Francis JM, Gumedze F, Karvounis H, Matthews PM, Wordsworth PB, Neubauer S, Karamitsos TDet al., 2018, Cardiovascular magnetic resonance characterization of myocardial and vascular function in rheumatoid arthritis patients., Hellenic J Cardiol

BACKGROUND: Rheumatoid arthritis (RA) is a multisystem, autoimmune disorder and confers one of the strongest risks for cardiovascular disease (CVD) morbidity and mortality. OBJECTIVE: To assess myocardial function and vascular stiffness in RA patients with and without cardiovascular risk factors (CVRFs) using cardiovascular magnetic resonance (CMR). METHODS: Twenty-three RA patients with no CVRFs (17 female, mean age 52 ± 13 years), 46 RA patients with CVRFs (32 female, mean age 53 ± 12), 50 normal controls (32 female, mean age 50 ± 11 years), and 13 controls with CVRFs (7 female, mean age 55 ± 7 years), underwent CMR at 1.5 Tesla, including evaluation of left ventricular (LV) ejection fraction, strain, and vascular elasticity (aortic distensibility [AD] and pulse wave velocity [PWV]). Disease activity and duration were recorded for each patient. Subjects with known symptomatic CVD were excluded. RESULTS: LV volumes, mass, and ejection fraction were similar in the four groups. RA patients with CVRFs showed the greatest abnormality in mid short-axis circumferential systolic strain, peak diastolic strain rate, and vascular indices. RA patients without CVRFs showed a similar degree of vascular dysfunction and deformational abnormality as controls with CVRFs. AD and total PWV correlated with myocardial strain and RA disease activity. On multivariate regression analysis, strain was related to age, RA disease activity, AD, and PWV. CONCLUSION: CMR demonstrates impaired myocardial deformation and vascular function in asymptomatic RA patients, worse in those with CVRFs. Subclinical cardiovascular abnormalities are frequent and appear to be incremental to those due to traditional CVRFs and likely contribute to the excess CVD in RA.

JOURNAL ARTICLE

Bishop CA, Ricotti V, Sinclair CDJ, Evans MRB, Butler JW, Morrow JM, Hanna MG, Matthews PM, Yousry TA, Muntoni F, Thornton JS, Newbould RD, Janiczek RLet al., 2018, Semi-Automated Analysis of Diaphragmatic Motion with Dynamic Magnetic Resonance Imaging in Healthy Controls and Non-Ambulant Subjects with Duchenne Muscular Dystrophy, FRONTIERS IN NEUROLOGY, Vol: 9, ISSN: 1664-2295

JOURNAL ARTICLE

Bai W, Suzuki H, Qin C, Tarroni G, Oktay O, Matthews PM, Rueckert Det al., 2018, Recurrent Neural Networks for Aortic Image Sequence Segmentation with Sparse Annotations, Pages: 586-594, ISSN: 0302-9743

© 2018, Springer Nature Switzerland AG. Segmentation of image sequences is an important task in medical image analysis, which enables clinicians to assess the anatomy and function of moving organs. However, direct application of a segmentation algorithm to each time frame of a sequence may ignore the temporal continuity inherent in the sequence. In this work, we propose an image sequence segmentation algorithm by combining a fully convolutional network with a recurrent neural network, which incorporates both spatial and temporal information into the segmentation task. A key challenge in training this network is that the available manual annotations are temporally sparse, which forbids end-to-end training. We address this challenge by performing non-rigid label propagation on the annotations and introducing an exponentially weighted loss function for training. Experiments on aortic MR image sequences demonstrate that the proposed method significantly improves both accuracy and temporal smoothness of segmentation, compared to a baseline method that utilises spatial information only. It achieves an average Dice metric of 0.960 for the ascending aorta and 0.953 for the descending aorta.

CONFERENCE PAPER

Stangel M, Kuhlmann T, Matthews PM, Kilpatrick TJet al., 2017, Achievements and obstacles of remyelinating therapies in multiple sclerosis, NATURE REVIEWS NEUROLOGY, Vol: 13, Pages: 742-754, ISSN: 1759-4758

JOURNAL ARTICLE

Owen DR, Fan J, Campioli E, Venugopal S, Midzak A, Daly E, Harlay A, Issop L, Libri V, Kalogiannopoulou D, Oliver E, Gallego-Colon E, Colasanti A, Huson L, Rabiner EA, Suppiah P, Essagian C, Matthews PM, Papadopoulos Vet al., 2017, TSPO mutations in rats and a human polymorphism impair the rate of steroid synthesis, BIOCHEMICAL JOURNAL, Vol: 474, Pages: 3985-3999, ISSN: 0264-6021

JOURNAL ARTICLE

Gibson L, Littlejohns T, Adamska L, Garratt S, Doherty N, Wardlaw J, Maskell G, Parker M, Brownsword R, Matthews P, Collins R, Allen N, Sellors J, Sudlow CLM, UK Biobank Imaging Working Groupet al., 2017, Impact of detecting potentially serious incidental findings during multi-modal imaging

Background : There are limited data on the impact of feedback of incidental findings (IFs) from research imaging.  We evaluated the impact of UK Biobank’s protocol for handling potentially serious IFs in a multi-modal imaging study of 100,000 participants (radiographer ‘flagging’ with radiologist confirmation of potentially serious IFs) compared with systematic radiologist review of all images. Methods : Brain, cardiac and body magnetic resonance, and dual-energy x-ray absorptiometry scans from the first 1000 imaged UK Biobank participants were independently assessed for potentially serious IFs using both protocols. We surveyed participants with potentially serious IFs and their GPs up to six months after imaging to determine subsequent clinical assessments, final diagnoses, emotional, financial and work or activity impacts. Results : Compared to systematic radiologist review, radiographer flagging resulted in substantially fewer participants with potentially serious IFs (179/1000 [17.9%] versus 18/1000 [1.8%]) and a higher proportion with serious final diagnoses (21/179 [11.7%] versus 5/18 [27.8%]). Radiographer flagging missed 16/21 serious final diagnoses (i.e., false negatives), while systematic radiologist review generated large numbers of non-serious final diagnoses (158/179) (i.e., false positives). Almost all (90%) participants had further clinical assessment (including invasive procedures in similar numbers with serious and non-serious final diagnoses [11 and 12 respectively]), with additional impact on emotional wellbeing (16.9%), finances (8.9%), and work or activities (5.6%). Conclusions : Compared with systematic radiologist review, radiographer flagging missed some serious diagnoses, but avoided adverse impacts for many participants with non-serious diagnoses. While systematic radiologist review may benefit some participants, UK Biobank’s responsibility to avoid both unnecessary harm to larger numbers of

JOURNAL ARTICLE

Suzuki H, Gao H, Bai W, Evangelou E, Glocker B, O'Regan DP, Elliott P, Matthews PMet al., 2017, Abnormal brain white matter microstructure is associated with both pre-hypertension and hypertension, PLOS ONE, Vol: 12, ISSN: 1932-6203

JOURNAL ARTICLE

Coffey S, Lewandowski AJ, Garratt S, Meijer R, Lynum S, Bedi R, Paterson J, Yaqub M, Noble JA, Neubauer S, Petersen SE, Allen N, Sudlow C, Collins R, Matthews PM, Leeson Pet al., 2017, Protocol and quality assurance for carotid imaging in 100,000 participants of UK Biobank: development and assessment, EUROPEAN JOURNAL OF PREVENTIVE CARDIOLOGY, Vol: 24, Pages: 1799-1806, ISSN: 2047-4873

JOURNAL ARTICLE

Datta G, Colasanti A, Rabiner EA, Gunn RN, Malik O, Ciccarelli O, Nicholas R, Van Vlierberghe E, Van Hecke W, Searle G, Santos-Ribeiro A, Matthews PMet al., 2017, Neuroinflammation and its relationship to changes in brain volume and white matter lesions in multiple sclerosis, BRAIN, Vol: 140, Pages: 2927-2938, ISSN: 0006-8950

JOURNAL ARTICLE

Peeters LM, Lamers I, Valkenborg D, Feys P, Somers V, Spooren A, Popescu V, Hens N, Matthews PM, Thalheim C, Van Wijmeersch B, Hellings Net al., 2017, Towards personalized therapy through extensive longitudinal follow-up using a multidisciplinary data infrastructure for people with MS: a-proof-of-concept study, 7th Joint European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS)-Americas-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ACTRIMS), Publisher: SAGE PUBLICATIONS LTD, Pages: 934-935, ISSN: 1352-4585

CONFERENCE PAPER

Datta G, Violante IR, Scott G, Zimmerman K, Santos-Ribeiro A, Rabiner EA, Gunn RN, Malik O, Ciccarelli O, Nicholas R, Matthews PMet al., 2017, Translocator positron-emission tomography and magnetic resonance spectroscopic imaging of brain glial cell activation in multiple sclerosis, MULTIPLE SCLEROSIS JOURNAL, Vol: 23, Pages: 1469-1478, ISSN: 1352-4585

JOURNAL ARTICLE

Matthews PM, 2017, Advanced MRI measures like DTI or fMRI should be outcome measures in future clinical trials - NO, MULTIPLE SCLEROSIS JOURNAL, Vol: 23, Pages: 1456-1458, ISSN: 1352-4585

JOURNAL ARTICLE

Datta G, Colasanti A, Kalk N, Owen D, Scott G, Rabiner EA, Gunn RN, Lingford-Hughes A, Malik O, Ciccarelli O, Nicholas R, Nei L, Battaglini M, Stefano ND, Matthews PMet al., 2017, C-11-PBR28 and F-18-PBR111 Detect White Matter Inflammatory Heterogeneity in Multiple Sclerosis, JOURNAL OF NUCLEAR MEDICINE, Vol: 58, Pages: 1477-1482, ISSN: 0161-5505

JOURNAL ARTICLE

Owen DR, Narayan N, Wells L, Healy L, Smyth E, Rabiner EA, Galloway D, Williams JB, Lehr J, Mandhair H, Peferoen LAN, Taylor PC, Amor S, Antel JP, Matthews PM, Moore CSet al., 2017, Pro-inflammatory activation of primary microglia and macrophages increases 18 kDa translocator protein expression in rodents but not humans, JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM, Vol: 37, Pages: 2679-2690, ISSN: 0271-678X

JOURNAL ARTICLE

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