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

571 results found

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

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

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

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

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

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

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

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

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 BM, Weaver J, Multiple Sclerosis Outcome Assessments Consortium MSOACet al., 2018, The MSOAC approach to developing performance outcomes to measure and monitor multiple sclerosis disability., Mult Scler, Vol: 24, Pages: 1469-1484

BACKGROUND: The Multiple Sclerosis Outcome Assessments Consortium (MSOAC) was formed by the National MS Society to develop improved measures of multiple sclerosis (MS)-related disability. OBJECTIVES: (1) To assess the current literature and available data on functional performance outcome measures (PerfOs) and (2) to determine suitability of using PerfOs to quantify MS disability in MS clinical trials. METHODS: (1) Identify disability dimensions common in MS; (2) conduct a comprehensive literature review of measures for those dimensions; (3) develop an MS Clinical Data Interchange Standards Consortium (CDISC) data standard; (4) create a database of standardized, pooled clinical trial data; (5) analyze the pooled data to assess psychometric properties of candidate measures; and (6) work with regulatory agencies to use the measures as primary or secondary outcomes in MS clinical trials. CONCLUSION: Considerable data exist supporting measures of the functional domains ambulation, manual dexterity, vision, and cognition. A CDISC standard for MS ( http://www.cdisc.org/therapeutic#MS ) was published, allowing pooling of clinical trial data. MSOAC member organizations contributed clinical data from 16 trials, including 14,370 subjects. Data from placebo-arm subjects are available to qualified researchers. This integrated, standardized dataset is being analyzed to support qualification of disability endpoints by regulatory agencies.

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

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

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

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

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

Bai W, Oktay O, Sinclair M, Suzuki H, Rajchl M, Tarroni G, Glocker B, King A, Matthews PM, Rueckert Det al., 2017, Semi-supervised learning for network-based cardiac MR image segmentation, Pages: 253-260, ISSN: 0302-9743

© Springer International Publishing AG 2017. Training a fully convolutional network for pixel-wise (or voxel-wise) image segmentation normally requires a large number of training images with corresponding ground truth label maps. However, it is a challenge to obtain such a large training set in the medical imaging domain, where expert annotations are time-consuming and difficult to obtain. In this paper, we propose a semi-supervised learning approach, in which a segmentation network is trained from both labelled and unlabelled data. The network parameters and the segmentations for the unlabelled data are alternately updated. We evaluate the method for short-axis cardiac MR image segmentation and it has demonstrated a high performance, outperforming a baseline supervised method. The mean Dice overlap metric is 0.92 for the left ventricular cavity, 0.85 for the myocardium and 0.89 for the right ventricular cavity. It also outperforms a state-of-the-art multi-atlas segmentation method by a large margin and the speed is substantially faster.

CONFERENCE PAPER

Bishop CA, Newbould RD, Lee JSZ, Honeyfield L, Quest R, Colasanti A, Ali R, Mattoscio M, Cortese A, Nicholas R, Matthews PM, Muraro PA, Waldman ADet al., 2017, Analysis of ageing-associated grey matter volume in patients with multiple sclerosis shows excess atrophy in subcortical regions, NEUROIMAGE-CLINICAL, Vol: 13, Pages: 9-15, ISSN: 2213-1582

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, 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

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

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

Gafson A, Craner MJ, Matthews PM, 2017, Personalised medicine for multiple sclerosis care, MULTIPLE SCLEROSIS JOURNAL, Vol: 23, Pages: 362-369, ISSN: 1352-4585

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

Gibson LM, Littlejohns TJ, Adamska L, Garratt S, Doherty N, UK Biobank Imaging Working Group, Wardlaw JM, Maskell G, Parker M, Brownsword R, Matthews PM, Collins R, Allen NE, Sellors J, Sudlow CLet al., 2017, Impact of detecting potentially serious incidental findings during multi-modal imaging., Wellcome Open Res, Vol: 2, ISSN: 2398-502X

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 participants and burdening

JOURNAL ARTICLE

Giovannoni G, Cutter G, Sormani MP, Belachew S, Hyde R, Koendgen H, Knappertz V, Tomic D, Leppert D, Herndon R, Wheeler-Kingshott CAM, Ciccarelli O, Selwood D, di Cantogno EV, Ben-Amor A-F, Matthews P, Carassiti D, Baker D, Schmierer Ket al., 2017, Is multiple sclerosis a length-dependent central axonopathy? The case for therapeutic lag and the asynchronous progressive MS hypotheses., Mult Scler Relat Disord, Vol: 12, Pages: 70-78

Trials of anti-inflammatory therapies in non-relapsing progressive multiple sclerosis (MS) have been stubbornly negative except recently for an anti-CD20 therapy in primary progressive MS and a S1P modulator siponimod in secondary progressive MS. We argue that this might be because trials have been too short and have focused on assessing neuronal pathways, with insufficient reserve capacity, as the core component of the primary outcome. Delayed neuroaxonal degeneration primed by prior inflammation is not expected to respond to disease-modifying therapies targeting MS-specific mechanisms. However, anti-inflammatory therapies may modify these damaged pathways, but with a therapeutic lag that may take years to manifest. Based on these observations we propose that clinically apparent neurodegenerative components of progressive MS may occur in a length-dependent manner and asynchronously. If this hypothesis is confirmed it may have major implications for the future design of progressive MS trials.

JOURNAL ARTICLE

He S, Yong M, Matthews PM, Guo Yet al., 2017, tranSMART-XNAT Connector tranSMART-XNAT connector-image selection based on clinical phenotypes and genetic profiles, BIOINFORMATICS, Vol: 33, Pages: 787-788, ISSN: 1367-4803

JOURNAL ARTICLE

Kalk NJ, Guo Q, Owen D, Cherian R, Erritzoe D, Gilmour A, Ribeiro AS, McGonigle J, Waldman A, Matthews P, Cavanagh J, McInnes I, Dar K, Gunn R, Rabiner EA, Lingford-Hughes ARet al., 2017, Decreased hippocampal translocator protein (18kDa) expression in alcohol dependence: a [C-11] PBR28 PET study, TRANSLATIONAL PSYCHIATRY, Vol: 7, ISSN: 2158-3188

JOURNAL ARTICLE

Lema A, Bishop C, Malik O, Mattoscio M, Ali R, Nicholas R, Muraro PA, Matthews PM, Waldman AD, Newbould RDet al., 2017, A Comparison of Magnetization Transfer Methods to Assess Brain and Cervical Cord Microstructure in Multiple Sclerosis, JOURNAL OF NEUROIMAGING, Vol: 27, Pages: 221-226, ISSN: 1051-2284

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

Nie L, Yang X, Matthews PM, Xu Z-W, Guo Y-Ket al., 2017, Inferring Functional Connectivity in fMRI Using Minimum Partial Correlation, INTERNATIONAL JOURNAL OF AUTOMATION AND COMPUTING, Vol: 14, Pages: 371-385, ISSN: 1476-8186

JOURNAL ARTICLE

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