{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,13]],"date-time":"2025-09-13T16:24:25Z","timestamp":1757780665605,"version":"3.37.3"},"reference-count":18,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2017,12,1]],"date-time":"2017-12-01T00:00:00Z","timestamp":1512086400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2017,12,1]],"date-time":"2017-12-01T00:00:00Z","timestamp":1512086400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Manual grading of lesions in retinal images is relevant to clinical management and clinical trials, but it is time-consuming and expensive. Furthermore, it collects only limited information - such as lesion size or frequency. The spatial distribution of lesions is ignored, even though it may contribute to the overall clinical assessment of disease severity, and correspond to microvascular and physiological topography. Capillary non-perfusion (CNP) lesions are central to the pathogenesis of major causes of vision loss. Here we propose a novel method to analyse CNP using spatial statistical modelling. This quantifies the percentage of CNP-pixels in each of 48 sectors and then characterises the spatial distribution with goniometric functions. We applied our spatial approach to a set of images from patients with malarial retinopathy, and found it compares favourably with the raw percentage of CNP-pixels and also with manual grading. Furthermore, we were able to quantify a biological characteristic of macular CNP in malaria that had previously only been described subjectively: clustering at the temporal raphe. Microvascular location is likely to be biologically relevant to many diseases, and so our spatial approach may be applicable to a diverse range of pathological features in the retina and other organs.<\/jats:p>","DOI":"10.1038\/s41598-017-16620-x","type":"journal-article","created":{"date-parts":[[2017,11,27]],"date-time":"2017-11-27T14:56:05Z","timestamp":1511794565000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Spatial statistical modelling of capillary non-perfusion in the retina"],"prefix":"10.1038","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8171-0332","authenticated-orcid":false,"given":"Ian J. C.","family":"MacCormick","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yalin","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Silvester","family":"Czanner","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yitian","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peter J.","family":"Diggle","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simon P.","family":"Harding","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gabriela","family":"Czanner","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,12,1]]},"reference":[{"key":"16620_CR1","unstructured":"Dithmar, S. & Holz, F. G. Fluorescence angiography in ophthalmology: fluorescein angiography, indocyanine green angiography, fundus autofluorescence (Springer, 2008)."},{"key":"16620_CR2","doi-asserted-by":"publisher","DOI":"10.1186\/s12936-015-0897-7","volume":"14","author":"IJC MacCormick","year":"2015","unstructured":"MacCormick, I. J. C. et al. Grading fluorescein angiograms in malarial retinopathy. Malar. J. \n                           14, 367 (2015).","journal-title":"Malar. J."},{"key":"16620_CR3","doi-asserted-by":"publisher","first-page":"2119","DOI":"10.1093\/brain\/awu001","volume":"137","author":"IJC MacCormick","year":"2014","unstructured":"MacCormick, I. J. C. et al. Cerebral malaria in children: using the retina to study the brain. Brain. \n                           137, 2119\u20132142 (2014).","journal-title":"Brain."},{"key":"16620_CR4","first-page":"39","volume":"7","author":"S Sakimoto","year":"2013","unstructured":"Sakimoto, S. et al. Relationship between grades of macular perfusion and foveal thickness in branch retinal vein occlusion. Clin. Ophthalmol. \n                           7, 39\u201345 (2013).","journal-title":"Clin. Ophthalmol."},{"key":"16620_CR5","doi-asserted-by":"publisher","first-page":"1140","DOI":"10.1001\/archophthalmol.2010.193","volume":"128","author":"BA Blodi","year":"2010","unstructured":"Blodi, B. A. et al. Standard Care vs Corticosteroid for Retinal Vein Occlusion (SCORE) Study system for evaluation of stereoscopic color fundus photographs and fluorescein angiograms: SCORE Study Report 9. Arch. Ophthalmol. \n                           128, 1140\u20131145 (2010).","journal-title":"Arch. Ophthalmol."},{"key":"16620_CR6","doi-asserted-by":"publisher","first-page":"367","DOI":"10.1001\/jamaophthalmol.2015.5658","volume":"134","author":"TS Hwang","year":"2016","unstructured":"Hwang, T. S. et al. Automated Quantification of Capillary Nonperfusion Using Optical Coherence Tomography Angiography in Diabetic Retinopathy. JAMA Ophthalmol. \n                           134, 367\u2013373 (2016).","journal-title":"JAMA Ophthalmol."},{"key":"16620_CR7","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1016\/j.mvr.2013.06.008","volume":"89","author":"H Jiang","year":"2013","unstructured":"Jiang, H. et al. Automated segmentation and fractal analysis of high-resolution non-invasive capillary perfusion maps of the human retina. Microvasc. Res. \n                           89, 172\u2013175 (2013).","journal-title":"Microvasc. Res."},{"key":"16620_CR8","doi-asserted-by":"crossref","unstructured":"Zheng, Y. L. et al. A Comprehensive Texture Segmentation Framework for Segmentation of Capillary Non-Perfusion Regions in Fundus Fluorescein Angiograms. PLoS ONE \n                           9 (e93624) (2014).","DOI":"10.1371\/journal.pone.0093624"},{"key":"16620_CR9","unstructured":"Cressie, N. A. C. Statistics for spatial data (Wiley, 2013)."},{"key":"16620_CR10","doi-asserted-by":"crossref","unstructured":"Friston, K. J. et al. Statistical parametric mapping: the analysis of functional brain images (Academic Press, 2007).","DOI":"10.1016\/B978-012372560-8\/50002-4"},{"key":"16620_CR11","doi-asserted-by":"publisher","first-page":"965","DOI":"10.1002\/sim.1741","volume":"23","author":"FD Bowman","year":"2004","unstructured":"Bowman, F. D. & Waller, L. A. Modelling of cardiac imaging data with spatial correlation. Stat. Med. \n                           23, 965\u2013985 (2004).","journal-title":"Stat. Med."},{"key":"16620_CR12","doi-asserted-by":"publisher","first-page":"527","DOI":"10.1214\/16-AOAS911","volume":"10","author":"B George","year":"2016","unstructured":"George, B. et al. Applying a spatiotemporal model for longitudinal cardiac imaging data. Ann. Appl. Stat. \n                           10, 527\u2013548 (2016).","journal-title":"Ann. Appl. Stat."},{"key":"16620_CR13","doi-asserted-by":"crossref","unstructured":"Lange, N. Statistical procedures for functional MRI in Functional MRI (ed. Moonen, C. W. T. & Bandettini P. A.) 301-335 (Springer-Verlag, 2000).","DOI":"10.1007\/978-3-642-58716-0_27"},{"key":"16620_CR14","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1002\/hbm.10127","volume":"20","author":"FD Bowman","year":"2003","unstructured":"Bowman, F. D. & Kilts, C. Modeling intra-subject correlation among repeated scans in positron emission tomography (PET) neuroimaging data. Human Brain Mapp. \n                           20, 59\u201370 (2003).","journal-title":"Human Brain Mapp."},{"key":"16620_CR15","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1167\/iovs.15-18287","volume":"57","author":"SG Gadde","year":"2016","unstructured":"Gadde, S. G. et al. Quantification of Vessel Density in Retinal Optical Coherence Tomography Angiography Images Using Local Fractal Dimension. Invest. Ophthalmol. Vis. Sci. \n                           57, 246\u201352 (2016).","journal-title":"Invest. Ophthalmol. Vis. Sci."},{"key":"16620_CR16","doi-asserted-by":"crossref","unstructured":"Taylor, T. E. Caring for children with cerebral malaria: insights gleaned from 20 years on a research ward in Malawi. Trans. R. Soc. Trop. Med. Hyg. 103, Supplement, S6\u2013S10 (2009).","DOI":"10.1016\/j.trstmh.2008.10.049"},{"key":"16620_CR17","doi-asserted-by":"crossref","unstructured":"Pinheiro, J. C. & Bates, D. M. Mixed-Effects Models in S and S-PLUS (Springer, 2000).","DOI":"10.1007\/978-1-4419-0318-1"},{"key":"16620_CR18","unstructured":"Raudenbush, S. W. & Bryk, A. S. Hierarchical Linear Models: Applications and Data Analysis Methods (Sage Publications, 2002)."}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-017-16620-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-017-16620-x","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-017-16620-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T14:49:29Z","timestamp":1671806969000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-017-16620-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,12,1]]},"references-count":18,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2017,12]]}},"alternative-id":["16620"],"URL":"https:\/\/doi.org\/10.1038\/s41598-017-16620-x","relation":{},"ISSN":["2045-2322"],"issn-type":[{"type":"electronic","value":"2045-2322"}],"subject":[],"published":{"date-parts":[[2017,12,1]]},"assertion":[{"value":"4 August 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 November 2017","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 December 2017","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare that they have no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing Interests"}}],"article-number":"16792"}}