Elaboration of a semi-automated algorithm for brain arteriovenous malformation segmentation: initial results.
Objectives: The purpose of our study was to distinguish the different components of a brain arteriovenous malformation (bAVM) on 3D rotational angiography (3D-RA) using a semi-automated segmentation algorithm.Materials and Methods: Data from 3D-RA of 15 patients (8 males, 7 females; 14 supratentoria...
| Publicado en: | European Radiology Vol. 25; no. 2; pp. 436 - 444 |
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| Autores principales: | , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Feb2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=110136745&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 110136745 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09387994 NPH jtl: European Radiology issn: 09387994 maglogo: N pubinfo: dt: Feb2015 vid: 25 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 110136745 NLM25239185 2012873604 10.1007/s00330-014-3421-5 NLM25239185 110136745 ppf: 436 ppct: 8 formats: fmt: @attributes: type: P tig: atl: Elaboration of a semi-automated algorithm for brain arteriovenous malformation segmentation: initial results. aug: au: Clarençon, Frédéric Maizeroi-Eugène, Franck Bresson, Damien Maingreaud, Flavien Sourour, Nader Couquet, Claude Ayoub, David Chiras, Jacques Yardin, Catherine Mounayer, Charbel affil: Department of Interventional Neuroradiology, Pitié-Salpêtrière Hospital, Paris VI University, 47, Bd de l'Hôpital, 75013, Paris, France, fredclare5@msn.com. sug: subj: Algorithms Angiography, Digital Subtraction Methods Cerebral Angiography Methods Imaging, Three-Dimensional Arteriovenous Malformations Radiography Adolescence Adult Aged Child Female Human Male Middle Age Reproducibility of Results Young Adult Adolescent: 13-18 years Adult: 19-44 years Aged: 65+ years Child: 6-12 years Middle Aged: 45-64 years Female Male ab: Objectives: The purpose of our study was to distinguish the different components of a brain arteriovenous malformation (bAVM) on 3D rotational angiography (3D-RA) using a semi-automated segmentation algorithm.Materials and Methods: Data from 3D-RA of 15 patients (8 males, 7 females; 14 supratentorial bAVMs, 1 infratentorial) were used to test the algorithm. Segmentation was performed in two steps: (1) nidus segmentation from propagation (vertical then horizontal) of tagging on the reference slice (i.e., the slice on which the nidus had the biggest surface); (2) contiguity propagation (based on density and variance) from tagging of arteries and veins distant from the nidus. Segmentation quality was evaluated by comparison with six frame/s DSA by two independent reviewers. Analysis of supraselective microcatheterisation was performed to dispel discrepancy.Results: Mean duration for bAVM segmentation was 64 ± 26 min. Quality of segmentation was evaluated as good or fair in 93% of cases. Segmentation had better results than six frame/s DSA for the depiction of a focal ectasia on the main draining vein and for the evaluation of the venous drainage pattern.Conclusion: This segmentation algorithm is a promising tool that may help improve the understanding of bAVM angio-architecture, especially the venous drainage.Key Points: • The segmentation algorithm allows for the distinction of the AVM's components • This algorithm helps to see the venous drainage of bAVMs more precisely • This algorithm may help to reduce the treatment-related complication rate. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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