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New predictive model for microsurgical outcome of intracranial arteriovenous malformations: study protocol
INTRODUCTION: Although microsurgical resection is currently the first-line treatment modality for arteriovenous malformations (AVMs), microsurgery of these lesions is complicated due to the fact that they are very heterogeneous vascular anomalies. The Spetzler-Martin grading system and the supplemen...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5278248/ https://www.ncbi.nlm.nih.gov/pubmed/28132013 http://dx.doi.org/10.1136/bmjopen-2016-014063 |
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author | Tong, Xianzeng Wu, Jun Cao, Yong Zhao, Yuanli Wang, Shuo |
author_facet | Tong, Xianzeng Wu, Jun Cao, Yong Zhao, Yuanli Wang, Shuo |
author_sort | Tong, Xianzeng |
collection | PubMed |
description | INTRODUCTION: Although microsurgical resection is currently the first-line treatment modality for arteriovenous malformations (AVMs), microsurgery of these lesions is complicated due to the fact that they are very heterogeneous vascular anomalies. The Spetzler-Martin grading system and the supplementary grading system have demonstrated excellent performances in predicting the risk of AVM surgery. However, there are currently no predictive models based on multimodal MRI techniques. The purpose of this study is to propose a predictive model based on multimodal MRI techniques to assess the microsurgical risk of intracranial AVMs. METHODS AND ANALYSIS: The study consists of 2 parts: the first part is to conduct a single-centre retrospective analysis of 201 eligible patients to create a predictive model of AVM surgery based on multimodal functional MRIs (fMRIs); the second part is to validate the efficacy of the predictive model in a prospective multicentre cohort study of 400 eligible patients. Patient characteristics, AVM features and multimodal fMRI data will be collected. The functional status at pretreatment and 6 months after surgery will be analysed using the modified Rankin Scale (mRS) score. The patients in each part of this study will be dichotomised into 2 groups: those with improved or unchanged functional status (a decreased or unchanged mRS 6 months after surgery) and those with worsened functional status (an increased mRS). The first part will determine the risk factors of worsened functional status after surgery and create a predictive model. The second part will validate the predictive model and then a new AVM grading system will be proposed. ETHICS AND DISSEMINATION: The study protocol and informed consent form have been reviewed and approved by the Institutional Review Board of Beijing Tiantan Hospital Affiliated to Capital Medical University (KY2016-031-01). The results of this study will be disseminated through printed media. TRIAL REGISTRATION NUMBER: NCT02868008. |
format | Online Article Text |
id | pubmed-5278248 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-52782482017-02-07 New predictive model for microsurgical outcome of intracranial arteriovenous malformations: study protocol Tong, Xianzeng Wu, Jun Cao, Yong Zhao, Yuanli Wang, Shuo BMJ Open Research Methods INTRODUCTION: Although microsurgical resection is currently the first-line treatment modality for arteriovenous malformations (AVMs), microsurgery of these lesions is complicated due to the fact that they are very heterogeneous vascular anomalies. The Spetzler-Martin grading system and the supplementary grading system have demonstrated excellent performances in predicting the risk of AVM surgery. However, there are currently no predictive models based on multimodal MRI techniques. The purpose of this study is to propose a predictive model based on multimodal MRI techniques to assess the microsurgical risk of intracranial AVMs. METHODS AND ANALYSIS: The study consists of 2 parts: the first part is to conduct a single-centre retrospective analysis of 201 eligible patients to create a predictive model of AVM surgery based on multimodal functional MRIs (fMRIs); the second part is to validate the efficacy of the predictive model in a prospective multicentre cohort study of 400 eligible patients. Patient characteristics, AVM features and multimodal fMRI data will be collected. The functional status at pretreatment and 6 months after surgery will be analysed using the modified Rankin Scale (mRS) score. The patients in each part of this study will be dichotomised into 2 groups: those with improved or unchanged functional status (a decreased or unchanged mRS 6 months after surgery) and those with worsened functional status (an increased mRS). The first part will determine the risk factors of worsened functional status after surgery and create a predictive model. The second part will validate the predictive model and then a new AVM grading system will be proposed. ETHICS AND DISSEMINATION: The study protocol and informed consent form have been reviewed and approved by the Institutional Review Board of Beijing Tiantan Hospital Affiliated to Capital Medical University (KY2016-031-01). The results of this study will be disseminated through printed media. TRIAL REGISTRATION NUMBER: NCT02868008. BMJ Publishing Group 2017-01-27 /pmc/articles/PMC5278248/ /pubmed/28132013 http://dx.doi.org/10.1136/bmjopen-2016-014063 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/ This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
spellingShingle | Research Methods Tong, Xianzeng Wu, Jun Cao, Yong Zhao, Yuanli Wang, Shuo New predictive model for microsurgical outcome of intracranial arteriovenous malformations: study protocol |
title | New predictive model for microsurgical outcome of intracranial arteriovenous malformations: study protocol |
title_full | New predictive model for microsurgical outcome of intracranial arteriovenous malformations: study protocol |
title_fullStr | New predictive model for microsurgical outcome of intracranial arteriovenous malformations: study protocol |
title_full_unstemmed | New predictive model for microsurgical outcome of intracranial arteriovenous malformations: study protocol |
title_short | New predictive model for microsurgical outcome of intracranial arteriovenous malformations: study protocol |
title_sort | new predictive model for microsurgical outcome of intracranial arteriovenous malformations: study protocol |
topic | Research Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5278248/ https://www.ncbi.nlm.nih.gov/pubmed/28132013 http://dx.doi.org/10.1136/bmjopen-2016-014063 |
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