E. Morales, G. Saurez Martinez, Carlos Cabal Mirabal, Evelio González Dalmau
{"title":"Tool of segmentation and 3D reconstruction of MRI to quantify cranial tumor activity","authors":"E. Morales, G. Saurez Martinez, Carlos Cabal Mirabal, Evelio González Dalmau","doi":"10.1109/STSIVA.2013.6644914","DOIUrl":null,"url":null,"abstract":"Currently in the biomedical field of image processing software are used for quantitative measurement of tumor lesions, but the analysis of longitudinal studies has limitations; mainly for monitoring of treatment effect and some of this software are owners. Existing software from brain tumor diagnosis and evaluation treatment is a manual process of mensuration of the size of the tumor and alone slide measurement selected, without one a tool that integrates all the functionalities for the quantitative evaluation of the lesions and applied treatments. This justifies finding new and validated tools for imaging biomarkers (IB) applied to magnetic resonance image (MRI). A series of 29 pediatric patients, 14 females and 15 males, between 3 to 18 years, with confirmed malignant brain tumors and treated with a monoclonal antibody nimotuzumab, were evaluated during 2 years for to validate IB-MRI. The MRI were obtained with a 1.5 T MR Symphony Maestro Class System (Siemens, Germany). The protocol included weighted images in T2, T1 and FLAIR. A tool developed in Matlab was obtained. Segmentation and reconstruction methods in three dimensions (3D) were applied and were also integrated in a single interface to integrate others separate tools. Additionally includes the use of an automated method of segmentation of background noise that reduces the amount of points to be processed. The volumes calculated overlap each technique reflecting different biological realities. Our tool is effective to quantitatively evaluate the antitumor effect to treatment.","PeriodicalId":359994,"journal":{"name":"Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/STSIVA.2013.6644914","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Currently in the biomedical field of image processing software are used for quantitative measurement of tumor lesions, but the analysis of longitudinal studies has limitations; mainly for monitoring of treatment effect and some of this software are owners. Existing software from brain tumor diagnosis and evaluation treatment is a manual process of mensuration of the size of the tumor and alone slide measurement selected, without one a tool that integrates all the functionalities for the quantitative evaluation of the lesions and applied treatments. This justifies finding new and validated tools for imaging biomarkers (IB) applied to magnetic resonance image (MRI). A series of 29 pediatric patients, 14 females and 15 males, between 3 to 18 years, with confirmed malignant brain tumors and treated with a monoclonal antibody nimotuzumab, were evaluated during 2 years for to validate IB-MRI. The MRI were obtained with a 1.5 T MR Symphony Maestro Class System (Siemens, Germany). The protocol included weighted images in T2, T1 and FLAIR. A tool developed in Matlab was obtained. Segmentation and reconstruction methods in three dimensions (3D) were applied and were also integrated in a single interface to integrate others separate tools. Additionally includes the use of an automated method of segmentation of background noise that reduces the amount of points to be processed. The volumes calculated overlap each technique reflecting different biological realities. Our tool is effective to quantitatively evaluate the antitumor effect to treatment.
目前生物医学领域的图像处理软件均用于肿瘤病灶的定量测量,但纵向分析研究存在局限性;主要用于监测治疗效果和部分业主使用此软件。现有的软件从脑肿瘤的诊断和评估治疗是一个手动的过程测量肿瘤的大小和单独的幻灯片测量选择,没有一个工具,整合所有功能的定量评估病变和应用治疗。这证明了寻找新的和有效的工具来成像生物标志物(IB)应用于磁共振成像(MRI)。29名儿童患者,14名女性和15名男性,年龄在3至18岁之间,确诊恶性脑肿瘤并接受单克隆抗体尼莫妥珠单抗治疗,在2年内评估以验证IB-MRI。MRI采用1.5 T MR Symphony Maestro Class System (Siemens, Germany)。该方案包括T2、T1和FLAIR加权图像。得到了用Matlab开发的工具。应用了三维(3D)的分割和重建方法,并将其集成在一个界面中,以集成其他独立的工具。另外还包括使用自动分割背景噪声的方法,该方法减少了待处理的点的数量。计算的体积重叠了反映不同生物现实的每种技术。本工具可定量评价治疗后的抗肿瘤效果。