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手术期间用于近红外标记物地下定量的宏观成像技术。

Macroscopic-imaging technique for subsurface quantification of near-infrared markers during surgery.

作者信息

Jermyn Michael, Kolste Kolbein, Pichette Julien, Sheehy Guillaume, Angulo-Rodríguez Leticia, Paulsen Keith D, Roberts David W, Wilson Brian C, Petrecca Kevin, Leblond Frederic

机构信息

McGill University, Brain Tumour Research Centre, Montreal Neurological Institute and Hospital, Department of Neurology and Neurosurgery, 3801 University Street, Montreal, Quebec H3A 2B4, CanadabPolytechnique Montreal, Department of Engineering Physics, CP.

Dartmouth College, Thayer School of Engineering, 14 Engineering Drive, Hanover, New Hampshire 03755, United States.

出版信息

J Biomed Opt. 2015 Mar;20(3):036014. doi: 10.1117/1.JBO.20.3.036014.

Abstract

Obtaining accurate quantitative information on the concentration and distribution of fluorescent markers lying at a depth below the surface of optically turbid media, such as tissue, is a significant challenge. Here, we introduce a fluorescence reconstruction technique based on a diffusion light transport model that can be used during surgery, including guiding resection of brain tumors, for depth-resolved quantitative imaging of near-infrared fluorescent markers. Hyperspectral fluorescence images are used to compute a topographic map of the fluorophore distribution, which yields structural and optical constraints for a three-dimensional subsequent hyperspectral diffuse fluorescence reconstruction algorithm. Using the model fluorophore Alexa Fluor 647 and brain-like tissue phantoms, the technique yielded estimates of fluorophore concentration within ±25% of the true value to depths of 5 to 9 mm, depending on the concentration. The approach is practical for integration into a neurosurgical fluorescence microscope and has potential to further extend fluorescence-guided resection using objective and quantified metrics of the presence of residual tumor tissue.

摘要

获取关于位于诸如组织等光学浑浊介质表面以下深度处的荧光标记物浓度和分布的准确定量信息是一项重大挑战。在此,我们介绍一种基于扩散光传输模型的荧光重建技术,该技术可在手术期间使用,包括指导脑肿瘤切除,用于近红外荧光标记物的深度分辨定量成像。高光谱荧光图像用于计算荧光团分布的地形图,这为三维后续高光谱漫射荧光重建算法提供了结构和光学约束。使用模型荧光团Alexa Fluor 647和类脑组织模型,该技术在5至9毫米深度处产生的荧光团浓度估计值与真实值的偏差在±25%以内,具体取决于浓度。该方法对于集成到神经外科荧光显微镜中是切实可行的,并且有潜力使用残留肿瘤组织存在的客观和量化指标进一步扩展荧光引导切除。

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