三维术中光场荧光成像系统用于PpIX引导的肿瘤切除
Three-dimensional intraoperative light field fluorescence imaging system for PpIX-guided tumour resection
AI总结：
本文提出一种双模光场成像系统，通过优化镜头焦距和深度映射，实现单次拍摄中获取三维结构和深度校正的荧光信息，用于提高术中肿瘤切除的准确性和荧光分级评估。
摘要：
传统2D荧光成像在胶质瘤手术中无法区分内源性荧光强度与深度衰减，导致深度-强度模糊，可能影响残余肿瘤评估和荧光分级。本研究开发并验证了一种双模式光场成像系统，通过采用商用Lytro Illum相机，可在单次快门中捕获三维结构和深度校正的荧光。通过定制的3D打印深度标准优化主镜头焦距，并从Lytro Desktop深度图中推导出灰度-距离线性关系。CdSe/ZnS量子点目标和荧光脑仿生体被成像以建立荧光强度距离衰减模型并恢复内源性荧光。在系统优化中，随着FU的增加，灰度深度线性性增强，实现了毫米级垂直分辨率（R² > 0.95）（FU ≥ 60 mm）。高浓度量子点井的荧光目标显示出一致的衰减。在荧光模式中，六个区域的荧光脑仿生体距离估计偏差为0.14至2.45%，基于荧光强度-距离模型的强度预测误差从-11.73%到6.08%，能够恢复内源性量子点浓度，这些浓度模拟了胶质瘤中的PpIX特性。本研究支持光场成像作为深度解析定量荧光和改进术中肿瘤特征化的实用方法。
英文摘要：
Conventional 2D fluorescence imaging in glioma surgery cannot separate intrinsic fluorophore strength from attenuation with depth, creating depth-intensity ambiguity that can compromise assessment of residual tumour and fluorescence based grading. This study develops and validates a dual mode light field imaging system that could capture 3D structure and depth corrected fluorescence in a single snapshot by adapting a commercial Lytro Illum camera. A custom 3D printed depth standard was used to optimise main lens focal length and to derive a grayscale - distance linearity from Lytro Desktop depth maps. CdSe/ZnS quantum dot targets and fluorescent brain phantoms were imaged to establish fluorescence intensity distance attenuation models and to recover intrinsic fluorescence. In system optimisation, the increasing FU strengthened grayscale depth linearity and achieved millimetre scale vertical resolution ($R^{2}$ > 0.95) for FU $\ge$ 60 mm. Higher concentration quantum dot wells of the fluorescent target showed consistent attenuation. In fluorescence mode, the deviations of distance estimations across six regions of a fluorescent brain phantom were 0.14 to 2.45% with intensity prediction errors from -11.73% to 6.08% based on the fluorescence intensity-distance model, enabling recovery of intrinsic quantum dot concentrations which are mimicking PpIX characteristics in glioma. This research supports light field imaging as a practical approach for depth resolved quantitative fluorescence and improved intraoperative tumour characterisation.
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