提出新方法精准量化胶质瘤中PpIX荧光，提升手术导航准确性
Quantification of dual-state 5-ALA-induced PpIX fluorescence: Methodology and validation in tissue-mimicking phantoms
- 通过无先验光谱信息的分离算法区分两种PpIX发光态
- 在类组织幻影上验证，与真实浓度相关性达R²=0.918±0.002
- 适合临床神经肿瘤荧光成像，尤其需精准定位的手术场景
原卟啉IX（PpIX）荧光在脑瘤中的定量检测有望显著改善神经肿瘤患者预后，但面临巨大成像挑战。在胶质瘤中，PpIX因微环境差异形成两种光化学状态，量子效率不同，发射光谱显著重叠且与组织自体荧光交叉。荧光信号受组织固有光学特性影响，并伴随胶质瘤内高度异质性。现有定量荧光系统多基于简化幻影验证，未能同步模拟荧光分子与组织光学特性的复杂交互。为此，本文提出新型量化流程，可不依赖先验光谱信息，有效区分两种PpIX发射态与背景自体荧光，并校正其量子效率差异；解混后的信号经波长相关光学畸变校正并加权，实现准确量化。该流程在全新设计的、模拟胶质瘤组织光学特性与PpIX光化学变异性的真实组织幻影上开发并验证，与真实PpIX浓度呈现强相关性（R² = 0.918 ± 0.002），展现出在临床环境中实现稳健、定量荧光成像的巨大潜力。
原文摘要 · Abstract (English)
Quantification of protoporphyrin IX (PpIX) fluorescence in human brain tumours has the potential to significantly improve patient outcomes in neuro-oncology, but represents a formidable imaging challenge. Protoporphyrin is a biological molecule which interacts with the tissue micro-environment to form two photochemical states in glioma. Each exhibits markedly different quantum efficiencies, with distinct but overlapping emission spectra that also overlap with tissue autofluorescence. Fluorescence emission is known to be distorted by the intrinsic optical properties of tissue, coupled with marked intra-tumoural heterogeneity as a hallmark of glioma tumours. Existing quantitative fluorescence systems are developed and validated using simplified phantoms that do not simultaneously mimic the complex interactions between fluorophores and tissue optical properties or micro-environment. Consequently, existing systems risk introducing systematic errors into PpIX quantification when used in tissue. In this work, we introduce a novel pipeline for quantification of PpIX in glioma, which robustly differentiates both emission states from background autofluorescence without reliance on a priori spectral information, and accounts for variations in their quantum efficiency. Unmixed PpIX emission forms are then corrected for wavelength-dependent optical distortions and weighted for accurate quantification. Significantly, this pipeline is developed and validated using novel tissue-mimicking phantoms replicating the optical properties of glioma tissues and photochemical variability of PpIX fluorescence in glioma. Our workflow achieves strong correlation with ground-truth PpIX concentrations (R2 = 0.918+-0.002), demonstrating its potential for robust, quantitative PpIX fluorescence imaging in clinical settings.
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