Quantification of dual-state 5-ALA-induced PpIX fluorescence: Methodology and validation in tissue-mimicking phantoms

TL;DR

This paper presents a new method for accurately quantifying PpIX fluorescence in glioma tissues, validated with tissue-mimicking phantoms, addressing previous limitations caused by tissue optical properties and heterogeneity.

Contribution

The authors develop and validate a novel pipeline that differentiates PpIX emission states from autofluorescence and corrects for optical distortions using realistic tissue phantoms.

Findings

Strong correlation with ground-truth PpIX concentrations (R2 = 0.918)

Effective differentiation of emission states without prior spectral info

Robust quantification accounting for tissue optical properties

Abstract

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.