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

## TL;DR

This paper introduces a new method to accurately measure PpIX fluorescence in brain tumors using realistic tissue-like models, improving potential clinical applications.

## Contribution

A novel pipeline for PpIX quantification that differentiates dual emission states and accounts for optical distortions in tissue-mimicking phantoms.

## Key findings

- The pipeline achieves strong correlation with ground-truth PpIX concentrations (R² = 0.918 ± 0.002).
- The method differentiates dual PpIX emission states without relying on prior spectral information.
- Tissue-mimicking phantoms replicate glioma optical properties and PpIX fluorescence variability.

## 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 (\documentclass[12pt]{minimal}
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$R^2 = 0.918 \pm 0.002$\end{document}R2=0.918±0.002), demonstrating its potential for robust, quantitative PpIX fluorescence imaging in clinical settings.