gms | German Medical Science

Objective: 5-Aminolevulinic acid (5-ALA)-mediated fluorescence does not regularly depict low-grade gliomas (LGG) or the infiltrative tumor portion of high-grade gliomas (HGG). While spectroscopic measurements improve sensitivity and precision, the quality of the generated data is currently limited by the presence of a second protoporphyrin IX (PpIX) fluorescence state at 620 nm and of autofluorescence from endogenous fluorophores. In this study, we investigated the autofluorescence to better characterize the present spectra and thus achieve more precise and sensitive PpIX quantification.

Methods: Patients undergoing 5-ALA mediated surgery for malignant glioma were included in this study. Fluorescence was assessed in one or more biopsies per patient and measured ex vivo using a hyperspectral device. Autofluorescence spectra were derived from the measurements by analyzing spectral features consistently present in the data that were independent of other features and comparing them to known fluorophores available in the literature. The contributions of the 620nm and 634nm PpIX state, and their ratio, Ratio620/634 were analyzed.

Results: Overall, in 128 patients, 2692 measured spectra in 275 biopsies were analyzed. It was found that all measurements consist of a combination of the 620nm and 634nm PpIX fluorescent states, as well as NADH, lipofuscin, and flavins. The basis spectra were characterized and their use in spectral unmixing led to 82.4% lower fitting error for weakly fluorescing areas (p < 0.001), and 92.3% fewer false-positive tumor identifications in control measurements (p = 0.0065) compared to previous works. They also decreased the PpIX620 contribution, thus halving the mean Ratio620/634 (p < 0.001). The ratio was approximately 0 for HGGs and increasing for LGGs, as demonstrated previously. Additionally, the Ratio620/634, the MIB-1/Ki-67 proliferation index, and the PpIX peak blue-shift were found to be significantly related to WHO grade, fluorescence visibility, and PpIX contribution (p < 0.001).

Conclusion: With this algorithm, it is possible to more accurately delineate the tumor margins, avoid false positives, and precisely calculate the PpIX contributions. This was found consistently in a large and diverse cohort of patients. This new analysis procedure also leads to different Ratio620/634 values than previously reported, though the general trend remains the same. Nevertheless, further studies are required before the ratio can serve as a biomarker to classify tumor regions.