Characterization of autofluorescence and quantitative protoporphyrin IX biomarkers for optical spectroscopy-guided glioma surgery

Abstract

Abstract5-Aminolevulinic acid (5-ALA)-mediated fluorescence does not effectively depict low grade gliomas (LGG) or the infiltrative tumor portion of high-grade gliomas (HGG). While spectroscopy improves sensitivity and precision, this is currently limited by autofluorescence and a second protoporphyrin IX (PpIX) fluorescence state at 620 nm. We investigated the autofluorescence to better characterize the present spectra and thus increase PpIX quantification precision and sensitivity. This study included 128 patients undergoing surgery for malignant glioma. 5-ALA (Gliolan) was administered before anesthesia, and fluorescence was measured using a hyperspectral device. It was found that all 2692 measured spectra consisted of contributions from 620 to 634 nm PpIX, 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), and the value of these three as quantitative biomarkers is discussed.

5-Aminolevulinic Acid-Induced Protoporphyrin IX Fluorescence Imaging for Tumor Detection: Recent Advances and Challenges

“…Tissue-derived autofluorescence can hamper PpIX fluorescence detection. For example, the accumulated concentration of PpIX is low in LGGs and marginal lesions of HGGs, making it difficult to analyze PpIX fluorescence because it is masked by background autofluorescence signals derived from FAD, collagen, and other molecules [ 11 ]. In addition, digestive tissues exhibit strong collagen-derived autofluorescence, which overlaps with PpIX fluorescence [ 14 , 15 ].…”

“…The signal intensity of PpIX fluorescence depends on the type and number of tumors; low-grade gliomas (LGGs), invasive margins of high-grade gliomas (HGGs), and gastrointestinal cancers generally emit only weak fluorescence after 5-ALA administration. PpIX fluorescence is reported to be attenuated at the margins of the HGGs, making accurate identification of tumor margins difficult [ 1 , 7 , 8 , 9 , 10 , 11 , 12 ]. In tumors that emit relatively weak PpIX signals, tissue autofluorescence derived from collagen and flavin adenine dinucleotide (FAD) affects their ability to be detected [ 13 ].…”

Robust estimation of 5-ALA-induced PpIX multiple-wavelength excitation fluorescence spectroscopy for improving glioma classification

“…These fluorophores and their high variability can lead to important crosstalks with PpIX. [8][9][10] To avoid crosstalk, the overall approach is to model the baseline with everything that is not due to 5-ALA-induced PpIX. Existing approaches are effective when the emission spectral band of the baseline is far from the one of the PpIX.…”

“…Existing approaches are effective when the emission spectral band of the baseline is far from the one of the PpIX. 8,[11][12][13] The baseline is modeled by a Gaussian function, 14,15 or expert dependent weighted sum, which contain a finite number of fluorophores whose fluorescence spectral shape is assumed known. 8,16 However, fluorophores that overlap with PpIX spectral emission band are difficult to consider.…”

“…8,[11][12][13] The baseline is modeled by a Gaussian function, 14,15 or expert dependent weighted sum, which contain a finite number of fluorophores whose fluorescence spectral shape is assumed known. 8,16 However, fluorophores that overlap with PpIX spectral emission band are difficult to consider. These important crosstalks largely impact specificity.…”