A new approach for clinical translation of infrared spectroscopy: exploitation of the signature of glioblastoma for general brain tumor recognition

• Published in: Journal of neuro-oncology Vol. 161; no. 1; pp. 57 - 66
• Main Authors: Steiner, Gerald, Galli, Roberta, Preusse, Grit, Michen, Susanne, Meinhardt, Matthias, Temme, Achim, Sobottka, Stephan B., Juratli, Tareq A., Koch, Edmund, Schackert, Gabriele, Kirsch, Matthias, Uckermann, Ortrud
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.01.2023; Springer Nature B.V
• Subjects: Brain - pathology; Brain cancer; Brain Neoplasms - diagnosis; Brain Neoplasms - pathology; Brain Neoplasms - surgery; Brain tumors; Discriminant analysis; Glioblastoma; Glioblastoma - pathology; Glioblastoma - surgery; Glioma - pathology; Humans; Infrared spectroscopy; Medicine; Medicine & Public Health; Metastases; Neurology; Neurosurgery; Oncology; Principal components analysis; Spectrophotometry, Infrared - methods; Spectroscopy, Fourier Transform Infrared - methods; Spectrum analysis; Translation; Tumors; Brain tumor; Infrared spectroscopy; Intraoperative; Delineation
• ISSN: 0167-594X; 1573-7373
• DOI: 10.1007/s11060-022-04204-3

Purpose Infrared (IR) spectroscopy has the potential for tumor delineation in neurosurgery. Previous research showed that IR spectra of brain tumors are generally characterized by reduced lipid-related and increased protein-related bands. Therefore, we propose the exploitation of these common spectral changes for brain tumor recognition. Methods Attenuated total reflection IR spectroscopy was performed on fresh specimens of 790 patients within minutes after resection. Using principal component analysis and linear discriminant analysis, a classification model was developed on a subset of glioblastoma (n = 135) and non-neoplastic brain (n = 27) specimens, and then applied to classify the IR spectra of several types of brain tumors. Results The model correctly classified 82% (517/628) of specimens as “tumor” or “non-tumor”, respectively. While the sensitivity was limited for infiltrative glioma, this approach recognized GBM (86%), other types of primary brain tumors (92%) and brain metastases (92%) with high accuracy and all non-tumor samples were correctly identified. Conclusion The concept of differentiation of brain tumors from non-tumor brain based on a common spectroscopic tumor signature will accelerate clinical translation of infrared spectroscopy and related technologies. The surgeon could use a single instrument to detect a variety of brain tumor types intraoperatively in future clinical settings. Our data suggests that this would be associated with some risk of missing infiltrative regions or tumors, but not with the risk of removing non-tumor brain.