title: Combined fluorescence and reflectance spectroscopy for in vivo quantification of cancer biomarkers in low- and high-grade glioma surgery.
abstract: Biomarkers are indicators of biological processes and hold promise for the diagnosis and treatment of disease. Gliomas represent a heterogeneous group of brain tumors with marked intra- and inter-tumor variability. The extent of surgical resection is a significant factor influencing post-surgical recurrence and prognosis. Here, we used fluorescence and reflectance spectral signatures for in vivo quantification of multiple biomarkers during glioma surgery, with fluorescence contrast provided by exogenously-induced protoporphyrin IX (PpIX) following administration of 5-aminolevulinic acid. We performed light-transport modeling to quantify multiple biomarkers indicative of tumor biological processes, including the local concentration of PpIX and associated photoproducts, total hemoglobin concentration, oxygen saturation, and optical scattering parameters. We developed a diagnostic algorithm for intra-operative tissue delineation that accounts for the combined tumor-specific predictive capabilities of these quantitative biomarkers. Tumor tissue delineation achieved accuracies of up to 94% (specificity = 94%, sensitivity = 94%) across a range of glioma histologies beyond current state-of-the-art optical approaches, including state-of-the-art fluorescence image guidance. This multiple biomarker strategy opens the door to optical methods for surgical guidance that use quantification of well-established neoplastic processes. Future work would seek to validate the predictive power of this proof-of-concept study in a separate larger cohort of patients.
authors: Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire 03755, USA. Pablo.A.Valdes@Dartmouth.edu
authors: Pablo A
authors: PA
authors: Valdés
authors: Anthony
authors: A
authors: Kim
authors: Frederic
authors: F
authors: Leblond
authors: Olga M
authors: OM
authors: Conde
authors: Brent T
authors: BT
authors: Harris
authors: Keith D
authors: KD
authors: Paulsen
authors: Brian C
authors: BC
authors: Wilson
authors: David W
authors: DW
authors: Roberts
mesh_terms: D000622:Aminolevulinic Acid / Q000008:administration & dosage / Q000493:pharmacokinetics; D014408:Biomarkers, Tumor / Q000032:analysis* / Q000737:chemistry / Q000378:metabolism; D003952:Diagnostic Imaging / Q000379:methods*; D005910:Glioma / Q000737:chemistry* / Q000378:metabolism / Q000473:pathology / Q000601:surgery*; D006801:Humans; D008954:Models, Biological; D011524:Protoporphyrins / Q000032:analysis / Q000737:chemistry / Q000378:metabolism; D012680:Sensitivity and Specificity; D013050:Spectrometry, Fluorescence / Q000379:methods*; D018709:Statistics, Nonparametric; D060388:Support Vector Machine; D025321:Surgery, Computer-Assisted / Q000379:methods*
chemical_list: D014408:Biomarkers, Tumor; D011524:Protoporphyrins; D000622:Aminolevulinic Acid; C028025:protoporphyrin IX