Label-free multiphoton imaging allows brain tumor recognition based on texture analysis-a study of 382 tumor patients.
Neurooncol Adv
; 2(1): vdaa035, 2020.
Article
in En
| MEDLINE
| ID: mdl-32642692
ABSTRACT
BACKGROUND:
Label-free multiphoton microscopy has been suggested for intraoperative recognition and delineation of brain tumors. For any future clinical application, appropriate approaches for image acquisition and analysis have to be developed. Moreover, an evaluation of the reliability of the approach, taking into account inter- and intrapatient variability, is needed.METHODS:
Coherent anti-Stokes Raman scattering (CARS), two-photon excited fluorescence (TPEF), and second-harmonic generation were acquired on cryosections of brain tumors of 382 patients and 28 human nontumor brain samples. Texture parameters of those images were calculated and used as input for linear discriminant analysis.RESULTS:
The combined analysis of texture parameters of the CARS and TPEF signal proved to be most suited for the discrimination of nontumor brain versus brain tumors (low- and high-grade astrocytoma, oligodendroglioma, glioblastoma, recurrent glioblastoma, brain metastases of lung, colon, renal, and breast cancer and of malignant melanoma) leading to a correct rate of 96% (sensitivity 96%, specificity 100%). To approximate the clinical setting, the results were validated on 42 fresh, unfixed tumor biopsies. 82% of the tumors and, most important, all of the nontumor samples were correctly recognized. An image resolution of 1 µm was sufficient to distinguish brain tumors and nontumor brain. Moreover, the vast majority of single fields of view of each patient's sample were correctly classified with high probabilities, which is important for clinical translation.CONCLUSION:
Label-free multiphoton imaging might allow fast and accurate intraoperative delineation of primary and secondary brain tumors in combination with endoscopic systems.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
Neurooncol Adv
Year:
2020
Document type:
Article
Affiliation country:
Germany