@article{MeyerGerhardHartmannLodesetal.2021,
  author    = {Meyer, Till Jasper and Gerhard-Hartmann, Elena and Lodes, Nina and Scherzad, Agmal and Hagen, Rudolf and Steinke, Maria and Hackenberg, Stephan},
  title     = {Pilot study on the value of Raman spectroscopy in the entity assignment of salivary gland tumors},
  series = {PLoS One},
  volume    = {16},
  journal   = {PLoS One},
  number    = {9},
  doi       = {10.1371/journal.pone.0257470},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-264736},
  year      = {2021},
  abstract  = {Background The entity assignment of salivary gland tumors (SGT) based on histomorphology can be challenging. Raman spectroscopy has been applied to analyze differences in the molecular composition of tissues. The aim of this study was to evaluate the suitability of RS for entity assignment in SGT. Methods Raman data were collected in deparaffinized sections of pleomorphic adenomas (PA) and adenoid cystic carcinomas (ACC). Multivariate data and chemometric analysis were completed using the Unscrambler software. Results The Raman spectra detected in ACC samples were mostly assigned to nucleic acids, lipids, and amides. In a principal component-based linear discriminant analysis (LDA) 18 of 20 tumor samples were classified correctly. Conclusion In this proof of concept study, we show that a reliable SGT diagnosis based on LDA algorithm appears possible, despite variations in the entity-specific mean spectra. However, a standardized workflow for tissue sample preparation, measurement setup, and chemometric algorithms is essential to get reliable results.},
  language  = {en}
}
@article{BasslerKnoblichGerhardHartmannetal.2023,
  author    = {Bassler, Miriam C. and Knoblich, Mona and Gerhard-Hartmann, Elena and Mukherjee, Ashutosh and Youssef, Almoatazbellah and Hagen, Rudolf and Haug, Lukas and Goncalves, Miguel and Scherzad, Agmal and St{\"o}th, Manuel and Ostertag, Edwin and Steinke, Maria and Brecht, Marc and Hackenberg, Stephan and Meyer, Till Jasper},
  title     = {Differentiation of salivary gland and salivary gland tumor tissue via Raman imaging combined with multivariate data analysis},
  series = {Diagnostics},
  volume    = {14},
  journal   = {Diagnostics},
  number    = {1},
  issn      = {2075-4418},
  doi       = {10.3390/diagnostics14010092},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-355558},
  year      = {2023},
  abstract  = {Salivary gland tumors (SGTs) are a relevant, highly diverse subgroup of head and neck tumors whose entity determination can be difficult. Confocal Raman imaging in combination with multivariate data analysis may possibly support their correct classification. For the analysis of the translational potential of Raman imaging in SGT determination, a multi-stage evaluation process is necessary. By measuring a sample set of Warthin tumor, pleomorphic adenoma and non-tumor salivary gland tissue, Raman data were obtained and a thorough Raman band analysis was performed. This evaluation revealed highly overlapping Raman patterns with only minor spectral differences. Consequently, a principal component analysis (PCA) was calculated and further combined with a discriminant analysis (DA) to enable the best possible distinction. The PCA-DA model was characterized by accuracy, sensitivity, selectivity and precision values above 90\% and validated by predicting model-unknown Raman spectra, of which 93\% were classified correctly. Thus, we state our PCA-DA to be suitable for parotid tumor and non-salivary salivary gland tissue discrimination and prediction. For evaluation of the translational potential, further validation steps are necessary.},
  language  = {en}
}