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Due to the wide variety of benign and malignant salivary gland tumors, classification and malignant behavior determination based on histomorphological criteria can be difficult and sometimes impossible. Spectroscopical procedures can acquire molecular biological information without destroying the tissue within the measurement processes. Since several tissue preparation procedures exist, our study investigated the impact of these preparations on the chemical composition of healthy and tumorous salivary gland tissue by Fourier-transform infrared (FTIR) microspectroscopy. Sequential tissue cross-sections were prepared from native, formalin-fixed and formalin-fixed paraffin-embedded (FFPE) tissue and analyzed. The FFPE cross-sections were dewaxed and remeasured. By using principal component analysis (PCA) combined with a discriminant analysis (DA), robust models for the distinction of sample preparations were built individually for each parotid tissue type. As a result, the PCA-DA model evaluation showed a high similarity between native and formalin-fixed tissues based on their chemical composition. Thus, formalin-fixed tissues are highly representative of the native samples and facilitate a transfer from scientific laboratory analysis into the clinical routine due to their robust nature. Furthermore, the dewaxing of the cross-sections entails the loss of molecular information. Our study successfully demonstrated how FTIR microspectroscopy can be used as a powerful tool within existing clinical workflows.
Glioblastoma WHO IV belongs to a group of brain tumors that are still incurable. A promising treatment approach applies photodynamic therapy (PDT) with hypericin as a photosensitizer. To generate a comprehensive understanding of the photosensitizer-tumor interactions, the first part of our study is focused on investigating the distribution and penetration behavior of hypericin in glioma cell spheroids by fluorescence microscopy. In the second part, fluorescence lifetime imaging microscopy (FLIM) was used to correlate fluorescence lifetime (FLT) changes of hypericin to environmental effects inside the spheroids. In this context, 3D tumor spheroids are an excellent model system since they consider 3D cell–cell interactions and the extracellular matrix is similar to tumors in vivo. Our analytical approach considers hypericin as probe molecule for FLIM and as photosensitizer for PDT at the same time, making it possible to directly draw conclusions of the state and location of the drug in a biological system. The knowledge of both state and location of hypericin makes a fundamental understanding of the impact of hypericin PDT in brain tumors possible. Following different incubation conditions, the hypericin distribution in peripheral and central cryosections of the spheroids were analyzed. Both fluorescence microscopy and FLIM revealed a hypericin gradient towards the spheroid core for short incubation periods or small concentrations. On the other hand, a homogeneous hypericin distribution is observed for long incubation times and high concentrations. Especially, the observed FLT change is crucial for the PDT efficiency, since the triplet yield, and hence the O2 activation, is directly proportional to the FLT. Based on the FLT increase inside spheroids, an incubation time 30 min is required to achieve most suitable conditions for an effective PDT.
Die prä-, intra- und postoperative Entitäts- und Dignitätsbestimmung von Speicheldrüsen-tumoren (ST) allein anhand von histomorphologischen Kriterien ist häufig mit großen Unsicherheiten verbunden.
Die Spektren der Raman-Spektroskopie (RS) und der Infrarot-Spektroskopie (IS) enthalten Informationen zu der molekularen Zusammensetzung des untersuchten Gewebes. Ziel der Arbeit war die Etablierung eines Gewebe-Aufarbeitungs-Workflows und die Analyse des Einflusses der Fixierung auf die spektrale Bioinformation. Zudem wird ein Überblick über den Einsatz der RS und IS im Kopf-Hals Bereich gegeben.
Es wurden 10 mm dicke, konsekutive kryo-, formalin- und paraffinfixierte ST-Gewebeschnitte von Zystadenolymphomen (n=5) und pleomorphen Adenomen (n=4) mit der RS und IS untersucht und die Daten multivariat ausgewertet. Die Messungen erfolgten in Korrelation zur Histomorphologie über einen korrespondierenden HE-Schnitt sowohl im Tumorgewebe als auch im gesunden Speicheldrüsengewebe.
In der Mittelwertspektrenanalyse zeigte sich eine deutliche Paraffin-Signatur, Formalin-Fixierung hatte keinen wesentlichen Einfluss. Dies konnte durch die Hauptkomponentenanalyse (PCA) bestätigt werden. Eine Diskriminierung von Tumor- und Nicht-Tumorgewebe durch die PCA und gekoppelte Diskriminanzanalyse war ebenfalls mit beiden spektroskopischen Methoden mit einer hohen Sensitivität möglich.
Für eine Translation von spektralen Verfahren ist das Wissen über Einflussfaktoren auf die spektrale Bioinformation der Gewebeaufarbeitung und -fixierung unabdingbar. Die Integration spektraler Verfahren additiv in bestehende Arbeitsabläufe ist möglich. Der Einfluss der Formalinfixierung auf die spektrale Bioinformation ist gering. Die bioinformatische Analyse der umfangreichen Datensätze ist herausfordernd.
IZKF Würzburg
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.
Malignant primary brain tumors are a group of highly aggressive and often infiltrating tumors that lack adequate therapeutic treatments to achieve long time survival. Complete tumor removal is one precondition to reach this goal. A promising approach to optimize resection margins and eliminate remaining infiltrative so-called guerilla cells is photodynamic therapy (PDT) using organic photosensitizers that can pass the disrupted blood–brain-barrier and selectively accumulate in tumor tissue. Hypericin fulfills these conditions and additionally offers outstanding photophysical properties, making it an excellent choice as a photosensitizing molecule for PDT. However, the actual hypericin-induced PDT cell death mechanism is still under debate. In this work, hypericin-induced PDT was investigated by employing the three distinct fluorescent probes hypericin, resorufin and propidium iodide (PI) in fluorescence-lifetime imaging microscopy (FLIM). This approach enables visualizing the PDT-induced photodamaging and dying of single, living glioma cells, as an in vitro tumor model for glioblastoma. Hypericin PDT and FLIM image acquisition were simultaneously induced by 405 nm laser irradiation and sequences of FLIM images and fluorescence spectra were recorded to analyze the PDT progression. The reproducibly observed cellular changes provide insight into the mechanism of cell death during PDT and suggest that apoptosis is the initial mechanism followed by necrosis after continued irradiation. These new insights into the mechanism of hypericin PDT of single glioma cells may help to adjust irradiation doses and improve the implementation as a therapy for primary brain tumors.
Die prä-, intra- und postoperative Entitäts- und Dignitätsbestimmung von Speicheldrüsen-tumoren (ST) allein anhand von histomorphologischen Kriterien ist nicht in allen Fällen zuverlässig möglich. Die Spektren der Raman-Spektroskopie (RS) enthalten Informationen zur molekularen Zusammensetzung des untersuchten Gewebes. Ziel der Arbeit war die Etablierung eines RS-basierten Mess-Setups und eines Workflows zur Differenzierung von Speicheldrüsentumorgewebe und Speicheldrüsengewebe. Zudem werden die Hürden der Translation von RS in der Speicheldrüsendiagnostik diskutiert. Es wurden 10 mm dicke, native Kryo-Gewebeschnitte von Warthin-Tumoren (n=5) und pleomorphen Adenomen (n=4) mit der RS sowohl im Tumorgewebe als auch im gesunden Speicheldrüsengewebe untersucht und die Daten multivariat ausgewertet. Alle Messungen wurden in einem korrespondierenden HE-Schnitt histomorphologisch lokalisiert. Durch eine "Principal component"-Analyse (PCA) der RS-Daten und gekoppelte Diskriminanzanalyse war sowohl eine Unterscheidung von Tumor- und Nicht-Tumorgewebe als auch die Differenzierung der verschiedenen Tumorentitäten (basierend auf der histopathologischen Begutachtung) mit einer hohen Genauigkeit (93%) möglich. Zusammenfassend konnte gezeigt werden, dass anhand der RS-Messungen sicher zwischen ST-gewebe und gesundem Speicheldrüsengewebe unterschieden werden konnte. Ein wichtiges Ergebnis ist ebenfalls, dass die Gewebeaufarbeitung mit pathologischen Standard-Methoden zuverlässig möglich ist. Die hohe Anzahl an verschiedenen ST-Entitäten stellt eine biostatistische Herausforderung dar. Lösungsansätze sind mehrstufige statistische Modelle und die gleichzeitige Korrelation mit histomorphologischen Kriterien.
The pre-, intra- and postoperative determination of the entity and dignity of salivary gland tumors (ST) based solely on histomorphological criteria is not reliably in all cases. The spectra of Raman spectroscopy (RS) contain information about the molecular composition of the examined tissue. The aim of the work was to establish an RS-based measurement setup and a workflow for the differentiation of salivary gland tumor tissue and salivary gland tissue. In addition, the barriers of translating RS in salivary gland diagnostics are discussed. 10 µm thick, native cryo-tissue sections of Warthin tumors (n=5) and pleomorphic adenomas (n=4) were examined using RS in both tumor tissue and healthy salivary gland tissue and the data were evaluated in a multivariate data analysis. All measurements were histomorphologically localized in a corresponding HE section. A "principal component" analysis (PCA) of the RS data and coupled discriminant analysis enabled both a distinction between tumor and non-tumor tissue as well as the differentiation of the various tumor entities (based on the histopathological assessment) with a high level of accuracy (93% ). In summary, it could be shown that the RS measurements could be used to reliably distinguish between ST and healthy salivary gland tissue. Another important result is that tissue processing is possible reliably using standard pathological methods. The high number of different ST entities represents a biostatistical challenge. Approaches to the solution include multi-level statistical models and simultaneous correlation with histomorphological criteria.
The early detection of head and neck cancer is a prolonged challenging task. It requires a precise and accurate identification of tissue alterations as well as a distinct discrimination of cancerous from healthy tissue areas. A novel approach for this purpose uses microspectroscopic techniques with special focus on hyperspectral imaging (HSI) methods. Our proof-of-principle study presents the implementation and application of darkfield elastic light scattering spectroscopy (DF ELSS) as a non-destructive, high-resolution, and fast imaging modality to distinguish lingual healthy from altered tissue regions in a mouse model. The main aspect of our study deals with the comparison of two varying HSI detection principles, which are a point-by-point and line scanning imaging, and whether one might be more appropriate in differentiating several tissue types. Statistical models are formed by deploying a principal component analysis (PCA) with the Bayesian discriminant analysis (DA) on the elastic light scattering (ELS) spectra. Overall accuracy, sensitivity, and precision values of 98% are achieved for both models whereas the overall specificity results in 99%. An additional classification of model-unknown ELS spectra is performed. The predictions are verified with histopathological evaluations of identical HE-stained tissue areas to prove the model’s capability of tissue distinction. In the context of our proof-of-principle study, we assess the Pushbroom PCA-DA model to be more suitable for tissue type differentiations and thus tissue classification. In addition to the HE-examination in head and neck cancer diagnosis, the usage of HSI-based statistical models might be conceivable in a daily clinical routine.
Characterization of brain tumours requires neuropathological expertise and is generally performed by histological evaluation and molecular analysis. One emerging technique to assist pathologists in future tumour diagnostics is multimodal optical spectroscopy. In the current clinical routine, tissue preprocessing with formalin is widely established and suitable for spectroscopic investigations since degradation processes impede the measurement of native tissue. However, formalin fixation results in alterations of the tissue chemistry and morphology for example by protein cross-linking. As optical spectroscopy is sensitive to these variations, we evaluate the effects of formalin fixation on multimodal brain tumour data in this proof-of-concept study. Nonfixed and formalin-fixed cross sections of different common human brain tumours were subjected to analysis of chemical variations using ultraviolet and Fourier-transform infrared microspectroscopy. Morphological changes were assessed by elastic light scattering microspectroscopy in the visible wavelength range. Data were analysed with multivariate data analysis and compared with histopathology. Tissue type classifications deduced by optical spectroscopy are highly comparable and independent from the preparation and the fixation protocol. However, formalin fixation leads to slightly better classification models due to improved stability of the tissue. As a consequence, spectroscopic methods represent an appropriate additional contrast for chemical and morphological information in neuropathological diagnosis and should be investigated to a greater extent. Furthermore, they can be included in the clinical workflow even after formalin fixation.
Commercially available homogenized cow- and plant-based milks were investigated by optical spectroscopy in the range of 400–1360 nm. Absorbance spectra, the effective scattering coefficient μs′, and the spectral absorption coefficient μa were recorded for 23 milk varieties and analyzed by multivariate data analysis. Cow- and plant-based milks were compared and discriminated using principal component analysis combined with a quadratic discriminant analysis. Furthermore, it was possible to discriminate the origin of plant-based milk by μa and the fat content in cow-based milk by μs′. Partial least squares regression models were developed to determine the fat content in cow-based milk. The model for μs′ proved to be the most efficient for this task with R2 = 0.98 and RMSEP = 0.19 g/100 mL for the external validation. Thus, optical spectroscopy together with multivariate data analysis is suitable for routine laboratory analysis or quality monitoring in the dairy production.
