Label-free tissue classification by FTIR- and QCL-based IR-imaging (Prof. K. Gerwert)
- Talk has been cancelled!
- Datum: 10.04.2018
- Uhrzeit: 14:30 - 15:30
- Vortragende(r): Prof. Dr. Klaus Gerwert
- Lehrstuhl für Biophysik, Ruhr-Universität Bochum
- Raum: New Lecture Hall, Room B 0.32
- Gastgeber: MPQ
1This approach is applied to fresh frozen but also to paraffin embedded
tissue samples usually used in pathology. For the entities colon, bladder, and
lung, classifiers are established to annotate cancerous tissue in an automated
workflow with sensitivity and specificity of over 95%.2 Recently, deep
learning methods are applied to improve the classifier performance. However,
the therapeutic decision of the clinician requires a differential diagnosis.
Therefore, in the next step a predictive differential diagnostics is
established. We were able to differentiate between the predictive subtypes in
lung 3, colon 4and recently bladder cancer. An important
milestone was than the combination with–omics technologies providing in
addition to spatial also molecular resolution. The label-free classified tissue
is cut out by laser microdissection and analyzed by proteomics. This is
successfully applied to the mesothelioma subtypes.5The currently
used biomarker panels in pathology are identified in a validation approach.
Recently, we identified in a discovery approach novel biomarker, which
differentiate between aggressive forms of bladder cancer, which are difficult
to distinguish by pathology today.
A break through is obtained now by a QCL-based microscope. The images show the same quality as the FTIR-images before. Especially disturbing coherence effects are largely reduced now. The most advantage is the reduction of measuring-time. This is now drastically reduced from about 20 hours down to few minutes. The QCL based approach opens now new avenues for clinical applications of tissue classification by IR-imaging.
References:
1 Gerwert K., Großerüschkamp F., Ollesch J. (2014), SPIE Newsroom, DOI:
10.1117/2.1201-312.005297.
2 Kallenbach-Thieltges A., Großerüschkamp F., Mosig A., Diem M.,
Tannapfel A., Gerwert K. (2013), J.
Biophotonics, 6(1), 88-100.
3 Großerüschkamp F., Kallenbach-Thieltges A., Behrens T., Brüning
T., Altmayer M., Stamatis G., Theegarten D., Gerwert, K. (2015), Analyst, 140(7), 2114-20.
4 Kuepper C., Großerueschkamp F., Kallenbach‐Thieltges A., Mosig A.,
Tannapfel A. and Gerwert K. (2016), Faraday
Discussion, DOI 10.1039/C5FD00157A.
5 Großerueschkamp, F., Bracht, T., Diehl, H. C., Kuepper, C.,
Ahrens, M., Kallenbach-Thieltges, A., Mosig, A., Eisenacher, M., Marcus, K.,
Behrens, Th., Brüning, Th., Theegarten, D., Sitek, B., Gerwert, K. (2017), Scientific Reports, 7, 44829, DOI:10.1038/srep44829.