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    Liquid-Core Microstructured Polymer Optical Fiber as Fiber-Enhanced Raman Spectroscopy Probe for Glucose Sensing
    (Washington, DC : OSA, 2020) Azkune, Mikel; Frosch, Timea; Arrospide, Eneko; Aldabaldetreku, Gotzon; Bikandi, Iñaki; Zubia, Joseba; Popp, Jürgen; Frosch, Torsten
    This work reports the development and application of two liquid-core microstructured polymer optical fibers (LC-mPOF) with different microstructure sizes. They are used in a fiber-enhanced Raman spectroscopy sensing platform, with the aim of detecting glucose in aqueous solutions in the clinically relevant range for sodium-glucose cotransporter 2 inhibitor therapy. The sensing platform is tested for low-concentration glucose solutions using each LC-mPOF. Results confirm that a significant enhancement of the Raman signal is achieved in comparison to conventional Raman spectroscopy. Additional measurements are carried out to obtain the valid measurement range, the resolution, and the limit of detection, showing that the LC-mPOF with 66-µm-diameter central hollow core has the highest potential for future clinical applications. Finally, preliminary tests successfully demonstrate glucose identification in urine. © 1983-2012 IEEE.
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    Systematic evaluation of particle loss during handling in the percutaneous transluminal angioplasty for eight different drug-coated balloons
    ([London] : Macmillan Publishers Limited, part of Springer Nature, 2020) Heinrich, Andreas; Engler, Martin S.; Güttler, Felix V.; Matthäus, Christian; Popp, Jürgen; Teichgräber, Ulf K.-M.
    Paclitaxel drug coated balloons (DCBs) should provide optimal drug transfer exclusively to the target tissue. The aim of this study was to evaluate the particle loss by handling during angioplasty. A robotic arm was developed for systematic and reproducible drug abrasion experiments. The contact force on eight different commercially available DCB types was gradually increased, and high-resolution microscopic images of the deflated and inflated balloons were recorded. Three types of DCBs were classified: no abrasion of the drug in both statuses (deflated and inflated), significant abrasion only in the inflated status, and significant abrasion in both statuses. Quantitative measurements via image processing confirmed the qualitative classification and showed changes of the drug area between 2.25 and 45.73% (13.28 ± 14.29%) in the deflated status, and between 1.66 and 40.41% (21.43 ± 16.48%) in the inflated status. The structures and compositions of the DCBs are different, some are significantly more susceptible to drug loss. Particle loss by handling during angioplasty leads to different paclitaxel doses in the target regions for same DCB types. Susceptibility to involuntary drug loss may cause side effects, such as varying effective paclitaxel doses, which may explain variations in studies regarding the therapeutic outcome.
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    Deep learning-based classification of blue light cystoscopy imaging during transurethral resection of bladder tumors
    ([London] : Macmillan Publishers Limited, part of Springer Nature, 2021) Ali, Nairveen; Bolenz, Christian; Todenhöfer, Tilman; Stenzel, Arnulf; Deetmar, Peer; Kriegmair, Martin; Knoll, Thomas; Porubsky, Stefan; Hartmann, Arndt; Popp, Jürgen; Kriegmair, Maximilian C.; Bocklitz, Thomas
    Bladder cancer is one of the top 10 frequently occurring cancers and leads to most cancer deaths worldwide. Recently, blue light (BL) cystoscopy-based photodynamic diagnosis was introduced as a unique technology to enhance the detection of bladder cancer, particularly for the detection of flat and small lesions. Here, we aim to demonstrate a BL image-based artificial intelligence (AI) diagnostic platform using 216 BL images, that were acquired in four different urological departments and pathologically identified with respect to cancer malignancy, invasiveness, and grading. Thereafter, four pre-trained convolution neural networks were utilized to predict image malignancy, invasiveness, and grading. The results indicated that the classification sensitivity and specificity of malignant lesions are 95.77% and 87.84%, while the mean sensitivity and mean specificity of tumor invasiveness are 88% and 96.56%, respectively. This small multicenter clinical study clearly shows the potential of AI based classification of BL images allowing for better treatment decisions and potentially higher detection rates.
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    Morpho-molecular signal correlation between optical coherence tomography and Raman spectroscopy for superior image interpretation and clinical diagnosis
    ([London] : Macmillan Publishers Limited, part of Springer Nature, 2021) Schie, Iwan W.; Placzek, Fabian; Knorr, Florian; Cordero, Eliana; Wurster, Lara M.; Hermann, Gregers G.; Mogensen, Karin; Hasselager, Thomas; Drexler, Wolfgang; Popp, Jürgen; Leitgeb, Rainer A.
    The combination of manifold optical imaging modalities resulting in multimodal optical systems allows to discover a larger number of biomarkers than using a single modality. The goal of multimodal imaging systems is to increase the diagnostic performance through the combination of complementary modalities, e.g. optical coherence tomography (OCT) and Raman spectroscopy (RS). The physical signal origins of OCT and RS are distinctly different, i.e. in OCT it is elastic back scattering of photons, due to a change in refractive index, while in RS it is the inelastic scattering between photons and molecules. Despite those diverse characteristics both modalities are also linked via scattering properties and molecular composition of tissue. Here, we investigate for the first time the relation of co-registered OCT and RS signals of human bladder tissue, to demonstrate that the signals of these complementary modalities are inherently intertwined, enabling a direct but more importantly improved interpretation and better understanding of the other modality. This work demonstrates that the benefit for using two complementary imaging approaches is, not only the increased diagnostic value, but the increased information and better understanding of the signal origins of both modalities. This evaluation confirms the advantages for using multimodal imaging systems and also paves the way for significant further improved understanding and clinically interpretation of both modalities in the future.