Dataset Information

Optical Characterization of Neurosurgical Operating Microscopes: Quantitative Fluorescence and Assessment of PpIX Photobleaching.

ABSTRACT: Protoporphyrin IX (PpIX) induced by 5-aminolevulinic acid (5-ALA) is increasingly used as a fluorescent marker for fluorescence-guided resection of malignant gliomas. Understanding how the properties of the excitation light source and PpIX fluorescence interact with the surgical microscope is critical for effective use of the fluorescence-guided tumor resection technique. In this study, we performed a detailed assessment of the intensity of the emitted blue light and white light and the light beam profile of clinical grade operating microscopes used for PpIX visualization. These measurements revealed both recognized fluorescence photobleaching limitations and unrecognized limitations that may alter quantitative observations of PpIX fluorescence obtained with the operating microscope with potential impact on research and clinical uses. We also evaluated the optical properties of a photostable fluorescent standard with an excitation-emission profile similar to PpIX. In addition, we measured the time-dependent dynamics of 5-ALA-induced PpIX fluorescence in an animal glioma model. Finally, we developed a ratiometric method for quantification of the PpIX fluorescence that uses the photostable fluorescent standard to normalize PpIX fluorescence intensity. This method increases accuracy and allows reproducible and direct comparability of the measurements from multiple samples.

SUBMITTER: Belykh E

PROVIDER: S-EPMC6105612 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Optical Characterization of Neurosurgical Operating Microscopes: Quantitative Fluorescence and Assessment of PpIX Photobleaching.

Belykh Evgenii E Miller Eric J EJ Patel Arpan A AA Bozkurt Baran B Yağmurlu Kaan K Robinson Timothy R TR Nakaji Peter P Spetzler Robert F RF Lawton Michael T MT Nelson Leonard Y LY Seibel Eric J EJ Preul Mark C MC

Scientific reports 20180822 1

Protoporphyrin IX (PpIX) induced by 5-aminolevulinic acid (5-ALA) is increasingly used as a fluorescent marker for fluorescence-guided resection of malignant gliomas. Understanding how the properties of the excitation light source and PpIX fluorescence interact with the surgical microscope is critical for effective use of the fluorescence-guided tumor resection technique. In this study, we performed a detailed assessment of the intensity of the emitted blue light and white light and the light be ...[more]

PMID: 30135440

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Project description:5-Aminolevulinic acid (5-ALA) induced fluorescence to augment surgical resection for high grade glioma has become a standard of care. Protoporphyrin IX (PpIX) visibility is however subject to the variability of the single tumor expression and to the interobserver interpretation. We therefore hypothesized that in different glioma cell lines with variable 5-ALA induced fluorescence, the signal can be pharmacologically increased. We therefore analyzed in three different GBM cell lines, with different expression of epidermal growth factor receptor (EGFR), the variability of 5-ALA induced PpIX fluorescence after the pharmacological blockade at different steps of PpIX breakdown and influencing the outbound transport of PpIX. Using flow cytometry, fluorescence microplate reader, and confocal microscopy the PpIX fluorescence was analyzed after exposure to tin protoporphyrin IX (SnPP), deferoxamine (DFO), and genistein. We furthermore constructed a microscope (Qp9-microscope) being able to measure quantitatively the concentration of PpIX. These values were compared with the extraction of PpIX in tumor biopsy taken during the GBM surgery. Although all three cell lines showed an increase to 5-ALA induced fluorescence their baseline activity was different. Treatment with either SnPP, DFO and genistein was able to increase 5-ALA induced fluorescence. Qp9-microscopy of tumor sample produced a color coded PpIX concentration map which was overlaid on the tumor image. The PpIX extraction from tumor sample analyzed using the plate reader gave lower values of the concentration, as compared to the expected values of the Qp9-microscope, however still in the same decimal range of ?g/mL. This may be due to homogenization of the values during extraction and cell disaggregation. In conclusion pharmacological augmentation in GBM cell lines of PpIX signal is possible. A quantitative PpIX map for surgery is feasible and may help refine surgical excision. Further correlations of tumor tissue samples and Qp9-microscopy is needed, prior to develop an intraoperative surgical adjunct to the already existing 5-ALA induced surgery.

Project description:BackgroundFluorescence loss in photobleaching (FLIP) is a widely used imaging technique, which provides information about protein dynamics in various cellular regions. In FLIP, a small cellular region is repeatedly illuminated by an intense laser pulse, while images are taken with reduced laser power with a time lag between the bleaches. Despite its popularity, tools are lacking for quantitative analysis of FLIP experiments. Typically, the user defines regions of interest (ROIs) for further analysis which is subjective and does not allow for comparing different cells and experimental settings.ResultsWe present two complementary methods to detect and quantify protein transport and aggregation in living cells from FLIP image series. In the first approach, a stretched exponential (StrExp) function is fitted to fluorescence loss (FL) inside and outside the bleached region. We show by reaction-diffusion simulations, that the StrExp function can describe both, binding/barrier-limited and diffusion-limited FL kinetics. By pixel-wise regression of that function to FL kinetics of enhanced green fluorescent protein (eGFP), we determined in a user-unbiased manner from which cellular regions eGFP can be replenished in the bleached area. Spatial variation in the parameters calculated from the StrExp function allow for detecting diffusion barriers for eGFP in the nucleus and cytoplasm of living cells. Polyglutamine (polyQ) disease proteins like mutant huntingtin (mtHtt) can form large aggregates called inclusion bodies (IB's). The second method combines single particle tracking with multi-compartment modelling of FL kinetics in moving IB's to determine exchange rates of eGFP-tagged mtHtt protein (eGFP-mtHtt) between aggregates and the cytoplasm. This method is self-calibrating since it relates the FL inside and outside the bleached regions. It makes it therefore possible to compare release kinetics of eGFP-mtHtt between different cells and experiments.ConclusionsWe present two complementary methods for quantitative analysis of FLIP experiments in living cells. They provide spatial maps of exchange dynamics and absolute binding parameters of fluorescent molecules to moving intracellular entities, respectively. Our methods should be of great value for quantitative studies of intracellular transport.

Project description:There have been few anatomical structure segmentation studies using deep learning. Numbers of training and ground truth images applied were small and the accuracies of which were low or inconsistent. For a surgical video anatomy analysis, various obstacles, including a variable fast-changing view, large deformations, occlusions, low illumination, and inadequate focus occur. In addition, it is difficult and costly to obtain a large and accurate dataset on operational video anatomical structures, including arteries. In this study, we investigated cerebral artery segmentation using an automatic ground-truth generation method. Indocyanine green (ICG) fluorescence intraoperative cerebral videoangiography was used to create a ground-truth dataset mainly for cerebral arteries and partly for cerebral blood vessels, including veins. Four different neural network models were trained using the dataset and compared. Before augmentation, 35,975 training images and 11,266 validation images were used. After augmentation, 260,499 training and 90,129 validation images were used. A Dice score of 79% for cerebral artery segmentation was achieved using the DeepLabv3+ model trained using an automatically generated dataset. Strict validation in different patient groups was conducted. Arteries were also discerned from the veins using the ICG videoangiography phase. We achieved fair accuracy, which demonstrated the appropriateness of the methodology. This study proved the feasibility of operating field view of the cerebral artery segmentation using deep learning, and the effectiveness of the automatic blood vessel ground truth generation method using ICG fluorescence videoangiography. Using this method, computer vision can discern blood vessels and arteries from veins in a neurosurgical microscope field of view. Thus, this technique is essential for neurosurgical field vessel anatomy-based navigation. In addition, surgical assistance, safety, and autonomous surgery neurorobotics that can detect or manipulate cerebral vessels would require computer vision to identify blood vessels and arteries.

Dataset Information

Optical Characterization of Neurosurgical Operating Microscopes: Quantitative Fluorescence and Assessment of PpIX Photobleaching.

Publications

Optical Characterization of Neurosurgical Operating Microscopes: Quantitative Fluorescence and Assessment of PpIX Photobleaching.

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