Publications by authors named "Ton G van Leeuwen"

190 Publications

Experimental validation of a recently developed model for single-fiber reflectance spectroscopy.

J Biomed Opt 2021 Feb;26(2)

University of Amsterdam, Amsterdam UMC, Cancer Center Amsterdam, Amsterdam Cardiovascular Sciences,, The Netherlands.

Significance: We recently developed a model for the reflectance measured with (multi-diameter) single-fiber reflectance (SFR) spectroscopy as a function of the reduced scattering coefficient μs', the absorption coefficient μa, and the phase function parameter psb. We validated this model with simulations.

Aim: We validate our model experimentally. To prevent overfitting, we investigate the wavelength-dependence of psb and propose a parametrization with only three parameters. We also investigate whether this parametrization enables measurements with a single fiber, as opposed to multiple fibers used in multi-diameter SFR (MDSFR).

Approach: We validate our model on 16 phantoms with two concentrations of Intralipid-20% (μs'=13 and 21  cm  -  1 at 500 nm) and eight concentrations of Evans Blue (μa  =  1 to 20  cm  -  1 at 605 nm). We parametrize psb as 10  -  5  ·    (  p1  (  λ  /  650  )    +  p2(λ/650)2  +  p3(λ/650)3  )  .

Results: Average errors were 7% for μs', 11% for μa, and 16% with the parametrization of psb; and 7%, 17%, and 16%, respectively, without. The parametrization of psb improved the fit speed 25 times (94 s to <4  s). Average errors for only one fiber were 50%, 33%, and 186%, respectively.

Conclusions: Our recently developed model provides accurate results for MDSFR measurements but not for a single fiber. The psb parametrization prevents overfitting and speeds up the fit.
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http://dx.doi.org/10.1117/1.JBO.26.2.025004DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7913601PMC
February 2021

The compatibility of immunolabeling with STR profiling.

Forensic Sci Int Genet 2021 Feb 15;52:102485. Epub 2021 Feb 15.

Amsterdam UMC, University of Amsterdam, Biomedical Engineering & Physics, Meibergdreef 9, Amsterdam, The Netherlands.. Electronic address:

Immunolabeling is a technique, which has recently been introduced to enhance the quality of developed fingermarks and subsequently strengthen the evidential value. The effect of this method on subsequent DNA analysis, however, has not been explored yet. Therefore, the current pilot study aimed to determine whether STR profiling is possible after immunolabeling. Since immunolabeling involves washing steps which could reduce DNA quantities, the use of different fixatives including methanol, formaldehyde and universal molecular fixative (UMFIX) were investigated. STR profiles from the (immunolabeled) fingermarks were generated after four days and four weeks by a direct PCR method to enable comparison of relatively fresh and old fingermarks. The fingermarks were deposited on diverse forensically relevant substrates, including glass, metal and tile. STR profiles could be recovered for all tested fixatives with no significant difference in performance. However, the mean number of detected alleles was the highest when methanol was used for fixation. Furthermore, immunolabeling on aged fingermarks (4 weeks) was also possible, but the number of detected alleles showed a non-significant decrease. DNA could be recovered from deposits on all substrates, of which glass showed the highest mean number of detected alleles followed by metal and tile.
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http://dx.doi.org/10.1016/j.fsigen.2021.102485DOI Listing
February 2021

Bayesian analysis of depth resolved OCT attenuation coefficients.

Sci Rep 2021 Jan 26;11(1):2263. Epub 2021 Jan 26.

Department of Biomedical Engineering and Physics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.

Optical coherence tomography (OCT) is an optical technique which allows for volumetric visualization of the internal structures of translucent materials. Additional information can be gained by measuring the rate of signal attenuation in depth. Techniques have been developed to estimate the rate of attenuation on a voxel by voxel basis. This depth resolved attenuation analysis gives insight into tissue structure and organization in a spatially resolved way. However, the presence of speckle in the OCT measurement causes the attenuation coefficient image to contain unrealistic fluctuations and makes the reliability of these images at the voxel level poor. While the distribution of speckle in OCT images has appeared in literature, the resulting voxelwise corruption of the attenuation analysis has not. In this work, the estimated depth resolved attenuation coefficient from OCT data with speckle is shown to be approximately exponentially distributed. After this, a prior distribution for the depth resolved attenuation coefficient is derived for a simple system using statistical mechanics. Finally, given a set of depth resolved estimates which were made from OCT data in the presence of speckle, a posterior probability distribution for the true voxelwise attenuation coefficient is derived and a Bayesian voxelwise estimator for the coefficient is given. These results are demonstrated in simulation and validated experimentally.
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http://dx.doi.org/10.1038/s41598-021-81713-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7838413PMC
January 2021

Toward improved endoscopic surveillance with multidiameter single fiber reflectance spectroscopy in patients with Barrett's esophagus.

J Biophotonics 2021 Jan 7:e202000351. Epub 2021 Jan 7.

Department of Gastroenterology and Hepatology, Catharina Hospital, Eindhoven, The Netherlands.

Patients with Barrett's esophagus are at an increased risk to develop esophageal cancer and, therefore, undergo regular endoscopic surveillance. Early detection of neoplasia enables endoscopic treatment, which improves outcomes. However, early Barrett's neoplasia is easily missed during endoscopic surveillance. This study investigates multidiameter single fiber reflectance spectroscopy (MDSFR) to improve Barrett's surveillance. Based on the concept of field cancerization, it may be possible to identify the presence of a neoplastic lesion from measurements elsewhere in the esophagus or even the oral cavity. In this study, MDSFR measurements are performed on non-dysplastic Barrett's mucosa, squamous mucosa, oral mucosa, and the neoplastic lesion (if present). Based on logistic regression analysis on the scattering parameters measured by MDSFR, a classifier is developed that can predict the presence of neoplasia elsewhere in the Barrett's segment from measurements on the non-dysplastic Barrett's mucosa (sensitivity 91%, specificity 71%, AUC = 0.77). Classifiers obtained from logistic regression analysis for the squamous and oral mucosa do not result in an AUC significantly different from 0.5.
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http://dx.doi.org/10.1002/jbio.202000351DOI Listing
January 2021

Deep Learning-based Recurrence Prediction in Patients with Non-muscle-invasive Bladder Cancer.

Eur Urol Focus 2020 Dec 22. Epub 2020 Dec 22.

Department of Biomedical Engineering and Physics, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands; Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands; Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.

Background: Non-muscle-invasive bladder cancer (NMIBC) is characterized by frequent recurrence of the disease, which is difficult to predict.

Objective: To combine digital histopathology slides with clinical data to predict 1- and 5-yr recurrence-free survival of NMIBC patients using deep learning.

Design, Setting, And Participants: Data of patients undergoing a transurethral resection of a bladder tumor between 2000 and 2018 at a Dutch academic medical center were selected. Corresponding histological slides were digitized. A three-step approach was used to predict 1- and 5-yr recurrence-free survival. First, a segmentation network was used to detect the urothelium on the digital histopathology slides. Second, a selection network was trained for the selection of patches associated with recurrence. Third, a classification network, combining the information of the selection network with clinical data, was trained to give the probability of 1- and 5-yr recurrence-free survival.

Outcome Measurements And Statistical Analysis: The accuracy of the deep learning-based model was compared with a multivariable logistic regression model using clinical data only.

Results And Limitations: In the 1- and 5-yr follow-up cohorts, 359 and 281 patients were included with recurrence rates of 27% and 63%, respectively. The areas under the curve (AUCs) of the model combining digital histopathology slide data with clinical data were 0.62 and 0.76 for 1- and 5-yr recurrence predictions, respectively, which were higher than those of the model using digital histopathology slide data only (AUCs of 0.56 and 0.72, respectively) and the multivariable logistic regression (AUCs of 0.58 and 0.57, respectively).

Conclusions: In our population, the deep learning-based model combining digital histopathology slides and clinical data enhances the prediction of recurrence (within 5 yr) compared with models using clinical data or image data only.

Patient Summary: By combining histopathology images and patient record data using deep learning, the prediction of recurrence in bladder cancer patients is enhanced.
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http://dx.doi.org/10.1016/j.euf.2020.12.008DOI Listing
December 2020

Subdiffuse scattering and absorption model for single fiber reflectance spectroscopy.

Biomed Opt Express 2020 Nov 22;11(11):6620-6633. Epub 2020 Oct 22.

Amsterdam UMC, University of Amsterdam, Department of Biomedical Engineering and Physics, Cancer Center Amsterdam, Amsterdam Cardiovascular Sciences, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands.

Single fiber reflectance (SFR) spectroscopy is a technique that is sensitive to small-scale changes in tissue. An additional benefit is that SFR measurements can be performed through endoscopes or biopsy needles. In SFR spectroscopy, a single fiber emits and collects light. Tissue optical properties can be extracted from SFR spectra and related to the disease state of tissue. However, the model currently used to extract optical properties was derived for tissues with modified Henyey-Greenstein phase functions only and is inadequate for other tissue phase functions. Here, we will present a model for SFR spectroscopy that provides accurate results for a large range of tissue phase functions, reduced scattering coefficients, and absorption coefficients. Our model predicts the reflectance with a median error of 5.6% compared to 19.3% for the currently used model. For two simulated tissue spectra, our model fit provides accurate results.
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http://dx.doi.org/10.1364/BOE.402466DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7687961PMC
November 2020

Quantification of Light Scattering Detection Efficiency and Background in Flow Cytometry.

Cytometry A 2020 Oct 21. Epub 2020 Oct 21.

Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.

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http://dx.doi.org/10.1002/cyto.a.24243DOI Listing
October 2020

Quantitative change of perfusion in gastric tube reconstruction by sidestream dark field microscopy (SDF) after esophagectomy, a prospective in-vivo cohort study.

Eur J Surg Oncol 2020 Sep 13. Epub 2020 Sep 13.

Amsterdam UMC, University of Amsterdam, Department of Surgery, Cancer Center Amsterdam, Amsterdam, The Netherlands.

Background: Anastomotic leakage is one of the most severe complications in patients undergoing esophagectomy with gastric tube reconstruction. Transection of the left gastric and gastro-epiploic artery and vein results in compromised perfusion which is seen as the major contributing factor for anastomotic dehiscence. The main objective of this prospective, observational, in-vivo pilot study is to microscopically evaluate gastric tube perfusion with Sidestream Darkfield Microscopy (SDF).

Methods: Intra-operative microscopic images of gastric-microcirculation were obtained with SDF directly after reconstruction in 22 patients. Quantitative perfusion related parameters were: velocity, Microvascular Flow Index(MFI), Total Vessel Density(TVD), Perfusion Vessel Density(PVD), Proportion of Perfused Vessels(PPV) and De Backer Score(DBS). Dedicated software was used to assess parameters predictive for compromised perfusion.

Results: SDF was feasible to accurately visualize and evaluate microcirculation in all patients. Velocity(μm/sec) was significantly decreased towards the fundus (p = 0.001). MFI, PVD and PVD were decreased distal of the watershed - between the right and left gastro-epiploic artery and vein - and in the fundus, compared to the base of the gastric tube(p = 0.0002). No differences in TVD and DBS were observed; because of vessel-dilation in the fundus-area. This suggests that venous congestion results in comprised inflow of oxygen rich blood and plays a role in the development of ischaemia.

Conclusion: We present quantitative perfusion imaging with SDF of the gastric tube. Velocity, MFI, TVD and PPV are accurate parameters to observe perfusion decrease. Also, venous congestion is visible in the fundus, suggesting an important role in the development of ischaemia. These parameters could allow early risk stratification, and, potentially, can accomplish a reduction in anastomotic leakage.
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http://dx.doi.org/10.1016/j.ejso.2020.09.006DOI Listing
September 2020

Limitations of Dutch Growth Research Foundation Commercial Software Weight Velocity for Age Standard Deviation Score.

Am J Case Rep 2020 Oct 14;21:e925551. Epub 2020 Oct 14.

Department of Pediatrics, Beatrix Children's Hospital, University Medical Center, Groningen, Netherlands.

BACKGROUND The commercial software for hospitals, Weight Velocity for Age Standard Deviation Score (SDSWVA), claims to document the growth and development of children, although published details are unavailable. The statistics-derived parameter SDSWVA includes the weight velocity at age t, WV(t) (weight gained between t and (t-1.23) years, divided by 1.23), and 3 standard weight velocity curves at average age AA, defined as AA=t-1.23/2 years. SDSWVA denotes the number of standard deviations that WV(t) deviates from the 0 SD weight velocity at AA. WV(t) yielded erroneous outcomes when applied to weights of a seriously underweight boy with an allergy to cows' milk who showed strong weight growth after being fed on food free of cows' milk. The SDSWVA software tacitly suggests that it is more accurate than WV(t). CASE REPORT The case of this boy was previously described in this Journal. Using SDSWVA(t,AA) software, his weight growth was analyzed by his third pediatrician, beginning at age 1.5 years. The diagnosis of the mother with Pediatric Condition Falsification was confirmed, adding 6 months to foster care, which totalled 8.5 months. Testing of the SDSWVA software on the boy's weight curve yielded results that were complex, nontransparent, and as erroneous as WV(t), explaining the misdiagnosis by the third pediatrician. CONCLUSIONS SDSWVA software should not be used for children under 3 years and during variable weight behavior. Erroneous performance, unpublished details, and an error identified in their new but untested software make the Dutch Growth Research Foundation unlikely to meet the 2020 European Union regulations for in vitro medical devices.
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http://dx.doi.org/10.12659/AJCR.925551DOI Listing
October 2020

Detection of extracellular vesicles in plasma and urine of prostate cancer patients by flow cytometry and surface plasmon resonance imaging.

PLoS One 2020 4;15(6):e0233443. Epub 2020 Jun 4.

Laboratory of Experimental Clinical Chemistry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.

Large (> 1 μm) tumor-derived extracellular vesicles (tdEVs) enriched from the cell fraction of centrifuged whole blood are prognostic in metastatic castration-resistant prostate cancer (mCRPC) patients. However, the highest concentration of tdEVs is expected in the cell-free plasma fraction. In this pilot study, we determine whether mCRPC patients can be discriminated from healthy controls based on detection of tdEVs (< 1μm, EpCAM+) and/or other EVs, in cell-free plasma and/or urine. The presence of marker+ EVs in plasma and urine samples from mCRPC patients (n = 5) and healthy controls (n = 5) was determined by flow cytometry (FCM) and surface plasmon resonance imaging (SPRi) using an antibody panel and lactadherin. For FCM, the concentrations of marker positive (+) particles and EVs (refractive index <1.42) were determined. Only the lactadherin+ particle and EV concentration in plasma measured by FCM differed significantly between patients and controls (p = 0.017). All other markers did not result in signals exceeding the background on both FCM and SPRi, or did not differ significantly between patients and controls. In conclusion, no difference was found between patients and controls based on the detection of tdEVs. For FCM, the measured sample volumes are too small to detect tdEVs. For SPRi, the concentration of tdEVs is probably too low to be detected. Thus, to detect tdEVs in cell-free plasma and/or urine, EV enrichment and/or concentration is required. Furthermore, we recommend testing other markers and/or a combination of markers to discriminate mCRPC patients from healthy controls.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0233443PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7272016PMC
August 2020

Automated Detection and Grading of Non-Muscle-Invasive Urothelial Cell Carcinoma of the Bladder.

Am J Pathol 2020 07 10;190(7):1483-1490. Epub 2020 Apr 10.

Department of Pathology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.

Accurate grading of non-muscle-invasive urothelial cell carcinoma is of major importance; however, high interobserver variability exists. A fully automated detection and grading network based on deep learning is proposed to enhance reproducibility. A total of 328 transurethral resection specimens from 232 patients were included, and a consensus reading by three specialized pathologists was used. The slides were digitized, and the urothelium was annotated by expert observers. The U-Net-based segmentation network was trained to automatically detect urothelium. This detection was used as input for the classification network. The classification network aimed to grade the tumors according to the World Health Organization grading system adopted in 2004. The automated grading was compared with the consensus and individual grading. The segmentation network resulted in an accurate detection of urothelium. The automated grading shows moderate agreement (κ = 0.48 ± 0.14 SEM) with the consensus reading. The agreement among pathologists ranges between fair (κ = 0.35 ± 0.13 SEM and κ = 0.38 ± 0.11 SEM) and moderate (κ = 0.52 ± 0.13 SEM). The automated classification correctly graded 76% of the low-grade cancers and 71% of the high-grade cancers according to the consensus reading. These results indicate that deep learning can be used for the fully automated detection and grading of urothelial cell carcinoma.
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http://dx.doi.org/10.1016/j.ajpath.2020.03.013DOI Listing
July 2020

Analytical model for diffuse reflectance in single fiber reflectance spectroscopy.

Opt Lett 2020 Apr;45(7):2078-2081

Cancer progression leads to changing scattering properties of affected tissues. Single fiber reflectance (SFR) spectroscopy detects these changes at small spatial scales, making it a promising tool for early in situ detection. Despite its simplicity and versatility, SFR signal modeling is hugely complicated so that, presently, only approximate models exist. We use a classic approach from geometrical probability to derive accurate analytical expressions for diffuse reflectance in SFR that shows a strong improvement over existing models. We consider the case of limited collection efficiency and the presence of absorption. A Monte Carlo light transport study demonstrates that we adequately describe the contribution of diffuse reflectance to the SFR signal. Additional steps are required to include semi-ballistic, non-diffuse reflectance also present in the SFR measurement.
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http://dx.doi.org/10.1364/OL.385845DOI Listing
April 2020

Label-free identification and chemical characterisation of single extracellular vesicles and lipoproteins by synchronous Rayleigh and Raman scattering.

J Extracell Vesicles 2020 19;9(1):1730134. Epub 2020 Feb 19.

Department of Medical Cell BioPhysics, TechMed Centre, University of Twente, Enschede, The Netherlands.

Extracellular vesicles (EVs) present in blood originate from cells of different origins such as red blood cells (RBCs), platelets and leukocytes. In patients with cancer, a small portion of EVs originate from tumour cells and their load is associated with poor clinical outcome. Identification of these tumour-derived extracellular vesicles (tdEVs) is difficult as they are outnumbered by EVs of different tissue of origin as well a large number of lipoproteins (LPs) that are in the same size range. In order to detect tdEVs from the abundant presence of other particles, single-particle techniques are necessary. Here, synchronous Rayleigh and Raman scattering is used for that purpose. This combination of light scattering techniques identifies optically trapped single particles based on Rayleigh scattering and distinguishes differences in chemical composition of particle populations based on Raman scattering. Here, we show that tdEVs can be distinguished from RBC EVs and LPs in a label-free manner and directly in suspension.
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http://dx.doi.org/10.1080/20013078.2020.1730134DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7048173PMC
February 2020

En-face optical coherence tomography for the detection of cancer in prostatectomy specimens: Quantitative analysis in 20 patients.

J Biophotonics 2020 06 30;13(6):e201960105. Epub 2020 Mar 30.

Department of Biomedical Engineering and Physics, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.

The increase histopathological evaluation of prostatectomy specimens rises the workload on pathologists. Automated histopathology systems, preferably directly on unstained specimens, would accelerate the pathology workflow. In this study, we investigate the potential of quantitative analysis of optical coherence tomography (OCT) to separate benign from malignant prostate tissue automatically. Twenty fixated prostates were cut, from which 54 slices were scanned by OCT. Quantitative OCT metrics (attenuation coefficient, residue, goodness-of-fit) were compared for different tissue types, annotated on the histology slides. To avoid misclassification, the poor-quality slides, and edges of annotations were excluded. Accurate registration of OCT data with histology was achieved in 31 slices. After removing outliers, 56% of the OCT data was compared with histopathology. The quantitative data could not separate malignant from benign tissue. Logistic regression resulted in malignant detection with a sensitivity of 0.80 and a specificity of 0.34. Quantitative OCT analysis should be improved before clinical use.
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http://dx.doi.org/10.1002/jbio.201960105DOI Listing
June 2020

A Systematic Approach to Improve Scatter Sensitivity of a Flow Cytometer for Detection of Extracellular Vesicles.

Cytometry A 2020 06 4;97(6):582-591. Epub 2020 Feb 4.

Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.

Extracellular vesicles (EVs) are commonly studied by flow cytometry. Due to their small size and low refractive index, the scatter intensity of most EVs is below the detection limit of common flow cytometers. Here, we aim to improve forward scatter (FSC) and side scatter (SSC) sensitivity of a common flow cytometer to detect single 100 nm EVs. The effects of the optical and fluidics configuration on scatter sensitivity of a FACSCanto (Becton Dickinson) were evaluated by the separation index (SI) and robust coefficient of variation (rCV) of polystyrene beads (BioCytex). Improvement is defined as increased SI and/or reduced rCV. Changing the obscuration bar improved the rCV 1.9-fold for FSC. A 10-fold increase in laser power improved the SI 19-fold for FSC and 4.4-fold for SSC, whereas the rCV worsened 0.8-fold and improved 1.5-fold, respectively. Confocalization worsened the SI 1.2-fold for FSC, and improved the SI 5.1-fold for SSC, while the rCV improved 1.1-fold and worsened 1.5-fold, respectively. Replacing the FSC photodiode with a photomultiplier tube improved the SI 66-fold and rCV 4.2-fold. A 2-fold reduction in sample stream width improved both SI and rCV for FSC by 1.8-fold, and for SSC by 1.3- and 2.2-fold, respectively. Decreasing the sample flow velocity worsened rCVs. Decreasing the flow channel dimensions and the pore size of the sheath filter did not substantially change the SI or rCV. Using the optimal optical configuration and fluidics settings, the SI improved 3.8∙10 -fold on FSC and 30-fold on SSC, resulting in estimated detection limits for EVs (assuming a refractive index of 1.40) of 246 and 91 nm on FSC and SSC, respectively. Although a 50-fold improvement on FSC is still necessary, these adaptions have produced an operator-friendly, high-throughput flow cytometer with a high sensitivity on both SSC and FSC. © 2020 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.
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http://dx.doi.org/10.1002/cyto.a.23974DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7383638PMC
June 2020

Subdiffuse scattering model for single fiber reflectance spectroscopy.

J Biomed Opt 2020 01;25(1):1-11

Amsterdam UMC, University of Amsterdam, Cancer Center Amsterdam, Amsterdam Cardiovascular Sciences,, The Netherlands.

To detect small-scale changes in tissue with optical techniques, small sampling volumes are required. Single fiber reflectance (SFR) spectroscopy has a sampling depth of a few hundred micrometers. SFR spectroscopy uses a single fiber to emit and collect light. The only available model to determine optical properties with SFR spectroscopy was derived for tissues with modified Henyey-Greenstein phase functions. Previously, we demonstrated that this model is inadequate for other tissue phase functions. We develop a model to relate SFR measurements to scattering properties for a range of phase functions, in the absence of absorption. Since the source and detector overlap, the reflectance cannot be accurately described by diffusion theory alone: SFR measurements are subdiffuse. Therefore, we describe the reflectance as a combination of a diffuse and a semiballistic component. We use the model of Farrell et al. for the diffuse component, solved for an overlapping source and detector fiber. For the semiballistic component, we derive a new parameter, , which incorporates the integrals of the phase function over 1 deg in the backward direction and 23 deg in the forward direction. Our model predicts the reflectance with a median error of 2.1%, compared to 9.0% for the currently available model.
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http://dx.doi.org/10.1117/1.JBO.25.1.015001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7008500PMC
January 2020

Multidiameter single-fiber reflectance spectroscopy of heavily pigmented skin: modeling the inhomogeneous distribution of melanin.

J Biomed Opt 2019 12;24(12):1-11

Amsterdam UMC, University of Amsterdam, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands.

When analyzing multidiameter single-fiber reflectance (MDSFR) spectra, the inhomogeneous distribution of melanin pigments in skin tissue is usually not accounted for. Especially in heavily pigmented skins, this can result in bad fits and biased estimation of tissue optical properties. A model is introduced to account for the inhomogeneous distribution of melanin pigments in skin tissue. visible MDSFR measurements were performed on heavily pigmented skin of type IV to VI. Skin tissue optical properties and related physiological properties were extracted from the measured spectra using the introduced model. The absorption of melanin pigments described by the introduced model demonstrates a good correlation with the co-localized measurement of the well-known melanin index.
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http://dx.doi.org/10.1117/1.JBO.24.12.127001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7006040PMC
December 2019

Synchronized Rayleigh and Raman scattering for the characterization of single optically trapped extracellular vesicles.

Nanomedicine 2020 02 24;24:102109. Epub 2019 Oct 24.

Department of Medical Cell BioPhysics, TechMed Centre, University of Twente, Enschede, The Netherlands. Electronic address:

Extracellular Vesicles (EVs) can be used as biomarkers in diseases like cancer, as their lineage of origin and molecular composition depend on the presence of cancer cells. Recognition of tumor-derived EVs (tdEVs) from other particles and EVs in body fluids requires characterization of single EVs to exploit their biomarker potential. We present here a new method based on synchronized Rayleigh and Raman light scattering from a single laser beam, which optically traps single EVs. Rapidly measured sequences of the Rayleigh scattering amplitude show precisely when an individual EV is trapped and the synchronously acquired Raman spectrum labels every time interval with chemical information. Raman spectra of many single EVs can thus be acquired with great fidelity in an automated manner by blocking the laser beam at regular time intervals. This new method enables single EV characterization from fluids at the single particle level.
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http://dx.doi.org/10.1016/j.nano.2019.102109DOI Listing
February 2020

Toward Automated Bladder Tumor Stratification Using Confocal Laser Endomicroscopy.

J Endourol 2019 11 29;33(11):930-937. Epub 2019 Oct 29.

Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.

Urothelial carcinoma of the bladder (UCB) is the most common urinary cancer. White-light cystoscopy (WLC) forms the corner stone for the diagnosis of UCB. However, histopathological assessment is required for adjuvant treatment selection. Probe-based confocal laser endomicroscopy (pCLE) enables visualization of the microarchitecture of bladder lesions during WLC, which allows for real-time tissue differentiation and grading of UCB. To improve the diagnostic process of UCB, computer-aided classification of pCLE videos of bladder lesions were evaluated in this study. We implemented preprocessing methods to optimize contrast and to reduce striping artifacts in each individual pCLE frame. Subsequently, a semiautomatic frame selection was performed. The selected frames were used to train a feature extractor based on pretrained ImageNet networks. A recurrent neural network, in specific long short-term memory (LSTM), was used to predict the grade of bladder lesions. Differentiation of lesions was performed at two levels, namely (i) healthy and benign malignant tissue and (ii) low-grade high-grade papillary UCB. A total of 53 patients with 72 lesions were included in this study, resulting in ∼140,000 pCLE frames. The semiautomated frame selection reduced the number of frames to ∼66,500 informative frames. The accuracy for differentiation of (i) healthy and benign malignant urothelium was 79% and (ii) high-grade and low-grade papillary UCB was 82%. A feature extractor in combination with LSTM results in proper stratification of pCLE videos of bladder lesions.
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http://dx.doi.org/10.1089/end.2019.0354DOI Listing
November 2019

Weight velocity equations with 14-448 days time separated weights should not be used for infants under 3 years of age.

Med Hypotheses 2019 Aug 20;129:109234. Epub 2019 May 20.

Department of Biomedical Engineering & Physics, Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, The Netherlands.

Abnormal growth of infants may indicate disease of the children, thus methods to identify growth disorders are wanted in medicine. We previously showed that two-time-points weight growth velocities at age t, calculated by a commercial software product as [Weight(t) - Weight(t - X)]/X, with X = 448 days, were erroneous due to the long separation of 448 days. We were convinced that shorter X-values would solve this accuracy problem. However, our hypothesis is that: "shorter time separations than 448 days cause a decreased accuracy of numerical weight velocity equations in realistic infant weights until an age of about three years". Supporting evidence comes from analyzing how shorter X-values will affect the accuracy of two-time-points weight velocity calculations. We systematically varied X between 1 and 448 days of various P50/0SD-related standard weight curves: (a) P50/0SD with the weights separated by 1 day and X = 1,28,224,448 days; (b) P50/0SD with the weights at variable ages and X = 14-448 days; and (c) case (b) and incorporating weight fluctuations typically occurring in infants. Cases (b) and (c) include details observed in a clinical case. Our results show that the combination of weight fluctuations and varying time intervals between consecutive weights make weight velocity predictions worse for shorter X values in children younger than three years. Because these two causes of failure occur naturally in infants whose weight is regularly measured, other weight velocity equations face the same causes for inaccuracy. In conclusion, our hypothesis suggests that any software that predicts weight velocities should be abandoned in infants < 3 years. Practically, it should require that when (commercial) software weight velocity prediction suggests a medical problem, careful clinical checking should be mandatory, e.g. by linking predicted and exact weight velocities at age t (the latter from the mathematical first derivative at age t of standard weight curves).
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http://dx.doi.org/10.1016/j.mehy.2019.109234DOI Listing
August 2019

Computed Tomography-Mediated Registration of Trapeziometacarpal Articular Cartilage Using Intraarticular Optical Coherence Tomography and Cryomicrotome Imaging: A Cadaver Study.

Cartilage 2019 Jul 11:1947603519860247. Epub 2019 Jul 11.

2 Biomedical Engineering and Physics, Amsterdam University Medical Centers, Location AMC, University of Amsterdam, Amsterdam, Netherlands.

Objective: Accurate, high-resolution imaging of articular cartilage thickness is an important clinical challenge in patients with osteoarthritis, especially in small joints. In this study, computed tomography (CT) mediated catheter-based optical coherence tomography (OCT) was utilized to create a digital reconstruction of the articular surface of the trapeziometacarpal (TMC) joint and to assess cartilage thickness in comparison to cryomicrotome data.

Design: Using needle-based introduction of the OCT probe, the articular surface of the TMC joint of 5 cadaver wrists was scanned in different probe positions with matching CT scans to record the intraarticular probe trajectory. Subsequently and based on the acquired CT data, 3-dimensional realignment of the OCT data to the curved intraarticular trajectory was performed for all probe positions. The scanned TMC joints were processed using a cryomicrotome imaging system. Finally, cartilage thickness measurements between OCT and cryomicrotome data were compared.

Results: Successful visualization of TMC articular cartilage was performed using OCT. The CT-mediated registration yielded a digital reconstruction of the articular surface on which thickness measurements could be performed. A near-perfect agreement between OCT and cryomicrotome thickness measurements was found ( = 0.989).

Conclusion: The proposed approach enables 3D reconstruction of the TMC articular surface with subsequent accurate cartilage thickness measurements, encouraging the development of intraarticular cartilage OCT for future (clinical) application.
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http://dx.doi.org/10.1177/1947603519860247DOI Listing
July 2019

Pilot feasibility study of in vivo intraoperative quantitative optical coherence tomography of human brain tissue during glioma resection.

J Biophotonics 2019 10 15;12(10):e201900037. Epub 2019 Jul 15.

Department of Biomedical Engineering & Physics, Amsterdam UMC, University of Amsterdam, Amsterdam Cardiovascular Sciences, Cancer Center Amsterdam, Amsterdam, The Netherlands.

This study investigates the feasibility of in vivo quantitative optical coherence tomography (OCT) of human brain tissue during glioma resection surgery in six patients. High-resolution detection of glioma tissue may allow precise and thorough tumor resection while preserving functional brain areas, and improving overall survival. In this study, in vivo 3D OCT datasets were collected during standard surgical procedure, before and after partial resection of the tumor, both from glioma tissue and normal parenchyma. Subsequently, the attenuation coefficient was extracted from the OCT datasets using an automated and validated algorithm. The cortical measurements yield a mean attenuation coefficient of 3.8 ± 1.2 mm for normal brain tissue and 3.6 ± 1.1 mm for glioma tissue. The subcortical measurements yield a mean attenuation coefficient of 5.7 ± 2.1 and 4.5 ± 1.6 mm for, respectively, normal brain tissue and glioma. Although the results are inconclusive with respect to trends in attenuation coefficient between normal and glioma tissue due to the small sample size, the results are in the range of previously reported values. Therefore, we conclude that the proposed method for quantitative in vivo OCT of human brain tissue is feasible during glioma resection surgery.
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http://dx.doi.org/10.1002/jbio.201900037DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7065626PMC
October 2019

Estimation of microvascular perfusion after esophagectomy: a quantitative model of dynamic fluorescence imaging.

Med Biol Eng Comput 2019 Sep 26;57(9):1889-1900. Epub 2019 Jun 26.

Department of Biomedical Engineering & Physics, Amsterdam University Medical Centers, Amsterdam, The Netherlands.

Most common complications of esophagectomy stem from a perfusion deficiency of the gastric conduit at the anastomosis. Fluorescent tracer imaging allows intraoperative visualization of tissue perfusion. Quantitative assessment of fluorescence dynamics has the potential to identify perfusion deficiency. We developed a perfusion model to analyze the relation between fluorescence dynamics and perfusion deficiency. The model divides the gastric conduit into two well-perfused and two anastomosed sites. Hemodynamics and tracer transport were modeled. We analyzed the value of relative time-to-threshold (RTT) as a predictor of the relative remaining flow (RRF). Intensity thresholds for RTT of 20% to 50% of the maximum fluorescence intensity of the well-perfused site were tested. The relation between RTT and RRF at the anastomosed sites was evaluated over large variations of vascular conductance and volume. The ability of RTT to distinguish between sufficient and impaired perfusion was analyzed using c-statistics. We found that RTT was a valuable estimate for low RRF. The threshold of 20% of the maximum fluorescence intensity provided the best prediction of impaired perfusion on the two anastomosed sites (AUC = 0.89 and 0.86). The presented model showed that for low flows, relative time-to-threshold may be used to estimate perfusion deficiency.
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http://dx.doi.org/10.1007/s11517-019-01994-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6706368PMC
September 2019

Deep learning for automatic Gleason pattern classification for grade group determination of prostate biopsies.

Virchows Arch 2019 Jul 16;475(1):77-83. Epub 2019 May 16.

Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.

Histopathologic grading of prostate cancer using Gleason patterns (GPs) is subject to a large inter-observer variability, which may result in suboptimal treatment of patients. With the introduction of digitization and whole-slide images of prostate biopsies, computer-aided grading becomes feasible. Computer-aided grading has the potential to improve histopathological grading and treatment selection for prostate cancer. Automated detection of GPs and determination of the grade groups (GG) using a convolutional neural network. In total, 96 prostate biopsies from 38 patients are annotated on pixel-level. Automated detection of GP 3 and GP ≥ 4 in digitized prostate biopsies is performed by re-training the Inception-v3 convolutional neural network (CNN). The outcome of the CNN is subsequently converted into probability maps of GP ≥ 3 and GP ≥ 4, and the GG of the whole biopsy is obtained according to these probability maps. Differentiation between non-atypical and malignant (GP ≥ 3) areas resulted in an accuracy of 92% with a sensitivity and specificity of 90 and 93%, respectively. The differentiation between GP ≥ 4 and GP ≤ 3 was accurate for 90%, with a sensitivity and specificity of 77 and 94%, respectively. Concordance of our automated GG determination method with a genitourinary pathologist was obtained in 65% (κ = 0.70), indicating substantial agreement. A CNN allows for accurate differentiation between non-atypical and malignant areas as defined by GPs, leading to a substantial agreement with the pathologist in defining the GG.
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http://dx.doi.org/10.1007/s00428-019-02577-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6611751PMC
July 2019

The First In Vivo Needle-Based Optical Coherence Tomography in Human Prostate: A Safety and Feasibility Study.

Lasers Surg Med 2019 May 14. Epub 2019 May 14.

Department of Urology, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands.

Objective: To demonstrate the safety and feasibility of clinical in vivo needle-based optical coherence tomography (OCT) imaging of the prostate.

Materials And Methods: Two patients with prostate cancer underwent each two percutaneous in vivo needle-based OCT measurements before transperineal template mapping biopsy. The OCT probe was introduced via a needle and positioned under ultrasound guidance. To test the safety, adverse events were recorded during and after the procedure. To test the feasibility, OCT and US images were studied during and after the procedure. Corresponding regions for OCT and biopsy were determined. A uropathologist evaluated and annotated the histopathology. Three experts assessed all the corresponding OCT images. The OCT and biopsy conclusions for the corresponding regions were compared.

Results: No adverse events during and following the, in total four, in vivo needle-based OCT measurements were reported. The OCT measurements showed images of prostatic tissue with a penetration depth of ~1.5 mm. The histological-proven tissue types, which were also found in the overlapping OCT images, were benign glands, stroma, glandular atrophy, and adenocarcinoma (Gleason pattern 3).

Conclusions: Clinical in vivo needle-based OCT of the prostate is feasible with no adverse events during measurements. OCT images displayed detailed prostatic tissue with a imaging depth up to ~1.5 mm. We could co-register four histological-proven tissue types with OCT images. The feasibility of in vivo OCT in the prostate opens the pathway to the next phase of needle-based OCT studies in the prostate. © 2019 The Authors. Lasers in Surgery and Medicine Published by Wiley Periodicals, Inc.
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http://dx.doi.org/10.1002/lsm.23093DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6617991PMC
May 2019

Simple and robust calibration procedure for k-linearization and dispersion compensation in optical coherence tomography.

J Biomed Opt 2019 05;24(5):1-11

University of Amsterdam, Amsterdam University Medical Center, Department of Biomedical Engineering a, The Netherlands.

In Fourier-domain optical coherence tomography (FD-OCT), proper signal sampling and dispersion compensation are essential steps to achieve optimal axial resolution. These calibration steps can be performed through numerical signal processing, but require calibration information about the system that may require lengthy and complex measurement protocols. We report a highly robust calibration procedure that can simultaneously determine correction vectors for nonlinear wavenumber sampling and dispersion compensation. The proposed method requires only two simple mirror measurements and no prior knowledge about the system's illumination source or detection scheme. This method applies to both spectral domain and swept-source OCT systems. Furthermore, it may be implemented as a low-cost fail-safe to validate the proper function of calibration hardware such as k-clocks. We demonstrate the method's simple implementation, effectiveness, and robustness on both types of OCT systems.
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http://dx.doi.org/10.1117/1.JBO.24.5.056001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6992960PMC
May 2019

Optical coherence tomography to detect acute esophageal radiation-induced damage in mice: A validation study.

J Biophotonics 2019 09 26;12(9):e201800440. Epub 2019 Jun 26.

Department of Biomedical Engineering and Physics, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.

Radiation therapy for patients with non-small-cell lung cancer is hampered by acute radiation-induced toxicity in the esophagus. This study aims to validate that optical coherence tomography (OCT), a minimally invasive imaging technique with high resolution (~10 μm), is able to visualize and monitor acute radiation-induced esophageal damage (ARIED) in mice. We compare our findings with histopathology as the gold standard. Irradiated mice receive a single dose of 40 Gy at proximal and distal spots of the esophagus of 10.0 mm in diameter. We scan mice using OCT at two, three, and seven days post-irradiation. In OCT analysis, we define ARIED as a presence of distorted esophageal layering, change in backscattering signal properties, or change in the esophageal wall thickness. The average esophageal wall thickness is 0.53 mm larger on OCT when ARIED is present based on histopathology. The overall sensitivity and specificity of OCT to detect ARIED compared to histopathology are 94% and 47%, respectively. However, the overall sensitivity of OCT to assess ARIED is 100% seven days post-irradiation. We validate the capability of OCT to detect ARIED induced by high doses in mice. Nevertheless, clinical studies are required to assess the potential role of OCT to visualize ARIED in humans.
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http://dx.doi.org/10.1002/jbio.201800440DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7065648PMC
September 2019

Three-dimensional histopathological reconstruction of bladder tumours.

Diagn Pathol 2019 Mar 28;14(1):25. Epub 2019 Mar 28.

Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.

Background: Histopathological analysis is the cornerstone in bladder cancer (BCa) diagnosis. These analysis suffer from a moderate observer agreement in the staging of bladder cancer. Three-dimensional reconstructions have the potential to support the pathologists in visualizing spatial arrangements of structures, which may improve the interpretation of specimen. The aim of this study is to present three-dimensional (3D) reconstructions of histology images.

Methods: En-bloc specimens of transurethral bladder tumour resections were formalin fixed and paraffin embedded. Specimens were cut into sections of 4 μm and stained with Hematoxylin and Eosin (H&E). With a Phillips IntelliSite UltraFast scanner, glass slides were digitized at 20x magnification. The digital images were aligned by performing rigid and affine image alignment. The tumour and the muscularis propria (MP) were manually delineated to create 3D segmentations. In conjunction with a 3D display, the results were visualized with the Vesalius3D interactive visualization application for a 3D workstation.

Results: En-bloc resection was performed in 21 BCa patients. Per case, 26-30 sections were included for the reconstruction into a 3D volume. Five cases were excluded due to export problems, size of the dataset or condition of the tissue block. Qualitative evaluation suggested an accurate registration for 13 out of 16 cases. The segmentations allowed full 3D visualization and evaluation of the spatial relationship of the BCa tumour and the MP.

Conclusion: Digital scanning of en-bloc resected specimens allows a full-fledged 3D reconstruction and analysis and has a potential role to support pathologists in the staging of BCa.
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http://dx.doi.org/10.1186/s13000-019-0803-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6440143PMC
March 2019

Grading upper tract urothelial carcinoma with the attenuation coefficient of in-vivo optical coherence tomography.

Lasers Surg Med 2019 Mar 28. Epub 2019 Mar 28.

Department of Urology, Amsterdam UMC, University of Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands.

Introduction: With catheter based optical coherence tomography (OCT), high resolution images of the upper urinary tract can be obtained, thereby facilitating the detection of upper tract urothelial carcinomas (UTUC). We hypothesized that the attenuation coefficient of the OCT signal (μ ) is related to the histopathologic grade of the tumor.

Objectives: In this study, we aimed to define the μ cut-off for discriminating high grade and low grade papillary UTUC.

Methods: For this post-hoc analysis, data from OCT imaging of papillary UTUC was obtained from patients during ureterorenoscopy. OCT images and raw data were simultaneously analyzed with in-house developed software. The μ determined in papillary UTUCs and corresponding histopathologic grading from either biopsies or radical resection specimens were compared.

Results: Thirty-five papillary UTUC from 35 patients were included. μ analysis was feasible in all cases. The median μ was 3.3 mm (IQR 2.7-3.7 mm ) for low-grade UTUC and 4.9 mm (IQR 4.3-6.1 mm ) for high-grade UTUC (P = 0.004). ROC analysis yielded a μ cut-off value of >4.0 mm (AUC = 0.85, P < 0.001) with a sensitivity of 83% and a specificity of 94% for high-grade papillary UTUC.

Conclusions: This study proposes a μ cut-off of 4.0 mm for quantitative grading of UTUC with ureterorenoscopic OCT imaging. The promising diagnostic accuracy calculations justify further studies to validate the proposed cut-off value. Implementation of the software for the μ analysis in OCT systems may allow for μ assessment at real time during ureterorenoscopy. Lasers Surg. Med. 9999:1-8, 2019. © 2019 Wiley Periodicals, Inc.
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http://dx.doi.org/10.1002/lsm.23079DOI Listing
March 2019

Refractive index measurement using single fiber reflectance spectroscopy.

J Biophotonics 2019 07 3;12(7):e201900019. Epub 2019 Apr 3.

Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.

A method using single fiber reflectance spectroscopy to measure the refractive indices of transparent and turbid media over a broad wavelength range is presented and tested. For transparent liquid samples, the accuracy is within 0.2%, and the accuracy increases with increasing wavelength. For liquid turbid media, the accuracy is within 0.3% and increases with decreasing wavelength. For solid turbid samples, such as human skin, the accuracy critically depends on the optical contact between the fiber and sample surface. It is demonstrated that this technique has the potential to measure refractive indices of biological tissue in vivo.
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http://dx.doi.org/10.1002/jbio.201900019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7065624PMC
July 2019