The CellRaft AIRⓇ system: A novel system enabling organoid imaging, identification, and isolation.

Three-dimensional (3D) culture systems have been developed that can re-capitulate organ level responses, simulate compound diffusion through complex structures, and assess cellular heterogeneity of tissues, making them attractive models for advanced in vitro research and discovery. Organoids are a unique subtype of 3D cell culture that are grown from stem cells, are self-organizing, and closely replicate in vivo pathophysiology. Organoids have been used to understand tissue development, model diseases, test drug sensitivity and toxicity, and advance regenerative medicine. However, traditional organoid culture methods are inadequate because they are low throughput and ill-suited for single organoid imaging, phenotypic assessment, and isolation from heterogenous organoid populations. To address these bottlenecks, we have adapted our tissue culture consumable and instrumentation to enable automated imaging, identification, and isolation of individual organoids. Organoids grown on the 3D CytoSortⓇ Array can be reliably tracked, imaged, and phenotypically analyzed using brightfield and fluorescent microscopy as they grow over time, then released and transferred fully intact for use in downstream applications. Using mouse hepatic and pancreatic organoids, we have demonstrated the use of this technology for single-organoid imaging, clonal organoid generation, parent organoid subcloning, and single-organoid RNA extraction for downstream gene expression or transcriptomic analysis. The results validate the ability of the CellRaft AIRⓇ System to facilitate efficient, user-friendly, and automated workflows broadly applicable to organoid research by overcoming several pain points: 1) single organoid time-course imaging and phenotypic assessment, 2) establishment of single cell-derived organoids, and 3) isolation and retrieval of single organoids for downstream applications.

Detection of dysplasia in Barrett's esophagus with in vivo depth-resolved nuclear morphology measurements.

BACKGROUND & AIMS: Patients with Barrett's esophagus (BE) show increased risk of developing esophageal adenocarcinoma and are routinely examined using upper endoscopy with biopsy to detect neoplastic changes. Angle-resolved low coherence interferometry (a/LCI) uses in vivo depth-resolved nuclear morphology measurements to detect dysplasia. We assessed the clinical utility of a/LCI in the endoscopic surveillance of patients with BE. METHODS: Consecutive patients undergoing routine surveillance upper endoscopy for BE were recruited at 2 endoscopy centers. A novel, endoscope-compatible a/LCI system measured the mean diameter and refractive index of cell nuclei in esophageal epithelium at 172 biopsy sites in 46 patients. At each site, an a/LCI measurement was correlated with a concurrent endoscopic biopsy specimen. Each biopsy specimen was assessed histologically and classified as normal, nondysplastic BE, indeterminate for dysplasia, low-grade dysplasia (LGD), or high-grade dysplasia (HGD). The a/LCI data from multiple depths were analyzed to evaluate its ability to differentiate dysplastic from nondysplastic tissue. RESULTS: Pathology characterized 5 of the scanned sites as HGD, 8 as LGD, 75 as nondysplastic BE, 70 as normal tissue types, and 14 as indeterminate for dysplasia. The a/LCI nuclear size measurements separated dysplastic from nondysplastic tissue at a statistically significant (P < .001) level for the tissue segment 200 to 300 µm beneath the surface with an accuracy of 86% (147/172). A receiver operator characteristic analysis indicated an area under the curve of 0.91, and an optimized decision point gave 100% (13/13) sensitivity and 84% (134/159) specificity. CONCLUSIONS: These preliminary data suggest a/LCI is accurate in detecting dysplasia in vivo in patients with BE.

A probability-based spectroscopic diagnostic algorithm for simultaneous discrimination of brain tumor and tumor margins from normal brain tissue.

This paper reports the development of a probability-based spectroscopic diagnostic algorithm capable of simultaneously discriminating tumor core and tumor margins from normal human brain tissues. The algorithm uses a nonlinear method for feature extraction based on maximum representation and discrimination feature (MRDF) and a Bayesian method for classification based on sparse multinomial logistic regression (SMLR). Both the autofluorescence and the diffuse-reflectance spectra acquired in vivo from patients undergoing craniotomy or temporal lobectomy at the Vanderbilt University Medical Center were used to train and validate the algorithm. The classification accuracy was observed to be approximately 96%, 80%, and 97% for the tumor, tumor margin, and normal brain tissues, respectively, for the training data set and approximately 96%, 94%, and 100%, respectively, for the corresponding tissue types in an independent validation data set. The inherently multi-class nature of the algorithm facilitates a rapid and simultaneous classification of tissue spectra into various tissue categories without the need for a hierarchical multi-step binary classification scheme. Further, the probabilistic nature of the algorithm makes it possible to quantitatively assess the certainty of the classification and recheck the samples that are classified with higher relative uncertainty.

Liquid-crystal tunable filter spectral imaging for brain tumor demarcation.

Past studies have demonstrated that combined fluorescence and diffuse reflectance spectroscopy can successfully discriminate between normal, tumor core, and tumor margin tissues in the brain. To achieve efficient, real-time surgical resection guidance with optical biopsy, probe-based spectroscopy must be extended to spectral imaging to spatially demarcate the tumor margins. We describe the design and characterization of a combined fluorescence and diffuse reflectance imaging system that uses liquid-crystal tunable filter technology. Experiments were conducted to quantitatively determine the linearity, field of view, spatial and spectral resolution, and wavelength sensitivity of the imaging system. Spectral images were acquired from tissue phantoms, mouse brain in vitro, and human cortex in vivo for functional testing of the system. The spectral imaging system produces measured intensities that are linear with sample emission intensity and integration time and possesses a 1 in. (2.54 cm) field of view for a 7 in. (18 cm) object distance. The spectral resolution is linear with wavelength, and the spatial resolution is pixel-limited. The sensitivity spectra for the imaging system provide a guide for the distribution of total image integration time between wavelengths. Functional tests in vitro demonstrate the capability to spectrally discriminate between brain tissues based on exogenous fluorescence contrast or endogenous tissue composition. In vivo imaging captures adequate fluorescence and diffuse reflectance intensities within a clinically viable 2 min imaging time frame and demonstrates the importance of hemostasis to acquired signal strengths and imaging speed.

Comparison of spectral variation from spectroscopy to spectral imaging.

Optical biopsy has been shown to discriminate between normal and diseased tissue with high sensitivity and specificity. Fiber-optic probe-based spectroscopy systems do not provide the necessary spatial information to guide therapy effectively, ultimately requiring a transition from probe-based spectroscopy to spectral imaging. The effect of such a transition on fluorescence and diffuse reflectance line shape is investigated. Inherent differences in spectral line shape between spectroscopy and imaging are characterized and many of these differences may be attributed to a shift in illumination-collection geometry between the two systems. Sensitivity of the line-shape disparity is characterized with respect to changes in sample absorption and scattering as well as to changes in various parameters of the fiber-optic probe design (e.g., fiber diameter, beam steering). Differences in spectral line shape are described in terms of the relative relationship between the light diffusion within the tissue and the distribution of source-detector separation distances for the probe-based and imaging illumination-collection geometries. Monte Carlo simulation is used to determine fiber configurations that minimize the line-shape disparity between the two systems. In conclusion, we predict that fiber-optic probe designs that mimic a spectral imaging geometry and spectral imaging systems designed to emulate a probe-based geometry will be difficult to implement, pointing toward a posteriori correction for illumination-collection geometry to reconcile imaging and probe-based spectral line shapes or independent evaluation of tissue discrimination accuracy for probe-based and spectral imaging systems.

Experimental and simulated angular profiles of fluorescence and diffuse reflectance emission from turbid media.

Given the wavelength dependence of sample optical properties and the selective sampling of surface emission angles by noncontact imaging systems, differences in angular profiles due to excitation angle and optical properties can distort relative emission intensities acquired at different wavelengths. To investigate this potentiality, angular profiles of diffuse reflectance and fluorescence emission from turbid media were evaluated experimentally and by Monte Carlo simulation for a range of incident excitation angles and sample optical properties. For emission collected within the limits of a semi-infinite excitation region, normalized angular emission profiles are symmetric, roughly Lambertian, and only weakly dependent on sample optical properties for fluorescence at all excitation angles and for diffuse reflectance at small excitation angles relative to the surface normal. Fluorescence and diffuse reflectance within the emission plane orthogonal to the oblique component of the excitation also possess this symmetric form. Diffuse reflectance within the incidence plane is biased away from the excitation source for large excitation angles. The degree of bias depends on the scattering anisotropy and albedo of the sample and results from the correlation between photon directions upon entrance and emission. Given the strong dependence of the diffuse reflectance angular emission profile shape on incident excitation angle and sample optical properties, excitation and collection geometry has the potential to induce distortions within diffuse reflectance spectra unrelated to tissue characteristics.

Dynamic, three-dimensional optical tracking of an ablative laser beam.

Surgical resection remains the treatment of choice for brain tumors with infiltrating margins but is currently limited by visual discrimination between normal and neoplastic marginal tissues during surgery. Imaging modalities such as computed tomography, magnetic resonance, positron emission tomography, and optical techniques can accurately localize tumor margins. We believe coupling the fine resolution of current imaging techniques with the precise cutting of midinfrared lasers through image-guided neurosurgery can greatly enhance tumor margin resection. This paper describes a feasibility study designed to optically track in three-dimensional space the articulated arm delivery of a noncontact ablative laser beam. To enable optical tracking of the laser beam focus, infrared-emitting diodes (IREDs) were attached to a handpiece machined for the distal end of the articulated arm of a surgical carbon dioxide laser. Crosstalk between the ablative laser beam and the tracking diodes was measured. The geometry of the adapted laser handpiece was characterized to track an externally attached passive tip and the laser beam focus. Target localization accuracies were assessed for both instrument points-of-interest and the sources of tracking errors were investigated. Stray infrared laser light did not affect optical tracking accuracy. The mean target registration errors while optically tracking the laser handpiece with a passive tip and the laser beam focus were 1.31+/-0.50 mm and 2.31+/-0.92 mm, respectively, and were equivalent to the errors tracking a 24-IRED pen probe from Northern Digital in a side-by-side comparison. The majority of error during ablation tracking derived from registration accuracy between physical space and the defined space of the ablation phantom and from an inability to freehand align the laser focus with the target in a consistent manner. While their magnitudes depend on spatial details of the tracking setup (e.g., number and distribution of fiducial points, working distance from the camera, etc.), these errors are inherent to any freehand laser surgery.