Use Of Multispectral Imaging Research Articles

Abstract 4162: Identifying T lymphocytes in IHC-stained tissues independently of CD3+ staining using morphometric features extracted by image analysis

Abstract Assessments of leukocyte populations in the context of cancer tissues are typically determined by staining for leukocyte subtype markers in formalin fixed tissues. This requires the identification, categorization, and localization of multiple leukocytes within tissue context utilizing multiple markers. Meeting these demands are challenging due to technical constraints on the number of individual markers which can be visualized or scored in a single slide, and the complexity of staining observed. The use of multispectral imaging with fluorescent multiplexed markers has better enabled the assessment of multiple markers in a single tissue section. However, these wet chemistry and image capture technologies are very complex, and can only be successfully implemented with significant laboratory infrastructure, specialty equipment, and experienced resources. For these reasons, this approach is not widely implementable in the clinical pathology laboratory setting, where such tests are oriented to a companion diagnostic utility. Approaches which rely on widely adopted chromogenic immunohistochemistry (IHC) staining are preferred in the clinical laboratory setting, but the number of assayable markers is limited to 1-3 unique markers in a single tissue. In order to create a useful approach that could be implemented in existing clinical laboratory workflow, Flagship Biosciences has developed an approach for deriving the complex endpoints often necessary in immuno-oncology studies which rely on 1-3 chromagenic stains and computer interpretation of the tissue using only hematoxylin counterstain to identify T-lymphocytes. In a proof-of-concept study, we utilized our Tissue Image Analysis (TIA) tools to identify morphometric parameters which could identify T-lymphocytes, independent of staining for the T-lymphocyte marker CD3. A cohort of non-small cell lung cancer (NSCLC) tissues was stained by CD3 IHC, and both CD3 and isotype-stained tissues were analyzed with Flagship's CellMap™ software to capture the morphometric and staining features of cells in the tissues. The morphometric features which characterized CD3+ cells were used to approximate the T-lymphocyte population frequency in the isotype-stained tissues. This T-lymphocyte classification scheme was defined based on hematoxylin staining alone, and accuracy of T-lymphocyte classification was verified by CD3 staining. Based on this study, the method described herein could be utilized to reasonably estimate the frequency of T-lymphocyte subsets (e.g. CD4+, CD8+, etc.) or different marker-positive leukocyte (e.g. macrophages) subsets relative to the total T-lymphocyte population without an additional T-lymphocyte marker such as CD3. The approach could, therefore, provide an added dimension of analysis for tissues stained by IHC without adding complexity to the wet assay by necessitating a marker for T-lymphocytes. Citation Format: Nathan T. Martin, Joshua Black, Famke Aeffner, Logan Cerkovnik, Jasmeet Bajwa, Staci J. Kearney, Crystal Pulliam, A.J. Milici, Joseph Krueger. Identifying T lymphocytes in IHC-stained tissues independently of CD3+ staining using morphometric features extracted by image analysis. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4162.

Viability prediction of Ricinus cummunis L. seeds using multispectral imaging.

The purpose of this study was to highlight the use of multispectral imaging in seed quality testing of castor seeds. Visually, 120 seeds were divided into three classes: yellow, grey and black seeds. Thereafter, images at 19 different wavelengths ranging from 375–970 nm were captured of all the seeds. Mean intensity for each single seed was extracted from the images, and a significant difference between the three colour classes was observed, with the best separation in the near-infrared wavelengths. A specified feature (RegionMSI mean) based on normalized canonical discriminant analysis, were employed and viable seeds were distinguished from dead seeds with 92% accuracy. The same model was tested on a validation set of seeds. These seeds were divided into two groups depending on germination ability, 241 were predicted as viable and expected to germinate and 59 were predicted as dead or non-germinated seeds. This validation of the model resulted in 96% correct classification of the seeds. The results illustrate how multispectral imaging technology can be employed for prediction of viable castor seeds, based on seed coat colour.

Use of multispectral imaging in varietal identification of tomato.

Multispectral imaging is an emerging non-destructive technology. In this work its potential for varietal discrimination and identification of tomato cultivars of Nepal was investigated. Two sample sets were used for the study, one with two parents and their crosses and other with eleven cultivars to study parents and offspring relationship and varietal identification respectively. Normalized canonical discriminant analysis (nCDA) and principal component analysis (PCA) were used to analyze and compare the results for parents and offspring study. Both the results showed clear discrimination of parents and offspring. nCDA was also used for pairwise discrimination of the eleven cultivars, which correctly discriminated upto 100% and only few pairs below 85%. Partial least square discriminant analysis (PLS-DA) was further used to classify all the cultivars. The model displayed an overall classification accuracy of 82%, which was further improved to 96% and 86% with stepwise PLS-DA models on high (seven) and poor (four) sensitivity cultivars, respectively. The stepwise PLS-DA models had satisfactory classification errors for cross-validation and prediction 7% and 7%, respectively. The results obtained provide an opportunity of using multispectral imaging technology as a primary tool in a scientific community for identification/discrimination of plant varieties in regard to genetic purity and plant variety protection/registration.

Classification of African Mosaic Virus Infected Cassava Leaves by the Use of Multi-Spectral Imaging

In this work, we have used multispectral imaging technology to classify cassava leaves infected by African mosaic virus by the use of their unique spectral finger print. The spectra are extracted from transmission, reflection and diffusion of their multispectral images; they have been then analyzed with statistical multivariate analysis techniques. Principal component analysis (PCA) has been used followed by K-means and Ascending Hierarchical Classification (AHC) to endorse the classification. The contribution of this work is the use of multispectral imagery which binds both spatial and spectral information to differentiate and sort infected leaves. The results show that the multimodal and imaging spectroscopy may allow blind identification and characterization of infected leaves.

The Use of Multispectral Imaging Combined with Quantum Dots In Fine Needle Aspiration Biopsies of Reactive Lymphoid Hyperplasia and Follicular Lymphoma

AbstractAbstract 3109 Background:Despite controversies regarding the ability of fine needle aspiration in diagnostic workup of lymphomas, authorities report widespread use of this diagnostic procedure. In this regard, cytologic distinction between reactive lymphoid hyperplasia (RLH) and small cell lymphomas, such as follicular lymphoma (FL), are especially difficult in fine needle aspirations (FNA). The use of ancillary tests in these cases is crucial, and often includes flow cytometry (FC), immunohistochemistry (IHC), and fluorescence in situ hybridization (FISH). The interpretation of IHC can be challenging due to the subjective and qualitative nature, in addition to the need for multiple sections for analysis of multiple antibodies. The FC and FISH require ample appropriate material which is sometimes not available due to the scanty yield of FNA procedure. Multispectral imaging (MSI) with quantum dots (QDs) uses highly fluorescent molecules that allow multiple spectra to be distinguished when used in combination, which allows for more precise signal quantitation. Briefly, QDs are semiconductor nanocrystals that possess unique properties of an extremely high fluorescence efficiency and lack of photobleaching due to their inorganic composition, making them ideal fluorophores. They can absorb light over a wide range of wavelengths, and due to their precise crystalline structure, their emission spectrum is tightly defined. Furthermore, their emission wavelength is tunable during synthesis producing a range of narrow emission spectra with little overlapping. The remarkable spectral properties of QDs allow easy multiplexing, and therefore more information can be acquired from fewer samples, an ideal property while working with FNA samples. An additional advantage of fluorescence detection is a more precise signal quantitation compared to chromogenic methods. Consequently, QDs have potential for multiplex biomarker quantitation. Thus, we examined the ability of MSI to provide quantitative and useful data to help in distinguishing RLH and FL in FNA biopsies, which might improve the diagnostic accuracy rates of FNA. Design:A total of 8 FNA cell block sections from 4 RLH and 4 FL cases were stained using immunohistochemical stains (CD3, CD20, CD10, and bcl-2) conjugated to quantum dot fluorophores. A series of slides were also used for controls and for creating a spectral library on the Nuance CRI Flex microscopy system (CRi, Cambridge Research & Instrumentation, Woburn, MA; spectral range 420 to 720 nm). A total of 3 fields of view (FOV) at 10x magnification were captured for each case and analyzed using the Nuance software version 2.10. Results:All 8 cases were from FNAs of lymph nodes and had confirmed diagnosis in subsequent excisional biopsy or complete immunophenotyping/molecular data. The analysis of the 24 FOV revealed that the FL cases tended to show significantly more CD20-positive cells than CD3-positive cells (lower CD3:CD20 ratio; 0.3 vs. 3.9), and tended to have more pixels colocalizing CD20/CD10/bcl-2. For quality control purposes, the average percent of pixels colocalizing CD3 and CD20 was less than 0.4%. Conclusions:This study shows that MSI is feasible on FNA cell block material and can be helpful in obtaining quantitative data from multiple antibodies used on a single slide. This allows a potentially objective reproducible quantitative expression of different antigens to be determined on a single slide which may be advantageous in FNA samples with limited material and may potentially be helpful in the cytologic distinction of RLH and FL. [Display omitted] Disclosures:No relevant conflicts of interest to declare.

Abstract 4959: Multispectral imaging of chromogenic multiplex IHC assays as an alternative to fluorescent methods

Abstract Detection and analysis of two or more co-localized antigens by light microscopy has been hindered by the difficulty in discerning and quantifying overlaying chromogens. Performing multi-analyte immunohistochemistry has many potential benefits and applications in the field of drug target evaluation and patient screening, including: 1) determination and quantification of immunoreactivity co-localization; 2) evaluation of spatial relationships between immunoreactive cell types; 3) signal transduction pathway activation studies; 4) reduction in tissue depletion; and 5) decreased reagent utilization. Multiplex immunofluorescence is not widely used as an analytical technique for clinical samples due to its lower sensitivity than chromogenic methods and concerns about autofluorescence in formalin-fixed tissue. Through the use of multispectral imaging, the absorption pattern of overlapping chromogens can be spectrally unmixed into quantitative individual dye components. This process works accurately when chromogens are developed to a lower intensity than typical for most standard pathology laboratories. The chromogens must be developed to a point where they do not scatter light or block subsequent chromogenic development. The current study was performed to define the accuracy of spectral unmixing of chromogens and evaluate whether interference existed between chromogens. Stained samples were imaged using multispectral imaging, and quantitative grayscale images for each analyte were created by spectral unmixing. The grayscale images were analyzed using image analysis software to determine the overall expression levels of each analyte. Development with Vulcan Red followed by DAB produced little interference, while high density development with DAB decreased the subsequent Vulcan Red staining intensity. Vulcan Red, DAB and hematoxylin unmixed properly and quantitatively. In summary, when multiplexed chromogenic IHC assays were developed using methods optimized for multispectral imaging, the technique demonstrated excellence performance characteristics without suffering from drawbacks commonly associated with fluorescence-based techniques. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4959.

The use of multispectral imaging to distinguish reactive urothelium from neoplastic urothelium

Context: The interpretation of urothelial atypia in a setting of chronic inflammation and reactive changes can prove difficult with small biopsies. Limited recuts lessen the efficacy of ancillary studies such as CK20, P53 and CD44 in these instances. Objective: To evaluate a triple-immunostain with the assistance of multispectral microscopy. Design: Fifty-three bladder biopsies with previous diagnosis of benign/reactive, dysplastic, carcinoma in situ or carcinoma were prepared using a triple-immunostain cocktail consisting of CK20, P53 and CD44. Three control stains were used for the purpose of creating a spectral library for the Nuance CRI Flex microscopy system. All specimens were interpreted by light microscopy, processed with the Nuance 2.71 software, and CK20 and P53 were scored blinded to the case diagnoses. CD44 was not scored as it proved difficult to interpret in many cases. Results: The results demonstrated that it was possible to separate CK20, P53 and the counterstain that were co-localized in the biopsies. Separation of the stains demonstrated a correlation of p53 and CK20 dual expression in biopsies diagnosed as carcinoma. Low or undetectable levels of expression were seen in biopsies later diagnosed as reactive or benign. Conclusion: The combination of multispectral microscopy and multiple immunostain cocktails form a powerful and useful tool for the interpretation of small biopsies with faint or difficult to interpret staining and for cases with limited material such as small-bladder biopsies.

A method for comparison of growth media in objective identification of Penicillium based on multi-spectral imaging

We consider the problems of using excessive growth media for identification and performing objective identification of fungi at the species level. We propose a method for choosing the subset of growth media, which provides the best discrimination between several fungal species. Furthermore, we propose the use of multi-spectral imaging as a means of objective identification. Three species of the fungal genus Penicillium are subject to classification. To obtain an objective classification we use multi-spectral images. Previously, RGB images have proven useful for the purpose. We use multi-spectral bands as they provide additional information about the chemistry of the fungal colonies. In this study three media [Czapek yeast extract agar (CYA), oatmeal agar (OAT), and yeast extract sucrose agar (YES)] have been compared on their ability to discriminate between the three species. We propose a statistical method to test which medium or combination of media gives the best discrimination. Statistical tests indicate that YES combined with CYA is the best choice of media in this case. However, for the objective identification one medium is sufficient to discriminate between the species. Statistical tests show that there are significant differences between the species on all individual media, and that these differences are largest on YES. The objective identification has been performed solely by means of digital image analysis. The features obtained from the image analysis merely correspond to macro-morphological features. The species have been classified using only 3–4 of the spectral bands with a 100% correct classification rate using both leave-one-out cross-validation and test set validation.

Systematic approach for using hyperspectral imaging data to develop multispectral imagining systems: Detection of feces on apples

The large size of data sets generated using hyperspectral imaging techniques significantly increases both the capability and difficulty of designing detection and classification systems. Of particular interest is the confluence with increasing use of multispectral imaging in machine vision, particularly in the area of food safety inspection. The purpose of this study was to develop a robust method for selecting one or two wavelengths for multispectral detection systems using hyperspectral data. The actual performance of detection algorithms in terms of true positives and false positives was used as optimization criteria. Detection of fecal contamination on apples is an important health safety issue. Prior observations suggest reflectance or fluorescence imaging in the visible to near-infrared can be used to detect such contamination. For this study, 1:2, 1:20, and 1:200 dilutions of dairy feces were applied to 100 Golden and 100 Red Delicious apples. Apples were imaged using a hyperspectral system, and a uniform power transformation was used to reduce inter-apple intensity variability. Detection was accomplished by applying a binary threshold to transformed single wavelength images and images construct using ratios or differences of images at two different wavelengths. Optimization criteria allowed for a maximum of three false positives. For reflectance imaging, maximum detection rates for 1:20 dilution spots on Golden and Red Delicious apples images were 100% and 62.5% using R816 − R697 and R784 − R738, respectively. For fluorescence imaging, maximum detection rates for 1:200 dilution spots on Golden and Red Delicious apples were 97.9% and 58.3% using F665/ F602 and F647/ F482, respectively. In all case, more concentrated dilution spots were detected at 100%. Maximum detection rates for Red Delicious apples required use of a Prewitt edge-detection filter. In comparison, tests of wavelengths and algorithms identified in previous studies using statistical methods such as principal component analysis produced lower detection rates, mainly due to problems with false positives. The procedures used for developing detection algorithms are not specific to detecting feces on apples, and it is theoretically easy to extend the results to detection schemes involving many wavelengths. The problem is the classical dilemma of rapidly increasing computational time. Still, given the costs of thoroughly testing a candidate detection algorithm, the time maybe warranted. Furthermore, as machine vision systems are often limited to one or two wavelengths due to practical considerations including cost, exhaustive search algorithms based-on optimizing the output of candidate detection algorithms should be cost-effective.

Lunar soil characterization consortium analyses: Pyroxene and maturity estimates derived from Clementine image data

The mineralogy of a planetary surface is a diagnostic product of its formation and geologic evolution. Global assessment of lunar mineralogy at high spatial resolution has been a long standing goal of lunar exploration. Currently, the only global data available for such study is multispectral imagery from the Clementine mission. We use the detailed compositional, petrographic, and spectroscopic data of lunar soils produced by the Lunar Soil Characterization Consortium to explore the use of multispectral imaging as a diagnostic tool. We compare several statistically optimized formulations of links between spectral and mineral parameters and apply them to Clementine UV–VIS data. The most reliable results are for estimations of pyroxene abundance and maturity parameters (agglutinate abundance, I s / FeO ). Estimations of different pyroxene composition (low-Ca versus high-Ca) appear good in a relative sense, but absolute values are limited by residual wavelength dependent Clementine photometric calibrations. Since the signal-to-noise of Clementine multispectral data is good at the 1-km scale, almost any combination of parameters that capture inherent spectral variance can provide spatially coherent maps, although the parameters may not actually be directly related to composition. Clementine estimates are useful for identifying scientific or exploration targets for imaging spectrometer sensors of the next generation that are specifically designed to characterize mineralogy.

An affordable multispectral imaging system for the digital museum

The use of multispectral imaging for the acquisition of the image content of a digital museum is proposed. The advantages of multispectral imaging over “traditional” RGB imaging are explained, and the two existing approaches to multispectral acquisition, based on narrowband and wideband sensors respectively, are detailed. The characteristics of wideband multispectral acquisition systems in view of their possible large-scale use for digital museum content acquisition are then discussed, and an example system assembled by the authors and tested in acquisitions of real artifacts is introduced. Finally, it is shown that multispectral representations collected with such systems can be used for several purposes, including reproduction with current and future devices and support for monitoring and restoration, making them a natural choice for master copies in cultural institutions’ archives.

Multispectral Surface Analytical Microscopy: A Third-Generation Scanning Auger Electron Microscope

The quantitative interpretation of scanning Auger electron microscope (SAM) images has been shown to require the use of multi-spectral imaging of the surface under study. In a multi-spectral analytical microscope (MULSAM) a set of maps (bands) is acquired from the same area of a sample using scattered electrons with different kinetic energies as well as other signals from the sample such as current flowing to ground, the conventional SEM signal and characteristic x-rays. The resulting set of bands is a multi-spectral image which can be processed using models of the electron scattering in the sample and statistical transforms well known in LANDSAT imaging technology. The processed images can separate the mixed effects of topography, surface chemical inhomogeneity and bulk chemical composition fluctuations occurring in the bands of raw data.A computer controlled, UHV, energy analysing, scanning electron SEM will be described in this paper. The microscope contains facilities for collecting up to 23 256 by 256 pixel image bands from the same area of the sample.