Roundness variation in JPEG images affects the automated process of nuclear immunohistochemical quantification: correction with a linear regression model

The volume of digital image (DI) storage continues to be an important problem in computer-assisted pathology. DI compression enables the size of files to be reduced but with the disadvantage of loss of quality. Previous results indicated that the efficiency of computer-assisted quantification of immunohistochemically stained cell nuclei may be significantly reduced when compressed DIs are used. This study attempts to show, with respect to immunohistochemically stained nuclei, which morphometric parameters may be altered by the different levels of JPEG compression, and the implications of these alterations for automated nuclear counts, and further, develops a method for correcting this discrepancy in the nuclear count. For this purpose, 47 DIs from different tissues were captured in uncompressed TIFF format and converted to 1:3, 1:23 and 1:46 compression JPEG images. Sixty-five positive objects were selected from these images, and six morphological parameters were measured and compared for each object in TIFF images and those of the different compression levels using a set of previously developed and tested macros. Roundness proved to be the only morphological parameter that was significantly affected by image compression. Factors to correct the discrepancy in the roundness estimate were derived from linear regression models for each compression level, thereby eliminating the statistically significant differences between measurements in the equivalent images. These correction factors were incorporated in the automated macros, where they reduced the nuclear quantification differences arising from image compression. Our results demonstrate that it is possible to carry out unbiased automated immunohistochemical nuclear quantification in compressed DIs with a methodology that could be easily incorporated in different systems of digital image analysis.     

Scanning fluorescent microscopy is an alternative for quantitative fluorescent cell analysis.

BACKGROUND: Fluorescent measurements on cells are performed today with FCM and laser scanning cytometry. The scientific community dealing with quantitative cell analysis would benefit from the development of a new digital multichannel and virtual microscopy based scanning fluorescent microscopy technology and from its evaluation on routine standardized fluorescent beads and clinical specimens. METHODS: We applied a commercial motorized fluorescent microscope system. The scanning was done at 20 x (0.5 NA) magnification, on three channels (Rhodamine, FITC, Hoechst). The SFM (scanning fluorescent microscopy) software included the following features: scanning area, exposure time, and channel definition, autofocused scanning, densitometric and morphometric cellular feature determination, gating on scatterplots and frequency histograms, and preparation of galleries of the gated cells. For the calibration and standardization Immuno-Brite beads were used. RESULTS: With application of shading compensation, the CV of fluorescence of the beads decreased from 24.3% to 3.9%. Standard JPEG image compression until 1:150 resulted in no significant change. The change of focus influenced the CV significantly only after +/-5 microm error. CONCLUSIONS: SFM is a valuable method for the evaluation of fluorescently labeled cells.     

Quantitative precision of an automated, fluorescence-based image cytometer.

Digital image-based cytometry of clinical specimens labeled with fluorescent, disease-specific markers holds promise for becoming an important diagnostic and prognostic technique because the technique can make a diverse range of quantitative biochemical, morphologic, densitometric and contextual measurements on intact specimens. It has been previously shown by us, using an image cytometer (IC) consisting entirely of commercially available components, that the nuclei of individual cells in slide-supported specimens can be detected automatically using a fluorescent DNA stain and image analysis software. The purpose of this study was to determine the precision of the IC for quantifying the integrated fluorescence intensity and area of fluorescent standard beads and nuclei. Integrated intensities could be quantified to between 2.3% and 3.5% precision using a 40x objective lens and between 1.6% and 2.3% using a 20x objective. The main contribution to this uncertainty was 2% inaccuracy in determining the variations in sensitivity over the imaging area. Areas could be quantified to between 0.91% and 2.1% using a 40x objective and between 2.8% and 3.2% using a 20x objective. Significant quantification errors were introduced if the objects were not in focus or were touching each other. Overall, however, these results demonstrated that image cytometry of fluorescence-stained specimens can yield quantitative results with sufficient precision for determining DNA ploidy distributions and for making other measurements on clinical specimens.     

The effects of aging on the intimal region of the human saphenous vein: insights from multimodal microscopy and quantitative image analysis

We hypothesized that structural remodeling associated with advancing age occurs in human saphenous veins. To address this hypothesis, we have identified structural remodeling in human saphenous veins by applying histochemistry, fluorescence staining and quantitative image analysis to specifically assess intimal area, intimal cellularity and intimal collagen content and organization. Saphenous veins were collected from patients undergoing coronary artery bypass graft surgery. Area measurements and cellularity were quantified using the image analysis software Stereo Investigator, employing planimetry and counting frames, respectively. Collagen content and organization were quantified in MetaMorph image analysis software based on measurements of color (hue, saturation, and intensity) from polarized light images. Intimal area and cellularity showed no statistically significant increases with age; in contrast, total collagen content showed a significant decrease with advancing age. Furthermore, collagen fiber types also demonstrated a statistically significant alteration with age; increases in age resulted in decreases in larger collagen fibers. No significant changes in small collagen fibers were identified. These results raise the possibility that age-associated structural alterations in total collagen content, specifically collagen fiber size, could be a factor in the etiology of age-associated venous diseases.     

Three-dimensional visualization and quantitative analysis of cervical cell nuclei with confocal laser scanning microscopy

OBJECTIVE: To develop a method for the acquisition and processing of 3-dimensional images based on confocal laser scanning microscopy for the purpose of 3-dimensional visualization and quantitative analysis of cell nuclei. STUDY DESIGN: A contour-based surface rendering method was used, and volume rendering was implemented according to the basic volume rendering pipeline. To extract quantitative features, a 3-dimensional labeling method based on slice information was used. After applying the labeling algorithm, the measurements for 3-dimensional quantitative analysis of nuclei were extracted: nuclear volume, surface area and spherical shape factor. We compared the 3-dimensional features of normal and abnormal cervical cell nuclei. RESULTS: Comparison of the size of 3-dimensional cervical cell nuclei between normal and abnormal revealed a statistically significant difference. The proposed method could overcome the limitation inherent in 2-dimensional analysis and could become a way of improving the accuracy and reproducibility of quantification of cell nuclei. CONCLUSION: Three-dimensional visualization and quantification of cell nuclei provide valuable medical information that can lead to a more objective diagnosis.     

Feature extraction from three-dimensional images in quantitative microscopy

Different methods are investigated in selecting and generating the appropriate microscope images for analysis of three-dimensional objects in quantitative microscopy. Traditionally, the ‘best’ focused image from a set is used for quantitative analysis. Such an objectively determined image is optimal for the extraction of some features, but may not be the best image for the extraction of all features. Various methods using multiple images are here developed to obtain a tighter distribution for all features.Three different approaches for analysis of images of stained cervical cells were analyzed. In the first approach, features are extracted from each image in the set. The feature values are then averaged to give the final result. In the second approach, a set of varying focused images are reconstructed to obtain a set of in-focus images. Features are then extracted from this set and averaged. In the third approach, a set of images in the three-dimensional scene is compressed into a single two-dimensional image. Four different compression methods are used. Features are then extracted from the resulting two-dimensional image. The third approach is employed on both the raw and transformed images.Each approach has its advantages and disadvantages. The first approach is fast and produces reasonable results. The second approach is more computationally expensive but produces the best results. The last approach overcomes the memory storage problem of the first two approaches since the set of images is compressed into one. The method of compression using the highest gradient pixel produces better results overall than other data reduction techniques and produces results comparable to the first approach.     

Computerized image analysis as a tool to quantify infiltrating leukocytes: a comparison between high- and low-magnification images.

The purpose of the present study was to establish a rapid and reproducible method for quantification of tissue-infiltrating leukocytes using computerized image analysis. To achieve this, the staining procedure, the image acquisition, and the image analysis method were optimized. Because of the adaptive features of the human eye, computerized image analysis is more sensitive to variations in staining compared with manual image analysis. To minimize variations in staining, an automated immunostainer was used. With a digital scanner camera, low-magnification images could be sampled at high resolution, thus making it possible to analyze larger tissue sections. Image analysis was performed by color thresholding of the digital images based on values of hue, saturation, and intensity color mode, which we consider superior to the red, green, and blue color mode for analysis of most histological stains. To evaluate the method, we compared computerized analysis of images with a x100 or a x12.5 magnification to assess leukocytes infiltrating rat brain tumors after peripheral immunizations with tumor cells genetically modified to express rat interferon-gamma (IFN-gamma) or medium controls. The results generated by both methods correlated well and did not show any significant differences. The method allows efficient and reproducible processing of large tissue sections that is less time-consuming than conventional methods and can be performed with standard equipment and software.(J Histochem Cytochem 49:1073-1079, 2001)     

Smart 3D-FISH: automation of distance analysis in nuclei of interphase cells by image processing.

BACKGROUND: Detection of fluorescent probes by fluorescence in situ hybridization in cells with preserved three-dimensional nuclear structures (3D-FISH) is useful for studying the organization of chromatin and localization of genes in interphase nuclei. Fast and reliable measurements of the relative positioning of fluorescent spots specific to subchromosomal regions and genes would improve understanding of cell structure and function. METHODS: 3D-FISH protocol, confocal microscopy, and digital image analysis were used. RESULTS: New software (Smart 3D-FISH) has been developed to automate the process of spot segmentation and distance measurements in images from 3D-FISH experiments. It can handle any number of fluorescent spots and incorporate images of 4',6-diamino-2-phenylindole counterstained nuclei to measure the relative positioning of spot loci in the nucleus and inter-spot distance. Results from a pilot experiment using Smart 3D-FISH on ENL, MLL, and AF4 genes in two lymphoblastic cell lines were satisfactory and consistent with data published in the literature. CONCLUSION: Smart 3D-FISH should greatly facilitate image processing and analysis of 3D-FISH images by providing a useful tool to overcome the laborious task of image segmentation based on user-defined parameters and decrease subjectivity in data analysis. It is available as a set of plugins for ImageJ software.     

Quantitative image analysis of connective tissue progenitors

OBJECTIVE: To develop an image analysis system to automatically identify colony-forming units (CFUs) in in vitro cell cultures of connective tissue progenitors. This system was designed to quantitatively assess colony morphology and number of colonies in 4-cm(2) culture wells. STUDY DESIGN: Large field-of-view high-resolution fluorescence images of 4',6-diamidino-2-phenylindole (DAPI)- and alkaline phosphatase (AP)-stained bone marrow cell cultures were obtained using an epi-fluorescence microscope and automated scanning stage. Cell nuclei were identified in the DAPI-stained images after removal of fluorescent debris from the image. An Euclidean distance map (EDM) of the segmented cell nuclei was used to cluster cell nuclei into colonies. The automated system was evaluated using 40 tissue culture wells of bone marrow aspirate samples. The results of the automated analysis were compared to the manual tracings of colonies by 3 reviewers. RESULTS: The automated method agreed with all 3 reviewers on average 87.5% of the time. Additionally, reviewers identified other colonies not outlined by the reviewers on average 2.7 times more than the automated method. CONCLUSION: The automated method is a less biased method for identifying CFUs than individual reviewers, it provides more quantitative information about colony morphology than can be obtained manually and it is less time consuming.     

Comparison of fine needle aspirates of breast cancers to imprint smears by means of digital cell image analysis

Morphonuclear assessments were performed using the SAMBA 2005 cell image processor on cell nuclei in fine needle aspirates and corresponding imprint smears from 17 not-otherwise-specified (NOS) breast carcinomas to study the influence of cell sampling on the morphonuclear measurements. Fourteen parameters related to densitometric (nuclear DNA content), morphometric (nuclear area) and textural (chromatin organization and distribution) characteristics were computed for each nucleus. The results demonstrated that such morphonuclear features evolved significantly and positively with respect to conventional histopathologic grading. The method of cell sampling significantly influenced the results, but without altering the general conclusions regarding evolution of the morphonuclear features.     

A red line not to cross: Evaluating the limitation and properness of gel image tuning procedures

Currently, results of gel electrophoresis are commonly documented in digital formats by image acquisition instruments. In this study, gel images tuned by a common image processing software package, Photoshop, were assessed to understand the transforming algorithms and their impacts on quantitative analysis. TotalLab 100, an electrophoresis gel image analysis software package, was applied for image quantitation and evaluation. The three most frequently used image tuning functions—adjustments of the brightness, contrast, and grayscale span (level) of images—were investigated using both data generated from a standard grayscale tablet and an actual electrophoresis gel image. The influences of these procedures were analyzed for the grayscale transformation between the input and output images. Although all three procedures differentially improved the visualization of the input image, adjusting the contrast of images disrupted the quantitative information because of its nonlinear transforming algorithm. Under certain conditions, adjusting the brightness or the level of images could preserve the quantitative information because of the linear transforming algorithms. It was found that when the minimum and maximum grayscales of a gel image were recognized, using a commercial software package to maximally stretch the level may significantly improve the quality of a gel image without jeopardizing quantitative analysis.     

3-D warped discrete cosine transform for MRI image compression

Image compression is an application of data compression on digital images. Several lossy/lossless transform coding techniques are used for image compression. Discrete cosine transform (DCT) is one such widely used technique. A variation of DCT, known as warped discrete cosine transform (WDCT), is used for 2-D image compression and it is shown to perform better than the DCT at high bit-rates. We extend this concept and develop the 3-D WDCT, a transform that has not been previously investigated. We outline some of its important properties, which make it especially suitable for image compression. We then propose a complete image coding scheme for volumetric data sets based on the 3-D WDCT scheme. It is shown that the 3-D WDCT-based compression scheme performs better than a similar 3-D DCT scheme for volumetric data sets at high bit-rates.     

Automated and customizable quantitative image analysis of whole Caenorhabditis elegans germlines

Arranged in a spatial-temporal gradient for germ cell development, the adult germline of Caenorhabditis elegans is an excellent system for understanding the generation, differentiation, function, and maintenance of germ cells. Imaging whole C. elegans germlines along the distal-proximal axis enables powerful cytological analyses of germ cell nuclei as they progress from the pre-meiotic tip through all the stages of meiotic prophase I. To enable high-content image analysis of whole C. elegans gonads, we developed a custom algorithm and pipelines to function with image processing software that enables: (1) quantification of cytological features at single nucleus resolution from immunofluorescence images; and (2) assessment of these individual nuclei based on their position within the germline. We show the capability of our quantitative image analysis approach by analyzing multiple cytological features of meiotic nuclei in whole C. elegans germlines. First, we quantify double-strand DNA breaks (DSBs) per nucleus by analyzing DNA-associated foci of the recombinase RAD-51 at single-nucleus resolution in the context of whole germline progression. Second, we quantify the DSBs that are licensed for crossover repair by analyzing foci of MSH-5 and COSA-1 when they associate with the synaptonemal complex during meiotic prophase progression. Finally, we quantify P-granule composition across the whole germline by analyzing the colocalization of PGL-1 and ZNFX-1 foci. Our image analysis pipeline is an adaptable and useful method for researchers spanning multiple fields using the C. elegans germline as a model system.     

Automated analysis of muscle fibre images

A technique for studying the distribution and size of different fibre types in muscles is proposed for automated analysis of individual fibres in optical density images from ATPase-stained muscle sections. After delineation, fibres may be classified into different histological types (1, 2A, 2B and 2C) using the measurement of their mean optical density (mOD). The densitometric measurements were obtained from three serial histological slides stained under different conditions. The delineation procedure is performed on one of the images: the resulting mask is fitted to the other images using a linear coordinate transform. Along with densitometric measurements, the lesser diameter of the fibres is computed. Both in processing and in analysis, extensive use was made of mathematical morphology tools. All software was implemented on a VICOM digital image processor, extended with a VISIOMORPH morphoprocessor board.     

Risk biomarker assessment for breast cancer progression: replication precision of nuclear morphometry.

Nuclear morphometry is a method for quantitative measurement of histopathologic changes in the appearance of stained cell nuclei. Numerous studies have indicated that these assessments may provide clinically relevant information related to the degree of progression and malignant potential of breast neoplasia. Nuclear features are derived from computerized analysis of digitized microscope images, and a quantitative Feulgen stain for DNA was used. Features analyzed included: (1) DNA content; (2) nuclear size and shape; and (3) texture features, describing spatial features of chromatin distribution. In this study replicated measurements are described on a series of 54 breast carcinoma specimens of differing pathologic grades. Duplicate measurements were performed using two serial sections, which were processed and analyzed separately. The value of a single feature measurement, the nuclear area profile, was shown to be the strongest indicator of progression. A quantitative nuclear grade was derived and shown to be strongly correlated with not only the pathologic nuclear grade, but also with tubule formation, mitotic grade, and with the overall histopathologic grade. Analysis of replication precision showed that the standard methods of the histopathology laboratory, if practiced in a uniform manner, are sufficient to ensure reproducibility of these assessments. We argue that nuclear morphometry provides a standardized and reproducible framework for quantitative pathologic assessments.     

Karyometric marker features in fine needle aspirates of invasive follicular carcinoma of the thyroid.

Karyometric measurements were performed on fine needle aspirates of clearly identifiable tumor areas and adjacent normal-appearing areas in the surgical specimens from ten patients with invasive follicular carcinoma of the thyroid. Similar measurements were performed on aspirates from nine patients free of thyroid disease (controls). A total of 95 karyometric features were evaluated for each nucleus. Analysis of variance of optical density values indicated (1) a similarity between tumor and normal-appearing nuclei from carcinoma cases, (2) a significant difference between those nuclei and control nuclei and (3) that most of the differences were due to the differences of tissue origin. Stepwise linear discriminant analysis selected ten features that produced a statistically highly significant separation of tumor nuclei from control nuclei. A similar analysis selected six features that produced a statistically highly significant discrimination of normal-appearing nuclei from control nuclei; the validity of those karyometric features as markers of malignancy in normal-appearing nuclei from tissues adjacent to invasive follicular carcinomas of the thyroid was demonstrated by analysis in further training and control sets of nuclei. This analysis in thyroid aspirates identified more marker features than did a previous similar analysis using tissue sections.     

The influence of variations in the measuring procedure on quantitative nuclear image features in histologic sections of lung tissue

The qualitative and quantitative features of cell nuclei in tissue sections play an important role in diagnostic histopathology; variations in staining intensity and measuring procedures may interfere with their proper evaluation. To identify nuclear features that are relatively insensitive to these technical variables, the influence of critical steps in a scanning-stage densitometer measuring system was studied on 87 quantitative nuclear image (QNI) features in histologic sections of lung tissue. The influences of the following measuring variations were evaluated: interactive segmentation (with and without median filtering; with and without 5% uniform distributed noise added); scanning (with and without median filtering); calibration of the photomultiplier (different background localizations and different intensity levels); and time. In addition, the influence of artificially changed intensity variations was investigated. The results showed that, while the coefficient of variation (CV) induced by variations in the measuring system was usually low (below 10%), for some QNI features the CV can be high (up to 216%). The influence of artificial variations in intensity was restricted: only a minority of the QNI features showed a significant difference. Of the 87 QNI features, 35 had a CV of less than 10%, and 25 of these were significantly correlated with each other. Thus, only ten uncorrelated, low-CV QNI features remained; these belonged to all of the different QNI feature categories used. These features may be diagnostically important since they may best describe the morphologic properties of the nuclei. The results of this study should help in selecting quantitative nuclear image features that are less sensitive to variations in the measuring procedure and staining intensity.     

Automated image analysis methods for 3-D quantification of the neurovascular unit from multichannel confocal microscope images.

BACKGROUND: There is a need for integrative and quantitative methods to investigate the structural and functional relations among elements of complex systems, such as the neurovascular unit (NVU), that involve multiple cell types, microvasculatures, and various genomic/proteomic/ionic functional entities. METHODS: Vascular casting and selective labeling enabled simultaneous three-dimensional imaging of the microvasculature, cell nuclei, and cytoplasmic stains. Multidimensional segmentation was achieved by (i) bleed-through removal and attenuation correction; (ii) independent segmentation and morphometry for each corrected channel; and (iii) spatially associative feature computation across channels. The combined measurements enabled cell classification based on nuclear morphometry, cytoplasmic signals, and distance from vascular elements. Specific spatial relations among the NVU elements could be quantified. RESULTS: A software system combining nuclear and vessel segmentation codes and associative features was constructed and validated. Biological variability contributed to misidentified nuclei (9.3%), undersegmentation of nuclei (3.7%), hypersegmentation of nuclei (14%), and missed nuclei (4.7%). Microvessel segmentation errors occurred rarely, mainly due to nonuniform lumen staining. CONCLUSIONS: Associative features across fluorescence channels, in combination with standard features, enable integrative structural and functional analysis of the NVU. By labeling additional structural and functional entities, this method can be scaled up to larger-scale systems biology studies that integrate spatial and molecular information.