Synergistic Tissue Counterstaining and Image Segmentation Techniques for Accurate, Quantitative Immunohistochemistry

Quantitative analysis of digitized IHC-stained tissue sections is increasingly used in research studies and clinical practice. Accurate quantification of IHC staining, however, is often complicated by conventional tissue counterstains caused by the color convolution of the IHC chromogen and the counterstain. To overcome this issue, we implemented a new counterstain, Acid Blue 129, which provides homogeneous tissue background staining. Furthermore, we combined this counterstaining technique with a simple, robust, fully automated image segmentation algorithm, which takes advantage of the high degree of color separation between the 3-amino-9-ethyl-carbazole (AEC) chromogen and the Acid Blue 129 counterstain. Rigorous validation of the automated technique against manual segmentation data, using Ki-67 IHC sections from rat C6 glioma and β-amyloid IHC sections from transgenic mice with amyloid precursor protein (APP) mutations, has shown the automated method to produce highly accurate results compared with ground truth estimates based on the manually segmented images. The synergistic combination of the novel tissue counterstaining and image segmentation techniques described in this study will allow for accurate, reproducible, and efficient quantitative IHC studies for a wide range of antibodies and tissues. (J Histochem Cytochem 56:873–880, 2008)     

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)     

Comparison of manual and automated methods for identifying target sounds in audio recordings of Pileated, Pale-billed, and putative Ivory-billed woodpeckers

ABSTRACT.   Although offering many benefits over manual recording and survey techniques for avian field studies, automated sound recording systems produce large datasets that must be carefully examined to locate sounds of interest. We compared two methods for locating target sounds in continuous sound recordings: (1) a manual method using computer software to provide a visual representation of the recording as a sound spectrogram and (2) an automated method using sound analysis software preprogrammed to identify specific target sounds. For both methods, we examined the time required to process a 24-h recording, scanning accuracy, and scanning comprehensiveness using four different target sounds of Pileated Woodpeckers ( Dryocopus pileatus ), Pale-billed Woodpeckers ( Campephilus guatemalensis ), and putative Ivory-billed Woodpeckers ( Campehilus principalis ). We collected recordings from the bottomland forests of Florida and the Neotropical dry forests of Costa Rica, and compared manual versus automated cross-correlation scanning techniques. The automated scanning method required less time to process sound recordings, but made more false positive identifications and was less comprehensive than the manual method, identifying significantly fewer target sounds. Although the automated scanning method offers a fast and economic alternative to traditional manual efforts, our results indicate that manual scanning is best for studies requiring an accurate account of temporal patterns in call frequency and for those involving birds with low vocalization rates.     

Comparison of methods for assessing abdominal adipose tissue from magnetic resonance images

Objective: To compare the inter‐rater and intra‐rater reliability and analysis time of two methods for quantifying visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) volumes from magnetic resonance (MR) images. Research Methods and Procedures: Ten subjects (BMI, 27.0 ± 2.1 kg/m²; 56 years of age ± 4 years) underwent MR imaging of the abdomen. Ten transverse T1‐weighted images were selected from each scan and analyzed using two software packages that differ in principle. The first method, ANALYZE version 5.0, represents the manual threshold method, and the second, HIPPO version 1.3, is based on the fuzzy clustering approach. Inter‐rater reliability for each method was assessed by comparing the intra‐class correlation coefficients (ICCs) for VAT and SAT results from two evaluators, and intra‐rater reliability for each method was assessed by comparing ICCs for VAT and SAT analyses performed 1 week apart by the same evaluator. The total time for analysis also was compared between methods. Results: The inter‐rater reliability for VAT was greater with HIPPO than with ANALYZE (ICC = 0.996 vs. 0.828), whereas inter‐rater reliability for SAT did not differ between methods (ICC = 0.975 and 0.987). The intra‐rater reliability was equally high with HIPPO and ANALYZE for both VAT (ICC = 0.998 vs. 0.992) and SAT (ICC = 0.996 vs. 0.992). HIPPO required less than one‐half as much analysis time as ANALYZE (15.9 ± 4.4 vs. 36.5 ± 8.2 minutes, p < 0.0001). Discussion: HIPPO software appears advantageous for the quantification of VAT from multislice MR images because inter‐rater results are more reliable, and it is more time‐efficient than less automated methods.     

Comparison of image analysis software packages in the assessment of adhesion of microorganisms to mucosal epithelium using confocal laser scanning microscopy

We have compared current image analysis software packages in order to find the most useful one for assessing microbial adhesion and inhibition of adhesion to tissue sections. We have used organisms of different sizes, the bacterium Helicobacter pylori and the yeast Candida albicans. Adhesion of FITC-labelled H. pylori and C. albicans was assessed by confocal microscopy. Four different Image analysis software packages, NIH-Image, IP Lab, Image Pro+, and Metamorph, were compared for their ability to quantify adhesion of the two organisms and several quantification methods were devised for each package. For both organisms, the dynamic range that could be detected by the software packages was 1x10(6)-1x10(9) cells/ml. Of the four software packages tested, our results showed that Metamorph software, using our 'Region of Interest' method, with the software's 'Standard Area Method' of counting, was the most suitable for quantifying adhesion of both organisms because of its unique ability to separate clumps of microbial cells. Moreover, fewer steps were required. By pre-incubating H. pylori with the glycoconjugate Lewis b-HSA, an inhibition of binding of 48.8% was achieved using 250 mug/ml Lewis b-HSA. The method we have devised using Metamorph software, provides a simple, quick and accurate way of quantifying adhesion and inhibition of adhesion of microbial cells to the epithelial surface of tissue sections. The method can be applied to organisms ranging in size from small bacteria to larger yeast cells.     

Volume scanning electron microscopy for imaging biological ultrastructure

Electron microscopy (EM) has been a key imaging method to investigate biological ultrastructure for over six decades. In recent years, novel volume EM techniques have significantly advanced nanometre‐scale imaging of cells and tissues in three dimensions. Previously, this had depended on the slow and error‐prone manual tasks of cutting and handling large numbers of sections, and imaging them one‐by‐one with transmission EM. Now, automated volume imaging methods mostly based on scanning EM (SEM) allow faster and more reliable acquisition of serial images through tissue volumes and achieve higher z‐resolution. Various software tools have been developed to manipulate the acquired image stacks and facilitate quantitative analysis. Here, we introduce three volume SEM methods: serial block‐face electron microscopy (SBEM), focused ion beam SEM (FIB‐SEM) and automated tape‐collecting ultramicrotome SEM (ATUM‐SEM). We discuss and compare their capabilities, provide an overview of the full volume SEM workflow for obtaining 3D datasets and showcase different applications for biological research.     

miREE: miRNA recognition elements ensemble

Background

The accurate prediction of ligand binding residues from amino acid sequences is important for the automated functional annotation of novel proteins. In the previous two CASP experiments, the most successful methods in the function prediction category were those which used structural superpositions of 3D models and related templates with bound ligands in order to identify putative contacting residues. However, whilst most of this prediction process can be automated, visual inspection and manual adjustments of parameters, such as the distance thresholds used for each target, have often been required to prevent over prediction. Here we describe a novel method FunFOLD, which uses an automatic approach for cluster identification and residue selection. The software provided can easily be integrated into existing fold recognition servers, requiring only a 3D model and list of templates as inputs. A simple web interface is also provided allowing access to non-expert users. The method has been benchmarked against the top servers and manual prediction groups tested at both CASP8 and CASP9.

Results

The FunFOLD method shows a significant improvement over the best available servers and is shown to be competitive with the top manual prediction groups that were tested at CASP8. The FunFOLD method is also competitive with both the top server and manual methods tested at CASP9. When tested using common subsets of targets, the predictions from FunFOLD are shown to achieve a significantly higher mean Matthews Correlation Coefficient (MCC) scores and Binding-site Distance Test (BDT) scores than all server methods that were tested at CASP8. Testing on the CASP9 set showed no statistically significant separation in performance between FunFOLD and the other top server groups tested.

Conclusions

The FunFOLD software is freely available as both a standalone package and a prediction server, providing competitive ligand binding site residue predictions for expert and non-expert users alike. The software provides a new fully automated approach for structure based function prediction using 3D models of proteins.     

Fuzzy algorithms: Application to adipose tissue quantification on MR images

Metabolic syndrome, which is related to abdominal obesity, is a fast growing disease in our western countries. Its presence greatly increases the risk of developing cardiovascular diseases. The accumulation of visceral adipose tissue plays a key role in the development of the metabolic syndrome. The increase of waist circumference is one of the five criteria of the metabolic syndrome diagnosis. But this increase can be due to visceral or subcutaneous adipose tissues. And these adipose tissues do not play the same rule in metabolic syndrome. The purpose of this study was to develop software for automatic and reliable quantification of visceral and subcutaneous adipose tissues, to detect patient with high risk to develop metabolic syndrome and to follow the evolution of adipose tissue repartition after treatment. A gradient echo magnetic resonance (MR) technique is used, with a TE such that fat and water are opposed in phase. The developed process is based on two fuzzy algorithms. First, we fuzzy generalized clustering algorithms allow to merge pixels according to their intensities. Then, fuzzy connectedness algorithm allows to merge pixels according to cost function related to distance, gradient distance and intensities. A validation is performed with a comparison between expert results made by manual drawing and purpose-made software results. Our software provides an automatic and reliable method to segment visceral and subcutaneous adipose tissue and additionally avoids in some case the problem of inhomogeneity of signal intensity.     

Etude Comparative de 3 Methodes D’analyse du Sperme

A comparative study between three methods of semen analysis reveals that the full automated CMA system gives higher values for sperm concentration than the mean of the three methods, probably due to misclassification of debris as sperm cells, whereas the semi-automatic Autosperm method and the conventional manual method identify spermatozoa in the microscopic field. The Autosperm method provides more reproducible results for concentration and velocity parameters and its values are better correlated with the manual method as recommended by the World Health Organization.     

Automated measurement of MIB-1 positive area as an alternative to counting in follicular lymphoma

Manual counting of MIB-1 positive cells which has been suggested as an alternative to centroblast counting for the diagnostic grading of follicular lymphoma is a laborious task. In this study, the validity of automated measurement of the MIB-1 positive area is analyzed as an alternative approach. Archival MIB-1 stained tissue sections of 15 follicular lymphomas were assessed manually and automatically by three independent observers. Concordance correlation coefficients and coefficients of variation were calculated to study reproducibility and variability of both methods and to compare result from both methods. A good concordance was observed between the two methods. The reproducibility of the automated method was slightly better than the manual counting of positive nuclei. Measurement of MIB-1 positive surface area may be used as a simple and fast alternative to tedious manual counting of positive nuclei as a potential help in follicular lymphoma grading.     

High Reproducibility of Histological Characterization by Whole Virtual Slide Quantification; An Example Using Carotid Plaque Specimens

Objective

Tissue biobanks are an important source for discovery and validation studies aiming for new proteins that are causally related with disease development. There is an increasing demand for accurate and reproducible histological characterization, especially for subsequent analysis and interpretation of data in association studies. We assessed reproducibility of one semiquantative and two quantitative methods for histological tissue characterization. We introduce a new automated method for whole digital slide quantification. Carotid atherosclerotic plaques were used to test reproducibility.

Methods

50 atherosclerotic plaques that were obtained during carotid endarterectomy were analysed. For the semiquantitative analysis, 6 different plaque characteristics were scored in categories by two independent observers, and Cohen''s κ was used to test intra- and interobserver reproducibility. The computer-aided method (assessed by two independent observers) and automated method were tested on CD68 (for macrophages) and α smooth muscle actin (for smooth muscle cells) stainings. Agreement for these two methods (done on a continuous scale) was assessed by intraclass correlation coefficients (ICCs).

Results

For the semiquantitative analysis, κ values ranged from 0.55 to 0.69 for interobserver variability, and were slightly higher for intraobserver reproducibility in both observers. The computer-aided method yielded intra- and interobserver ICCs between 0.6 and 0.9. The new automated method performed most optimal regarding reproducibility, with ICCs ranging from 0.92 to 0.97.

Conclusions

The analysis of performance of three methods for histological slide characterization on carotid atherosclerotic plaques showed high precision and agreement in repeated measurements for the automated method for whole digital slide quantification. We suggest that this method can fulfill the need for reproducible histological quantification.     

Conventional xylene and xylene-free methods for routine histopathological preparation of tissue sections

Abstract

Xylene customarily has been used as a clearing agent for routine tissue processing. Because xylene is a relatively hazardous solvent, laboratories are under pressure to seek less toxic alternatives for routine use. We prepared 30 paired soft tissue specimens for routine histopathological evaluation using conventional xylene and xylene-free methods to evaluate and compare their efficacy for fixation, processing, embedding, staining and turnaround time. All specimens were measured before and after processing. Three pathologists evaluated and scored the histological sections. Tissue shrinkage was greater when using the xylene method compared to the xylene-free method. The quality of tissue sections including tissue architecture; quality of staining; preservation of epithelial, fibrous, glandular, muscle and adipose tissue; inflammatory cells; and vascular tissue was better after using the xylene method, but differences were not statistically significant. Xylene-free method produced adequate results that nearly equaled the xylene method. Added advantages included cost effectiveness, better working atmosphere and decreased toxicity.     

Automated neurite labeling and analysis in fluorescence microscopy images.

BACKGROUND: To investigate the intricate nervous processes involved in many biological activities by computerized image analysis, accurate and reproducible labeling and measurement of neurites are prerequisite. We have developed an automated neurite analysis method to assist this task. METHODS: Our approach can be considered as automated with certain user interaction in setting initial parameters. Single and connected centerlines along neurites are extracted. The computerized method can also generate branching and end points. Owing to its multi-scale flexibility, both thick and thin neurites are simultaneously detected. RESULTS: We employ the relative neurite length difference (defined as the difference between the lengths obtained by automated and manual analysis divided by the total length of the latter) and neurite centerline deviation (defined as the area of the regions enclosed by different paths between automated and manual analysis divided by the total length of the former) to evaluate the performance of our algorithm, which is of great interest in neurite analysis. The average of the relative length difference is about 0.02, while the average of the centerline deviation is about 2.8 pixels. The probabilities of the distributions being the same from the Kolmogorov-Smirnov (KS) test of the automatic and manual results are 99.79%. The KS test also shows no significant bias between different observers based on the proposed new validation scheme. CONCLUSIONS: With the accurate and automated extraction of neurite centerlines and measurement of neurite lengths, the proposed method, which greatly reduces human labor and improves efficiency, can serve as a candidate tool for large-scale neurite analysis beyond the capability of manual tracing methods.     

Proteomic 2DE database for spot selection,automated annotation,and data analysis

We present a software solution that enables faster and more accurate data analysis of 2DE/MALDI TOF MS data. The software supports data analysis through a number of automated data selection functions and advanced graphical tools. Once protein identities are determined using MALDI TOF MS, automated data retrieval from online databases provides biological information. The software, called 2DDB, reduces analysis time to a fraction without losing any quality compared to more manual data analysis. The database contains over 100,000 data entries, and selected parts can be reached at http://2ddb.org.     

Automatic identification and quantitative morphometry of unstained spinal nerve using molecular hyperspectral imaging technology

Quantitative observation of nerve fiber sections is often complemented by morphological analysis in both research and clinical condition. However, existing manual or semi-automated methods are tedious and labour intensive, fully automated morphometry methods are complicated as the information of color or gray images captured by traditional microscopy is limited. Moreover, most of the methods are time-consuming as the nerve sections need to be stained with some reagents before observation. To overcome these shortcomings, a molecular hyperspectral imaging system is developed and used to observe the spinal nerve sections. The molecular hyperspectral images contain both the structural and biochemical information of spinal nerve sections which is very useful for automatic identification and quantitative morphological analysis of nerve fibers. This characteristic makes it possible for researchers to observe the unstained spinal nerve and live cells in their native environment. To evaluate the performance of the new method, the molecular hyperspectral images were captured and the improved spectral angle mapper algorithm was proposed and used to segment the myelin contours. Then the morphological parameters such as myelin thickness and myelin area were calculated and evaluated. With these morphological parameters, the three dimension surface view images were drawn to help the investigators observe spinal nerve at different angles. The experiment results show that the hyperspectral based method has the potential to identify the spinal nerve more accurate than the traditional method as the new method contains both the spectral and spatial information of nerve sections.     

A novel method for embedding neonatal murine calvaria in methyl methacrylate suitable for visualizing mineralization, cellular and structural detail

The study of undecalcified bone by histological methods is essential in the field of bone research. Culturing skeletal tissues such as neonatal murine calvaria provides a reliable bridge between assessment of bone formation in vitro and anabolic activity in vivo and contains most of the essential elements of bone for studying bone formation. Neonatal calvarial assay, supported by histological methods, is used to study the anabolic effects of a wide variety of factors and compounds on bone tissue. To optimize visualization and histomorphometric measurements using neonatal calvaria, we developed a method that provides high quality tissue sections suitable for routine and histochemical staining. Undecalcified neonatal mouse calvaria were processed and embedded using a low temperature methyl methacrylate procedure. Various staining methods were performed on deplastisized and floated sections to examine mineralization and to identify cells. The Von Kossa stain counterstained with a modified H & E yielded precise images of unmineralized bone including mineralization sites, and distinct osteoblasts and osteoclasts. Toluidine blue, Ladewig's trichrome, tartrate-resistant acid phosphatase, Goldner, H & E and Villanueva stains also were tested on the undecalcified neonatal calvaria sections.     

A novel method for embedding neonatal murine calvaria in methyl methacrylate suitable for visualizing mineralization,cellular and structural detail

The study of undecalcified bone by histological methods is essential in the field of bone research. Culturing skeletal tissues such as neonatal murine calvaria provides a reliable bridge between assessment of bone formation in vitro and anabolic activity in vivo and contains most of the essential elements of bone for studying bone formation. Neonatal calvarial assay, supported by histological methods, is used to study the anabolic effects of a wide variety of factors and compounds on bone tissue. To optimize visualization and histomorphometric measurements using neonatal calvaria, we developed a method that provides high quality tissue sections suitable for routine and histochemical staining. Undecalcified neonatal mouse calvaria were processed and embedded using a low temperature methyl methacrylate procedure. Various staining methods were performed on deplastisized and floated sections to examine mineralization and to identify cells. The Von Kossa stain counterstained with a modified H & E yielded precise images of unmineralized bone including mineralization sites, and distinct osteoblasts and osteoclasts. Toluidine blue, Ladewig's trichrome, tartrate-resistant acid phosphatase, Goldner, H & E and Villanueva stains also were tested on the undecalcified neonatal calvaria sections.     

A novel method for embedding neonatal murine calvaria in methyl methacrylate suitable for visualizing mineralization, cellular and structural detail.

The study of undecalcified bone by histological methods is essential in the field of bone research. Culturing skeletal tissues such as neonatal murine calvaria provides a reliable bridge between assessment of bone formation in vitro and anabolic activity in vivo and contains most of the essential elements of bone for studying bone formation. Neonatal calvarial assay, supported by histological methods, is used to study the anabolic effects of a wide variety of factors and compounds on bone tissue. To optimize visualization and histomorphometric measurements using neonatal calvaria, we developed a method that provides high quality tissue sections suitable for routine and histochemical staining. Undecalcified neonatal mouse calvaria were processed and embedded using a low temperature methyl methacrylate procedure. Various staining methods were performed on deplastisized and floated sections to examine mineralization and to identify cells. The Von Kossa stain counterstained with a modified H & E yielded precise images of unmineralized bone including mineralization sites, and distinct osteoblasts and osteoclasts. Toluidine blue, Ladewig's trichrome, tartrate-resistant acid phosphatase, Goldner, H & E and Villanueva stains also were tested on the undecalcified neonatal calvaria sections.     

Automatic identification and quantitative morphometry of unstained spinal nerve using molecular hyperspectral imaging technology

Quantitative observation of nerve fiber sections is often complemented by morphological analysis in both research and clinical condition. However, existing manual or semi-automated methods are tedious and labour intensive, fully automated morphometry methods are complicated as the information of color or gray images captured by traditional microscopy is limited. Moreover, most of the methods are time-consuming as the nerve sections need to be stained with some reagents before observation. To overcome these shortcomings, a molecular hyperspectral imaging system is developed and used to observe the spinal nerve sections. The molecular hyperspectral images contain both the structural and biochemical information of spinal nerve sections which is very useful for automatic identification and quantitative morphological analysis of nerve fibers. This characteristic makes it possible for researchers to observe the unstained spinal nerve and live cells in their native environment. To evaluate the performance of the new method, the molecular hyperspectral images were captured and the improved spectral angle mapper algorithm was proposed and used to segment the myelin contours. Then the morphological parameters such as myelin thickness and myelin area were calculated and evaluated. With these morphological parameters, the three dimension surface view images were drawn to help the investigators observe spinal nerve at different angles. The experiment results show that the hyperspectral based method has the potential to identify the spinal nerve more accurate than the traditional method as the new method contains both the spectral and spatial information of nerve sections.