Computer-assisted Image Analysis Method Research Articles

Image analysis-based quantification of fungal sporulation by automatic conidia counting and gray value correlation

The present work describes a new computer-assisted image analysis method for the rapid, simple, objective and reproducible quantification of actively discharged fungal spores which can serve as a manual for laboratories working in this context. The method can be used with conventional laboratory equipment by using bright field microscopes, standard scanners and the open-source software ImageJ. Compared to other conidia quantification methods by computer-assisted image analysis, the presented method bears a higher potential to be applied for large-scale sample quantities. The key to make quantification faster is the calculation of the linear relationship between the gray value and the automatically counted number of conidia that has only to be performed once in the beginning of analysis. Afterwards, the gray value is used as single parameter for quantification. The fast, easy and objective determination of sporulation capacity enables facilitated quality control of fungal formulations designed for biological pest control.•Rapid, simple, objective and reproducible quantification of fungal sporulation suitable for large-scale sample quantities.•Requires conventional laboratory equipment and open-source software without technical or computational expertise.•The number of automatically counted conidia can be correlated with the gray value and after initial calculation of a linear fit, the gray value can be applied as single quantification parameter.

Automated quantification of Ki-67 index associates with pathologic grade of pulmonary neuroendocrine tumors.

Background:Classification of the pulmonary neuroendocrine tumor (pNET) categories is a step-wise process identified by the presence of necrosis and number of mitoses per 2 mm2. In neuroendocrine tumor pathology, Ki-67 was first described as a prognostic factor in the pancreas and incorporated into the grading system of digestive tract neuroendocrine neoplasms in the 2010 WHO classification. However, the significance of Ki-67 in pNETs was still a controversial issue. This study was to investigate the potentially diagnostic value of Ki-67 in pNETs.Methods:We retrieved 159 surgical specimens of pNETs, including 35 typical carcinoids (TCs), 2 atypical carcinoid (ACs), 28 large-cell neuroendocrine carcinomas (LCNECs), 94 small-cell lung cancers (SCLCs). Manual conventional method (MCM) and computer-assisted image analysis method (CIAM) were used to calculate the Ki-67 proliferative index. In CIAM, 6 equivalent fields (500 × 500 μm) at 10× magnification were manually annotated for digital image analysis.Results:The Ki-67 index among the 4 groups with ranges of 0.38% to 12.66% for TC, 4.34% to 29.48% for AC, 30.67% to 93.74% for LCNEC, and 40.71% to 96.87% for SCLC. The cutoff value of Ki-67 index to distinguish low grade with high grade was 30.07%. For the univariate survival analyses in pNETs, both the overall survival and progression-free survival correlated with Ki-67 index. In addition, the Ki-67 index performed by CIAM was proved to be of great positive correlation with MCM.Conclusions:Ki-67 index counted by CIAM is a reliable method and can be a useful adjunct to classify the low- and high-grade NETs.

MORPHOMETRY OF FEMORAL NECK SHAFT ANGLE IN DRY FEMORA OF SOUTH INDIA BY COMPUTER ASSISTED IMAGE ANALYSIS METHOD

MORPHOMETRY OF FEMORAL NECK SHAFT ANGLE IN DRY FEMORA OF SOUTH INDIA BY COMPUTER ASSISTED IMAGE ANALYSIS METHOD

Usefulness of Ki-67, Mitoses, and Tumor Size for Predicting Metastasis in Carcinoid Tumors of the Lung: A Study of 48 Cases at a Tertiary Care Centre in Canada.

Background. Evaluation of Ki-67 index in lung carcinoid tumors (LCTs) has been of interest in order to identify high risk subsets. Our objectives are (1) to evaluate the usefulness of Ki-67 index, mitoses, and tumor size in predicting metastasis and (2) to compare the Manual Conventional Method (MCM) and the Computer Assisted Image Analysis Method (CIAM) for Ki-67 calculation. Methods. We studied 48 patients with LCTs from two academic centres in Canada. For Ki-67 calculation, digital images of 5000 cells were counted using an image processing software and 2000 cells by MCM. Mitoses/10 HPF was counted. Results. We had 37 typical carcinoids (TCs) and 11 atypical carcinoids (ACs). 7/48 patients developed metastasis. There was a positive relationship between metastasis and carcinoid type (P = 0.039) and metastasis and mitoses (≥2) (P = 0.017). Although not statistically significant, the mean Ki-67 index for ACs was higher than for TCs (0.95% versus 0.72%, CIAM, P = 0.299). Similarly, although not statistically significant, the mean Ki-67 index for metastatic group (MG) was higher than for nonmetastatic group (NMG) (1.01% versus 0.71% by CIAM, P = 0.281). However when Ki-67 index data was categorized at various levels, there is suggestion of a useful cutoff (≥0.50%) to predict metastasis (P = 0.106, CIAM). A significantly higher proportion of patients with mitosis ≥2 and Ki-67 index ≥0.50% had metastasis (P = 0.033) compared to other patients. Similarly patients with tumor size ≥3 cm and Ki-67 ≥0.50% had a greater percentage of metastases than others (P = 0.039). Although there was a strong correlation between two (MCM versus CIAM) counting methods (r = 0.929, P = 0.001), overall the calculated Ki-67 index was slightly higher by MCM (range 0 to 6.4, mean 1.5) compared to CIAM (range 0 to 2.9, mean 0.75). Conclusion. This study confirms that mitoses ≥2 is a powerful predictor of metastasis in LCTs. Although this is a small sample size, there is suggestion that analysis of Ki-67 index along with mitoses and tumor size may be a useful adjunct for predicting metastasis in LCTs.

Beta-catenin and E-cadherin tissue “content” as prognostic markers in left-side colorectal cancer

To investigate the relationship between beta-catenin and E-cadherin tissue quantitative expression (content) in tumors and clinical prognostic factors in patients with left colon cancer. Twenty nine patients with colon adenocarcinoma located distal to the splenic flexure were studied. Diagnosis and histological variables related to adenocarcinoma prognosis were evaluated using hematoxylin-eosin. Beta-catenin and E-cadherin were analysed by immunohistochemistry with specific anti-beta-catenin and anti-E-cadherin monoclonal antibodies. Tissue quantitative expression (content) was determined by computer assisted image analysis method. Results were analysed with statistical tests, adopting a significance level of 5%. There are correlations between beta-catenin and TNM stage (p< 0.01). There are progressively greater amounts of beta-catenin in patients with deeper invasion of the tumor in colon layers (p=0.03), progressive lymph node involvement (p=0.05), as well as in patients with distant metastasis (p=0.04). Worse histological grades are related to lower expression of E-cadherin in tumor tissue (p=0.01). E-cadherin can be used as an indicator of tumor differentiation degree, whereas beta-catenin can be used as a predictor of invasion depth and spread of distal colorectal cancer.

Computerized Histologic Image-Based Risk Score (IbRiS) Classifier for ER+ Breast Cancer.

Abstract Background: Measurement of estrogen receptor (ER) expression is a routine part of clinical evaluation of individual breast cancers and is used to guide treatment. However not all ER+ breast cancers show equal benefit from hormonal or other treatment. The RT-PCR based Oncotype Dx assay, has been recently shown to robustly stratify early stage ER+ breast cancer and identify those tumors that will have low recurrence rates when treated with adjuvant hormonal therapy alone. Interestingly, standard pathologic grading, based on visual analysis of tumor morphology by trained pathologists, has a strong correlation with Oncotype Dx recurrence scores; low recurrence tumors are mostly low grade, and high recurrence tumors are mostly high grade. However, a major problem with use of pathologist-assigned histologic grade as a prognostic tool is the lack of reproducibility of histological grading between different pathologists. Computer aided image analysis and machine learning techniques offer a way to obtain highly reproducible image-based classification of ER+ breast cancer. These analyses can be performed on digital images of routinely obtained breast cancer histology and be incorporated into a prognostic assay.Materials and Methods: High resolution digital images were obtained for a series of ER+ breast cancers for which associated Oncotype Dx Assay results were available. Regions of invasive breast cancer were identified and then processed by computer-assisted image analysis methods. An automated nuclear detection scheme based on Expectation Maximization algorithm was used to identify cancer cell nuclei, followed by graph-based feature extraction using the Voronoi graph, Delaunay Triangulation and Minimum Spanning Trees, and dimensionality reduction using Graph Embedding with Support Vector Machine based classification. The final manifold generated by GE was unwrapped into a linear space and a Euclidean distance metric was used to generate a single score (Image Based Risk Score- (IbRiS)) for each sample. Correlations between IbRS, clinical features such as grade, and Oncotype Dx Recurrance Score were determined.Results: Unsupervised analysis of image-based features of high resolution digital images of ER+ breast cancer histology leads to natural separation of tumors, with low grade tumors separating from high grade tumors. There is also a robust separation of tumors with high Oncotype Dx Recurrance Scores from tumors with low Recurrance Scores.Discussion: Unsupervised analysis of high resolution image-based features can stratify ER+ breast cancers in a fashion that correlates well with a gene-expression based prognostic assay, Oncotype Dx. These data suggest that tumors with distinct gene-expression profiles also have distinct image-based features that can be measured by computer-aided image analysis and used to build prognostic and predictive assays. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 3046.

Decrease of parafollicular thyroid C-cells in experimental esophageal atresia: further evidence of a neural crest pathogenic pathway

Adriamycin-induced experimental esophageal atresia (EA) is often associated with malformations of neural crest (NC) origin, such as abnormal pharyngeal pouch derivatives like the thymus and the parathyroids. The aim of the present study was to examine whether NC-derived thyroid C-cells were abnormal in a rat model. Pregnant rats received intraperitoneally either 2 mg/kg Adriamycin (EA) or vehicle (controls) on days 8 and 9 of gestation. Fetuses were recovered on day 21, and blocks including the trachea and thyroid were fixed in formalin, coronally sectioned at 3-mum widths, and stained with standard hematoxylin and eosin until the largest area of thyroid was reached. From this point on, the 1st, 10th, and 20th slices were immunohistochemically stained with anti-calcitonin antibody. Positively-stained cells in each section of the gland were counted using a computer-assisted image analysis method, and the results were averaged. The distribution of the cells within the gland was assessed as well. Comparisons between EA and control rats were made by nonparametric tests with a significance threshold of p<0.05. The number of C-cells was dramatically reduced in EA animals compared with controls (32.4+/-36 vs. 92.3+/-60.5, p<0.001). Histology of the thyroid was similar in both groups, but the distribution of positive C-cells within the gland followed an abnormal pattern in EA rats. Adriamycin causes a pattern of NC-derived malformations, including a severe decrease in thyroid C-cells accompanied by abnormal distribution or migration patterns. These results represent further evidence of the involvement of NC organogenic control dysregulation in the pathogenesis of EA and its associated malformations. The similarities between the rat model and the clinical picture strongly support investigating other subclinical NC-derived anomalies in patients with EA.

Magnetic age hardening of cold-deformed bulk equiatomic Fe–Pd intermetallics during isothermal annealing

The interplay between the ordering reaction with recovery and recrystallization of the as-deformed state leads to combined reactions (CRs) during annealing of cold-deformed disordered Fe–Pd intermetallics at temperatures below the critical ordering temperature. CRs can be exploited to control the scale and morphology of the Fe–Pd alloy microstructures in order to optimize alloy properties. Here, the magnetic age hardening behavior and microstructural evolution of cold-deformed (cold rolled to 97% reduction in thickness) binary equiatomic Fe–Pd has been studied for isothermal annealing at temperatures of 400°C, 500°C, and 600°C. The evolution of the microstructure during the annealing treatments has been characterized by a combination of X-ray diffraction (XRD) and scanning electron microscopy (SEM). The magnetic age hardening behavior, the evolution of the coercivity as a function of annealing time, has been determined using a vibrating sample magnetometer (VSM). The microstructures of the transforming material have been characterized quantitatively using computer assisted image analysis methods. The CR transformed microstructures are morphologically equiaxed with average grain sizes in the sub-micron range and show coercivity up to five-fold larger than for conventionally processed equiatomic bulk Fe–Pd. During annealing the coercivity increases up to a maximum peak value and has been correlated with the increasing fraction of ordered material. The maximum coercivity obtains, as the ordering phase transformation is complete. With respect to conventionally processed material the ordering transformation in the cold-deformed material exhibits accelerated kinetics and is facilitated by a CR, which involves heterogeneous nucleation and growth processes akin to a ‘massive ordering’ reaction. Further annealing leads to decreasing coercivity, which has been attributed to the onset of grain growth in the population of CR-transformed grains. The characteristic magnetic age hardening response has been rationalized in terms of the microstructural observations.

Multiple Regression Models for Age Estimation by Assessment of Morphologic Dental Changes According to Teeth Source

The aims of this study were twofold: (1). to measure parameters that contribute significantly to estimates of dental age, using a combination of classic methods and a computer-assisted image analysis procedure to avoid the bias inherent in observer subjectivity; and (2). to develop new mathematical regression models for age prediction according to postmortem interval. Two different populations were studied. Forty-three permanent teeth (Group I), extracted for valid clinical reasons, were taken from patients 25-79 years of age. The other population group (Group II) was composed of 37 healthy erupted permanent teeth obtained from human skeletal remains (age 22-82 years) with a postmortem interval ranging from 21 to 37 years. Morphologic age-related changes were investigated by measuring variables on intact and half-sectioned teeth. Multiple regression analyses were performed with age as the dependent variable for each sample source. In fresh extracted teeth, the variables that made the greatest contributions to predictions of age were dental attrition, dentin color, and translucency width, the latter measured with a computer-assisted image analysis method. In teeth from human skeletal remains, the variables that made the greatest contributions to age calculation were cementum apposition, pulp length measured by computer-assisted image analysis, dental attrition, root translucency, and dental color. We conclude by recommending different regression models to calculate age depending on the postmortem interval.

Computer-assisted image analysis of neovascularization in thyroid neoplasms from dogs.

To develop a computer-assisted image analysis procedure for quantitation of neovascularization in formalin-fixed paraffin-embedded specimens of thyroid gland tissue from dogs with and without thyroid gland neoplasia. 47 thyroid gland carcinomas, 8 thyroid gland adenomas, and 8 specimens of thyroid tissue from dogs without thyroid gland abnormalities (normal). Serial tissue sections were prepared and stained with antibodies against human CD31 or factor VIII-related antigen (factor VIII-rag). The areas of highest vascularity were identified in CD31-stained sections, and corresponding areas were then identified in factor VIII-rag-stained sections. Image analysis was used to calculate the total vascular density in each section, and neovascularization, expressed as a percentage, was determined as the absolute value of the total vascular density derived from factor VIII-rag-stained sections minus the vascular density derived from CD31-stained sections. Mean vascular density of thyroid gland carcinomas derived from CD31-stained sections was significantly greater than density derived from factor VII I-rag-stained sections. This incremental difference was presumed to represent degree of neovascularization. However, significant differences were not detected between vascular densities derived from CD31 and factor VIII-rag-stained sections for either normal thyroid gland tissue or thyroid gland adenomas. No significant correlations were found between vascular density in thyroid gland carcinomas and survival time following surgery. A computer-assisted image analysis method was developed for quantifying neovascularization in thyroid gland tumors of dogs. This method may allow identification of dogs with tumors that are most likely to respond to treatment with novel antiangiogenesis agents.

Quantitative Assessment of Angiogenesis and Tumor Vessel Architecture by Computer-Assisted Digital Image Analysis: Effects of VEGF–Toxin Conjugate on Tumor Microvessel Density

Tumor growth is angiogenesis dependent. As a consequence, strategies aimed at disrupting this mechanism are heavily investigated. Several angiogenesis assays are used to directly compare the efficacy of anti-angiogenic compounds. However, objective assessment of new vascular growth has been difficult to achieve. The aim of this study was to test and develop a computer-assisted image analysis method that would give an unbiased quantification of the microvessel density. Human tumors were grown in athymic mice and tumor biopsies were taken after a weeklong treatment with VEGF–toxin conjugate. Frozen tumor sections were prepared and stained with PE-conjugated anti-CD-31 antibodies and vessels were imaged with a fluorescence microscope. Vessel density was analyzed by quantifying PE-positive pixels per recorded field. In addition, images were further processed to investigate morphological differences by an automated binarization and skeletonization protocol. This procedure allowed the computer-assisted estimation of important angiogenic parameters such as total vessel number, length, and branch points. Based on these indices, differences in the angiogenic response between control tumors and those treated with VEGF–toxin conjugate were readily detected (P < 0.007 for all parameters). More importantly, computer-generated measurements correlated well with manual microvessel counts and showed significantly less variation. Our results suggest that computer-assisted image analysis represents a rapid, objective, and alternative method for the quantitative assessment of tumor angiogenesis and vessel architecture.

Choline availability alters embryonic development of the hippocampus and septum in the rat

Choline availability in the diet during pregnancy alters fetal brain biochemistry with resulting behavioral changes that persist throughout the lifetime of the offspring. In the present study, the effects of dietary choline on cell proliferation, migration, and apoptosis in neuronal progenitor cells in the hippocampus and septum were analyzed in fetal brains at different stages of embryonic development. Timed-pregnant rats on day E12 were fed AIN-76 diet with varying levels of dietary choline for 6 days, and, on days E18 or E20, fetal brain sections were collected. We found that choline deficiency (CD) significantly decreased the rate of mitosis in the neuroepithelium adjacent to the hippocampus. An increased number of apoptotic cells were found in the region of the dentate gyrus of CD hippocampus compared to controls (5.5±0.7 vs. 1.9±0.3 apoptotic cells per section; p<0.01). Using a combination of bromodeoxyuridine (BrdU) labeling and an unbiased computer-assisted image analysis method, we found that modulation of dietary choline availability changed the distribution and migration of precursor cells born on E16 in the fimbria, primordial dentate gyrus, and Ammon's horn of the fetal hippocampus. CD also decreased the migration of newly born cells from the neuroepithelium into the lateral septum, thus indicating that the sensitivity of fetal brain to choline availability is not restricted to the hippocampus. We found an increase in the expression of TOAD-64 protein, an early neuronal differentiation marker, in the hippocampus of CD day E18 fetal brains compared to controls. These results show that dietary choline availability alters the timing of the genesis, migration, and commitment to differentiation of progenitor neuronal-type cells in fetal brain hippocampal regions known to be associated with learning and memory processes in adult brain.

Noninvasive determination of liver collagen content in chronic hepatitis. Multivariate regression modeling with blood chemical parameters as variables.

To evaluate the diagnostic utility of blood biochemical parameters in assessing degree of hepatic fibrosis, serum levels of aminoterminal type III procollagen peptide (P III P), type IV collagen (IV-collagen), 7S domain of type IV collagen (7S-collagen), and hyaluronan (HA) were measured in 54 patients with chronic viral liver disease. Liver collagen content was quantified by a computer-assisted image analysis method. Significant correlations were found between the amount of collagen in the liver and serum levels of P III P (r = 0.482; P < 0.02), IV-collagen (r = 0.705; P < 0.001), 7S-collagen (r = 0.771; P < 0.001), and HA (r = 0.595; P < 0.001). To optimize diagnostic efficacy, we applied multivariate regression analysis to the combined results obtained for these blood biochemical parameters and some additional laboratory tests. The correlation coefficient obtained from the application of this model was 0.809. To measure the predictive value of the proposed model, we used it to estimate collagen content in an additional 16 patients with chronic liver disease and compared the estimated to the actual amount of collagen determined by direct measurement. The correlation coefficient was 0.937. These results suggest that application of the model would be useful for the assessment of collagen content of fibrotic liver.

Changes of the basement membrane and type IV collagen in human skin during aging.

To determine the relationship between skin collagen IV and basement membrane changes during aging, a total of 35 women who had been admitted for surgery, were studied. Subjects were arranged into six age-groups (from 35 to 60 years). Skin biopsies were performed in all patients and the samples were taken from a site 6 cm above the pubic symphysis. The collagen IV content and the epithelial basement membrane were analyzed by using immunohistochemical, transmission electron microscopy and computer-assisted image analysis methods. The skin collagen IV content was measured by an image analysis program and expressed in arbitrary units of integrate optical density, and, the basement membrane thickness was expressed in nanometers. Type IV collagen content decreased with age after 35 years (r = -0.9561). The epithelial basement membrane thickness increased significantly with age (r = 0.98192; P < 0.01) and there is an inverse correlation between these two parameters (r = -0.990502). Although type IV collagen is a basement membrane component and declines with aging, the total thickness of this membrane increases, which suggests a reduction in tissue turnover.

Aspects of neural plasticity in the central nervous system—I. Computer-assisted image analysis methods

Microdensitometric and morphometric techniques have been developed to quantitatively characterize cell groups and terminal populations of transmitter-identified neuronal systems. Various microdensitometric methods implemented on the image analyzer or on the scanning microdensitometer were introduced and compared. On this basis a technique to assess the half-life of dopamine stores determined by quantitative immunocytochemistry has been developed. The problem of relative and absolute quantification of microdensitometric analysis of immunocytochemical preparations is discussed here. A method has been developed for the study, both in 2- and 3-dimensions, of the overall features of the profile distribution in a defined neuroanatomical area. An approach to determine the degree of uniformity of a certain profile distribution is also proposed. Furthermore, methods for the evaluation of the codistribution of two or more different types of profiles and to characterize the morphometric features of patches of profiles in a certain region are presented. All these quantitative morphological approaches were tested in relevant preparations of the central nervous system.