Automated image analysis of nuclear atypia in high-power field histopathological image

2015 ◽  
Vol 258 (3) ◽  
pp. 233-240 ◽  
Author(s):  
CHENG LU ◽  
MENGYAO JI ◽  
ZHEN MA ◽  
MRINAL MANDAL
Keyword(s):  
Image Analysis ◽  
High Power ◽  
Automated Image Analysis ◽  
High Power Field ◽  
Nuclear Atypia ◽  
Histopathological Image

Clinical Measurement of Prognostic Immune Signature in Follicular Lymphoma by RT-PCR Based Gene Expression Profiling and Immunohistochemistry Demonstrates Favourable T-Cell and Unfavorable Macrophage Infiltration.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 359-359
Author(s):  
Richard J. Byers ◽  
Ebrahim Sakhinia ◽  
Preethi Joseph ◽  
Caroline Glennie ◽  
Sara McDermott ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Image Analysis ◽  
Real Time ◽  
High Power ◽  
Real Time Pcr ◽  
High Power Field ◽  
Gene Signatures ◽  
Expression Levels ◽  
Survival Interval

Abstract Gene expression profiling studies have demonstrated immune response gene signatures predictive of outcome in follicular lymphoma (FL) and there is a need for validation of these signatures and for their translation to clinical use. However, measurement of these genes in routine practice remains difficult and to date there have been very few studies validating the hypothesis. We have previously demonstrated the utility of real-time PCR measurement of gene expression levels in globally amplified polyA cDNA as a clinically practical method for translation of gene signatures to clinical use. In this project we extended the method to analysis of immune response signatures in FL. We used real-time PCR to measure expression levels (normalised to the mean of 4 housekeeping genes) of 36 candidate Indicator genes, selected from microarray studies, in polyA cDNAs prepared using polyA PCR (method detailed in Sakhinia et al 2007) from 58 archived human frozen lymph nodes, together with immunohistochemistry for CD3, CD4, CD7, CD8, CD10, CD20, CD21 and CD68 in parallel formalin fixed paraffin embedded tissue samples to measure immune response in FL. Immunohistochemical positivity was measured by a semi-automated image analysis method using spectral unmixing to identify areas of immunopositivity. Kaplan-Mier survival analysis was performed against the normalised real-time PCR expression levels of each of the genes and against the percentage immunohistochemical postivity for CD3, CD4, CD7, CD8, CD10, CD20, CD21; for CD68 survival analysis was performed for cases with either 15 or less or more than 15 CD68 positive cells per high power field (hpf). High levels of CCR1, a marker of monocyte actication, were associated with a shorter survival interval (p<0.02) (figure 1a), whilst immunohistochemistry demonstrated association of high numbers of CD7 positive T-cells with longer survival interval (figure 1b) (p<0.032) and of high numbers of CD68 positive macrophages with a shorter survival interval (figure 1c) (p<0.02). The results confirm the role of the host immune response in outcome in FL and identify CCR1 as a prognostic indicator and marker of immune switch between macrophage and T-cell dominant response. The methods used are clinically applicable, whilst the clinical utility of polyA DNA and real-time PCR for measurement of gene signatures and the strength of this approach as a “molecular block” are confirmed. Kaplan-Meier Survival Plots for upper (3&4) and lower (1&2) quartiles of a) CCR1 expression and b) number of CD7 +ve cells, and c) cases with less then vs greater than or equal to 15 macrophages per high power field CCR1 measured by real-time PCR and CD7 and macrophage numbers by immunohistochemistry and image analysis Kaplan-Meier Survival Plots for upper (3&4) and lower (1&2) quartiles of a) CCR1 expression and b) number of CD7 +ve cells, and c) cases with less then vs greater than or equal to 15 macrophages per high power field CCR1 measured by real-time PCR and CD7 and macrophage numbers by immunohistochemistry and image analysis

scholarly journals Computational Image Analysis Identifies Histopathological Image Features Associated With Somatic Mutations and Patient Survival in Gastric Adenocarcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Jun Cheng ◽  
Yuting Liu ◽  
Wei Huang ◽  
Wenhui Hong ◽  
Lingling Wang ◽  
...  
Keyword(s):  
Image Analysis ◽  
High Risk ◽  
Gastric Adenocarcinoma ◽  
Prognostic Model ◽  
Somatic Mutations ◽  
Patient Survival ◽  
Risk Index ◽  
Image Features ◽  
Automated Image Analysis ◽  
Histopathological Image

Computational analysis of histopathological images can identify sub-visual objective image features that may not be visually distinguishable by human eyes, and hence provides better modeling of disease phenotypes. This study aims to investigate whether specific image features are associated with somatic mutations and patient survival in gastric adenocarcinoma (sample size = 310). An automated image analysis pipeline was developed to extract quantitative morphological features from H&amp;E stained whole-slide images. We found that four frequently somatically mutated genes (TP53, ARID1A, OBSCN, and PIK3CA) were significantly associated with tumor morphological changes. A prognostic model built on the image features significantly stratified patients into low-risk and high-risk groups (log-rank test p-value = 2.6e-4). Multivariable Cox regression showed the model predicted risk index was an additional prognostic factor besides tumor grade and stage. Gene ontology enrichment analysis showed that the genes whose expressions mostly correlated with the contributing features in the prognostic model were enriched on biological processes such as cell cycle and muscle contraction. These results demonstrate that histopathological image features can reflect underlying somatic mutations and identify high-risk patients that may benefit from more precise treatment regimens. Both the image features and pipeline are highly interpretable to enable translational applications.

scholarly journals Computerized Calculation of Mitotic Count Distribution in Canine Cutaneous Mast Cell Tumor Sections: Mitotic Count Is Area Dependent

2019 ◽  
Vol 57 (2) ◽  
pp. 214-226 ◽  
Author(s):  
Christof A. Bertram ◽  
Marc Aubreville ◽  
Corinne Gurtner ◽  
Alexander Bartel ◽  
Sarah M. Corner ◽  
...  
Keyword(s):  
Mast Cell ◽  
High Power ◽  
Ground Truth ◽  
Mitotic Count ◽  
Automated Image Analysis ◽  
High Power Field ◽  
Borderline Cases ◽  
Area Selection ◽  
Cutaneous Mast Cell ◽  
Mitotic Figures

Mitotic count (MC) is an important element for grading canine cutaneous mast cell tumors (ccMCTs) and is determined in 10 consecutive high-power fields with the highest mitotic activity. However, there is variability in area selection between pathologists. In this study, the MC distribution and the effect of area selection on the MC were analyzed in ccMCTs. Two pathologists independently annotated all mitotic figures in whole-slide images of 28 ccMCTs (ground truth). Automated image analysis was used to examine the ground truth distribution of the MC throughout the tumor section area, which was compared with the manual MCs of 11 pathologists. Computerized analysis demonstrated high variability of the MC within different tumor areas. There were 6 MCTs with consistently low MCs (MC<7 in all tumor areas), 13 cases with mostly high MCs (MC ≥7 in ≥75% of 10 high-power field areas), and 9 borderline cases with variable MCs around 7, which is a cutoff value for ccMCT grading. There was inconsistency among pathologists in identifying the areas with the highest density of mitotic figures throughout the 3 ccMCT groups; only 51.9% of the counts were consistent with the highest 25% of the ground truth MC distribution. Regardless, there was substantial agreement between pathologists in detecting tumors with MC ≥7. Falsely low MCs below 7 mainly occurred in 4 of 9 borderline cases that had very few ground truth areas with MC ≥7. The findings of this study highlight the need to further standardize how to select the region of the tumor in which to determine the MC.

Automated Image Analysis Of Nuclear And Cytoplasmic Changes In Exfoliated Cells From Tracheas Treated With Carcinogen

1977 ◽  
Vol 35 ◽  
pp. 220-221
Author(s):  
S.F. Stinson ◽  
J.C. Lilga ◽  
M.B. Sporn
Keyword(s):  
Image Analysis ◽  
Pattern Analysis ◽  
Relative Proportion ◽  
Automated Image Analysis ◽  
Image Analyzer ◽  
Cross Sectional ◽  
Exfoliated Cells ◽  
Neoplastic Lesions ◽  
Analysis System ◽  
Morphologic Criterion

Increased nuclear size, resulting in an increase in the relative proportion of nuclear to cytoplasmic sizes, is an important morphologic criterion for the evaluation of neoplastic and pre-neoplastic cells. This paper describes investigations into the suitability of automated image analysis for quantitating changes in nuclear and cytoplasmic cross-sectional areas in exfoliated cells from tracheas treated with carcinogen.Neoplastic and pre-neoplastic lesions were induced in the tracheas of Syrian hamsters with the carcinogen N-methyl-N-nitrosourea. Cytology samples were collected intra-tracheally with a specially designed catheter (1) and stained by a modified Papanicolaou technique. Three cytology specimens were selected from animals with normal tracheas, 3 from animals with dysplastic changes, and 3 from animals with epidermoid carcinoma. One hundred randomly selected cells on each slide were analyzed with a Bausch and Lomb Pattern Analysis System automated image analyzer.

Progress In The Practical Application Of Automated Image Analysis To Tem Negatives

1977 ◽  
Vol 35 ◽  
pp. 214-217
Author(s):  
F. A. Heckman ◽  
E. Redman ◽  
J.E. Connolly
Keyword(s):  
Image Analysis ◽  
Image Quality ◽  
Exposure Time ◽  
Image Contrast ◽  
Automated Image Analysis ◽  
Practical Application ◽  
Factors Affecting ◽  
High Image Quality ◽  
Qualitative Evidence ◽  
Comprehensive Study

In our initial publication on this subject1) we reported results demonstrating that contrast is the most important factor in producing the high image quality required for reliable image analysis. We also listed the factors which enhance contrast in order of the experimentally determined magnitude of their effect. The two most powerful factors affecting image contrast attainable with sheet film are beam intensity and KV. At that time we had only qualitative evidence for the ranking of enhancing factors. Later we carried out the densitometric measurements which led to the results outlined below.Meaningful evaluations of the cause-effect relationships among the considerable number of variables in preparing EM negatives depend on doing things in a systematic way, varying only one parameter at a time. Unless otherwise noted, we adhered to the following procedure evolved during our comprehensive study:Philips EM-300; 30μ objective aperature; magnification 7000- 12000X, exposure time 1 second, anti-contamination device operating.

Interfacing of a TEM/STEM System to a Computer

1981 ◽  
Vol 39 ◽  
pp. 250-251
Author(s):  
P. Hagemann
Keyword(s):  
Image Analysis ◽  
Transmission Rate ◽  
Analytical Electron Microscopy ◽  
Signal Beam ◽  
Automated Image Analysis ◽  
Beam Deflection ◽  
External Control ◽  
Computer Input ◽  
Instrument Control ◽  
Data Acquisition And Processing

The use of computers in the analytical electron microscopy today shows three different trends (1) automated image analysis with dedicated computer systems, (2) instrument control by microprocessors and (3) data acquisition and processing e.g. X-ray or EEL Spectroscopy.While image analysis in the T.E.M. usually needs a television chain to get a sequential transmission suitable as computer input, the STEM system already has this necessary facility. For the EM400T-STEM system therefore an interface was developed, that allows external control of the beam deflection in TEM as well as the control of the STEM probe and video signal/beam brightness on the STEM screen.The interface sends and receives analogue signals so that the transmission rate is determined by the convertors in the actual computer periphery.

scholarly journals Author Correction: Efficient microbial colony growth dynamics quantification with ColTapp, an automated image analysis application

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Julian Bär ◽  
Mathilde Boumasmoud ◽  
Roger D. Kouyos ◽  
Annelies S. Zinkernagel ◽  
Clément Vulin
Keyword(s):  
Image Analysis ◽  
Growth Dynamics ◽  
Colony Growth ◽  
Automated Image Analysis ◽  
Analysis Application

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

scholarly journals Scoring of radiation-induced microuclei in cytokinesis-blocked human lymphocytes by automated image analysis

Cytometry ◽  
1994 ◽  
Vol 17 (2) ◽  
pp. 119-127 ◽  
Author(s):  
F. Verhaegen ◽  
A. Vral ◽  
J. Seuntjens ◽  
N. W. Schipper ◽  
L. de Ridder ◽  
...  
Keyword(s):  
Image Analysis ◽  
Human Lymphocytes ◽  
Automated Image Analysis ◽  
Radiation Induced

An automated image analysis platform for the study of weakly -adhered cells

Biofouling ◽  
2021 ◽  
pp. 1-10
Author(s):  
Zhijing Wan ◽  
Ben T. MacVicar ◽  
Shea Wyatt ◽  
Diana E. Varela ◽  
Rajkumar Padmawar ◽  
...  
Keyword(s):  
Image Analysis ◽  
Automated Image Analysis ◽  
Analysis Platform
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