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
Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 359-359
Author(s):  
Richard J. Byers ◽  
Ebrahim Sakhinia ◽  
Preethi Joseph ◽  
Caroline Glennie ◽  
Sara McDermott ◽  
...  

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


2021 ◽  
Vol 11 ◽  
Author(s):  
Jun Cheng ◽  
Yuting Liu ◽  
Wei Huang ◽  
Wenhui Hong ◽  
Lingling Wang ◽  
...  

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.


2019 ◽  
Vol 57 (2) ◽  
pp. 214-226 ◽  
Author(s):  
Christof A. Bertram ◽  
Marc Aubreville ◽  
Corinne Gurtner ◽  
Alexander Bartel ◽  
Sarah M. Corner ◽  
...  

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.


Author(s):  
S.F. Stinson ◽  
J.C. Lilga ◽  
M.B. Sporn

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.


Author(s):  
F. A. Heckman ◽  
E. Redman ◽  
J.E. Connolly

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.


Author(s):  
P. Hagemann

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.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Julian Bär ◽  
Mathilde Boumasmoud ◽  
Roger D. Kouyos ◽  
Annelies S. Zinkernagel ◽  
Clément Vulin

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


Cytometry ◽  
1994 ◽  
Vol 17 (2) ◽  
pp. 119-127 ◽  
Author(s):  
F. Verhaegen ◽  
A. Vral ◽  
J. Seuntjens ◽  
N. W. Schipper ◽  
L. de Ridder ◽  
...  

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

Sign in / Sign up

Export Citation Format

Share Document