Canine Neuroendocrine Tumors of the Pancreas: A Study Using Image Analysis Techniques for the Discrimination of Metastatic Versus Nonmetastatic Tumors

1997 ◽  
Vol 34 (2) ◽  
pp. 138-145 ◽  
Author(s):  
G. Minkus ◽  
U. Jütting ◽  
M. Aubele ◽  
K. Rodenacker ◽  
P. Gais ◽  
...  
Keyword(s):  
Image Analysis ◽  
Neuroendocrine Tumors ◽  
Nucleolar Organizer ◽  
Biological Behavior ◽  
Proliferation Index ◽  
Nucleolar Organizer Regions ◽  
Ki 67 ◽  
Analysis Techniques ◽  
Significant Difference ◽  
Image Analysis Techniques

Canine pancreatic neuroendocrine tumors were studied using different image analysis techniques (nuclear image histometry, analysis of argyrophilic proteins of nucleolar organizer regions, determination of the mouse anti-Ki 67 antigen proliferation index, and DNA densitometry) to correlate their biological behavior with objective phenotypic markers. The methods were compared to determine the best method for distinguishing between metastatic and nonmetastatic tumors. Discrimination between the two types of tumor was possible using nuclear image histometry in combination with morphometric analysis of argyrophilic proteins of nucleolar organizer regions. In contrast, the mouse anti-Ki 67 antigen proliferation index, DNA measurement, and immunohistochemical parameters revealed no significant difference between the two types of tumors.

Comparison of Manual and Digital Assessment of KI-67 in Neuroendocrine Tumors

2020 ◽  
Vol 154 (Supplement_1) ◽  
pp. S125-S125
Author(s):  
B S Raju ◽  
M Quinton ◽  
L Hassell
Keyword(s):  
Image Analysis ◽  
Neuroendocrine Tumors ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Hot Spot ◽  
World Health ◽  
Proliferation Index ◽  
Digital Analysis ◽  
Ki 67 ◽  
Digital Assessment

Abstract Introduction/Objective Proliferative activity is an essential prognostic and treatment indicator for neuroendocrine tumors (NET). Ki-67 proliferation index, if reported by unaided microscopic estimation on hot-spot locations could lead to variability and inconsistencies. This study aims to compare the Ki-67 assessment of NETs by visual estimation versus automated digital image analysis (Roche iCoreo/Virtuoso). Methods 212 patients with Ki-67-graded GI NETs (117 G1; 61 G2; 34 G3) from 2010 to 2019 were reassessed using digital image analysis quantification of hot spot areas of at least 500 cells (average 800 cells). Revised tumor grades were assigned according to the European Neuroendocrine Tumor Society guidelines and the 2010 World Health Organization classification and compared to initially reported grade. Results We found 75% concordance for G1, with 22% of cases upgraded to G2 and 3% of cases upgraded to G3. For G2, there was 70.5% agreement, with 13.1% of cases downgraded to G1 and 16.4% upgraded to G3. For G3, there was 100% agreement, (kappa=0.64, overall). Retrospective review of discordant G3 cases revealed cases with known metastasis, small fragments of tissue, or polyps. Scanning and scoring required approximately 10 minutes per case. Conclusion Our data shows the time/effort difference of visually estimating versus automated digital analysis may lead to significant classification errors in these tumors. Although digital analysis has limitations, including tumor heterogeneity, misidentification of tumor cells, and poor immunostaining which could require manual counting by a pathologist, this rigor should be reinforced and explicitly stated to increase accuracy and reproducibility of grading.

Ki‐67 proliferation index in neuroendocrine tumors: Can augmented reality microscopy with image analysis improve scoring?

2020 ◽  
Vol 128 (8) ◽  
pp. 535-544
Author(s):  
Swati P. Satturwar ◽  
Joshua L. Pantanowitz ◽  
Christopher D. Manko ◽  
Lindsey Seigh ◽  
Sara E. Monaco ◽  
...  
Keyword(s):  
Image Analysis ◽  
Augmented Reality ◽  
Neuroendocrine Tumors ◽  
Proliferation Index ◽  
Ki 67

scholarly journals A multilabeling technique for simultaneous demonstration and quantitation of Ki-67 and nucleolar organizer regions (AgNORs) in paraffin-embedded tissue.

1994 ◽  
Vol 42 (6) ◽  
pp. 789-793 ◽  
Author(s):  
S Munakata ◽  
J B Hendricks
Keyword(s):  
Nucleolar Organizer ◽  
Staining Procedure ◽  
Nucleolar Organizer Regions ◽  
Nuclear Area ◽  
Human Tonsil ◽  
Ki 67 ◽  
Significant Difference ◽  
Agnor Staining ◽  
Tonsil Tissue ◽  
The Individual

Although many investigators have demonstrated a relationship between argyrophilic nucleolar organizer regions (AgNORs) and Ki-67 expression in solid tumors, no previous studies have simultaneously assessed the relationship between AgNOR and Ki-67 expression in paraffin-embedded tissue. We describe a method for simultaneous demonstration and quantitation of Ki-67 and AgNORs in routinely processed tissue. The Ki-67 equivalent monoclonal antibody MIB1, which can detect proliferative activity in routinely processed tissue with microwave heating, was employed. Fresh human tonsil tissue was fixed in formalin and embedded in paraffin for Ki-67/AgNOR dual staining. Image analysis was employed for quantitation of AgNOR staining in Ki-67-positive and Ki-67-negative nuclei. The double-staining procedure had no measurable effect on the individual parameters: Ki-67 labeling index, mean AgNOR number (NN), and NOR percentage nuclear area (NPNA). However, microwave processing for Ki-67 immunostaining significantly increased nuclear area (NA) and AgNOR area (AA). A significant difference was found between Ki-67-positive and Ki-67-negative cells for NN (p < 0.001), NA (p < 0.001), AA (p < 0.001), and NPNA (p < 0.001). These results suggest a direct relationship between AgNOR and Ki-67 in paraffin-embedded tissue.

A Review on Automatic Bill of Material Generation and Visual Inspection on PCBs

2019 ◽  
Author(s):  
Mukhil Azhagan M. S ◽  
Dhwani Mehta ◽  
Hangwei Lu ◽  
Sudarshan Agrawal ◽  
Mark Tehranipoor ◽  
...  
Keyword(s):  
Image Analysis ◽  
Visual Inspection ◽  
Automated System ◽  
Imaging Modalities ◽  
Future Research ◽  
Analysis Techniques ◽  
Bill Of Materials ◽  
Pros And Cons ◽  
Index Terms ◽  
Image Analysis Techniques

Abstract Globalization and complexity of the PCB supply chain has made hardware assurance a challenging task. An automated system to extract the Bill of Materials (BoM) can save time and resources during the authentication process, however, there are numerous imaging modalities and image analysis techniques that can be used to create such a system. In this paper we review different imaging modalities and their pros and cons for automatic PCB inspection. In addition, image analysis techniques commonly used for such images are reviewed in a systematic way to provide a direction for future research in this area. Index Terms—Component Detection, PCB, Authentication, Image Analysis, Machine Learning

scholarly journals Quality Evaluation of Potato Tubers Using Neural Image Analysis Method

Agriculture ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 112 ◽  
Author(s):  
Andrzej Przybylak ◽  
Radosław Kozłowski ◽  
Ewa Osuch ◽  
Andrzej Osuch ◽  
Piotr Rybacki ◽  
...  
Keyword(s):  
Image Analysis ◽  
Neural Model ◽  
Assessment Method ◽  
Analysis Method ◽  
Potato Tubers ◽  
Specialized Knowledge ◽  
Analysis Techniques ◽  
Quality Assessment Method ◽  
Sorting Process ◽  
Image Analysis Techniques

This paper describes the research aimed at developing an effective quality assessment method for potato tubers using neural image analysis techniques. Nowadays, the methods used to identify damage and diseases are time-consuming, require specialized knowledge, and often rely on subjective judgment. This study showed the use of the developed neural model as a tool supporting the evaluation of potato tubers during the sorting process in the storage room.

scholarly journals Using PhotoCube as an extensible demonstration platform for advanced image analysis techniques

2012 ◽  
Author(s):  
Grimur Tomasson ◽  
Gisli Kristjan Olafsson ◽  
Hlynur Sigurporsson ◽  
Bjorn Por Jonsson ◽  
Kristjan Runarsson ◽  
...  
Keyword(s):  
Image Analysis ◽  
Analysis Techniques ◽  
Image Analysis Techniques

Considerations for Whole-Slide Analysis of Murine Xenografts Experiments

2021 ◽  
Vol 69 (10) ◽  
pp. 627-631
Author(s):  
Abigail R. Bland ◽  
John C. Ashton
Keyword(s):  
Cell Death ◽  
Image Analysis ◽  
Cell Counting ◽  
Analysis Techniques ◽  
The Core ◽  
Necrotic Region ◽  
Areas Of Interest ◽  
Image Analysis Techniques ◽  
Immunohistochemical Analyses ◽  
Animal Models Of Cancer

Histochemistry of tumor sections is a widely employed technique utilized to examine cell death in preclinical xenograft animal models of cancer. However, this is under the assumption that tumors are homogeneous, leading to practices such as automatic cell counting across the entire section. We have noted that in our experiments the core of the tumor is largely or partially necrotic, and lacks evidence of vascularization (in contrast to the outer areas of the tumor). We note that this can bias and confound immunohistochemical analyses that do not take care to sample areas of interest in a way to take this into account. Design-based stereology with image analysis techniques is an alternative process that could be used to measure the volume of the necrotic region compared to the volume of the whole tumor.

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