Recent Advances in Pathology: the 2022 Annual Review Issue of <i>The Journal of Pathology</i>

Herrington, C. Simon; Poulsom, Richard; Pillay, Nischalan; Bankhead, Peter; Coates, Philip J.

doi:10.1002/path.5972

Cited by 5 publications

(5 citation statements)

References 15 publications

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“…Although numerous models built by machine learning are being developed to make for easier diagnosis of lesions using multiple cellular morphometric features [14], directly utilizing the parameters may be useful to aid tissue diagnosis in special cases.…”

Section: Discussionmentioning

confidence: 99%

The Role of Cell Detection Tool of QuPath-0.3.2 Software in Differentiating Benign Cervical Epithelium from Malignant Epithelial Clusters

Olaniyi

Morakinyo

Oluwole

2023

JAMMR

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Aim: The study aims to be an initial assessment of the ability of the Qu Path software to quantitatively distinguish between benign cervical epithelium and non-keratinizing squamous cell carcinoma cell clusters. Study Design: We carried out a retrospective cross-sectional study of nineteen slides of cervical biopsies of non-keratinizing squamous cell carcinoma (NKSCC) of the cervix. Place and Duration of Study: These are from cases of cervical carcinomas seen in UniOsun Teaching Hospital, Osogbo between 1st January 2006 and 31st December 2015. Materials and Methods: These slides had been prepared by standard laboratory protocol and stained with hematoxylin and eosin. The slides were scanned using CS2 APERIO digital slide scanner with standard settings. The scanned slides were viewed using QuPath-0.3.2 software. For each normal or NKSCC cell found in the randomly sampled cluster of the biopsy, the nuclear and cytoplasmic morphometric features were analyzed using Microsoft Excel and SPSS version 20. Results: The cells in the normal clusters were 13,774 and that of the NKSCC was 26,114. There is a higher mean nuclear area in NKSCC cells compared to normal cells. The malignant cells have a higher mean nuclear area, circularity, and perimeter than cells of the benign epithelium. There was a higher nuclear hematoxylin OD (optic density) mean, hematoxylin OD max, and hematoxylin OD sum in the malignant cells. There was a higher cell eccentricity, mean cytoplasmic eosin OD, maximum eosin OD and minimum eosin OD in the malignant cells. The maximum nuclear caliper is higher in cells of NKSCC than that of benign epithelium. Conclusion: The QuPath software (version 0.3.2) can be a useful aid to differentiate non-keratinizing squamous cell carcinoma (NKSCC) from normal squamous cervical epithelium especially in fragmented biopsies.

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Section: Discussionmentioning

confidence: 99%

The Role of Cell Detection Tool of QuPath-0.3.2 Software in Differentiating Benign Cervical Epithelium from Malignant Epithelial Clusters

Olaniyi

Morakinyo

Oluwole

2023

JAMMR

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“…Our study shows some differences in the various cells of the categories of CIN. These can be eventually explored in the development of algorithms that can help to distinguish them using digital pathology [11,12].…”

Section: Discussionmentioning

confidence: 99%

“…Qu Path software is a tool that is able to objectively measure many parameters of the cell such as the size of nucleus, eccentricity of nucleus, circularity of the nucleus and size of cytoplasm. It has been used in numerous computer-aided image analysis to help to develop novel methods of tissue diagnosis in histopathology [11].…”

Section: Introductionmentioning

confidence: 99%

Morphometric Features of Cells of Cervical Intraepithelial Neoplasia Using Computer Aided Image Analysis

Olaniyi

Morakinyo

Oluwole

2023

AJMAH

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Aim: Our goal is to evaluate and compare the different cell morphometric parameters in the various categories of cervical intraepithelial neoplasia (CIN). Study Design: We conducted a cross-sectional study of all cervical intraepithelial neoplasia identified in some areas of biopsies of cervical carcinomas. Place and Duration of Study: The study was in the department of histopathology of LAUTECH Teaching Hospital, Osogbo from January 2006 to December 2015. Materials and Methods: The histologic slides produced were scanned using CS2 APERIO digital slide scanner with standard settings. The scanned slides were then viewed using Qu Path-0.3.2 software. All areas of cervical intraepithelial neoplasia were selected. The perimeter, area, maximum caliper, circularity, eccentricity, and the various measures of hematoxylin optic densities (OD) of the nucleus of the cells were measured. The cytoplasmic morphometric measurements and the nuclear-cell ratio were then estimated. Results: Two cases of CIN 1, one case of CIN 2 and one case of CIN 3 were seen in the background of the eighty-seven cases of cervical carcinomas seen during the study period. A total of 5,935 cells were in the annotated regions with cervical intraepithelial neoplasia. The cells in CIN 1 area are 3,828, CIN 2 area has 1183 cells and CIN 3 areas has 924 cells. Cells of CIN 3 had higher average nuclei hematoxylin optic density (OD), nuclei hematoxylin OD standard deviation and maximum hematoxylin OD than cells of CIN 2 and CIN 1. Cells of CIN 1 have higher average cell area, cell perimeter, cell circularity and mean cytoplasm eosin OD compared to cells of CIN 2 and 3. Conclusion: Computer-aided image analysis using Qu Path software can be very instrumental in differentiating the various categories of cervical intraepithelial neoplasia especially in fragmented biopsies.

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“…Currently, histopathological analysis is the principal method used to evaluate interactions between engineered and host tissues. [ 2 ] Despite providing critical tissue information, this method does not allow monitoring of the tissue regeneration process. Moreover, the properties of biomaterials may be altered during histological analysis, which may lead to misleading results.…”

Section: Introductionmentioning

confidence: 99%

Visualizable and Lubricating Hydrogel Microspheres Via NanoPOSS for Cartilage Regeneration

et al. 2023

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The monitoring of tissue regeneration is particularly important. However, most materials do not allow direct observation of the regeneration process in the cartilage layer. Here, using sulfhydryl polyhedral oligomeric silsesquioxane (POSS‐SH) as a nano‐construction platform, poly(ethylene glycol) (PEG), Kartogenin (KGN), hydrogenated soya phosphatidylcholine (HSPC), and fluorescein are linked through the “click chemistry” method to construct nanomaterial with fluorescence visualization for cartilage repair: POSS linked with PEG, KGN, HSPC, and fluorescein (PPKHF). PPKHF nanoparticles are encapsulated with hyaluronic acid methacryloyl to prepare PPKHF‐loaded microfluidic hyaluronic acid methacrylate spheres (MHS@PPKHF) for in situ injection into the joint cavity using microfluidic technology. MHS@PPKHF forms a buffer lubricant layer in the joint space to reduce friction between articular cartilages, while releasing encapsulated positively charged PPKHF to the deep cartilage through electromagnetic force, facilitating visualization of the location of the drug via fluorescence. Moreover, PPKHF facilitates differentiation of bone marrow mesenchymal stem cells into chondrocytes, which are located in the subchondral bone. In animal experiment, the material accelerates cartilage regeneration while allowing monitoring of cartilage layer repair progression via fluorescence signals. Thus, these POSS‐based micro–nano hydrogel microspheres can be used for cartilage regeneration and monitoring and potentially for clinical osteoarthritis therapy.

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Recent Advances in Pathology: the 2022 Annual Review Issue of The Journal of Pathology

Cited by 5 publications

References 15 publications

The Role of Cell Detection Tool of QuPath-0.3.2 Software in Differentiating Benign Cervical Epithelium from Malignant Epithelial Clusters

The Role of Cell Detection Tool of QuPath-0.3.2 Software in Differentiating Benign Cervical Epithelium from Malignant Epithelial Clusters

Morphometric Features of Cells of Cervical Intraepithelial Neoplasia Using Computer Aided Image Analysis

Visualizable and Lubricating Hydrogel Microspheres Via NanoPOSS for Cartilage Regeneration

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