Computer-assisted morphometric image analysis of cells of normal oral epithelium and oral squamous cell carcinoma

Kumar, Madhuresh; Chatterjee, Kabita; Purkait, Swapan; Samaddar, Dipankar

doi:10.4103/0973-029x.203760

Cited by 11 publications

(12 citation statements)

References 13 publications

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“…These findings correlate with our observation of increase in cellular area in the spinous cell layer compared to superficial cells. [ 17 19 , 20 ] Previous studies found that tissues undergoing malignant transformation typically showed a reduction in cellular area before showing reduction in nuclear area, using semiautomatic image analysis techniques. [ 6 17 ] Shabana et al [ 5 ] studied the shape and size of the cells in basal cell layer of the oral epithelium, and they found a progressive increase in the dimensions of nuclei from normal mucosa through traumatic keratosis, lichen planus, leukoplakia, and risk group to carcinoma, with considerable variations.…”

Section: Discussionmentioning

confidence: 99%

Morphometric analysis of suprabasal cell layer in oral epithelial dysplasia: A computer-assisted microscopic study

et al. 2020

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A BSTRACT Background: Oral leukoplakia is the most common precancerous lesion. Various grading systems based on histological findings have been proposed for dysplasia. Recently, computer-assisted morphometric analysis has been established to reduce the interobserver and intraobserver variability during the histological grading of epithelial dysplasia. This study was undertaken to establish the morphometric changes in the suprabasal cell layer of different grades of oral epithelial dysplasia. Materials and Methods: Forty paraffin-embedded tissue sections (10 normal mucosa, 10 mild dysplasia, 10 moderate dysplasia, and 10 severe dysplasia cases) were stained using hematoxylin and eosin stain, and analyzed for cellular and nuclear morphometry using binocular microscope. Results: Our results showed that values of nuclear area, nuclear perimeter, nuclear volume density, and nuclear/cytoplasmic (N/C) ratio were increased gradually in dysplasia compared to control groups and the values were statistically significant ( P = 0.001). Nuclear diameter and cellular area were increased in dysplasia when compared to control group ( P = 0.001). Mild and moderate dysplasia showed decreased value of nuclear form factor compared to control group, whereas severe dysplasia showed highest value. A fair correlation was found when comparing histological grading and grouping based on nuclear area, nuclear perimeter, N/C ratio, and nuclear volume density. Conclusion: Nuclear features reflect cell behavior, and its morphometric analysis can be considered as a reliable tool for differentiating various grades of epithelial dysplasia.

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Section: Discussionmentioning

confidence: 99%

Morphometric analysis of suprabasal cell layer in oral epithelial dysplasia: A computer-assisted microscopic study

et al. 2020

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“…In contrast, no correlation was found between the staining intensity of the nuclear area (Avg) and the NP (Avg). Kumar et al analyzed the nuclear morphological features of 30 cases of normal oral mucosa and well to moderately differentiated oral squamous cell carcinoma (SCC) by H&E staining, and found that the nuclear area and the NP of SCC were significantly larger than those of normal squamous epithelium ( 15 ). According to the data of the nuclear morphological analysis of 64 cases of breast cancer, as analyzed by cytologic smear, Kashyap et al classified cellular atypia based on Robinson's grading system.…”

Section: Discussionmentioning

confidence: 99%

Image analysis of the nuclear characteristics of emerin protein and the correlation with nuclear grooves and intranuclear cytoplasmic inclusions in lung adenocarcinoma

et al. 2018

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Nuclear size and shape are important components in the diagnosis of pathological specimens. However, a qualitative evaluation is typically applied rather than a quantitative evaluation technique. In the present study, we sought to evaluate the nuclear morphological characteristics of lung adenocarcinoma using whole-slide imaging (WSI) and computer-assisted image analysis (IA). We evaluated the nuclear characteristics of 106 cases of surgically resected lung adenocarcinoma according to Feulgen staining and immunohistochemistry (IHC) for the inner nuclear membrane protein emerin. According to the Feulgen reaction, although the nuclear area (size) of the carcinoma cells was correlated with the nuclear perimeter (NP) (R=0.8973), the nuclear staining intensity of carcinoma cells was not correlated with the nuclear area. Using emerin IHC, we used IA software that was able to detect both the NP and the emerin-stained nuclear membrane length (ENML) in the nucleus, and found that the more nuclei exhibited a longer ENML relative to the NP, the more nuclear grooves and intranuclear cytoplasmic inclusions were present. In addition, the nuclear area was correlated with the percentage of nuclei that had a longer ENML compared to the NP against the total nuclei (R=0.7759). Furthermore, the emerin low expression group showed an enlarged nuclear area (P=0.0264), elongated NP (P=0.0091), and lower shape factor (P=0.0486) compared with the normal emerin expression group. Our data indicated the usefulness of WSI and IA for pathological specimen analysis. In addition, this study is the first to report that the low expression of emerin in cancer cell results in an oval shape of nuclei and nuclear enlargement in clinical samples.

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“…Recently, the field of digital image analysis has emerged and aims to support the evaluation and annotation of microscopic images using machine learning algorithms . In particular, the morphometric analysis of cells in histological images has gained interest as it can be used for the automatic detection and classification of cells . Morphometry uses quantitative statistical models to learn about size and shape (e.g.…”

Section: Figurementioning

confidence: 99%

Morphometric Cell Classification for Single‐Cell MALDI‐Mass Spectrometry Imaging

et al. 2020

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The large‐scale and label‐free molecular characterization of single cells in their natural tissue habitat remains a major challenge in molecular biology. We present a method that integrates morphometric image analysis to delineate and classify individual cells with their single‐cell‐specific molecular profiles. This approach provides a new means to study spatial biological processes such as cancer field effects and the relationship between morphometric and molecular features.

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Computer-assisted morphometric image analysis of cells of normal oral epithelium and oral squamous cell carcinoma

Cited by 11 publications

References 13 publications

Morphometric analysis of suprabasal cell layer in oral epithelial dysplasia: A computer-assisted microscopic study

Morphometric analysis of suprabasal cell layer in oral epithelial dysplasia: A computer-assisted microscopic study

Image analysis of the nuclear characteristics of emerin protein and the correlation with nuclear grooves and intranuclear cytoplasmic inclusions in lung adenocarcinoma

Morphometric Cell Classification for Single‐Cell MALDI‐Mass Spectrometry Imaging

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