Objective malignancy grading of squamous cell carcinoma of the lung. Stereologic estimates of mean nuclear size are of prognostic value, independent of clinical stage of disease

Ladekarl, Morten; Hansen, Torben Bæk; Henrik-Nielsen, R.; Mouritzen, C; Henriques, U.; Sørensen, Flemming Brandt

doi:10.1002/1097-0142(19950901)76:5<797::aid-cncr2820760513>3.0.co;2-m

Cited by 20 publications

(16 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In fact these basal cells are similar to those observed in invasive carcinoma. Thus, in contrast to those described in other neoplasias (Sørensen, 1989;Ladekarl et al, 1995), the invasive features in prostate cancer are not immediately related to the increase of nuclear volume.…”

Section: Discussionmentioning

confidence: 99%

Cell Proliferation and Volume-Weighted Mean Nuclear Volume in High-Grade Pin and Adenocarcinoma, Compared With Normal Prostate

Teba¹,

Martı́n²,

Gómez³

et al. 2011

Image Anal Stereol

View full text Add to dashboard Cite

High-grade prostate intraepithelial neoplasia (PIN) is considered a precursor of prostate adenocarcinoma. The aim of this study was to quantitate the differences between basal and luminal cells of PIN in relation to mean nuclear volume (ν V nuc), and proliferating cell nuclear antigen labeling index (LI PCNA ), and to compare these estimates with those obtained in normal prostate and carcinoma. The epithelium of both normal and PIN specimens was segmented in basal and luminal compartments, and the ν V nuc and LI PCNA measured in both strata. ν V nuc was significantly lower in normal epithelium than in both PIN and carcinoma. The ν V nuc of basal layer of PIN was significantly higher than in luminal stratum. The luminal ν V nuc was similar in both PIN and adenocarcinoma. The LI PCNA was greater in PIN and adenocarcinoma than in normal glands. The LI PCNA of basal cells from PIN was similar to that observed in the basal stratum from normal prostate, whereas the luminal proliferation from PIN was similar to that observed in adenocarcinoma. The similarities in nuclear size between PIN and carcinoma are according to the premalignant character of PIN. The increase of basal ν V nuc in PIN indicates that the changes heralding the progression from PIN to carcinoma are produced in this layer, whereas the nuclear features of the luminal layer are the same to those of the carcinoma. These remarks make sense in reference to the progression of malignant changes from PIN basal layer to PIN luminal layer and from this to carcinoma.

show abstract

Section: Discussionmentioning

confidence: 99%

Cell Proliferation and Volume-Weighted Mean Nuclear Volume in High-Grade Pin and Adenocarcinoma, Compared With Normal Prostate

Teba¹,

Martı́n²,

Gómez³

et al. 2011

Image Anal Stereol

View full text Add to dashboard Cite

show abstract

“…In this section we describe detection, grading, and CAD systems for four carcinoma types: cervix [56,57,76,79,122], prostate [41,42,105,106,108], breast [6,43,109], and lung [75,78,87,131]. …”

Section: Carcinoma Detection Grading and Cadmentioning

confidence: 99%

“…CAD systems [75,78,87,131] attempt to improve on this variability for reproducible assessments. A training image set is constructed in [78] for different histological classes, and nine texture and morphometry features are used to compare test images with the training set for classification of tumor and non-tumor cases.…”

Section: Carcinoma Detection Grading and Cadmentioning

confidence: 99%

“…In histology image analysis for cancer diagnosis, histopathologists visually examine the regularities of cell shapes and tissue distributions, decide whether tissue regions are cancerous, and determine the malignancy level. Such histopathological study has been extensively employed for cancer detection and grading applications, including prostate [41,42,105,106,108], breast [6,43,109], cervix [56,57,79,122], and lung [75,78,87,131] cancer grading, neuroblastoma categorization [61,81,83,84], and follicular lymphoma grading [34,82,134]. In this paper we use examples of one class of cancers that originates from epithelial cells, i.e., carcinoma , to illustrate common histopathology image analysis functions.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Histology image analysis for carcinoma detection and grading

Long

Antani

et al. 2012

Computer Methods and Programs in Biomedicine

318

184

View full text Add to dashboard Cite

This paper presents an overview of the image analysis techniques in the domain of histopathology, specifically, for the objective of automated carcinoma detection and classification. As in other biomedical imaging areas such as radiology, many computer assisted diagnosis (CAD) systems have been implemented to aid histopathologists and clinicians in cancer diagnosis and research, which have been attempted to significantly reduce the labor and subjectivity of traditional manual intervention with histology images. The task of automated histology image analysis is usually not simple due to the unique characteristics of histology imaging, including the variability in image preparation techniques, clinical interpretation protocols, and the complex structures and very large size of the images themselves. In this paper we discuss those characteristics, provide relevant background information about slide preparation and interpretation, and review the application of digital image processing techniques to the field of histology image analysis. In particular, emphasis is given to state-of-the-art image segmentation methods for feature extraction and disease classification. Four major carcinomas of cervix, prostate, breast, and lung are selected to illustrate the functions and capabilities of existing CAD systems.

show abstract

“…This method was also useful in estimating the tumor grade of lung squamous cell carcinoma, which was shown by Ladekarl et al in 1995. 8 Yokozaki et al 9 differentiated between atypical adenomatous hyperplasia and adenocarcinoma of the lung by DNA histogram patterns and nuclear size, using an image cytometer. By means of high-resolution image analysis, Jü tting et al 10 evaluated the diagnosis and prognosis of neuroendocrine lung tumors in 1999.…”

mentioning

confidence: 99%

Quantitative nuclear texture features analysis confirms WHO classification 2004 for lung carcinomas

et al. 2006

View full text Add to dashboard Cite

The purpose of this study was to discriminate the main subsets of lung carcinomas of the WHO classification of 2004 by nuclear chromatin texture feature analysis. Our collective comprised 56 typical and 19 atypical carcinoids, 37 small-cell carcinomas, 15 large-cell neuroendocrine carcinomas, 42 adenocarcinomas, and 26 squamous cell carcinomas. After Feulgen staining, cell nuclei were automatically measured using a highresolution image analyser (CytoSavant Oncometrics, Vancouver, BC, Canada). Texture features describing the granularity and the compactness of the nuclear chromatin were extracted for calculation of classification rules, which allowed the discrimination of different tumor groups. By applying the classification rule that described the granularity of the nuclear chromatin (defined by four different parameters) small-cell and non-small-cell lung carcinoma could correctly be discriminated in 93%. No significant discrimination was possible between the different subtypes of large-cell carcinomas, including large-cell neuroendocrine carcinoma. When using compactness of chromatin (defined by four texture parameters) as a means of discrimination, carcinoids and non-small-cell lung carcinomas were correctly distinguished in 92%. No significant discrimination between neuroendocrine tumors was achieved though. Our findings are in accordance with the new WHO classification of 2004: neuroendocrine tumors of the lung are now classified according only to their mitotic counts and presence of necrosis but not by their morphology; their discrimination by the means of nuclear image analysis is not sufficient and therefore not appropriate any longer.

show abstract

Objective malignancy grading of squamous cell carcinoma of the lung. Stereologic estimates of mean nuclear size are of prognostic value, independent of clinical stage of disease

Cited by 20 publications

References 24 publications

Cell Proliferation and Volume-Weighted Mean Nuclear Volume in High-Grade Pin and Adenocarcinoma, Compared With Normal Prostate

Cell Proliferation and Volume-Weighted Mean Nuclear Volume in High-Grade Pin and Adenocarcinoma, Compared With Normal Prostate

Histology image analysis for carcinoma detection and grading

Quantitative nuclear texture features analysis confirms WHO classification 2004 for lung carcinomas

Contact Info

Product

Resources

About