Diagnosis and Prognosis of Neuroendocrine Tumours of the Lung by Means of High Resolution Image Analysis
Neuroendocrine tumours (NET) of the lung are divided in subtypes with different malignant potential. The first is the benign or low‐grade malignant tumours, well‐differentiated, called typical carcinoids (TC) and the second is the high‐grade malignant tumours, poorly differentiated of small (SCLC) o...
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| Format: | Article |
| Language: | English |
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Wiley
1999-01-01
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| Series: | Analytical Cellular Pathology |
| Online Access: | http://dx.doi.org/10.1155/1999/695907 |
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| author | Uta Jütting Peter Gais Karsten Rodenacker Joachim Böhm Susanne Koch Heinz W. Präuer Heinz Höfler |
| author_facet | Uta Jütting Peter Gais Karsten Rodenacker Joachim Böhm Susanne Koch Heinz W. Präuer Heinz Höfler |
| author_sort | Uta Jütting |
| collection | DOAJ |
| description | Neuroendocrine tumours (NET) of the lung are divided in subtypes with different malignant potential. The first is the benign or low‐grade malignant tumours, well‐differentiated, called typical carcinoids (TC) and the second is the high‐grade malignant tumours, poorly differentiated of small (SCLC) or large cell type (LCLC). Between these tumour types lies the well‐differentiated carcinoma with a lower grade of malignancy (WDNEC). In clinical routine it is very important with regard to prognosis to distinguish patients with low malignant potential from those with higher ones. In this study 32 cases of SCLC, 13 of WDNEC and 14 of TC with a follow‐up time up to 7 years were collected. Sections 4 μm thick from paraffin embedded tissue were Feulgen stained. By means of high resolution image analysis 100 nuclei per case were randomly gathered to extract morphometric, densitometric and textural quantitative features. To investigate the ploidy status of the tumour the corrected DNA distribution was calculated. Stepwise linear discriminant analysis to differentiate the classes and Cox regression analysis for the survival time analysis were applied. Using chromatin textural and morphometric features in two two‐class discriminations, 11 of the 14 TC cases and 8 of the 13 WDNEC cases were correctly classified and 11/13 WDNEC cases and 28/32 SCLC cases, respectively. The WDNEC cases are more similar in chromatin structure to TC than to SCLC. For the survival analysis, only chromatin features were selected to differentiate patients with better and worse prognosis independent of staging and tumour type. |
| format | Article |
| id | doaj-art-e0fe0d2d6a9a4ee28298d5f5ba1a8312 |
| institution | Kabale University |
| issn | 0921-8912 1878-3651 |
| language | English |
| publishDate | 1999-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Analytical Cellular Pathology |
| spelling | doaj-art-e0fe0d2d6a9a4ee28298d5f5ba1a83122025-02-03T05:57:21ZengWileyAnalytical Cellular Pathology0921-89121878-36511999-01-0118210911910.1155/1999/695907Diagnosis and Prognosis of Neuroendocrine Tumours of the Lung by Means of High Resolution Image AnalysisUta Jütting0Peter Gais1Karsten Rodenacker2Joachim Böhm3Susanne Koch4Heinz W. Präuer5Heinz Höfler6Institute for Biomathematics and Biometry, GSF‐National Research Center for Environment and Health, Neuherberg, GermanyInstitute of Pathology, GSF‐National Research Center for Environment and Health, Neuherberg, GermanyInstitute for Biomathematics and Biometry, GSF‐National Research Center for Environment and Health, Neuherberg, GermanyInstitute of Pathology, Technical University of Munich, School of Medicine, Munich, GermanyInstitute of Pathology, GSF‐National Research Center for Environment and Health, Neuherberg, GermanyDepartment of Surgery, Technical University of Munich, School of Medicine, Munich, GermanyInstitute of Pathology, GSF‐National Research Center for Environment and Health, Neuherberg, GermanyNeuroendocrine tumours (NET) of the lung are divided in subtypes with different malignant potential. The first is the benign or low‐grade malignant tumours, well‐differentiated, called typical carcinoids (TC) and the second is the high‐grade malignant tumours, poorly differentiated of small (SCLC) or large cell type (LCLC). Between these tumour types lies the well‐differentiated carcinoma with a lower grade of malignancy (WDNEC). In clinical routine it is very important with regard to prognosis to distinguish patients with low malignant potential from those with higher ones. In this study 32 cases of SCLC, 13 of WDNEC and 14 of TC with a follow‐up time up to 7 years were collected. Sections 4 μm thick from paraffin embedded tissue were Feulgen stained. By means of high resolution image analysis 100 nuclei per case were randomly gathered to extract morphometric, densitometric and textural quantitative features. To investigate the ploidy status of the tumour the corrected DNA distribution was calculated. Stepwise linear discriminant analysis to differentiate the classes and Cox regression analysis for the survival time analysis were applied. Using chromatin textural and morphometric features in two two‐class discriminations, 11 of the 14 TC cases and 8 of the 13 WDNEC cases were correctly classified and 11/13 WDNEC cases and 28/32 SCLC cases, respectively. The WDNEC cases are more similar in chromatin structure to TC than to SCLC. For the survival analysis, only chromatin features were selected to differentiate patients with better and worse prognosis independent of staging and tumour type.http://dx.doi.org/10.1155/1999/695907 |
| spellingShingle | Uta Jütting Peter Gais Karsten Rodenacker Joachim Böhm Susanne Koch Heinz W. Präuer Heinz Höfler Diagnosis and Prognosis of Neuroendocrine Tumours of the Lung by Means of High Resolution Image Analysis Analytical Cellular Pathology |
| title | Diagnosis and Prognosis of Neuroendocrine Tumours of the Lung by Means of High Resolution Image Analysis |
| title_full | Diagnosis and Prognosis of Neuroendocrine Tumours of the Lung by Means of High Resolution Image Analysis |
| title_fullStr | Diagnosis and Prognosis of Neuroendocrine Tumours of the Lung by Means of High Resolution Image Analysis |
| title_full_unstemmed | Diagnosis and Prognosis of Neuroendocrine Tumours of the Lung by Means of High Resolution Image Analysis |
| title_short | Diagnosis and Prognosis of Neuroendocrine Tumours of the Lung by Means of High Resolution Image Analysis |
| title_sort | diagnosis and prognosis of neuroendocrine tumours of the lung by means of high resolution image analysis |
| url | http://dx.doi.org/10.1155/1999/695907 |
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