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Value of Shape and Texture Features from (18)F-FDG PET/CT to Discriminate between Benign and Malignant Solitary Pulmonary Nodules: An Experimental Evaluation
In this paper, we investigate the role of shape and texture features from [Formula: see text] F-FDG PET/CT to discriminate between benign and malignant solitary pulmonary nodules. To this end, we retrospectively evaluated cross-sectional data from 111 patients (64 males, 47 females, age = 67.5 ± 11....
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7555302/ https://www.ncbi.nlm.nih.gov/pubmed/32942729 http://dx.doi.org/10.3390/diagnostics10090696 |
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author | Palumbo, Barbara Bianconi, Francesco Palumbo, Isabella Fravolini, Mario Luca Minestrini, Matteo Nuvoli, Susanna Stazza, Maria Lina Rondini, Maria Spanu, Angela |
author_facet | Palumbo, Barbara Bianconi, Francesco Palumbo, Isabella Fravolini, Mario Luca Minestrini, Matteo Nuvoli, Susanna Stazza, Maria Lina Rondini, Maria Spanu, Angela |
author_sort | Palumbo, Barbara |
collection | PubMed |
description | In this paper, we investigate the role of shape and texture features from [Formula: see text] F-FDG PET/CT to discriminate between benign and malignant solitary pulmonary nodules. To this end, we retrospectively evaluated cross-sectional data from 111 patients (64 males, 47 females, age = 67.5 ± 11.0) all with histologically confirmed benign ([Formula: see text]) or malignant ([Formula: see text]) solitary pulmonary nodules. Eighteen three-dimensional imaging features, including conventional, texture, and shape features from PET and CT were tested for significant differences (Wilcoxon-Mann-Withney) between the benign and malignant groups. Prediction models based on different feature sets and three classification strategies (Classification Tree, k-Nearest Neighbours, and Naïve Bayes) were also evaluated to assess the potential benefit of shape and texture features compared with conventional imaging features alone. Eight features from CT and 15 from PET were significantly different between the benign and malignant groups. Adding shape and texture features increased the performance of both the CT-based and PET-based prediction models with overall accuracy gain being 3.4–11.2 pp and 2.2–10.2 pp, respectively. In conclusion, we found that shape and texture features from [Formula: see text] F-FDG PET/CT can lead to a better discrimination between benign and malignant lung nodules by increasing the accuracy of the prediction models by an appreciable margin. |
format | Online Article Text |
id | pubmed-7555302 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75553022020-10-19 Value of Shape and Texture Features from (18)F-FDG PET/CT to Discriminate between Benign and Malignant Solitary Pulmonary Nodules: An Experimental Evaluation Palumbo, Barbara Bianconi, Francesco Palumbo, Isabella Fravolini, Mario Luca Minestrini, Matteo Nuvoli, Susanna Stazza, Maria Lina Rondini, Maria Spanu, Angela Diagnostics (Basel) Article In this paper, we investigate the role of shape and texture features from [Formula: see text] F-FDG PET/CT to discriminate between benign and malignant solitary pulmonary nodules. To this end, we retrospectively evaluated cross-sectional data from 111 patients (64 males, 47 females, age = 67.5 ± 11.0) all with histologically confirmed benign ([Formula: see text]) or malignant ([Formula: see text]) solitary pulmonary nodules. Eighteen three-dimensional imaging features, including conventional, texture, and shape features from PET and CT were tested for significant differences (Wilcoxon-Mann-Withney) between the benign and malignant groups. Prediction models based on different feature sets and three classification strategies (Classification Tree, k-Nearest Neighbours, and Naïve Bayes) were also evaluated to assess the potential benefit of shape and texture features compared with conventional imaging features alone. Eight features from CT and 15 from PET were significantly different between the benign and malignant groups. Adding shape and texture features increased the performance of both the CT-based and PET-based prediction models with overall accuracy gain being 3.4–11.2 pp and 2.2–10.2 pp, respectively. In conclusion, we found that shape and texture features from [Formula: see text] F-FDG PET/CT can lead to a better discrimination between benign and malignant lung nodules by increasing the accuracy of the prediction models by an appreciable margin. MDPI 2020-09-15 /pmc/articles/PMC7555302/ /pubmed/32942729 http://dx.doi.org/10.3390/diagnostics10090696 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Palumbo, Barbara Bianconi, Francesco Palumbo, Isabella Fravolini, Mario Luca Minestrini, Matteo Nuvoli, Susanna Stazza, Maria Lina Rondini, Maria Spanu, Angela Value of Shape and Texture Features from (18)F-FDG PET/CT to Discriminate between Benign and Malignant Solitary Pulmonary Nodules: An Experimental Evaluation |
title | Value of Shape and Texture Features from (18)F-FDG PET/CT to Discriminate between Benign and Malignant Solitary Pulmonary Nodules: An Experimental Evaluation |
title_full | Value of Shape and Texture Features from (18)F-FDG PET/CT to Discriminate between Benign and Malignant Solitary Pulmonary Nodules: An Experimental Evaluation |
title_fullStr | Value of Shape and Texture Features from (18)F-FDG PET/CT to Discriminate between Benign and Malignant Solitary Pulmonary Nodules: An Experimental Evaluation |
title_full_unstemmed | Value of Shape and Texture Features from (18)F-FDG PET/CT to Discriminate between Benign and Malignant Solitary Pulmonary Nodules: An Experimental Evaluation |
title_short | Value of Shape and Texture Features from (18)F-FDG PET/CT to Discriminate between Benign and Malignant Solitary Pulmonary Nodules: An Experimental Evaluation |
title_sort | value of shape and texture features from (18)f-fdg pet/ct to discriminate between benign and malignant solitary pulmonary nodules: an experimental evaluation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7555302/ https://www.ncbi.nlm.nih.gov/pubmed/32942729 http://dx.doi.org/10.3390/diagnostics10090696 |
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