We did this study to investigate the effect of thick (5mm) and thin (1 or 0.625 mm) slice thickness of CT images on evaluating pulmonary nodules' growth to improve their diagnostic accuracy. The clinical and CT data of 251 patients with lung nodules and two follow-up CTs from October 2016 to October 2019 were analyzed retrospectively. Malignant nodules were confirmed by pathology, and benign nodules were confirmed by pathology or follow-up. Two radiologists double-blindly assessed the CT features (density, shape, lobes, border), maximum diameter, and volume of nodules on the thick (5MM) and thin (≤1MM) images of two follow-up CTs. We use One-way analysis of variance for quantitative data; the X2 test or FISHER exact probability method was used for qualitative data; and the ROC curve was used to analyze the diagnostic power of nodule size, volume, and change in differentiating benign and malignant lesions. Among 251 pulmonary nodules, 117 (46.6%) benign nodules and 134 (53.3%) malignant nodules. During the CT follow-up, the volume measured on the thick-section image, the diameter, and the volume measured on the thin-section image were statistically different in benign and malignant lung nodules (P<0.001). In contrast, the diameter measured on the thick-section image was similar between these two groups (P=0.328). For benign and malignant pulmonary nodules, the diameter, volume, and change measured on the thin-section image were significantly larger than the thick-section image's data (P<0.001). The ROC curve showed that the diagnostic efficiency of volume was higher compared to the diameter. There were significant differences in nodule type, density change, shape, lobulation, and pleural retraction between benign and malignant nodules for CT features. Accurately assessing the volume changes combined with CT characteristics will help improve lung nodules' diagnosis accuracy. Volume measured on thin-section (1mm) CT images is the best quantitative parameter for assessing the change of pulmonary nodules. Combining Volume change with CT characteristics would help to improve the diagnostic accuracy.
| Published in | International Journal of Medical Imaging (Volume 9, Issue 2) |
| DOI | 10.11648/j.ijmi.20210902.13 |
| Page(s) | 109-116 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Computed Tomography, Volume Measurements, Diameter Measurements, Malignant Tumors, Benign Nodules, MDCT
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APA Style
Jannatul Maoya Bashanti, Binjie Fu, Wang Jia Li, Mohammad Arman Hossain, Fajin Lv. (2021). The Influence of Quantitative Parameters Measured on CT with Different Slice Thicknesses on Evaluating the Growth of Pulmonary Nodules. International Journal of Medical Imaging, 9(2), 109-116. https://doi.org/10.11648/j.ijmi.20210902.13
ACS Style
Jannatul Maoya Bashanti; Binjie Fu; Wang Jia Li; Mohammad Arman Hossain; Fajin Lv. The Influence of Quantitative Parameters Measured on CT with Different Slice Thicknesses on Evaluating the Growth of Pulmonary Nodules. Int. J. Med. Imaging 2021, 9(2), 109-116. doi: 10.11648/j.ijmi.20210902.13
AMA Style
Jannatul Maoya Bashanti, Binjie Fu, Wang Jia Li, Mohammad Arman Hossain, Fajin Lv. The Influence of Quantitative Parameters Measured on CT with Different Slice Thicknesses on Evaluating the Growth of Pulmonary Nodules. Int J Med Imaging. 2021;9(2):109-116. doi: 10.11648/j.ijmi.20210902.13
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Download@article{10.11648/j.ijmi.20210902.13,
author = {Jannatul Maoya Bashanti and Binjie Fu and Wang Jia Li and Mohammad Arman Hossain and Fajin Lv},
title = {The Influence of Quantitative Parameters Measured on CT with Different Slice Thicknesses on Evaluating the Growth of Pulmonary Nodules},
journal = {International Journal of Medical Imaging},
volume = {9},
number = {2},
pages = {109-116},
doi = {10.11648/j.ijmi.20210902.13},
url = {https://doi.org/10.11648/j.ijmi.20210902.13},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmi.20210902.13},
abstract = {We did this study to investigate the effect of thick (5mm) and thin (1 or 0.625 mm) slice thickness of CT images on evaluating pulmonary nodules' growth to improve their diagnostic accuracy. The clinical and CT data of 251 patients with lung nodules and two follow-up CTs from October 2016 to October 2019 were analyzed retrospectively. Malignant nodules were confirmed by pathology, and benign nodules were confirmed by pathology or follow-up. Two radiologists double-blindly assessed the CT features (density, shape, lobes, border), maximum diameter, and volume of nodules on the thick (5MM) and thin (≤1MM) images of two follow-up CTs. We use One-way analysis of variance for quantitative data; the X2 test or FISHER exact probability method was used for qualitative data; and the ROC curve was used to analyze the diagnostic power of nodule size, volume, and change in differentiating benign and malignant lesions. Among 251 pulmonary nodules, 117 (46.6%) benign nodules and 134 (53.3%) malignant nodules. During the CT follow-up, the volume measured on the thick-section image, the diameter, and the volume measured on the thin-section image were statistically different in benign and malignant lung nodules (P<0.001). In contrast, the diameter measured on the thick-section image was similar between these two groups (P=0.328). For benign and malignant pulmonary nodules, the diameter, volume, and change measured on the thin-section image were significantly larger than the thick-section image's data (P<0.001). The ROC curve showed that the diagnostic efficiency of volume was higher compared to the diameter. There were significant differences in nodule type, density change, shape, lobulation, and pleural retraction between benign and malignant nodules for CT features. Accurately assessing the volume changes combined with CT characteristics will help improve lung nodules' diagnosis accuracy. Volume measured on thin-section (1mm) CT images is the best quantitative parameter for assessing the change of pulmonary nodules. Combining Volume change with CT characteristics would help to improve the diagnostic accuracy.},
year = {2021}
}
TY - JOUR T1 - The Influence of Quantitative Parameters Measured on CT with Different Slice Thicknesses on Evaluating the Growth of Pulmonary Nodules AU - Jannatul Maoya Bashanti AU - Binjie Fu AU - Wang Jia Li AU - Mohammad Arman Hossain AU - Fajin Lv Y1 - 2021/05/26 PY - 2021 N1 - https://doi.org/10.11648/j.ijmi.20210902.13 DO - 10.11648/j.ijmi.20210902.13 T2 - International Journal of Medical Imaging JF - International Journal of Medical Imaging JO - International Journal of Medical Imaging SP - 109 EP - 116 PB - Science Publishing Group SN - 2330-832X UR - https://doi.org/10.11648/j.ijmi.20210902.13 AB - We did this study to investigate the effect of thick (5mm) and thin (1 or 0.625 mm) slice thickness of CT images on evaluating pulmonary nodules' growth to improve their diagnostic accuracy. The clinical and CT data of 251 patients with lung nodules and two follow-up CTs from October 2016 to October 2019 were analyzed retrospectively. Malignant nodules were confirmed by pathology, and benign nodules were confirmed by pathology or follow-up. Two radiologists double-blindly assessed the CT features (density, shape, lobes, border), maximum diameter, and volume of nodules on the thick (5MM) and thin (≤1MM) images of two follow-up CTs. We use One-way analysis of variance for quantitative data; the X2 test or FISHER exact probability method was used for qualitative data; and the ROC curve was used to analyze the diagnostic power of nodule size, volume, and change in differentiating benign and malignant lesions. Among 251 pulmonary nodules, 117 (46.6%) benign nodules and 134 (53.3%) malignant nodules. During the CT follow-up, the volume measured on the thick-section image, the diameter, and the volume measured on the thin-section image were statistically different in benign and malignant lung nodules (P<0.001). In contrast, the diameter measured on the thick-section image was similar between these two groups (P=0.328). For benign and malignant pulmonary nodules, the diameter, volume, and change measured on the thin-section image were significantly larger than the thick-section image's data (P<0.001). The ROC curve showed that the diagnostic efficiency of volume was higher compared to the diameter. There were significant differences in nodule type, density change, shape, lobulation, and pleural retraction between benign and malignant nodules for CT features. Accurately assessing the volume changes combined with CT characteristics will help improve lung nodules' diagnosis accuracy. Volume measured on thin-section (1mm) CT images is the best quantitative parameter for assessing the change of pulmonary nodules. Combining Volume change with CT characteristics would help to improve the diagnostic accuracy. VL - 9 IS - 2 ER -
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