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Observational Study of the Natural Growth History of Peripheral Small-Cell Lung Cancer on CT Imaging
Background: This study aimed to investigate the natural growth history of peripheral small-cell lung cancer (SCLC) using CT imaging. Methods: A retrospective study was conducted on 27 patients with peripheral SCLC who underwent at least two CT scans. Two methods were used: Method 1 involved direct m...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10417025/ https://www.ncbi.nlm.nih.gov/pubmed/37568923 http://dx.doi.org/10.3390/diagnostics13152560 |
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author | Jiang, Xu Liu, Meng-Wen Zhang, Xue Dong, Ji-Yan Miao, Lei Sun, Zi-Han Dong, Shu-Shan Zhang, Li Yang, Lin Li, Meng |
author_facet | Jiang, Xu Liu, Meng-Wen Zhang, Xue Dong, Ji-Yan Miao, Lei Sun, Zi-Han Dong, Shu-Shan Zhang, Li Yang, Lin Li, Meng |
author_sort | Jiang, Xu |
collection | PubMed |
description | Background: This study aimed to investigate the natural growth history of peripheral small-cell lung cancer (SCLC) using CT imaging. Methods: A retrospective study was conducted on 27 patients with peripheral SCLC who underwent at least two CT scans. Two methods were used: Method 1 involved direct measurement of nodule dimensions using a calliper, while Method 2 involved tumour lesion segmentation and voxel volume calculation using the “py-radiomics” package in Python. Agreement between the two methods was assessed using the intraclass correlation coefficient (ICC). Volume doubling time (VDT) and growth rate (GR) were used as evaluation indices for SCLC growth, and growth distribution based on GR and volume measurements were depicted. We collected potential factors related to imaging VDT and performed a differential analysis. Patients were classified into slow-growing and fast-growing groups based on a VDT cut-off point of 60 days, and univariate analysis was used to identify factors influencing VDT. Results: Median VDT calculated by the two methods were 61 days and 71 days, respectively, with strong agreement. All patients had continuously growing tumours, and none had tumours that decreased in size or remained unchanged. Eight patients showed possible growth patterns, with six possibly exhibiting exponential growth and two possibly showing Gompertzian growth. Tumours deeper in the lung grew faster than those adjacent to the pleura. Conclusions: Peripheral SCLC tumours grow rapidly and continuously without periods of nongrowth or regression. Tumours located deeper in the lung tend to grow faster, but further research is needed to confirm this finding. |
format | Online Article Text |
id | pubmed-10417025 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-104170252023-08-12 Observational Study of the Natural Growth History of Peripheral Small-Cell Lung Cancer on CT Imaging Jiang, Xu Liu, Meng-Wen Zhang, Xue Dong, Ji-Yan Miao, Lei Sun, Zi-Han Dong, Shu-Shan Zhang, Li Yang, Lin Li, Meng Diagnostics (Basel) Article Background: This study aimed to investigate the natural growth history of peripheral small-cell lung cancer (SCLC) using CT imaging. Methods: A retrospective study was conducted on 27 patients with peripheral SCLC who underwent at least two CT scans. Two methods were used: Method 1 involved direct measurement of nodule dimensions using a calliper, while Method 2 involved tumour lesion segmentation and voxel volume calculation using the “py-radiomics” package in Python. Agreement between the two methods was assessed using the intraclass correlation coefficient (ICC). Volume doubling time (VDT) and growth rate (GR) were used as evaluation indices for SCLC growth, and growth distribution based on GR and volume measurements were depicted. We collected potential factors related to imaging VDT and performed a differential analysis. Patients were classified into slow-growing and fast-growing groups based on a VDT cut-off point of 60 days, and univariate analysis was used to identify factors influencing VDT. Results: Median VDT calculated by the two methods were 61 days and 71 days, respectively, with strong agreement. All patients had continuously growing tumours, and none had tumours that decreased in size or remained unchanged. Eight patients showed possible growth patterns, with six possibly exhibiting exponential growth and two possibly showing Gompertzian growth. Tumours deeper in the lung grew faster than those adjacent to the pleura. Conclusions: Peripheral SCLC tumours grow rapidly and continuously without periods of nongrowth or regression. Tumours located deeper in the lung tend to grow faster, but further research is needed to confirm this finding. MDPI 2023-08-01 /pmc/articles/PMC10417025/ /pubmed/37568923 http://dx.doi.org/10.3390/diagnostics13152560 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Jiang, Xu Liu, Meng-Wen Zhang, Xue Dong, Ji-Yan Miao, Lei Sun, Zi-Han Dong, Shu-Shan Zhang, Li Yang, Lin Li, Meng Observational Study of the Natural Growth History of Peripheral Small-Cell Lung Cancer on CT Imaging |
title | Observational Study of the Natural Growth History of Peripheral Small-Cell Lung Cancer on CT Imaging |
title_full | Observational Study of the Natural Growth History of Peripheral Small-Cell Lung Cancer on CT Imaging |
title_fullStr | Observational Study of the Natural Growth History of Peripheral Small-Cell Lung Cancer on CT Imaging |
title_full_unstemmed | Observational Study of the Natural Growth History of Peripheral Small-Cell Lung Cancer on CT Imaging |
title_short | Observational Study of the Natural Growth History of Peripheral Small-Cell Lung Cancer on CT Imaging |
title_sort | observational study of the natural growth history of peripheral small-cell lung cancer on ct imaging |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10417025/ https://www.ncbi.nlm.nih.gov/pubmed/37568923 http://dx.doi.org/10.3390/diagnostics13152560 |
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