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Role of quantitative CT in predicting postoperative FEV(1 )and chronic dyspnea in patients undergoing lung resection
Lung resection is the mainstay of treatment in patients with early stage non-small cell lung cancer. However, lung cancer patients often suffer from comorbidities and the respiratory reserve should be carefully evaluated preoperatively in order to avoid postoperative complications. Forced expiratory...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3463043/ https://www.ncbi.nlm.nih.gov/pubmed/22958356 http://dx.doi.org/10.1186/2049-6958-5-3-188 |
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author | Papageorgiou, Chrysovalantis V Antoniou, Dimosthenis Kaltsakas, Georgios Koulouris, Nikolaos G |
author_facet | Papageorgiou, Chrysovalantis V Antoniou, Dimosthenis Kaltsakas, Georgios Koulouris, Nikolaos G |
author_sort | Papageorgiou, Chrysovalantis V |
collection | PubMed |
description | Lung resection is the mainstay of treatment in patients with early stage non-small cell lung cancer. However, lung cancer patients often suffer from comorbidities and the respiratory reserve should be carefully evaluated preoperatively in order to avoid postoperative complications. Forced expiratory volume in 1 second (FEV(1)) is considered to be an index that depicts the patient's respiratory efficacy and its prediction has a key role in the preoperative evaluation of lung cancer patients with impaired lung function. Prediction of postoperative FEV(1 )is currently possible with the use of perfusion radionuclide lung scanning. Quantitative CT is the analysis of data acquired during normal chest CT scan using the system's software. By applying a dual threshold of -500 to -910 Hounsfield Units, functional lung volumes are estimated and postoperative FEV(1 )can be predicted by reducing the preoperative measurement by the fraction of the part to be resected. Studies have shown that preoperative predictions correlate well with the actual postoperative measurements. Additionally, quantitative CT results are in good agreement with perfusion scintigraphy predictions. Newer radiological techniques such as perfusion MRI and co-registered SPECT/CT have also been used in the preoperative evaluation with similar results. In conclusion, chest CT which is obligatory for staging, can be used for quantitative analysis of the already available data. It is technically simple, providing an accurate prediction of postoperative FEV(1). Thus, quantitative CT appears to be a useful tool in the preoperative evaluation of lung cancer patients undergoing lung resection. |
format | Online Article Text |
id | pubmed-3463043 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-34630432012-10-05 Role of quantitative CT in predicting postoperative FEV(1 )and chronic dyspnea in patients undergoing lung resection Papageorgiou, Chrysovalantis V Antoniou, Dimosthenis Kaltsakas, Georgios Koulouris, Nikolaos G Multidiscip Respir Med Technical Note Lung resection is the mainstay of treatment in patients with early stage non-small cell lung cancer. However, lung cancer patients often suffer from comorbidities and the respiratory reserve should be carefully evaluated preoperatively in order to avoid postoperative complications. Forced expiratory volume in 1 second (FEV(1)) is considered to be an index that depicts the patient's respiratory efficacy and its prediction has a key role in the preoperative evaluation of lung cancer patients with impaired lung function. Prediction of postoperative FEV(1 )is currently possible with the use of perfusion radionuclide lung scanning. Quantitative CT is the analysis of data acquired during normal chest CT scan using the system's software. By applying a dual threshold of -500 to -910 Hounsfield Units, functional lung volumes are estimated and postoperative FEV(1 )can be predicted by reducing the preoperative measurement by the fraction of the part to be resected. Studies have shown that preoperative predictions correlate well with the actual postoperative measurements. Additionally, quantitative CT results are in good agreement with perfusion scintigraphy predictions. Newer radiological techniques such as perfusion MRI and co-registered SPECT/CT have also been used in the preoperative evaluation with similar results. In conclusion, chest CT which is obligatory for staging, can be used for quantitative analysis of the already available data. It is technically simple, providing an accurate prediction of postoperative FEV(1). Thus, quantitative CT appears to be a useful tool in the preoperative evaluation of lung cancer patients undergoing lung resection. BioMed Central 2010-06-30 /pmc/articles/PMC3463043/ /pubmed/22958356 http://dx.doi.org/10.1186/2049-6958-5-3-188 Text en Copyright ©2010 Novamedia srl |
spellingShingle | Technical Note Papageorgiou, Chrysovalantis V Antoniou, Dimosthenis Kaltsakas, Georgios Koulouris, Nikolaos G Role of quantitative CT in predicting postoperative FEV(1 )and chronic dyspnea in patients undergoing lung resection |
title | Role of quantitative CT in predicting postoperative FEV(1 )and chronic dyspnea in patients undergoing lung resection |
title_full | Role of quantitative CT in predicting postoperative FEV(1 )and chronic dyspnea in patients undergoing lung resection |
title_fullStr | Role of quantitative CT in predicting postoperative FEV(1 )and chronic dyspnea in patients undergoing lung resection |
title_full_unstemmed | Role of quantitative CT in predicting postoperative FEV(1 )and chronic dyspnea in patients undergoing lung resection |
title_short | Role of quantitative CT in predicting postoperative FEV(1 )and chronic dyspnea in patients undergoing lung resection |
title_sort | role of quantitative ct in predicting postoperative fev(1 )and chronic dyspnea in patients undergoing lung resection |
topic | Technical Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3463043/ https://www.ncbi.nlm.nih.gov/pubmed/22958356 http://dx.doi.org/10.1186/2049-6958-5-3-188 |
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