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UMass Chan AffiliationsDepartment of Radiology
Document TypeJournal Article
area under the curve
receiver operating characteristic
region of interest
Analytical, Diagnostic and Therapeutic Techniques and Equipment
Respiratory Tract Diseases
MetadataShow full item record
AbstractPurpose: To determine the accuracy of quantitative CT to diagnose pulmonary edema compared to qualitative CT and CXR and to determine a threshold Hounsfield unit (HU) measurement for pulmonary edema on CT examinations. Method: Electronic medical records were searched for patients with a billing diagnosis of heart failure and a Chest CT and CXR performed within three hours between 1/1/2016 to 10/1/2016, yielding 100 patients. CXR and CT examinations were scored for the presence and severity of edema, using a 0-5 scale, and CT HU measurements were obtained in each lobe. Polyserial correlation coefficients evaluated the association between CT HUs and CXR scores, and receiver operating characteristic (ROC) curve analysis determined a cutoff CT HU value for identification of pulmonary edema. Results: Correlation between CT HU and CXR score was moderately strong (r=0.585-0.685) with CT HU measurements demonstrating good to excellent accuracy in differentiating between no edema (grade 0) and mild to severe edema (grades 1-5) in every lobe, with AUCs ranging between 0.869 and 0.995. The left upper lobe demonstrated the highest accuracy, using a cutoff value of -825 HU (AUC of 0.995, sensitivity=100 % and specificity=95.1 %). Additionally, qualitative CT evaluation was less sensitive (84 %) than portable CXR in identifying pulmonary edema. However, quantitative CT evaluation was as sensitive as portable CXR (100 %) and highly specific (95 %). Conclusions: Quantitative CT enables the identification of pulmonary edema with high accuracy and demonstrates a greater sensitivity than qualitative CT in assessment of pulmonary edema.
Barile M, Hida T, Hammer M, Hatabu H. Simple quantitative chest CT for pulmonary edema. Eur J Radiol Open. 2020 Oct 30;7:100273. doi: 10.1016/j.ejro.2020.100273. PMID: 33163584; PMCID: PMC7607389. Link to article on publisher's site
Permanent Link to this Itemhttp://hdl.handle.net/20.500.14038/48467
Rights© 2020 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Except where otherwise noted, this item's license is described as © 2020 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).