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The Role of Computed Tomography Perfusion in Various Focal Liver Lesions

Background This study aims to identify the potential advantages of quantitative determination of various focal liver pathologies, identify lesion hemodynamics, and distinguish benign and malignant pathologies based on CT perfusion (CTP) parameters. Methodology In this study, we examined 36 patients...

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Autores principales: Gadupudi, Vignesh, Ramachandran, Rajoo, Pulivadula Mohanarangam, Venkata Sai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cureus 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9833639/
https://www.ncbi.nlm.nih.gov/pubmed/36644059
http://dx.doi.org/10.7759/cureus.32420
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author Gadupudi, Vignesh
Ramachandran, Rajoo
Pulivadula Mohanarangam, Venkata Sai
author_facet Gadupudi, Vignesh
Ramachandran, Rajoo
Pulivadula Mohanarangam, Venkata Sai
author_sort Gadupudi, Vignesh
collection PubMed
description Background This study aims to identify the potential advantages of quantitative determination of various focal liver pathologies, identify lesion hemodynamics, and distinguish benign and malignant pathologies based on CT perfusion (CTP) parameters. Methodology In this study, we examined 36 patients using contrast-enhanced CT (CECT) and proposed inclusion and exclusion criteria. Of the 36 patients, 18 had malignant lesions and 14 had benign lesions. CTP was performed on patients comprising cases of hepatocellular carcinoma (HCC), metastasis, hemangiomas, hepatic cysts, and hepatic abscess. Images were post-processed and analyzed to calculate various perfusion parameters such as blood flow (BF), blood volume (BV), permeability surface (PS), mean transit time (MTT), the hepatic arterial fraction (HAF), and induced residue fraction time of onset (IRFTO). Parameters were compared between benign and malignant lesions, and descriptive analysis was performed for individual lesions. Results Data were analyzed with IBM SPSS Statistics (IBM Corp., Armonk, NY, USA). IRFTO showed the area of the curve (AOC) = 0.659, P-value = 0.040, sensitivity 66.7%, and specificity 64.3%. BV showed AOC = 0.659, P-value = 0.040, with a cutoff value of 1.26, sensitivity of 66.7%, and specificity of 64.3%. BF showed AOC = 0.786 and P-value = 0.006, with a cutoff value of 171.2, sensitivity of 83.3%, and specificity of 78.6%. MTT showed AOC = 0.778 and P-value = 0.008, with a cutoff value of 6.94, sensitivity of 77.8%, and specificity of 78.6%. Statistically significant changes were observed in the perfusion parameters in the BV, BF, MTT, and IRFTO. Conclusions The noninvasive CT liver perfusion technique makes it possible to compare the hemodynamic changes in healthy and sick liver tissues, identify focal liver lesions, and evaluate the effectiveness of tumor therapy.
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spelling pubmed-98336392023-01-12 The Role of Computed Tomography Perfusion in Various Focal Liver Lesions Gadupudi, Vignesh Ramachandran, Rajoo Pulivadula Mohanarangam, Venkata Sai Cureus Radiology Background This study aims to identify the potential advantages of quantitative determination of various focal liver pathologies, identify lesion hemodynamics, and distinguish benign and malignant pathologies based on CT perfusion (CTP) parameters. Methodology In this study, we examined 36 patients using contrast-enhanced CT (CECT) and proposed inclusion and exclusion criteria. Of the 36 patients, 18 had malignant lesions and 14 had benign lesions. CTP was performed on patients comprising cases of hepatocellular carcinoma (HCC), metastasis, hemangiomas, hepatic cysts, and hepatic abscess. Images were post-processed and analyzed to calculate various perfusion parameters such as blood flow (BF), blood volume (BV), permeability surface (PS), mean transit time (MTT), the hepatic arterial fraction (HAF), and induced residue fraction time of onset (IRFTO). Parameters were compared between benign and malignant lesions, and descriptive analysis was performed for individual lesions. Results Data were analyzed with IBM SPSS Statistics (IBM Corp., Armonk, NY, USA). IRFTO showed the area of the curve (AOC) = 0.659, P-value = 0.040, sensitivity 66.7%, and specificity 64.3%. BV showed AOC = 0.659, P-value = 0.040, with a cutoff value of 1.26, sensitivity of 66.7%, and specificity of 64.3%. BF showed AOC = 0.786 and P-value = 0.006, with a cutoff value of 171.2, sensitivity of 83.3%, and specificity of 78.6%. MTT showed AOC = 0.778 and P-value = 0.008, with a cutoff value of 6.94, sensitivity of 77.8%, and specificity of 78.6%. Statistically significant changes were observed in the perfusion parameters in the BV, BF, MTT, and IRFTO. Conclusions The noninvasive CT liver perfusion technique makes it possible to compare the hemodynamic changes in healthy and sick liver tissues, identify focal liver lesions, and evaluate the effectiveness of tumor therapy. Cureus 2022-12-11 /pmc/articles/PMC9833639/ /pubmed/36644059 http://dx.doi.org/10.7759/cureus.32420 Text en Copyright © 2022, Gadupudi et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Radiology
Gadupudi, Vignesh
Ramachandran, Rajoo
Pulivadula Mohanarangam, Venkata Sai
The Role of Computed Tomography Perfusion in Various Focal Liver Lesions
title The Role of Computed Tomography Perfusion in Various Focal Liver Lesions
title_full The Role of Computed Tomography Perfusion in Various Focal Liver Lesions
title_fullStr The Role of Computed Tomography Perfusion in Various Focal Liver Lesions
title_full_unstemmed The Role of Computed Tomography Perfusion in Various Focal Liver Lesions
title_short The Role of Computed Tomography Perfusion in Various Focal Liver Lesions
title_sort role of computed tomography perfusion in various focal liver lesions
topic Radiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9833639/
https://www.ncbi.nlm.nih.gov/pubmed/36644059
http://dx.doi.org/10.7759/cureus.32420
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