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Integrated prognostication of intrahepatic cholangiocarcinoma by contrast-enhanced computed tomography: the adjunct yield of radiomics

PURPOSE: To test radiomics for prognostication of intrahepatic mass-forming cholangiocarcinoma (IMCC) and to develop a comprehensive risk model. METHODS: Histologically proven IMCC (representing the full range of stages) were retrospectively analyzed by volume segmentation on baseline hepatic venous...

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Autores principales: Silva, Mario, Maddalo, Michele, Leoni, Eleonora, Giuliotti, Sara, Milanese, Gianluca, Ghetti, Caterina, Biasini, Elisabetta, De Filippo, Massimo, Missale, Gabriele, Sverzellati, Nicola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8435517/
https://www.ncbi.nlm.nih.gov/pubmed/34165602
http://dx.doi.org/10.1007/s00261-021-03183-9
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author Silva, Mario
Maddalo, Michele
Leoni, Eleonora
Giuliotti, Sara
Milanese, Gianluca
Ghetti, Caterina
Biasini, Elisabetta
De Filippo, Massimo
Missale, Gabriele
Sverzellati, Nicola
author_facet Silva, Mario
Maddalo, Michele
Leoni, Eleonora
Giuliotti, Sara
Milanese, Gianluca
Ghetti, Caterina
Biasini, Elisabetta
De Filippo, Massimo
Missale, Gabriele
Sverzellati, Nicola
author_sort Silva, Mario
collection PubMed
description PURPOSE: To test radiomics for prognostication of intrahepatic mass-forming cholangiocarcinoma (IMCC) and to develop a comprehensive risk model. METHODS: Histologically proven IMCC (representing the full range of stages) were retrospectively analyzed by volume segmentation on baseline hepatic venous phase computed tomography (CT), by two readers with different experience (R1 and R2). Morphological CT features included: tumor size, hepatic satellite lesions, lymph node and distant metastases. Radiomic features (RF) were compared across CT protocols and readers. Univariate analysis against overall survival (OS) warranted ranking and selection of RF into radiomic signature (RSign), which was dichotomized into high and low-risk strata (RSign*). Models without and with RSign* (Model 1 and 2, respectively) were compared. RESULTS: Among 78 patients (median follow-up 262 days, IQR 73–957), 62/78 (79%) died during the study period, 46/78 (59%) died within 1 year. Up to 10% RF showed variability across CT protocols; 37/108 (34%) RF showed variability due to manual segmentation. RSign stratified OS (univariate: HR 1.37 for R1, HR 1.28 for R2), RSign* was different between readers (R1 0.39; R2 0.57). Model 1 showed AUC 0.71, which increased in Model 2: AUC 0.81 (p < 0.001) and AIC 89 for R1, AUC 0.81 (p = 0.001) and AIC 90.2 for R2. CONCLUSION: The use of RF into a unified RSign score stratified OS in patients with IMCC. Dichotomized RSign* classified survival strata, its inclusion in risk models showed adjunct yield. The cut-off value of RSign* was different between readers, suggesting that the use of reference values is hampered by interobserver variability. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00261-021-03183-9.
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spelling pubmed-84355172021-09-24 Integrated prognostication of intrahepatic cholangiocarcinoma by contrast-enhanced computed tomography: the adjunct yield of radiomics Silva, Mario Maddalo, Michele Leoni, Eleonora Giuliotti, Sara Milanese, Gianluca Ghetti, Caterina Biasini, Elisabetta De Filippo, Massimo Missale, Gabriele Sverzellati, Nicola Abdom Radiol (NY) Hepatobiliary PURPOSE: To test radiomics for prognostication of intrahepatic mass-forming cholangiocarcinoma (IMCC) and to develop a comprehensive risk model. METHODS: Histologically proven IMCC (representing the full range of stages) were retrospectively analyzed by volume segmentation on baseline hepatic venous phase computed tomography (CT), by two readers with different experience (R1 and R2). Morphological CT features included: tumor size, hepatic satellite lesions, lymph node and distant metastases. Radiomic features (RF) were compared across CT protocols and readers. Univariate analysis against overall survival (OS) warranted ranking and selection of RF into radiomic signature (RSign), which was dichotomized into high and low-risk strata (RSign*). Models without and with RSign* (Model 1 and 2, respectively) were compared. RESULTS: Among 78 patients (median follow-up 262 days, IQR 73–957), 62/78 (79%) died during the study period, 46/78 (59%) died within 1 year. Up to 10% RF showed variability across CT protocols; 37/108 (34%) RF showed variability due to manual segmentation. RSign stratified OS (univariate: HR 1.37 for R1, HR 1.28 for R2), RSign* was different between readers (R1 0.39; R2 0.57). Model 1 showed AUC 0.71, which increased in Model 2: AUC 0.81 (p < 0.001) and AIC 89 for R1, AUC 0.81 (p = 0.001) and AIC 90.2 for R2. CONCLUSION: The use of RF into a unified RSign score stratified OS in patients with IMCC. Dichotomized RSign* classified survival strata, its inclusion in risk models showed adjunct yield. The cut-off value of RSign* was different between readers, suggesting that the use of reference values is hampered by interobserver variability. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00261-021-03183-9. Springer US 2021-06-24 2021 /pmc/articles/PMC8435517/ /pubmed/34165602 http://dx.doi.org/10.1007/s00261-021-03183-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Hepatobiliary
Silva, Mario
Maddalo, Michele
Leoni, Eleonora
Giuliotti, Sara
Milanese, Gianluca
Ghetti, Caterina
Biasini, Elisabetta
De Filippo, Massimo
Missale, Gabriele
Sverzellati, Nicola
Integrated prognostication of intrahepatic cholangiocarcinoma by contrast-enhanced computed tomography: the adjunct yield of radiomics
title Integrated prognostication of intrahepatic cholangiocarcinoma by contrast-enhanced computed tomography: the adjunct yield of radiomics
title_full Integrated prognostication of intrahepatic cholangiocarcinoma by contrast-enhanced computed tomography: the adjunct yield of radiomics
title_fullStr Integrated prognostication of intrahepatic cholangiocarcinoma by contrast-enhanced computed tomography: the adjunct yield of radiomics
title_full_unstemmed Integrated prognostication of intrahepatic cholangiocarcinoma by contrast-enhanced computed tomography: the adjunct yield of radiomics
title_short Integrated prognostication of intrahepatic cholangiocarcinoma by contrast-enhanced computed tomography: the adjunct yield of radiomics
title_sort integrated prognostication of intrahepatic cholangiocarcinoma by contrast-enhanced computed tomography: the adjunct yield of radiomics
topic Hepatobiliary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8435517/
https://www.ncbi.nlm.nih.gov/pubmed/34165602
http://dx.doi.org/10.1007/s00261-021-03183-9
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