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Repeatability and reproducibility of deep-learning-based liver volume and Couinaud segment volume measurement tool

PURPOSE: Volumetric and health assessment of the liver is crucial to avoid poor post-operative outcomes following liver resection surgery. No current methods allow for concurrent and accurate measurement of both Couinaud segmental volumes for future liver remnant estimation and liver health using no...

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Autores principales: Mojtahed, Amirkasra, Núñez, Luis, Connell, John, Fichera, Alessandro, Nicholls, Rowan, Barone, Angela, Marieiro, Mariana, Puddu, Anthony, Arya, Zobair, Ferreira, Carlos, Ridgway, Ged, Kelly, Matt, Lamb, Hildo J., Caseiro-Alves, Felipe, Brady, J. Michael, Banerjee, Rajarshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8776724/
https://www.ncbi.nlm.nih.gov/pubmed/34605963
http://dx.doi.org/10.1007/s00261-021-03262-x
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author Mojtahed, Amirkasra
Núñez, Luis
Connell, John
Fichera, Alessandro
Nicholls, Rowan
Barone, Angela
Marieiro, Mariana
Puddu, Anthony
Arya, Zobair
Ferreira, Carlos
Ridgway, Ged
Kelly, Matt
Lamb, Hildo J.
Caseiro-Alves, Felipe
Brady, J. Michael
Banerjee, Rajarshi
author_facet Mojtahed, Amirkasra
Núñez, Luis
Connell, John
Fichera, Alessandro
Nicholls, Rowan
Barone, Angela
Marieiro, Mariana
Puddu, Anthony
Arya, Zobair
Ferreira, Carlos
Ridgway, Ged
Kelly, Matt
Lamb, Hildo J.
Caseiro-Alves, Felipe
Brady, J. Michael
Banerjee, Rajarshi
author_sort Mojtahed, Amirkasra
collection PubMed
description PURPOSE: Volumetric and health assessment of the liver is crucial to avoid poor post-operative outcomes following liver resection surgery. No current methods allow for concurrent and accurate measurement of both Couinaud segmental volumes for future liver remnant estimation and liver health using non-invasive imaging. In this study, we demonstrate the accuracy and precision of segmental volume measurements using new medical software, Hepatica™. METHODS: MRI scans from 48 volunteers from three previous studies were used in this analysis. Measurements obtained from Hepatica™ were compared with OsiriX. Time required per case with each software was also compared. The performance of technicians and experienced radiologists as well as the repeatability and reproducibility were compared using Bland–Altman plots and limits of agreement. RESULTS: High levels of agreement and lower inter-operator variability for liver volume measurements were shown between Hepatica™ and existing methods for liver volumetry (mean Dice score 0.947 ± 0.010). A high consistency between technicians and experienced radiologists using the device for volumetry was shown (± 3.5% of total liver volume) as well as low inter-observer and intra-observer variability. Tight limits of agreement were shown between repeated Couinaud segment volume (+ 3.4% of whole liver), segmental liver fibroinflammation and segmental liver fat measurements in the same participant on the same scanner and between different scanners. An underestimation of whole-liver volume was observed between three non-reference scanners. CONCLUSION: Hepatica™ produces accurate and precise whole-liver and Couinaud segment volume and liver tissue characteristic measurements. Measurements are consistent between trained technicians and experienced radiologists. GRAPHIC ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00261-021-03262-x.
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spelling pubmed-87767242022-02-02 Repeatability and reproducibility of deep-learning-based liver volume and Couinaud segment volume measurement tool Mojtahed, Amirkasra Núñez, Luis Connell, John Fichera, Alessandro Nicholls, Rowan Barone, Angela Marieiro, Mariana Puddu, Anthony Arya, Zobair Ferreira, Carlos Ridgway, Ged Kelly, Matt Lamb, Hildo J. Caseiro-Alves, Felipe Brady, J. Michael Banerjee, Rajarshi Abdom Radiol (NY) Hepatobiliary PURPOSE: Volumetric and health assessment of the liver is crucial to avoid poor post-operative outcomes following liver resection surgery. No current methods allow for concurrent and accurate measurement of both Couinaud segmental volumes for future liver remnant estimation and liver health using non-invasive imaging. In this study, we demonstrate the accuracy and precision of segmental volume measurements using new medical software, Hepatica™. METHODS: MRI scans from 48 volunteers from three previous studies were used in this analysis. Measurements obtained from Hepatica™ were compared with OsiriX. Time required per case with each software was also compared. The performance of technicians and experienced radiologists as well as the repeatability and reproducibility were compared using Bland–Altman plots and limits of agreement. RESULTS: High levels of agreement and lower inter-operator variability for liver volume measurements were shown between Hepatica™ and existing methods for liver volumetry (mean Dice score 0.947 ± 0.010). A high consistency between technicians and experienced radiologists using the device for volumetry was shown (± 3.5% of total liver volume) as well as low inter-observer and intra-observer variability. Tight limits of agreement were shown between repeated Couinaud segment volume (+ 3.4% of whole liver), segmental liver fibroinflammation and segmental liver fat measurements in the same participant on the same scanner and between different scanners. An underestimation of whole-liver volume was observed between three non-reference scanners. CONCLUSION: Hepatica™ produces accurate and precise whole-liver and Couinaud segment volume and liver tissue characteristic measurements. Measurements are consistent between trained technicians and experienced radiologists. GRAPHIC ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00261-021-03262-x. Springer US 2021-10-04 2022 /pmc/articles/PMC8776724/ /pubmed/34605963 http://dx.doi.org/10.1007/s00261-021-03262-x 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
Mojtahed, Amirkasra
Núñez, Luis
Connell, John
Fichera, Alessandro
Nicholls, Rowan
Barone, Angela
Marieiro, Mariana
Puddu, Anthony
Arya, Zobair
Ferreira, Carlos
Ridgway, Ged
Kelly, Matt
Lamb, Hildo J.
Caseiro-Alves, Felipe
Brady, J. Michael
Banerjee, Rajarshi
Repeatability and reproducibility of deep-learning-based liver volume and Couinaud segment volume measurement tool
title Repeatability and reproducibility of deep-learning-based liver volume and Couinaud segment volume measurement tool
title_full Repeatability and reproducibility of deep-learning-based liver volume and Couinaud segment volume measurement tool
title_fullStr Repeatability and reproducibility of deep-learning-based liver volume and Couinaud segment volume measurement tool
title_full_unstemmed Repeatability and reproducibility of deep-learning-based liver volume and Couinaud segment volume measurement tool
title_short Repeatability and reproducibility of deep-learning-based liver volume and Couinaud segment volume measurement tool
title_sort repeatability and reproducibility of deep-learning-based liver volume and couinaud segment volume measurement tool
topic Hepatobiliary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8776724/
https://www.ncbi.nlm.nih.gov/pubmed/34605963
http://dx.doi.org/10.1007/s00261-021-03262-x
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