2021
DOI: 10.1007/s00261-021-03262-x
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Repeatability and reproducibility of deep-learning-based liver volume and Couinaud segment volume measurement tool

Abstract: 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 … Show more

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Cited by 21 publications
(13 citation statements)
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“…Thus, our findings require further validation in patients with liver disease due to other etiologic causes. Third, a threshold of ± 13% for ΔLS-VR was chosen based on the reported reproducibility range of liver volume measurements [ 20 ], which may not address the measurement error range of LS-VR. To determine a reliable threshold for ΔLS VR, the reproducibility of MRI-based LS VR measurements needs to be determined in a future study.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Thus, our findings require further validation in patients with liver disease due to other etiologic causes. Third, a threshold of ± 13% for ΔLS-VR was chosen based on the reported reproducibility range of liver volume measurements [ 20 ], which may not address the measurement error range of LS-VR. To determine a reliable threshold for ΔLS VR, the reproducibility of MRI-based LS VR measurements needs to be determined in a future study.…”
Section: Discussionmentioning
confidence: 99%
“…Following univariable analysis, multivariable analysis was performed using two models; the baseline multivariable model included baseline MRI indices (LS-SIR and LS-VR) and clinical variables alone that showed p < 0.1 at the univariable analysis, whereas the follow-up multivariable model included both follow-up MRI indices (ΔLS-SIR and ΔLS-VR) and the variables in the baseline multivariable model. The ΔLS-VR was categorized as < -13%, -13% to 13%, and > 13%, and a threshold of ± 13% was chosen based on the reported reproducibility range of MRI-based volume measurement in a previous study [ 20 ]. The optimal cutoff values for the other MRI indices were determined using the minimum Wald p value method in the Cox model [ 21 ].…”
Section: Methodsmentioning
confidence: 99%
“…Mojtahed et al reported that the DL-based segmentation technique had a high consistency to experienced radiologists and each liver segment volume (± 3.5% of the total liver volume). 35 …”
Section: Use Of Machine Learning and Deep Learning For Diagnosis Via ...mentioning
confidence: 99%
“…At this visit, participants will be invited for an abdominal non-contrast enhanced MRI scan. Images will be processed to generate metrics indicating the liver tissue characteristics (Liver MultiScan ) and future liver remnant volume (Hepatica) as previously described 12…”
Section: Study Assessments and Data Collectionmentioning
confidence: 99%