Automatic scan range for dose-reduced multiphase CT imaging of the liver utilizing CNNs and Gaussian models.

Luu, MH; Walsum, TV; Mai, HS; Franklin, D; Nguyen, TTT; Le, TM; Moelker, A; Le, VK; Vu, DL; Le, NH; Tran, QL; Chu, DT; Trung, NL

Automatic scan range for dose-reduced multiphase CT imaging of the liver utilizing CNNs and Gaussian models.

Luu, MH Walsum, TV Mai, HS Franklin, D

Nguyen, TTT Le, TM Moelker, A Le, VK Vu, DL Le, NH Tran, QL Chu, DT Trung, NL

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Publisher:: Elsevier BV
Publication Type:: Journal Article
Citation:: Med Image Anal, 2022, 78, pp. 102422
Issue Date:: 2022-03-17

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Field	Value	Language
dc.contributor.author	Luu, MH
dc.contributor.author	Walsum, TV
dc.contributor.author	Mai, HS
dc.contributor.author	Franklin, D https://orcid.org/0000-0002-9563-5943
dc.contributor.author	Nguyen, TTT
dc.contributor.author	Le, TM
dc.contributor.author	Moelker, A
dc.contributor.author	Le, VK
dc.contributor.author	Vu, DL
dc.contributor.author	Le, NH
dc.contributor.author	Tran, QL
dc.contributor.author	Chu, DT
dc.contributor.author	Trung, NL
dc.date.accessioned	2022-04-07T08:07:42Z
dc.date.available	2022-03-11
dc.date.available	2022-04-07T08:07:42Z
dc.date.issued	2022-03-17
dc.identifier.citation	Med Image Anal, 2022, 78, pp. 102422
dc.identifier.issn	1361-8415
dc.identifier.issn	1361-8423
dc.identifier.uri	http://hdl.handle.net/10453/155981
dc.description.abstract	Multiphase CT scanning of the liver is performed for several clinical applications; however, radiation exposure from CT scanning poses a nontrivial cancer risk to the patients. The radiation dose may be reduced by determining the scan range of the subsequent scans by the location of the target of interest in the first scan phase. The purpose of this study is to present and assess an automatic method for determining the scan range for multiphase CT scans. Our strategy is to first apply a CNN-based method for detecting the liver in 2D slices, and to use a liver range search algorithm for detecting the liver range in the scout volume. The target liver scan range for subsequent scans can be obtained by adding safety margins achieved from Gaussian liver motion models to the scan range determined from the scout. Experiments were performed on 657 multiphase CT volumes obtained from multiple hospitals. The experiment shows that the proposed liver detection method can detect the liver in 223 out of a total of 224 3D volumes on average within one second, with mean intersection of union, wall distance and centroid distance of 85.5%, 5.7 mm and 9.7 mm, respectively. In addition, the performance of the proposed liver detection method is comparable to the best of the state-of-the-art 3D liver detectors in the liver detection accuracy while it requires less processing time. Furthermore, we apply the liver scan range generation method on the liver CT images acquired from radiofrequency ablation and Y-90 transarterial radioembolization (selective internal radiation therapy) interventions of 46 patients from two hospitals. The result shows that the automatic scan range generation can significantly reduce the effective radiation dose by an average of 14.5% (2.56 mSv) compared to manual performance by the radiographer from Y-90 transarterial radioembolization, while no statistically significant difference in performance was found with the CT images from intra RFA intervention (p = 0.81). Finally, three radiologists assess both the original and the range-reduced images for evaluating the effect of the range reduction method on their clinical decisions. We conclude that the automatic liver scan range generation method is able to reduce excess radiation compared to the manual performance with a high accuracy and without penalizing the clinical decision.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	Elsevier BV
dc.relation.ispartof	Med Image Anal
dc.relation.isbasedon	10.1016/j.media.2022.102422
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.subject	09 Engineering, 11 Medical and Health Sciences
dc.subject.classification	Nuclear Medicine & Medical Imaging
dc.title	Automatic scan range for dose-reduced multiphase CT imaging of the liver utilizing CNNs and Gaussian models.
dc.type	Journal Article
utslib.citation.volume	78
utslib.location.activity	Netherlands
utslib.for	09 Engineering
utslib.for	11 Medical and Health Sciences
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	in_progress	*
dc.date.updated	2022-04-07T08:07:40Z
pubs.publication-status	Published online
pubs.volume	78

Abstract:

Multiphase CT scanning of the liver is performed for several clinical applications; however, radiation exposure from CT scanning poses a nontrivial cancer risk to the patients. The radiation dose may be reduced by determining the scan range of the subsequent scans by the location of the target of interest in the first scan phase. The purpose of this study is to present and assess an automatic method for determining the scan range for multiphase CT scans. Our strategy is to first apply a CNN-based method for detecting the liver in 2D slices, and to use a liver range search algorithm for detecting the liver range in the scout volume. The target liver scan range for subsequent scans can be obtained by adding safety margins achieved from Gaussian liver motion models to the scan range determined from the scout. Experiments were performed on 657 multiphase CT volumes obtained from multiple hospitals. The experiment shows that the proposed liver detection method can detect the liver in 223 out of a total of 224 3D volumes on average within one second, with mean intersection of union, wall distance and centroid distance of 85.5%, 5.7 mm and 9.7 mm, respectively. In addition, the performance of the proposed liver detection method is comparable to the best of the state-of-the-art 3D liver detectors in the liver detection accuracy while it requires less processing time. Furthermore, we apply the liver scan range generation method on the liver CT images acquired from radiofrequency ablation and Y-90 transarterial radioembolization (selective internal radiation therapy) interventions of 46 patients from two hospitals. The result shows that the automatic scan range generation can significantly reduce the effective radiation dose by an average of 14.5% (2.56 mSv) compared to manual performance by the radiographer from Y-90 transarterial radioembolization, while no statistically significant difference in performance was found with the CT images from intra RFA intervention (p = 0.81). Finally, three radiologists assess both the original and the range-reduced images for evaluating the effect of the range reduction method on their clinical decisions. We conclude that the automatic liver scan range generation method is able to reduce excess radiation compared to the manual performance with a high accuracy and without penalizing the clinical decision.

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http://hdl.handle.net/10453/155981