Task-based optimization of flip angle for texture analysis in MRI

Jonathan F. Brand; Lars R. Furenlid; Maria I. Altbach; Jean Phillippe Galons; Achyut Bhattacharyya; Puneet Sharma; Tulshi Bhattacharyya; Ali Bilgin; Diego R. Martin

doi:10.1117/12.2214564

Task-based optimization of flip angle for texture analysis in MRI

Jonathan F. Brand, Lars R. Furenlid, Maria I. Altbach, Jean Phillippe Galons, Achyut Bhattacharyya, Puneet Sharma, Tulshi Bhattacharyya, Ali Bilgin, Diego R. Martin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Chronic liver disease is a worldwide health problem, and hepatic fibrosis (HF) is one of the hallmarks of the disease. The current reference standard for diagnosing HF is biopsy followed by pathologist examination, however this is limited by sampling error and carries risk of complications. Pathology diagnosis of HF is based on textural change in the liver as a lobular collagen network that develops within portal triads. The scale of collagen lobules is characteristically on order of 1-5 mm, which approximates the resolution limit of in vivo gadolinium-enhanced magnetic resonance imaging in the delayed phase. We have shown that MRI of formalin fixed human ex vivo liver samples mimic the textural contrast of in vivo Gd-MRI and can be used as MRI phantoms. We have developed local texture analysis that is applied to phantom images, and the results are used to train model observers. The performance of the observer is assessed with the area-under-the-receiveroperator- characteristic curve (AUROC) as the figure of merit. To optimize the MRI pulse sequence, phantoms are scanned with multiple times at a range of flip angles. The flip angle that associated with the highest AUROC is chosen as optimal based on the task of detecting HF.

Original language	English (US)
Title of host publication	Medical Imaging 2016
Subtitle of host publication	Image Perception, Observer Performance, and Technology Assessment
Editors	Craig K. Abbey, Matthew A. Kupinski
Publisher	SPIE
ISBN (Electronic)	9781510600225
DOIs	https://doi.org/10.1117/12.2214564
State	Published - 2016
Event	Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment - San Diego, United States Duration: Mar 2 2016 → Mar 3 2016

Publication series

Name	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	9787
ISSN (Print)	1605-7422

Conference

Conference	Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment
Country/Territory	United States
City	San Diego
Period	3/2/16 → 3/3/16

Keywords

Hepatic fibrosis
Hotelling observer
Liver
MRI
Magnetic resonance imaging
Optimization
Texture analysis

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Atomic and Molecular Physics, and Optics
Biomaterials
Radiology Nuclear Medicine and imaging

Access to Document

10.1117/12.2214564

Cite this

Brand, J. F., Furenlid, L. R., Altbach, M. I., Galons, J. P., Bhattacharyya, A., Sharma, P., Bhattacharyya, T., Bilgin, A., & Martin, D. R. (2016). Task-based optimization of flip angle for texture analysis in MRI. In C. K. Abbey, & M. A. Kupinski (Eds.), Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment Article 97870B (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 9787). SPIE. https://doi.org/10.1117/12.2214564

Task-based optimization of flip angle for texture analysis in MRI. / Brand, Jonathan F.; Furenlid, Lars R.; Altbach, Maria I. et al.
Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment. ed. / Craig K. Abbey; Matthew A. Kupinski. SPIE, 2016. 97870B (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 9787).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Brand, JF, Furenlid, LR, Altbach, MI, Galons, JP, Bhattacharyya, A, Sharma, P, Bhattacharyya, T, Bilgin, A & Martin, DR 2016, Task-based optimization of flip angle for texture analysis in MRI. in CK Abbey & MA Kupinski (eds), Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment., 97870B, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 9787, SPIE, Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, San Diego, United States, 3/2/16. https://doi.org/10.1117/12.2214564

Brand JF, Furenlid LR, Altbach MI, Galons JP, Bhattacharyya A, Sharma P et al. Task-based optimization of flip angle for texture analysis in MRI. In Abbey CK, Kupinski MA, editors, Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment. SPIE. 2016. 97870B. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE). doi: 10.1117/12.2214564

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abstract = "Chronic liver disease is a worldwide health problem, and hepatic fibrosis (HF) is one of the hallmarks of the disease. The current reference standard for diagnosing HF is biopsy followed by pathologist examination, however this is limited by sampling error and carries risk of complications. Pathology diagnosis of HF is based on textural change in the liver as a lobular collagen network that develops within portal triads. The scale of collagen lobules is characteristically on order of 1-5 mm, which approximates the resolution limit of in vivo gadolinium-enhanced magnetic resonance imaging in the delayed phase. We have shown that MRI of formalin fixed human ex vivo liver samples mimic the textural contrast of in vivo Gd-MRI and can be used as MRI phantoms. We have developed local texture analysis that is applied to phantom images, and the results are used to train model observers. The performance of the observer is assessed with the area-under-the-receiveroperator- characteristic curve (AUROC) as the figure of merit. To optimize the MRI pulse sequence, phantoms are scanned with multiple times at a range of flip angles. The flip angle that associated with the highest AUROC is chosen as optimal based on the task of detecting HF.",

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AB - Chronic liver disease is a worldwide health problem, and hepatic fibrosis (HF) is one of the hallmarks of the disease. The current reference standard for diagnosing HF is biopsy followed by pathologist examination, however this is limited by sampling error and carries risk of complications. Pathology diagnosis of HF is based on textural change in the liver as a lobular collagen network that develops within portal triads. The scale of collagen lobules is characteristically on order of 1-5 mm, which approximates the resolution limit of in vivo gadolinium-enhanced magnetic resonance imaging in the delayed phase. We have shown that MRI of formalin fixed human ex vivo liver samples mimic the textural contrast of in vivo Gd-MRI and can be used as MRI phantoms. We have developed local texture analysis that is applied to phantom images, and the results are used to train model observers. The performance of the observer is assessed with the area-under-the-receiveroperator- characteristic curve (AUROC) as the figure of merit. To optimize the MRI pulse sequence, phantoms are scanned with multiple times at a range of flip angles. The flip angle that associated with the highest AUROC is chosen as optimal based on the task of detecting HF.

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Task-based optimization of flip angle for texture analysis in MRI

Abstract

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Conference

Keywords

ASJC Scopus subject areas

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