Quantification of heterogeneity in dynamic contrast enhanced MRI data for tumor treatment assessment

L. Alić; J. Veenland; M. van Vliet; C.F. van Dijke; A.M.M. Eggermont; W.J. Niessen

doi:10.1109/ISBI.2006.1625075

Quantification of heterogeneity in dynamic contrast enhanced MRI data for tumor treatment assessment

L. Alić^*, J. Veenland, M. van Vliet, C.F. van Dijke, A.M.M. Eggermont, W.J. Niessen

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

8 Citations (Scopus)

Abstract

Experimental evidence exists that especially the heterogeneity in contrast enhancement as evaluated by Dynamic Contrast Enhanced MRI (DCE-MRI) is a predictive feature for treatment outcome in a variety of tumor types. In this study it is investigated whether texture descriptors derived from DCE-MRI based heuristic feature maps are suitable to quantify the heterogeneity in contrast uptake. An automated analysis method is proposed that for each voxel first partitions the signal intensity curve into different temporal regions indicating different stages of enhancement. Within these regions, heuristic features describing the contrast dynamics are estimated. The corresponding features maps are used as the basis for texture analysis, based on cooccurrence matrices, to assess tumor contrast uptake heterogeneity. The method has been applied in pre- and post treatment DCE-MRI data in ten patients with soft tissue sarcomas who underwent Isolated Limb Perfusion. The correspondence between texture measures and the heterogeneity in contrast uptake as visually assessed by a radiologist has been evaluated, and the ability of the texture measures to discriminate between two treatment outcome classes has been assessed. The preliminary results suggest that some of the proposed texture measures are suitable to quantify the heterogeneity in contrast uptake in tumor tissue.

Original language	English
Title of host publication	2006 3rd IEEE International Symposium on Biomedical Imaging
Subtitle of host publication	From Nano to Macro - Proceedings
Place of Publication	Piscataway, NJ
Publisher	IEEE
Pages	944-947
Number of pages	4
ISBN (Electronic)	0-7803-9577-8, 9780780395770
ISBN (Print)	0-7803-9576-X
DOIs	https://doi.org/10.1109/ISBI.2006.1625075
Publication status	Published - 17 Nov 2006
Externally published	Yes
Event	2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Arlington, United States Duration: 6 Apr 2006 → 9 Apr 2006 Conference number: 3

Publication series

Name	IEEE International Symposium on Biomedical Imaging
Publisher	IEEE
Volume	2006
ISSN (Print)	1945-7928
ISSN (Electronic)	1945-8452

Conference

Conference	2006 3rd IEEE International Symposium on Biomedical Imaging
Country/Territory	United States
City	Arlington
Period	6/04/06 → 9/04/06

Keywords

Magnetic resonance imaging
Neoplasms
Biomedical imaging
Biomedical measurements
Cancer
Biological tissues
Radiology
Oncological surgery
Oncology
Medical diagnostic imaging

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/ISBI.2006.1625075

Cite this

Alić, L., Veenland, J., van Vliet, M., van Dijke, C. F., Eggermont, A. M. M., & Niessen, W. J. (2006). Quantification of heterogeneity in dynamic contrast enhanced MRI data for tumor treatment assessment. In 2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings (pp. 944-947). Article 162575 (IEEE International Symposium on Biomedical Imaging; Vol. 2006). IEEE. https://doi.org/10.1109/ISBI.2006.1625075

@inproceedings{cd396545bf4248c5b2f96654030077f7,

title = "Quantification of heterogeneity in dynamic contrast enhanced MRI data for tumor treatment assessment",

abstract = "Experimental evidence exists that especially the heterogeneity in contrast enhancement as evaluated by Dynamic Contrast Enhanced MRI (DCE-MRI) is a predictive feature for treatment outcome in a variety of tumor types. In this study it is investigated whether texture descriptors derived from DCE-MRI based heuristic feature maps are suitable to quantify the heterogeneity in contrast uptake. An automated analysis method is proposed that for each voxel first partitions the signal intensity curve into different temporal regions indicating different stages of enhancement. Within these regions, heuristic features describing the contrast dynamics are estimated. The corresponding features maps are used as the basis for texture analysis, based on cooccurrence matrices, to assess tumor contrast uptake heterogeneity. The method has been applied in pre- and post treatment DCE-MRI data in ten patients with soft tissue sarcomas who underwent Isolated Limb Perfusion. The correspondence between texture measures and the heterogeneity in contrast uptake as visually assessed by a radiologist has been evaluated, and the ability of the texture measures to discriminate between two treatment outcome classes has been assessed. The preliminary results suggest that some of the proposed texture measures are suitable to quantify the heterogeneity in contrast uptake in tumor tissue.",

keywords = "Magnetic resonance imaging, Neoplasms, Biomedical imaging, Biomedical measurements, Cancer, Biological tissues, Radiology, Oncological surgery, Oncology, Medical diagnostic imaging",

author = "L. Ali{\'c} and J. Veenland and {van Vliet}, M. and {van Dijke}, C.F. and A.M.M. Eggermont and W.J. Niessen",

year = "2006",

month = nov,

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doi = "10.1109/ISBI.2006.1625075",

language = "English",

isbn = "0-7803-9576-X",

series = "IEEE International Symposium on Biomedical Imaging",

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Alić, L, Veenland, J, van Vliet, M, van Dijke, CF, Eggermont, AMM & Niessen, WJ 2006, Quantification of heterogeneity in dynamic contrast enhanced MRI data for tumor treatment assessment. in 2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings., 162575, IEEE International Symposium on Biomedical Imaging, vol. 2006, IEEE, Piscataway, NJ, pp. 944-947, 2006 3rd IEEE International Symposium on Biomedical Imaging, Arlington, Virginia, United States, 6/04/06. https://doi.org/10.1109/ISBI.2006.1625075

Quantification of heterogeneity in dynamic contrast enhanced MRI data for tumor treatment assessment. / Alić, L.; Veenland, J.; van Vliet, M. et al.
2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings. Piscataway, NJ: IEEE, 2006. p. 944-947 162575 (IEEE International Symposium on Biomedical Imaging; Vol. 2006).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Quantification of heterogeneity in dynamic contrast enhanced MRI data for tumor treatment assessment

AU - Alić, L.

AU - Veenland, J.

AU - van Vliet, M.

AU - van Dijke, C.F.

AU - Eggermont, A.M.M.

AU - Niessen, W.J.

N1 - Conference code: 3

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N2 - Experimental evidence exists that especially the heterogeneity in contrast enhancement as evaluated by Dynamic Contrast Enhanced MRI (DCE-MRI) is a predictive feature for treatment outcome in a variety of tumor types. In this study it is investigated whether texture descriptors derived from DCE-MRI based heuristic feature maps are suitable to quantify the heterogeneity in contrast uptake. An automated analysis method is proposed that for each voxel first partitions the signal intensity curve into different temporal regions indicating different stages of enhancement. Within these regions, heuristic features describing the contrast dynamics are estimated. The corresponding features maps are used as the basis for texture analysis, based on cooccurrence matrices, to assess tumor contrast uptake heterogeneity. The method has been applied in pre- and post treatment DCE-MRI data in ten patients with soft tissue sarcomas who underwent Isolated Limb Perfusion. The correspondence between texture measures and the heterogeneity in contrast uptake as visually assessed by a radiologist has been evaluated, and the ability of the texture measures to discriminate between two treatment outcome classes has been assessed. The preliminary results suggest that some of the proposed texture measures are suitable to quantify the heterogeneity in contrast uptake in tumor tissue.

AB - Experimental evidence exists that especially the heterogeneity in contrast enhancement as evaluated by Dynamic Contrast Enhanced MRI (DCE-MRI) is a predictive feature for treatment outcome in a variety of tumor types. In this study it is investigated whether texture descriptors derived from DCE-MRI based heuristic feature maps are suitable to quantify the heterogeneity in contrast uptake. An automated analysis method is proposed that for each voxel first partitions the signal intensity curve into different temporal regions indicating different stages of enhancement. Within these regions, heuristic features describing the contrast dynamics are estimated. The corresponding features maps are used as the basis for texture analysis, based on cooccurrence matrices, to assess tumor contrast uptake heterogeneity. The method has been applied in pre- and post treatment DCE-MRI data in ten patients with soft tissue sarcomas who underwent Isolated Limb Perfusion. The correspondence between texture measures and the heterogeneity in contrast uptake as visually assessed by a radiologist has been evaluated, and the ability of the texture measures to discriminate between two treatment outcome classes has been assessed. The preliminary results suggest that some of the proposed texture measures are suitable to quantify the heterogeneity in contrast uptake in tumor tissue.

KW - Magnetic resonance imaging

KW - Neoplasms

KW - Biomedical imaging

KW - Biomedical measurements

KW - Cancer

KW - Biological tissues

KW - Radiology

KW - Oncological surgery

KW - Oncology

KW - Medical diagnostic imaging

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DO - 10.1109/ISBI.2006.1625075

M3 - Conference contribution

AN - SCOPUS:33750956918

SN - 0-7803-9576-X

T3 - IEEE International Symposium on Biomedical Imaging

SP - 944

EP - 947

BT - 2006 3rd IEEE International Symposium on Biomedical Imaging

PB - IEEE

CY - Piscataway, NJ

T2 - 2006 3rd IEEE International Symposium on Biomedical Imaging

Y2 - 6 April 2006 through 9 April 2006

ER -

Alić L, Veenland J, van Vliet M, van Dijke CF, Eggermont AMM, Niessen WJ. Quantification of heterogeneity in dynamic contrast enhanced MRI data for tumor treatment assessment. In 2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings. Piscataway, NJ: IEEE. 2006. p. 944-947. 162575. (IEEE International Symposium on Biomedical Imaging). doi: 10.1109/ISBI.2006.1625075

Quantification of heterogeneity in dynamic contrast enhanced MRI data for tumor treatment assessment

Abstract

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Keywords

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