A new similarity metric for groupwise registration of variable flip angle sequences for improved T10 estimation in DCE-MRI

Andre Hallack; Michael A. Chappell; Mark J. Gooding; Julia A. Schnabel

doi:10.1007/978-3-319-08554-8_16

A new similarity metric for groupwise registration of variable flip angle sequences for improved T₁₀ estimation in DCE-MRI

Andre Hallack
, Michael A. Chappell
, Mark J. Gooding
, Julia A. Schnabel

University of Oxford
Mirada Medical Limited

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

8 Scopus citations

Abstract

Relaxation time (T₁₀) estimation using variable flip angle sequences is a key step for pharmacokinetic (PK) analysis of tumours in DCE-MRI exams. In this study, the effects of motion within flip angle sequences on the T₁₀ and subsequent K_trans and k_ep estimation were examined. It was found that errors in T₁₀ estimation caused by motion had a significant impact on subsequent PK analysis. A new similarity metric, based on the T₁₀ regression error, for groupwise motion correction of variable flip angle sequences is proposed and compared against Groupwise Normalized Mutual Information (GNMI). In rigid registration experiments on simulated data, the new metric outperformed GNMI, showing an improvement alignment of over 14% in terms of average target registration error, which is also reflected by a lower T₁₀ estimation error. Finally, registration was applied to 46 clinical sequences to identify the average amount of motion found in this type of acquisition; this showed an estimated displacement of 0.98mm, which could lead to over 25% K_trans estimation error if motion were not corrected.

Original language	English
Title of host publication	Biomedical Image Registration - 6th International Workshop, WBIR 2014, Proceedings
Publisher	Springer Verlag
Pages	154-163
Number of pages	10
ISBN (Print)	9783319085531
DOIs	https://doi.org/10.1007/978-3-319-08554-8_16
State	Published - 2014
Externally published	Yes
Event	6th International Workshop on Biomedical Image Registration, WBIR 2014 - London, United Kingdom Duration: 7 Jul 2014 → 8 Jul 2014

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8545 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	6th International Workshop on Biomedical Image Registration, WBIR 2014
Country/Territory	United Kingdom
City	London
Period	7/07/14 → 8/07/14

Access to Document

10.1007/978-3-319-08554-8_16

Cite this

Hallack, A., Chappell, M. A., Gooding, M. J., & Schnabel, J. A. (2014). A new similarity metric for groupwise registration of variable flip angle sequences for improved T₁₀ estimation in DCE-MRI. In Biomedical Image Registration - 6th International Workshop, WBIR 2014, Proceedings (pp. 154-163). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8545 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-08554-8_16

Hallack, Andre ; Chappell, Michael A. ; Gooding, Mark J. et al. / A new similarity metric for groupwise registration of variable flip angle sequences for improved T₁₀ estimation in DCE-MRI. Biomedical Image Registration - 6th International Workshop, WBIR 2014, Proceedings. Springer Verlag, 2014. pp. 154-163 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{12cde0c5e99b4213b4ea3205dd47d5ce,

title = "A new similarity metric for groupwise registration of variable flip angle sequences for improved T10 estimation in DCE-MRI",

abstract = "Relaxation time (T10) estimation using variable flip angle sequences is a key step for pharmacokinetic (PK) analysis of tumours in DCE-MRI exams. In this study, the effects of motion within flip angle sequences on the T10 and subsequent Ktrans and kep estimation were examined. It was found that errors in T10 estimation caused by motion had a significant impact on subsequent PK analysis. A new similarity metric, based on the T10 regression error, for groupwise motion correction of variable flip angle sequences is proposed and compared against Groupwise Normalized Mutual Information (GNMI). In rigid registration experiments on simulated data, the new metric outperformed GNMI, showing an improvement alignment of over 14\% in terms of average target registration error, which is also reflected by a lower T10 estimation error. Finally, registration was applied to 46 clinical sequences to identify the average amount of motion found in this type of acquisition; this showed an estimated displacement of 0.98mm, which could lead to over 25\% Ktrans estimation error if motion were not corrected.",

author = "Andre Hallack and Chappell, \{Michael A.\} and Gooding, \{Mark J.\} and Schnabel, \{Julia A.\}",

year = "2014",

doi = "10.1007/978-3-319-08554-8\_16",

language = "English",

isbn = "9783319085531",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "154--163",

booktitle = "Biomedical Image Registration - 6th International Workshop, WBIR 2014, Proceedings",

note = "6th International Workshop on Biomedical Image Registration, WBIR 2014 ; Conference date: 07-07-2014 Through 08-07-2014",

}

Hallack, A, Chappell, MA, Gooding, MJ & Schnabel, JA 2014, A new similarity metric for groupwise registration of variable flip angle sequences for improved T₁₀ estimation in DCE-MRI. in Biomedical Image Registration - 6th International Workshop, WBIR 2014, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8545 LNCS, Springer Verlag, pp. 154-163, 6th International Workshop on Biomedical Image Registration, WBIR 2014, London, United Kingdom, 7/07/14. https://doi.org/10.1007/978-3-319-08554-8_16

A new similarity metric for groupwise registration of variable flip angle sequences for improved T₁₀ estimation in DCE-MRI. / Hallack, Andre; Chappell, Michael A.; Gooding, Mark J. et al.
Biomedical Image Registration - 6th International Workshop, WBIR 2014, Proceedings. Springer Verlag, 2014. p. 154-163 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8545 LNCS).

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

TY - GEN

T1 - A new similarity metric for groupwise registration of variable flip angle sequences for improved T10 estimation in DCE-MRI

AU - Hallack, Andre

AU - Chappell, Michael A.

AU - Gooding, Mark J.

AU - Schnabel, Julia A.

PY - 2014

Y1 - 2014

N2 - Relaxation time (T10) estimation using variable flip angle sequences is a key step for pharmacokinetic (PK) analysis of tumours in DCE-MRI exams. In this study, the effects of motion within flip angle sequences on the T10 and subsequent Ktrans and kep estimation were examined. It was found that errors in T10 estimation caused by motion had a significant impact on subsequent PK analysis. A new similarity metric, based on the T10 regression error, for groupwise motion correction of variable flip angle sequences is proposed and compared against Groupwise Normalized Mutual Information (GNMI). In rigid registration experiments on simulated data, the new metric outperformed GNMI, showing an improvement alignment of over 14% in terms of average target registration error, which is also reflected by a lower T10 estimation error. Finally, registration was applied to 46 clinical sequences to identify the average amount of motion found in this type of acquisition; this showed an estimated displacement of 0.98mm, which could lead to over 25% Ktrans estimation error if motion were not corrected.

AB - Relaxation time (T10) estimation using variable flip angle sequences is a key step for pharmacokinetic (PK) analysis of tumours in DCE-MRI exams. In this study, the effects of motion within flip angle sequences on the T10 and subsequent Ktrans and kep estimation were examined. It was found that errors in T10 estimation caused by motion had a significant impact on subsequent PK analysis. A new similarity metric, based on the T10 regression error, for groupwise motion correction of variable flip angle sequences is proposed and compared against Groupwise Normalized Mutual Information (GNMI). In rigid registration experiments on simulated data, the new metric outperformed GNMI, showing an improvement alignment of over 14% in terms of average target registration error, which is also reflected by a lower T10 estimation error. Finally, registration was applied to 46 clinical sequences to identify the average amount of motion found in this type of acquisition; this showed an estimated displacement of 0.98mm, which could lead to over 25% Ktrans estimation error if motion were not corrected.

UR - https://www.scopus.com/pages/publications/84903709057

U2 - 10.1007/978-3-319-08554-8_16

DO - 10.1007/978-3-319-08554-8_16

M3 - Conference contribution

AN - SCOPUS:84903709057

SN - 9783319085531

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 154

EP - 163

BT - Biomedical Image Registration - 6th International Workshop, WBIR 2014, Proceedings

PB - Springer Verlag

T2 - 6th International Workshop on Biomedical Image Registration, WBIR 2014

Y2 - 7 July 2014 through 8 July 2014

ER -

Hallack A, Chappell MA, Gooding MJ, Schnabel JA. A new similarity metric for groupwise registration of variable flip angle sequences for improved T₁₀ estimation in DCE-MRI. In Biomedical Image Registration - 6th International Workshop, WBIR 2014, Proceedings. Springer Verlag. 2014. p. 154-163. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-08554-8_16