Automated identification of brain new lesions in multiple sclerosis using subtraction images. Issue 6 (31st October 2013)
- Record Type:
- Journal Article
- Title:
- Automated identification of brain new lesions in multiple sclerosis using subtraction images. Issue 6 (31st October 2013)
- Main Title:
- Automated identification of brain new lesions in multiple sclerosis using subtraction images
- Authors:
- Battaglini, Marco
Rossi, Francesca
Grove, Richard A.
Stromillo, Maria Laura
Whitcher, Brandon
Matthews, Paul M.
De Stefano, Nicola - Abstract:
- Abstract : Purpose: To propose and evaluate a new automated method for the identification of new/enlarging multiple sclerosis (MS) lesions on subtracted images (SI). The subtraction of serially acquired images has shown great potential in assessing new/enlarging brain magnetic resonance imaging (MRI) lesions in MS patients. However, this approach relies on the manual definition of lesions, which is labor‐intensive and subject to operator‐dependent variability. Materials and Methods: An overestimated mask of candidate SI lesions was created and then these hyperintense voxel clusters were filtered using specific constraints for extent, shape, and intensity. The method was tested on normal and pathological MRI datasets. Results: The automated method did not detect hyperintense voxels on SI of healthy controls. SI lesions were identified manually and automatically in a multicenter MS dataset of 19 patients with paired MRI over 36 weeks. Sensitivity of the method was high (0.91) and in agreement with the results of manually defined SI lesions (Cohen's k = 0.82, 95% confidence interval [CI]: 0.77–0.87). On a second multicenter MS dataset of 103 patients with paired MRI over 76 weeks, the number of SI lesions detected automatically correlated with the number of gadolinium‐enhancing lesions ( r = 0.74). Conclusion: The proposed method is robust, accurate, and sensitive and may be used with confidence in Phase II MS trials.J. Magn. Reson. Imaging 2014;39:1543–1549 . ©2013 WileyAbstract : Purpose: To propose and evaluate a new automated method for the identification of new/enlarging multiple sclerosis (MS) lesions on subtracted images (SI). The subtraction of serially acquired images has shown great potential in assessing new/enlarging brain magnetic resonance imaging (MRI) lesions in MS patients. However, this approach relies on the manual definition of lesions, which is labor‐intensive and subject to operator‐dependent variability. Materials and Methods: An overestimated mask of candidate SI lesions was created and then these hyperintense voxel clusters were filtered using specific constraints for extent, shape, and intensity. The method was tested on normal and pathological MRI datasets. Results: The automated method did not detect hyperintense voxels on SI of healthy controls. SI lesions were identified manually and automatically in a multicenter MS dataset of 19 patients with paired MRI over 36 weeks. Sensitivity of the method was high (0.91) and in agreement with the results of manually defined SI lesions (Cohen's k = 0.82, 95% confidence interval [CI]: 0.77–0.87). On a second multicenter MS dataset of 103 patients with paired MRI over 76 weeks, the number of SI lesions detected automatically correlated with the number of gadolinium‐enhancing lesions ( r = 0.74). Conclusion: The proposed method is robust, accurate, and sensitive and may be used with confidence in Phase II MS trials.J. Magn. Reson. Imaging 2014;39:1543–1549 . ©2013 Wiley Periodicals, Inc . … (more)
- Is Part Of:
- Journal of magnetic resonance imaging. Volume 39:Issue 6(2014)
- Journal:
- Journal of magnetic resonance imaging
- Issue:
- Volume 39:Issue 6(2014)
- Issue Display:
- Volume 39, Issue 6 (2014)
- Year:
- 2014
- Volume:
- 39
- Issue:
- 6
- Issue Sort Value:
- 2014-0039-0006-0000
- Page Start:
- 1543
- Page End:
- 1549
- Publication Date:
- 2013-10-31
- Subjects:
- multiple sclerosis -- white matter lesions -- subtraction images -- MRI -- active lesions
Magnetic resonance imaging -- Periodicals
616 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1522-2586 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/jmri.24293 ↗
- Languages:
- English
- ISSNs:
- 1053-1807
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5010.791000
British Library DSC - BLDSS-3PM
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- 8103.xml