Skip to main content
Advertisement

Main menu

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • AJNR Case Collection
    • Case of the Week Archive
    • Classic Case Archive
    • Case of the Month Archive
  • Special Collections
    • Spinal CSF Leak Articles (Jan 2020-June 2024)
    • 2024 AJNR Journal Awards
    • Most Impactful AJNR Articles
  • Multimedia
    • AJNR Podcast
    • AJNR Scantastics
    • Video Articles
  • For Authors
    • Submit a Manuscript
    • Author Policies
    • Fast publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Manuscript Submission Guidelines
    • Imaging Protocol Submission
    • Submit a Case for the Case Collection
  • About Us
    • About AJNR
    • Editorial Board
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home
  • Other Publications
    • ajnr

User menu

  • Alerts
  • Log in

Search

  • Advanced search
American Journal of Neuroradiology
American Journal of Neuroradiology

American Journal of Neuroradiology

ASHNR American Society of Functional Neuroradiology ASHNR American Society of Pediatric Neuroradiology ASSR
  • Alerts
  • Log in

Advanced Search

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • AJNR Case Collection
    • Case of the Week Archive
    • Classic Case Archive
    • Case of the Month Archive
  • Special Collections
    • Spinal CSF Leak Articles (Jan 2020-June 2024)
    • 2024 AJNR Journal Awards
    • Most Impactful AJNR Articles
  • Multimedia
    • AJNR Podcast
    • AJNR Scantastics
    • Video Articles
  • For Authors
    • Submit a Manuscript
    • Author Policies
    • Fast publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Manuscript Submission Guidelines
    • Imaging Protocol Submission
    • Submit a Case for the Case Collection
  • About Us
    • About AJNR
    • Editorial Board
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home
  • Follow AJNR on Twitter
  • Visit AJNR on Facebook
  • Follow AJNR on Instagram
  • Join AJNR on LinkedIn
  • RSS Feeds

Welcome to the new AJNR, Updated Hall of Fame, and more. Read the full announcements.


AJNR is seeking candidates for the position of Associate Section Editor, AJNR Case Collection. Read the full announcement.

 

Research ArticleBRAIN

Segmentation of Subtraction Images for the Measurement of Lesion Change in Multiple Sclerosis

Y. Duan, P.G. Hildenbrand, M.P. Sampat, D.F. Tate, I. Csapo, B. Moraal, R. Bakshi, F. Barkhof, D.S. Meier and C.R.G. Guttmann
American Journal of Neuroradiology February 2008, 29 (2) 340-346; DOI: https://doi.org/10.3174/ajnr.A0795
Y. Duan
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
P.G. Hildenbrand
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
M.P. Sampat
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
D.F. Tate
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
I. Csapo
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
B. Moraal
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
R. Bakshi
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
F. Barkhof
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
D.S. Meier
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
C.R.G. Guttmann
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Info & Metrics
  • Responses
  • References
  • PDF
Loading

Article Figures & Data

Figures

  • Tables
  • Fig 1.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Fig 1.

    Subtraction of PD images from a 45-year-old male patient with MS scanned at an interval of 4.7 years shows resolving (white arrow and arrowhead), new (black arrowhead), and enlarging (black arrows) lesions. Left column, Baseline MR image. Middle column, Coregistered second time-point MR image. Right column, Subtraction image (time point 2 minus baseline). Subcortical resolving lesion and deep WM resolving lesion in the subtraction image are shown with a white arrowhead and white arrow, respectively. Subtle artifacts are seen on the boundary of the brain surface due to slight misregistration. (In all of the images, the skull has been stripped by masking with ICC.)

  • Fig 2.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Fig 2.

    Yin-Yang artifact: scan-rescan MR images from the same day. Left column, Baseline image (scan). Middle column, Coregistered second time-point image (rescan). Right column, Subtraction image (rescan-scan). Yin-Yang artifacts are shown (white arrows) in the subtraction image (right column). An artifact from vessel misregistration is shown (white arrowhead) in the subtraction image. (In all of the images, the skull has been stripped by masking with ICC.)

  • Fig 3.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Fig 3.

    Positive, negative, and net changes from pairs of subtraction images: the discriminatory power of SSEG. Change measurements obtained from pairs of dual-echo images using CSEG and SSEG methods are depicted. A, Patient-by-patient representation of lesion volume changes measured with SSEG and CSEG in pairs of dual-echo MR images from 21 patients with MS. The CSEG method can only measure the net change in lesion volume (black bar in each patient). In contrast, the SSEG method provides information about the volume change in new (red bars), enlarging (yellow bars), and resolving lesions (blue bars), as well as yielding a net lesion volume change (sum of new and enlarging lesion volumes minus resolving lesion volume; green bars). B, The average lesion volume changes measured with the CSEG and SSEG methods are shown. Greater average net lesion volume change is measured with the SSEG method, although no statistically significant difference is found in the net lesion volume change measured with both methods (P = 0.14, Wilcoxon test).

  • Fig 4.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Fig 4.

    Reproducibility of SSEG and CSEG methods: Bland-Altman analysis in 10 patients (scan-rescan group). The solid line and the 2 dotted lines represent the mean ± 1.96 SD (95% confidence interval) of the difference of rescan lesion volume and baseline lesion volume, respectively. For both measurements, we use the same baseline lesion volume measured by CSEG. A, For the CSEG measurement, we used the baseline and rescan lesion volumes. B, For the SSEG measurement, the rescan lesion volume is the sum of baseline lesion volume (measured by CSEG) and the net change in lesion volume measured by the SSEG method. We see that the SSEG method has smaller confidence intervals, which indicate greater reproducibility.

  • Fig 5.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Fig 5.

    A juxtacortical lesion in a 44-year-old female patient with MS scanned at an interval of 3 years. A new juxtacortical lesion (arrow), difficult to appreciate on the native images and missed by CSEG, is clearly visible on the subtraction image (C) and SSEG (F). Baseline image (A) and its CSEG (D); Coregistered second time-point image (B) and its CSEG (E). The CSEG images were coregistered in this example to allow direct comparison. The CSEG method (D and E) segments CSF (blue), GM (orange), lesion (yellow), and WM (green); and SSEG method (F) only segments new lesion (pink). Subtle artifacts are seen on the boundary of the brain surface due to slight misregistration. (In all of the images, the skull has been stripped by masking with ICC.)

  • Fig 6.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Fig 6.

    Two new cortical lesions and a new deep WM lesion in a 44-year-old female patient with MS scanned at an interval of 3 years. Baseline image (A) and its CSEG (D). Coregistered second time-point image (B) and the registered CSEG (E). Subtraction image (time point 2 minus baseline (C) and its SSEG (F). Two cortical lesions (arrowheads) are misclassified as normal GM with the CSEG method, but the subtraction image clearly shows these lesions. In addition, a new lesion is seen in the left preventricular deep WM (arrow). The CSEG method (D and E) segments CSF (blue), GM (orange), lesion (yellow), and WM (green); and SSEG method (F) only segments new lesions (pink). Subtle artifacts are seen on the boundary of the brain surface due to slight misregistration. (In all of the images, the skull has been stripped by masking with ICC.)

Tables

  • Figures
    • View popup
    Table 1:

    Scan-rescan group lesion volume and interscan coefficient of variation

    MethodsBaseline Lesion Volume, Mean ± SD, cm3Rescan Lesion Volume, Mean ± SD, cm3Average Interscan COV, Mean ± SD, %Lesion Volume Change, Mean ± SD, cm3Percentage of Lesion Volume Change, Mean ± SD, %
    CSEG7.98 ± 6.8*8.50 ± 7.668.64 ± 9.910.77 ± 1.111.40 ± 12.00
    SSEG7.98 ± 6.8*8.12 ± 7.08†0.98 ± 1.550.14 ± 0.281.50 ± 2.30
    • Note:—COV indicates coefficient of variation; CSEG, serial single time-point conventional segmentation; SSEG, segmentation of subtraction images.

    • * The same baseline lesion volume (calculated with CSEG) is used with the 2 methods.

    • † Rescan volume with SSEG = baseline volume (calculated with CSEG) + net lesion volume change (calculated with SSEG); percentage of lesion volume change = lesion volume change/baseline lesion volume.

    • View popup
    Table 2:

    Correlation coefficients between clinical measurements and net lesion volume change and annual lesion volume change per year

    MeasurementNet Lesion Volume Change, cm3Annual Lesion Volume Change, cm3/y
    SSEG, R, PCSEG, R, PSSEG, R, PCSEG, R, P
    Net BPF change−0.446, 0.046*−0.180, 0.421N/AN/A
    Annual BPF changeN/AN/A−0.430, 0.055†−0.232, 0.299
    Interval time between MR imaging scans0.234, 0.2950.151, 0.499N/AN/A
    Disease durationN/AN/A−0.508, 0.023*−0.360, 0.108
    • Note:—CSEG indicates serial single time-point conventional segmentation; SSEG, segmentation of subtraction images; BPF, brain parenchymal fraction; N/A, nonapplicability of a paired correlation. SSEG reveals relationships with net BPF change and disease duration, whereas CSEG does not.

    • * Significant results.

    • † Nearly significant results.

PreviousNext
Back to top

In this issue

American Journal of Neuroradiology: 29 (2)
American Journal of Neuroradiology
Vol. 29, Issue 2
February 2008
  • Table of Contents
  • Index by author
Advertisement
Print
Download PDF
Email Article

Thank you for your interest in spreading the word on American Journal of Neuroradiology.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Segmentation of Subtraction Images for the Measurement of Lesion Change in Multiple Sclerosis
(Your Name) has sent you a message from American Journal of Neuroradiology
(Your Name) thought you would like to see the American Journal of Neuroradiology web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Cite this article
Y. Duan, P.G. Hildenbrand, M.P. Sampat, D.F. Tate, I. Csapo, B. Moraal, R. Bakshi, F. Barkhof, D.S. Meier, C.R.G. Guttmann
Segmentation of Subtraction Images for the Measurement of Lesion Change in Multiple Sclerosis
American Journal of Neuroradiology Feb 2008, 29 (2) 340-346; DOI: 10.3174/ajnr.A0795

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
0 Responses
Respond to this article
Share
Bookmark this article
Segmentation of Subtraction Images for the Measurement of Lesion Change in Multiple Sclerosis
Y. Duan, P.G. Hildenbrand, M.P. Sampat, D.F. Tate, I. Csapo, B. Moraal, R. Bakshi, F. Barkhof, D.S. Meier, C.R.G. Guttmann
American Journal of Neuroradiology Feb 2008, 29 (2) 340-346; DOI: 10.3174/ajnr.A0795
del.icio.us logo Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Purchase

Jump to section

  • Article
    • Abstract
    • Materials and Methods
    • Results
    • Discussion
    • Conclusion
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • Responses
  • References
  • PDF

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • PACS Integration of Semiautomated Imaging Software Improves Day-to-Day MS Disease Activity Detection
  • Food allergies are associated with increased disease activity in multiple sclerosis
  • Detection of Focal Longitudinal Changes in the Brain by Subtraction of MR Images
  • Automatic Lesion Incidence Estimation and Detection in Multiple Sclerosis Using Multisequence Longitudinal MRI
  • One year activity on subtraction MRI predicts subsequent 4 year activity and progression in multiple sclerosis
  • Crossref (25)
  • Google Scholar

This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.

  • MRI in multiple sclerosis: current status and future prospects
    Rohit Bakshi, Alan J Thompson, Maria A Rocca, Daniel Pelletier, Vincent Dousset, Frederik Barkhof, Matilde Inglese, Charles RG Guttmann, Mark A Horsfield, Massimo Filippi
    The Lancet Neurology 2008 7 7
  • Recommendations to improve imaging and analysis of brain lesion load and atrophy in longitudinal studies of multiple sclerosis
    H. Vrenken, M. Jenkinson, M. A. Horsfield, M. Battaglini, R. A. van Schijndel, E. Rostrup, J. J. G. Geurts, E. Fisher, A. Zijdenbos, J. Ashburner, D. H. Miller, M. Filippi, F. Fazekas, M. Rovaris, A. Rovira, F. Barkhof, N. de Stefano
    Journal of Neurology 2013 260 10
  • Automated detection of multiple sclerosis lesions in serial brain MRI
    Xavier Lladó, Onur Ganiler, Arnau Oliver, Robert Martí, Jordi Freixenet, Laia Valls, Joan C. Vilanova, Lluís Ramió-Torrentà, Àlex Rovira
    Neuroradiology 2012 54 8
  • Improved Detection of Active Multiple Sclerosis Lesions: 3D Subtraction Imaging
    Bastiaan Moraal, Mike P. Wattjes, Jeroen J. G. Geurts, Dirk L. Knol, Ronald A. van Schijndel, Petra J. W. Pouwels, Hugo Vrenken, Frederik Barkhof
    Radiology 2010 255 1
  • Automatic Lesion Incidence Estimation and Detection in Multiple Sclerosis Using Multisequence Longitudinal MRI
    E.M. Sweeney, R.T. Shinohara, C.D. Shea, D.S. Reich, C.M. Crainiceanu
    American Journal of Neuroradiology 2013 34 1
  • Intra- and Interobserver Variability of Linear and Volumetric Measurements of Brain Metastases Using Contrast-Enhanced Magnetic Resonance Imaging
    Hans-Christian Bauknecht, Valentina C. Romano, Patrik Rogalla, Randolf Klingebiel, Claudia Wolf, Lars Bornemann, Bernd Hamm, Patrick A. Hein
    Investigative Radiology 2010 45 1
  • Temporally Consistent Probabilistic Detection of New Multiple Sclerosis Lesions in Brain MRI
    Colm Elliott, Douglas L. Arnold, D. Louis Collins, Tal Arbel
    IEEE Transactions on Medical Imaging 2013 32 8
  • Subtraction MR Images in a Multiple Sclerosis Multicenter Clinical Trial Setting
    Bastiaan Moraal, Dominik S. Meier, Peter A. Poppe, Jeroen J. G. Geurts, Hugo Vrenken, William M. A. Jonker, Dirk L. Knol, Ronald A. van Schijndel, Petra J. W. Pouwels, Christoph Pohl, Lars Bauer, Rupert Sandbrink, Charles R. G. Guttmann, Frederik Barkhof
    Radiology 2009 250 2
  • Long‐interval T2‐weighted subtraction magnetic resonance imaging: A powerful new outcome measure in multiple sclerosis trials
    Bastiaan Moraal, Ivo J. van den Elskamp, Dirk L. Knol, Bernard M. J. Uitdehaag, Jeroen J. G. Geurts, Hugo Vrenken, Petra J. W. Pouwels, Ronald A. van Schijndel, Dominik S. Meier, Charles R. G. Guttmann, Frederik Barkhof
    Annals of Neurology 2010 67 5
  • Validation of White-Matter Lesion Change Detection Methods on a Novel Publicly Available MRI Image Database
    Žiga Lesjak, Franjo Pernuš, Boštjan Likar, Žiga Špiclin
    Neuroinformatics 2016 14 4

More in this TOC Section

  • Optimal MRI Sequence for Identifying Occlusion Location in Acute Stroke: Which Value of Time-Resolved Contrast-Enhanced MRA?
  • SWI or T2*: Which MRI Sequence to Use in the Detection of Cerebral Microbleeds? The Karolinska Imaging Dementia Study
  • Progression of Microstructural Damage in Spinocerebellar Ataxia Type 2: A Longitudinal DTI Study
Show more Brain

Similar Articles

Advertisement

Indexed Content

  • Current Issue
  • Accepted Manuscripts
  • Article Preview
  • Past Issues
  • Editorials
  • Editors Choice
  • Fellow Journal Club
  • Letters to the Editor

Cases

  • Case Collection
  • Archive - Case of the Week
  • Archive - Case of the Month
  • Archive - Classic Case

Special Collections

  • Special Collections

Resources

  • News and Updates
  • Turn around Times
  • Submit a Manuscript
  • Author Policies
  • Manuscript Submission Guidelines
  • Evidence-Based Medicine Level Guide
  • Publishing Checklists
  • Graphical Abstract Preparation
  • Imaging Protocol Submission
  • Submit a Case
  • Become a Reviewer/Academy of Reviewers
  • Get Peer Review Credit from Publons

Multimedia

  • AJNR Podcast
  • AJNR SCANtastic
  • Video Articles

About Us

  • About AJNR
  • Editorial Board
  • Not an AJNR Subscriber? Join Now
  • Alerts
  • Feedback
  • Advertise with us
  • Librarian Resources
  • Permissions
  • Terms and Conditions

American Society of Neuroradiology

  • Not an ASNR Member? Join Now

© 2025 by the American Society of Neuroradiology All rights, including for text and data mining, AI training, and similar technologies, are reserved.
Print ISSN: 0195-6108 Online ISSN: 1936-959X

Powered by HighWire