RadioGraphics
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

DOI: 10.1148/rg.262045187
This Article
Right arrow Abstract Freely available
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by d’Arcy, J. A.
Right arrow Articles by Leach, M. O.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by d’Arcy, J. A.
Right arrow Articles by Leach, M. O.
Related Collections
Right arrow Magnetic Resonance Imaging
Right arrow Physics and Basic Science

Magnetic Resonance Imaging Workbench: Analysis and Visualization of Dynamic Contrast-enhanced MR Imaging Data1

James A. d’Arcy, MSci, David J. Collins, BA, MInstP, Anwar R. Padhani, FRCP, FRCR, Simon Walker-Samuel, MSci, John Suckling, PhD and Martin O. Leach, PhD, FInstP, FMedSci

1 From the Cancer Research UK Clinical MR Research Group, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey, United Kingdom SM2 5PT (J.A.D., D.J.C., S.W.S., M.O.L.); the Department of Radiology, Mount Vernon Hospital, North-wood, Middlesex, England (A.R.P.); and the Department of Psychiatry, University of Cambridge, Addenbrooke’s Hospital, Cambridge, England (J.S.). Presented as an infoRAD exhibit at the 2003 RSNA Annual Meeting. Received July 19, 2005; revision requested October 13 and received November 11; accepted December 6. J.A.D., D.J.C., and M.O.L. may benefit financially from the licensing and commercialization of the MRIW software; A.R.P. has used the MRIW software to analyze results of commercially sponsored clinical drug trials; the other authors have no financial relationships to disclose. Supported by grant C1060/A808 from Cancer Research UK.

Figure 1
View larger version (82K):

[in a new window]
  		Figure 1.  Screen from MRIW displays three parametric overlays for permeability (top) and three parametric overlays for perfusion (bottom). This display gives the user a quick overview of the results and the heterogeneity present in the tumor. Larger, single-parameter images are available in the postprocessing window under the "Analysis" menu.

 

Figure 2
View larger version (115K):

[in a new window]
  		Figure 2a.  Skull base meningioma in a 48-year-old man. (a) Axial contrast-enhanced high-resolution T1-weighted MR image obtained through the tumor. (b) Ktrans map for the same section, overlaid on a low-resolution T1-weighted dynamic image and displayed in the postprocessing window, shows the heterogeneity of the tumor; the heterogeneity would not be evident if only the whole ROI was processed. Alongside the map is an individual pixel CTC and fit from the tumor ROI.

 

Figure 2
View larger version (46K):

[in a new window]
  		Figure 2b.  Skull base meningioma in a 48-year-old man. (a) Axial contrast-enhanced high-resolution T1-weighted MR image obtained through the tumor. (b) Ktrans map for the same section, overlaid on a low-resolution T1-weighted dynamic image and displayed in the postprocessing window, shows the heterogeneity of the tumor; the heterogeneity would not be evident if only the whole ROI was processed. Alongside the map is an individual pixel CTC and fit from the tumor ROI.

 

Figure 3
View larger version (46K):

[in a new window]
  		Figure 3a.  Perfusion data for the same data and section position as in Figure 2. Screens from MRIW show the relative blood flow map for the tumor, the {Delta}R2* curve for an individual pixel, and the fitted gamma-variate curve. (a) {Delta}R2* curve shows the first pass of contrast agent through the vasculature with no obvious recirculation peak. This result is the expected behavior in a vessel where the blood-brain barrier is intact. (b) {Delta}R2* curve selected from the tumor shows considerable retention of contrast agent in the pixel after the first pass. This result is typical of tumor {Delta}R2* curves because the vasculature is disordered, tortuous, and leaky, thus leading to the large tail in the curve. MRIW uses the data from the bolus arrival time and the following 30 seconds to perform gamma-variate fitting. This feature prevents the slow washout of contrast agent from affecting the quality of the fit for the first pass.

 

Figure 3
View larger version (46K):

[in a new window]
  		Figure 3b.  Perfusion data for the same data and section position as in Figure 2. Screens from MRIW show the relative blood flow map for the tumor, the {Delta}R2* curve for an individual pixel, and the fitted gamma-variate curve. (a) {Delta}R2* curve shows the first pass of contrast agent through the vasculature with no obvious recirculation peak. This result is the expected behavior in a vessel where the blood-brain barrier is intact. (b) {Delta}R2* curve selected from the tumor shows considerable retention of contrast agent in the pixel after the first pass. This result is typical of tumor {Delta}R2* curves because the vasculature is disordered, tortuous, and leaky, thus leading to the large tail in the curve. MRIW uses the data from the bolus arrival time and the following 30 seconds to perform gamma-variate fitting. This feature prevents the slow washout of contrast agent from affecting the quality of the fit for the first pass.

 




HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
RADIOGRAPHICS RADIOLOGY RSNA JOURNALS ONLINE
Copyright © 2006 by the Radiological Society of North America.