Transcript National Alliance for Medical Image Computing: Namic

NA-MIC
National Alliance for Medical Image Computing
http://na-mic.org
Lesion Classification in
Lupus Update
H. Jeremy Bockholt
DBP2, MIND
Background and Significance
• Systemic lupus erythematosus (SLE) is an autoimmune disease
affecting multiple tissues, including the brain
–
the facial rash of some people with lupus looked like the bite or scratch of a wolf ("lupus" is
Latin for wolf and "erythematosus" is Latin for red). patients may feel weak and fatigued, have
muscle aches, loss of appetite, swollen glands, and hair loss, sometimes have abdominal
pain, nausea, diarrhea, and vomiting.
• Estimates of SLE prevalence range from 14.6-372 per 105
– About 1.5 million americans, 90% diagnosed are female
• Neuropsychiatric SLE (NPSLE), a term that subsumes the
neurologic and psychiatric complications of SLE, occurs in up to
95% of SLE patients
• While MRI often reveals distinct white matter abnormalities in
active NPSLE, the pathologic processes underlying these lesions,
whether purely autoimmune or vascular (e.g., hemostasis), are
unknown
National Alliance for Medical Image Computing
http://na-mic.org
Aims of the RO1 Study
• Test hypotheses concerning the possible thrombotic or
embolic origin of white matter brain lesions in NPSLE
• Examine whether the incidence of lesions correlates with
either levels of thrombosis markers or emboli in the blood
or a potential source of emboli in the heart
• Examine whether overall lesion load or the levels of
particular classes of lesion correlate with cognitive function
National Alliance for Medical Image Computing
http://na-mic.org
Background and Objective
• Critical to understanding the etiology of brain lesions in
NPSLE will be the accurate measurement of their location,
size, and time course.
• Lupus brain lesions are known to vary in MRI intensity and
temporal evolution and include acute, chronic, and
resolving cases.
• Monitoring the time course of image intensity changes in
the vicinity of lesions, therefore, may serve to classify them
based on their temporal characteristics.
• Major objective of this DBP will be the evaluation of
existing tools and the development new tools using the NAMIC kit for the time series analysis of brain lesions in
lupus. As a roadmap initiative we are currently engaged in
an end-to-end tutorial for lesion analyses in Slicer 3.
National Alliance for Medical Image Computing
http://na-mic.org
The MIND Institute / UNM
The Analysis of Brain Lesions in
Neuropsychiatric Systemic Lupus Erythematosis
INVESTIGATORS:
H. Jeremy Bockholt, MIND
Charles Gasparovic, UNM
Steve Pieper, Isomics
Ross Whitaker, Utah
Guido Gerig, Utah
Marcel Prastawa, Utah
Kilian Pohl, BWH
Brad Davis, Kitware
CONSULTANTS:
Vincent Magnotta, UIOWA
Vince Calhoun, MIND, UNM
PROGRAMMER:
Mark Scully, MIND
BACKGROUND:
• NPSLE is an autoimmune disorder that
causes neurological and psychiatric
complications
• Afflicted patients have distinct white matter
lesions that vary over time
• To understand the etiology of brain lesions in
NPSLE, accurate measurement of lesion
location, size, and time course must be
achieved
AIMS:
•
Create an end-to-end tutorial in the NA-MIC
kit for lesion analyses in NPSLE
•
Using the NA-MIC kit, create a time series
analysis tool for brain lesions found in NPSLE
DATA:
•
National Alliance for Medical Image Computing
http://na-mic.org
MRI sequences T1, T2, and FLAIR
Example NPSLE Lesion
Hypointense on T1
Hyperintense T2
National Alliance for Medical Image Computing
http://na-mic.org
Hyperintense on FLAIR
Challenges
• Lesion trace bronze standard will be
manual traces done by expert rater
– What happens if automated analyses
find broader range of lesions not visible
to human
• Co-registration of T1, T2, FLAIR
– Small lesions can be mostly edges and
suffer from partial voluming
– Geometric distortion across sequences
National Alliance for Medical Image Computing
http://na-mic.org
Summary of MRI Protocol
• The MRI data in the roadmap initiative are collected on
both a 1.5T Siemens Sonata scanner using an 8-channel
head coil or 3.0T Siemens Trio using a 12-channel head
coil. We plan to collect 5 patients and 5 controls with
baseline and 6 month follow-up scans.
Sc anner C ontras t Sequenc e T R
TE
TI
V ox
T ime
1 .5 T
T1
FL A SH
12
4 .7 6
.
1 .1 x1 .1 x1 .5 mm 6 m3 2 s
T2
FS E
9040 64
.
1 .1 x1 .1 x1 .5 mm 6 m2 s
FL A I R
FS E
1 0 0 0 1 0 5 2 5 0 0 1 .1 x1 .1 x1 .5 mm 9 m2 s
3 .0 T
T1
T2
FL A I R
M E M P R 2 5 3 0 1 .6 4
.
1 .0 x1 .0 x1 .0 mm 6 m3 s
M U GLE R 3 2 0 0 44 7
.
1 .0 x1 .0 x1 .0 mm 7 m8 s
M U G L E R 6 0 0 0 1 0 5 2 5 0 0 1 .0 x1 .0 x1 .0 mm 9 m2 s
National Alliance for Medical Image Computing
http://na-mic.org
Roadmap
• Process baseline 5 lupus + 5 control
data-sets
– EM Segment within Slicer 3
– Marcel Prastawa custom/ITK
– Magnotta BRAINS/ITK
– Manual identification of lesions
National Alliance for Medical Image Computing
http://na-mic.org
Progress to Date
• Participation in Jan 2008 Programming Week
– Training
•
•
•
•
EM Segmenter
Plugins for Slicer3
DBP Engineers Lunch
Batchmake
• Participation in June 2007 Programming Week
– Training
• Slicer 3
• KWWidgets
• ITK
National Alliance for Medical Image Computing
http://na-mic.org
Progress
• Successful build of slicer3 from svn
repository on Mac G4/G5 OS 10.4
environment
• Becoming comfortable with the NA-MIC
and feel confident on
• Initial EM Segment results
– Working with Brad and Killian, we have run a
lupus and control subject successfully
• Prastawa/Gerig results
– Working with Marcel and Guido, we have an
initial result, including lesion segmentation
National Alliance for Medical Image Computing
http://na-mic.org
Jan 08 to June 08 Workplan
• Jan: Finish Data collection of 5 patients
and 5 controls for roadmap tutorial
• Feb: Establish final criteria for lesion
definitions and final manual traces for
roadmap data-set
• Mar/April: Write up methods paper
including Brad/Killian/others as co-authors
• April/May: apply methods to clinical
sample (n=40)
• June: Finish Data 6 month follow-up visits
National Alliance for Medical Image Computing
http://na-mic.org
Future
• Work with Kilian on tumor growth
project
– This will give us a head start on the
longitudinal lesion analysis phase of
this DBP
National Alliance for Medical Image Computing
http://na-mic.org