A Revolutionary Approach for Post-Processed Noise

PhyZiodynamics
®
A Revolutionary Approach for
Post-Processed Noise Reduction, Motion
Coherence and Functional Analytics
Heather A. Brown, PhD
Ziosoft, Inc.
T
he turn of the millennium brought
monumental advances in non-invasive
cardiac imaging as gated CT and MRI
techniques allowed physicians to look inside
the body and capture diagnostic images of
the beating heart. The complement of noninvasive techniques now available, including
ultrasound, computed tomography (CT),
magnetic resonance imaging (MRI) and nuclear
imaging, provides many imaging options.
Each has its own strengths and limitations
and presents a complex decision making
Figure 1:
PhyZiodynamics Cardiac Imaging
Two views of the heart from a case
processed with PhyZiodynamics noise
reduction.
1a. View of the left atrium showing
confluence of pulmonary veins for preoperative assessment for pulmonary vein
ablation procedure.
1b. Mitral stenosis case with endocardial
view showing exquisite detail of the
papillary muscles and chordae tendonae
in relationship to the posterior leaflet of
the mitral valve.
process for clinicians. How can they get the
most diagnostic information that is safest for
the patient? As cardiac imaging continues to
evolve, scientists push the physical barriers of
each modality. Computational methods may
play a significant role in maximizing information
from a single data set. This paper explores
a paradigm shift in how the medical industry
approaches the need for improved image quality
and functional measurements in cardiac CTA
and other non-invasive imaging techniques.
PhyZiodynamics®, a non-rigid registration
based algorithm, introduces an opportunity to
re-evaluate the CT scan and its role in cardiac
imaging, ultimately offering more information both functional and anatomical - about the heart.
PHYZIODYNAMICS: NON-RIGID
REGISTRATION
Phase1
Phase2
Rigid
Registration
Phase1
Phase2
Non-rigid
Registration
Registration is a standard technique utilized
throughout image processing. Specific to
medicine, registration allows radiologists to fuse
and compare PET and CT scans in oncology
or correct for motion in a brain perfusion scan.
Both of these applications utilize rigid registration
where one data set is aligned with the other by
translational and rotational movements (Figure
2a). Non-rigid registration takes this concept a
step further by morphologically adjusting one
phase of the data set to match the boundaries
of the other phases as the object of interest
is changing shape and position through time
(Figure 2b). This technique is appropriate for
cardiac imaging where the heart is continually
deforming and moving as it is imaged at various
points along the cardiac cycle.
By performing non-rigid registration between
dose remains
adjacent phases, the voxels in the data sets are
a predominant
precisely aligned with each other. Standard 4D
issue in CT
2a. Rigid registration is limited to translation
volumetric imaging simply presents the volume
scanning,
shape and size from Phase 1 to Phase 2, it
grid of voxels and fades from one phase to the
manufacturers
not adjusted.
next to show apparent motion. PhyZiodynamics
are developing
2b. Non-rigid registration adjusts the
tracks the movement of individual voxels through
mechanisms to
space and time based on the registration
manage noise
between phases. This voxel-to-voxel mapping
while reducing
of information enables the employment of
dose. Recently, iterative reconstruction (IR)
additional algorithms that reduce noise, improve
algorithms applied to the raw data have
motion coherence, and measure function.
demonstrated improved noise reduction and
Figure 2:
Rigid and Non-rigid Registration
and rotation. As an object changes position,
can be realigned but the size and shape are
translation and rotation of the object and
morphologically adjusts the shape and size
of the object in Phase 2 to match that of
Phase 1.
image quality beyond conventional filtered
NOISE REDUCTION
back projection techniques. These findings
One parameter of image quality is noise. Noise
have provided physicians the confidence to
exists to varying levels in every image and
decrease the dose while maintaining diagnostic
degrades image quality as it increases. As
quality images (Szucs-Farkas, et al. 2010).
PhyZiodynamics provides a vendor-neutral
be masked. PhyZiodynamics introduces a novel
option that can be applied to any DICOM multi-
approach by performing deformable registration
phase data set, offering noise reduction for any
to align the voxels in each phase of the data
vendor’s images regardless of reconstruction
set and uses interphase filtering algorithms to
techniques.
reduce noise while preserving anatomical data.
kVp vs Noise in Water Phantom
Original
To quantify
PhyZio 1
PhyZio 2
60
kVp vs Noise in Water Phantom
noise reduction, water
50
phantoms were scanned
Noise
40
at various kVp settings.
PhyZiodynamics allows
30
the user to control
Original
20
the strength of noise
PhyZio (1x0.3)
PhyZio (2x0.3)
10
120
0 100
kVp
PhyZiodynamics
reduction by registering to
80
140
120
100
80
kVp
1 or 2 sets of neighboring
phases and by adjusting
the weighting of the filter
y placing an ROI at the same locatin with the same coordinates in each data set and
ues did not change.
Figure 3: PhyZiodynamics Noise Reduction
between the core and
kVp is plotted against noise for the original data set and two iterations of PhyZiodynamics. As kVp decreases, noise
increases. PhyZio 1 data was generated from 1 neighbor set and noise reduction of 0.3. PhyZio 2 data was generated from 2 neighbor sets and noise reduction of 0.3. PhyZiodynamics data show 23% and 32% noise reduction
respectively in comparison to the original data at 80 kVp.
neighbors. Using mirrored
regions of interest (ROI)
between original data
Non-rigid registration offers the first post-
and PhyZiodynamics data, noise was measured
processing technique that reduces noise without
as the standard deviation within the ROI.
degrading other image quality parameters. In
PhyZiodynamics using one neighbor set reduces
comparison, a common technique used to
noise 11-23% in the water phantoms depending
reduce noise is to increase slice thickness (either
on the weighting parameters selected. Using
through retrospective reconstruction at the
two sets of neighbors further reduced noise up
scanner or with post-processing techniques of
to 36%.
averaging slices together), thereby sacrificing
spatial resolution for minimal noise reduction.
Figure 3 illustrates the relationship between kVp
For example, doubling the slice thickness from
and noise for the original data set in comparison
0.625 to 1.25 reduces noise by 15% (Kanal, et al.
to two iterations of PhyZiodynamics. Noise
2007). Another image processing technique is
reduction was the greatest at 36% with the
to apply a filter that ‘smooths’ the data based on
most aggressive parameters of using 2 neighbor
neighboring voxels; this technique presents the
sets and 0.3 weighting ratio between phases,
obvious concern that small critical details may
while with one neighbor set and 0.3 weighting
ratio reduced noise by 28%. Notably, the
PhyZiodynamics data set at 80 kVp contained
approximately the same level of noise as the
original data set at 100 kVp, suggesting that
p
PhyZiodynamics’ noise reduction algorithm can
provide another option beyond IR techniques to
p
reduce dose.
Noise reduction also may mean the difference
between a diagnostic quality scan for an obese
patient and one that is not. The American
Heart Association reports that 33% of the US
population is obese. Morbidly obese patients
pose an imaging challenge because even at
maximum tube current and kVP, noise may
impair the diagnostic quality of the fine detail of
the coronary arteries or other cardiac structures.
p
PhyZiodynamics improves image quality by
reducing noise while preserving anatomical
p
detail. Figure 4 illustrates the noise reduction
for an obese patients. Side by side comparison
of the original (Figure 4a) to the PhyZiodynamics
data (Figure 4b) reveals a 33% reduction in
background noise. Specifically, PhyZiodynamics
noise reduction does not smooth data within the
image (which could mask important findings),
but looks at adjacent phases to compare voxels
and determine what is anatomically present
throughout the phases versus the random
Figure 4: Noise Reduction in Obese Patients
appearance of noise. This can be observed
Axial slice comparisons of original data to PhyZiodynamics processed data (1 neigh-
by comparing the fine detail of the aortic valve
bor, 0.3 noise reduction). Identical ROIs were used to measure noise in the aorta.
PhyZiodynamics reduced noise 33%. Magnified images show the enhanced detail
leaflets.
of the valve leaflet and the removal of noise without degradation of the eccentric
PhyZiodynamics clearly enhances the fidelity
axial slice at the proximal RCA which shows an
of the valve while reducing background noise
eccentric calcific lesion. There is a dark ‘spot’
in the aorta. This can be seen in the original
in the lumen that could be interpreted as a filling
calcium in the lumen of the proximal RCA.
defect (i.e. noncalcified plaque, thrombus). The
objects are in motion. One of the fundamental
PhyZiodynamics data at the same level shows
requirements for the brain to process biological
that the lumen is patent. This was verified on
motion is motion coherence. Motion coherence
adjacent phases and demonstrates that the
describes the phenomenon that if frames
interphase noise reduction algorithm correctly
are removed from a cohesive set (i.e. create
identifies voxels with anatomical or pathological
more gaps in the movement), a person will
data while reducing noise.
not perceive the motion the same way. This
is analogous to
Noise reduction
is a critical
Conventional 4D Motion
the standard
aspect of cardiac
10-phase cardiac
CT imaging for
CT study in
numerous reasons.
comparison to an
One of the most
Phase 1
Phase 2
that clearly
critical reasons
for lowering dose
echocardiogram
PhyZiodynamic 4D Motion
displays the fidelity
®
is in pediatrics
of a valve leaflet.
where children
PhyZiodynamics
may be exposed
supports this
to repetitive
Phase 1
scans throughout
Phase 2
u Time
fundamental
concept by
1
performing non-
their youth.
PhyZiodynamics is the first post-processing
linear interpolation between registered voxels to
technique that reduces noise without
generate a 50-phase data set from the original
compromising spatial resolution. While IR
10-phase exam.
techniques can be applied at the scanner
console to reconstruct the axial data set,
PhyZiodynamics allows the user to generate
PhyZiodynamics provides additional noise
up to 9 additional phases between the original
reduction capability independently of existing IR
adjacent phases for motion coherence. The
techniques.
supercomputing foundation of PhyZiodynamics
processes the computationally intense
MOTION COHERENCE
The human brain is naturally “wired” to detect
biological motion (Fox and McDaniel 1982)
and specific regions of the brain involved
in processing biological motion have been
identified (Grossman, et al. 2000). In simplistic
terms, human perception changes when
optical flow algorithm and allows the user to
interactively manipulate the 50-phase data
set. While PhyZiodynamics does not alter the
temporal resolution (which is determined by the
physical limitations of the scanner), it improves
the fidelity of biological motion of the cardiac
cycle by increasing the frame rate. Traditional
4D visualization blends and fades from one
phase to the next to simulate the motion seen
of the beating heart (Figure 5). PhyZiodynamics
improves the frame rate by filling in the
interphase motion with intelligently interpolated
data. By visualizing more frames per second,
the cardiac cycle incurs a more natural, true-tolife 4D image.
FUNCTIONAL ANALYTICS
One of the most promising deliverables of
PhyZiodynamics is the ability to measure voxelto-voxel interactions. The non-rigid registration
aligns the cardiac structures from phaseto-phase, virtually tracking individual voxels
through the cardiac cycle. By applying standard
physical equations, parameters such as velocity,
acceleration
Improved motion
and strain can
coherence in
be calculated.
CT allows the
As physicians
modality to
seek more
be used more
information from
effectively in
each data set,
analyzing a wide
calculations of
range of motion-
kinematics and
dependent
cardiomyopathies,
strain provide
Figure 6: Valvular Assessment
additional
6a. Mitral valve prolapse of the posterior leaflet is clearly visible in the 3-chamber view. 4D assessment
insight into
including valvular
reveals limited papillary movement.
disease, atrial
6b. Porcine valve replacement. The leaflets of the valve are clearly seen. Coaptation of the aorta and
fibrillation, and
cardiac function.
valvular function can be assessed in 4D.
CHF. With realtime interactive viewing of 50-phase data sets,
physicians have recognized findings that were
not salient in the original 10-phase data set. In a
similar way to interactive ultrasound, physicians
can adjust the plane of section as they are
viewing the cardiac motion to interrogate the
enhanced 4D data set. The coherent motion
has significant potential in valvular studies where
physicians can track the detailed motion of submillimeter leaflets and chordae tendinae (Figure
6a). It also enables more detailed post-operative
assessment of valvular repair (Figure 6b).
Kinematics
have been addressed in research primarily
in ultrasound. Ultrasound techniques have
been used to measure myocardial velocity
which is an indicator of contractility (Cain,
Baglin, et al. 2001). Peak segmental velocities
during dobutamine stress echocardiography
was associated with ischemic myocardium of
stenosed arterial segments (Cain, Marwick, et al.
2001). Other research investigating kinematics
includes using acceleration to predict left atrial
appendage thrombosis (Takahashi, et al. 2008).
With multi-phase data sets, PhyZiodynamics
tracks the motion from voxel-to-voxel
to calculate displacement, velocity and
left ventricle, particularly an area that is scarred
acceleration. The kinematics are displayed as
from a previous infarct (Truong, et al. 2008). By
a parametric map that is overlaid on the volume
visualizing surface velocity maps in relationship
rendered surface and can be manipulated while
to the coronary veins, researchers at MGH are
in motion providing 5D imaging of the heart
analyzing whether PhyZiodynamics can help
(Figure 7).
identify optimal placement of the LV lead in
viable myocardium.
PhyZiodynamics is applicable to any volumetric
DICOM data set. MR tagging studies rely on the
precise tracking of tags which deform with the
myocardium. PhyZiodynamics techniques are
used to align and track the tags and calculate
strain and strain rate (Figure 8). Currently,
few clinicians utilize MR tagging to analyze
strain due to the fact that there are limited
commercial packages available to process
Figure 7: Velocity Map
PhyZiodynamic functional analytics calculates surface velocity for CRT pre-operative
planning. The relationship of the coronary veins to the velocity of the left ventricular
myocardium may guide more accurate placement of the LV lead.
Figure 8: Strain Analysis
This information may prove critical in presurgical
planning for cardiac resynchronization therapy
Circumferential (a) and radial (b) strain parametric map is overlaid on MR tagged
short axis view.
(CRT). Biventricular pacing is a potential lifesaving device for end-stage congestive heart
the data. However, strain has the potential of
failure patients. The device synchronizes right
being a key clinical indicator for contractility
and left ventricular contractions and is currently
(Abraham and Nishimura 2001), dyssynchrony
being investigated in clinical trials in the US
(Helm, et al. 2005), and viability (Pasquet, et
and is approved for use in Europe. Studies
al. 1999). The developers of PhyZiodynamics
show that 30% of patients who receive a CRT
are currently supporting academic research
device are non-responders. One hypothesis
to validate its novel MR strain application and
suggests that it may be related to inappropriate
incorporate it into a full suite of cardiac MR and
placement of the third lead in the wall of the
CT applications.
THE FUTURE OF
PHYZIODYNAMICS
The advanced visualization market has been
stagnant for several years as clinicians have
adopted standard 3D/4D image post processing.
PhyZiodynamics offers an unprecedented
advance in the industry that provides more
information from any conventional data set. The
ability of PhyZiodynamics to reduce noise while
preserving anatomical detail lends itself to 3D
ultrasound. As manufacturers of ultrasound
equipment conform to the DICOM standard,
PhyZiodynamics can improve image quality
by reducing noise. Further development of
PhyZiodynamics includes other potential
applications in CT, MR, PET and US, including
cross-modality registration. The combined ability
to reduce noise, improve motion coherence
and provide functional calculations offers new
opportunities in cardiac imaging.
®
by
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