Ex Parte Pfister

Patent Trial and Appeal Board

Mar 7, 2016

12840649 (P.T.A.B. Mar. 7, 2016)

UNITED STA TES p A TENT AND TRADEMARK OFFICE
APPLICATION NO. FILING DATE
12/840,649 07/21/2010
26574 7590 03/09/2016
SCHIFF HARDIN, LLP
PA TENT DEPARTMENT
233 S. Wacker Drive-Suite 6600
CHICAGO, IL 60606-6473
FIRST NAMED INVENTOR
Marcus Pfister
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
Address: COMMISSIONER FOR PATENTS
P.O. Box 1450
Alexandria, Virginia 22313-1450
www .uspto.gov
ATTORNEY DOCKET NO. CONFIRMATION NO.
Pl0,0153 (26965-4518) 1507
EXAMINER
IMPINK, BRADLEY GERALD
ART UNIT PAPER NUMBER
3768
NOTIFICATION DATE DELIVERY MODE
03/09/2016 ELECTRONIC
Please find below and/or attached an Office communication concerning this application or proceeding.
The time period for reply, if any, is set in the attached communication.
Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the
following e-mail address( es):
patents-CH@schiffhardin.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte MARCUS PFISTER1
Appeal2014-001608
Application 12/840,649
Technology Center 3700
Before DONALD E. ADAMS, JEFFREY N. FREDMAN, and
JACQUELINE T. HARLOW, Administrative Patent Judges.
PERCURIAM
DECISION ON APPEAL
This is an appeal under 35 U.S.C. § 134(a) involving claims to a
method for visualizing aortal stent placement. The claims are rejected as
obvious. We have jurisdiction under 35 U.S.C. § 6(b ).
We AFFIRM.
1 According to Appellant, the Real Party in Interest is Siemens
Aktiengesellschaft (App. Br. 1).
Appeal2014-001608
Application 12/840,649
STATEMENT OF THE CASE
The Specification describes a method for visualizing stent placement
that purports to reduce contrast use relative to prior methods (3:21--4: 12).
Claims 1 and 3-7 are on appeal. Claim 1 is illustrative and reads as follows
(emphasis added):
1. A method for visualizing placement of a stent in an aorta
of a patient with reduced use of contrast agent, comprising the
steps of:
providing a 3D volume image of the aorta of the patient
from a CT scan of the patient before placing the stent;
providing an angiography system with a C-arm to take 2D
images of the patient;
providing a computer having registration software for
registering the 3D volume image and 2D images taken by the
angiography system;
performing a first segmentation on the 3D volume image
to segment the aorta from remaining parts of the 3D image;
performing a second segmentation on the 3D volume
image to segment a bony structure of the patient from remaining
parts of the 3D volume image;
using the angiography system obtaining a first 2D image
of the aorta from a first direction with use of a contrast agent;
using the angiography system obtaining a second 2D
image of said bony structure from a second direction but without
use of contrast agent;
registering the segmented aorta in the 3D volume image to
the C-arm of the angiography system to create a registered 3D
volume image by registering the first 2D image to the segmented
aorta and registering the second 2D image to the segmented bony
structure; and
placing the stent in the aorta while observing on said
angiography system a continuous plurality of additional 2D
images taken when placing the stent by said angiography system
and which are superimposed on the registered 3D volume image.
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Application 12/840,649
Claims 1 and 3-7 stand rejected under 35 U.S.C. § 103(a) as being
obvious based on the combination of Shina2 and Bertrams3 alone, or
alternatively, in further combination with Srinivasan. 4
Findings of Fact
FF 1. Shina discloses
A method of estimating a position of a foreign object in the body,
comprising: (a) providing a 3D data set of at least one blood
vessel; (b) acquiring at least one 2D projection image of the
vessel including the object; ( c) registering the 2D projection
image of the vessel to the 3D data set; and ( d) using the
registration to estimate a 3D position of said object restricted to
be in a blood vessel, according to said 3D data set.
(Shina Abstract; see also Ans. 3.)
FF 2. Shina discloses that
a 3D data set, for example a multi-slice CT data set (MSCT), is
registered to a single or multi-plane projection image acquired
during catheterization and used to generate a 3D position of a
catheter or other foreign object (optionally movable) that is
inside a body. Alternatively or additionally, data from the 3D
data set and from the image are combined, for example, to
generate an enhanced presentation or to correct for errors in data.
(Shina i-f 8; see also Ans. 3.)
FF 3. Shina discloses that
the projection image(s) is an angiography image ... registered to
a CT data set, for example a data set of the heart. [A] vascular
tree of the heart is extracted from the CT data set and optionally
used to find a correct transformation that projects the 3D data set
2 Shina, US 2006/0036167 Al, issued Feb. 16, 2006.
3 Bertrams et al., WO 2008/065581 A2, published June 5, 2008.
4 Srinivasan et al., Segmentation Techniques for Target Recognition, 1
INTERNATIONAL JOURNAL OF COMPUTERS AND COMMUNICATIONS 3:75-81
(2007).
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Application 12/840,649
onto the projection image. Optionally, the projection image and
the data set are registered based on a correspondence of the
vascular tree and the angiographic image.
(Shina i-f 10; see also Ans. 3.)
FF 4. Shina discloses a stent delivery catheter that may be applied to
the abdominal aorta using an apparatus that includes a 3D imager and a C-
arm imager, and that "a computer is programmed and/or circuitry built to
carry out the method" along with "registration software for registering CT
data to projection data" (see Shina i-fi-1 12, 73, 82, 83, 179, 183, 186; see also
Ans. 3--4).
FF 5. Shina discloses that
the better structural definition in a 3D data set (such as CT) is
used to complement better spatial resolution but otherwise
limited data sets, for example, as in IVUS (where much data may
be missing and/or be at an unknown position) and/or
angiographic images (where the projection hides structural
information). Optionally, it is the segmentation of the 3D data
set \vhich is used to complement (or be enhanced by) the other
imaging modality.
(Shina i-f 17.)
FF 6. Shina discloses
(a) providing a 3D data set of at least one blood vessel; [](b)
acquiring at least one 2D projection image of the vessel including
the object; [](c) registering the 2D projection image of the vessel
to the 3D data set; and []( d) using the registration to estimate a
3D position of said object restricted to be in a blood vessel,
according to said 3 D data set.
(Id. at i-fi-120-23; see also Ans. 4.)
FF 7. Shina discloses "enhancing said 3D data set with said 2D
projection image," in which "enhancing comprises enhancing multiple
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Application 12/840,649
projection images" and "enhancing comprises adding angiography data from
said projection image to said 3D data set" (Shina i-f 32; see also Ans. 3).
FF 8. Shina discloses that "the 3D image data set is analyzed to
identify blood vessels[,]" and that "the blood vessels are extracted from the
data as a vascular tree" (Shina i-f 91; see also Ans. 4, 7). Shina further
discloses that that the "tree extraction includes generating a model for other
parts of the body, such as a heart," that "the image of the heart is used to
assist a physician in orienting himself in the body," and that "additional
extraction of data is performed" to prevent disorientation (Shina i-f96; see
also Ans. 4, 7).
FF 9. Shina discloses that "[i]n some cases, however, it is desired to
further minimize exposure to radiation and/or contrast material" and that
"the catheter/tip position is used also for advancing of a catheter, optionally
without contrast material, for example, using the vascular tree and [] low-
level radiation imaging" (Shina i-fi-1 126, 177; see also Ans. 3, 6).
FF 10. Bertrams 5 discloses
an apparatus for determining a position of a first object [] within
a second object[]. The apparatus []comprises a provision unit[]
for providing a three-dimensional model [] of the second
object[]. A projection unit [] generates a two-dimensional
projection image [] of the first object [] and of the second
object[], and a registration unit[] registers the three-dimensional
model [] with the two-dimensional projection image[].
(Bertrams Abstract; see also Ans. 4--5.)
5 For convenience, the Examiner refers to the US equivalent of Bertrams,
US 2010/0020161 Al, published Jan. 28, 2010 (Ans. 2-3). For purposes of
this Appeal, we likewise cite to the US equivalent.
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Application 12/840,649
FF 11. Rertrams discloses that "the second object[] is segmented
within the three-dimensional image, and the segmented second object [] is
visualized by, for example, surface rendering yielding a three-dimensional
model of the second object" and that
2D-3D registration can, for example, be performed by using two
two-dimensional projection images, which have been generated
in different projection directions. The three-dimensional model
of the second object [] can be sized, rotated and translated by
means of known graphical techniques such that the three-
dimensional model is aligned with one of the two-dimensional
projection images by using "fiducial points" (image features that
indicate certain anatomical structures or that are visible in both
the two-dimensional projection image and the three-dimensional
model) or by using an X-ray contrast medium injection to outline
the shape of [] the heart chamber under consideration[], or by
using [] the spine or ribs that can easily be seen in both, the two-
dimensional projection image and the three-dimensional model
of the second object[]. . . . [T]he projection unit is rotated
preferably around 90°, and the three-dimensional model is
rotated accordingly. The second of the two two-dimensional
projection images corresponds to this rotated projection
direction, i.e. the second two-dimensional projection image has
been generated in this rotated projection direction, and the three-
dimensional model is also aligned with respect to this second
two-dimensional projection image.
(Bertrams iii! 38, 40; see also Ans. 5.)
FF 12. Srinivasan discloses "methodologies and algorithms for
segmenting 2D images as a means in detecting target objects embedded in
visual images for Automatic Target Detection/Recognition applications"
(Srinivasan Abstract; see also Ans. 7-8).
FF 13. Srinivasan discloses that "Automatic Target
Detection/Recognition (ATDR) is an application of pattern recognition for
image processing that detects and identifies types of target objects" and that
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Application 12/840,649
"ATDR is a major objective in processing digital images for detecting,
classifying, and tracking target objects embedded in an image" (Srinivasan
75, pt col.; see also Ans. 7-8).
FF 14. Srinivasan discloses that the
separation of an image into object[ s] and background is usually
done by simplifying and/or changing the representation of an
image by enhancing the visual representation of boundaries
(lines, curves, etc.). This makes the object differentiation,
isolation and detection task easier. The process is known as
image segmentation. Image segmentation is one of the primary
steps in image analysis for object [ d]etection, recognition and
identification[.]
(Srinivasan 75, 1st col.; see also Ans. 7-8.)
FF 15. Srinivasan disclose that
segmentation refers to the process of partitioning a digital image
into multiple regions (sets of pixels). The result of image
segmentation is a set of regions that collectively cover the entire
image, or a set of contours extracted from the image. Each pixel
within a region is uniquely similar with respect to some
characteristic or computed property, such as color, intensity, or
texture. Pixels from adjacent regions are significantly different
with respect to the same characteristic( s ).
(Srinivasan 75, cols. 1-2; see also Ans. 7-8.)
Analysis
Claims 1 and 3-5:
We adopt the Examiner's findings of fact and reasoning regarding the
scope and content of the prior art (Ans. 2-8; FF 1-15), and agree that the
claims are obvious over Shina, Bertrams, and Srinavasan. We address
Appellant's arguments below.
Appellant contends that "Shina only has one 2D image and only one
segmentation of a 3D volume image to segment an aorta and does not have a
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Application 12/840,649
second segmentation to segment a bony structure" (App. Rr. 6). Appellant
argues that the additional 3D volume segmentations disclosed by Shina do
not suggest segmentation of an aorta and a bony structure (id. at 7-8; Reply
Br. 3).
Similarly, Appellant contends that Bertrams teaches segmentation of
only one object within the 3D image (App. Br. 6). Appellant acknowledges
Bertrams' teaching that the spine can be used as a fiducial point in the 2D
and 3D images, but argues that Bertrams fails to disclose segmentation of
the spine from the same 3D image as the aorta (id. at 7). Appellant likewise
contends that Bertrams fails to disclose segmentation of the catheter tip in
the 3D image (Reply Br. 1-2).
We do not agree. Shina teaches "acquiring at least one 2D projection
image" (FF 1, 6 (emphasis added)), and "enhancing said 3D data set with
said 2D projection image," in which "enhancing comprises enhancing
multiple projection images" (FF 7 (emphasis added)). Shina also teaches
that "the blood vessels are extracted from the [3D image] data as a vascular
tree," that the "tree extraction includes generating a model for other parts of
the body," and that "additional extraction of data is performed" to prevent
disorientation (FF 8 (emphasis added)). Srinivasan discloses that
segmentation of images for target recognition is well known in the field
(FF 12-15).
Furthermore, Appellant's arguments do not account for Bertrams'
contribution to the combination. Bertrams teaches that "the second object []
is segmented within the three-dimensional image," "using two two-
dimensional projection images," and that
the three-dimensional model is aligned with one of the two-
dimensional projection images by using "fiducial points" (image
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Application 12/840,649
features that indicate certain anatomical structures or that are
visible in both the two-dimensional projection image and the
three-dimensional model) or by using an X-ray contrast medium
injection ... or by using [] the spine or ribs that can easily be
seen in both, the two-dimensional projection image and the
three-dimensional model ...
(FF 11 (emphasis added).) See In re Keller, 642 F.2d 413, 425 (CCPA 1981).
We agree with the Examiner that
In order to accurately perform the registration process[,] one of
ordinary skill would have recognized the need to first locate in
the 3D data set the different structures which are to be registered
with the 2D image data such as the aorta as in Shina and the spine
and ribs as in Bertrams. One of ordinary skill in the art would
have recognized that this could be done in either one
segmentation step or in two separate segmentation steps with the
end result being the same in that the different structures are
identified and ready for subsequent processing. Furthermore,
Shina even suggests extraction (i.e. segmenting the data of
interest from the remaining portions of the image not
useful/needed for the task at hand) of the vessel tree and other
structures such as the heart which may serve to assist the
physician in orienting himself when viewing the images in order
to avoid disorientation. These additional segmentations could
obviously have included the spine and ribs (as taught by
Bertrams) which one of ordinary skill would have recognized as
useful reference structures for providing orientation. Finally, in
light of Srinivasan, it is well known to use segmentation for
partitioning an image into multiple regions where each region
shares some common characteristics which differ from other
regions in order to differentiate and isolate different structures.
In order to accurately perform a 2D-3D registration it would have
been obvious to first segment the different structures (such as the
spine and aorta) which again could obviously be done in a single
step or multiple steps without materially affecting the process.
(Ans. 10.) See In re Merck & Co., 800 F.2d 1091, 1097 (Fed. Cir. 1986)
("Non-obviousness cannot be established by attacking references
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Application 12/840,649
individually where the rejection is based upon the teachings of a
combination of references []. [The reference] must be read, not in isolation,
but for what it fairly teaches in combination with the prior art as a whole.").
Appellant also contends that Srinivasan does not teach that "the first
segmentation is an aorta and the second segmentation is a bony structure"
(App. Br. 7). Appellant argues that while Srinivasan teaches isolation of
different objects, Srinivasan does not teach "a second segmentation of a 3D
volume image to segment a bony structure of the patient and obtaining a
second 2D image of said bony structure from a second direction without use
of contrast agent" (Reply Br. 3). We do not find this argument persuasive as
it fails to account for Bertrams' and Shina's contributions to the combination
as discussed above. See In re Keller, 642 F.2d 413, 425 (CCPA 1981).
Appellant further argues that if neither Shina nor Bertrams teaches
two segmentations in the same 3D volume image, then it is not possible that
the combination of Shina and Bertrams could teach two segmentations (App.
Br. 7). Appellant contends that the combination of Bertrams and Shina
would "only suggest providing a 2D image of a segmented aorta and a
second non-segmented 2D image of a catheter tip 14 or a heart 13" but
would not suggest "a second segmentation of a 3D volume image of a bony
structure and no second 2D image of the bony structure without use of
contrast agent" (Reply. Br. 2). Appellant argues that because the Examiner
does not indicate where it is in the reference that Bertrams teaches
registration of bony structures such as the spine or ribs, the Examiner erred
in concluding that it would have been obvious to take a second 2D image of
a bony structure without a contrast agent (id.). Appellant contends that
while Shina teaches, at paragraph 126, minimizing exposure to contrast
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Application 12/840,649
material, this is a broad non-specific teaching that would not lead one skilled
in the art to take second 2D image of a bony structure without contrast agent
(id. at 2-3).
We are not persuaded. We first note that Bertrams teaches, at
paragraph 38, that "the second object [] is segmented within the three-
dimensional image," and at paragraph 40, that "[t]he 2D-3D registration can,
for example, be performed ... using [] the spine or ribs that can easily be
seen in both, the two-dimensional projection image and the three-
dimensional model" (FF 11). We also note that Shina teaches "[i]n some
cases, [] it is desired to further minimize exposure to radiation and/or
contrast material[,]" and describes an embodiment where the position of a
catheter is visualized "without contrast material" when using low-level
radiation imaging (FF 9). Appellant has not provided any evidentiary basis
on this record to support a conclusion that "it is not possible that the
combination of Shina and Bertrams could teach two segmentations" (App.
Br. 7) or that Shina "is a broad non-specific teaching that would not lead one
skilled in the art to take second 2D image of a bony structure without
contrast agent" (Reply Br. 2-3), especially in light of the teachings of
Srinivasan concerning segmentation (FF 12-15). See In re Geisler, 116 F.3d
1465, 1470 (Fed. Cir. 1997) ("[A]ttomey argument [is] not the kind of
factual evidence that is required to rebut a prima facie case of obviousness").
Claim 6:
Appellant contends that "[i]ndependent claim 6 distinguishes at least
for the reasons noted with respect to claim 1 and also by reciting that it is the
abdominal aorta which is being segmented and the bony structure is the
spine" (App. Br. 9; see also Reply Br. 4). As explained above, in our
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discussion of the bony structure, Rertrams discloses that the spine may be
segmented and used for 2D-3D registration (FF 11; Ans. 10). In addition,
we note that Shina explains that the disclosed imaging methods may be
applied to the abdominal aorta (FF 4). Likewise, Appellant's argument that
the cited art fails to disclose segmentation of both structures in combination
(App. Br. 9) is unpersuasive for the reasons set forth above. Therefore, we
affirm the rejection of claim 6.
Claim 7:
Appellant contends that "[ c ]laim 7 is similar to claim 1 but is broader
since it does not recite the two segmentations, but does recite obtaining the
second 2D image of a bony structure without use of contrast agent, a feature
not taught by the references as discussed above" (Reply Br. 4; see also App.
Br. 9). We have already addressed above the limitations concerning the
bony structure and the non-use of a contrast agent. Therefore, we also
affirm the rejection of claim 7.
SUMMARY
We affirm the rejection of claims 1, 6, and 7 under 35 U.S.C. § 103(a)
based on Shina, and Bertrams alone and alternatively, Srinivasan. Claims 3-
5 fall with claim 1.
TIME PERIOD FOR RESPONSE
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a)(l )(iv).
AFFIRMED
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