Ex Parte Griswold et al

Patent Trial and Appeal Board

May 25, 2018

14257081 (P.T.A.B. May. 25, 2018)

UNITED STA TES p A TENT AND TRADEMARK OFFICE
APPLICATION NO. FILING DATE
14/257,081 04/21/2014
26710 7590 05/30/2018
QUARLES & BRADYLLP
Attn: IP Docket
411 E. WISCONSIN A VENUE
SUITE 2350
MILWAUKEE, WI 53202-4426
FIRST NAMED INVENTOR
Mark Griswold
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.
155798.00101.CW2014-2633 3549
EXAMINER
YANG, WEI WEN
ART UNIT PAPER NUMBER
2667
NOTIFICATION DATE DELIVERY MODE
05/30/2018 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):
pat-dept@quarles.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte MARK GRISWOLD, YUN JIANG, DAN MA,
ANAGHA DESHMANE, CHAITRA BADVE, and
VIKAS GULAN!
Appeal2017-009609
Application 14/257 ,08 l1
Technology Center 2600
Before MICHAEL J. STRAUSS, IRVINE. BRANCH, and
NABEEL U. KHAN, Administrative Patent Judges.
KHAN, Administrative Patent Judge.
DECISION ON APPEAL
Appellants appeal under 35 U.S.C. § 134(a) from the final rejection of
claims 1-32, 34--36, 38, and 39. We have jurisdiction under 35 U.S.C.
§ 6(b).
We affirm-in-part.
1 Appellants identify Case W estem Reserve University as the real party in
interest. App. Br. 1.
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Application 14/257 ,081
BACKGROUND
THE INVENTION
According to Appellants, the invention relates to "[a]pparatus,
methods, and other embodiments associated with NMR fingerprinting."
Abstract. NMR fingerprinting is used to facilitate identifying tissue types
based on clusters of data using magnetic resonance parameters. Spec. ,r 22.
Such parameters may include combinations of Tl relaxation times, T2
relaxation times, and off-resonance frequencies. Spec. ,r,r 22-24.
Exemplary independent claim 1 is reproduced below.
1. A method, comprising:
accessing a set of known signal evolutions;
accessing an acquired nuclear magnetic resonance (NMR)
signal, where the acquired NMR signal is acquired from a
volume that contains one or more resonant species that
simultaneously produced individual NMR signals in response to
magnetic resonance fingerprinting (MRF) excitation using
random or pseudo-random imaging parameters;
finding a selected entry in the set of known signals that
matches the acquired NMR signal;
identifying two or more magnetic resonance (MR)
parameters for the volume based on stored MR parameters
associated with the selected entry, where the two or more MR
parameters include:
a default or natural alignment to which spins align
when placed in a main magnetic field (Mo) of an MRI
system used to acquire the NMR signal; and
at least one of Tl relaxation associated with the
resonance species, T2 relaxation associated with the
resonant species, off-resonance relaxation associated with
the resonant species, and diffusion weighted relaxation
associated with the resonant species, Tl being spin-lattice
relaxation, T2 being spin-spin relaxation, and
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assigning the volume that produced the acquired NMR
signal to a cluster in a plurality of clusters based on the two or
more MR parameters.
REFERENCES AND REJECTION
Claims 1-32, 34--36, 38, and 39 stand rejected under 35 U.S.C. § 103
as unpatentable over Assaf (US 2010/0215239 Al, published Aug. 26, 2010)
and Seiberlich (US 2012/0235678 Al, published Sept. 20, 2012). Final Act.
6-25.
DISCUSSION
Claim 1
Claim 1 recites,
identifying two or more magnetic resonance (MR) parameters
for the volume based on stored MR parameters associated with
the selected entry, where the two or more MR parameters
include: a default or natural alignment to which spins align
when placed in a main magnetic field (Mo) of an MRI system
used to acquire the NMR signal.
The Examiner finds Assaf "clearly discloses [that] two or more parameters
(Mo, tl) are useful/based on in assigning volume of tissues." Ans. 29. In
particular, the Examiner cites to Assaf' s formula used for assigning a
volume of tissues into a cluster that includes both Mo and Tl as variables as
evidence that Assaf teaches or suggests using these two parameters in
assigning volumes to clusters. Ans. 29 (citing Assaf,I 85 which discloses
the following formula: M(TL)/Mo = 1 -2eC-Tii/Tl)).
Appellants argue, "Neither Seiberlich nor Assaf describe assigning a
volume to a cluster based on two or more MR parameters," (App. Br. 7),
where one of the parameters is "a default or natural alignment to which spins
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align when placed in a main magnetic field (Mo) of an MRI system used to
acquire the NMR signal" (App. Br. 8). According to Appellants, "[t]he fact
that T 1 relates mathematically to other parameters does not constitute a
teaching of clustering based on those other parameters." Reply Br. 2.
Appellants also indicate that the same paragraph of Assaf that the Examiner
relies on for including the formula relating Mo and T 1 also states that,
"[f]ollowing the fit, each pixel or voxel can be assigned a single Tl value
from which the inversion time that zeroed the magnetization of that pixel
can be calculated." Reply Br. 2. Appellants contend this evidences "that the
clustering is uni-parameter and not based on Mo." Reply Br. 2.
These arguments are unpersuasive of Examiner error. Claim 1
requires identifying two or more parameters, where one of the parameters is
Mo and one other is at least one of Tl, T2, off-resonance relaxation,
diffusion-weighted relaxation. Once the parameters are identified, the claim
requires "assigning the volume that produced the acquired NMR signal to a
cluster in a plurality of clusters based on the two or more MR parameters."
The Specification describes assigning clusters based on MR parameters as
follows:
In one embodiment, a member of the plurality of clusters
may be defined by a relationship between two MR parameters.
The two MR parameters may be, for example, Tl and T2. In
another embodiment, a member of the plurality of clusters may
be defined by a relationship between three MR parameters. The
three MR parameters may be, for example, Tl, T2, and MO, MO
being the default or natural alignment to which spins align when
placed in the main magnetic field.
Spec. ,r 67 ( emphases added). In other words, the cluster assignment based
on two or more MR parameters may be defined by a relationship between
those two or more MR parameters.
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Assaf discloses a method of associating regions with different brain
structures (i.e. assignment of regions to clusters). Assaf,I 84. This
association is done by fitting the data to a function according to the formula:
M(TL)/Mo = 1-2eC-Tii!Tl), which expresses a relationship between the
parameters Mo and T 1. Assaf ,r 85. Because the cited formula expresses a
relationship between Mo and Tl, we agree with the Examiner that Assaf
teaches or suggests assigning a volume to a cluster based on two of more
MR parameters as claimed.
Appellants next argue Assaf teaches away from the claimed invention
and that the combination of Assaf and Seiberlich is based on impermissible
hindsight and would produce an inoperable result. In particular, Appellants
argue:
Assaf relies upon traditional MR imaging techniques that do not
utilize random or pseudo-random imaging parameters, as
claimed. In fact, one of ordinary skill in the art will readily
acknowledge that Assaf s techniques for clustering, which rely
on "classification of the pixels or voxels into clusters according
to their inversion times" or the like would fail if one attempted
to use the claimed random or pseudo-random imaging
parameters.
App. Br. 10 (citing Assaf,I 86). According to Appellants, "Seiberlich does
not discuss or contemplate clustering or, more to the point, teach or suggest
how one could achieve a clustering technique with MRF data acquired using
random or pseudo-random imaging parameters, as claimed." App. Br. 11.
And although Assaf does cluster, it does so without using random or pseudo-
random imaging parameters. App. Br. 11.
Initially, we note the Examiner relies on Assaf for disclosing
acquiring NMR signals, but relies on Seiberlich for disclosing that these
NMR signals are produced in response to magnetic resonance fingerprinting
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excitation using random or pseudo-random imaging parameters. Final Act.
7, 9-10. The fact that Assaf does not teach the use of random or pseudo-
random imaging parameters is not enough, on its own, to provide a showing
of teaching away from the use of such parameters. Teaching away requires
a reference to actually criticize, discredit, or otherwise discourage the
claimed solution. See In re Fulton, 391 F.3d 1195, 1201 (Fed. Cir. 2004)
("The prior art's mere disclosure of more than one alternative does not
constitute teaching away from any of these alternatives because such
disclosure does not criticize, discredit, or otherwise discourage the solution
claimed.") Here, Appellants have not persuasively shown Assaf discredits
or discourages using the claimed random or pseudo-random parameters.
Further, Appellants have not persuasively shown that combining
Assaf and Seiberlich would be improper. Instead, all Appellants have
argued is that Assaf or Seiberlich taken alone do not disclose the entirety of
the claimed invention because one does not use random/pseudo-random
parameters, and the other does not cluster. But the Examiner relies on both
references in combination and has provided a reason to do so. In particular,
the Examiner has found both references to be in the same field of endeavor
and has articulated a rational reason to combine the two references. See
Final Act. 10. Thus, we find the combination to be proper.
Accordingly, we sustain the Examiner's rejection of claim 1.
Dependent Claims
Appellants generally contend that for the dependent claims, "the
Examiner merely recited the claim language followed by a parenthetical
citation to the art without explanation" and that "[t]his fall[s] far short of the
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requirements of the MPEP and the standards clearly articulated by the
Supreme Court." App. Br. 11.
We disagree. Our reviewing court has explained
all that is required of the [US PTO] to meet its prima facie burden
of production is to set forth the statutory basis of the rejection
and the reference or references relied upon in a sufficiently
articulate and informative manner as to meet the notice
requirement of § 132. As the statute itself instructs, the
examiner must "notify the applicant," "stating the reasons for
such rejection," "together with such information and references
as may be useful in judging the propriety of continuing
prosecution of his application." 35 U.S.C. § 132.
In re Jung, 637 F.3d 1356, 1363 (Fed. Cir. 2011). We have reviewed the
decision to reject the claims for patent-ineligibility articulated by the
Examiner (see Final Act. 2-3; Ans. 7-12) and find it meets the notice
requirements of 35 U.S.C. § 132. The Examiner has set forth the statutory
basis for the rejection, identified where in the prior art the various limitations
may be found (see Final Act. 11-25) and explained the rejection in sufficient
detail to permit Appellants to respond meaningfully.
Accordingly, we are unpersuaded by Appellants' general argument
directed at the dependent claims that the Examiner provided insufficient
analysis, except where we specifically note below.
Claim 2
Claim 2 depends from claim 1 and recites "where assigning the
volume to the cluster is performed using k-means clustering, where k is a
number that identifies the number of clusters into which a data space
associated with the acquired NMR signal is partitioned."
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The Examiner finds "Assaf clearly discloses where assigning the
volume to the cluster is performed using k-means clustering, where k is a
number that identifies the number of clusters into which a data space
associated with the acquired NMR signal is partitioned." Ans. 31-32 (citing
Assaf ,I 125).
Appellants indicate that they do "not understand this paragraph [125
of Assaf] to teach or suggest the claimed step of 'assigning the volume to the
cluster is performed using k-means clustering, where k is a number that
identifies the number of clusters into which a data space associated with the
acquired NMR signal is partitioned.'" App. Br. 12-13.
We are unpersuaded by Appellants' arguments. Paragraph 125 of
Assaf teaches "a cluster analysis based on the multi-parametric data" that
includes a "k-means clustering algorithm" being employed where "[t]he
number of k-cluster was set to 5 or 6 according to the results of the Gaussian
mixture analysis." Assaf,I 125. Appellants' argument that "they do not
understand this paragraph to teach or suggest" the disputed limitation does
not persuasively rebut the Examiner's findings. Thus, we agree with the
Examiner that Assaf teaches or suggests "assigning the volume to the cluster
is performed using k-means clustering, where k is a number that identifies
the number of clusters into which a data space associated with the acquired
NMR signal is partitioned."
Claim 3
Claim 3 recites, "The method of claim 2, comprising selecting k as a
function of the number of expected material components in the volume."
The Examiner finds Assaf teaches k-means clustering where "[t]he number
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of k-cluster was set to 5 or 6 according to the results of the Gaussian mixture
analysis." Ans. 32-33. The Examiner further finds Assaf discloses that
each pixel or voxel includes more than one Tl. Typically, N
equals 7 or 8, such that 5 or 6 of the longitudinal relaxation times
can be identified as corresponding to cortical layers, one
longitudinal relaxation time can be identified as corresponding
to CSP and one longitudinal relaxation time can be identified as
corresponding to white matter.
Ans. 32-33 (quoting Assaf,I 88).
Appellants argue
To reject claim 3, the Examiner asserted that Assaf teaches
"more than on Tl." The use of different Tl values does not teach
or suggest clustering based on a number that identifies the
number of clusters into which a data space associated with the
acquied [sic] NMR signal is partitioned that is selected as "a
function of the number of expected material components in the
volume." Rather Assaf explains, as is typical of traditional
clustering, that the number of clustered to be sued [sic] is
predetermined. This is logical because, as a basis of traditional
clustering, threshold values for, in this case Tl, are selected
before clustering is performed.
App. Br. 13.
Appellants' arguments are unpersuasive. The Examiner's findings
show that the number of k-cluster is set to 5 or 6 according to the result of
the Gaussian mixture. See Ans. 32-33 (citing Assaf,I 125). Assaf goes on
to explain that the Gaussian mixture analysis shows a histogram of
longitudinal relaxation times with 5-6 peaks. Assaf,I 129. Assaf further
explains that these longitudinal relaxation times correspond to cortical
layers, to CSP, and to white matter. Assaf,I 88. In other words, the
longitudinal relaxation times correspond to various material components of
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the brain. Thus, the number of k-clusters (i.e. the 5 or 6 clusters in Assaf's
example) is related to the number of material components.
Accordingly, we sustain the Examiner's rejection of claim 3.
Claims 19 and 20
Claims 19 and 20 recite, "The method of claim 1, where the volume is
assigned to the cluster with an accuracy of at least 99%" and "99 .9%"
respectively. The Examiner cites to paragraphs 151 of Assaf and paragraph
7 of Seiberlich as teaching or suggesting these limitations explaining that
paragraph 151 of Assaf discloses a correlation coefficient, which has a p-
value < 0.0001, which reflects that the accuracy of the cluster analysis is
higher than 99% and 99.9%. Ans. 33 (citing Assaf,I 151).
Appellants contend that they do
not understand these paragraph to teach or suggest the claimed
clustering assignment accuracy of at least 99%. Assaf is
describing a graph of MRI layer width vs. cytoarchitechtonic
layer width. Furthermore, the cited portion of Seiberlich is
confounding. Of course, as discussed, Seiberlich does not
discuss clustering. So, Appellants are at a loss to evaluate how
this passage speaks to the issue of clustering assignment
accuracy of greater than 99%.
App. Br. 14.
We are unpersuaded by Appellants' arguments. Under the broadest
reasonable interpretation of the claims, the limitations reciting that the
volumes be assigned to the cluster with a certain level of accuracy are
simply expressions of the intended result of performing the assignment step
of claim 1. In other words, claims 19 and 20 limit claim 1 only by
describing the level of accuracy desired of the assignment of volumes to
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clusters without requiring any additional positively recited steps themselves.
As such, we do not give substantial weight to these limitations. See lvlinton
v. Nat'! Ass 'n of Securities Dealers, Inc., 336 F.3d 1373 (Fed. Cir. 2003) (a
whereby '"clause in a method claim is not given weight when it simply
expresses the intended result of a process step positively recited.")
Further, other than stating that they do not understand the cited
paragraph to teach or suggest the disputed limitation, and briefly
summarizing the Assaf's disclosure regarding i\,1RI layer width, Appellants
do not address the Examiner's finding regarding Assaf s correlation
coefficient having a p value of less than 0.0001.
Accordingly, we sustain the Examiner's rejection of claims 19 and 20.
Claim 21
Claim 21 depends from claim 1 and recites, "where the two or more
MR parameters include a diffusion coefficient associated with the volume, a
spin density associated with the volume, a proton density associated with the
volume, a magnetic field to which the volume is exposed, or a gradient field
to which the volume was exposed."
The Examiner finds Assaf and Seiberlich teach or suggest these
limitations. In particular, the Examiner relies on Assaf as teaching that
relaxation times and the density distribution of the nuclear spin are
properties which vary from one normal tissue to the other and from one
diseased tissue to the other" and that "therefore [ these quantities are]
responsible for contrast between tissues in various imaging techniques."
Ans. 34 ( quoting Assaf ,Ii-I 61---63). Assaf also discloses diffusion MRI.
Ans. 34 ( citing Assaf,I,I 94--95). The Examiner further relies on Seiberlich
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as teaching NMR fingerprinting involving MR parameters such as proton
density. Ans. 34 ( citing Seiberlich ,r 8).
Appellants argue
[t]his conclusory set of statements seems to imply that, because
these parameters exist, it would be obvious to use them in
clustering. However, this does explain why or address the fact
that the claimed invention is not directed to MRI-based
clustering, as in Assaf, but MRF-based clustering, which had not
been done to Appellant's knowledge, prior to the work of the
present inventors.
App. Br. 14--15.
Appellants' argument is unpersuasive. The Examiner relies on
Seiberlich, not Assaf for teaching MRF-based clustering. Thus, Appellants
argument that Assaf is not directed to MRF-based clustering fails to address
the Examiner's findings as a whole.
Accordingly, we sustain the Examiner's rejection of claim 21.
Claims 28-31
Claims 28-31 depend from claim 1 and require that the "set of known
signal evolutions includes a signal selected from a set of signals described
by" a variety of formulas.
The Examiner finds Assaf teaches or suggests these formulas by
disclosing the exponential decay function formula "M(TL)/Mo = 1 - 2eC-
Tii/n) _" Ans. 35 (citing Assaf,I 85).
Appellants argue,
To address all these claims, the Examiner summarily provided
'Re Claims 28-31, see Assaf: e.g., formula in [0085], and [0088],
also see Seiberlich: e.g., --M=(Mx, My, Mz)--, in [0086].'
Appellant can understand no way that this brief set of citations
addresses the claimed invention. As the Examiner provided no
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guidance or explanation for either the interpretation or
application of this paragraph to the claimed invention, Appellant
cannot be held to guess at the basis for rejection or refute
hypothetical applications of the prior art.
App. Br. 17.
We are persuaded by Appellants' argument. It is clear, at least from
the express recitation of the various formulas included in claims 28-31, that
they differ from the formula the Examiner relies upon from Assaf. Although
the Examiner explains that certain variables found in Assaf s equation can
be substituted for variables found in the claimed equations, the Examiner
does not explain why one of ordinary skill would make such substitutions
and why those substitutions would lead to an equivalent equation as the ones
claimed. Further, we find insufficient analysis for claims 29-31. Thus, the
Examiner has not sufficiently explained how this one formula teaches or
suggests the formulas recited in claims 28-31.
Accordingly, we do not sustain the Examiner's rejection of claims 28-
31.
Claim 32
Appellants make many of the same arguments for claim 32 as they did
for claim 1. For the reasons stated above with respect to claim 1, we do not
find these arguments to be persuasive. In addition, Appellants focus on
claim 32 's limitation that "the plurality of clusters represent Voronoi groups
produced by a k-means analysis, and where the plurality of clusters segment
an MR parameter data space associated with the object." App. Br. 20-21.
Appellants argue the Examiner failed to clearly articulate reasons why the
invention would be obvious by simply providing parenthetical citations
without explanation. App. Br. 21. Further, Appellants argue the cited
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portions do even include the word "Voronoi" and that the Examiner "did not
even provide a citation that seems to address this specific technique for
creating the Voronoi groups." App. Br. 21. Claim 32 also requires that the
clustering achieve an accuracy of at least 99. 7%, for which the Examiner
cites the same paragraphs of Assaf and Seiberlich as for claims 19 and 20
(i.e., paragraphs 151 of Assaf and paragraph 7 of Seiberlich). Appellants
assert that they do "not understand these paragraph to teach or suggest the
claimed clustering assignment accuracy of at least 99%. Assaf is describing
a graph of MRI layer width vs. cytoarchitechtonic layer width." App. Br.
22.
As to the Voronoi groups, the Examiner finds Assaf discloses
employing a k-means clustering algorithm which leads to the same k-means
clustering analysis of the claims. Ans. 39--40 (citing Assaf,I 125). The
Examiner also finds that Assaf discloses providing high contrast for different
parts of the cortex which parallel the clustering for the regions. Final Act.
21.
We agree with the Examiner that Assaf s k-means clustering and high
contrast regional profiles discloses that the clusters represent V oronoi
groups. In particular, we note that Appellants' Specification defines "[a]
'cluster' as used herein refers to, for example, a Voronoi group produced by
k-means cluster analysis." Spec. ,r 33. The Specification goes on to explain:
K-means analysis is a method for quantization of vectors. K-
means analysis or clustering partitions n observations into k
clusters in which each observation belongs to the cluster with the
nearest mean. The nearest mean may be a "seed value" that
serves as a prototype for the cluster. Example seed values may
have been computed from previously acquired signals or from
signals stored in the dictionary. The result of k-means clustering
is a partitioning of the data space into Voronoi cells.
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Spec. ,r 58 ( emphasis added). Thus, by disclosing the same k-means
clustering as the claimed invention, Assaf teaches or suggests that the
clusters represent Voronoi groups produced by a k-means analysis.
As to Appellants' arguments regarding claim 32's requirement of
99. 7% accuracy for clustering, the Examiner finds Assaf teaches or suggests
an accuracy of at least 99. 7% by disclosing a "correlation coefficient" that
provides accuracy of above cluster analysis, which has a p value of less than
0.0001 reflecting the accuracy of the cluster analysis as being higher than
99.7%. Ans. 40 (citing Assaf,I 151). We are unpersuaded of Examiner
error by Appellants' argument that they do "not understand these paragraph
to teach or suggest the claimed clustering assignment accuracy of at least
99%. Assaf is describing a graph of MRI layer width vs. cytoarchitechtonic
layer width." App. Br. 22. In particular, we are not persuaded that
providing a correlation coefficient between Assaf s "cluster analysis of an
inversion recovery dataset" and "cyto-architectonic analysis" does not show
accuracy of the clustering assignment. Assaf ,r 14 7. Indeed, Assaf states
that a "[b Jetter understanding of the biological meaning of the MRI layers"
is provided "by one-to-one comparison" with cyto-architectonic analysis.
Assaf,I 146. By simply stating that they do not understand the cited
paragraph to teach or suggest the disputed limitation, and briefly
summarizing the Assaf' s disclosure regarding rvfRI layer width versus cyto-
architectonic layer width, Appellants do not address the Examiner's finding
regarding Assaf's correlation coefficient having a p value of less than
0.0001.
Accordingly, we sustain the Examiner's rejection of claim 32.
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Claim 39
Appellants make many of the same arguments for claim 39 as they did
for claim 1. As with claim 32, we find these arguments to be unpersuasive
for the reasons stated above with respect to claim 1. In addition, Appellants
focus on the formula for signal evolution contained in claim 39 and argue
the claims make explicit that Mo is treated as a distinct MR
parameter that can and is separated from other MR parameters
such as Tl and T2 relaxation. Whether or not Mo, Tl, and T2 are
related does not equate to using two of these, at least one of
which is Mo, in the claimed clustering process using MRF data.
App. Br. 24.
The Examiner finds the formula recited in claim 39 is taught by
Assaf's equation in paragraph 85: "M(TL)/Mo = 1 - 2eC-Tii/n)_" See Final
Act. 25. This is the same finding the Examiner made with respect to claims
28-31. We are persuaded of Examiner error for the same reasons as stated
with respect to claims 28-31.
DECISION
The Examiner's rejection of claims 1-27, 32, 34--36, and 38 is
affirmed.
The Examiner's rejection of claims 28-31 and 39 is reversed.
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a). See 37 C.F.R.
§ 41.50(±).
AFFIRMED-IN-PART
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