DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
Applicants Amendments filed on June 6, 2026, have been entered and made of record.
Currently pending Claim(s): 1-20
Independent Claim(s): 1, 14, 15
Amended Claim(s): 1, 13-15
New Claim(s): 20
Response to Arguments
This office action is responsive to the Applicant’s Arguments/Remarks Made in an Amendment
received on June 6, 2026.
Claim Rejections – 35 U.S.C. 101
In view of the new claim amendments and Applicant’s arguments filed on June 6, 2026, with respect to Claims 1-11 and 16-19, under 35 U.S.C 101 claim rejections has been fully considered and the arguments are found to be not persuasive.
The Applicant argued (on Remarks pg. 8, paragraph 3), that the human mind is not equipped to “evaluate a region of the image based on an assessment of risk of the anatomical nodal region comprising a malign lymph node”. The Applicant explained (on Remarks pg. 9, paragraph 2) that “the human mind is not equipped to perform an evaluation of more than a few lymph nodes”, and thus the claimed “per nodal region” approach cannot be practically performed in the human mind.
The Examiner respectfully disagrees with the Applicant’s assertion. The claim language does not explicitly teach that each region comprises multiple lymph nodes. Furthermore, Applicant’s specification states that a person may examine a region of the image, and determine if the region comprises a malign lymph node (see paragraph [0004]). Thus, the Examiner argues that a person can practically ‘evaluate a region of the image based on an assessment of risk of the anatomical nodal region comprising a malign lymph node’.
The Applicant then argued (on Remarks pg. 9, paragraph 3), that the element of “evaluating a region of the image based on assessment of risk of the anatomical nodal region comprising a malign lymph node” should be analyzed as an ‘additional limitation’. The Applicant explained (on Remarks, pg. 12, paragraph 2) that this additional limitation “provide[s] an improved risk assessment per nodal region approach which addresses the problem of existing lymph node assessments being limited to a few selected lymph nodes”, and thus the element constitutes significantly more than an abstract idea.
The Examiner respectfully disagrees. The Examiner has categorized the argued limitation as an ‘abstract idea’. As discussed earlier, the Examiner argues that a person may reasonably examine a region of an image, and determine if the region comprises a malign lymph nodes. The claim language does not explicitly teach that each region comprises multiple lymph nodes. Therefore, the Examiner maintains that the element of ‘evaluating a region of the image based on assessment of risk of the anatomical nodal region comprising a malign lymph node’ is an abstract idea, and therefore cannot be categorized as ‘additional limitation’.
Furthermore, the broadest reasonable interpretation of the claims does not specifically reflect any improvement disclosed in the specification.
MPEP 2106.05(f) provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instructions to implement an abstract idea on a computer: (1) whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished; (2) whether the claim invokes computers or other machinery merely as a tool to perform an existing process; and (3) the particularity or generality of the application of the judicial exception.
The limitation of ‘a region’ under the broadest reasonable limitation may comprise lymph nodes, but the neither the claims specification does not explicitly teach that the region comprises an amount of lymph nodes that would prevent a person from examining the region and determining if the region comprises a malign lymph node. Furthermore, the claim language does not explicitly teach that each region comprises multiple lymph nodes. Thus, the Examiner has concluded that that the current claim language does not reflect an improvement, and thus, Claim 1 remains rejected under 35 U.S.C 101.
Accordingly, the rejection of claims under 35 U.S.C 101 is maintained.
Claim Rejections – 35 U.S.C. 103
In view of the claim amendments filed on June 6, 2026, the Applicant has amended independent Claim 1 to recite the additional imitation of “obtaining lymph nodes delineated from segmented image data corresponding to the image”. Originally, (in the claim set dated June 13, 2024) Claim 1 recited, “receiving lymph nodes delineated from segmented image data; classifying at least one of the lymph nodes as belonging to an anatomical nodal region; evaluating a region of the image based on an assessment of the risk of the anatomical nodal region comprising a malign lymph node; and indicating the evaluation of the region”, and was rejected over Kim et al., (KR Pub No 20100019057), hereinafter Kim , in view of Liu et al. (Liu, J., et al., , “Mediastinal lymph node detection and station mapping on chest CT using spatial priors and random forest”. Med. Phys., 43: 4362-4374, (2016)), hereinafter Liu.
As discussed in the following paragraphs, Applicant's arguments filed have been fully considered but they are not persuasive. In view of Applicant’s Arguments/Remarks filed on June 6, 2026, with respect to the claims, the Applicant explained (on Remarks pg. 13, paragraph 1) that Kim discloses a “node-based extraction of a lymph node”, and therefore, cannot disclose “ a region-based assessment of risk of an anatomical region”.
The Examiner respectfully disagrees. The instant specification states that ‘a region’ is “an anatomical nodal region (e.g. an anatomically defined region of nodes (e.g. lymph nodes))”. Kim teaches obtaining lymph nodes (see paragraph [0054], “automatically extracts a lymph node region”);
determining an anatomical position of the lymph node region (see paragraph [0044], “According to the present invention, the signal intensity information, the manifestation diffusion coefficient information, and the anatomical position information of the lymph node, which are pre-specified for the lymph node, are obtained”)
evaluating a region of the image based on an assessment of the risk of the anatomical region comprising a malign lymph node (see paragraph [0046], “In addition, after the final extraction of the lymph node region, the present invention may further include predicting lymph node metastasis using image information and pre-entered clinical information about the lymph node region”, and region (see Kim, Fig. 10, where multiple lymph nodes are identified as malignant, and the corresponding lymph node regions are marked). Thus, it is clear that Kim teaches region based assessment of anatomical region.
The Applicant then argued (on Remarks, pg. 13, paragraph 3), that the combination of Kim and Liu would not teach “a region-based assessment of risk of an anatomical nodal region”. The Examiner respectfully disagrees. Kim teaches extracting a lymph node region (see paragraph [0054]), and evaluating a region of the image based on an assessment of the risk of the anatomical region comprising a malign lymph node (see paragraph [0046]). Liu teaches the classification of lymph node regions (see page 4370, Section 3). Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the delineation and classification of lymph nodes taught by Liu with the method taught by Kim. The motivation for doing so would be to accurately report diseased lymph nodes in a standardized way (see Liu, pg. 4362, Section 1).
Thus, for the reasons described above, the Examiner maintains the 103 rejection of Claims 1, 14, and 15 over Kim and Liu. Therefore, the rejection to the dependent Claims 2-13, and 16-19 are maintained.
As to newly added Claim 20, Kim teaches segmenting lymph nodes in image data corresponding to the image (see Kim, paragraph [0067], “The tertiary extraction step (S123) is to attempt the third segment of the lymph node based on the predetermined anatomical position of the lymph node region in the secondary segmented region using this point”), and Liu teaches that lymph nodes can delineated from segmented image data (see page 4365, “In this work, using the centroids of lymph node candidates as seed points a level-set-based curve evolution is applied to segment the lymph nodes. An ellipsoid [Fig. 8(c)] is fitted and its short axis is estimated”), and see Fig. 8, where the green ellipsoid delineates the lymph node). Thus, Claim 20 is rejected under Kim and Liu. The motivation for combining Liu with Kim would be to be to use the delineation taught by Liu to determine the length of the short axis of the lymph node, which can be used to determine malignancy (see Liu, page 4362, Section 1).
Claim Objections
Claim 13 is objected to because of the following informalities:
Claim 13 recites the limitation of “the model” in line 8. There is insufficient antecedent basis for this limitation in the claim.
Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim(s) 1-11 and 16-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The limitations, under their broadest reasonable interpretation, cover mental processes (concepts performed in a human mind, including an observation, evaluation, judgment, opinion, organizing human activity and/or mathematical concepts and calculations).
The independent Claims 1, 14, and 15 disclose a method and a system for identifying malignant lymph nodes. This judicial exception is not integrated into a practical application because the steps do not add meaningful limitations to be considered specifically applied to a particular technological problem to be solved .The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the steps of the claimed invention can be done mentally and no additional features in the claims would preclude them from being performed as such except for the generic computer elements at high level of generality (i.e., processor, memory).
According to the USPTO guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that the Claims 23, 40 ,41 and 42 are directed to an abstract idea as shown below:
STEP 1: Do the claims fall within one of the statutory categories?
YES. The independent claims 1, 14, and 15 is directed towards a method (a process), a product (manufactures) , and a system (an apparatus) for identifying malignant lymph nodes, respectively.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?
YES, the claims are directed toward a mental processes and/or mathematical concepts (i.e. abstract idea).
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
The method of Claim 1 and the system in Claim 15 comprise mental processes that can be practicably performed in the human mind (or generic computers or components configured to perform the method) and, therefore, an abstract idea.
Regarding the method of Claim 1: the method recites the steps of
classifying at least one of the lymph nodes as belonging to an anatomical nodal region (classifying lymph nodes can be done in the human mind as an observation, evaluation, judgement or opinion);
evaluating a region of the image based on an assessment of the risk of the anatomical nodal region comprising a malign lymph node (a person may observe an image, observe whether a malign lymph node exists, and evaluate a region of the image mentally ).
Regarding the product of Claim 14 and the system of Claim 15: the product and system recite the limitations of
classify at least one of the lymph nodes as belonging to an anatomical nodal region (classifying lymph nodes can be done in the human mind as an observation, evaluation, judgement or opinion);
evaluate a region of the image based on an assessment of the risk of the anatomical nodal region comprising a malign lymph node (a person may observe an image, observe whether a malign lymph node exists, and evaluate a region of the image mentally).
These limitations, as drafted, are a simple process that, under their broadest reasonable interpretation, covers performance of the limitations in the mind or by a human. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that “can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same).
As such, a person could mentally classify the lymph nodes and evaluate the region of the image through observation and evaluation. The mere nominal recitation that the various steps are being executed by a system with a memory and processor does not take the limitations out of the mental process and/or mathematical concepts groupings. Thus, the claims recite a mental process.
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
NO, the claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Independent Claims 1 and 15 do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application.
Claim 1 recites the further limitations of:
A computer implemented method of processing an image of a subject (generic computer component configured to perform the method);
obtaining lymph nodes delineated from segmented image data corresponding to the image (insignificant pre-solution activity of gathering data);
and indicating the evaluation of the region (insignificant post-solution activity of displaying data).
Claim 14 recites the further limitations of:
A non-transitory computer-readable storage medium having stored a computer program comprising instructions, which, when executed by a processor, cause the processor to (generic computer or components configured to perform the method).
obtain lymph nodes delineated from segmented image data corresponding to the image (insignificant pre-solution activity of gathering data);
and indicate the evaluation of the region (insignificant post-solution activity of displaying data).
Claim 15 recites the further limitations of:
A system for processing an image of a subject comprising lymph nodes, the system comprising (generic computer or components configured to perform the method);
a memory comprising instruction data representing a set of instructions (generic computer or components configured to perform the method);
a processor configured to communicate with the memory and to execute the set of instructions, wherein the set of instructions, when executed by the processor, cause the processor to (generic computer or components configured to perform the method);
indicate the evaluation of the region (insignificant post-solution activity of displaying data).
These limitations are recited at a high level of generality (i.e. as a general action or change being taken based on the results of the acquiring step) and amounts to mere post solution actions, which is a form of insignificant extra-solution activity. Further, the claims are claimed generically and are operating in their ordinary capacity such that they do not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No, the claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Independent Claims 1, 14, and 15 do not recite any additional elements that are not well-understood, routine or conventional. The use of a generic computer elements are routine, well-understood and conventional process that is performed by computers.
Thus, since Claims 1 and 15 are: (a) directed toward an abstract idea, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that independent claims 1 and 15 are not eligible subject matter under 35 U.S.C 101.
Regarding Claim 2: the additional limitations do not integrate the mental process into a practical application or add significantly more to the mental process. The limitation(s) “wherein the region is evaluated with respect to at least one risk factor” falls into the mental processes grouping of abstract ideas. An individual may mentally evaluate an image with respect towards a risk factor.
Regarding Claim 3: the additional limitations do not integrate the mental process into a practical application or add significantly more to the mental process. The limitation(s) “a volume of a lymph node; a length of a short axis of a lymph node; a length of a long axis of a lymph node; a quantitative texture measure; a positron emission tomography (PET) intensity; an increased size of a lymph node; a metabolic activity; a formation of a merged lymph node cluster; a regional lymphatic tissue volume; or a grey-value statistic” falls into the mental processes grouping of abstract ideas. An individual may observe an image and determine if a merged lymph node cluster has formed.
Regarding Claim 4: the additional limitations do not integrate the mental process into a practical application or add significantly more to the mental process. The limitation(s) “wherein the evaluation comprises evaluating a plurality of lymph nodes with respect to at least one risk factor, and evaluating the region based on the evaluation of at least one of the plurality of lymph nodes in the region” falls into the mental processes grouping of abstract ideas. An individual may visually observe multiply lymph nodes within an image, and then evaluate the lymph nodes.
Regarding Claim 5: the additional limitations do not integrate the mental process into a practical application or add significantly more to the mental process. The limitation(s) “wherein the risk factor is region dependent” falls into the mental processes grouping of abstract ideas. An individual may visually observe what region the lymph node is, and then determine the appropriate risk factor.
Regarding Claim 6: the additional limitations do not integrate the mental process into a practical application or add significantly more to the mental process. The limitation(s) “wherein indicating the evaluation comprises outputting at least one of: a risk statistic of the region; a colour overlay corresponding to the image indicating the risk associated with the region; a heat map corresponding to the image indicating the risk associated with the region; or an overlay on a potentially malignant lymph node” are merely expanding on the insignificant post-solution activity of displaying data.
Regarding Claim 7: the additional limitations do not integrate the mental process into a practical application or add significantly more to the mental process. The limitation(s) “wherein the evaluating further comprises comparing the assessment of risk of a region to a previously obtained assessment of risk of the region” falls into the mental processes grouping of abstract ideas. An individual may observe a region of the image, and then mentally evaluate the image by comparing to a previous assessment.
Regarding Claim 8: the additional limitations do not integrate the mental process into a practical application or add significantly more to the mental process. The limitation(s) “wherein the evaluating further comprises determining if the region has at least one of: an increased risk compared to the previously assessed risk; or a high-variation in the previous assessment of risk and the current assessment of risk compared to the previously assessed risk” falls into the mental processes grouping of abstract ideas. An individual may observe a region of an image and determine if the risk has changed compared to a previous assessment.
Regarding Claim 9: the additional limitations do not integrate the mental process into a practical application or add significantly more to the mental process. The limitation(s) “ wherein the evaluation is performed for a plurality of regions of the image” falls into the mental processes grouping of abstract ideas. An individual may observe multiple regions of an image, and evaluate all regions mentally.
Regarding Claim 10: the additional limitations do not integrate the mental process into a practical application or add significantly more to the mental process. The limitation(s) “wherein the indication of the evaluation comprises at least one of: a region risk statistic; a list of regions with an indication of the evaluation of each region; a list of regions ordered based on the evaluation of each region; or a heatmap corresponding to the evaluation of each region” are merely expanding on the insignificant post-solution activity of displaying data.
Regarding Claim 11: the additional limitations do not integrate the mental process into a practical application or add significantly more to the mental process. The limitation(s) “a trained model” is a generic computer component.
Regarding Claim 14: the additional limitations do not integrate the mental process into a practical application or add significantly more to the mental process. The limitation(s) “A computer program product comprising a computer readable medium, the computer readable medium having computer readable code embodied therein, the computer readable code being configured such that, on execution by a suitable computer or processor” is/are a generic computer components.
Regarding Claim 16 and 18: the additional limitations do not integrate the mental process into a practical application or add significantly more to the mental process. The limitation(s) “segmenting lymph nodes in image data corresponding to the image” falls into the mental processes grouping of abstract ideas. An individual may observe an image and mentally determine where a lymph node is an image.
Regarding Claim 17 and 19: the additional limitations do not integrate the mental process into a practical application or add significantly more to the mental process. The limitation(s) “ delineating lymph nodes from segmented image data” falls into the mental processes grouping of abstract ideas. An individual may observe an image and manually delineate or outline lymph nodes with the assistance of pen and paper.
Regarding Claim 12, the limitation(s) “the training data includes an image of a subject with at least one annotation of a lymph node, and the risk of the lymph node being malign or a set of rules for assessing whether a lymph node is malign, and an annotation indicating at least one anatomical nodal region” are NOT directed toward an abstract idea since it recites additional elements that integrate the judicial exception into a practical application and add significantly more that the judicial exception. Therefore, Claim 13 is not directed to an abstract idea and therefore is/are not rejected under 35 USC 101.
Regarding Claim 13, the limitation(s) “obtaining training data, the training data comprising an image of a subject with at least one annotation of a lymph node, and the risk of the lymph node being malign or a set of rules for assessing whether a lymph node is malign, and an annotation indicating at least one anatomical nodal region; and training the model based on the training data to evaluate a region of the image based on an assessment of the risk of the anatomical nodal region comprising a malign lymph node” are NOT directed toward an abstract idea since it recites additional elements that integrate the judicial exception into a practical application and add significantly more that the judicial exception. Therefore, Claim 13 is not directed to an abstract idea and therefore is/are not rejected under 35 USC 101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim 1-6, 9-13, and 16-17 is rejected under 35 U.S.C. 103 as being unpatentable over Kim et al., (KR Pub No 20100019057), hereinafter Kim , in view of Liu et al. (Liu, J., et al., , “Mediastinal lymph node detection and station mapping on chest CT using spatial priors and random forest”. Med. Phys., 43: 4362-4374, (2016)), hereinafter Liu.
As to Claim 1, Kim teaches obtaining lymph nodes from segmented image data corresponding to the image (see paragraph [0054], “The lymph node extraction system 100 based on the diffusion emphasis image will be described with reference to FIG. 2 as follows. The lymph node extraction system 100 includes a lymph node segment 110, a lymph node classifier 120, an image display unit 130, and a setting input unit 140”);
determining an anatomical position of the lymph node region (see paragraph [0044], “According to the present invention, the signal intensity information, the manifestation diffusion coefficient information, and the anatomical position information of the lymph node, which are pre-specified for the lymph node, are obtained”)
evaluating a region of the image based on an assessment of the risk of the anatomical region comprising a malign lymph node (see paragraph [0046], “In addition, after the final extraction of the lymph node region, the present invention may further include predicting lymph node metastasis using image information and pre-entered clinical information about the lymph node region”); and
indicating the evaluation of the region (see paragraph [0075], “In addition, for each lymph node region, information such as the manifestation of diffusion coefficient, long diameter, short diameter, irregularity of the outer margin, volume of the primary tumor, invasion direction of the primary tumor, age, sex, and serum tumor factors may be displayed together”).
Kim fails to explicitly teach receiving delineated lymph nodes from segmented image data. Furthermore, Kim fails to explicitly teach classifying at least one of the lymph nodes as belonging to an anatomical nodal region
In an analogous art, Liu teaches that lymph nodes can be delineated from segmented image data (see page 4368-4369,Section 2.D., “In this work, using the centroids of lymph node candidates as seed points a level-set-based curve evolution is applied to segment the lymph nodes. An ellipsoid [Fig. 8(c)] is fitted and its short axis is estimated”), and see Fig. 8, where the green ellipsoid delineates the lymph node)),
and then be assigned to an anatomical nodal region see paragraph (see page 4370, Section 3, “With the segmentation of anatomic structures, we successfully assign the manually labeled lymph nodes to their stations in our previous work. In this work, we assign the detected lymph nodes to their stations to automate the standardized lymph node reporting according to the IASLC system”, where ‘station’ refers to anatomical nodal region).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the delineation and classification of lymph nodes taught by Liu with the method taught by Kim. The motivation for doing so would be to accurately report diseased lymph nodes in a standardized way. Liu teaches in page 4362, Section 1, “With regard to reporting pathologically enlarged mediastinal lymph node locations in the context of lung cancer, the International Association for the Study of Lung Cancer(IASLC) Staging Project has recently formulated a lymph node map to standardize reporting lymph node locations… The purpose of our work is to automatically detect pathologically enlarged mediastinal lymph nodes and to automate the standardized reporting of these lymph nodes according to the IASLC system.” Thus, it would have been obvious to combine the teachings of Kim with the teachings of Liu in order to obtain the invention as claimed in Claim 1.
As to Claim 2, Kim in view of Liu teaches wherein the region is evaluated with respect to at least one risk factor (see Kim, paragraph [0071], “In addition, the clinical information used for predicting the possibility of lymph node metastasis is clinical information about the lymph node in which metastasis is already confirmed, and is related to the volume of the primary tumor, the direction of expansion of the primary tumor, the age, sex, and primary tumor of the cancer patient”, where the volume of the lymph node is a risk factor).
As to Claim 3, Liu in view of Kim teaches wherein a risk factor comprises one or more of: a volume of a lymph node; a length of a short axis of a lymph node; a length of a long axis of a lymph node; a quantitative texture measure; a positron emission tomography (PET) intensity; an increased size of a lymph node; a metabolic activity; a formation of a merged lymph node cluster; a regional lymphatic tissue volume; or a grey-value statistic (see Kim, paragraph [0071], “In addition, the clinical information used for predicting the possibility of lymph node metastasis is clinical information about the lymph node in which metastasis is already confirmed, and is related to the volume of the primary tumor, the direction of expansion of the primary tumor, the age, sex, and primary tumor of the cancer patient”).
As to Claim 4, Liu in view of Kim teaches wherein the evaluation comprises evaluating a plurality of lymph nodes with respect to at least one risk factor, and evaluating the region based on the evaluation of at least one of the plurality of lymph nodes corresponding to the region (see Kim, Fig. 10, where multiple lymph nodes are identified as malignant, and the corresponding lymph node regions are marked).
As to Claim 5, Kim in view of Liu teaches that the region of the lymph node can help determine the malignancy of the lymph node (see Kim, paragraph [0071], “In addition, the clinical information used for predicting the possibility of lymph node metastasis is clinical information about the lymph node in which metastasis is already confirmed, and is related to the volume of the primary tumor, the direction of expansion of the primary tumor, the age, sex, and primary tumor of the cancer patient”, where the direction of expansion indicates that the region of the lymph is used to determine malignancy).
As to Claim 6, Kim in view of Liu teaches wherein indicating the evaluation comprises outputting at least one of: a risk statistic of the region; a colour overlay corresponding to the image indicating the risk associated with the region; a heat map corresponding to the image indicating the risk associated with the region; or an overlay on a potentially malignant lymph node region (see Kim, paragraph [0075], “The lymph node (large arrow) on the left side of the screen has a 100% chance of metastasis and the lymph node on the right (small arrow) has a 20% chance of metastasis. The prediction result may be a color representation (rainbow color table), a numerical representation (percentage, etc.), for visual division of probability. In addition, for each lymph node region, information such as the manifestation of diffusion coefficient, long diameter, short diameter, irregularity of the outer margin, volume of the primary tumor, invasion direction of the primary tumor, age, sex, and serum tumor factors may be displayed together”, and see Fig, 10, where risk statistic is shown).
As to Claim 9, Kim in view of Liu teaches wherein the evaluation is performed for a plurality of regions of the image (see Kim, Fig. 10, where two different regions are highlighted).
As to Claim 10, Kim in view of Liu teaches that the indication of the evaluation comprises at least one of: a region risk statistic; a list of regions with an indication of the evaluation of each region; a list of regions ordered based on the evaluation of each region; or a heatmap corresponding to the evaluation of each region (see Kim, paragraph [0075], “The lymph node (large arrow) on the left side of the screen has a 100% chance of metastasis and the lymph node on the right (small arrow) has a 20% chance of metastasis. The prediction result may be a color representation (rainbow color table), a numerical representation (percentage, etc.), for visual division of probability. In addition, for each lymph node region, information such as the manifestation of diffusion coefficient, long diameter, short diameter, irregularity of the outer margin, volume of the primary tumor, invasion direction of the primary tumor, age, sex, and serum tumor factors may be displayed together”, and see corresponding Fig. 10).
As to Claim 11, Kim in view of Liu wherein the evaluation is performed by a trained model (see Kim, paragraph [0070], “In this case, the lymph node classification unit 120 may predict the lymph node metastasis and classify the lymph node region as lymph node transition or non-transition”, where the ‘lymph node classifier’ is the trained model).
As to Claim 12, Kim teaches a model which can perform the evaluation (see paragraph [0070], “The lymph node classification unit 120 performs automated learning on the determination of lymph node metastasis based on each database of the accumulated image information and clinical information. The lymph node classifier 120 further improves the accuracy and reliability of the lymph node transition determination later”, where the ‘lymph node classifier’ is the trained model).
Kim fails to explicitly teach that the training data includes an image of a subject with at least one annotation of a lymph node, and the risk of the lymph node being malign or a set of rules for assessing whether a lymph node is malign, and an annotation indicating at least one anatomical nodal region.
Liu teaches a trained model has been trained to perform the evaluation based on training data comprising an image of a subject with at least one annotation of a lymph node and an annotation indicating at least one region (see Liu, page 4371, section 4.A, “A radiologist manually traced these lymph nodes slice-by-slice on the CT images. For each lymph node, its station was also recorded. These tracings and station labels served as the ground truth”). Liu additionally teaches a set of rules of assessing whether a lymph node is malignant (see page 4369, Section 2.D., “In our implementation, the lymph node candidates which have short axis less than 8 mm are removed from the detections since they do not meet the clinical criteria for abnormality and our system is designed to detect enlarged lymph nodes (lymph nodes measuring 10 mm or greater)”, where the minimum length of 10 mm is the ‘rule’ for determining malignancy).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the training data taught by Liu with the lymph node classifier taught by Kim. The motivation for doing so would be to would be to automatically identify malignant lymph nodes despite noise caused by surrounding tissues (see page 4372, Section 5., “In this work, we present an automatic method for mediastinal lymph nodes detection and station labeling on chest CT images, which is challenging due to the low contrast between surrounding structures and lymph nodes”). Thus, it would have been obvious to combine the training data taught by Liu with the teachings of Kim in order to obtain the invention as claimed in Claim 12.
As to Claim 13, Kim fails to explicitly teach obtaining training data. Kim teaches a model which can be used to evaluate a region of the image based on an assessment of the risk of the anatomical nodal region comprising a malign lymph node (see paragraph [0070], “The lymph node classification unit 120 performs automated learning on the determination of lymph node metastasis based on each database of the accumulated image information and clinical information”), but does not explicitly teach how the model is trained.
However, Liu teaches obtaining training data, the training data comprising an image of a subject with at least one annotation of a lymph node (see Liu, page 4371, section 4.A, “A radiologist manually traced these lymph nodes slice-by-slice on the CT images. For each lymph node, its station was also recorded. These tracings and station labels served as the ground truth”),
and the risk of the lymph node being malign or a set of rules for assessing whether a lymph node is malign (see page 4369, Section 2.D., “In our implementation, the lymph node candidates which have short axis less than 8 mm are removed from the detections since they do not meet the clinical criteria for abnormality and our system is designed to detect enlarged lymph nodes (lymph nodes measuring 10 mm or greater)”),
and an annotation indicating at least one anatomical nodal region (see Liu, page 4371, section 4.A, “A radiologist manually traced these lymph nodes slice-by-slice on the CT images. For each lymph node, its station was also recorded”); and
training the model based on the training data to evaluate a region of the image based on an assessment of the risk of the anatomical nodal region comprising a malign lymph node (see page 4371, Fig 18, where enlarged lymph nodes are shown with their station) .
Thus. it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the training data taught by Liu with the lymph node classifier taught by Kim. The motivation for doing so would be to automatically identify malignant lymph nodes despite noise caused by surrounding tissues as taught by Liu on page 4372. Thus, it would have been obvious to combine the training data taught by Liu with the teachings of Kim in order to obtain the invention as claimed in Claim 12.
As to Claim 16, Kim in view of Liu teaches segmenting lymph nodes in image data corresponding to the image (see Kim, paragraph [0067], “The tertiary extraction step (S123) is to attempt the third segment of the lymph node based on the predetermined anatomical position of the lymph node region in the secondary segmented region using this point”).
As to Claim 17, Kim in view of Liu fails to explicitly teach delineating lymph nodes from segmented image data. However, Liu teaches that lymph nodes can delineated from segmented image data (see page 4365, “In this work, using the centroids of lymph node candidates as seed points a level-set-based curve evolution is applied to segment the lymph nodes. An ellipsoid [Fig. 8(c)] is fitted and its short axis is estimated”), and see Fig. 8, where the green ellipsoid delineates the lymph node).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the lymph node delineation taught by Liu with the teachings of Kim in order to obtain the invention as claimed in Claim 17. The motivation for doing so would be to be to use the delineation to determine the length of the short axis of the lymph node, which can be used to determine malignancy (see Liu, page 4362, section 1, “lymph nodes measuring more than 15 mm in the short axis are designated as pathologically enlarged target lesions to be tracked”, where the risk factor is the length of the short axis of the lymph node, and see page 4392, “An ellipsoid [Fig. 8(c)] is fitted and its short axis is estimated”, and see Fig. 8(c), where lesion is delineated with ellipsoid, and the ellipsoid is used to determine the length of the short axis). Thus, it would have been obvious to combine the delineation taught by Liu with the teachings of Kim in order to obtain the invention as claimed in Claim 17.
Claim 7-8, 14-15, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Kim et al., (KR 20100019057), hereinafter Kim, in view of Liu et al. (Liu, J., et al., “Mediastinal lymph node detection and station mapping on chest CT using spatial priors and random forest”. Med. Phys., 43: 4362-4374, (2016)), hereinafter Liu, and further in view Jeraj et al. (US Pub No 20250057472), hereinafter Jeraj .
As to Claim 7, Liu in view of Kim fails to explicitly teach the evaluating further comprises comparing the assessment of risk of a region to a previously obtained assessment of risk of the region. However, in an analogous art, Jeraj teaches that a patient may be imaged at different points of time (see paragraph [0043], “The patient 12 may be imaged at multiple times including at least two different scans to produce molecular imaging data 15 that may be collected into two “scans” 16 a and 16 b, for example, scan 16a taken before and scan 16b taken after a session of treatment of the patient 12 by chemotherapy, radiation therapy, or the like.”
and that these two images can be evaluated to obtain an assessment of malignancy [0049], “Referring still to FIG. 2, at succeeding process block 36 a three-dimensional binary lesion mask 38 may be prepared for each of scans 16a and 16b representing a lesion 40, for example, at each voxel with a value of “1” and the absence of a lesion with a “0”),
and that these two assessments can be compared (see paragraph [0058], “At succeeding process block 62 and referring also to FIG. 5 , the resulting identification of corresponding lesions 40 among scans 16a and 16b allows each lesion 42 be identified as a corresponding lesion (having counterparts in both scans 16a and 16b) or an appearing lesion existing in scan 16b but having no counterpart in scan 16a or a disappearing lesions 40 having an instance in scan 16a but no corresponding lesion in scan 16b”).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the risk comparison taught by Jeraj with the teachings of Liu and Kim. The motivation for doing so would be to determine disease progression. Jeraj teaches in paragraph [0006], “The ability to obtain images of lesions has led to the investigation of automatic methods of lesion tracking using such images. In these systems, lesions are automatically identified, for example, by the molecular imaging signatures (e.g., uptake) in different images separated in time. Comparison of these images allows assessment of disease progression and/or the efficacy of the treatment”. Thus, it would have been obvious to combine the teachings of Jeraj with the teachings of Liu and Kim in order to obtain the invention as claimed in Claim 7.
As to Claim 8, Kim in view of Liu fails to explicitly teach wherein the evaluating further comprises determining if the region has at least one of: an increased risk compared to the previously assessed risk; or a -variation in the previous assessment of risk and the current assessment of risk compared to the previously assessed risk.
However, Jeraj teaches comparing two assessments of the same region (see paragraph [0058], “At succeeding process block 62 and referring also to FIG. 5 , the resulting identification of corresponding lesions 40 among scans 16a and 16b allows each lesion 42 be identified as a corresponding lesion (having counterparts in both scans 16a and 16b) or an appearing lesion existing in scan 16 b but having no counterpart in scan 16a or a disappearing lesions 40 having an instance in scan 16 a but no corresponding lesion in scan 16b”),
and determining if there is an increased risk or variation from the previous assessment (see paragraph [0058], “More generally shaded region areas 72 can be applied to the image 66 providing a mathematical generalization of those regions with respect to increase or decrease in lesion volume of the lesions in those regions, for example, red showing an increase in lesion volume and green showing a decrease in lesion volume”).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the risk comparison taught by Jeraj with the teachings of Liu and Kim. The motivation for doing so would be to determine disease progression as taught by Jeraj in paragraph [0006]. Thus, it would have been obvious to combine the teachings of Jeraj with the teachings of Liu and Kim in order to obtain the invention as claimed in Claim 8.
As to Claim 14 Kim in view of Liu teaches system for processing an image of a subject comprising lymph nodes (see Kim, Fig. 2, ‘lymph node extraction system’ 100), which can:
obtain lymph nodes delineated from segmented image data corresponding to an image; (see Kim, paragraph [0054], and see Liu page 4368-4369);
classify at least one of the lymph nodes as belonging to an anatomical nodal region (see Liu, page 4368-4369,Section 2.D.),
evaluate a region of the image based on an assessment of the risk of the anatomical nodal region comprising a malign lymph node (see Kim, paragraph [0046]), and
indicate the evaluation of the anatomical nodal region (see Kim, paragraph [0075]).
Kim in view of Liu fails to explicitly teach a non-transitory computer-readable storage medium having stored a computer program comprising instructions. However, Jeraj teaches a method of identifying lesions from medical image (see abstract), that can be stored on a computer readable media (see paragraph [0253], “The disclosed embodiments may comprise or utilize a special-purpose or general-purpose computer including computer hardware, such as, for example, one or more processors (such as hardware processor(s) 108) and system memory (such as hardware storage device(s) 112), as discussed in greater detail below. Embodiments also include physical and other computer-readable media for carrying or storing computer-executable instructions and/or data structures”).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the computer readable medium taught by Jeraj with method taught by Kim and Liu. The motivation for doing so would be allow a computer system to run the computerized process in a variety of computing systems. Jeraj teaches in paragraph [0250], “As noted above, a computing system 100 may include and/or be used to perform any of the operations described herein. Computing system 100 may take various different forms. For example, computing system 100 may be embodied as a tablet, a desktop, a laptop, a mobile device, a cloud device, a head-mounted display, or a standalone device”. Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the computer readable medium taught by Jeraj with the method taught by Kim and Liu in order to obtain the invention as claimed in Claim 14.
As to Claim 15, Kim in view of Liu teaches system for processing an image of a subject comprising lymph nodes (see Kim, Fig. 2, ‘lymph node extraction system’ 100), which can:
obtain lymph nodes delineated from segmented image data corresponding to an image; (see Kim, paragraph [0054], and see Liu page 4368-4369);
classify at least one of the lymph nodes as belonging to an anatomical nodal region (see Liu, page 4368-4369,Section 2.D.),
evaluate a region of the image based on an assessment of the risk of the anatomical nodal region comprising a malign lymph node (see Kim, paragraph [0046]), and
indicate the evaluation of the anatomical nodal region (see Kim, paragraph [0075]).
Kim in view of Liu fails to explicitly teach that the system comprises a memory comprising instruction data representing a set of instructions and a processor configured to communicate with the memory and to execute the set of instructions. However, Jeraj teaches a method of identifying lesions from medical image (see abstract), that can be stored on a computer readable media (see paragraph [0253], “The disclosed embodiments may comprise or utilize a special-purpose or general-purpose computer including computer hardware, such as, for example, one or more processors (such as hardware processor(s) 108) and system memory (such as hardware storage device(s) 112), as discussed in greater detail below”).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the computer readable medium taught by Jeraj with method taught by Kim and Liu. The motivation for doing so would be allow a computer system to run the computerized process in a variety of computing systems as taught by Jeraj in paragraph [0250].
As to Claim 18, Claim 18 teaches the same limitation as Claim 16 and is dependent on a similarly rejected independent claim. Therefore, the rejection and rationale are analogous to that made in Claim 16.
As to Claim 19, Claim 19 teaches the same limitation as Claim 17 and is dependent on a similarly rejected independent claim. Therefore, the rejection and rationale are analogous to that made in Claim 17.
As to Claim 20, Kim in view of Jeraj teaches segmenting lymph nodes in image data corresponding to the image (see Kim, paragraph [0067], “The tertiary extraction step (S123) is to attempt the third segment of the lymph node based on the predetermined anatomical position of the lymph node region in the secondary segmented region using this point”).
Kim in view of Jeraj fails to explicitly teach delineating lymph nodes from segmented image data. However, Liu teaches that lymph nodes can delineated from segmented image data (see page 4365, “In this work, using the centroids of lymph node candidates as seed points a level-set-based curve evolution is applied to segment the lymph nodes. An ellipsoid [Fig. 8(c)] is fitted and its short axis is estimated”), and see Fig. 8, where the green ellipsoid delineates the lymph node).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the lymph node delineation taught by Liu with the teachings of Kim and Jeraj in order to obtain the invention as claimed in Claim 20. The motivation for doing so would be to be to use the delineation to determine the length of the short axis of the lymph node, which can be used to determine malignancy (see Liu, page 4362, Section 1). Thus, it would have been obvious to combine the delineation taught by Liu with the teachings of Kim and Jeraj in order to obtain the invention as claimed in Claim 20.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Grimmer et al. (US Pub No 20200311919) teaches obtaining segmented lymph nodes, and then assigning the lymph nodes to an anatomical region. Grimmer et al. further teaches highlighting anatomical lymph node regions which comprises malignant lymph nodes (see paragraph [0113]), and highlighting anatomical lymph node regions indicate resection recommendations (see paragraphs [0116]).
Wagner et al. (US Pub No 20230285081) teaches a system for identifying anatomical lymph node regions which should be biopsied.
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/S.T./Examiner, Art Unit 2664 /JENNIFER MEHMOOD/Supervisory Patent Examiner, Art Unit 2664
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