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 Arguments
Applicant’s arguments and amendments in the Amendment filed May 20, 2026 (herein “Amendment”), with respect to the rejection of claims 2 and 4–12 under 35 U.S.C. 101 for being directed towards an abstract idea without significantly more have been fully considered and are persuasive. The rejection of claims 2 and 4–12 under 35 U.S.C. 101 has been withdrawn.
Applicant’s arguments and amendments in the Amendment with respect to the rejections of claim 2 under 35 U.S.C. 103 as being unpatentable over Jeraj in view of Brynolfsson2 has been fully considered but are not persuasive. Specifically, the combination of Jeraj and the detailed teachings of Brynolfsson2 covering many permutations of visualizing tumors, organs, full body scans, differences in tumors over time with respective different scans, meet the claims as they have been presently amended. Jeraj fig. 5 teaches a visualization/display comprised of a full body scan which would cover multiple regions with different organs, and a chart depicting changes over time of the lesions. Although Jeraj does not explicitly teach multiple organs (despite showing a full body scan), it would be obvious in view of Brynolfsson2’s teachings of explicitly identifying, displaying and linking multiple organs over differently timed scans, to modify Jeraj with Brynolfsson2 to meet the newly claimed “aggregate measure of lesion changes for the at least two organs.” Therefore, the rejection of claim 2 under 35 U.S.C. 103 for the combination of Jeraj and Brynolfsson2 is maintained. In the present action, the additional rejection of claim 2 under 35 U.S.C. 103 as being unpatentable over Brynolfsson1, Dzyubachyk and Brynolfsson2 is withdrawn although these references continue to be relevant to the claims at issue.
Applicant’s arguments and amendments in the Amendment with respect to the rejections of claims 4–12 under 35 U.S.C. 103 as being unpatentable over Brynolfsson1 and Dzyubachyk have been fully considered but are not persuasive. Specifically, Applicant argues that Dzyubachyk does not teach or suggest the newly amended “graphically depicted link … that identify lesions as being linked pairs,” however, Brynolfsson1 is relied upon for teaching the graphically depicted link, and in the updated rejection rationale below, teaches also that the links identify lesions as being linked in pairs. Therefore, the rejection of claims 4–12 under 35 U.S.C. 103 for the combination of Brynolfsson1 and Dzyubachyk is maintained.
Applicant’s arguments and amendments in the Amendment with respect to the rejections of claims 4 and 7–12 under 35 U.S.C. 103 as being unpatentable over Jeraj in view of Brynolfsson1 have been fully considered but are not persuasive. Specifically, Applicant argues that “it is believed that Jeraj does not teach or suggest the newly amended “graphically depicted link … that identify lesions as being linked pairs,” however, Brynolfsson1 is relied upon for teaching the graphically depicted link, and in the updated rejection rationale below, Jeraj is relied upon for teaching that the links identify lesions as being linked in pairs. Therefore, the rejection of claims 4 and 7–12 under 35 U.S.C. 103 for the combination of Jeraj in view of Brynolfsson1 is maintained.
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 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.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Jeraj et al., US Patent Application Publication No. US 2022/0338805 A1 (herein “Jeraj”) in view of Brynolfsson et al., US Patent Application Publication No. US 2023/0410985 A1 (herein “Brynolfsson2”).
Regarding claim 2, with deficiencies of Jeraj noted in square brackets [], Jeraj teaches an apparatus for assessing treatment of a patient comprising (Jeraj Abstract, ¶¶5–6, apparatus for tracking disease progression and therapeutic response):
an electronic computer executing a stored program to (Jeraj ¶44):
(a) receive a set of at least two scans of tissue of the patient at different times revealing diseased tissue, the two scans in the form of an array of digital image values in an electronic format from a diagnostic imaging machine (Jeraj ¶43, patient imaged at least two different scans of image data (digitized image values in an electronic format), and then supplemented with scans from other scanners (diagnostic imaging machine), where ¶47 teaches pre-treatment earlier scans 16a and post-treatment later scans 16b (two scans, different times));
(b) process the digital image values to segment [at least two organs] within the patient (Jeraj ¶¶47, 49–51, lesions are registered (segmented) from the image including identification of lesions using binary lesion masks to keep track of specific lesions between scans);
(c) process the digital image values to determine lesion volumes in the scan as assigned to identifiers (Jeraj ¶49, lesion mask representing volumes, with each voxel having a value of either 1 for lesion present, or 0 for absence of a lesion);
(d) process the digital image values to determine an overlapping of lesion volumes between pairs of scans of the set to provide a set of overlap measures for each pair of scans for each pair of identifiers (Jeraj ¶52, amounts of overlap for each lesion in the scans are compiled and recorded in a matrix);
(e) process the digital image values to link pairs of the identifiers of different scans to globally maximize the overlap measures of the set over all of the scans (Jeraj ¶¶56, 58, linear assignment (link) of lesions in one scan to lesions in another scan is solved such that the amount of overlap between corresponding lesions is globally maximized); and
(f) output a display indicating a lesion change identified to given linked lesions (Jeraj ¶¶58, 44, identification of corresponding lesions from among the scans is provided on a display 30 in the form of a chart);
(g) link lesion changes to particular organs for multiple organs and lesions (Jeraj ¶¶44–45, output indicating disease progression or regression based on measures based on the scans, where the tracking can be of skin or brain lesions (skin and brain are organs), where ¶ 58 teaches the changes of lesions indicated x for disappearing lesions, or n for appearing lesions); and
wherein the output further identifies [an aggregate measure of] lesion changes [for the at least two organs] over the different separated times as linked [to the given organ for each of the at least two organs] (Jeraj ¶58, each lesion is identified and marked with an “x” for disappearing lesions or “n” for appearing lesions (change) between a first time scan 16a and a second time scan 16b , where ¶¶44–45, teaches indicating disease progression or regression based on measures based on the different separated times scans, where the tracking can be of skin or brain lesions (skin and brain are multiple organs)).
While Jeraj at least suggests that the output identifies some measure of a lesion change to one of the different organs for each of the different organs, Jeraj does not explicitly teach that the identification is “an aggregate measure of,” or with respect to multiple organs.
Brynolfsson2 teaches an aggregate measure of (Brynolfsson2 ¶¶41, 81–82, identifying hotspots indicating lesions and calculating a set of values tracking a change (aggregate measure) of the tumor burden over time for a plurality of medical images, and causing the display of a graphical representation of the values).
Brynolfsson2 further teaches for the at least two organs to the given organ for each of the at least two organs (Brynolfsson2 ¶¶81, and 271–272, figs. 10 and 11, quantifying tumor progression over time by obtaining scans obtained at a particular time, including first and second scans, where the scans are full body showing multiple organs, and the second scan is registered (linked) to the first, ¶¶283–284 teach matching (linking) hotspots appearing in different in time images with each other and identified as representing to a same underlying physical lesion, and where ¶146 teaches that an image or any other result (thus identifying of a lesion between two images) is displayed, and ¶¶183, 187, fig. 2, teaching that the segmentation map aligned with the boundaries of the multiple organs is overlaid upon a scan/functional image to classify hotspots, the hotspots being segmented, individually labeled and identifiable as corresponding to an organ).
Therefore, taking the teachings of Jeraj and Brynolfsson2 together as a whole, it would have been obvious to a person having ordinary skill in the art (herein “PHOSITA”) before the effective filing date of the claimed invention to have modified the image output of Jeraj to include the aggregate measures and multiple organs as disclosed in Brynolfsson2 at least because doing so would allow for informing clinical decision making, evaluating treatment efficacy, and predicting patient responses. See Brynolfsson2 Abstract.
Claims 4–12 are rejected under 35 U.S.C. 103 as being unpatentable over Brynolfsson1 in view of Dzyubachyk et al., “Comparative exploration of whole-body MR through locally rigid transforms,” Int J CARS, Springer, 2013 (herein “Dzyubachyk”).
Regarding claim 4, Brynolfsson1 teaches with deficiencies noted in square brackets [], Brynolfsson1 teaches an apparatus for assessing treatment of a patient comprising (Brynolfsson1 Abstract, ¶5, systems to analyze 3D images for lesion classification, where such information is used by physician to provide a recommended course of treatment to the patient and to track the progression of disease):
an electronic computer executing a stored program to (Brynolfsson1 ¶284, environment for the disclosed system including application servers (electronic computer) with storage and retrieval capabilities, and software to process data):
(a) receive a set of [at least three] scans of tissue of the patient revealing diseased tissue, [the three scans] in the form of an array of digital image values in an electronic format from a diagnostic imaging machine (Brynolfsson1 Fig. 7, ¶¶168, 201, 209, an anatomical CT image and a functional PET image forming a composite image pair are received, the images including pelvic lymph regions with hotspots that can be classified as a tumor (diseased tissue));
(b) process the digital image values to determine lesion volumes in the scan as assigned to identifiers (Brynolfsson1 ¶¶171–173, 201, 203–204, Fig. 9A, regions and boundaries in the anatomical and functional image are identified from reference markers in a pelvic atlas image that identify particular sub-volumes within the pelvic image, including a sub-volume associated with a particular pelvic lymph sub-region which is identified);
(c) process the digital image values to determine an overlapping of lesion volumes between all pairs of scans of the set to provide a set of overlap measures for each pair of scans for each pair of identifiers (Brynolfsson1 ¶¶180, 183, the Dice Score (overlap measures) is calculated as a performance metric to maximize (optimize) overlap between pelvic bone regions of a target segmentation map which represents a target anatomical image, and a pelvic bone regions of a pelvic atlas image (pair of identifiers));
(d) process the digital image values to link pairs of the identifiers of different scans to globally maximize the overlap measures of the set over all of the scans (Brynolfsson1 ¶¶180, 183, optimizing alignment (globally maximize) by co-registering the pelvic atlas image pelvic bone regions with the corresponding (link) pelvic bone regions of a target segmentation map derived from a target anatomic image from the CT image (scan)); and
(e) output a display indicating a lesion [change] identified to given linked lesions (Brynolfsson1 ¶¶287, 204, computer system including a display, and where hotspots located within a pelvic region can be overlaid on the functional image to identify corresponding volumes within the functional image, where the hotspot is identified as belonging to a potential lesion located within a particular one of the one or more pelvic lymph sub-regions, and where claim 16, element (e) teaches providing the transformed 3D pelvic atlas image);
further including a graphic display and wherein the electronic computer executing the stored program further outputs a graphic display providing a graphically depicted link (Brynolfsson1 ¶¶ 154–155, 160, fig. 4, each segmented hotspot (of a lesion) within a hotspot map is labeled, for example CIR, CIL, OBR, OBL) between representations of lesions of different scans of the patient (Brynolfsson1 ¶¶28, 116, transformed 3D pelvic images comprising the identified one or more pelvic lymph sub-regions aligned to the 3D anatomical images and segmentation thereof, and providing the transformed 3D pelvic atlas images to a display) that identify lesions as being linked pairs (Brynolfsson1 ¶¶151,154–155, each segmented hotspot within a hotspot map is individually identifiable/individually labeled (linked) and are labeled as corresponding to a bone, lymph or prostate lesion, thus linking the anatomical image to the functional image (linking between the two different scans/linked pairs)).
While Brynolfsson1 teaches that a set of anatomical images are received, Brynolfsson1 does not explicitly teach that the set consists of at least three scans.
Further, while Brynolfsson1 teaches that a transformed image with lesion hotspots shown on the image being provided and that the disclosed system includes a display, Brynolfsson1 does not explicitly teach the lesion change being indicated in the display.
Dzyubachyk teaches receiving a set of at least three scans of tissue (Dzyubachyk page 642, Fig. 6, visualization of changes between a baseline scan and three consecutive follow-up scans of lesions (tissue)), and the lesion change being indicated in the display (Dzyubachyk pages 641–642, figs. 5–6, color fusion in the displayed images simplifying visual assessment of changes between the baseline and follow-up scans).
Therefore, taking the teachings of Brynolfsson1 and Dzyubachyk together as a whole, it would have been obvious to a PHOSITA to have modified the images processed and displayed in Brynolfsson1 to be at least three scans and indicating lesion change in the display as taught in Dzyubachyk, at least because doing so would greatly simplify visual assessment of changes for a radiologist, thus saving time (see Dzyubachyk Abstract, Fig. 6).
Regarding claim 5, Brynolfsson1 does not explicitly teach, but Dzyubachyk teaches wherein the electronic computer executing the stored program further: receives input from a user to alter the linking of (d) and after that alteration repeats (e) (Dzyubachyk pages 640–641, the user interface allows users to click on a displayed image and align (linking) the follow-up image to the baseline using the locally rigid transform estimation surrounding the clicked point, where the images include overlay components including uncertainty contours overlay).
Therefore, taking the teachings of Brynolfsson1 and Dzyubachyk together as a whole, it would have been obvious to a PHOSITA to have modified the images processed and displayed in Brynolfsson to allow for user input resulting in changes in the display as taught in Dzyubachyk, at least because doing so would greatly simplify visual assessment of changes for a radiologist, thus saving time (see Dzyubachyk Abstract, Fig. 6).
Regarding claim 6, Brynolfsson1 does not explicitly teach, but Dzyubachyk teaches wherein the electronic computer executing the stored program further outputs uncertainty values on the graphics display associated with the linkage (Dzyubachyk page 641, an overlay on the displayed images including uncertainty contours which indicate accuracy of the estimation of the organ structures).
Therefore, taking the teachings of Brynolfsson1 and Dzyubachyk together as a whole, it would have been obvious to a person having ordinary skill in the art (herein “PHOSITA”) to have modified the images processed and displayed in Brynolfsson1 to include the uncertainty contours in the display as taught in Dzyubachyk, at least because doing so would greatly simplify visual assessment of changes for a radiologist, thus saving time (see Dzyubachyk Abstract, Fig. 6).
Regarding claim 7, Brynolfsson1 teaches wherein the lesion volumes are dilations of lesion images (Brynolfsson1 ¶¶190–191, 193, 201, multiple registration transformations are performed including a coarse registration transformation, and a fine registration transformation, of pelvic regions including lesions, the fine registration being determined using a second different resolution (dilation)).
Regarding claim 8, Brynolfsson1 teaches where in the electronic computer executing the stored program further clusters lesions in a given image to present a combined lesion volume at (b) (Brynolfsson1 ¶¶101, 340, processing of 3D images to identify cancerous lesions including image segmentation based on identification of clusters of voxels connected to each other in an n-component fashion having intensity values about a threshold thereby defining segmented volume for the hotspot (combined lesion)).
Regarding claim 9, Brynolfsson1 teaches wherein the clustering is according to a distance derived from an overlapping lesion from an other scan of the pair (Brynolfsson1 ¶¶282–291, in generating the hotspot map identifying cancerous lesions, matching hotspot volumes (overlapping) are identified based on proximity such as centers of gravity within a threshold distance).
Regarding claim 10, Brynolfsson1 does not explicitly teach, but Dzyubachyk teaches wherein the output characterizes the lesions as appearing or disappearing (Dzyubachyk page 64, color fusion view depicts areas that are decreasing (disappearing) with an orange color, and areas that are increasing (appearing) with a blue color).
Therefore, taking the teachings of Brynolfsson1 and Dzyubachyk together as a whole, it would have been obvious to a person having ordinary skill in the art (herein “PHOSITA”) to have modified the images processed and displayed in Brynolfsson1 to include the color fusion view in the display as taught in Dzyubachyk, at least because doing so would greatly simplify visual assessment of changes for a radiologist, thus saving time (see Dzyubachyk Abstract, Fig. 6).
Regarding claim 11, Brynolfsson1 teaches wherein the output indicates lesion volume (Brynolfsson ¶¶151, volumes within the functional image with segmentation map overlaid to identify volumes to classify hotspots). Brynolfsson1 does not explicitly teach, but Dzyubachyk teaches and change in other lesion measurements between scans (Dzyubachyk page 64, color fusion view depicts areas that are decreasing with an orange color, and areas that are increasing with a blue color (change in other lesion measurements)).
Therefore, taking the teachings of Brynolfsson1 and Dzyubachyk together as a whole, it would have been obvious to a person having ordinary skill in the art (herein “PHOSITA”) to have modified the images processed and displayed in Brynolfsson1 to include the color fusion view in the display as taught in Dzyubachyk, at least because doing so would greatly simplify visual assessment of changes for a radiologist, thus saving time (see Dzyubachyk Abstract, Fig. 6).
Regarding claim 12, Brynolfsson1 teaches wherein the output indicating a linkage is superimposed on at least one scan image (Brynolfsson1 ¶¶28, 116, transformed 3D pelvic images comprising the identified one or more pelvic lymph sub-regions aligned (linkage) to the 3D anatomical images and segmentation thereof, and providing the transformed 3D pelvic atlas images (superimposing) to a display).
Claims 4, and 7–12 are rejected under 35 U.S.C. 103 as being unpatentable over Jeraj in view of Brynolfsson1.
Regarding claim 4, Jeraj teaches an apparatus for assessing treatment of a patient comprising (Jeraj Abstract, ¶¶5–6, apparatus for tracking disease progression and therapeutic response):
an electronic computer executing a stored program to (Jeraj ¶44):
(a) receive a set of at least three scans of tissue of the patient revealing diseased tissue, the three scans in the form of an array of digital image values in an electronic format from a diagnostic imaging machine (Jeraj ¶43, patient imaged at least two different scans of image data (digitized image values in an electronic format), and then supplemented with scans from other scanners (diagnostic imaging machine));
(b) process the digital image values to determine lesion volumes in the scan as assigned to identifiers (Jeraj ¶49, lesion mask representing volumes, with each voxel having a value of either 1 for lesion present, or 0 for absence of a lesion);
(c) process the digital image values to determine an overlapping of lesion volumes between all pairs of scans of the set to provide a set of overlap measures for each pair of scans for each pair of identifiers (Jeraj ¶52, amounts of overlap for each lesion in the scans are compiled and recorded in a matrix);
(d) process the digital image values to link pairs of the identifiers of different scans to globally maximize the overlap measures of the set over all of the scans (Jeraj ¶¶56, 58, linear assignment (link) of lesions in one scan to lesions in another scan is solved such that the amount of overlap between corresponding lesions is globally maximized); and
(e) output a display indicating a lesion change identified to given linked lesions (Jeraj ¶¶58, 44, identification of corresponding lesions from among the scans is provided on a display 30 in the form of a chart); and
further including a graphic display (Jeraj ¶44, graphics display 30) and wherein the electronic computer executing the stored program further outputs a graphic display between representations of lesions of different scans of the patient (Jeraj ¶58, each lesion is identified from corresponding lesions in the scans, where an “x” for disappearing lesions or “n” for appearing lesions and a circle for corresponding lesions (linkage), additionally shading can be applied to the patient image with respect to increase or decrease in lesion volume between scans 16a and 16b) that identify lesions as being linked pairs (Jeraj ¶58, 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 (linked pairs)).
While Jeraj teaches a circle indication for corresponding lesions, Jeraj does not teach “providing a graphically depicted link” as claimed.
Brynolfsson1 teaches providing a graphically depicted link (Brynolfsson1 ¶¶ 154–155, 160, fig. 4, each segmented hotspot (of a lesion) within a hotspot map is labeled, for example CIR, CIL, OBR, OBL).
Therefore, taking the teachings of Jeraj and Brynolfsson1 together as a whole, it would have been obvious to a PHOSITA before the effective filing date of the claimed invention to have modified the visual display taught in Jeraj to include the graphical labels as disclosed in Brynolfsson1, at least because doing so would help determine predictions of cancer status, progression and response to treatment. Brynolfsson1 ¶151.
Regarding claim 7, Jeraj teaches wherein the lesion volumes are dilations of lesion images (Jeraj ¶¶50–51, identified lesions are dilated or expanded to create an expanded region about the lesions).
Regarding claim 8, Jeraj teaches where in the electronic computer executing the stored program further clusters lesions in a given image to present a combined lesion volume at (b) (Jeraj ¶¶53–54, possibility of merged lesions addressed through clustering operation where determined individual lesions are clustered to be a single logical lesion).
Regarding claim 9, Jeraj teaches wherein the clustering is according to a distance derived from an overlapping lesion from an other scan of the pair (Jeraj ¶54, clustering based on distance d between centroids of the determined individual lesions).
Regarding claim 10, Jeraj teaches wherein the output characterizes the lesions as appearing or disappearing (Jeraj ¶58, each lesion is identified from corresponding lesions in the scans, where an “x” for disappearing lesions or “n” for appearing lesions).
Regarding claim 11, Jeraj teaches wherein the output indicates lesion volume and change in other lesion measurements between scans (Jeraj ¶¶49, 58, lesion mask representing volumes, with each voxel having a value of either 1 for lesion present, or 0 for absence of a lesion, and each lesion is identified from corresponding lesions in the scans, where an “x” for disappearing lesions or “n” for appearing lesions (change)).
Regarding claim 12, Jeraj teaches wherein the output indicating a linkage is superimposed on at least one scan image (Jeraj ¶58, each lesion is identified from corresponding lesions in the scans, where an “x” for disappearing lesions or “n” for appearing lesions (linkage) and a circle for corresponding lesions, where fig. 5 teaches that the indications are marked (superimposed) on the image 66 of the patient (at least one scan image)).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: Sirohey et al., US Patent No. 7,953,265, directed towards visualizing changes in a lesion in a multi-organ scan, over time.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHELLE M KOETH whose telephone number is (571)272-5908. The examiner can normally be reached Monday-Thursday, 09:00-17:00, Friday 09:00-13:00, EDT/EST.
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MICHELLE M. KOETH
Primary Examiner
Art Unit 2671
/MICHELLE M KOETH/Primary Examiner, Art Unit 2671
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