DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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 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.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the claims at issue are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/forms/. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 52 and 63 are rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over Claims 1 and 13 of USPN 12002199 Although the claims at issue are not identical, they are not patentably distinct from each other. (see Claim-Comparison Table below for independent claim 52 of the instant application against Claim 1 of USPN 12002199).
Claim
Application#18645146
Claim
USPN 12002199
52
A computer system comprising
1
A system for determining characteristics of a brain lesion and tissue encompassing boundaries surrounding the brain lesion in three dimensions, the system comprising: a computer system including at least one processor configured to:
52
a segmentation application configured to receive magnetic resonance imaging data including one or more images and configured to segment the one or more images into one or more regions; (Claim limitation is more generic than the limitation on the right and therefore encompasses the scope of the claim limitation on the right)
1
receive data from a magnetic resonance imaging (MRI) machine configured to generate one or more series of images corresponding to a structural and a functional characteristic of a brain lesion and tissue encompassing one or more enlarged boundaries surrounding the brain lesion, the brain lesion having an outer boundary and at least part of the one or more enlarged boundaries surrounding the brain lesion being offset by a given distance from the outer boundary of the brain lesion; segment the received data to isolate a portion of the received data corresponding to the brain lesion and the tissue surrounding the brain lesion within the one or more enlarged boundaries;
52
a three-dimensional imaging application configured to receive a region of interest of the one or more regions from the segmentation application and generate one or more three- dimensional models of the region of interest, the region of interest corresponding to one or more brain lesions; and (Claim limitation is more generic than the limitation on the right and therefore encompasses the scope of the claim limitation on the right)
1
create, based on the segmented data, one or more three-dimensional (3D) models of the brain lesion and the tissue surrounding the brain lesion within the one or more enlarged boundaries; analyze, based on the one or more 3D models, one or more 3D phenotypic characteristics of the brain lesion and a slope of a blood oxygen level dependent (BOLD) signal from within the brain lesion through the one or more enlarged boundaries, and
52
a processing device configured to analyze one or more phenotypic characteristics of the one or more brain lesions and a slope of a blood oxygen level dependent signal from within the one or more brain lesions using the one or more three-dimensional models the processing device configured to determine an indicator of one or more brain lesion characteristics using the one or more phenotypic characteristics and the slope. (Claim limitation is more generic than the limitation on the right and therefore encompasses the scope of the claim limitation on the right)
1
determine, based on the one or more 3D phenotypic characteristics and the slope, indicators of one or more characteristics selected from a group of characteristics consisting of: lesion age, extent of injury, remyelination capacity, tissue integrity within the brain lesion, tissue integrity within tissue surrounding the brain lesion, and metabolic activity of the brain lesion within tissue surrounding the brain lesion.
Claim 62 of the instant application is equivalent in scope with Claim 13 of USPN 12002199.
Claim Rejections - 35 USC § 103
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 of this title, 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.
Claims 52-53, 55-58, 60-62, 65-68 and 70-71 are rejected under 35 U.S.C. 103 as being unpatentable over Sperling US2013/0211230 in view of Meyer et al. US2018/0344161 hereinafter referred to as Meyer and Santosh et al. US2009/0246138 hereinafter referred to as Santosh.
As per Claim 52, Sperling teaches a computer system comprising:
a segmentation application configured to receive magnetic resonance imaging data including one or more images and (Sperling, Paragraph [0036], “The medical imaging scan may comprise a magnetic resonance imaging scan having plurality of magnetic resonance planar images displaced along an axis, and the ultrasound data may comprise a plurality of ultrasound planar images, wherein the plurality of magnetic resonance planar images are inclines with respect to the plurality of ultrasound planar images”)
configured to segment the one or more images into one or more regions; (Sperling, Paragraph[0053], “Once received, the radiologist performs processing 52 of the MRI data, which includes segmentation… However, a radiologist will typical annotate 2D slices of radiological images, which does not require a 3D model, and the 3D modeling may benefit from a focus in accurately modeling the regions of interest, and thus in a preferred embodiment, the analysis precedes the segmentation”)
a three-dimensional imaging application configured to receive a region of interest of the one or more regions from the segmentation application and generate one or more three- dimensional models of the region of interest, and (Sperling, Paragraph[0053], “In this way, a 3D model may be generated for each region of interest. A digital file containing the post-processed MRI data is generated. In general, it is preferred that regions of interest are accurately modeled, so the annotation data provides clues to the modeling process of critical physical constraints. In the more general case, the MRI model may be formulated without any annotations, and indeed the 3D modeling may be performed prior to or concurrently with the radiological analysis.”)
Sperling does not explicitly teach the region of interest corresponding to one or more brain lesions;
a processing device configured to analyze one or more phenotypic characteristics of the one or more brain lesions
determine an indicator of one or more brain lesion characteristics using the one or more phenotypic characteristics
Meyer teaches the region of interest corresponding to one or more brain lesions;
a processing device configured to analyze one or more phenotypic characteristics of the one or more brain lesions
determine an indicator of one or more brain lesion characteristics using the one or more phenotypic characteristics(Meyer, Paragraph [0025], “For example, in addition to the displayed difference a region-wise profile that represents the characteristics of the lesions (e.g. in a region-of-interest) such as size, number, fractional volume etc. may be generated and displayed on the graphical user interface. The value of the parameter may for example in case of the brain be obtained by analyzing the identified (first and second) lesions with respect to its extension relative to the orientation of fiber bundles passing through the lesion to the cortical region of the brain”)
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Meyer into Sperling because by utilizing characteristics and region of interest to isolate lesions will allow for characterization and information about the lesions of a patient for further processing.
Sperling in view of Meyer does not explicitly teach a processing device configured to analyze a slope of a blood oxygen level dependent signal configured to determine an indicator of one or more brain lesion characteristics using the one or the slope.
Santosh teaches a processing device configured to analyze a slope of a blood oxygen level dependent signal configured to determine an indicator of one or more brain lesion characteristics using the one or the slope. (Santosh, Paragraph [0009], “The invention to be more particularly described hereinafter utilizes a contrast imaging technique of the "BOLD" type but adapted here by use together with an oxygen challenge to provide imaging for the assessment of the metabolic responses of tissue over a period of time. This approach permits the discrimination of oxygen, deoxyhaemoglobin and oxyhaemoglobin over a time period of evaluation of tissue metabolism which is not possible using hitherto published techniques. Thereby, oxygen use as contemplated herein with BOLD MRI imaging can be utilized as a biotracer, which offers benefits in the management of many common diseases”)
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Santosh into Sperling in view of Meyer because by including another metric to measure a brain lesion characteristic such as BOLD signal will allow for accurate characterization of brain lesions.
Therefore it would have been obvious to one of ordinary skill to combine the three references to obtain the invention in Claim 1.
As per Claim 53, Sperling in view of Meyer and Santosh teaches the computer system of claim 52, wherein the region of interest is selected automatically by the processing device. (Meyer, Paragraph [0025], “For example, in addition to the displayed difference a region-wise profile that represents the characteristics of the lesions (e.g. in a region-of-interest) such as size, number, fractional volume etc. may be generated and displayed on the graphical user interface. The value of the parameter may for example in case of the brain be obtained by analyzing the identified (first and second) lesions with respect to its extension relative to the orientation of fiber bundles passing through the lesion to the cortical region of the brain”)
The rationale applied to the rejection of claim 52 has been incorporated herein.
As per Claim 55, Sperling in view of Meyer and Santosh teaches the computer system of claim 52, further comprising: one or more databases storing the one or more brain lesion characteristics. (Meyer, Paragraph [0096], “The statistical analysis may be carried out on the identified white matter lesions (e.g. in the region of interest), and the white matter fibers which are affected by the white matter lesions are extracted. The results are visualized in a convenient format…The statistical assessment of the white matter lesions in the selected region of interest may comprise e.g. the number of white matter lesions, their total volume, their fractional volume (total volume of white matter lesions divided by total volume of the region), comparison of the statistical indices to reference databases and/or to a previous scan of the patient etc.).”)
The rationale applied to the rejection of claim 52 has been incorporated herein.
As per Claim 56, Sperling in view of Meyer and Santosh teaches the computer system of claim 52, wherein the one or more images include tissue within one or more boundaries surrounding the one or more brain lesions, at least a portion of the one or more boundaries being offset by a distance from an outer boundary of the one or more brain lesions. (Sperling, Paragraph[0053] and Meyer, Paragraph [0025])
The rationale applied to the rejection of claim 52 has been incorporated herein.
As per Claim 57, Sperling in view of Meyer and Santosh teaches the computer system of claim 52, wherein the one or more phenotypic characteristics include at least one of lesion volume, lesion surface texture, or lesion shape. (Meyer, Paragraph [0025], “For example, in addition to the displayed difference a region-wise profile that represents the characteristics of the lesions (e.g. in a region-of-interest) such as size, number, fractional volume etc. may be generated and displayed on the graphical user interface. The value of the parameter may for example in case of the brain be obtained by analyzing the identified (first and second) lesions with respect to its extension relative to the orientation of fiber bundles passing through the lesion to the cortical region of the brain”)
The rationale applied to the rejection of claim 52 has been incorporated herein.
As per Claim 58, Sperling in view of Meyer and Santosh teaches the computer system of claim 52, wherein the one or more brain lesion characteristics include at least one of a geometric characteristic, a surface characteristic, or a signal characteristic. (Meyer, Paragraph [0025], “For example, in addition to the displayed difference a region-wise profile that represents the characteristics of the lesions (e.g. in a region-of-interest) such as size, number, fractional volume etc. may be generated and displayed on the graphical user interface. The value of the parameter may for example in case of the brain be obtained by analyzing the identified (first and second) lesions with respect to its extension relative to the orientation of fiber bundles passing through the lesion to the cortical region of the brain”)
The rationale applied to the rejection of claim 52 has been incorporated herein.
As per Claim 60, Sperling in view of Meyer and Santosh teaches the computer system of claim 52, wherein the one or more images are two- dimensional images obtained using a magnetic resonance imaging device. (Sperling, Paragraph [0036], “The medical imaging scan may comprise a magnetic resonance imaging scan having plurality of magnetic resonance planar images displaced along an axis, and the ultrasound data may comprise a plurality of ultrasound planar images, wherein the plurality of magnetic resonance planar images are inclines with respect to the plurality of ultrasound planar images”)
The rationale applied to the rejection of claim 52 has been incorporated herein.
As per Claim 61, Sperling in view of Meyer and Santosh teaches the computer system of claim 52, wherein the slope is a rate of change in venous blood oxygen content from lesion tissue of the one or more brain lesions to brain tissue surrounding the one or more brain lesions. (Santosh, Paragraph [0009])
The rationale applied to the rejection of claim 52 has been incorporated herein.
As per Claim 62, Claim 62 claims a method as claimed in Claim 52. Therefore the rejection and rationale are analogous to that made in Claim 52.
As per Claim 65, Claim 65 claims the same limitation as Claim 55 and is dependent on a similarly rejected independent claim. Therefore the rejection and rationale are analogous to that made in Claim 55.
As per Claim 66, Claim 66 claims the same limitation as Claim 56 and is dependent on a similarly rejected independent claim. Therefore the rejection and rationale are analogous to that made in Claim 56.
As per Claim 67, Claim 67 claims the same limitation as Claim 57 and is dependent on a similarly rejected independent claim. Therefore the rejection and rationale are analogous to that made in Claim 57.
As per Claim 68, Claim 68 claims the same limitation as Claim 58 and is dependent on a similarly rejected independent claim. Therefore the rejection and rationale are analogous to that made in Claim 58.
As per Claim 70, Claim 70 claims the same limitation as Claim 60 and is dependent on a similarly rejected independent claim. Therefore the rejection and rationale are analogous to that made in Claim 60.
As per Claim 71, Claim 71 claims the same limitation as Claim 61 and is dependent on a similarly rejected independent claim. Therefore the rejection and rationale are analogous to that made in Claim 61.
Claims 54, 63-64 are rejected under 35 U.S.C. 103 as being unpatentable over Sperling US2013/0211230 in view of Meyer et al. US2018/0344161 hereinafter referred to as Meyer and Santosh et al. US2009/0246138 hereinafter referred to as Santosh as applied to Claim 52 and 62 respectively and further in view of Chiu et al. US2020/0001112 hereinafter referred to a Chiu.
As per Claim 54, Sperling in view of Meyer and Santosh teaches the computer system of claim 52,
Sperling in view of Meyer and Santosh does not explicitly teach wherein the one or more three-dimensional models include at least one of one or more three-dimensional maximum intensity projections images or one or more three-dimensional orthographic images.
Chiu teaches wherein the one or more three-dimensional models include at least one of one or more three-dimensional maximum intensity projections images or one or more three-dimensional orthographic images. (Chiu, Paragraph [0028])
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Chiu into Sperling in view of Meyer and Santosh because by providing the three-dimensional model with orthographic images will provide a model with stronger features for further processing.
Therefore it would have been obvious to one of ordinary skill to combine the four references to obtain the invention in Claim 54.
As per Claim 63, Sperling in view of Meyer and Santosh teaches the method of claim 62, further comprising:
Sperling in view of Meyer and Santosh does not explicitly teach causing a printing device to generate a physical representation of the one or more three- dimensional models.
Chiu teaches causing a printing device to generate a physical representation of the one or more three- dimensional models. (Chiu, Paragraph [0028])
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Chiu into Sperling in view of Meyer and Santosh because by providing means to 3D print the model will allow for another representation of the model for future processing.
Therefore it would have been obvious to one of ordinary skill to combine the four references to obtain the invention in Claim 63.
As per Claim 64, Claim 64 claims the same limitation as Claim 54 and is dependent on a similarly rejected independent claim. Therefore the rejection and rationale are analogous to that made in Claim 54.
Claims 59 and 69 are rejected under 35 U.S.C. 103 as being unpatentable over Sperling US2013/0211230 in view of Meyer et al. US2018/0344161 hereinafter referred to as Meyer and Santosh et al. US2009/0246138 hereinafter referred to as Santosh as applied to Claim 52 and 62 respectively and further in view of Moriya US2011/0075913.
As per Claim 59, Sperling in view of Meyer and Santosh teaches the computer system of claim 52,
Sperling in view of Meyer and Santosh does not explicitly teach wherein the indicator of the one or more brain lesion characteristics is determined using at least one of artificial intelligence, machine learning, or a deep learning technique.
Moriya teaches wherein the indicator of the one or more brain lesion characteristics is determined using at least one of artificial intelligence, machine learning, or a deep learning technique. (Moriya, Paragraph [0076], “Here, each of the plurality of lesion area extraction processing data is an evaluation function obtained with respect to each type of lesions, such as brain tumor, chest nodule, liver tumor, liver cyst, kidney cyst, and the like through machine learning a plurality of sample images which include each type of lesion area in advance to evaluate whether or not each pixel in a medical image is a pixel representing a contour of each type of lesion area”)
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Moriya into Sperling in view of Meyer and Santosh because by using machine learning will allow for automation of a manual process in assisting in determining lesions.
Therefore it would have been obvious to one of ordinary skill to combine the four references to obtain the invention in Claim 59.
As per Claim 69, Claim 69 claims the same limitation as Claim 59 and is dependent on a similarly rejected independent claim. Therefore the rejection and rationale are analogous to that made in Claim 59.
Conclusion
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/MING Y HON/Primary Examiner, Art Unit 2666
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