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
Claims 1, 12, 16, and 20 are amended. Claims 1-20 are pending in this application.
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(s) 1-8, 10-16, and 18-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Grimmer et al., US 2018/0350075 in view of Charles et al., US 2021/0059561.
Regarding claim 1, Grimmer discloses a method of dynamically determining one or more anatomical structures associated with a biological lifeform (Abstract; indicating a measure of variation over time for the area of interest), comprising:
by a system:
obtaining first and second magnetic resonance (MR) measurements associated with the biological lifeform, and the first and second MR measurements were acquired at different times (para [0011]-[0019], [0091], [0127]-[0130], [0163]; a first medical image generated at a first time; a second medical image generated at a second time subsequent to the first time; scanning device used to obtain the respective image; a first medical image generated at a first time; magnetic resonance scanning device);
dynamically determining first and second instances of the one or more anatomical structures based at least in part on the first and second MR measurements, and a segmentation technique, wherein a given instance of the one or more anatomical structures corresponds to a given MR measurement (para [0011]-[0019], [0143],
[0164]-[0165]- area of interest may comprise a two or three dimensional portion of a medical image that is identified through segmentation. For example, it may be defined as a shape or volume within these dimensions, such as a circle or sphere having a defined center point and diameter; identifying an area of interest within the first medical image; identifying an area within the second medical image corresponding to the area of interest within the first medical image; the area of interest may be an area of an organ on which a medical treatment or therapy is to be performed); and
performing a quantitative comparison of the first instance of the one or more anatomical structures and the second instance of the one or more anatomical structures, wherein the quantitative comparison has an uncertainty of less than a predefined value (para [0145], [0165], [0168], [0169], [0173], [0200]- the control device 30 performs texture analysis on the identified area of interest to determine at least one texture metric associated with the first time. Texture analysis may comprise processing sets of pixel or voxel intensities from the area of interest to determine measures of the spatial arrangement of those intensities. The at least one texture metric may be a measure of this spatial arrangement, e.g. a computed statistical metric based on the sets of pixel or voxel intensities; correction factor, based on the scanning characteristic may be calculated by the control device 30 and the correction factor may be applied by the control device 30 to the respective image (i.e. the first or second medical image); the control device 30 compares the at least one texture metric associated with the second time with the at least one texture metric associated with the first time. If a plurality of texture metrics are generated based on each respective image, then the two sets of metrics may form the input to a comparison function; generate a more accurate and/or robust change metric; correction factor enables more accurate and robust comparison of medical images).
Grimmer discloses claim 1 as enumerated above, but Grimmer does not explicitly disclose wherein the first and second MR measurements were acquired while the
biological lifeform engaged in free breathing, without prospective gating based on a cardiac rhythm of the biological lifeform, or both, and the first and second MR measurements correspond to a single complete phase or cycle of motion during the free breathing as claimed.
However, Charles discloses generating at least one of the following using pre-acquired 19F magnetic resonance image (MRI) signal data of a patient associated with a perfluorinated gas and oxygen mixture: (i) a cine (the term “cine” refers to a series of images shown dynamically, e.g., a breathing lung in motion during a respiratory cycle or cycles (both inhale and exhale portions of the breathing cycle)) of free-breathing images of the lungs of the subject illustrating a temporal and spatial distribution of the perfluorinated gas in the lung space and lungs of the subject to provide ventilation image data over at least one respiratory cycle; The patient can then freely breathe air from the room and additional 19F signal can be obtained during additional respiratory cycles. The dissipation or trapping of the signal can be evaluated to assess regional or global measures of ventilation (para [0017], [0028], [0122], [0195], [0233]-[0235], [0238]).
Therefore, taking the combined disclosures of Grimmer and Charles as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate generating at least one of the following using pre-acquired 19F magnetic resonance image (MRI) signal data of a patient associated with a perfluorinated gas and oxygen mixture: (i) a cine (the term “cine” refers to a series of images shown dynamically, e.g., a breathing lung in motion during a respiratory cycle or cycles (both inhale and exhale portions of the breathing cycle)) of free-breathing images of the lungs of the subject illustrating a temporal and spatial distribution of the perfluorinated gas in the lung space and lungs of the subject to provide ventilation image data over at least one respiratory cycle; The patient can then freely breathe air from the room and additional 19F signal can be obtained during additional respiratory cycles. The dissipation or trapping of the signal can be evaluated to assess regional or global measures of ventilation as taught by Charles into the invention of Grimmer for the benefit of enhance the system to accurately perform quantitative comparison of anatomical structures in images.
Regarding claim 2, the method of claim 1, Grimmer in the combination further disclose wherein the biological lifeform comprises an animal or a human (para [0150]- object (for example, a patient 13)).
Regarding claim 3, the method of claim 1, Grimmer in the combination further disclose wherein the first or the second MR measurements comprise an MR scan of at least a portion of the biological lifeform (para [0127]-[0130]- magnetic resonance scanning device).
Regarding claim 4, the method of claim 1, Grimmer in the combination further disclose wherein the first or the second MR measurements comprise magnetic resonance imaging (MRI) or another MR technique (para [0127]-[0130]- magnetic resonance scanning device).
Regarding claim 5, the method of claim 1, Grimmer in the combination further disclose wherein obtaining the first and second MR measurements comprises: accessing the first and second MR measurements in memory; receiving the first and second MR measurements from a second system; or performing the first and second MR measurements (para [0011]-[0019]- accessing the first and second MR measurements in memory).
Regarding claim 6, the method of claim 1, Grimmer in the combination further disclose wherein the segmentation technique comprises or uses a pretrained model that was trained using a supervised learning technique (para [0159], [0164], [0212]- the machine learning algorithm may learn to detect features in the sample data; identify the area of interest based on input from a human operator, and/or on the basis of a machine learning algorithm; support vector machines, Bayesian classifiers, k-means clustering, decision trees, convolutional neural networks, deep belief networks, deep residual learning, reinforcement learning, recurrent neural networks, inductive programming, genetic algorithms and evolutionary algorithms).
Regarding claim 7, the method of claim 6, Grimmer in the combination further disclose wherein the supervised learning technique comprises a machine-learning technique (para [0159], [0164]- machine learning algorithm).
Regarding claim 8, the method of claim 6, Grimmer in the combination further disclose wherein the pretrained model comprises a neural network (para [0212] - convolutional neural networks, deep belief networks, deep residual learning, reinforcement learning, recurrent neural networks).
Regarding claim 10, the method of claim 1, Grimmer in the combination further disclose wherein the one or more anatomical structures comprises: a portion of an organ, or the organ (para [0164]- the area of interest may be an area of an organ on which a medical treatment or therapy is to be performed).
Regarding claim 11, the method of claim 1, Grimmer in the combination further disclose wherein the quantitative comparison comprises determining as a function of time: minimum and maximum volumes of the one or more anatomical structures; a center of mass of the one or more anatomical structures; or a moment of a distribution associated with the one or more anatomical structures (para [0024], [0174], [0185] - output a change metric indicating a measure of variation over time for the area of interest; the texture metrics may include one or more of: mean pixel intensity, maximum pixel intensity, minimum pixel intensity, uniformity, entropy (e.g. an irregularity of a gray-level histogram distribution), standard deviation of the gray level histogram distribution).
Regarding claim 12, this claim recites substantially the same limitations that are performed by claim 1 above, and it is rejected for the same reasons.
Regarding claim 13, this claim recites substantially the same limitations that are performed by claim 3 above, and it is rejected for the same reasons.
Regarding claim 14, this claim recites substantially the same limitations that are performed by claim 5 above, and it is rejected for the same reasons.
Regarding claim 15, this claim recites substantially the same limitations that are performed by claim 6 above, and it is rejected for the same reasons.
Regarding claim 16, this claim recites substantially the same limitations that are performed by claim 8 above, and it is rejected for the same reasons.
Regarding claim 18, this claim recites substantially the same limitations that are performed by claim 10 above, and it is rejected for the same reasons.
Regarding claim 19, this claim recites substantially the same limitations that are performed by claim 11 above, and it is rejected for the same reasons.
Regarding claim 20, this claim recites substantially the same limitations that are performed by claim 1 above, and it is rejected for the same reasons.
Claim(s) 9 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Grimmer et al., US 2018/0350075 in view of Charles et al., US 2021/0059561 and further in view of Kaditz et al., US 2017/0007148.
Regarding claim 9, the method of claim 1, Grimmer and Charles in the combination do not explicitly disclose wherein the predefined value comprises 10% as claimed.
However, Kaditz discloses the convergence criterion may include that the difference between the MR signals and the simulated MR signals is less than a predefined value (such as 0.1, 1, 3, 5 or 10%) and/or that the changes to the scanning instructions are less than the predefined value (para [0086], [0142], [0161]).
Therefore, taking the combined disclosures of Grimmer, Charles, and Kaditz as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the convergence criterion may include that the difference between the MR signals and the simulated MR signals is less than a predefined value (such as 0.1, 1, 3, 5 or 10%) and/or that the changes to the scanning instructions are less than the predefined value as taught by Kaditz into the inventions of Grimmer and Charles for the benefit of limiting the allowed uncertainty to a required less than 10% based on the criticality of the comparison performed.
Regarding claim 17, this claim recites substantially the same limitations that are performed by claim 9 above, and it is rejected for the same reasons.
Response to Arguments
Applicant's arguments filed 03/18/2026 have been fully considered but they are not persuasive.
Regarding independent claim 1, Applicant argues that Charles in the combination do not disclose “the first and second MR measurements correspond to a single complete phase or cycle of motion during the free breathing” as claimed. Examiner respectfully disagrees. As stated in the rejection above, Charles in the combination disclose generating at least one of the following using pre-acquired 19F magnetic resonance image (MRI) signal data of a patient associated with a perfluorinated gas and oxygen mixture: (i) a cine (the term “cine” refers to a series of images shown dynamically, e.g., a breathing lung in motion during a respiratory cycle or cycles (both inhale and exhale portions of the breathing cycle) (i.e., a single complete cycle)) of free-breathing images of the lungs of the subject illustrating a temporal and spatial distribution of the perfluorinated gas in the lung space and lungs of the subject to provide ventilation image data over at least one respiratory cycle; The patient can then freely breathe air from the room and additional 19F signal can be obtained during additional respiratory cycles. The dissipation or trapping of the signal can be evaluated to assess regional or global measures of ventilation (para [0017], [0028], [0122, [0195], [0238]).
Further, Charles discloses cine images of breathing lungs can be generated as a “movie of breathing” that shows lung air spaces as they fill and evacuate during a respiratory cycle (including inhalation to exhalation); A typical respiratory cycle (inhale to exhale) is about 2-5 seconds long; In this context, ‘gating’ is taken to mean any of a variety of strategies to detect and follow the respiratory cycle (para [0233]-[0235]; a single complete cycle).
The MPEP 2111 states that the USPTO must employ the “broadest reasonable interpretation" of the claims. With the broadest reasonable interpretation, Examiner interprets the claimed “the first and second MR measurements correspond to a single complete phase or cycle of motion during the free breathing”, in light of the specification, as a cine (the term “cine” refers to a series of images shown dynamically, e.g., a breathing lung in motion during a respiratory cycle or cycles (both inhale and exhale portions of the breathing cycle) (i.e., a single complete cycle)) of free-breathing images of the lungs of the subject.
Therefore, the claimed “the first and second MR measurements correspond to a single complete phase or cycle of motion during the free breathing” reads on the disclosure of Charles.
In view of the above arguments, the Examiner believes all rejections are proper and should be maintained.
Conclusion
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/VAN D HUYNH/Primary Examiner, Art Unit 2665