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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 11/26/2024 is/are compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Office Action Summary
Claim(s) 1-4, 8-9, 11-14, and 18-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sun et al (Correction for Artifacts Induced by B0 and B1 Field Inhomogeneities in pH-Sensitive Chemical Exchange Saturation Transfer (CEST) Imaging; hereinafter “Sun (2007)”) in view of Jiang et al (A theoretical analysis of chemical exchange saturation transfer echo planar imaging (CEST-EPI) steady state solution and the CEST sensitivity efficiency-based optimization approach), further in view of Sun (Simplified Quantification of Labile Proton Concentration-Weighted Chemical Exchange Rate (kws) with RF Saturation Time Dependent Ratiometric Analysis (QUESTRA): Normalization of Relaxation and RF Irradiation Spillover Effects for Improved Quantitative Chemical Exchange Saturation Transfer (CEST) MRI; hereinafter “Sun (2012)”).
Claim(s) 5-6, 10, 15-16, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sun et al (Correction for Artifacts Induced by B0 and B1 Field Inhomogeneities in pH-Sensitive Chemical Exchange Saturation Transfer (CEST) Imaging; hereinafter “Sun (2007)”) in view of Jiang et al (A theoretical analysis of chemical exchange saturation transfer echo planar imaging (CEST-EPI) steady state solution and the CEST sensitivity efficiency-based optimization approach) and Sun (Simplified Quantification of Labile Proton Concentration-Weighted Chemical Exchange Rate (kws) with RF Saturation Time Dependent Ratiometric Analysis (QUESTRA): Normalization of Relaxation and RF Irradiation Spillover Effects for Improved Quantitative Chemical Exchange Saturation Transfer (CEST) MRI; hereinafter “Sun (2012)”), further in view of Dong et al (US 2010/0085050 A1).
Claim(s) 7and 17 is/are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
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) 1-4, 8-9, 11-14, and 18-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sun et al (Correction for Artifacts Induced by B0 and B1 Field Inhomogeneities in pH-Sensitive Chemical Exchange Saturation Transfer (CEST) Imaging; hereinafter “Sun (2007)”) in view of Jiang et al (A theoretical analysis of chemical exchange saturation transfer echo planar imaging (CEST-EPI) steady state solution and the CEST sensitivity efficiency-based optimization approach), further in view of Sun (Simplified Quantification of Labile Proton Concentration-Weighted Chemical Exchange Rate (kws) with RF Saturation Time Dependent Ratiometric Analysis (QUESTRA): Normalization of Relaxation and RF Irradiation Spillover Effects for Improved Quantitative Chemical Exchange Saturation Transfer (CEST) MRI; hereinafter “Sun (2012)”).
Regarding claim(s) 1 and 11, Sun (2007) teaches a system for standardizing magnetization resonance (MR) data, comprising:
one or more processors (Page 1210, Numerical Simulation, 2nd Paragraph: “The fitting takes about 6s using an office PC with an Athelon Dual-core CPU”); and
one or more hardware storage devices having stored thereon computer-executable instructions which are executable by the one or more processors to cause the computing system (Page 1210, Numerical Simulation, 2nd Paragraph: “The fitting takes about 6s using an office PC with an Athelon Dual-core CPU”) to perform at least the following:
providing MR data of the region of interest (Page 1210, MRI and Data Processing, 1st Paragraph: “All images were acquired on a 9.4 T Bruker Biospec Imager (Bruker Biospin, Billerica, MA, USA) […] T1 images were acquired using an inversion recovery sequence […] The T2 map was derived from five separate spin-echo images […] The B0 map was obtained by acquiring five phase images […] The B1 map was obtained using the double angle method […] The CEST imaging comprised acquisition of three z-spectra from –1500 Hz to 1500 Hz with an offset interval of 50 Hz […]”);
determining (Figure 3B; Page 1207, Right Col., Last Paragraph: “In the presence of B0 field inhomogeneity, the RF irradiation frequency at which the CEST contrast is maximal is shifted according to the local field per voxel”; Page 1212, Right Col., 1st Paragraph: “[…] the proposed algorithm corrected MTRasym toward the fully-compensated PTR, with MTRasym, ΔMTR, PTR’, and PTR scatter-plotted against the B0 inhomogeneity per voxel”; Page 1210, MRI and Data Processing, 1st Paragraph: “The CEST imaging comprised acquisition of three z-spectra from –1500 Hz to 1500 Hz with an offset interval of 50 Hz […]”; Page 1210, MRI and Data Processing, 2nd Paragraph: “z-Spectra were obtained by normalizing RF-irradiated images by the control map, and plotted against the irradiation RF offset […] Absolute T1 and T2 maps were derived by least square fitting of image intensity against the inversion delay and echo time, respectively”; and Page 1210, Right Col., 2nd Paragraph: “The PTR map was corrected using Eq. [7] based on the measured B0 and B1 field map, as well as T1 and T2 values”).
Sun (2007) fails to teach to determining a quasi-steady state signal for each voxel of the MR data for each saturation offset
However, Jiang teaches determining a quasi-steady state signal for (Figure 1; Figure 2B; Equation 2; Page 416, Left Col., 1st Paragraph: “Because the fully relaxed magnetization state under an extremely long repetition time is rarely used, we here derived a steady state analytical solution for the CEST MRI effect […]”; Page 416, 2.1. Quantitative […] CEST MRI effect, 1st Paragraph: “For the irradiated scans, the steady state signal (see Appendix A.1) can be solved as […]”; Page 417, Right Col., 2nd Paragraph: “Figure 2(b) shows the CESTR estimated from the steady state nonequilibrium solution”; Page 422, A.1. Steady state non-thermal equilibrium CEST effect solution; Page 416, Right Col., 1st Paragraph: “[…] where R1,2w are the bulk water longitudinal and transverse relaxation rates, δs is the labile proton offset and α is the saturation coefficient […] where ω1 and Δω are the RF irradiation level and offset […]”; Page 416, Left Col., 1st Paragraph: “the RF irradiation level (B1) and duration […] the CEST effect depends on experimental factors such as repetition time (TR) and flip angle (FA)”; and Page 416, Right Col., 1st Paragraph: “[…] short EPI readout time (i.e., TR = Tr + Ts, where Tr and Ts are the relaxation recovery and saturation times)”), Examiner’s Note: Jiang teaches determining a steady-state, non-thermal-equilibrium CEST signal, which corresponds to the claimed quasi-steady-state signal under the broadest reasonable interpretation).
Sun (2007) teaches acquiring and processing spatially resolved CEST data over a plurality of RF irradiation offsets and further teaches that the RF irradiation frequency corresponding to maximal CEST contrast is shifted according to the local field per voxel. Jiang teaches solving a steady-state, non-thermal equilibrium CEST signal for irradiated scans and further teaches an offset dependent analytical model in which the RF irradiation level and offset affect the calculated signal.
Therefore, it would have been obvious to one of ordinary skill in the art to combine before the effective filing date of the claimed invention to applying Jiang’s offset dependent steady-state signal calculation to Sun’s (2007) voxel resolved CEST data acquired at successive irradiation offsets would have predictably resulted in determining a corresponding steady-state signal for each voxel at each saturation offset. The motivation for this combination of references would have been to improve the accuracy of quantitative CEST analysis by incorporating experimental factors into the steady-state signal solution. This motivation for the combination of Sun (2007) and Jiang is/are supported by KSR exemplary rationale (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention. MPEP 2141 (III).
Sun (2007) and Jiang fails to teach standardizing each voxel using the quasi-steady state signal for each saturation offset. However, Sun (2012) teaches standardizing each voxel using the quasi-steady state signal for each saturation offset (Equation [1] – Equation [3]; Page 937, Left Col., 2nd Paragraph: “the concept of QUEST algorithm with ratiometric analysis (QUESTRA). Specifically, given that label and reference scans are subject to approximately equal relaxation recovery and RF spillover effects, we postulated that such effects could be normalized by analyzing the ratio of magnetization transfer ratio (MTR) at label and reference frequencies”; Page 937, Theory, 1st Paragraph: “We have MTR = 1 - I(Δω, ω1)/I0, where I(Δω, ω1) is the image intensity with RF irradiation, with ω1 (ω1 = ϒB1, where ϒ is the gyromagnetic ratio and B1 is the RF irradiation field strength) and Δω being its amplitude and offset, respectively, and I0 is the control scan without RF irradiation […] the proposed QUESTRA method investigates the relative rate by which MTRlabel and MTRref approach their steady state […] MTRlabel_ss and MTRref_ss are the steady state MTR for the label and reference scans, respectively”, Examiner’s Note: Under the broadest reasonable interpretation, the normalization of measured MR quantities using corresponding steady-state quantities taught by Sun (2012) corresponds to the claimed standardizing using the quasi-steady state signal).
Sun (2007) teaches acquiring and processing voxel resolved CEST MR data over a plurality of RF irradiation offsets using quantitative parameter maps including T1 and B1 information. Jiang teaches determining a steady-state, non-thermal equilibrium CEST signal using experimental parameters including RF irradiation level (B1), saturation time (Ts), repetition time (TR), flip angle (FA), relaxation information, and RF irradiation offset. Sun (2012) further teaches normalizing measured CEST quantities using corresponding steady-state quantities in order to compensate for relaxation recovery and RF spillover effects.
Therefore, it would have been obvious to one of ordinary skill in the art to combine before the effective filing date of the claimed invention to apply Jiang’s steady-state analytical signal determination to the voxel resolved CEST data acquired by Sun (2007) and to utilize the resulting steady-state signal as the normalization reference according to the normalization technique taught by Sun (2012), thereby determining a corresponding steady-state signal for each voxel at each saturation offset and standardizing each voxel using the corresponding steady-state signal. The motivation for this combination of references would have been to improve the accuracy, robustness, and quantitative reliability of voxel resolved CEST imaging by incorporating experimental acquisition parameters into the steady-state signal determination and by normalizing measured CEST signals using corresponding steady-state signals to reduce relaxation recovery and RF spillover effects. This motivation for the combination of Sun (2007), Jiang, and Sun (2007) is/are supported by KSR exemplary rationale (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention. MPEP 2141 (III).
Regarding claim(s) 2 and 12, Sun (2007) as modified by Jiang and Sun (2007) teaches the method according to claim 1, where Jiang teaches wherein the determining the quasi-steady state spectrum for each voxel includes:
determining a steady state spinlock relaxation rate using at least the saturation time (Equation 2; Equation 3; Equation A1.2c; Page 417, Right Col., 1st Paragraph: “The steady state CEST solution was derived following the spin locking theorem (50,54) and relaxation recovery”; Page 416, Right Col., 1st Paragraph: “[…] short EPI readout time (i.e., TR = Tr + Ts, where Tr and Ts are the relaxation recovery and saturation times). We have R1p […] The CEST MRI signal is given as (see Appendix A.1)”; and Page 422, A.1. Steady state non-thermal equilibrium CEST effect solution: “[…] The spin signal evolution following the RF saturation can be described by the spin locking theorem […]”); and
determining the quasi-steady state signal for each voxel for each saturation offset based on the steady state spinlock relaxation rate (Equation 2; Equation 3; Equation A1.2c; Equation A1.3; Page 416, 2.1. Quantitative solution of CEST MRI effect, 1st Paragraph: “For the irradiated scans, the steady state signal (see Appendix A.1) can be solved […]”; Page 416, Right Col., 1st Paragraph: “[…] short EPI readout time (i.e., TR = Tr + Ts, where Tr and Ts are the relaxation recovery and saturation times). We have R1p […] The CEST MRI signal is given as (see Appendix A.1)”; Page 422, A.1. Steady state non-thermal equilibrium CEST effect solution: “[…] The spin signal evolution following the RF saturation can be described by the spin locking theorem […] Hence, the detectable signal is the sine projection of magnetization Isat(TR)”; and Page 416, Right Col., 1st Paragraph: “[…] where R1,2w are the bulk water longitudinal and transverse relaxation rates, δs is the labile proton offset and α is the saturation coefficient […] where ω1 and Δω are the RF irradiation level and offset […]”).
Regarding claim(s) 3 and 13, Sun (2007) as modified by Jiang and Sun (2007) teaches the method according to claim 1, where Sun (2007) teaches further comprising:
determining one or more quantitative measurements using each standardized voxel (Figure 1a; Figure 3b; Equation [7]; Page 1207, Right Col., 2nd Paragraph: “Such an MTR offset, if not properly accounted for, may cause nonnegligible errors in quantitative CEST imaging […] Given that commonly obtainable endogenous CEST imaging contrast is only a few percent, it is crucial to correct for field inhomogeneity-induced measurement errors for quantitative CEST imaging”; Page 1208, Left Col., Last Paragraph: “In the presence of B0 inhomogeneity, MTRasym is equal to the difference of images acquired at the mismatched “label” and “reference” frequencies”; Page 1208, Right Col., Last Paragraph: “the compensated PTR is given as […]”; and Page 1212, Right Col., 1st Paragraph: “Figure 3b shows how the proposed algorithm corrected MTRasym toward the fully-compensated PTR, with MTRasym, ΔMTR, PTR, and PTR scatter-plotted against the B0 inhomogeneity per voxel […] The MTRasym was 12
±
4% […] the fully compensated PTR (blue dots) was obtained to be 15
±
2%, comparable to 17
±
1% measured under the condition of homogeneous B0 field”).
Regarding claim(s) 4 and 14, Sun (2007) as modified by Jiang and Sun (2007) teaches the method according to claim 3, where Sun (2007) teaches further comprising:
correcting each voxel of the MR data (Page 1207, Right Col., Last Paragraph: “In the presence of B0 field inhomogeneity, the RF irradiation frequency at which the CEST contrast is maximal is shifted according to the local field per voxel”; Page 1213, Right Col., 2nd Paragraph: “B0 inhomogeneity-induced measurement errors in CEST imaging can be compensated for by interpolating the z-spectrum using high-order polynomials and adjusting the measurements per voxel”; Page 1210, Right Col., 2nd Paragraph: “The PTR map was corrected using Eq. [7] based on the measured B0 and B1 field map, as well as T1 and T2 values”; and Page 1212, Right Col., 1st Paragraph: “Figure 3b shows how the proposed algorithm corrected MTRasym toward the fully-compensated PTR, with MTRasym, ΔMTR, PTR, and PTR scatter-plotted against the B0 inhomogeneity per voxel […] The MTRasym was 12
±
4% […] the fully compensated PTR (blue dots) was obtained to be 15
±
2%, comparable to 17
±
1% measured under the condition of homogeneous B0 field”);
wherein the quasi-steady state signal is determined for each voxel, and each corrected voxel is standardized and further quantified (Figure 3a: “After compensating for the MTR offset and the modulation factor using the proposed correction algorithm, the obtained PTR map shows reasonably homogeneous CEST contrast across the phantom”; Page 1212, Right Col., 1st Paragraph: “Figure 3b shows how the proposed algorithm corrected MTRasym toward the fully-compensated PTR, with MTRasym, ΔMTR, PTR, and PTR scatter-plotted against the B0 inhomogeneity per voxel […] The MTRasym was 12
±
4% […] the fully compensated PTR (blue dots) was obtained to be 15
±
2%, comparable to 17
±
1% measured under the condition of homogeneous B0 field”; and Page 1213, Left Col., 1st Paragraph: “[…] the PTR of the inner and outer tubes were compensated to be 11.7
±
0.9% and 21.7
±
2.8%, respectively. The corresponding CEST contrast was 10%, significantly higher than that prior to correction (2.7%) and in very good agreement with that derived with homogeneous B0 field (9.5%)”), Examiner’s note: As discussed with respect to claim 1, Sun (2007) teaches voxel resolved CEST MR data, while Jiang teaches determining an offset dependent steady-state CEST signal. Applying Jiang’s analytical steady-state signal determination to Sun’s voxel resolved CEST data would have predictably resulted in determining a corresponding quasi-steady state signal for each voxel.
Regarding claim(s) 8 and 18, Sun (2007) as modified by Jiang and Sun (2007) teaches the method according to claim 4, where Sun (2007) teaches wherein the MR data corresponds to CEST data or MT data (Page 1210, MRI and Data Processing, 1st Paragraph: “The CEST imaging comprised acquisition of three z-spectra from –1500 Hz to 1500 Hz with an offset interval of 50 Hz […] For the dual-pH phantom, B0, B1, T1, and T2 maps and CEST z-spectra were acquired as described previously. In addition, three-point CEST imaging was performed […]“).
Regarding claim(s) 9 and 19, Sun (2007) as modified by Jiang and Sun (2007) teaches the method according to claim 8, where Sun (2007) teaches the CEST data is non Z-spectrum data and the MT data is non Z spectrum data (Figure 3: “The measured MTRasym map shows severe heterogeneity […] After compensating for the MTR offset and the modulation factor using the proposed correction algorithm, the obtained PTR map shows reasonably homogeneous CEST contrast across the phantom”; and Page 1210, Left Col., Last Paragraph: “The MTRasym map was computed by taking the difference between the label and reference images.”).
Claim(s) 5-6, 10, 15-16, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sun et al (Correction for Artifacts Induced by B0 and B1 Field Inhomogeneities in pH-Sensitive Chemical Exchange Saturation Transfer (CEST) Imaging; hereinafter “Sun (2007)”) in view of Jiang et al (A theoretical analysis of chemical exchange saturation transfer echo planar imaging (CEST-EPI) steady state solution and the CEST sensitivity efficiency-based optimization approach) and Sun (Simplified Quantification of Labile Proton Concentration-Weighted Chemical Exchange Rate (kws) with RF Saturation Time Dependent Ratiometric Analysis (QUESTRA): Normalization of Relaxation and RF Irradiation Spillover Effects for Improved Quantitative Chemical Exchange Saturation Transfer (CEST) MRI; hereinafter “Sun (2012)”), further in view of Dong et al (US 2010/0085050 A1).
Regarding claim(s) 5 and 15, Sun (2007) as modified by Jiang and Sun (2007) teaches the method according to claim 4, but do not specifically teach further comprising: providing an inhomogeneity field/response map of a region of interest; wherein each voxel of the MR data corresponds to a plurality of subvoxels of the inhomogeneity field/response map.
Where Dong teaches further comprising: providing an inhomogeneity field/response map of a region of interest (Figure 5; Paragraph [0066]: “[…] high resolution MR images for field mapping were acquired using a commercial 3D MRI pulse sequence called Incoherent RF Spoiled Gradient Echo (SPGR) […]”; Paragraph [0088]: “These unwrapped phase images were converted into field maps as represented by the frequency deviations across the slices”; Paragraph [0090]: “FIG. 5 is a scan 501 that illustrates an example magnetic field map from MRI data and corresponding magnetic resonance spectroscopy (MRS) volumes for MRSI […] the MRI data offers a high spatial resolution of the frequency dispersion Δf within each MRS volume”; and Paragraph [0108]: “Using the MRI field mapping data, lineshapes in the frequency domain were constructed […]”);
wherein each voxel of the MR data corresponds to a plurality of subvoxels of the inhomogeneity field/response map (Paragraph [0065]: “In step 720, MRI complex signal data is collected from multiple high resolution MRI voxels within each MRS volume at two different echo times”; Paragraph [0066]: “each MRSI slice covers 5 MRI slices and each MRS volume overlaps 1280 MRI voxels”; and Paragraph [0090]: “the MRI data offers a high spatial resolution of the frequency dispersion Δf within each MRS volume”), Examiner’s Note: Thus, under the broadest reasonable interpretation, Dong’s lower-resolution MRS volume corresponds to the claimed voxel of the MR data, while the multiple high-resolution MRI voxels located within that MRS volume and having respective field-map values constitute the claimed plurality of subvoxels of the inhomogeneity field map.
Therefore, it would have been obvious to one of ordinary skill in the art to combine Sun (2007), Jiang, Sun (2012), and Dong before the effective filing date of the claimed invention. The motivation for this combination of references would have been to more accurately characterize spatial variations of the inhomogeneous magnetic field within each MR voxel and thereby improve the accuracy of field/inhomogeneity correction. This motivation for the combination of Sun (2007), Jiang, Sun (2012), and Dong is/are supported by KSR exemplary rationale (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention. MPEP 2141 (III).
Regarding claim(s) 6 and 16, Sun (2007) as modified by Jiang and Sun (2007) teaches the method according to claim 5, but do not specifically teach wherein the correcting each voxel of the MR data includes: registering the inhomogeneity field/response map and the MR data; determining an intravoxel inhomogeneity correction coefficient for each voxel of at least one subregion of the region of the interest using the registered field inhomogeneity field/response map and MR data; and correcting each voxel of the MR data of the region of interest using the voxel inhomogeneity correction coefficient.
However, Dong teaches registering the inhomogeneity field/response map and the MR data (Paragraph [0066]: “The slices of the 3D SPGR were parallel to the slices of the MRSI and the imaged volume of the 3D SPGR is slightly larger than that of the MRSI […] each MRSI slice covers 5 MRI slices and each MRS volume overlaps 1280 MRI voxels. To ensure identical field inhomogeneity during both the MRSI scan and MRI scan, only first order shimming was performed for MRSI, and the same shim values were kept for the MRI scans”; and Paragraph [0067]: “Step 720 follows step 710 in a preferred embodiment, because the shimming, PE encoding and other operational settings of the MRS measurement are already in place for the corresponding MRI measurements. In some embodiments, the shimming scan is done first; then the MRI scans are done without further shimming; then the MRSI scan is done without further shimming. In this way, both MRI and MRSI scans have the same shimming, and thus the same magnetic field inhomogeneity.”);
determining an intravoxel inhomogeneity correction coefficient for each voxel of at least one subregion of the region of the interest using the registered field inhomogeneity field/response map and MR data (Equation 8; Equation 16; Paragraph [0088]: “These unwrapped phase images were converted into field maps as represented by the frequency deviations across the slices”; Paragraph [0091]: “the lineshape profile for each voxel in the matrix of a 2D MRSI slice was determined from these field maps as follows to match the processing of each MRS volume […] The resulting lineshape profile is LV(td) given by Equation 16a”; and Paragraph [0092]: “In some embodiments, the lineshape profile can be obtained by directly simulating the phase encoding procedure of the real-world MRSI data acquisition […] The resultant lineshape signal for the voxel V is LV(td, k) given by Equation 16”); and
correcting each voxel of the MR data of the region of interest using the voxel inhomogeneity correction coefficient (Equation 17; Paragraph [0057]: “The ideal signal
s
V
0
(
t
d
)
can be recovered from the measured signal SV(td) by dividing the lineshape profile in a point-by-point manner as given in Equation 9 […] Thus, the ideal signal
s
V
0
(
t
d
)
is retrieved by de-convolving the measured echo from an MRS volume, SV(td), with the lineshape profile”; Paragraph [0093]: “step 750 includes de-convolving the lineshape profile for an MRS voxel from the echo data to produce corrected echo data […] Ideally, this de-convolution eliminates the linebroadening caused by the field inhomogeneity”; Paragraph [0094]: “A 3D lineshape signal […] for each MRSI slice and at the in-plane resolution of the MRSI voxel was constructed from field maps within the MRSI slice”; and Paragraph [0098]: “The spatial time domain MRSI data after water-removal were submitted to the de-convolution procedure represented by Equation 17a. After de-convolution, the time domain data were zero-padded to 2048 points and transformed to frequency domain to obtain the more ideal MR spectrum”).
Regarding claim(s) 10 and 20, Sun (2007) as modified by Jiang and Sun (2007) teaches the method according to claim 4, but do not specifically teach wherein the MR data corresponds to CEST MR spectroscopy (MRS) image(s)/spectrum, MR spectroscopy (MRS) image(s)/spectrum, and/or MR spectroscopic imaging (MRSI) image(s)/spectrum.
However, Dong teaches wherein the MR data corresponds to CEST MR spectroscopy (MRS) image(s)/spectrum, MR spectroscopy (MRS) image(s)/spectrum, and/or MR spectroscopic imaging (MRSI) image(s)/spectrum (Paragraph [0009]: “In order to obtain the frequency-domain NMR spectrum (intensity vs. frequency) for magnetic resonance spectroscopy (MRS) and MRS imaging (MRSI), this time-domain signal is Fourier transformed.”; and Paragraph [0043]: “ for enhancing the spectral resolution of magnetic resonance spectroscopy (MRS) and, consequently magnetic resonance spectroscopic imaging (MRSI)”).
Therefore, it would have been obvious to one of ordinary skill in the art to combine Sun (2007), Jiang, Sun (2012), and Dong before the effective filing date of the claimed invention. The motivation for this combination of references would have been to predictably extended the known correction technique of Sun (2007) to another well-known type of MR data to improve the quality and accuracy of the resulting MR spectroscopy information. This motivation for the combination of Sun (2007), Jiang, Sun (2012), and Dong is/are supported by KSR exemplary rationale (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention. MPEP 2141 (III).
Allowable Subject Matter
Claim(s) 7 and 17 is/are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Relevant Prior Art Directed to State of Art
Keupp (US2021/0063519 A1) is/are relevant prior art not applied in the rejection(s) above. Keupp discloses determine from the MRI data chemical exchange saturation transfer, CEST, voxel values corresponding to a transfer of saturation between a predefined pool of protons and water protons, the pool of protons having a predefined chemical shift; weight the CEST values in order to distinguish CEST values of fluid-rich tissues from CEST values of solid tissues in the target volume, the MRI data being acquired using predefined MRI sequences, wherein the first MRI data comprises non-saturated data at a predefined large saturation frequency offset or without RF saturation and saturation transfer data at N saturation frequency offsets, wherein N>=2, wherein the weighting comprises: performing a quantitative tissue scoring using a subset of the saturation transfer data comprising N2 saturation frequency offsets and the non-saturated data in order to assess fluid content and solid tissue content at each voxel in the MRI data, generating a correction function using results of the scoring, and using the correction function to weight the CEST value of each voxel, wherein using the correction function to weight the CEST values comprises multiplying a correction factor CF=ε × MTR(−Δωc)+MTR(Δωc)) with CEST values, wherein ±Δωc are the saturation frequency offsets and c is a factor that is determined such that the application of the correction factor results in the CEST values within the fluid-rich tissues being rescaled while the CEST values remain unchanged for the solid tissues.
Noterdaeme et al (US 7782056 B2) is/are relevant prior art not applied in the rejection(s) above. Noterdaeme discloses a method for removing intensity inhomogeneities in magnetic resonance (MR) images comprising: acquiring an MR image for a body of tissue using a scanner; acquiring at least two calibration images, varying a flip angle α for the acquisition of the calibration images; determining from the at least two calibration images a calibration factor M0, M0 being a function of the gain setting g associated with the scanner and the proton density ρ; determining an estimated bias field; and removing the estimated bias field from the MR image through use of the calibration factor M0 to derive an MR image in which inhomogeneities have been reduced.
Conclusion
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