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 .
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.
Claim(s) 1-2, 12-19, 37 and 61-64 is/are rejected under 35 U.S.C. 103 as being unpatentable over Simon et al. (US Pub No. 2018/0353145) in view of Mansi et al. (US Pub No. 2018/0366225), Fischer et al. (US Pub No. 2021/0093304) and Warntjes (US Pub No. 2010/0103166).
With regards to claims 1, 19 and 37, Simon et al. disclose a method, a system and a non-transitory computer-accessible medium having stored thereon computer- executable instructions for remotely initiating at least one medical imaging scan of at least one patient, wherein, when a hardware computing arrangement executes the instructions, the hardware computing arrangement is configured to perform procedures(paragraphs [0041], [0070]-[0073]; Figure 1) comprising:
receiving, over a network (i.e. “wide area network (WAN) 22”), first information (i.e. “patient ID”) related to first parameters of the at least one patient (paragraphs [0041]-0042], referring to a hospital or radiology practice may communicate over the WAN (22) and utilize satellite volume imaging stations comprising the imaging apparatus (40) that are remotely installed to provide a needed portable facility for obtaining patient data without requiring the patient to travel to a central hospital or radiology facility; paragraph [0063], referring to automatically communicating the recognized patient ID to the database (26) which uses the ID as an index into the database (26); Figures 1, 8-9);
determining second information (i.e. “prescribed exam type”) related to image acquisition second parameters based on the first information (paragraph [0063], referring to using the communicated patient ID as an index into the database (26) to retrieve and return the prescribed exam type; Figures 1, 8-9);
at a first facility, electronically and automatically generating in real time at least one imaging sequence (i.e. “programmed imaging sequence”) based on the second information (paragraphs [0062], [0066], referring to “If proper positioning is verified…a scan step is then performed according to a programmed imaging sequence associated with the required exam type. For example, the scan step may include moving and activating the (source and detector) imaging components and acquiring 2D projection images for the associated exam type; Figure 9); and
electronically initiating the at least one medical imaging scan based on the at
least one imaging sequence (paragraphs [0062], [0066], referring to “If proper positioning is verified…a scan step is then performed according to a programmed imaging sequence associated with the required exam type. For example, the scan step may include moving and activating the (source and detector) imaging components and acquiring 2D projection images for the associated exam type; Figures 1, 8-9).
However, Simon et al. do not specifically disclose that the first information is “encrypted”.
Further, Simon et al. do not specifically disclose that the electronically initiating of the at least one medical imaging scan is performed “remotely from the at least one patient”, wherein the at least one medical imaging scan is to be performed on the at least one patient at a medical second facility which is remote from the first facility, wherein the initiation is performed by the first facility in a direct communication with the second medical facility.
Additionally, Simon et al. do not specifically disclose that the hardware computing arrangement is further configured to, during the at least one medical imaging scan, causing a modification of at least one parameter that affects at least one of contrast, signal-to-noise ratio (SNR) or acquisition time.
Mansi et al. disclose transmitting data through a secure channel, wherein any number of suitable sub-steps can be performed prior to or during the transmitting of data to the remote computing system (Abstract; paragraphs 0069], [0073]-[0074]). These sub-steps can include encrypting any or all of the dataset (e.g., patient information) prior to transmitting to the remote computing system, etc. (paragraphs [0055], [0074]).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have the first information of Simon et al. be “encrypted”, as taught by Mansi et al., in order to provide secure transmission of the information (paragraphs [0073]-[0074]).
However, the above combined references do not specifically disclose that the electronically initiating of the at least one medical imaging scan is performed “remotely from the at least one patient”, wherein the at least one medical imaging scan is to be performed on the at least one patient at a medical second facility which is remote from the first facility, wherein the initiation is performed by the first facility in a direct communication with the second medical facility.
Further, the above combined references do not specifically disclose that the hardware computing arrangement is further configured to, during the at least one medical imaging scan, causing a modification of at least one parameter that affects at least one of contrast, signal-to-noise ratio (SNR) or acquisition time.
Fischer et al. disclose a system for MRI-guided interventional procedures, wherein navigation software (204), which may reside on a robot controller (222) or on another computer, both retrieves MR images from MRI scanner interface (206) and also controls the MRI scanner (Abstract; paragraph [0043]; Figure 2). Scanner control can include scan parameters, slice locations and slice orientation (paragraph [0044], note that the navigation software therefore initiates/controls the MRI scanner (206) based on an imaging sequence (i.e. defined by the scan parameters, slice locations, etc.; Figure 2). The navigation software interface, which initiates/controls an MR scan, is in a remote location, wherein “remote” may refer to an off-site location, a doctor’s office, etc. (paragraphs [0043], [0047], note that the initiating/controlling of the MR scan is performed remotely from the patient being scanned, the MR imaging scan being performed on the patient at a medical second facility (i.e. facility that is not the Doctor’s office or not at the off-site location) which is remote from the facility (i.e. Doctor’s office or off-site location) where an imaging sequence (i.e. decision of scan parameters, slice location/orientation performed by the Navigation Software) is generated; Figure 2). The robot controller (222), in which the navigation software (204) resides within, communicates with an MRI scanner interface (206) via fiber optic interface (220) using fiber optic cables, thus providing direct communication between the MRI scanner room and the MRI Scanner interface room (paragraph [0044], Figure 2, which depicts that the initiation/control of the MR scan is performed by the first facility (i.e. MRI room which includes the Navigation software (204)/room above the MRI Patch panel (212)) in a direct communication (via the fiberoptic interface cables) with the second medical facility (MRI scanner interface room which includes the MRI scanner interface (206)/room below the MRI Patch Panel (212)).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have the electronic initiating of the at least one medical imaging scan be performed “remotely from the at least one patient”, wherein the at least one medical imaging scan is to be performed on the at least one patient at a medical second facility which is remote from the first facility, wherein the initiation is performed by the first facility in a direct communication with the second medical facility, as taught by Fischer et al., in order to provide a teleoperated MRI system, which avoids the disadvantage of having to perform procedures in the limited space in closed-bored high-field MRI scanners and allows surgeons/doctors to make decisions outside the facility in which the scanning is being performed (paragraphs [0006], [0010]).
However, the above combined references do not specifically disclose that the hardware computing arrangement is further configured to, during the at least one medical imaging scan, causing a modification of at least one parameter that affects at least one of contrast, signal-to-noise ratio (SNR) or acquisition time.
Warntjes discloses an arbitrary initial MR contrast image is synthesized using some default scanner parameter settings as a starting point for generating such an initial contrast image (Abstract; paragraph [0025]; Figure 2). A computer interprets a movement of an indication of a ROI in the displayed synthesized MR image as a request for an automatic change of scanner settings for the displayed synthesized MR image, depending on the T1, T2 and PD inside the ROI (paragraph [0027]; Figure 2). In response to such a request the computer determines the requirement for the updated scanner settings satisfy some pre-determined condition (paragraph [0027]; Figure 2). For example, the condition may advantageously be the optimal setting for TR and flip angle for the highest signal-to-noise ration (SNR) (paragraph [0027]; Figure 2). Scanner settings are thus changed and the updated MR image is displayed (see Figure 2, step 213). The most optimal contrast images are thus automatically synthesized based on only limited input of the user, which will save time and resources (Abstract; paragraph [0013]).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have the hardware computing arrangement of the above combined references be further configured to, during the at least one medical imaging scan, cause a modification of at least one parameter that affects at least one of contrast, signal-to-noise ratio (SNR) or acquisition time, as taught by Warntjes, in order to obtain the most optimal contrast images in a manner which saves time and resources (Abstract; paragraph [0013]).
With regards to claim 2, Simon et al. disclose that the at least one medical imaging scan is at least one magnetic resonance imaging (MRI) sequence (paragraph [0035], referring to the modality being magnetic resonance imaging (MRI), which would inherently include a MRI “sequence” for the scan).
With regards to claim 12, as discussed above, the above combined references meet the limitations of claim 12. However, they do not specifically disclose that the hardware computing arrangement is configured to determine the first parameters using at least one lookup table.
Mansi et al. disclose using a lookup table to correlate a point-of-care (e.g, healthcare facility, hub, physician, etc.) or contact, with a patient condition or correlate any treatment option with the patient condition (paragraphs [0034], [0118], [0120]-[0122]).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have the hardware computing arrangement of the above combined references be configured to determine the first parameters [of the at least one patient] using at least one lookup table, as taught by Mansi et al., in order to provide a desired output as lookup tables are known to provide an effective correlation of parameters associated with a patient and the desired output (paragraphs [0034], [0120]-[0122]).
With regards to claim 13, Simon et al. disclose that the at least one medical imaging scan includes (i) a positron emission tomography scan, (ii) a computed tomography scan, or (iii) an x-ray scan (paragraph [0035], referring to the modality being conventional x-ray radiography, fluoroscopy or tomography; paragraphs [0040]-[0041], referring to the tomographic imaging apparatus including computed tomography (CT) systems).
With regards to claim 14, as discussed above, the above combined references meet the limitations of claim 1. However, the above combined references do not specifically disclose that the first parameters include health information for the at least one patient, geographical information of the at least one patient, a height of the at least one patient and a weight of the at least one patient.
Mansi et al. disclose that data which can be received at a remote computing system can include blood data, clinical notes, or any other suitable data related to a patient’s medical state, condition or medical history, wherein one or more instances (e.g., images) can be tagged with one or more patient identifiers, patient demographic information, patient history, medical record, etc. (paragraphs 0058]-[0065], note that patient information therefore includes health information of the patient). Providing such information enable a quick location of the patient (paragraph [0065]).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have the first parameters include health information for the at least one patient, geographical information of the at least one patient, a height of the at least one patient and a weight of the at least one patient, as taught by Mansi et al., in order to provide further identifying information of the patient which enables a quick location/identification of the patient (paragraph [0065]).
With regards to claim 15, Simon et al. disclose that the hardware computing arrangement is further configured to assign a unique key to the at least one patient (paragraphs [0056]-[0057], [0062]-[0063], referring to providing the patient with an encoded ID card or ID token from a doctor or medical facility).
With regards to claim 16, as discussed above, the above combined references meet the limitations of claim 1. However, they do not specifically disclose that the hardware computing arrangement is further configured to generate at least one image based on the at least one medical imaging scan using cloud computing.
Mansi et al. disclose a remote computing system, wherein a method performed at a remote computing system can be cloud based, the method including transmitting image data to the remote computing system which functions to enable remote processing of the image data (Abstract; paragraphs [0034], [0069]-[0074], [0076]).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have the hardware computing arrangement of the above combined references be further configured to generate at least one image based on the at least one medical imaging scan using cloud computing, as taught by Mansi et al., in order to enable effective remote processing of data (paragraphs [0069]-[0074], [0076]).
With regards to claim 17, Simon et al. disclose that the hardware computing arrangement is further configured to generate at least one report (i.e. reconstructed volume image serves as a report/output of the at least one medical imaging scan), and to provide the report (paragraph [0066], referring to reconstructing the volume image and transmitting the reconstructed image to a local or network connected facility for viewing by medical personnel; Figures 1, 9). With regards to the limitation of the report being specifically provided “to the at least one patient”, the limitation is considered to be directed to an intended use and/or manner of operating the apparatus. A recitation of the intended use of the claimed invention must result in a structural difference between the claimed invention and the prior art in order to patentably distinguish the claimed invention from the prior art. If the prior art structure is capable of performing the intended use, then it meets the claim. Since the report of Simon et al. is capable of being provided to any user, including to the at least one patient, Simon et al. meet the above limitation.
With regards to claim 18, Simon et al. disclose that the hardware computing arrangement is further configured to receive an initiation request from the at least one patient (paragraphs [0062]-[0063], referring to the patient opening the door (48) and entering the imaging apparatus (40) alone after a proper access ID procedure is followed which can be accomplished by providing the patient with an encoded ID card or ID token, wherein such steps serve as an initiation request from the patient as the patient is performing the actions of opening the door and providing an ID card/token; Figure 9), and initiate the at least one medical imaging scan only after the initiation request is received (paragraphs [0062]-[0066], Figure 9, note that the step of executing the scan sequence (S960) can occur only after the patient entry (S900) is performed).
With regards to claim 61, Warntjes discloses that the MRI acquisiton parameters are jointly optimized for multiple pulse sequences give a scanning protocol (see Figure 2, wherein steps 207, 211, and 215 correspond to multiple pulse sequences given a scanning protocol and wherein MRI acquisition parameters (i.e. scanner settings) are jointly optimized for the multiple pulse sequences).
With regards to claims 62, 63 and 64, Warntjes discloses that the at least one parameter comprises one of a repetition time (TR), an echo time (TE), a flip angle (FA), and a number of signal averages (NSA) (paragraph [0027], referring to determining the optimal settings for TR and flip angle; Figure 2).
Claim(s) 3-4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Simon et al. in view of Mansi et al., Fischer et al. and Warntjes as applied to claim 2 above, and further in view of Wiggins (US Pub No. 2008/0265883).
With regards to claim 3, as discussed above, the above combined references meet the limitations of claim 2. However, though Simon et al. do disclose that the at least one medical imaging scan is at least one MRI sequence, and therefore it would follow that the image acquisition second parameters are “MRI” acquisition parameters (paragraph [0035], referring to the modality being magnetic resonance imaging (MRI), which would thus inherently require the acquisition parameters to be “MRI” acquisition parameters), Simon et al. do not specifically disclose that the at least one imaging sequence is at least one gradient recalled echo (GRE) pulse sequence.
Wiggins discloses a method for magnetic resonance imaging, wherein a gradient recalled echo (GRE) pulse sequence is used to acquire NMR imaging data in a short time period and provides separately phase encoded NMR signals so that a set of views sufficient to reconstruct an image in a single pulse sequence of 20-100 milliseconds in duration can be acquired (paragraphs [0009], [0040]-[0044]; Figure 3).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have the at least one imaging sequence be at least one GRE pulse sequence, as taught by Wiggins, in order to acquire NMR imaging data in a short time period and provide separately phase encoded NMR signals so that a set of views sufficient to reconstruct an image in a single pulse sequence of 20-100 milliseconds in duration can be acquired (paragraph [0009]).
With regards to claim 4, Wiggins discloses that the hardware computing arrangement is further configured to generate the at least one GRE pulse sequence based on at least one radiofrequency (RF) offset (222) (paragraphs [0042], [0046], [0049]; Figure 3).
Claim(s) 5-6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Simon et al. in view of Mansi et al., Fischer et al. and Warntjes and Wiggins as applied to claim 4 above, and further in view of Kustner et al. (“Automated reference-free detection of motion artifacts in magnetic resonance images”, September 2017), as cited by Applicant, and Huang et al. (“Extreme learning machine: Theory and applications”, 2006), as cited by Applicant in the 9/14/22 IDS.
With regards to claim 5, as discussed above, the above combined references meet the limitations of claim 4. However, they do not specifically disclose that the hardware computing arrangement is further configured to generate the at least one RF offset using at least one convolutional neural network (CNN) performed in real time using at least one slice position generated by an extreme learning machine.
Kustner et al. disclose an automated method for spatially resolved detection and quantification of motion artifacts in MR images as well as a quality control of the trained architecture, wherein CNN is used for the quantification and localization of motion artifacts which is trained to detect rigid head motion and non-rigid respiratory motion (Abstract, last paragraph in left column on pg. 244; also pg. 244, right column, first full paragraph). A feedback to the scanner during acquisition can trigger a partial re-scan of the artifact-corrupted region, e.g., re-acquisition of an affected 2D slice, instead of re-running the whole sequence (pg. 244, left column, last paragraph; note that the RF offset of the above combined references is used for slice selection, and therefore, since the CNN is used to identify artifacts which is then provided as feedback to reacquire a particular affected 2D slice [which is associated with at least one slice position], the at least one RF offset (associated with the particular affected 2D slice) would be generated using the CNN in the above combined references). By providing quantification and localization of motion artifacts, data validity and quality control in a clinical setting with increased processing of high quality data is provided (pg. 244, right column, 2nd-3rd full paragraphs)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have the hardware computing arrangement of the above combined references be further configured to acquire a particular slice using at least one CNN [and thus generate the at least one RF offset associated with the particular slice] performed in real time using at least one slice position, as taught by Kustner et al., in order to provide data validity and quality control in a clinical setting with increased processing of high quality data (pg. 244, right column, 2nd-3rd full paragraphs).
However, though Kustner et al. do disclose that a machine learning algorithm is used to generate the at least one slice position (pg. 244), the above combined references do not specifically disclose that the machine learning algorithm comprises an extreme learning machine.
Huang et al. disclose a new learning algorithm called extreme learning machine (ELM) which can produce good generalization performance and can learn thousands of times faster than conventional popular learning algorithms (Abstract).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have the CNN/machine learning algorithm of the above combined references be performed using an extreme learning machine, as taught by Huang et al., in order to produce good generalization performance and learn thousands of times faster than conventional popular learning algorithms (Abstract), thus providing a more efficient computation.
With regards to claim 6, Kustner et al. disclose that the hardware computing arrangement is further configured to train the at least one CNN based on a single axial slice of an image of a brain of at least one further patient (pg. 245, right column, 1st-2nd full paragraphs, referring to training being performed on all be one volunteer data set, and the resulting classifier was then applied to the left-out volunteer data set; Figure 1, wherein single slices of a brain of at least one further patient/volunteer data set are ued for training).
Claim(s) 8-11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Simon et al. in view of Mansi et al., Fischer et al. and Warntjes as applied to claim 2 above, and further in view of Wang et al. (US Pub No. 2018/0045799).
With regards to claim 8, as discussed above, the above combined references meet the limitations of claim 2. However, they do not specifically disclose that the hardware computing arrangement is further configured to perform a Bloch equation simulation to generate simulated results of a magnetic resonance (MR) scan of the at least one patient based on the first parameters and the image acquisition second parameters.
Wang et al. disclose techniques for optimizing MRI protocols, wherein the optimization of imaging parameters is achieve by simulating the relationship between the imaging parameters and objective functions for a given MRI scanner setting and k-space strategy using an analytical and/or empirical and/or approximated solution of Bloch equations, simulating the relationship for regions of interests with tissue MRI parameters [i.e. image acquisition second parameters] and determining the optimal imaging parameters using the optimal objective function based on potential applications of the acquired images, wherein optionally, MR parameters can be changed by various factors, such as the subject’s age, a change or disease in tissue [i.e. first parameters of the patient] (Abstract, paragraph [0004], paragraphs [0085]-[0087], [0074]).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have the hardware computing arrangement of the above combined references be further configured to perform a Bloch equation simulation to generate simulated results of a magnetic resonance (MR) scan of the at least one patient based on the first parameters and the image acquisition second parameters, as taught by Wang et al., in order to provide an optimized MRI protocol (Abstract; paragraph [0004]).
With regards to claim 9, Wang et al. disclose that the hardware computing arrangement is configured to generate the at least one imaging sequence based on the simulated results (paragraphs [0085]-[0087], [0094], [0097]-[0100], [0110], [0120], [0138]; Figure 16).
With regards to claim 10, Wang et al. disclose that the hardware computing arrangement is further configured to modify at least one MR value based on the simulated results, and wherein the initiation of the at least one medical imaging scan is performed based on the at least one modified imaging sequence (i.e. images are acquired using the optimal (i.e. modified from less than optimal state) imaging parameters) (paragraphs [0110]-[0112], paragraphs [0131]-[0132], [0085]-[0087], [0094], [0097]-[0100], [0110], [0120], note that the optimal imaging parameters are a result of modifying previous MR parameters/values).
With regards to claim 11, Simon et al. disclose that the hardware computing arrangement is configured to initiate the at least one medical imaging scan only if the at least one MR value is above a predetermined value (paragraph [0064], referring to the image verification step which checks that the required imaging conditions are met, and thus would require that at least one MR value, such as an MR equipment setting and/or power level must inherently be above a minimum imaging condition requirement). Wang et al. further teaches this limitation (paragraphs [0110]-[0112], [0131]-[0132]).
Claim(s) 56, 58 and 60 is/are rejected under 35 U.S.C. 103 as being unpatentable over Simon et al. in view of Mansi et al., Fischer et al. and Warntjes as applied to claims 1, 11 and 37 above, and further in view of Kearby et al. (US Pub No. 2007/0050212).
With regards to claims 56, 58 and 60, as discussed above, the above combined references meet the limitations of claims 1, 11 and 37. Further, though it would be inherent that the hardware computing arrangement is further configured to decrypt the encrypted first information since the received encrypted first information would not be able to be used to determine the second information unless decryption occurs (i.e. decryption is necessarily required), the above combined references do not specifically disclose that the decryption of the encrypted first information is performed with a unique patient encryption key.
Kearby et al. disclose a system and method for secure telerehabilitation, wherein a server (6) can generate a patient data key value which is unique for each patient (Abstract; paragraph [0049]). The server (6) can use the decrypted physician data private key to decrypt the unique patient key to decrypt patient data records (paragraph [0049], [0054]-[0055]). Security and privacy of patient information is therefore provided, limiting access to patients and doctors (paragraph [0004]).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have the decryption of the encrypted first information of the above combined references be performed with a unique patient encryption key, as taught by Kearby et al., in order to provide security and privacy of patient information by limiting access to patients and doctors (paragraph [0004]).
Allowable Subject Matter
Claim 7 is 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.
Claims 65-66 are allowed.
The following is a statement of reasons for the indication of allowable subject matter: The prior art does not teach or suggest that the hardware computing arrangement is further configured to optimize the MRI acquisition parameters for an MR value which is a ratio of contrast to acquisition time [claims 7 and 65], and wherein the MRI acquisition parameters are jointly optimized for multiple pulse sequences given a scanning protocol [claim 7, wherein the MRI acquisition parameters includes the ratio of contrast to acquisition time], in combination with the other claimed elements.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-6, 8-19, 37, 56, 58, 60-64 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Warntjes has been introduced to teach that, during the at least one medical imaging scan, causing a modification of at least one parameter that affects at least one of contrast, SNR or acquisition time.
Conclusion
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.
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/KATHERINE L FERNANDEZ/Primary Examiner, Art Unit 3798
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