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 .
Election/Restrictions
Claims 2 and 10-20 remain withdrawn as being directed towards a non-elected invention.
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged. Applicant has not complied with one or more conditions for receiving the benefit of an earlier filing date under 35 U.S.C. 119(e) as follows:
The later-filed application must be an application for a patent for an invention which is also disclosed in the prior application (the parent or original nonprovisional application or provisional application). The disclosure of the invention in the parent application and in the later-filed application must be sufficient to comply with the requirements of 35 U.S.C. 112(a) or the first paragraph of pre-AIA 35 U.S.C. 112, except for the best mode requirement. See Transco Products, Inc. v. Performance Contracting, Inc., 38 F.3d 551, 32 USPQ2d 1077 (Fed. Cir. 1994).
The disclosure of the prior-filed application, Application No. 62072177 and 62112348, fail to provide adequate support or enablement in the manner provided by 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph for one or more claims of this application. Applications 62072177 and 62112348 do not provide any support for details of machine learning model trained to evaluate wound bed tissue, as required by claims 1 and 10. As such, the effective filing date is considered as February 9, 2015, which corresponds to the earliest date of which support for such subject matter is found.
Claim Objections
Claims 1, 3, and 4 are objected to because of the following informalities:
In Claim 1, line 12, “a wound” is inconsistent with earlier defined “the wound tissue”; three lines from end, “the wound” should be “the wound tissue” to maintain antecedent basis.
Regarding Claim 3 line 3-4 “the wound”, and lines 4-5 “the wound” are inconsistent with the antecedent basis from parent claim 1. These should be “the wound tissue” to maintain antecedent basis.
Regarding Claim 4, line 1 “the wound” is inconsistent with the antecedent basis from parent claim 1. This should be “the wound tissue” to maintain antecedent basis.
Appropriate correction is required.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1 and 3 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 5701902 to Vari.
Regarding Claim 1, Vari teaches a multispectral imaging system (Figure 2) comprising:
at least one light emitter configured to emit each of first and second wavelengths of light to illuminate wound tissue (burn injury is being evaluated, as specified in col. 7, line 1 with both fluorescence and reflectance; reflectance is measured as in col. 7, lines 58-col. 8, lines 20 using lasers 36, 38, 40, 42 of different wavelengths);
a light detection element configured to collect light emitted from the at least one light emitter and reflected from the wound tissue at each of the first and second wavelengths of light (light sensor 44, col. 7, lines 58-col. 8, lines 20);
one or more processors (processor 46) in communication with the at least one light emitter and the light detection element and configured to:
control the at least one light emitter to emit each of the first and second wavelengths of light toward a tissue region of a patient, the tissue region including at least a portion of [a] the wound tissue (processor 46 activates the lasers 36, 38, 40, 42, as in col. 7, lines 58-col. 8, lines 20 and Figure 14);
receive multispectral image data from the light detection element, the multispectral image data including at least a first image corresponding to light emitted at the first wavelength of light reflected from the tissue region (col. 7, lines 58-col. 8, lines 20; e.g. Figure 14 “pulse 775nm” and “read & store I775”) and at least a second image corresponding to light emitted at the second wavelength of light reflected from the tissue region (col. 7, lines 58-col. 8, lines 20; e.g. Figure 14 “pulse 810nm” and “read & store I810”), wherein the first image is generated based on reflected light received by the light detection element in the first wavelength of light, and wherein the second image is generated based on reflected light received by the light detection element in the second wavelength of light (col. 7, lines 58-col. 8, lines 20: “monitors the reflected light have the same wavelength as the selected laser”);
input the first and second images into a machine learning model trained to evaluate wound bed tissue (col. 8, lines 35-58; Figure 16-17 show all spectra data are utilized as input to the model);
generate, using the machine learning model, an output representing a characteristic of a wound bed of the wound (condition of a burn injury is output by the model, col. 8, lines 35-58); and
based on the output of the machine learning model, output information identifying viable would bed tissue within the wound bed (the condition of the burn injury is output by the model, col. 8, lines 35-58 which includes structural and metabolic constituents in the burn injury skin, including whether or not the skin is viable or necrotic, Abstract and col. 8, lines 21-34).
Regarding Claim 3, Vari further teaches wherein the machine learning model is trained to classify tissue into one or more tissue classes (e.g. viable tissue, necrotic tissue), wherein the output represents at least one tissue class associated with the at least a portion of the wound, and wherein the information includes an area of the at least a portion of the wound (“area” is considered to mean the location of measured burn tissue; the condition of the burn injury is output by the model, col. 8, lines 35-58 which includes structural and metabolic constituents in the burn injury skin, including whether or not the skin is viable or necrotic, Abstract and col. 8, lines 21-34).
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, 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 4-8 are rejected under 35 U.S.C. 103 as being unpatentable over 5701902 to Vari in view of NPL “BurnCalc assessment study of computer-aided individual three-dimensional burn area calculation” to Sheng (copy submitted with parent application 15972858 on June 24, 2021; published in 2014).
Regarding Claim 4, Vari further teaches wherein the wound [tissue] comprises a burn (burn evaluation, Abstract). Vari does not teach wherein the one or more processors are configured to determine a percentage burned surface area of the patient based on the area of the burn. Instead, Vari teaches local determination of the tissue viability at the burn site where the probe takes a measurement.
Sheng teaches the importance of determination of burned area as a percentage of total body surface area (%TBSA) to make treatment care decisions (Background, first sentence). Sheng utilizes a body scanner to accurately determine body surface area and create a body model (Methodology section, Figure 1). Sheng then maps the locations of measured burn information to the body model (Figure 5). A calculation of %TBSA is then made from the collected data (“BurnCalc” software calculates burn surface area as in Table 2 and body surface area as in Table 3 to calculate %TBSA as in Table 4 “real calculated TBSA*” column).
One of ordinary skill in the art before the effective filing date of the claimed invention would have found it obvious to combine the scanning methods of Vari and Sheng to provide the calculation of %TBSA to inform treatment care decisions, as taught by Sheng to be the standard for guiding burn care. One would be motivated to utilize the spectroscopy measurements of Vari as input to the burn determination software of Sheng in order to link Vari’s scanned locations to the body model, in order to more accurately determine viability of the tissue.
Regarding Claim 5, Vari in view of Sheng further teaches a classified image representing the percentage burned surface area of the patient (Sheng Figure 5 shows the body model with burn areas marked on it; Sheng also suggests highlighting the burn areas with various colors based on the severity of the burn, page 10 last paragraph).
Regarding Claim 6, Vari in view of Sheng further teaches wherein the one or more processors are configured to:
determine an additional percentage burned surface area of an additional patient based on an additional output of the machine learning model when provided with additional images captured at least at the first and second wavelengths of an additional tissue region of the additional patient (the method is repeated for different patients, as in Figure 9 of Sheng); and
output information for performing mass casualty burn care triaging of at least the patient and the additional patient based on the percentage burned surface area of the patient and the additional percentage burned surface area of the additional patient (the BurnCalc software outputs the %TBSA for each measured patient; the measurement of %TSBA is sufficient for a user to perform triage, e.g. by comparing two measurements of %TBSA between patients; Sheng also suggests further display of burns by severity (page 10, last paragraph) which a user is capable of utilizing for triage purposes).
Examiner notes the claim does not specify what the “information” for triage is and the broadest reasonable interpretation of such is utilized. As claimed, the “information” must only be capable of being used for triage purposes. Since %TBSA and burn severity are commonly utilized for assessing patient care and guiding treatment decisions (first sentence of Sheng), they are capable of being utilized for triage purposes.
Regarding Claim 7, Vari in view of Sheng do not teach wherein the one or more processors are configured to determine a treatment for the patient based at least partly on the percentage burned surface area of the patient, wherein the information includes an indication of the treatment. Instead, Sheng teaches a user taking the %TBSA and make a determination of the treatment (first sentence of Sheng). However, courts have held that broadly providing an automatic means to replace a manual activity which accomplished the same result is not sufficient to distinguish over the prior art (In re Venner, 262 F.2d 91, 95, 120 USPQ 193, 194 (CCPA 1958)). In this case, the processor is broadly providing the same function performed by the medical professional to determine subsequent wound care based on %TBSA, e.g. to give fluids, to perform surgery. As such, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to provide an automated software means to suggest the medical treatment based on %TBSA in the same way a medical professional would do so, in order to inform the user and minimize medical errors.
Regarding Claim 8, Vari in view of Sheng further teaches wherein the one or more processors are configured to determine an amount of fluid to administer to the patient based at least partly on the percentage burned surface area of the patient, wherein the treatment includes the amount of fluid (for the same reasons as above for claim 7, examiner finds it obvious to automate the treatment suggestion of fluid amount to deliver in response to %TBSA, as indicated by Sheng as a standard of care).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over 5701902 to Vari in view of US 20090275841 to Melendez.
Regarding Claim 9, while Vari teaches monitoring various constituents over a time period using reflected light, including hemoglobin and oxygenated hemoglobin which relate to blood volume circulation characteristics (Figure 11-13), Vari does not expressly teach these are acquired by using a plethysmographic signal type (a time-variant waveform).
Melendez teaches optical imaging to measure burn tissue (Abstract, par. 0007, 0094). Melendez teaches that combining a body image with perfusion and oxygen saturation is important to identify changes in the burn tissue including frequency variations over time, which also help identify target (i.e. tissue) or non-target (i.e. bedsheet or clothing, par. 0018-0019, e.g. Figure 2A compared to Figure 2B) as compared to static measurements. One of ordinary skill recognizes that the signal utilized for pulse oximetry implicitly relies on changes in blood flow via the plethysmographic signal. As such, one of ordinary skill in the art before the effective filing date of the claimed invention would have found it obvious to provide the PPG (photoplethymographic) data of Melendez as additional input into the machine learning model of Vari to provide both tissue oxygenation for burn tissue assessment over time (as already in Vari) and also for determination of target or non-target as in Melendez. One of ordinary skill would recognize that the combination of data would improve accuracy of the system by reducing false positives (i.e. pixels labeled as tissue when they are not tissue at all).
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 conflicting claims 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); 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 nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined 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 § 2146 et seq. 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 filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual 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 www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1, 3-9 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-19 of U.S. Patent No. 9717417 in view of US 5701902 to Vari. Although the claims at issue are not identical, they are not patentably distinct from each other because the patented claims teach the features of the instant claims and therefore anticipate those features. However, while the patent claims teach tissue classification of burn wound bed (i.e. claim 1 “burn” is necrotic tissues and “region where skin has been excised” is debrided area of a burn to reveal viable wound bed) does not teach the feature of a “machine learning” to perform the classification. However, as explained in the rejection of claim 1 above, Vari teaches machine learning to classify burn wounds as viable or necrotic based on spectral data. One of ordinary skill would find it obvious to combine the teachings of Vari to utilize machine learning as the patent claim 1 classification means to provide a classification that is quick and accurate. Other limitations are taught as follows and are either taught by the patent claims or combined with the references as in the prior art rejection above:
Instant Claim
Patent Claim
1
1+Vari
3, 4, 5, 6, 7, 8
1+Vari+Sheng
9
1+6+7+Vari
Claims 1, 3-9 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-19 of U.S. Patent No. 9962090 in view of US 5701902 to Vari. Although the claims at issue are not identical, they are not patentably distinct from each other because the patented claims teach the features of the instant claims and therefore anticipate those features. However, while the patent claims teach tissue classification of burn wound bed (i.e. claim 1 “wound” is necrotic tissues and “region where skin has been excised” is debrided area of a burn to reveal viable wound bed) does not teach the feature of a “machine learning” to perform the classification or specifically limit to burns. However, as explained in the rejection of claim 1 above, Vari teaches machine learning to classify burn wounds as viable or necrotic based on spectral data. One of ordinary skill would find it obvious to combine the teachings of Vari to utilize machine learning as the patent claim 1 classification means to provide a classification of burns that is quick and accurate. Other limitations are taught as follows and are either taught by the patent claims or combined with the references as in the prior art rejection above:
Instant Claim
Patent Claim
1
1+Vari
3, 4, 5, 6, 7, 8
1+Vari+Sheng
9
1+6+7+Vari
Response to Arguments
Rejections under 35 USC 112(b) are withdrawn. Objections for inconsistent terminology are maintained for “wound tissue” versus “wound”. The data being input into the claimed model is not general data but rather the specific data acquired with the light emitter and light detection element at a specific site (i.e. the wound tissue). It should maintain antecedent basis. Applicant’s arguments, see pages 8-11, filed December 18, 2025, with respect to the rejection(s) of claim(s) 1, 3-9 under USC 102 with Vari have been fully considered and are persuasive. In particular, Applicant argues the cited portions of Vari are teaching fluorescence imaging, i.e. an emitted wavelength is different than the detected wavelength. Examiner agrees. Therefore, in light of the claim amendments, the rejection has been withdrawn. However, upon further consideration, a new ground of rejection is made in view of Vari because Vari teaches both fluorescence imaging and reflectance imaging used in combination. As such, Examiner has made a new ground of rejection with Vari and cited different portions of the same reference to teach the claim limitations. While the claim requires reflectance imaging, it does not preclude additional fluorescence imaging as in Vari. Applicant also argues Vari does not utilize the reflectance data in the machine learning model, but instead only uses it to detect a compound of interest. However, Vari says “each wavelength band discussed above” is utilized in the machine learning model (col. 8, lines 40-41), which includes the “wavelength band centered about the wavelength of the respective light source” performed for the reflectance imaging (col. 7, lines 58-col. 8, line 20, there are several wavelength bands for the reflectance mode). Vari further makes it clear in Figure 17 that all spectra are utilized as inputs. Vari makes it further clear in Figure 14 that both normal skin and burned skin are measured with both fluorescence and reflectance. The combined data is utilized to determine the condition of the wound. As such, Vari still anticipates on claim 1.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. NPL “Multispectral Imaging of Burn Wounds: A New Clinical Instrument for Evaluating Burn Depth” to Afromowitz and NPL “Reflection-optical multispectral imaging method for objective determination of burn depth” to Eisenbeiss teaches hyperspectral reflectance imaging to assess burn wounds. Eisenbeiss additionally utilizes machine learning to classify the burn using the hyperspectral data as input.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANGELA MARIE HOFFA whose telephone number is (571)270-7408. The examiner can normally be reached Monday - Friday 9:30 am - 6:00 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Keith Raymond can be reached at (571)270-1790. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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ANGELA M. HOFFA
Primary Examiner
Art Unit 3799
/Angela M Hoffa/Primary Examiner, Art Unit 3799