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
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, 4-6, 11-12, and 15- 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Albers (PGPUB: 20230062684 A1) in view of Migliavacca (PGPUB: 20250252563 A1).
Regarding claims 1, 19, and 20. Albers teaches a method for guiding removal of a thrombus, the method comprising:
receiving image data indicative of positions of marker elements on a thrombectomy device positioned proximate the thrombus in a patient (see paragraph 151, advancing the thrombectomy device includes inserting the catheter into the venous vessel until a radiopaque distal tip of the catheter is distally past the thrombus. In some embodiments, deploying the thrombectomy device from the constrained configuration to the expanded configuration includes advancing the shaft distally until the thrombectomy device is beyond a distal end of the catheter. Deploying the thrombectomy device further includes determining a position of the thrombectomy device with respect to the catheter via imaging of a first radiopaque marker located on the catheter and a second radiopaque marker located on at least one of the shaft or mesh structure); and
at least one characteristic of the thrombus of the image data (see Fig. 4, paragraph 165, observation of imaging changes 499 can be clinically A computer-based 491 tracking system 400 can be used in patient studies to investigate clot composition with respect to the age 450, composition 460 and size of a thrombus 470. During formation of a thrombus, characteristic alterations in fluorescence contrast imaging 410 and thrombus imaging 430 may be registered useful in evaluating the potential utility of various alternative therapeutic interventions, such as, for example, drug thrombolytic therapy 440 and mechanical thrombectomy 441).
However, Albers does not expressly teach predicting at least one characteristic of the thrombus by applying a trained machine learning algorithm to the image data.
Migliavacca teaches that a thrombus fracture model is also placed into the finite element model of the thrombectomy surgery. By collecting the results of a certain number of simulations of thrombectomy with fracture model it is possible to train a predictive model that, based on indicators such as vascular geometric characteristics, thrombus properties and used thrombectomy technique, provides the likelihood of the thrombus fracture to occur (see Fig. 6 and 9, paragraph 35).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Albers by Migliavacca to obtain
that by collecting the results of a certain number of simulations of thrombectomy with fracture model it is possible to train a predictive model that, based on indicators such as vascular geometric characteristics, thrombus properties and used thrombectomy technique, provides the likelihood of the thrombus fracture to occur, in order to provide predicting at least one characteristic of the thrombus by applying a trained machine learning algorithm to the image data. Therefore, combining the elements from prior arts according to known methods and technique would yield predictable results.
Regarding claim 2. The combination teaches the method of claim 1, wherein the machine learning algorithm analyzes three-dimensional positions of the marker elements (see Albers, Fig. 8, paragraph 191, different structures for these protruding elements are exemplified separately to show how the different shapes and dimensions and configurations can be selected to provide unique and designed functions with respect to different types of clots, thrombus and debris based on size, texture, rheology and dimensions of the unwanted materials to be captured).
Regarding claim 4. The combination teaches the method of claim 1, wherein the machine learning algorithm analyzes a change in position of a marker element across a period of time (see Albers, paragraph 159, fluoroscopically monitoring deployment of the thrombectomy device beyond first radiopaque marker located on the catheter relative to a second radiopaque marker located on the thrombectomy device).
Regarding claim 5. The combination teaches the method of claim 1, wherein the machine learning algorithm analyzes the relative positions of multiple marker elements at a given timepoint (see Albers, paragraph 151, advancing the thrombectomy device includes inserting the catheter into the venous vessel until a radiopaque distal tip of the catheter is distally past the thrombus. In some embodiments, deploying the thrombectomy device from the constrained configuration to the expanded configuration includes advancing the shaft distally until the thrombectomy device is beyond a distal end of the catheter. Deploying the thrombectomy device further includes determining a position of the thrombectomy device with respect to the catheter via imaging of a first radiopaque marker located on the catheter and a second radiopaque marker located on at least one of the shaft or mesh structure).
Regarding claim 6. The combination teaches the method of claim 1, wherein the machine learning algorithm analyzes a change in the relative positions of multiple marker elements across a period of time (see Albers, paragraph 159, fluoroscopically monitoring deployment of the thrombectomy device beyond first radiopaque marker located on the catheter relative to a second radiopaque marker located on the thrombectomy device).
Regarding claim 11. The combination teaches the method of claim 1, wherein predicting at least one characteristic of the thrombus comprises predicting a material characteristic of the thrombus (see Albers, paragraph 3, Blood clots are made up of platelets and a meshwork of protein fibrin strands. Clots in arteries have a different composition than clots in veins. Two main types of blood clots include the thrombus or the embolus. Clots in arteries are mostly made up of platelets. Clots in veins are mostly made up of fibrin. Studies have been made of captured clot materials, and the present technology can advance those studies by retrieving more intact thrombi,).
Regarding claim 12. The combination teaches the method of claim 11, wherein the material characteristic of the thrombus comprises stiffness of the thrombus (see Albers, paragraph 220, depending on timing of patient presentation and imaging, thrombi may have very different composition and imaging characteristics. The lower stiffness and friction and increased permeability of the initial RBC component may facilitate higher penetration of thrombolytic agent and easier extraction).
Regarding claim 15. The combination teaches the method of claim 1, wherein the thrombectomy device comprises a stent retriever (see Albers, paragraph 153, Withdrawing the thrombectomy device from the patient includes: retracting the thrombus extraction device relative to the introducer sheath until an opening is within the self-expanding stent, collapsing the stent portion and mesh structure so as to compress the thrombus, retracting the stent portion and mesh structure into the introducer sheath, and removing the thrombectomy device from the introducer sheath).
Regarding claim 16. The combination teaches the method of claim 1, wherein the marker elements are distributed around a circumference of the thrombectomy device (see Albers, paragraph 159, fluoroscopically monitoring deployment of the thrombectomy device beyond first radiopaque marker located on the catheter relative to a second radiopaque marker located on the thrombectomy device . In some embodiments, the thrombus is located in the peripheral vasculature of the patient and the blood vessel has a diameter of at least 5 millimeters and includes at least one of the following: a femoral vein, an iliac vein, a popliteal vein, a posterior tibial vein, an anterior tibial vein, or a peroneal vein).
Regarding claim 17. The combination teaches the combination teaches the method of claim 1, wherein the marker elements are distributed along an axial length of the thrombectomy device (see Albers, paragraph 204 and 159, an axial view 1500 of a blood vessel 1502 with a clot 1504 attached more against a single wall. There is a general open area 1506 within the blood vessel 1502, and a greatest distance 1508 between the clot 1504 and the wall 1502; fluoroscopically monitoring deployment of the thrombectomy device beyond first radiopaque marker located on the catheter relative to a second radiopaque marker located on the thrombectomy device . In some embodiments, the thrombus is located in the peripheral vasculature of the patient and the blood vessel has a diameter of at least 5 millimeters and includes at least one of the following: a femoral vein, an iliac vein, a popliteal vein, a posterior tibial vein, an anterior tibial vein, or a peroneal vein).
Regarding claim 18. The combination teaches the method of claim 1, wherein the marker elements comprise radiopaque elements (see Albers, paragraph 159, fluoroscopically monitoring deployment of the thrombectomy device beyond first radiopaque marker located on the catheter relative to a second radiopaque marker located on the thrombectomy device).
Claim(s) 3, 7-10, and 13-14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Albers (PGPUB: 20230062684 A1) in view of Migliavacca (PGPUB: 20250252563 A1), and in view of KENICHI (CA 3237390 A1).
Regarding claim 3. The combination does not expressly teach the method of claim 1, wherein the machine learning algorithm analyzes the position of a marker element at a given timepoint.
KENICHI teaches that (Estimation of the catheter tip position using a 2nd marker)
Aneurysm embolization catheters are marked with a tip marker (1st marker) and
a 2nd marker (usually at a position 3 cm from the tip). It is important for the surgeon to know where the tip of the catheter is located within the aneurysm in order to perform the procedure safely (see paragraph 135).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination by KENICHI to obtain Aneurysm embolization catheters are marked with a tip marker (1st marker) and a 2nd marker (usually at a position 3 cm from the tip). It is important for the surgeon to know where the tip of the catheter is located within the aneurysm in order to perform the procedure safely, in order to provide wherein the machine learning algorithm analyzes the position of a marker element at a given timepoint. Therefore, combining the elements from prior arts according to known methods and technique would yield predictable results.
Regarding claim 7. The combination does not expressly teach the method of claim 1, wherein predicting at least one characteristic of the thrombus (see ) comprises predicting a boundary of the thrombus.
KENICHI teaches that an image processing apparatus comprising a storage device and a processor connected to the storage device, wherein the processor acquires an image that includes at least a device for examination or treatment in a blood vessel as a subject, acquires one or more regions that include at least a portion of the device in the image as a region of interest, and tracks each of the regions of interest in the image, and wherein the user is notified on the condition that the region of interest passes, or is predicted to pass, a specific boundary line specified on the image (see paragraph 210).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination by KENICHI to obtain acquires one or more regions that include at least a portion of the device in the image as a region of interest, and tracks each of the regions of interest in the image, and wherein the user is notified on the condition that the region of interest passes, or is predicted to pass, a specific boundary line specified on the image, in order to provide wherein predicting at least one characteristic of the thrombus (see ) comprises predicting a boundary of the thrombus. Therefore, combining the elements from prior arts according to known methods and technique would yield predictable results.
Regarding claim 8. The combination teaches the method of claim 7, wherein predicting at least one characteristic of the thrombus comprises predicting the boundary of the thrombus during expansion of the thrombectomy device in the patient (see KENICHI, paragraph 269, The image processing apparatus according to any one of Supplementary Notes 1 to 37, wherein the notification unit notifies the user when a region including the tip portion of the catheter or the tip portion of the guide wire is set as the region of interest, on the condition that the region of interest has moved, or the region of interest exceeds a specific range specified on the image. (Supplementary Note 39) The image processing apparatus according to Supplementary Note 38, wherein the boundary line of the specific range is represented by a straight line, a curve, a circle, a rectangle, or any other polygon) (see Albers, paragraph 151, advancing the thrombectomy device includes inserting the catheter into the venous vessel until a radiopaque distal tip of the catheter is distally past the thrombus. In some embodiments, deploying the thrombectomy device from the constrained configuration to the expanded configuration includes advancing the shaft distally until the thrombectomy device is beyond a distal end of the catheter).
Regarding claim 9. The combination teaches the method of claim 7, wherein predicting at least one characteristic of the thrombus comprises predicting the boundary of the thrombus after expansion of the thrombectomy device in the patient (see Albers paragraph 177, deploying the thrombectomy device from a constrained configuration to an expanded configuration, wherein the thrombectomy device is in an expanded state between about 20 degrees and about 50 degrees; and, removing the thrombectomy device from the patient) (see KENICHI, paragraph , The image processing apparatus according to Supplementary Note B17 or B18, wherein prediction of passage is performed based on distance between the region of interest and the boundary line, or on the distance/velocity of the region of interest).
Regarding claim 10. The combination teaches the method of claim 7, wherein predicting at least one characteristic of the thrombus comprises predicting the boundary of the thrombus during withdrawal of the thrombectomy device from the patient (see KENICHI, paragraph 277, The image processing apparatus according to Supplementary Note B17 or B18, wherein prediction of passage is performed based on distance between the region of interest and the boundary line, or on the distance/velocity of the region of interest) (see paragraph 213, the forward face of the expanding section 1522 (moving in direction 1526) may have protuberances, edges, thin blades, posts, etc. to penetrate into the thrombus, helping to break it into smaller pieces that may be able to be withdrawn into the lumen/cannula of the delivery catheter. There may even be a second signal causing these forward face additions to vibrate, further enhancing clot breakage).
Regarding claim 13. The combination does not expressly teach the method of claim 1, further comprising providing the predicted characteristic of the thrombus to a user.
KENICHI teaches that the image processing apparatus according to Supplementary Note B52 or B53, wherein candidates for regions that can be specified by a user are automatically displayed in accordance with the situation of a surgery. (Supplementary Note B60) The image processing apparatus according to Supplementary Note B52 or B53, wherein the image temporarily becomes a still image when a user specifies a region. Supplementary Note B61) The image processing apparatus according to Supplementary Note B52 or B53, wherein the image playback is temporarily slowed when a user specifies a region) (see paragraph 278).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination by KENICHI to obtain wherein candidates for regions that can be specified by a user are automatically displayed in accordance with the situation of a surgery. (Supplementary Note B60) The image processing apparatus according to Supplementary Note B52 or B53, wherein the image temporarily becomes a still image when a user specifies a region, in order to provide providing the predicted characteristic of the thrombus to a user. Therefore, combining the elements from prior arts according to known methods and technique would yield predictable results.
Regarding claim 14. The combination teaches the method of claim 13, wherein providing the predicted characteristic of the thrombus comprises displaying the predicted characteristic of the thrombus on a display screen (see KENICHI, paragraph 278, The image processing apparatus according to Supplementary Note B52 or B53, wherein candidates for regions that can be specified by a user are automatically displayed in accordance with the situation of a surgery. (Supplementary Note B60) The image processing apparatus according to Supplementary Note B52 or B53, wherein the image temporarily becomes a still image when a user specifies a region. Supplementary Note B61) The image processing apparatus according to Supplementary Note B52 or B53, wherein the image playback is temporarily slowed when a user specifies a region).
Conclusion
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/XIN JIA/Primary Examiner, Art Unit 2663
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