Coronary artery bypass graft optimization

Abstract

Example systems and techniques are disclosed that may generate a surgical regimen for a CABG surgery. An example system may include a memory configured to store a surgical regime of a coronary artery bypass graft (CABG) surgery and processing circuitry communicatively coupled to the memory. The processing circuitry is configured to obtain input data including imaging data of a vasculature of a patient. The processing circuitry is configured to determine a surgical regime based on the input data, the surgical regime including at least one recommended graft location, the recommended graft location including a recommended graft start point, a recommended graft path, and a recommended graft end point. The processing circuitry is configured to output the surgical protocol for display.

Description

[0001] This application claims the benefit of U.S. Provisional Application No. 63 / 486,803, filed February 24, 2023, entitled “CORONARY ARTERY BYPASS GRAFT TECHNICAL FIELD

[0002] The present disclosure relates to coronary artery bypass graft (CABG) surgery planning. BACKGROUND

[0003] A CABG surgery is a medical procedure that can harvest one or more blood vessels or one or more portions of blood vessels from a patient and graft them to the patient’s anatomy to bypass the patient’s occluded arteries and improve blood flow to the anatomy. The need for a CABG surgery can be determined by a clinician based on imaging data of a patient from an imaging system, such as a coronary computed tomography angiography (CCTA) imaging system or other imaging system, and / or other testing that can be performed by the clinician after the patient presents with coronary artery symptoms. CABG surgeries are typically performed based on general rules for a general patient population. SUMMARY

[0004] Generally, the present disclosure relates to various techniques and medical systems for generating a surgical plan for a CABG procedure based on patient-specific data. For example, a medical system can use image data of a particular patient’s vasculature (e.g., CCTA image data and / or other image data, such as angiography data or fractional flow reserve (FFR) angiography data) and / or other patient-specific information to determine a recommendation(s) for graft location, graft vessel routing determination, harvest location, harvest vessel length(s), etc. The medical system can present such recommendation(s) to a clinician in a surgical plan. The clinician can use such recommendations to provide assistance to the clinician during a CABG procedure. The surgical plan can include recommended graft location(s), recommended graft length(s) and diameter(s), graft (e.g., harvest) vessel edge conditions (such as cut angle, taper, etc.), recommended harvest vessel segment, recommended surgical approach options for accessing the patient’s anatomy, etc. Because each patient’s anatomy can be different, a patient-specific surgical plan can enable a better match of donor vessel diameter to the original obstructed anatomy, a better match of harvested vessel segment length to the length needed for the CABG procedure, etc. compared to by using general population-based general rules. The techniques of the present disclosure can improve patient outcomes by improving graft patency, reducing or minimizing harvest waste, reducing blood supply loss at the harvest site(s), shortening or minimizing procedure time, and shortening or otherwise improving patient recovery time.

[0005] In some examples, the medical system can provide the clinician with an opportunity to edit the recommendations according to the clinician’s preferences. For example, if the clinician wants to determine the graft vessel routing in a different manner than what is recommended by the medical system, the clinician can use a user interface to edit the recommendation.

[0006] Compared to conventional general population-based approaches, the techniques of the present disclosure can provide a more precise way of determining graft location for a CABG procedure for a given patient, which vessels segments to harvest, how many vessels to harvest, etc. via generating a patient-specific surgical plan. In view of the above, the present disclosure describes a technical improvement or technical solution that is incorporated into practical applications.

[0007] Unlike conventional medical systems, the techniques and systems of the present disclosure can obtain input data (including imaging data of a patient's vasculature), determine a surgical plan (including a recommended graft location), and output the surgical plan to a display. By basing recommendations for graft location on imaging data associated with an individual patient, the techniques and systems of the present disclosure can facilitate improved CABG surgery, improved identification of harvested vessel segments of appropriate length, diameter, and / or other characteristics for use as grafts, and thus improve patient outcomes.

[0008] In one example, a medical system includes a memory configured to store a surgical plan for a coronary artery bypass graft (CABG) procedure; and processing circuitry communicatively coupled to the memory, the processing circuitry configured to: obtain input data comprising imaging data of a patient's vasculature; determine the surgical plan based on the input data, the surgical plan comprising at least one recommended graft location including a recommended graft origin, a recommended graft path, and a recommended graft endpoint; and output the surgical plan for display.

[0009] In another example, a method includes obtaining, by processing circuitry, input data comprising imaging data of a patient's vasculature; determining, by the processing circuitry, a surgical plan based on the input data, the surgical plan comprising at least one recommended graft position, the recommended graft position comprising a recommended graft origin, a recommended graft path, and a recommended graft endpoint; and outputting, by the processing circuitry, the surgical plan for display.

[0010] In another example, a non-transitory computer-readable medium stores instructions that, when executed, cause a processing circuit system to: obtain input data, the input data comprising imaging data of a patient's vasculature; determine a surgical plan based on the input data, the surgical plan comprising at least one recommended graft position, the recommended graft position comprising a recommended graft origin, a recommended graft path, and a recommended graft endpoint; and output the surgical plan for display.

[0011] These and other aspects of the present disclosure will become apparent from the following detailed description.The above summary, however, should in no way be construed as limiting the claimed subject matter, which is defined solely by the appended claims.

[0012] This summary is intended to provide an overview of the subject matter described in this disclosure. This summary is not intended to provide an exclusive or exhaustive explanation of the devices and methods described in detail in the following figures and the specification. Further details of one or more examples are set forth in the following figures and the specification. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 is a schematic perspective view of an example medical system according to one or more aspects of the present disclosure.

[0014] Figure 2 is a block diagram of an example of a computing device according to one or more aspects of the present disclosure.

[0015] Figure 3 is a block diagram illustrating the contents of an example surgical plan according to one or more aspects of the present disclosure.

[0016] Figure 4 is a flow chart illustrating an example CABG surgical planning technique according to one or more aspects of the present disclosure.

[0017] Figure 5 is a conceptual diagram illustrating example potential harvesting vessels according to one or more aspects of the present disclosure.

[0018] Figures 6A to 6D is a conceptual diagram showing different example surgical approach techniques.

[0019] Figure 7 is a conceptual diagram of an example three-dimensional (3D) model of a heart according to one or more aspects of the present disclosure.

[0020] Figure 8 is a conceptual diagram illustrating example recommended graft positions according to one or more aspects of the present disclosure.

[0021] Figure 9 is a conceptual diagram showing an example acquisition of the radial artery.

[0022] Figure 10 is a conceptual diagram illustrating an example use of a 3D model generated based on imaging data other than CCTA imaging data, according to one or more aspects of the present disclosure.

[0023] Figure 11 is a conceptual diagram illustrating the contents of another example surgical plan according to one or more aspects of the present disclosure. DETAILED DESCRIPTION

[0024] CABG surgery is performed in relatively large numbers globally, with approximately 340,000 performed in the United States of America each year alone. However, such CABG surgery does not appear to include much patient-specific planning prior to the CABG surgery itself. CABG surgery is often performed within a short window after acute symptoms are detected (e.g., within 48 hours), and clinicians (such as surgeons) tend to follow general guidelines for CABG surgery that apply to the general population. In some cases, following guidelines that apply to the general population can be reasonable, as patient-specific analysis can take time to perform, and performing CABG surgery earlier rather than later can be more beneficial to the patient.

[0025] However, as patient scans (such as coronary computed tomography angiography (CCTA)) become more refined, processor technology shortens computation times, and software becomes more available within hospitals themselves, it can be desirable for patient-specific CABG planning, as patient-specific CABG planning can yield better patient outcomes.

[0026] For example, patient-specific CABG planning solutions will match harvestable vessels to autologous anatomy, which can facilitate graft patency, reduce or minimize harvest waste, and shorten or minimize planning and surgery times. Such improvements can improve the quality of patient outcomes.

[0027] For example, the techniques of the present disclosure can include processing circuitry and / or software that interacts with patient scans (e.g., imaging data) and / or clinician input to generate a surgical plan for a CABG surgery. The surgical plan can include recommended graft location(s), recommended length(s) and diameter(s) of graft(s), recommended harvest vessel segments, recommended entry options for accessing patient anatomy, etc. For example, the surgical plan can include a harvest site plan that includes lengths of segment(s) of vessel(s) needed for the CABG surgery, a suggested (e.g., optimal) vessel segment for each bypass, a corresponding bypass pathway, and / or an indication of a need for saphenous vein graft (SVG) support, if applicable. The surgical plan can include estimate(s) of blood flow restoration (e.g., a comparison of restored distal segments and / or bypasses to obstructed vessels). The surgical plan can include robotic positioning and entry location(s), if applicable. Target outputs for robotic anastomosis can also be generated and included.

[0028] In some examples, such a surgical plan can provide the clinician with insight into potential case difficulties (e.g., required graft length, robotic joint activity limitations, vessel conditions, etc.) that can not be available if the clinician were to use a population-based, general approach for a CABG surgery. The clinician’s use of such a surgical plan can result in improved blood flow for the patient due to minimizing graft length and improving diameter matching between the occluded vessel and the grafted (e.g., harvested) vessel, and / or can result in reduced blood supply loss at the harvest site.

[0029] As case data is collected over time, the software can be updated to improve the efficacy of the surgical plans that the software can generate. Use of such a surgical plan can save time in the operating room by reducing the time that a clinician can spend selecting, cutting, and / or positioning vessels for grafting. For example, the software can include computer vision algorithms that can be trained to identify vessels and their characteristics, such as diameter (e.g., internal diameter), length, identity of the vessel, whether the vessel is occluded, whether the vessel is branched or unbranched, etc. The computer vision algorithms can also be trained to identify contours of anatomical structures (such as the heart), structure of the heart, potential obstacles to avoid when determining a recommended graft path, etc.

[0030] Length, diameter, and location of vessels have a significant impact on resulting blood flow. Currently, due to the urgency and criticality of CABG surgeries, many clinicians prefer a “one-size-fits-all” approach (e.g., a population-based approach), but such an approach can not truly be the best fit for all patients. Currently, a clinician can consider a variety of factors when planning a CABG surgery. The clinician can consider which sites are available for harvesting vessels. Typically, graft vessels are harvested from any one or any combination of the following three locations: radial artery, internal mammary artery (IMA), or saphenous vein (SVG). Some of these potential harvest sites can be affected due to prior surgeries, patient conditions, or natural differences in patient anatomy. Branching and / or branching at certain intervals of potential harvested vessels can make some vessel segments or vessel sections difficult to use for grafting. With conventional CABG techniques, the clinician can not be aware of such branching and / or branching before starting a CABG surgery (e.g., before harvesting).

[0031] A clinician can consider the size of the occluded artery. It can be important to know the length and diameter of the replaced artery when performing a CABG procedure to ensure that sufficient blood flow is restored to the patient through the CABG procedure. For example, using a segment of blood vessel that is significantly narrower than the occluded blood vessel (e.g., a segment of blood vessel with a significantly smaller inner diameter) as a graft can not provide sufficient blood flow. A clinician can consider which type of graft can most closely match the autologous blood flow in the patient. Currently, this consideration is determined primarily through “rules of thumb.” For example, the American College of Cardiology makes the following description. For left anterior descending artery (LAD) occlusion, the left internal mammary artery (LIMA) is preferred as the harvest vessel if possible, with the right internal mammary artery (RIMA) being the second choice. For left circumflex artery (LCX) and right coronary artery (RCA), the internal mammary artery (IMA) is used if the RCA is more than 90% stenosed. The radial artery can be used to bypass a left side artery if it is more than 70% stenosed, and the radial artery can be used to bypass a right side artery if it is more than 90% stenosed. The overall patency over time from best to worst is as follows: IMA, second is radial artery, then SVG.

[0032] A clinician can consider multiple bypasses that can be needed. It is not uncommon for multiple severe occlusions to be found at the same time. Thus, a clinician can desire to know how multiple grafts can interact with each other.

[0033] If an SVG is selected, a clinician can consider any issues regarding graft vessel remodeling. Currently, SVGs are the most common grafts in the world due to their relative ease of harvest and the length of the vessel. Some SVG patency issues appear to be related to remodeling over time. The cause of the remodeling is related to the difference between arterial and venous pressure. In some examples, the remodeling can be mitigated through specific surgical techniques or by adding a device support to the SVG.

[0034] In the most severe cases, these and other factors can be addressed by a clinician shortly before or during a CABG procedure. As can be seen, these factors are numerous and can be complex, even when applied based on a general population model. When attempting to plan a CABG procedure that includes patient-specific factors, the planning can be too complex to be completed in a human brain. The stress associated with a fast turnaround or emergency procedure can further complicate this planning.

[0035] In conjunction with graft planning, the clinician can also consider graft location. Distal graft connections should generally be made distal to the coronary obstruction, and should generally be kept close to the end of the obstruction to maximize the amount of revascularization. Additionally, the clinician can consider the proximal attachment location on the aorta of the graft vessel. For example, based on how blood is supplied to the coronary arteries (e.g., diastolic blood flow from the aorta), the clinician can consider making the proximal attachment as far down the aortic root as possible. This is also supported by the natural openings of the right coronary artery (RCA) and the left coronary artery (LCA). Additionally, the clinician can desire that the grafted vessel follow the contours of the heart while maintaining limited tension, slack, and redundant length. For example, grafts that are too long can increase the likelihood of poor blood flow due to, for example, kinking risk, dead space, friction loss, etc.

[0036] Currently, surgical access is typically accomplished via a full or partial sternotomy or thoracotomy. Generally, more access can make it easier and faster for the surgeon to make anastomoses (e.g., connections between adjacent blood vessels), but can lengthen the patient’s recovery time (which can increase hospital costs and bed occupancy), increase the likelihood of complications, and increase the patient’s pain. Based on the surgeon’s reach and visibility, some graft locations or combinations of grafts can preclude minimally invasive surgery.

[0037] It should be noted that some CABG procedures (including robotically assisted surgical procedures) can be accomplished through an incision between the ribs without performing a sternotomy. Thus, in some examples, such as in non-emergency situations, it can be desirable to plan graft locations that are balanced against access, such as the reach of a robotic manipulator.

[0038] Figure 1 is a schematic perspective view of an example medical system in accordance with one or more aspects of the present disclosure. The medical system 100 can include an imager 140 (which can be a CCTA imager), a display device 110, a table 120, additional imager(s) 142, a computing device 150, a network 156, and a server 160. In some examples, fewer or more components can be present.

[0039] The medical system 100 can be used for a medical procedure, such as a CABG procedure. In accordance with the techniques of the present disclosure, the medical system 100 can generate and display a procedure plan for a CABG procedure. For example, the computing device 150 and / or the server 160 can generate a procedure plan that includes at least one recommended graft location. The recommended graft location can include a recommended graft origin, a recommended graft path, and a recommended graft termination. The medical system 100 can display the procedure plan, e.g., on the display device 110, for viewing by a clinician. Such a medical system can facilitate a more informed decision by a clinician prior to or during a CABG procedure, which can improve graft patency, reduce or minimize harvest waste, reduce loss of blood supply at the harvest site(s), reduce or minimize procedure time, and shorten or otherwise improve patient outcomes, including recovery time.

[0040] The medical system 100 can be an example of a medical system for use in a surgical ward, a catheterization lab (cath lab), or other healthcare environment. In some examples, the medical system 100 can include other devices. In some examples, the medical system 100 can be used during a medical procedure, such as a CABG procedure. In some examples, the system 100 can be used during a diagnostic phase to diagnose a cardiovascular issue for a patient.

[0041] The computing device 150 can include, for example, an off-the-shelf device, such as a notebook computer, a desktop computer, a tablet computer, a smartphone, or other similar device. In other examples, the computing device 150 can be a special-purpose computing device, such as a special-purpose computing device designed specifically for use in the medical system 100. The computing device 150 includes memory and processing circuitry.

[0042] In some examples, the computing device 150 can be configured to control a robotic medical device, an electrosurgical generator, a peristaltic pump, a power supply, or any other accessories and peripherals related to or forming part of the medical system 100. In some examples, the computing device 150 can perform various control functions with respect to the imager 140, additional imager(s) 142, the display device 110, additional equipment 152, etc. The computing device 150 can be communicatively coupled to the imager 140, additional imager(s) 142, one or more devices of the additional equipment 152, the display device 110, the server 160, and / or the network 156.

[0043] While multiple features are described herein as belonging to the computing device 150, in some examples, features attributed to the computing device 150 can be performed by processing circuitry of the computing device 150, the imager 140, the server 160, the network 156 (e.g., one or more computing devices forming or connected to the network 156), other elements of the medical system 100, or any combination thereof. In some examples, processing circuitry associated with the computing device 150 can be distributed and shared among any combination of the computing device 150, the imager 140, the server 160, the network 156, the display device 110, the additional equipment 152, and / or other elements of the medical system 100. Additionally, in some examples, processing operations or other operations performed by processing circuitry of the computing device 150 can be performed by remotely-resident processing circuitry, such as one or more cloud servers or processors. For ease of discussion herein, such processing circuitry can be considered to be part of the computing device 150.

[0044] The medical system 100 includes a network 156, which can be a suitable network, such as a local area network (LAN), a wide area network (WAN), a wireless mobile network, a Bluetooth network, or the Internet, including wired or wireless networks. In some examples, the network 156 can be a secure network, such as a hospital network, which can limit access by users. In some examples, the network 156 can interconnect various devices of the medical system 100.

[0045] The imager 140 can be a CCTA imager and can image portions of the patient’s body, such as areas around or near the patient’s heart and areas with potential harvest vessels, during or prior to a medical procedure to visualize characteristics and locations of one or more occluded vessels to bypass, locations of potential grafts, anatomical structures in the patient’s heart region, characteristics and locations of potential harvest vessels, and the like. The additional imager(s) 142 can also be configured to image portions of the patient’s body, such as the patient’s heart vasculature. In some examples, the additional imager(s) 142 can include one or more devices other than a CCTA imager, such as an angiography device (e.g., a fractional flow reserve (FFR) angiography device), an ultrasound device (e.g., with an external probe, an intravenous probe, and the like), a fluoroscopy device, an optical coherence tomography (OCT) device, a near-infrared spectroscopy (NIRS) device, a magnetic resonance imaging (MRI) device, a positron emission tomography (PET) device, and the like. The additional imager(s) 142 can capture details of the patient’s anatomy that can not be captured by the imager 140, which can be used to update and / or provide further details of the surgical plan. In some examples, the additional imager(s) 142 can capture imaging data of the patient prior to the CABG procedure (e.g., during the same visit to the site of the CABG procedure, during a different visit to the site, or during a visit to another site). In some examples, the additional imager(s) 142 can capture imaging data of the patient during the CABG procedure.

[0046] In some examples, the computing device 150 can be configured to obtain clinician input, such as through a user interface that the computing device 150 can use to iterate on the surgical plan. For example, a clinician can input a graft angle preference, change a recommended graft location, replace a desired harvest vessel, and the like. The computing device 150 can then update the surgical plan based on the clinician input.

[0047] The computing device 150 can be configured to execute computer vision algorithms to determine the surgical plan or portions thereof, such as to determine a recommended graft location, determine a recommended harvest segment, and / or generate a three-dimensional (3D) model of the heart and surrounding vascular tissue.

[0048] According to the techniques of this disclosure, the computing device 150 can obtain input data including imaging data of a patient’s vasculature. For example, the computing device 150 can obtain the imaging data from the imager 140 and / or additional imager(s) 142. The computing device 150 can determine a procedure plan based on the input data, the procedure plan including at least one recommended graft location, the recommended graft location including a recommended graft origin, a recommended graft path, and a recommended graft termination. The computing device 150 can output the procedure plan for display. For example, the computing device can output the procedure plan to the display device 110 for display so that a clinician can view the procedure plan.

[0049] The additional equipment 152 can include devices configured to be used during a medical procedure, such as a CABG procedure, including but not limited to clamps, forceps, scissors, a cardiopulmonary bypass machine, tubes, SVG support devices, and the like.

[0050] The display device 110 can be configured to display imaging data captured from, for example, the imager 140 and / or additional imager(s) 142. In some examples, instead of or in addition to the captured imaging data, the display device 110 can be configured to display a 3D model of the patient’s coronary vasculature (which can be part of a procedure plan). In some examples, the display device 110 can be configured to display various user interfaces disclosed herein. In some examples, the display device 110 can be configured to display a procedure plan and / or a modified procedure plan as disclosed herein. The display device 110 can be configured to display any other content discussed in this disclosure as being displayed.

[0051] The table 120 can be, for example, an operating table or other table suitable for use during a medical procedure, such as a CABG procedure. Although depicted as being in the same environment as the imager 140, in some examples, the table 120 can not be in the same environment as the imager 140.

[0052] The server 160 can be configured to store data obtained and / or determined or generated by the computing device 150. In some examples, the server 160 can be configured to perform techniques attributed to the computing device 150. The server 160 can be communicatively coupled to the computing device 150, for example, through wired, optical, or wireless communication and / or through the network 156. The server 160 can be a hospital server (which can or can not be located in an operating room), a cloud-based server, and the like. The server 160 can be configured to store patient data, electronic medical records, and the like.

[0053] Figure 2 is a block diagram of an example of a computing device in accordance with one or more aspects of the disclosure. The computing device 200 can beFigure 1 Examples of computing device 150, network of computing devices 156, and / or server 160 are provided and may include workstations, desktop computers, laptop computers, servers, smartphones, tablet computers, dedicated computing devices, or any other computing device capable of executing the techniques of the present disclosure.

[0054] In some examples, computing device 200 may be configured to perform Figure 1 The computing device 200 may include, for example, memory 202, processing circuitry 204, display 206, network interface 208, input device(s) 210, or output device(s) 212, each of which, for ease of description, may represent any one of multiple instances of such a device within a computing system.

[0055] Although processing circuitry 204 appears Figure 2 In the computing device 200 of FIG. 1 , however, in some examples, features attributed to the processing circuitry 204 may be provided by Figure 1 In some examples, one or more processors associated with processing circuitry 204 in computing device 200 may be executed by processing circuitry of any of computing device 150, imager 140, server 160, network of computing devices 156, or other components. Figure 1 The processing circuitry 204 may be distributed and shared among any combination of the computing device 150, imager 140, server 160, network of computing devices 156, or other components. In addition, in some examples, the processing operations or other operations performed by the processing circuitry 204 may be performed by one or more remotely resident processors, such as one or more cloud servers or processors, each of which may be considered part of the computing device 200. The computing device 200 may be used to perform any of the techniques described in this disclosure and may be used alone or in conjunction with other components such as a server or server. Figure 1 The computing device 150, imager 140, server 160, network of computing devices 156, other components, or components of a system including any or all of such devices) may combine to form all or part of a device or system configured to perform such techniques.

[0056] The memory 202 of the computing device 200 includes any non-transitory computer-readable storage medium for storing data or software that is executable by the processing circuitry 204 and that controls the operation of the computing device 150. In one or more examples, the memory 202 can include one or more solid-state storage devices such as flash memory chips. In one or more examples, the memory 202 can include one or more mass storage devices connected to the processing circuitry 204 via a mass storage controller (not shown) and a communication bus (not shown).

[0057] Although the description of the computer-readable medium herein refers to a solid state storage, those skilled in the art will appreciate that the computer-readable storage medium can be any available medium that can be accessed by the processing circuitry 204. That is, the computer-readable storage medium includes non-transitory, volatile, and non-volatile, removable, and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. For example, the computer-readable storage medium includes RAM, ROM, EPROM, EEPROM, flash memory or other solid state memory technology, CD-ROM, DVD, Blue-ray or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and that can be accessed by the computing device 200. In one or more examples, the computer-readable storage medium can be stored in the cloud or remote storage and accessed using one or more any suitable technologies over at least one of a wired or wireless connection.

[0058] The memory 202 can store computer vision algorithms 224. The computer vision algorithms 224 can be trained using imaging data and / or user input data collected from past medical procedures. The memory 202 can also store user interface(s) 218. The user interface(s) 218 can include one or more user interfaces that the processing circuitry 204 can output for display by the display 206 and / or the display device 110. For example, a clinician can interact with the user interface(s) 218 to provide input data for use by the processing circuitry 204 in generating, updating, or modifying a procedure plan.

[0059] The memory 202 can store imaging data 214, procedure plan(s) 220, electronic medical record(s) 236, 3D model(s) 232. The imaging data 214 can be collected by the imager 140 and / or additional imager(s) 142 Figure 1) during a medical procedure for a patient. Processing circuitry 204 can obtain imaging data 214 from imager 140 and / or additional imager(s) 142 and store imaging data 214 in memory 202. Processing circuitry 204 can use imaging data 214 to determine procedure plan(s) 220, etc. Processing circuitry 204 can use imaging data 214 to determine one or more 3D models and / or update 3D model(s) 232. Processing circuitry 204 can use information obtained from a clinician to iterate and update procedure plan(s) 220.

[0060] Processing circuitry 204 can execute any of user interface(s) 218 to cause display 206 (and / or display device 110 of system 100) to present the UI of user interface(s) 218 to one or more clinicians performing a medical procedure. Figure 1

[0061] For example, processing circuitry 204 can obtain information indicative of one or more occluded arteries. For example, processing circuitry 204 can obtain data related to current arterial obstruction from imager 140, which can be a CCTA imager. Additionally or alternatively, processing circuitry 204 can obtain data related to potential graft sites. For example, processing circuitry 204 can obtain image data of potential graft sites from imager 140 and / or obtain manually entered information related to potential graft sites from a user interface (e.g., input device(s) 210) or network interface 208.

[0062] Processing circuitry 204 can obtain a coronary perfusion pressure (CPP) or an estimate of CPP, e.g., from a device of additional equipment 152. CPP can be a measure of the difference between aortic diastolic pressure and left ventricular end-diastolic pressure. Processing circuitry 204 can obtain a clinician’s preference for a graft, e.g., from a user interface (e.g., input device(s) 210) or network interface 208. Processing circuitry 204 can obtain an indication of whether a procedure is robotic or robot-assisted, e.g., from a user interface (e.g., input device(s) 210) or network interface 208.

[0063] ​The processing circuitry 204 can determine, from the obtained information / data, one or more suggested (e.g., optimal) locations for proximal aortic anastomosis, the shortest graft path(s) that bypass one or more blockages, suggested suitable graft length(s) for achieving full (or sufficient) restoration of blood flow, suitable donor vessels as graft options based on the diameter of the blocked artery and the length needed to restore blood flow, an estimate of the SVG support needed (if it can be calculated based on available data) as sometimes the SVG vein graft can collapse, options for reaching the IMA graft from the chest wall, initial estimates of robotic or robotic-assisted surgical methods for minimizing incision size, etc. For example, the processing circuitry 204 can generate surgical plan(s) 220 that include any of this information or any combination thereof. The processing circuitry 204 can store the surgical plan(s) 220 in the memory 202. The processing circuitry 204 can control a display device (e.g., the display 206, the display device 110, etc.) to display the surgical plan(s) 220 for viewing by the clinician.

[0064] In some examples, the processing circuitry 204 can facilitate the clinician interacting with the surgical plan(s) 220. For example, the processing circuitry 204 can allow the clinician to confirm or modify aortic and / or vascular anastomosis locations via the user interface(s) 218, the input device(s) 210, and / or the network interface 208. The processing circuitry 204 can permit the clinician to review the surgical plan(s) 220 and any associated imaging data 214 to view potential bypass sites to ensure that the potential bypass sites are free of plaque buildup or other potential blockages. The processing circuitry 204 can permit the clinician to select a graft site location, which the processing circuitry 204 can record in the surgical plan(s) 220. The processing circuitry 204 can permit the clinician to modify the robotic method (if needed) and store the modified method in the surgical plan(s) 220.

[0065] After considering any clinician input, processing circuitry 204 can iterate on the surgical plan(s) 220 and generate a final surgical plan. For example, processing circuitry 204 can base the final surgical plan on the original surgical plan and any clinician input. Processing circuitry 204 can store the final surgical plan in the surgical plan(s) 220. The final surgical plan in the surgical plan(s) 220 can include a harvest site plan including lengths of segment(s) needed for the CABG procedure, a suggested (e.g., optimal) harvest vessel segment for each bypass, a corresponding bypass path, an indication of a need for SVG support (if applicable), and the like. The final surgical plan in the surgical plan(s) 220 can include an estimate of blood flow restoration (e.g., distal segments restored and comparison of bypass to blocked vessel). The final surgical plan in the surgical plan(s) 220 can include robotic positioning and access locations (if applicable) and / or target outputs for robotic anastomosis.

[0066] For example, processing circuitry 204 can control display 206, output device(s) 212, and / or display device 110 to display the surgical plan (e.g., the final surgical plan), e.g., to provide real-time guidance during the harvest portion and / or bypass portion of the CABG procedure. The display of the surgical plan can assist the clinician in better understanding the harvest location, selecting an appropriate graft length, and determining a particular section of the harvested vessel that is not interrupted by a branch. As a result, the harvest operation of the CABG procedure can be expedited, and blood supply loss at the harvest site can be reduced.

[0067] The display of the surgical plan can assist the clinician in understanding the length of the IMA graft needed and whether the IMA graft can achieve a crossing over the obstruction without tension. As a result, the display of the surgical plan can minimize (or reduce) the length of the needed vessel that is dissected from the patient’s chest wall.

[0068] The display of the surgical plan can also assist the clinician in attaching the bypass graft to the ideal (e.g., recommended) location on the aorta to prevent the vessel from becoming congested and / or crossing, while maximizing blood flow to the affected area of the patient’s heart.

[0069] Processing circuitry 204 can assist the clinician in selecting a location(s) for the aortic anastomosis. For example, processing circuitry 204 can identify the ascending aorta and the pulmonary artery from the imaging data 214 via execution of a computer vision algorithm 224 that can be trained to identify such vessels. For example, it can be desirable to attach the graft as close to the aortic valve as possible in order to mimic the native anatomy. However, it can also be desirable for the graft to bypass the pulmonary trunk without flipping down and without the risk of blood flow strangulation.

[0070] For example, processing circuitry 204 can organize the bypass and take a sternum approach based on proximity to an occlusion. In some examples, a clinician can adjust the starting point following the initial procedure plan recommendation. For example, if there is a patient condition that invalidates the initial placement, such as calcification that can affect anastomosis success, the clinician can desire to adjust the starting point in the initial procedure plan. Accordingly, the clinician can adjust the starting point in the initial procedure plan via input device(s) 210, user interface(s) 218, and / or network interface 208.

[0071] For example, processing circuitry 204 can determine a recommended (e.g., optimal) aortic graft location based on imaging data 214 and determine potential obstacles. For example, processing circuitry 204 can execute computer vision algorithm 224 to determine potential obstacles, and processing circuitry 204 can determine the recommended aortic graft location as a recommended graft path that includes avoiding such obstacles.

[0072] In some examples, processing circuitry 204 can facilitate a clinician placing representative clamps and aortic root cannula in a model of the patient’s anatomy in 3D model(s) 232 and / or procedure plan(s) 220. Clamps and aortic root cannula can reduce the amount of aorta available for a CABG procedure. By allowing a clinician to represent such equipment in 3D model(s) 232, processing circuitry 204 can determine better anastomosis location recommendations and better blood flow restoration estimates. For example, computer vision algorithm 224 can be trained on data including imaging data from past procedures with clamps and / or aortic root cannula attached and blood flow data associated with the past procedures. Accordingly, a clinician can place representative clamps and / or aortic root cannula in 3D model(s) 232 via input device(s) 210, user interface(s) 218, and / or network interface 208.

[0073] The processing circuitry 204 can determine a recommended path for each bypass based on the imaging data 214. For example, it can be desirable for the path to extend generally parallel to the autologous anatomy, and the processing circuitry 204 can recommend a path for each bypass that extends parallel or generally parallel to the autologous anatomy appearing in the imaging data 214. For example, after establishing the source curvature and the initial curvature, the processing circuitry 204 can generate the remaining path elements. For example, the processing circuitry 204 can generate a 3D model of the heart (e.g., in the 3D model(s) 232) based on the obtained imaging data, such as a CCTA scan. In some examples, one or more of the 3D model(s) 232 is part of the one or more surgical plans 220. Based on the path and curvatures that can be represented in the 3D model, the processing circuitry 204 can determine the length of the harvested blood vessel to be taken. In some examples, the processing circuitry 204 can include some additional length for the clinician to work with, such as 1 mm to 2 mm.

[0074] The processing circuitry 204 can identify restricted blood flow and the degree of each obstruction based on the obtained imaging data 214 and / or manually entered data. For example, if the processing circuitry 204 recommends going over an obstruction 8 mm to merge with the occluded blood vessel (which can be editable by the clinician), the processing circuitry 204 can generate a profile that generally follows the autologous blood vessel and merges with the first path segment tangentially to the outer profile of the heart (e.g., to avoid the pulmonary trunk), where possible. After the processing circuitry 204 generates the complete path, the processing circuitry 204 can convert the length of the path to the length of individual grafts needed and the total harvested length of all grafts needed to perform the CABG procedure.

[0075] In addition to the path requirements, the blood vessel diameter can also play a role in the success of the graft. Thus, the processing circuitry 204 can rank the possible graft blood vessels and / or segments based on the degree of similarity of each diameter (e.g., inner diameter) of the possible harvested blood vessels and / or segments to the diameter (e.g., inner diameter) of the obstructed anatomy based on the imaging data 214, such as the CCTA scan data of the obstructed blood vessel(s) and / or the harvesting site information. For example, if the inner diameter of the autologous blood vessel distal to the obstruction is 2.5 mm (which closely matches the patient’s radial artery inner diameter of 2.2 mm), the patient’s radial artery can be a blood vessel that is suitable for the graft (e.g., a good match) and the blood vessel is easy to anastomize.

[0076] The processing circuitry 204 recommends and / or can facilitate the clinician inputting other information for inclusion into the final surgical plan in the surgical plan(s) 220, e.g., via the input device(s) 210, user interface(s) 218, and / or network interface 208. For example, the clinician can input a profile for the anastomotic incision (e.g., angled or straight), which would affect the length of the graft and blood flow characteristics. The clinician can input a desire to keep the grafts with additional slack, allowing for a reattempt at making an anastomosis in the event of an initial anastomosis failure. In this case, the processing circuitry 204 can add additional length to the recommended donor vessel(s) and / or segments to be harvested. The clinician can input a desire to use graft vessel from a single source for all bypasses of a given CABG surgery to protect the harvest site, which can speed up the harvest procedure and potentially reduce the number of harvest procedures performed. For example, if three grafts are to be performed and only the SVG can provide graft vessel segments for all three grafts, the processing circuitry 204 can recommend taking down the vessel segments for the grafts from a particular location (e.g., the SVG).

[0077] In some examples, such as in the case where the clinician can have harvested a vessel prior to the processing circuitry 204 determining the recommended graft location, the processing circuitry 204 can determine the recommended graft location based at least in part on a diameter (e.g., inner diameter) of the harvested vessel. For example, the clinician can harvest segment(s) of a vessel and can desire to use such segment(s) as grafts. Because the inner diameter of the segments to be used as grafts can not necessarily match the inner diameter of the occluded vessel at a given location, the processing circuitry can determine where to position the grafts based at least in part on the inner diameter of the harvested segments. Such a location can be different than a case where the inner diameter of the segments matches the inner diameter of the occluded vessel.

[0078] In some examples, the IMA (also referred to as the internal thoracic artery (ITA)) can be used as a graft vessel. The IMA generally extends along the inner side of the chest wall and supplies blood to the anterior chest. The vessel is often sectioned and repositioned to supply blood distal to the blockage. The processing circuitry 204 can determine a recommendation to section the IMA from the chest wall that can minimize or reduce the loss of blood supply to the anterior chest wall (which can be associated with sternal wound infection) when using the IMA as a graft vessel. In some examples, the processing circuitry 204 can recommend performing a harvest, such as a resection of the IMA from the chest wall up to a specified rib, rather than all the way up to the clavicle.

[0079] Processing circuitry 204 can examine potential harvest sites and provide recommendations and / or ordering of potential harvest vessel segments based on bypass needs, such as bypass needs determined by processing circuitry 204 and / or input by a clinician. For example, processing circuitry 204 can utilize bypass pathway determination results, such as (diameters, lengths of individual segments, and / or total procedure needs) and input from a preliminary harvest site scan, e.g., imaging data 214, to provide guidance during harvesting.

[0080] For example, a minimum total harvest length needed for all grafts to be performed during a CABG procedure can be utilized to determine a harvest location. For example, an SVG is typically significantly longer than a radial artery, satisfying more and / or longer bypass requirements. If the length of the radial artery is insufficient to cover all bypasses, a clinician can harvest from the SVG, rather than from multiple sites. Alternatively or additionally, an internal diameter of a potential harvest vessel can be utilized to determine a harvest vessel. For example, it can be desirable for an internal diameter of a graft to match or relatively match an internal diameter of an occluded vessel.

[0081] If imaging data of a harvest site is not available for some reason, processing circuitry 204 can provide a clinician with an option to utilize a representation of typical anatomy of a patient. In some examples, the typical anatomy can be based on a typical person. In some examples, the typical anatomy can include a length and / or a diameter of a harvest site vessel(s) that can be equal to a length and / or a diameter of a harvest site vessel(s) of an average person.

[0082] If imaging data 214 is available, a clinician can use a procedure in procedure(s) 220 to plan multiple vessel segments within a single harvest operation. For example, segments with fewer branch interruptions can be preferred and can match a length needed for a bypass. By providing an indication of such harvest vessel recommendations, processing circuitry 204 can facilitate limiting removal of donor vessel tissue to only vessel tissue needed for a graft, reducing loss of blood supply at a harvest site.

[0083] Processing circuitry 204 can provide and include in a procedure an estimate of recovered blood flow predicted to occur after a CABG procedure following a procedure. Processing circuitry 204 can estimate recovered blood flow to areas after a CABG procedure based on a planned graft using a blood flow diagnostic model. In some examples, processing circuitry 204 can display such a planned graft with the determined recovered blood flow estimate as part of a procedure. Such information can be useful to a clinician and can influence a decision by a clinician whether to alter a procedure.

[0084] For example, a display such as display 206 can display a representation (e.g., displayed via color) of estimated FFR for the planned graft and other affected vessels in the graft blood vessels as set forth in the surgical plan. For example, a bypassed vessel can be shown in red, indicating poor FFR, while the planned graft vessel(s) can be displayed in white, green, or another color, indicating good or acceptable FFR and restored blood flow. In this way, a clinician can review the surgical plan prior to performing the CABG procedure and determine that the surgical plan achieves a suitable outcome. If the clinician reviews the surgical plan and determines that the surgical plan does not achieve a suitable outcome, the clinician can modify the surgical plan prior to performing the CABG procedure. In this case, processing circuitry 204 can update the surgical plan and control the display to display updated estimated FFR based on the modified surgical plan.

[0085] In some examples, processing circuitry 204 can consider competitive blood flow in determining the estimate of restored blood flow. For example, processing circuitry 204 can consider residual blood flow through the occluded blood vessel, blood flow through the proposed graft, and any reduced blood flow to the original ostium. If any of these items can be problematic (e.g., negatively impact the blood flow analysis), processing circuitry 204 can provide a warning to the clinician and / or recommend adjustments to the surgical plan. For example, the graft can constrict due to blood flow issues, which can be detrimental to the patient.

[0086] In some examples, processing circuitry 204 can determine an estimate of backflow from the graft into the native blood vessel. Where appropriate, processing circuitry 204 can warn of the potential for poor hemodynamics and backflow causing calcium deposits to dislodge and create new blockages distally based on such determined estimate of backflow. For example, if the determined estimate of backflow satisfies a backflow threshold, processing circuitry 204 can provide such a warning to the clinician via a display such as display 206 or any of output device(s) 212. Such a warning can be visual, audible, haptic, etc.

[0087] In some examples, the techniques of the present disclosure can be used for patients at moderate or low risk of clinical events. For example, a patient can present with initial symptoms and undergo one or more screenings, which can include CCTA or other imaging to collect imaging data 214. In some examples, a clinician can choose to use traditional “rule of thumb” techniques for patients with the most severe conditions, rather than using the patient-specific techniques described in the present disclosure.

[0088] Additional tests and / or scans can be performed to provide imaging data 214 for patients who are less ill and who are scheduled for "elective" surgery. Processing circuitry 204 can determine a recommended graft location or combination of graft locations based on input data, such as imaging data 214. Additionally or alternatively, processing circuitry 204 can determine a recommended harvest segment based on input data, such as imaging data 214. Processing circuitry 204 can control a display (e.g., display 206) to display or otherwise provide a recommendation (an initial surgical plan of surgical plan(s) 220) to a clinician. Processing circuitry 204 can provide an opportunity for the clinician to refine the initial surgical plan. For example, the clinician can change the location of a new opening for a 2 graft on the aorta. Processing circuitry 204 can re-determine a recommendation based on the clinician input and output a revised surgical plan of surgical plan(s) 220 for display, which processing circuitry 204 can iterate with the clinician. Processing circuitry 204 can generate a final surgical plan for the clinician to use in preparing for and / or during the CABG surgery.

[0089] Processing circuitry 204 can be implemented by one or more processors, which can include any suitable number of fixed function circuits, programmable circuits, or a combination thereof. In various examples, control of any functionality by processing circuitry 204 can be implemented directly within processing circuitry 204 or in combination with any suitable electronic circuitry designated for a specified function. Fixed function circuitry refers to circuitry that provides a particular functionality and is preset on the operations that can be executed. Programmable circuitry refers to circuitry that can be programmed to perform various tasks and provides flexible functionality among the operations that can be executed. For example, programmable circuitry can execute software or firmware that causes the programmable circuitry to operate in the manner defined by instructions of the software or firmware. Fixed function circuitry can execute software instructions (e.g., to receive parameters or output parameters), but the types of operations that the fixed function circuitry executes are generally immutable. In some examples, one or more of the units can be distinct circuit blocks (fixed function or programmable), and in some examples, one or more of the units can be an integrated circuit.

[0090] The instructions can be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), graphics processing units (GPUs), or other equivalent integrated or discrete logic circuitry. Accordingly, as used herein the term processing circuitry 204 can refer to one or more processors, any of which can include one or more of the above-described processors or processing structures, or any other structure suitable for implementation of the techniques described herein. In addition, in some aspects, the functionality described herein can be provided within dedicated hardware and / or software modules configured for encoding and decoding, or incorporated in a combined codec. Also, the techniques could be fully implemented in one or more circuits or logic elements.

[0091] Display 206 can be touch-sensitive or voice-activated, such that display 206 can function as an input and output device. Alternatively, a keyboard (not shown), mouse (not shown), joystick (not shown), or other data entry device(s) (e.g., input device(s) 210) can be utilized. In some examples, display 206 can include a virtual reality and / or augmented reality headset. In some examples, display 206 can include a holographic device.

[0092] Network interface 208 can be adapted to connect to a network (e.g., network 156), such as a local area network (LAN), wide area network (WAN), wireless mobile network, Bluetooth network, or the Internet, including wired or wireless networks. In some examples, network interface 208 can include one or more application programming interfaces (APIs) for facilitating communication with other devices. For example, computing device 200 can receive imaging data 214 from imager 140 and / or additional imager(s) 142 during a medical procedure via network interface 208. Computing device 200 can interact with server 160 via network interface 208. Computing device 200 can receive updates to its software (e.g., application programs 216) via network interface 208. Computing device 200 can also display a notification on display 206 that a software update is available.

[0093] Input device(s) 210 can include any device that enables a user to interact with computing device 200, such as a mouse, joystick, keyboard, foot pedal, touch screen, augmented reality input device(s) that receive gestures or body movements, or a voice interface.

[0094] Output device(s) 212 can include any connection ports or buses, such as a parallel port, serial port, universal serial bus (USB), or any other similar connection ports known to those skilled in the art.

[0095] The application programs 216 can include one or more software programs stored in the memory 202 and executed by the processing circuitry 204 of the computing device 200.

[0096] Figure 3 is a conceptual diagram illustrating an example surgical plan according to one or more aspects of the present disclosure. The surgical plan 300 can be an example of any of the surgical plan(s) 220, such as an original surgical plan, an iteration of a surgical plan, or a final surgical plan.

[0097] The surgical plan 300 can include recommended graft location(s) 302. For each recommended graft, the recommended graft location(s) 302 can include one or more of a recommended graft origin, a recommended graft path, and a recommended graft terminus. For example, for a given recommended graft location, the recommended graft location(s) 302 can include a recommended graft origin (which can be one of a distal or proximal end of the obstruction) and a recommended graft terminus (which can be the other of the distal or proximal end of the obstruction) and a recommended graft path therebetween.

[0098] The surgical plan 300 can include recommended vessel edge conditions 330. For example, the recommended vessel edge conditions 330 can include a recommended cut angle (a cut angle to be used for the vessel for grafting), a recommended taper (or no taper), or other conditions for the edges or ends of the vessel to be used for grafting. For example, the processing circuitry 204 can perform a blood flow analysis, and determine that a particular cut angle to be used for the vessel for grafting can provide an acceptable or preferred flow rate after the CABG procedure, and recommend that cut angle (e.g., 45 degrees) in the recommended vessel edge conditions 330.

[0099] The surgical plan 300 can include a harvesting plan 304. The harvesting plan 304 can include harvesting recommended segment(s) for grafting from a harvesting vessel. The processing circuitry 204 can determine such recommended segment(s) based on a length of segment (e.g., segment length 322) required to traverse the recommended graft path 310 and attach at the recommended graft origin 306 and the recommended graft terminus 308, and / or a determined diameter (e.g., inner diameter) of the occluded vessel 332 and a determined diameter (e.g., inner diameter) of the harvesting vessel segment 324. For example, the harvesting plan 304 can include a length of segment(s) required for the CABG procedure, a suggested (e.g., optimal) harvesting vessel segment for each bypass, a corresponding bypass path, an indication of a need for SVG support (if applicable), and the like.

[0100] In some examples, the surgical plan 300 can include the above-described Figure 2one or more of the described 3D model(s) 232. In some examples, the surgical plan 300 can include imaging data 214. In some examples, the surgical plan 300 can include SVG support 312, such as an estimated need (or lack of need) for SVG support and / or a recommendation of one or more SVG support devices to use during the CABG procedure. In some examples, the surgical plan 300 can include one or more recommendations for segmenting an IMA graft from a chest wall (to reach the IMA 314), such as a recommendation of where to stop rib separation from the chest wall to separate the IMA.

[0101] In some examples, the surgical plan 300 can include an estimate of blood flow restoration 316 to be accomplished by the CABG procedure. For example, the estimate of blood flow restoration 316 can include an estimated fractional flow reserve (FFR) value associated with a graft to be accomplished during the CABG procedure. In some examples, the surgical plan 300 can include an indication of a recommendation of robotic assistance 318 for the CABG procedure, such as a recommendation of a robotic assisted surgical approach. In some examples, the recommendation of robotic assistance 318 can include a recommended robotic positioning, at least one recommended entry location on the patient, and / or at least one target output for robotic anastomosis. In some examples, the surgical plan 300 can include a recommendation of a surgical approach strategy 320, such as how to enter the patient’s area for graft attachment while minimizing incision size.

[0102] Figure 4 is a conceptual diagram illustrating example surgical plan techniques in accordance with one or more aspects of the present disclosure. While Figure 4 techniques are described as being performed by Figure 2 computing device 200, these techniques can also be performed by any device or combination of devices of Figure 1 medical system 100 or any device(s) capable of performing these techniques.

[0103] The processing circuitry 204 obtains input data including imaging data of a vasculature of a patient (400). For example, the processing circuitry 204 can obtain input data including imaging data 214 of a vasculature of a patient from the imager 140 and / or additional imager(s) 142. The processing circuitry 204 can determine a procedure plan including at least one recommended graft location including a recommended graft origin, a recommended graft path, and a recommended graft terminus based on the input data (402). For example, the processing circuitry 204 can determine a patient-specific procedure plan 300 for the patient. The procedure plan 300 can include at least one recommended graft location (e.g., recommended graft location(s) 302). The recommended graft location can include at least one of a recommended graft origin 306 (e.g., a first attachment location for the graft), a recommended graft path 310 (e.g., a route that the transplanted blood vessel can take from the graft origin to the graft terminus), and a recommended graft terminus 308 (e.g., a second attachment location for the graft). The processing circuitry 204 can output the procedure plan for display (404). For example, the processing circuitry 204 can output the procedure plan 300 to the display 206 and / or the display device 110.

[0104] In some examples, the at least one recommended graft location includes a recommended graft location for a proximal aortic anastomosis. In some examples, the at least one recommended graft location includes a recommended graft location for a distal anastomosis distal to a coronary artery occlusion. In some examples, the recommended graft path includes a path between the recommended graft origin and the recommended graft terminus configured to avoid any obstacles between the recommended graft origin and the recommended graft terminus.

[0105] In some examples, the procedure plan 300 further includes at least one recommended blood vessel edge condition to be used for the transplanted blood vessel. In some examples, the at least one recommended blood vessel edge condition includes at least one cut angle.

[0106] In some examples, processing circuitry 204 is further configured to determine one or more recommended harvest vessel segment lengths based at least in part on the at least one recommended graft location. In some examples, surgical plan 300 further includes the one or more recommended harvest vessel segment lengths. In some examples, processing circuitry 204 is further configured to determine at least one recommended harvest vessel segment based at least in part on the one or more recommended harvest vessel segment lengths and a recommended harvest vessel anatomy. In some examples, surgical plan 300 further includes a harvest plan including an identification of the at least one recommended harvest vessel segment. In some examples, the recommended harvest vessel anatomy includes a recommended harvest vessel diameter, the recommended harvest vessel diameter based on a diameter of the obstructed vessel.

[0107] In some examples, processing circuitry 204 is further configured to obtain user input associated with surgical plan 300. In some examples, the user input can be obtained during the CABG procedure. In some examples, the user input can be obtained prior to the CABG procedure. In some examples, processing circuitry 204 can modify surgical plan 300 based on the user input to generate a modified surgical plan (e.g., in surgical plan(s) 220) or an iteration of the surgical plan. In some examples, processing circuitry 204 is configured to output the modified surgical plan for display.

[0108] In some examples, imaging data 214 includes CCTA imaging data. In some examples, imaging data 214 includes angiographic imaging data. In some examples, imaging data 214 includes FFR angiographic imaging data. In some examples, imaging data 214 includes at least one of imaging data of the at least one obstructed vessel or imaging data of the at least one potential harvest vessel. In some examples, input data further includes at least one of: information related to the at least one potential harvest vessel, a measured or estimated value of coronary perfusion pressure (CPP), or an indication of whether the CABG procedure is a robotically assisted procedure. For example, a clinician can input such information via user interface(s) 218, input device(s) 210, or network interface 208, and / or processing circuitry 204 can obtain such information from additional equipment 152.

[0109] In some examples, the processing circuitry 204 is further configured to determine at least one of: an estimate of the SVG support, one or more recommendations to dissect the IMA graft from the chest wall, or one or more recommendations for a robotic assisted surgical procedure. In such examples, the surgical plan 300 can further include at least one of: the estimate of the SVG support, the one or more recommendations to dissect the IMA graft from the chest wall, or the one or more recommendations for a robotic assisted surgical procedure.

[0110] In some examples, the processing circuitry 204 is further configured to determine an estimate of blood flow restoration based on at least one of the recommendations. In such examples, the surgical plan 300 can further include a representation of the blood flow restoration estimate.

[0111] In some examples, the processing circuitry 204 is further configured to determine at least one of: a recommended robotic positioning, at least one recommended entry location on the patient, or at least one target output for robotic anastomosis. In such examples, the surgical plan 300 can include at least one of: the recommended robotic positioning, the at least one recommended entry location on the patient, or the at least one target output for robotic anastomosis.

[0112] The surgical plan 300 can provide the clinician with insight into the specifics of the case (e.g., graft length needed, robotic joint activity limitations, vessel conditions, etc.). Performing a CABG procedure by the clinician with the surgical plan 300 (when compared to not using such a surgical plan) can result in improved blood flow due to minimized graft length and matching vessel diameters, and reduced blood supply loss at the harvest site. Using the surgical plan 300 can save time in selecting, cutting, and / or positioning the graft for a CABG procedure.

[0113] Figure 5is a conceptual diagram illustrating example potential harvest vessels according to one or more aspects of the present disclosure. Any of IMA 500, radial artery 502, or greater saphenous vein 506, or other harvest sites (not shown) can be potential harvest vessels for a CABG procedure. For example, processing circuitry 204 can determine one or more recommended graft locations 302 based on imaging data 214. The recommended graft locations can include at least one of a recommended graft origin 306, a recommended graft path 310, or a recommended graft termination 308. For a given graft location, processing circuitry 204 can determine an appropriate harvest vessel segment length for the recommended graft based on the graft location. Further, processing circuitry 204 can determine an appropriate harvest vessel segment diameter (e.g., inner diameter) to use for the graft based on a diameter (e.g., inner diameter) of the occluded vessel that the graft is intended to bypass. Processing circuitry 204 can use the determined length and diameter information to attempt to find an appropriate harvest vessel segment to use for the graft. For example, processing circuitry 204 can use imaging data 214 of the potential harvest vessels to identify vessel segments in the potential harvest vessels that have an appropriate length and diameter for use in the graft. Processing circuitry 204 can attempt to identify bifurcations or other structural features in the potential harvest vessels that can make some segments less suitable for use in order to avoid using such segments when possible.

[0114] It should be noted that the techniques of the present disclosure can be used even when the harvest procedure is not part of a CABG procedure. For example, a clinician can use one or more artificial, cadaver, or animal blood vessels for a CABG procedure as an alternative or in addition to one or more harvest vessels of a patient.

[0115] FIG. 6 is a conceptual diagram illustrating different example surgical access techniques. When determining the surgical plan 300, the processing circuitry 204 can recommend a surgical access strategy, e.g., based on the graft location(s) 302. The surgical access strategy 600 can include a median sternotomy, and can provide maximum access and / or visibility to the area on the patient’s body where the grafts will be positioned. However, the surgical access strategy 600 can involve vertically fully cutting open the sternum to open the entire thoracic cavity. As such, the surgical access strategy 600 can be considered a relatively high-invasiveness procedure, and typically requires the patient to undergo a longer recovery period than other potential surgical access strategies. If less access can be needed to perform the CABG procedure, the processing circuitry 204 can recommend a different surgical access strategy, such as any of the surgical access strategies 602, 604, or 606. The surgical access strategy 602 can involve vertically partially cutting open the sternum, and then making one or more lateral cuts on the sternum to open a portion of the thoracic cavity (e.g., an upper portion of the thoracic cavity). The surgical access strategy 604 can involve vertically partially cutting open the sternum, and then making a single lateral cut on one side of the sternum to open a portion of the thoracic cavity (e.g., an upper left portion of the thoracic cavity). The surgical access strategy 606 can avoid cutting open the sternum altogether, and instead form an incision through the tissue between the ribs to open access through the incision itself. The examples of FIG. 6 are generally presented in order of invasiveness / accessibility / visibility from greatest to least, where the surgical access strategy 600 has the greatest invasiveness / accessibility / visibility, followed by the surgical access strategy 602, then the surgical access strategy 604, followed by the surgical access strategy 606, which has the least invasiveness / accessibility / visibility. Since patient recovery time and comfort can be affected by the access strategy used by the clinician, the processing circuitry 204 can recommend the surgical access strategy with the least invasiveness that can provide sufficient access to perform the recommended grafts as part of the surgical plan 300.

[0116] Figure 7 is a conceptual diagram of an example 3D model of a heart in accordance with one or more aspects of the present disclosure. The 3D model 700 can be Figures 2 to 3Fig. 7 is a conceptual diagram illustrating an example of one of the 3D models 232. The processing circuitry 204 can present the 3D model 700 via the user interface(s) 218, for example on the display 206, as part of the surgical plan 300 or separately. The clinician can interact with the user interface(s) 218 to place the clip representation 702 and / or the aortic root cannula representation 704 in a preferred location(s) on the representation of the patient’s heart, for example. Since the clip and the aortic root cannula can reduce the amount of available aorta for the CABG procedure, the processing circuitry 204 can use the preferred location(s) as input to iterate the recommended graft location(s) and any associated harvesting plan. For example, the processing circuitry 204 can generate an updated plan including the updated recommended graft location(s).

[0117] Figure 8 Fig. 8 is a conceptual diagram illustrating an example recommended graft location in accordance with one or more aspects of the present disclosure. Figure 8 The recommended graft location 800 can include a recommended graft origin 802 and a recommended graft path 804. The recommended graft path 804 can avoid the pulmonary trunk and follow the contours of the heart surface while avoiding obstacles and connecting the recommended graft origin 802 to a recommended graft destination 806 to bypass the obstruction.

[0118] Figure 9 Fig. 9 is a conceptual diagram illustrating an example harvested radial artery. The harvested radial artery 900 can be an example of a radial artery segment harvested without using the harvesting plan 304. For example, the harvested radial artery 900 can be harvested for use in two grafts. After harvesting, the clinician can cut the harvested radial artery 900 for use in the two grafts. A segment 902 can be designated for use in a first graft, and a segment 904 can be designated for use in a second graft. However, the segment 902 can include a pinch-off branch 908 (e.g., formerly known as a bifurcation), which can be undesirable in a graft. Additionally, the length of the harvested radial artery 900 can be greater than necessary, as the harvested radial artery 900 has an arbitrary end point 906 where the clinician cut the radial artery during harvesting. Thus, the harvested radial artery 900 includes a redundant segment 910 that is best left in situ in the patient’s arm. If the harvesting plan 304 is used, the harvesting plan can propose a better planned end point than the arbitrary end point 906 and avoid recommending the segment 902 for use in a graft due to the pinch-off branch 908 or bifurcation.

[0119] Figure 10is a conceptual diagram illustrating example use of 3D models generated based on imaging data other than CCTA imaging data in accordance with one or more aspects of the present disclosure. As discussed above, the techniques of the present disclosure can be used with imaging data such as CCTA imaging data and / or other imaging data. For example, not all patients will leave the emergency room to receive CCTA, but the techniques of the present disclosure can still be used for such patients via other imaging modalities. For example, a patient can go to a catheterization lab for coronary angiography and / or percutaneous coronary intervention (PCI) due to the patient experiencing chest pain, fatigue, etc. Upon entering the catheterization lab, the clinician can find that the patient has multi-vessel disease. The patient can then be referred for CABG surgery in this case.

[0120] As the use of techniques such as FFR angiography become more widespread, the techniques can become a relatively quick and reliable way to diagnose multiple lesions and assess lesion severity. For example, additional imaging instrument(s) 142 can include one or more imaging instruments such as FFR angiography imaging instruments. Additional imaging instrument(s) 142 can capture and / or perform analysis of the entire coronary tree (including the RCA and LCA) at once by taking multiple images of the blood vessels. Such a procedure can be easier and faster than threading a pressure wire through each potential lesion area (such as traditional FFR and / or instantaneous wave-free ratio (IFR)).

[0121] System 100 can utilize imaging data 214 from other imaging instrument(s) 142 such as FFR angiography imaging instruments to generate 3D models for calculating FFR from angiography images. In some examples, system 100 can store such 3D models in 3D model(s) 232. In some examples, system 100 can use the imaging data and / or 3D models for calculating FFR to generate one or more of 3D model(s) 232 and / or procedural plan(s) 220 including a recommended graft origin, a recommended graft path, and a recommended graft termination. For example, system 100 can display a user interface 1000, e.g., on display device 110, which can include a representation of a 3D model for calculating FFR. User interface 1000 can be an example of a user interface of user interface(s) 218 Figure 2 ) of system 100. User interface 1000 can include a user-selectable button or icon 1002 that a clinician can select to invoke additional processing by system 100 to adjust (e.g., optimize) the 3D model for use by system 100 in generating procedural plan(s) 220 for graft placement.

[0122] Figure 11is a conceptual diagram illustrating content of another example surgical plan according to one or more aspects of the present disclosure. This additional processing step can take only a few minutes, which can be initiated by a clinician at any time, such as during the transition from diagnosis to surgical intervention, during a follow-up examination, etc. In some examples, this additional processing step can be initiated by a structural heart surgeon rather than an interventional cardiologist because the patient is transitioning from diagnosis to surgical intervention and / or is using already captured images (e.g., imaging data 214) rather than obtaining more images (such as CCTA images) from imager 140 to perform surgical preparation.

[0123] In some examples, this process can also be performed during a follow-up visit if the lesion finding is not severe enough to require CABG on the day of discovery, as imaging data 214 can already be stored within system 100. In this case, system 100 can capture additional images (such as CCTA images) from imager 140 and / or additional imager(s) 142 as needed to obtain additional data that can be used to generate or alter any of 3D model(s) 232 and / or surgical plan(s) 220.

[0124] In some examples, site information acquisition can not be available, for example, if only coronary angiography imaging data is used. However, the generated surgical plan(s) 220 can still incorporate recommendations, such as lengths and diameters of harvested vessels, to assist a clinician in determining a harvest site, such as recommendation 1100 for a harvested vessel 1102 to use as a bypass vessel. Additional information can be included in surgical plan(s) 220, such as placement locations in diseased arteries and placement of the aorta. For example, surgical plan(s) 220 can include a recommended graft origin, a recommended graft path, and a recommended graft termination, regardless of whether imaging data 214 includes CCTA imaging data, FFR angiography imaging data, or other imaging data.

[0125] The techniques discussed herein can be used in any combination or alone.

[0126] The techniques described in this disclosure can be implemented, at least in part, in hardware, software, firmware or any combination thereof. For example, various aspects of the described techniques can be implemented within one or more processors or processing circuits, including one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or any other equivalent integrated or discrete logic circuitry, as well as any combinations of such components. The terms “controller,” “processor,” or “processing circuitry” can generally refer to any of the foregoing logic circuitry, alone or in combination, or any other equivalent electrical circuitry. A control unit comprising hardware can also perform one or more techniques of this disclosure. Such hardware, software, and firmware can be im plemented within the same device or within different devices to support the various operations and functions outlined herein. Additionally, any of the described units, circuits, or components can be implemented together or separately as discrete but interoperable logic devices. Depiction of different features as circuits or units is intended to highlight different functional aspects and does not necessarily imply that such circuits or units must be realized by separate hardware or software components. Rather, functionality associated with one or more circuits or units can be performed by the same hardware or software components or within different hardware or software components.

[0127] The techniques described in this disclosure can also be embedded in or encoded in a computer-readable medium, such as a computer-readable storage medium containing instructions. Instructions embedded or encoded in a computer-readable storage medium can cause a programmable processor, or other processor, to perform the methods, e.g., when the instructions are executed. Computer-readable storage media can include random access memory (RAM), read only memory (ROM), programmable read only memory (PROM), erasable programmable read only memory (EPROM), or electrically erasable programmable read only memory (EEPROM), or other computer-readable media.

[0128] This disclosure includes the following non-limiting examples.

[0129] Example 1. A medical system comprising: a memory configured to store a surgical plan for a coronary artery bypass graft (CABG) procedure; and processing circuitry communicatively coupled to the memory, the processing circuitry configured to: obtain input data, the input data comprising imaging data of a vasculature of a patient; determine the surgical plan based on the input data, the surgical plan comprising at least one recommended graft location, the recommended graft location comprising a recommended graft origin, a recommended graft path, and a recommended graft termination; and output the surgical plan for display.

[0130] Example 2. The medical system of Example 1, wherein the at least one recommended graft location comprises a recommended graft location for a proximal anastomosis.

[0131] Example 3. The medical system of Example 1 or 2, wherein the at least one recommended graft location comprises a recommended graft location for a distal anastomosis distal to a coronary artery blockage.

[0132] Example 4. The medical system of any of Examples 1-3, wherein the recommended graft path comprises a path between the recommended graft origin and the recommended graft terminus, the recommended graft path configured to avoid any obstacles between the recommended graft origin and the recommended graft terminus.

[0133] Example 5. The medical system of any of Examples 1-4, wherein the surgical plan further comprises at least one recommended vessel edge condition to be used for a grafting.

[0134] Example 6. The medical system of Example 5, wherein the at least one recommended vessel edge condition comprises at least one cut angle.

[0135] Example 7. The medical system of any of Examples 1-6, wherein the processing circuitry is further configured to determine one or more recommended harvested vessel segment lengths based at least in part on the at least one recommended graft location, and wherein the surgical plan further comprises the one or more recommended harvested vessel segment lengths.

[0136] Example 8. The medical system of Example 7, wherein the processing circuitry is further configured to determine at least one recommended harvested vessel segment based at least in part on the one or more recommended harvested vessel segment lengths and a recommended harvested vessel anatomy, and wherein the surgical plan further comprises a harvesting plan comprising an identification of the at least one recommended harvested vessel segment.

[0137] Example 9. The medical system of Example 8, wherein the recommended harvested vessel anatomy comprises a recommended harvested vessel diameter, the recommended harvested vessel diameter based on a diameter of an obstructed vessel.

[0138] Example 10. The medical system of any of Examples 1-9, wherein the processing circuitry is further configured to: obtain a user input associated with the surgical plan; modify the surgical plan based on the user input to generate a modified surgical plan; and output the modified surgical plan for display.

[0139] Example 11. The medical system of any of examples 1 to 10, wherein the imaging data comprises coronary computed tomography angiography (CCTA) imaging data.

[0140] Example 12. The medical system of any of examples 1 to 11, wherein the imaging data comprises angiography imaging data.

[0141] Example 13. The medical system of any of examples 1 to 12, wherein the imaging data comprises fractional flow reserve (FFR) angiography imaging data.

[0142] Example 14. The medical system of any of examples 1 to 13, wherein, as part of determining the procedure plan, the processing circuitry is configured to determine a three-dimensional model based on the input data.

[0143] Example 15. The medical system of any of examples 1 to 14, wherein the imaging data comprises at least one of imaging data of at least one occluded blood vessel or imaging data of at least one potential harvest blood vessel.

[0144] Example 16. The medical system of any of examples 1 to 15, wherein the input data further comprises at least one of: information related to at least one potential harvest blood vessel, a measured or estimated value of coronary perfusion pressure (CPP), or an indication of whether the CABG procedure is a robotically assisted procedure.

[0145] Example 17. The medical system of any of examples 1 to 16, wherein the processing circuitry is further configured to determine at least one of: an estimate of saphenous vein graft (SVG) support, one or more recommendations for partitioning an internal mammary artery (IMA) graft from a chest wall, or one or more recommendations for a robotically assisted surgical procedure method, and wherein the procedure plan further comprises at least one of: the estimate of SVG support, the one or more recommendations for partitioning the IMA graft from the chest wall, or the one or more recommendations for the robotically assisted surgical procedure method.

[0146] Example 18. The medical system of any of examples 1 to 17, wherein the processing circuitry is further configured to determine an estimate of blood flow restoration based on at least one of the recommendations, and wherein at least one of the procedure plan further comprises a representation of the blood flow restoration estimate.

[0147] Example 19. The medical system of any of examples 1 to 18, wherein the processing circuitry is further configured to determine at least one of: a recommended robotic positioning, at least one recommended access location on the patient, or at least one target output for robotic anastomosis, and wherein the procedure plan comprises at least one of: the recommended robotic positioning, the at least one recommended access location on the patient, or the at least one target output for robotic anastomosis.

[0148] Example 20. A method comprising: obtaining, by processing circuitry, input data comprising imaging data of a vasculature of a patient; determining, by the processing circuitry, a procedure plan based on the input data, the procedure plan comprising at least one recommended graft location, the recommended graft location comprising a recommended graft origin, a recommended graft path, and a recommended graft destination; and outputting, by the processing circuitry, the procedure plan for display.

[0149] Example 21. The method of example 20, wherein the at least one recommended graft location comprises a recommended graft location for a proximal aortic anastomosis.

[0150] Example 22. The method of example 20 or 21, wherein the at least one recommended graft location comprises a recommended graft location for a distal anastomosis distal to a coronary artery blockage.

[0151] Example 23. The method of any of examples 20 to 22, wherein the recommended graft path comprises a path between the recommended graft origin and the recommended graft destination, the recommended graft path configured to avoid any obstacles between the recommended graft origin and the recommended graft destination.

[0152] Example 24. The method of any of examples 20 to 23, wherein the procedure plan further comprises at least one recommended vessel edge condition to be used for a grafting vessel.

[0153] Example 25. The method of example 24, wherein the at least one vessel edge condition comprises at least one cutting angle.

[0154] Example 26. The method of any of examples 20 to 25, further comprising determining, by the processing circuitry, one or more recommended harvested vessel segment lengths based at least in part on the at least one recommended graft location, and wherein the procedure plan further comprises the one or more recommended harvested vessel segment lengths.

[0155] Example 27. The method of example 26, further comprising determining, by the processing circuitry, at least one recommended harvest vessel segment, the at least one recommended harvest vessel segment based at least in part on the one or more recommended harvest vessel segment lengths and a recommended harvest vessel anatomy, and wherein the surgical plan further comprises a harvest plan comprising an identification of the at least one recommended harvest vessel segment.

[0156] Example 28. The method of example 27, wherein the recommended harvest vessel anatomy comprises a recommended harvest vessel diameter, the recommended harvest vessel diameter based on a diameter of an obstructed vessel.

[0157] Example 29. The method of any one of examples 20 to 28, further comprising: obtaining, by the processing circuitry, user input associated with the surgical plan; modifying, by the processing circuitry, the surgical plan based on the user input to generate a modified surgical plan; and outputting, by the processing circuitry, the modified surgical plan for display.

[0158] Example 30. The method of any one of examples 20 to 29, wherein the imaging data comprises coronary computed tomography angiography (CCTA) imaging data.

[0159] Example 31. The method of any one of examples 20 to 30, wherein the imaging data comprises angiography imaging data.

[0160] Example 32. The method of any one of examples 20 to 31, wherein the imaging data comprises fractional flow reserve (FFR) angiography imaging data.

[0161] Example 33. The method of any one of examples 20 to 32, wherein determining the surgical plan comprises determining a three-dimensional model based on the input data.

[0162] Example 34. The method of any one of examples 20 to 33, wherein the imaging data comprises at least one of imaging data of at least one obstructed vessel or imaging data of at least one potential harvest vessel.

[0163] Example 35. The method of any one of examples 20 to 34, wherein the input data further comprises at least one of: information related to at least one potential harvest vessel, a measured or estimated value of coronary perfusion pressure (CPP), or an indication of whether a CABG surgery is a robotically assisted surgery.

[0164] Example 36. The method of any of examples 20 to 35, further comprising determining, by the processing circuitry, at least one of: an estimate of saphenous vein graft (SVG) support, one or more recommendations to dissect an internal mammary artery (IMA) graft from a chest wall, or one or more recommendations for a robotic assisted surgical procedure, and wherein the surgical plan further comprises at least one of: the estimate of SVG support, the one or more recommendations to dissect the IMA graft from the chest wall, or the one or more recommendations for the robotic assisted surgical procedure.

[0165] Example 37. The method of any of examples 20 to 36, further comprising determining, by the processing circuitry, an estimate of blood flow restoration based on at least one of the recommendations, and wherein at least one of the surgical plan further comprises a representation of the blood flow restoration estimate.

[0166] Example 38. The method of any of examples 20 to 37, further comprising determining, by the processing circuitry, at least one of: a recommended robotic positioning, at least one recommended entry location on the patient, or at least one target output for robotic anastomosis, and wherein the surgical plan comprises at least one of: the recommended robotic positioning, the at least one recommended entry location on the patient, or the at least one target output for robotic anastomosis.

[0167] Example 39. A non-transitory computer-readable storage medium storing instructions that, when executed, cause processing circuitry to: obtain input data, the input data comprising imaging data of a vasculature of a patient; determine, based on the input data, a surgical plan, the surgical plan comprising at least one recommended graft location, the recommended graft location comprising a recommended graft origin, a recommended graft path, and a recommended graft termination; and output the surgical plan for display.

[0168] Various different examples have been described. These and other examples fall within the scope of the following claims.

Claims

1. A medical system comprising: a memory configured to store a surgical plan for a coronary artery bypass graft (CABG) surgery; as well as processing circuitry communicatively coupled to the memory, the processing circuitry configured to: obtaining input data comprising imaging data of a patient's vasculature; determining the surgical plan based on the input data, the surgical plan comprising at least one recommended graft position, the recommended graft position comprising a recommended graft starting point, a recommended graft path, and a recommended graft endpoint; as well as The surgical plan is output for display.

2. The medical system according to claim 1, wherein: The at least one recommended graft position includes a recommended graft position for a proximal aortic anastomosis.

3. The medical system according to claim 1 or 2, wherein: The at least one recommended graft position includes a recommended graft position for distal anastomosis distal to the coronary artery occlusion.

4. The medical system according to any one of claims 1 to 3, wherein: The recommended graft path includes a path between the recommended graft start point and the recommended graft end point, the recommended graft path being configured to avoid any obstacles between the recommended graft start point and the recommended graft end point.

5. The medical system according to any one of claims 1 to 4, wherein: The surgical plan further includes at least one recommended vessel edge condition of the blood vessel to be used for the graft.

6. The medical system of claim 5, wherein: The at least one recommended blood vessel edge condition includes at least one cutting angle.

7. The medical system according to any one of claims 1 to 6, wherein: The processing circuitry is further configured to determine one or more recommended harvesting vessel segment lengths based at least in part on the at least one recommended graft position, and wherein the surgical plan further includes the one or more recommended harvesting vessel segment lengths.

8. The medical system of claim 7, wherein: The processing circuitry is further configured to determine at least one recommended harvesting vessel segment based at least in part on the one or more recommended harvesting vessel segment lengths and the recommended harvesting vessel anatomy, and wherein the surgical plan further comprises a harvesting plan including identification of the at least one recommended harvesting vessel segment.

9. The medical system of claim 8, wherein: The recommended harvesting vessel anatomy includes a recommended harvesting vessel diameter based on a diameter of the obstructed vessel.

10. The medical system according to any one of claims 1 to 9, wherein: The processing circuitry is further configured to: obtaining user input associated with the surgical plan; modifying the surgical plan based on the user input to generate a modified surgical plan; and The modified surgical plan is output for display.

11. The medical system according to any one of claims 1 to 10, wherein: The imaging data includes at least one of coronary computed tomography angiography (CCTA) imaging data, angiography imaging date, or fractional flow reserve (FFR) angiography imaging data.

12. The medical system according to any one of claims 1 to 11, wherein: The imaging data includes at least one of imaging data of at least one occluded blood vessel or imaging data of at least one potential acquisition blood vessel.

13. The medical system according to any one of claims 1 to 12, wherein: The input data further includes at least one of information related to at least one potential harvest vessel, a measurement or estimate of coronary perfusion pressure (CPP), or an indication of whether the CABG procedure is a robotic-assisted procedure.

14. The medical system according to any one of claims 1 to 13, wherein: The processing circuit system is further configured to determine at least one of: an estimate of saphenous vein graft (SVG) support, one or more recommendations for segmenting an internal mammary artery (IMA) graft from the chest wall, or one or more recommendations for a robotic-assisted surgical approach, and wherein the surgical plan further includes at least one of: the estimate of SVG support, the one or more recommendations for segmenting the IMA graft from the chest wall, or the one or more recommendations for the robotic-assisted surgical approach.

15. A method comprising: obtaining, by processing circuitry, input data comprising imaging data of a patient's vasculature; determining, by the processing circuitry, a surgical plan based on the input data, the surgical plan comprising at least one recommended graft position, the recommended graft position comprising a recommended graft starting point, a recommended graft path, and a recommended graft endpoint; as well as The surgical plan is output by the processing circuit system for display.

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