Abstract:
In part, the invention relates to a method for sizing a stent for placement in a vessel. In one embodiment, the method includes the steps of: dividing the vessel into a plurality of segments, each segment being defined as the space between branches of the vessel; selecting a starting point that appears to have substantially no disease; defining the diameter at this point to be the maximum diameter; calculating the maximal diameter of the next adjacent segment according to a power law; measuring the actual diameter of the next adjacent segment; selecting either the calculated maximum diameter or the measured maximum diameter depending upon which diameter is larger; using the selected maximum diameter to find the maximum diameter of this next segment; iteratively proceeding until the entire length of the vessel is examined; and selecting a stent in response to the diameters of the end proximal and distal segments.
Abstract:
The present disclosure provides systems and methods for dynamically visualizing the delivery of a device within a vessel by correlating at least one first extraluminal image with second extraluminal images. The extraluminal images may be correlated based on motion features, without the use of other sensors or timestamps. The first extraluminal image may be a high dose contrast x-ray angiogram (“XA”) and the second extraluminal images may be low dose contrast XAs. The high dose contrast XA may be used to generate a vessel map. The low dose contrast XAs may be taken during the delivery of a device, such as a balloon, stent, probe, or the like. Correlating the high dose XA and low dose XA based on motion features allows for the vessel map to be overlaid on the low dose XA to provide the physician visualization of where the device is within the vessel tree in real time.
Abstract:
In part, the disclosure relates to methods, and systems suitable for evaluating image data from a patient on a real time or substantially real time basis using machine learning (ML) methods and systems. Systems and methods for improving diagnostic tools for end users such as cardiologists and imaging specialists using machine learning techniques applied to specific problems associated with intravascular images that have polar representations. Further, given the use of rotating probes to obtain image data for OCT, IVUS, and other imaging data, dealing with the two coordinate systems associated therewith creates challenges. The present disclosure addresses these and numerous other challenges relating to solving the problem of quickly imaging and diagnosis a patient such that stenting and other procedures may be applied during a single session in the cath lab.
Abstract:
In part, the disclosure relates to method of displaying a representation of an artery. The method may include storing an intravascular image dataset in a memory device of a diagnostic imaging system, the intravascular image dataset generated in response to intravascular imaging of a segment of an artery; automatically detecting lumen boundary of the segment on a per frame basis; automatically detecting EEL and displaying a stent sizing workflow. In part, the disclosure also relates to automatically detecting one or more regions of calcium relative to lumen boundary of the segment; calculating an angular or circumferential measurement of detected calcium for one or more frames; calculating a calcium thickness of detected calcium for one or more frames; and displaying the calcium thickness and the angular or circumferential measurement of detected calcium for a first frame of the one or more frames.
Abstract:
The present disclosure provides systems and methods to receiving OCT or IVUS image data frames to output one or more representations of a blood vessel segment. The image data frames may be stretched and/or aligned using various windows or bins or alignment features. Arterial features, such as the calcium burden, may be detected in each of the image data frames. The arterial features may be scored. The score may be a stent under-expansion risk. The representation may include an indication of the arterial features and their respective score. The indication may be a color coded indication.
Abstract:
In part, the disclosure relates to determining a stent deployment location and other parameters using blood vessel data. Stent deployment can be planned such that the amount of blood flow restored from stenting relative to an unstented vessel increases one or more metrics. An end user can specify one or more stent lengths, including a range of stent lengths. In turn, diagnostic tools can generate candidate virtual stents having lengths within the specified range suitable for placement relative to a vessel representation. Blood vessel distance values such as blood vessel diameter, radius, area values, chord values, or other cross-sectional, etc. its length are used to identify stent landing zones. These tools can use or supplement angiography data and/or be co-registered therewith. Optical imaging, ultrasound, angiography or other imaging modalities are used to generate the blood vessel data.
Abstract:
In part, the disclosure relates to method of displaying a representation of an artery. The method may include storing an intravascular image dataset in a memory device of a diagnostic imaging system, the intravascular image dataset generated in response to intravascular imaging of a segment of an artery; automatically detecting lumen boundary of the segment on a per frame basis; automatically detecting EEL and displaying a stent sizing workflow. In part, the disclosure also relates to automatically detecting one or more regions of calcium relative to lumen boundary of the segment; calculating an angular or circumferential measurement of detected calcium for one or more frames; calculating a calcium thickness of detected calcium for one or more frames; and displaying the calcium thickness and the angular or circumferential measurement of detected calcium for a first frame of the one or more frames.
Abstract:
In part, the disclosure relates to methods, and systems suitable for evaluating image data from a patient on a real time or substantially real time basis using machine learning (ML) methods and systems. Systems and methods for improving diagnostic tools for end users such as cardiologists and imaging specialists using machine learning techniques applied to specific problems associated with intravascular images that have polar representations. Further, given the use of rotating probes to obtain image data for OCT, IVUS, and other imaging data, dealing with the two coordinate systems associated therewith creates challenges. The present disclosure addresses these and numerous other challenges relating to solving the problem of quickly imaging and diagnosis a patient such that stenting and other procedures may be applied during a single session in the cath lab.
Abstract:
The present disclosure provides systems and methods to receiving OCT or IVUS image data frames to output one or more representations of a blood vessel segment. The image data frames may be stretched and/or aligned using various windows or bins or alignment features. Arterial features, such as the calcium burden, may be detected in each of the image data frames. The arterial features may be scored. The score may be a stent under-expansion risk. The representation may include an indication of the arterial features and their respective score. The indication may be a color coded indication.
Abstract:
In part, the disclosure relates to intravascular data collection systems and the software-based visualization and display of intravascular data relating to detected side branches and side branch obstruction. An estimate of side branch diameter can be made based on a vessel profile or a maximum diameter of a vessel at a distal and proximal location relative to the side branch. A amount of side branch obstruction may be determined by comparing an observed side branch diameter with in the image data with the estimated side branch diameter. In addition, an amount of blood flow obstruction may also be determined.