LightLab Imaging, Inc.

Aspects of the disclosure provide for an x-ray detection device for detecting radiation scattered off of a target during an imaging procedure and generating temporal data indicating the time of occurrence of a pulse of radiation emitted towards the target. The temporal data can be sent to a host device and used to timestamp images generated from the pulses of radiation. The x-ray detection device is portable and can be installed in a catheterization laboratory or imaging environment to detect the occurrence of radiation, without occluding or partially occluding the beam source. Aspects of the disclosure also provide for a system for receiving temporal data generated by the x-ray detection device, and accurately tagging received image frames based on the temporal data.

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.

Aspects of the disclosure relate to the identification of when a blood vessel has been sufficiently cleared of blood so as to capture intravascular images of the vessel wall. The disclosed systems and methods allow for the identification of an initial and a final blood clearing based on the identification of edges within scanlines of a plurality of image frames. The edges of a plurality of scanlines may be analyzed to determine an average edge offset for each image frame, and the average edge offsets for a plurality of image frames may be averaged over various time-windows, so as to determine when the initial and final blood clearing events have occurred. Once a final blood clearing event has been identified, the disclosed system may automatically initiate a catheter pullback procedure, so as to capture intravascular images over a length of the vessel that has been sufficiently cleared of blood.

Aspects of the disclosure provide for automated self-inspection by an OCT imaging engine or device, to identify and resolve failures or inefficiencies in the hardware and/or software of the system or device during imaging. An OCT imaging engine can include a catheter connection check system for checking the quality of a physical connection point between a catheter and other components of an OCT imaging device or system. In some examples, the OCT imaging engine includes a self-inspection engine implemented to perform routine self-inspection by using a reference reflector internal to the OCT imaging engine to generate system performance data. The OCT imaging engine can use the system performance data to periodically search for and resolve failures or inefficiencies in the system. The OCT imaging engine can perform a self-calibration process to perform k-linearization and/or correct for chromatic dispersion using mirror measurements collected from an internal reference reflector.

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.

In one embodiment, the disclosure relates to a probe that a cylindrical marker band defining an inner surface, an outer surface, a first end and a second end and having a band length, the inner surface defining a marker band bore, the cylindrical marker band includes a radiopaque material; a molded unitary lens defining an elongate optical fiber receiving section having a fiber section length and a beam directing surface, wherein the fiber section length and the band length overlap along an overlap distance; and an optical fiber, wherein a first section of the optical fiber is disposed in the optical fiber receiving section, wherein a portion of the first section of the optical fiber is disposed within the marker band bore.

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.

A method and apparatus of automatically locating in an image of a blood vessel the lumen boundary at a position in the vessel and from that measuring the diameter of the vessel. From the diameter of the vessel and estimated blood flow rate, a number of clinically significant physiological parameters are then determined and various user displays of interest generated. One use of these images and parameters is to aid the clinician in the placement of a stent. The system, in one embodiment, uses these measurements to allow the clinician to simulate the placement of a stent and to determine the effect of the placement. In addition, from these patient parameters various patient treatments are then performed.

The disclosure relates generally to the field of vascular system and peripheral vascular system data collection, imaging, image processing and feature detection relating thereto. In part, the disclosure more specifically relates to methods for detecting position and size of contrast cloud in an x-ray image including with respect to a sequence of x-ray images during intravascular imaging. Methods of detecting and extracting metallic wires from x-ray images are also described herein such as guidewires used in coronary procedures. Further, methods for of registering vascular trees for one or more images, such as in sequences of x-ray images, are disclosed. In part, the disclosure relates to processing, tracking and registering angiography images and elements in such images. The registration can be performed relative to images from an intravascular imaging modality such as, for example, optical coherence tomography (OCT) or intravascular ultrasound (IVUS).