System and Method for Suggesting Catheter Parameters

A vasculature assessment system, comprising:

• a plurality of the vasculature assessment devices, each vasculature assessment device comprising:
• an imaging probe configured to acquire raw image data of a blood vessel of a patient;
• and
• a device module having a console coupled with the imaging probe, the console including a processor and a memory having logic stored thereon that, when executed by the processor performs operations that include:
• receiving the raw image data from the imaging probe;
• determining blood vessel data from the raw image data;
• applying a trained machine learning (ML) model to the blood vessel data to determine suggested catheter parameters pertaining to catheter to be inserted within the blood vessel;
• and
• depicting the suggested catheter parameters on a display of the device module;
• and
• a computing system coupled with the vasculature assessment devices, the computing system including memory having ML logic stored thereon that, when executed by processors, performs ML operations that include performing a ML algorithm on historical catheter placement data sets to define the trained ML model, wherein the historical catheter placement data sets include:
• blood vessel data sets received from the vasculature assessment devices;
• and
• actual catheter parameter data sets,
• wherein each actual catheter parameter data set corresponds to a blood vessel data set in a one to one relationship.

A system method of determining suggested catheter parameters, comprising:

• receiving a plurality of blood vessel data sets from a plurality of vasculature assessment devices;
• receiving a plurality of actual catheter parameter data sets from an electronic medical record (EMR) system, each catheter parameter data set corresponding to a blood vessel data set;
• performing a machine learning (ML) algorithm on the blood vessel data sets and the actual catheter parameter data sets to train a ML model that relates the blood vessel data sets to the actual catheter parameter data sets;
• acquiring raw image data of a blood vessel from an instant patient utilizing one of the vasculature assessment devices;
• determining instant blood vessel data from the raw image data;
• applying the (ML) model to the instant blood vessel data to determine suggested catheter parameters for a catheter to be inserted within the blood vessel;
• and
• depicting the suggested catheter parameters on a display of the one of the vasculature assessment devices.