Methods and systems for predicting sensitivity of blood flow calculations to changes in anatomical geometry

摘要

Embodiments include methods and systems and for determining a sensitivity of a patient's blood flow characteristic to anatomical or geometrical uncertainty. For each of one or more of individuals, a sensitivity of a blood flow characteristic may be obtained for one or more uncertain parameters. An algorithm may be trained based on the sensitivities of the blood flow characteristic and one or more of the uncertain parameters for each of the plurality of individuals. A geometric model, a blood flow characteristic, and one or more of the uncertain parameters of at least part of the patient's vascular system may be obtained for a patient. The sensitivity of the patient's blood flow characteristic to one or more of the uncertain parameters may be calculated by executing the algorithm on the blood flow characteristic of at least part of the patient's vascular system, and one or more of the uncertain parameters.

主权项

1. A computer-implemented method of determining a sensitivity of a patient's blood flow characteristic to uncertainty in one or more anatomical or geometrical features of the patient, the method comprising:
obtaining, for each of a plurality of individuals, a geometric model of at least a portion of a vascular system of each individual; identifying a plurality of vessel regions in each geometric model; determining, for each geometric model, at least one sensitivity of a blood flow characteristic to at least one uncertainty in geometry in one or more of the identified plurality of vessel regions; associating each of the one or more vessel regions with a determined sensitivity; using the determined sensitivities and associated one or more vessel regions in a machine learning algorithm to construct a machine learning predictor for calculating sensitivities of blood flow characteristics to uncertainties; generating, for a patient, a geometric model of at least part of the patient's vascular system using patient-specific imaging data of at least a portion of the patient's vascular system; determining, for the patient, a designation of a blood flow characteristic, and at least one value of uncertainty in the geometry of at least part of the patient's vascular system; identifying a vessel region of interest in the geometric model generated for the patient; and determining a sensitivity of the blood flow characteristic of the patient to the at least one value of uncertainty in the patient's vascular geometry for at least the vessel region of interest in the patient's geometric model, using the machine learning predictor.