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公开(公告)号:US20240252234A1
公开(公告)日:2024-08-01
申请号:US17246768
申请日:2021-05-03
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor: Alon RAZON , Yotam REISNER , Yael PISTONOVICH , Alisa KOMLEVA , Asi ELAD , Gal SHLEIFER , Yehonatan BEN DAVID , Zalman IBRAGIMOV
CPC classification number: A61B18/1492 , A61B18/1206 , G06N20/00 , A61B2018/0072 , A61B2018/0075 , A61B2018/00755 , A61B2018/00761 , A61B2018/00767 , A61B2018/1467 , A61B2560/0487
Abstract: A controller, system and method for determining whether an ablation performed by an ablation catheter creates a lesion having a depth reaching or exceeding a predetermined depth, e.g. whether the lesion is transmural. The system comprises an ablation catheter with at least two electrodes for performing an ablation on tissue. One of the electrodes is an ablation electrode and the other electrode or electrodes are reference electrodes. A processor is used to determine, e.g. in real time, whether the depth of the lesion resulting from the ablation has reached or exceeded the predetermined depth based on ablation-dependent variables. The ablation-dependent variables may comprise an electrical signal received by the ablation electrode and one or more impedance values between the electrodes. A machine learning algorithm can thus be used to classify the tissue which is being ablated. The inputs, i.e. the input data, of the machine learning algorithm are features derived from the ablation-dependent variables, wherein the features correlate with the depth of a lesion resulting from the ablation. The machine learning algorithm is adapted to output, in real time, a classification comprising an indication whether or not a depth of the lesion resulting from the ablation reaches or exceeds a predetermined depth.