Aghababaie Zahra, Jamart Kevin, Chan Chih-Hsiang Alexander, Amirapu Satya, Cheng Leo K, Paskaranandavadivel Niranchan, Avci Recep, Angeli Timothy R
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:1436-1439. doi: 10.1109/EMBC44109.2020.9176220.
Gastric motility disorders are associated with bioelectrical abnormalities in the stomach. Recently, gastric ablation has emerged as a potential therapy to correct gastric dysrhythmias. However, the tissue-level effects of gastric ablation have not yet been evaluated. In this study, radiofrequency ablation was performed in vivo in pigs (n=7) at temperature-control mode (55-80°C, 5-10 s per point). The tissue was excised from the ablation site and routine H&E staining protocol was performed. In order to assess tissue damage, we developed an automated technique using a fully convolutional neural network to segment healthy tissue and ablated lesion sites within the muscle and mucosa layers of the stomach. The tissue segmentation achieved an overall Dice score accuracy of 96.18 ± 1.0 %, and Jacquard score of 92.77 ± 1.9 %, after 5-fold cross validation. The ablation lesion was detected with an overall Dice score of 94.16 ± 0.2 %. This method can be used in combination with high-resolution electrical mapping to define the optimal ablation dose for gastric ablation.Clinical Relevance-This work presents an automated method to quantify the ablation lesion in the stomach, which can be applied to determine optimal energy doses for gastric ablation, to enable clinical translation of this promising emerging therapy.
胃动力障碍与胃生物电异常有关。最近，胃消融已成为一种纠正胃节律失常的潜在疗法。然而，胃消融的组织水平效应尚未得到评估。在本研究中，对7头猪进行了体内射频消融，采用温度控制模式（55 - 80°C，每点5 - 10秒）。从消融部位切除组织并进行常规苏木精-伊红染色。为了评估组织损伤，我们开发了一种自动化技术，使用全卷积神经网络对胃肌肉层和粘膜层内的健康组织和消融病变部位进行分割。经过5折交叉验证后，组织分割的总体骰子系数准确率为96.18±1.0%，杰卡德系数为92.77±1.9%。检测到的消融病变总体骰子系数为94.16±0.2%。该方法可与高分辨率电标测结合使用，以确定胃消融的最佳消融剂量。临床意义——这项工作提出了一种自动化方法来量化胃内的消融病变，可用于确定胃消融的最佳能量剂量，以推动这种有前景的新兴疗法的临床转化。
