Monitoring of thermal lesions in ultrasound using fully convolutional neural networks: A preclinical study.

Accurate monitoring of thermal ablation regions is an important guarantee for successful ablation treatment, which mainly depends on the subjective judgment of radiologists in current clinical practice. This work innovatively applied fully convolutional neural networks (FCNs) for detection and monitoring of thermal ablation regions in ultrasound (US) and comprehensively compared the performance of VGG16-FCN, U-Net, UNet++, Attention U-Net, MultiResUNet, and ResUNet, which have shown outstanding performance in medical image segmentation. The input of the models was US echo envelope data backscattered from the ablated regions. Excised porcine liver ablation dataset and clinical liver tumors ablation dataset were respectively used to evaluate the prediction ability of the models. With 1000 excised porcine liver ablation samples for training and 200 samples for testing, the UNet++ achieves both the highest Dice score (DSC) of 0.7824 ± 0.1098 and the best Hausdorff distance (HD) of 2.70 ± 1.38 mm. Additionally, considering potential clinical usage, we also tested the model generalizability by training on the excised dataset and testing on the clinical data, in which we obtained the performance with the highest DSC obtained by the ResUNet and the best HD by the UNet++. Our comparative study suggests that both UNet++ and ResUNet have relatively outstanding segmentation performance among all compared models, which are potential candidates for automatic segmentation of thermal ablation regions in US during clinical ablation treatment.

In vivo monitoring of microwave ablation in a porcine model using ultrasonic differential attenuation coefficient intercept imaging.

In this study, the feasibility of using ultrasonic differential attenuation coefficient intercept (Δα0) imaging to evaluate thermal lesions induced by microwave ablation (MWA) was explored using an in vivo porcine model. The attenuation coefficient intercept (Δα0 is estimated by subtracting an initial value of Δα0 images. Receiver operating characteristic (ROC) curves and the area under ROC curve (AUC) were employed to statistically assess the predictability of ultrasonic imaging. Ultrasonic Δα0 values were approximately 0.13 dB/cm and 0.16 dB/cm in a normal liver and kidney, respectively, increasing to 2.9 dB/cm and 2.55 dB/cm in ablated regions after MWA. The CNR values of the ultrasonic Δα0 images (0.9 dB and 0.6 dB in the liver and kidney, respectively) were significantly higher (p < 0.05) than the values of B-mode images (0.6 dB and 0.3 dB). The AUC value of the ultrasonic Δα0 image was higher than the B-mode image value, 0.95 compared with 0.88. This in vivo study suggests that ultrasonic Δα0 imaging has the potential to evaluate thermal lesions with high accuracy and better image contrast for monitoring MWA.

Feasibility of Using Ultrasonic Nakagami Imaging for Monitoring Microwave-Induced Thermal Lesion in Ex Vivo Porcine Liver.

The feasibility of using ultrasonic Nakagami imaging to evaluate thermal lesions induced by microwave ablation (MWA) in ex vivo porcine liver was explored. Dynamic changes in echo amplitudes and Nakagami parameters in the region of the MWA-induced thermal lesion, as well as the contrast-to-noise ratio (CNR) between the MWA-induced thermal lesion and the surrounding normal tissue, were calculated simultaneously during the MWA procedure. After MWA exposure, a bright hyper-echoic region appeared in ultrasonic B-mode and Nakagami parameter images as an indicator of the thermal lesion. Mean values of the Nakagami parameter in the thermal lesion region increased to 0.58, 0.71 and 0.91 after 1, 3 and 5 min of MVA. There were no significant differences in envelope amplitudes in the thermal lesion region among ultrasonic B-mode images obtained after different durations of MWA. Unlike ultrasonic B-mode images, Nakagami images were less affected by the shadow effect in monitoring of MWA exposure, and a fairly complete hyper-echoic region was observed in the Nakagami image. The mean value of the Nakagami parameter increased from approximately 0.47 to 0.82 during MWA exposure. At the end of the postablation stage, the mean value of the Nakagami parameter decreased to 0.55 and was higher than that before MWA exposure. CNR values calculated for Nakagami parameter images increased from 0.13 to approximately 0.61 during MWA and then decreased to 0.26 at the end of the post-ablation stage. The corresponding CNR values calculated for ultrasonic B-mode images were 0.24, 0.42 and 0.17. This preliminary study on ex vivo porcine liver suggested that Nakagami imaging have potential use in evaluating the formation of MWA-induced thermal lesions. Further in vivo studies are needed to evaluate the potential application.