Enhancement of instrumented ultrasonic tracking images using deep learning.

PURPOSE: Instrumented ultrasonic tracking provides needle localisation during ultrasound-guided minimally invasive percutaneous procedures. Here, a post-processing framework based on a convolutional neural network (CNN) is proposed to improve the spatial resolution of ultrasonic tracking images. METHODS: The custom ultrasonic tracking system comprised a needle with an integrated fibre-optic ultrasound (US) transmitter and a clinical US probe for receiving those transmissions and for acquiring B-mode US images. For post-processing of tracking images reconstructed from the received fibre-optic US transmissions, a recently-developed framework based on ResNet architecture, trained with a purely synthetic dataset, was employed. A preliminary evaluation of this framework was performed with data acquired from needle insertions in the heart of a fetal sheep in vivo. The axial and lateral spatial resolution of the tracking images were used as performance metrics of the trained network. RESULTS: Application of the CNN yielded improvements in the spatial resolution of the tracking images. In three needle insertions, in which the tip depth ranged from 23.9 to 38.4 mm, the lateral resolution improved from 2.11 to 1.58 mm, and the axial resolution improved from 1.29 to 0.46 mm. CONCLUSION: The results provide strong indications of the potential of CNNs to improve the spatial resolution of ultrasonic tracking images and thereby to increase the accuracy of needle tip localisation. These improvements could have broad applicability and impact across multiple clinical fields, which could lead to improvements in procedural efficiency and reductions in risk of complications.

Correlation of Ultrasound Shear Wave Elastography with Pathological Analysis in a Xenografic Tumour Model.

The objective of this study was to evaluate the potential value of ultrasound (US) shear wave elastography (SWE) in assessing the relative change in elastic modulus in colorectal adenocarcinoma xenograft models in vivo and investigate any correlation with histological analysis. We sought to test whether non-invasive evaluation of tissue stiffness is indicative of pathological tumour changes and can be used to monitor therapeutic efficacy. US-SWE was performed in tumour xenografts in 15 NCr nude immunodeficient mice, which were treated with either the cytotoxic drug, Irinotecan, or saline as control. Ten tumours were imaged 48 hours post-treatment and five tumours were imaged for up to five times after treatment. All tumours were harvested for histological analysis and comparison with elasticity measurements. Elastic (Young's) modulus prior to treatment was correlated with tumour volume (r = 0.37, p = 0.008). Irinotecan administration caused significant delay in the tumour growth (p = 0.02) when compared to control, but no significant difference in elastic modulus was detected. Histological analysis revealed a significant correlation between tumour necrosis and elastic modulus (r = -0.73, p = 0.026). SWE measurement provided complimentary information to other imaging modalities and could indicate potential changes in the mechanical properties of tumours, which in turn could be related to the stages of tumour development.