High Resolution Microultrasound (μUS) Investigation of the Gastrointestinal (GI) Tract

Review article: Current status and future directions of ingestible electronic devices in gastroenterology

BACKGROUND

Advances in microelectronics have greatly expanded the capabilities and clinical potential of ingestible electronic devices.

AIM

To provide an overview of the structure and potential impact of ingestible devices in development that are relevant to the gastrointestinal tract.

METHODS

We performed a detailed literature search to inform this narrative review.

RESULTS

Technical success of ingestible electronic devices relies on the ability to miniaturise the microelectronic circuits, sensors and components for interventional functions while being sufficiently powered to fulfil the intended function. These devices offer the advantages of being convenient and minimally invasive, with real-time assessment often possible and with minimal interference to normal physiology. Safety has not been a limitation, but defining and controlling device location in the gastrointestinal tract remains challenging. The success of capsule endoscopy has buoyed enthusiasm for the concepts, but few ingestible devices have reached clinical practice to date, partly due to the novelty of the information they provide and also due to the challenges of adding this novel technology to established clinical paradigms. Nonetheless, with ongoing technological advancement and as understanding of their potential impact emerges, acceptance of such technology will grow. These devices have the capacity to provide unique insight into gastrointestinal physiology and pathophysiology. Interventional functions, such as sampling of tissue or luminal contents and delivery of therapies, may further enhance their ability to sharpen gastroenterological diagnoses, monitoring and treatment.

CONCLUSIONS

The development of miniaturised ingestible microelectronic-based devices offers exciting prospects for enhancing gastroenterological research and the delivery of personalised, point-of-care medicine.

A Learning-Based Microultrasound System for the Detection of Inflammation of the Gastrointestinal Tract

Inflammation of the gastrointestinal (GI) tract accompanies several diseases, including Crohn's disease. Currently, video capsule endoscopy and deep bowel enteroscopy are the main means for direct visualisation of the bowel surface. However, the use of optical imaging limits visualisation to the luminal surface only, which makes early-stage diagnosis difficult. In this study, we propose a learning enabled microultrasound ( μ US) system that aims to classify inflamed and non-inflamed bowel tissues. μ US images of the caecum, small bowel and colon were obtained from mice treated with agents to induce inflammation. Those images were then used to train three deep learning networks and to provide a ground truth of inflammation status. The classification accuracy was evaluated using 10-fold evaluation and additional B-scan images. Our deep learning approach allowed robust differentiation between healthy tissue and tissue with early signs of inflammation that is not detectable by current endoscopic methods or by human inspection of the μ US images. The methods may be a foundation for future early GI disease diagnosis and enhanced management with computer-aided imaging.

Design and Simulation of a Ring-Shaped Linear Array for Microultrasound Capsule Endoscopy

Video capsule endoscopy (VCE) has significantly advanced visualization of the gastrointestinal tract since its introduction in the last 20 years. Work is now under way to combine VCE with microultrasound imaging. However, small maximum capsule dimensions, coupled with the electronics required to integrate ultrasound imaging capabilities, pose significant design challenges. This paper describes a simulation process for testing transducer geometries and imaging methodologies to achieve satisfactory imaging performance within the physical limitations of the capsule size and outlines many of the tradeoffs needed in the design of this new class of ultrasound capsule endoscopy (USCE) device. A hybrid MATLAB model is described, incorporating Krimholtz-Leedom-Matthaei circuit elements and digitizing and beamforming elements to render a gray-scale B-mode. This model is combined with a model of acoustic propagation to generate images of point scatterers. The models are used to demonstrate the performance of a USCE transducer configuration comprising a single, unfocused transmit ring of radius 5 mm separated into eight segments for electrical impedance control and a 512-element receive linear array, also formed into a ring. The MATLAB model includes an ultrasonic pulser circuit connected to a piezocrystal composite transmit transducer with a center frequency of 25 MHz. B-scan images are simulated for wire target phantoms, multilayered phantoms, and a gut wall model. To demonstrate the USCE system's ability to image tissue, a digital phantom was created from single-element ultrasonic transducer scans of porcine small bowel ex vivo obtained at a frequency of 45 MHz.

Ultrasound capsule endoscopy: sounding out the future

Video capsule endoscopy (VCE) has been of immense benefit in the diagnosis and management of gastrointestinal (GI) disorders since its introduction in 2001. However, it suffers from a number of well recognized deficiencies. Amongst these is the limited capability of white light imaging, which is restricted to analysis of the mucosal surface. Current capsule endoscopes are dependent on visual manifestation of disease and limited in regards to transmural imaging and detection of deeper pathology. Ultrasound capsule endoscopy (USCE) has the potential to overcome surface only imaging and provide transmural scans of the GI tract. The integration of high frequency microultrasound (µUS) into capsule endoscopy would allow high resolution transmural images and provide a means of both qualitative and quantitative assessment of the bowel wall. Quantitative ultrasound (QUS) can provide data in an objective and measurable manner, potentially reducing lengthy interpretation times by incorporation into an automated diagnostic process. The research described here is focused on the development of USCE and other complementary diagnostic and therapeutic modalities. Presently investigations have entered a preclinical phase with laboratory investigations running concurrently.