Jacobian-Based Iterative Method for Magnetic Localization in Robotic Capsule Endoscopy.

The purpose of this study is to validate a Jacobian-based iterative method for real-time localization of magnetically controlled endoscopic capsules. The proposed approach applies finite-element solutions to the magnetic field problem and least-squares interpolations to obtain closed-form and fast estimates of the magnetic field. By defining a closed-form expression for the Jacobian of the magnetic field relative to changes in the capsule pose, we are able to obtain an iterative localization at a faster computational time when compared with prior works, without suffering from the inaccuracies stemming from dipole assumptions. This new algorithm can be used in conjunction with an absolute localization technique that provides initialization values at a slower refresh rate. The proposed approach was assessed via simulation and experimental trials, adopting a wireless capsule equipped with a permanent magnet, six magnetic field sensors, and an inertial measurement unit. The overall refresh rate, including sensor data acquisition and wireless communication was 7 ms, thus enabling closed-loop control strategies for magnetic manipulation running faster than 100 Hz. The average localization error, expressed in cylindrical coordinates was below 7 mm in both the radial and axial components and 5° in the azimuthal component. The average error for the capsule orientation angles, obtained by fusing gyroscope and inclinometer measurements, was below 5°.

In-silico pre-clinical trials for implantable cardioverter defibrillators.

Regulatory authorities require that the safety and efficacy of a new high-risk medical device be proven in a Clinical Trial (CT), in which the effects of the device on a group of patients are compared to the effects of the current standard of care. Phase III trials can run for several years, cost millions of dollars, and expose patients to an unproven device. In this paper, we demonstrate how to use a large group of synthetic patients based on computer modeling to improve the planning of a CT so as to increase the chances of a successful trial for implantable cardioverter defibrillators (ICDs). We developed a computer model of the electrical generation and propagation in the heart. This model was used to generate a large group of heart instances capable of producing episodes of 19 different arrhythmias. We also implemented two arrhythmia detection algorithms from the literature: Rhythm ID from Boston Scientific and PR Logic + Wavelet from Medtronic. Using this setup, we conducted multiple in-silico trials to compare the ability of the two algorithms to appropriately discriminate between potentially fatal Ventricular Tachy-arrhythmias (VT) and nonfatal Supra-Ventricular Tachy-arrhythmias (SVTs). The results of our in-silico trial indicate that Rhythm ID was less able to discriminate between SVT and VT and so may lead to more cases of inappropriate therapy. This corroborates the findings of the Rhythm ID Going Head to Head Trial (RIGHT), a clinical trial that compared the two algorithms in patients. We further demonstrated that the result continues to hold if we vary the distribution of arrhythmias in the synthetic population. We also used the same in-silico cohort to explore the sensitivity of the outcome to different parameter settings of the device algorithms, which is not feasible in a real clinical trial. In-silico trials can provide early insight into the factors which affect the outcome of a CT at a fraction of the cost and duration and without the ethical issues.

A platform for gastric cancer screening in low- and middle-income countries.

Gastric cancer is the second leading cause of cancer death worldwide and screening programs have had a significant impact on reducing mortality. The majority of cases occur in low- and middle-income countries (LMIC), where endoscopy resources are traditionally limited. In this paper, we introduce a platform designed to enable inexpensive gastric screening to take place in remote areas of LMIC. The system consists of a swallowable endoscopic capsule connected to an external water distribution system by a multichannel soft tether. Pressurized water is ejected from the capsule to orient the view of the endoscopic camera. After completion of a cancer screening procedure, the outer shell of the capsule and the soft tether can be disposed, while the endoscopic camera is reclaimed without needing further reprocessing. The capsule, measuring 12 mm in diameter and 28 mm in length, is able to visualize the inside of the gastric cavity by combining waterjet actuation and the adjustment of the tether length. Experimental assessment was accomplished through a set of bench trials, ex vivo analysis, and in vivo feasibility validation. During the ex vivo trials, the platform was able to visualize the main landmarks that are typically observed during a gastric cancer screening procedure in less than 8 min. Given the compact footprint, the minimal cost of the disposable parts, and the possibility of running on relatively available and inexpensive resources, the proposed platform can potentially widen gastric cancer screening programs in LMIC.

Wireless tissue palpation for intraoperative detection of lumps in the soft tissue.

In an open surgery, identification of precise margins for curative tissue resection is performed by manual palpation. This is not the case for minimally invasive and robotic procedures, where tactile feedback is either distorted or not available. In this paper, we introduce the concept of intraoperative wireless tissue palpation. The wireless palpation probe (WPP) is a cylindrical device (15 mm in diameter, 60 mm in length) that can be deployed through a trocar incision and directly controlled by the surgeon to create a volumetric stiffness distribution map of the region of interest. This map can then be used to guide the tissue resection to minimize healthy tissue loss. The wireless operation prevents the need for a dedicated port and reduces the chance of instrument clashing in the operating field. The WPP is able to measure in real time the indentation pressure with a sensitivity of 34 Pa, the indentation depth with an accuracy of 0.68 mm, and the probe position with a maximum error of 11.3 mm in a tridimensional workspace. The WPP was assessed on the benchtop in detecting the local stiffness of two different silicone tissue simulators (elastic modulus ranging from 45 to 220 kPa), showing a maximum relative error below 5%. Then, in vivo trials were aimed to identify an agar-gel lump injected into a porcine liver and to assess the device usability within the frame of a laparoscopic procedure. The stiffness map created intraoperatively by the WPP was compared with a map generated ex vivo by a standard uniaxial material tester, showing less than 8% local stiffness error at the site of the lump.