Endoscope field of view measurement.

The current International Organization for Standardization (ISO) standard (ISO 8600-3: 1997 including Amendment 1: 2003) for determining endoscope field of view (FOV) does not accurately characterize some novel endoscopic technologies such as endoscopes with a close focus distance and capsule endoscopes. We evaluated the endoscope FOV measurement method (the FOVWS method) in the current ISO 8600-3 standard and proposed a new method (the FOVEP method). We compared the two methods by measuring the FOV of 18 models of endoscopes (one device for each model) from seven key international manufacturers. We also estimated the device to device variation of two models of colonoscopes by measuring several hundreds of devices. Our results showed that the FOVEP method was more accurate than the FOVWS method, and could be used for all endoscopes. We also found that the labelled FOV values of many commercial endoscopes are significantly overstated. Our study can help endoscope users understand endoscope FOV and identify a proper method for FOV measurement. This paper can be used as a reference to revise the current endoscope FOV measurement standard.

Diffusion tensor and volumetric magnetic resonance imaging using an MR-compatible hand-induced robotic device suggests training-induced neuroplasticity in patients with chronic stroke.

Stroke is the third leading cause of mortality and a frequent cause of long-term adult impairment. Improved strategies to enhance motor function in individuals with chronic disability from stroke are thus required. Post­stroke therapy may improve rehabilitation and reduce long-term disability; however, objective methods for evaluating the specific impact of rehabilitation are rare. Brain imaging studies on patients with chronic stroke have shown evidence for reorganization of areas showing functional plasticity after a stroke. In this study, we hypothesized that brain mapping using a novel magnetic resonance (MR)-compatible hand device in conjunction with state­of­the­art magnetic resonance imaging (MRI) can serve as a novel biomarker for brain plasticity induced by rehabilitative motor training in patients with chronic stroke. This hypothesis is based on the premises that robotic devices, by stimulating brain plasticity, can assist in restoring movement compromised by stroke-induced pathological changes in the brain and that these changes can then be monitored by advanced MRI. We serially examined 15 healthy controls and 4 patients with chronic stroke. We employed a combination of diffusion tensor imaging (DTI) and volumetric MRI using a 3-tesla (3T) MRI system using a 12-channel Siemens Tim coil and a novel MR-compatible hand­induced robotic device. DTI data revealed that the number of fibers and the average tract length significantly increased after 8 weeks of hand training by 110% and 64%, respectively (p<0.001). New corticospinal tract (CST) fibers projecting progressively closer to the motor cortex appeared during training. Volumetric data analysis showed a statistically significant increase in the cortical thickness of the ventral postcentral gyrus areas of patients after training relative to pre-training cortical thickness (p<0.001). We suggest that rehabilitation is possible for a longer period of time after stroke than previously thought, showing that structural plasticity is possible even after 6 months due to retained neuroplasticity. Our study is an example of personalized medicine using advanced neuroimaging methods in conjunction with robotics in the molecular medicine era.

Connectivity alterations assessed by combining fMRI and MR-compatible hand robots in chronic stroke.

The aim of this study was to investigate functional reorganization of motor systems by probing connectivity between motor related areas in chronic stroke patients using functional magnetic resonance imaging (fMRI) in conjunction with a novel MR-compatible hand-induced, robotic device (MR_CHIROD). We evaluated data sets obtained from healthy volunteers and right-hand-dominant patients with first-ever left-sided stroke > or =6 months prior and mild to moderate hemiparesis affecting the right hand. We acquired T1-weighted echo planar and fluid attenuation inversion recovery MR images and multi-level fMRI data using parallel imaging by means of the GeneRalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) algorithm on a 3 T MR system. Participants underwent fMRI while performing a motor task with the MR_CHIROD in the MR scanner. Changes in effective connectivity among a network of primary motor cortex (M1), supplementary motor area (SMA) and cerebellum (Ce) were assessed using dynamic causal modeling. Relative to healthy controls, stroke patients exhibited decreased intrinsic neural coupling between M1 and Ce, which was consistent with a dysfunctional M1 to Ce connection. Stroke patients also showed increased SMA to M1 and SMA to cerebellum coupling, suggesting that changes in SMA and Ce connectivity may occur to compensate for a dysfunctional M1. The results demonstrate for the first time that connectivity alterations between motor areas may help counterbalance a functionally abnormal M1 in chronic stroke patients. Assessing changes in connectivity by means of fMRI and MR_CHIROD might be used in the future to further elucidate the neural network plasticity that underlies functional recovery in chronic stroke patients.

MR_CHIROD v.2: magnetic resonance compatible smart hand rehabilitation device for brain imaging.

This paper presents the design, fabrication, and testing of a novel, one degree-of-freedom, magnetic resonance compatible smart hand interfaced rehabilitation device (MR_CHIROD v.2), which may be used in brain magnetic resonance (MR) imaging during handgrip rehabilitation. A key feature of the device is the use of electrorheological fluids (ERFs) to achieve computer controlled, variable, and tunable resistive force generation. The device consists of three major subsystems: 1) an ERF based resistive element, 2) handles, and c) two sensors, one optical encoder and one force sensor, to measure the patient induced motion and force. MR_CHIROD v.2 is designed to resist up to 50% of the maximum level of gripping force of a human hand and be controlled in real time. Our results demonstrate that the MR environment does not interfere with the performance of the MR_CHIROD v.2, and, reciprocally, its use does not cause fMR image artifacts. The results are encouraging in jointly using MR_CHIROD v.2 and brain MR imaging to study motor performance and assess rehabilitation after neurological injuries such as stroke.

Functional MRI of Rehabilitation in Chronic Stroke Patients Using Novel MR-Compatible Hand Robots.

We monitored brain activation after chronic stroke by combining functional magnetic resonance imaging (fMRI) with a novel MR-compatible, hand-induced, robotic device (MR_CHIROD). We evaluated 60 fMRI datasets on a 3 T MR system from five right-handed patients with left-sided stroke >/=6 months prior and mild to moderate hemiparesis. Patients trained the paretic right hand at approximately 75% of maximum strength with an exercise ball for 1 hour/day, 3 days/week for 4 weeks. Multi-level fMRI data were acquired before, during training, upon completion of training, and after a non-training period using parallel imaging employing GeneRalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) while the participant used the MR_CHIROD. Training increased the number of activated sensorimotor cortical voxels, indicating functional cortical plasticity in chronic stroke patients. The effect persisted four weeks after training completion, indicating the potential of rehabilitation in inducing cortical plasticity in chronic stroke patients.

Magnetic resonance-compatible robotic and mechatronics systems for image-guided interventions and rehabilitation: a review study.

The continuous technological progress of magnetic resonance imaging (MRI), as well as its widespread clinical use as a highly sensitive tool in diagnostics and advanced brain research, has brought a high demand for the development of magnetic resonance (MR)-compatible robotic/mechatronic systems. Revolutionary robots guided by real-time three-dimensional (3-D)-MRI allow reliable and precise minimally invasive interventions with relatively short recovery times. Dedicated robotic interfaces used in conjunction with fMRI allow neuroscientists to investigate the brain mechanisms of manipulation and motor learning, as well as to improve rehabilitation therapies. This paper gives an overview of the motivation, advantages, technical challenges, and existing prototypes for MR-compatible robotic/mechatronic devices.

fMRI-compatible rehabilitation hand device.

BACKGROUND: Functional magnetic resonance imaging (fMRI) has been widely used in studying human brain functions and neurorehabilitation. In order to develop complex and well-controlled fMRI paradigms, interfaces that can precisely control and measure output force and kinematics of the movements in human subjects are needed. Optimized state-of-the-art fMRI methods, combined with magnetic resonance (MR) compatible robotic devices for rehabilitation, can assist therapists to quantify, monitor, and improve physical rehabilitation. To achieve this goal, robotic or mechatronic devices with actuators and sensors need to be introduced into an MR environment. The common standard mechanical parts can not be used in MR environment and MR compatibility has been a tough hurdle for device developers. METHODS: This paper presents the design, fabrication and preliminary testing of a novel, one degree of freedom, MR compatible, computer controlled, variable resistance hand device that may be used in brain MR imaging during hand grip rehabilitation. We named the device MR_CHIROD (Magnetic Resonance Compatible Smart Hand Interfaced Rehabilitation Device). A novel feature of the device is the use of Electro-Rheological Fluids (ERFs) to achieve tunable and controllable resistive force generation. ERFs are fluids that experience dramatic changes in rheological properties, such as viscosity or yield stress, in the presence of an electric field. The device consists of four major subsystems: a) an ERF based resistive element; b) a gearbox; c) two handles and d) two sensors, one optical encoder and one force sensor, to measure the patient induced motion and force. The smart hand device is designed to resist up to 50% of the maximum level of gripping force of a human hand and be controlled in real time. RESULTS: Laboratory tests of the device indicate that it was able to meet its design objective to resist up to approximately 50% of the maximum handgrip force. The detailed compatibility tests demonstrated that there is neither an effect from the MR environment on the ERF properties and performance of the sensors, nor significant degradation on MR images by the introduction of the MR_CHIROD in the MR scanner. CONCLUSION: The MR compatible hand device was built to aid in the study of brain function during generation of controllable and tunable force during handgrip exercising. The device was shown to be MR compatible. To the best of our knowledge, this is the first system that utilizes ERF in MR environment.