MR Imaging of the Extracranial Facial Nerve with the CISS Sequence.

BACKGROUND AND PURPOSE: MR imaging is not routinely used to image the extracranial facial nerve. The purpose of this study was to determine the extent to which this nerve can be visualized with a CISS sequence and to determine the feasibility of using that sequence for locating the nerve relative to tumor. MATERIALS AND METHODS: Thirty-two facial nerves in 16 healthy subjects and 4 facial nerves in 4 subjects with parotid gland tumors were imaged with an axial CISS sequence protocol that included 0.8-mm isotropic voxels on a 3T MR imaging system with a 64-channel head/neck coil. Four observers independently segmented the 32 healthy subject nerves. Segmentations were compared by calculating average Hausdorff distance values and Dice similarity coefficients. RESULTS: The primary bifurcation of the extracranial facial nerve into the superior temporofacial and inferior cervicofacial trunks was visible on all 128 segmentations. The mean of the average Hausdorff distances was 1.2 mm (range, 0.3-4.6 mm). Dice coefficients ranged from 0.40 to 0.82. The relative position of the facial nerve to the tumor could be inferred in all 4 tumor cases. CONCLUSIONS: The facial nerve can be seen on CISS images from the stylomastoid foramen to the temporofacial and cervicofacial trunks, proximal to the parotid plexus. Use of a CISS protocol is feasible in the clinical setting to determine the location of the facial nerve relative to tumor.

MR Imaging of the Facial Nerve through the Temporal Bone at 3T with a Noncontrast Ultrashort Echo Time Sequence.

The pointwise encoding time reduction with radial acquisition (PETRA) ultrashort echo time MR imaging sequence at 3T enables visualization of the facial nerve from the brain stem, through the temporal bone, to the stylomastoid foramen without intravenous contrast. Use of the PETRA sequence, or other ultrashort echo time sequences, should be considered in the MR imaging evaluation of certain skull base tumors and perhaps other facial nerve and temporal bone pathologies.

Design and development of a mobile image overlay system for needle interventions.

Previously, a static and adjustable image overlay systems were proposed for aiding needle interventions. The system was either fixed to a scanner or mounted over a large articulated counterbalanced arm. Certain drawbacks associated with these systems limited the clinical translation. In order to minimize these limitations, we present the mobile image overlay system with the objective of reduced system weight, smaller dimension, and increased tracking accuracy. The design study includes optimal workspace definition, selection of display device, mirror, and laser source. The laser plane alignment, phantom design, image overlay plane calibration, and system accuracy validation methods are discussed. The virtual image is generated by a tablet device and projected into the patient by using a beamsplitter mirror. The viewbox weight (1.0 kg) was reduced by 8.2 times and image overlay plane tracking precision (0.21 mm, STD = 0.05) was improved by 5 times compared to previous system. The automatic self-calibration of the image overlay plane was achieved in two simple steps and can be done away from patient table. The fiducial registration error of the physical phantom to scanned image volume registration was 1.35 mm (STD = 0.11). The reduced system weight and increased accuracy of optical tracking should enable the system to be hand held by the physician and explore the image volume over the patient for needle interventions.

Automatic Segmentation of Breast Carcinomas from DCE-MRI using a Statistical Learning Algorithm.

Segmenting regions of high angiogenic activity corresponding to malignant tumors from DCE-MRI is a time-consuming task requiring processing of data in 4 dimensions. Quantitative analyses developed thus far are highly sensitive to external factors and are valid only under certain operating assumptions, which need not be valid for breast carcinomas. In this paper, we have developed a novel Statistical Learning Algorithm for Tumor Segmentation (SLATS) for automatically segmenting cancer from a region selected by the user on DCE-MRI. In this preliminary study, SLATS appears to demonstrate high accuracy (78%) and sensitivity (100%) in segmenting cancers from DCE-MRI when compared to segmentations performed by an expert radiologist. This may be a useful tool for delineating tumors for image-guided interventions.

Optimal transseptal puncture location for robot-assisted left atrial catheter ablation.

BACKGROUND: The preferred method of treatment for atrial fibrillation (AF) is by catheter ablation, in which a catheter is guided into the left atrium through a transseptal puncture. However, the transseptal puncture constrains the catheter, thereby limiting its manoeuvrability and increasing the difficulty in reaching various locations in the left atrium. In this paper, we address the problem of choosing the optimal transseptal puncture location for performing cardiac ablation to obtain maximum manoeuvrability of the catheter. METHODS: We have employed an optimization algorithm to maximize the global isotropy index (GII) to evaluate the optimal transseptal puncture location. As part of this algorithm, a novel kinematic model for the catheter has been developed, based on a continuum robot model. Pre-operative MR/CT images of the heart are segmented using the open source image-guided therapy software, 3D Slicer, to obtain models of the left atrium and septal wall. These models are input to the optimization algorithm to evaluate the optimal transseptal puncture location. RESULTS: The continuum robot model accurately describes the kinematics of the catheter. Simulation and experimental results for the optimal transseptal puncture location are presented in this paper. The optimization algorithm generates discrete points on the septal wall for which the dexterity of the catheter in the left atrium is maximum, corresponding to a GII of 0.4362. CONCLUSION: We have developed an optimization algorithm based on the GII to evaluate the optimal position of the transseptal puncture for left atrial cardiac ablation.

Image Registered Gastroscopic Ultrasound (IRGUS) in human subjects: a pilot study to assess feasibility.

BACKGROUND AND STUDY AIMS: Endoscopic ultrasound (EUS) is a complex procedure due to the subtleties of ultrasound interpretation, the small field of observation, and the uncertainty of probe position and orientation. Animal studies demonstrated that Image Registered Gastroscopic Ultrasound (IRGUS) is feasible and may be superior to conventional EUS in efficiency and image interpretation. This study explores whether these attributes of IRGUS will be evident in human subjects, with the aim of assessing the feasibility, effectiveness, and efficiency of IRGUS in patients with suspected pancreatic lesions. PATIENTS AND METHODS: This was a prospective feasibility study at a tertiary care academic medical center in human patients with pancreatic lesions on computed tomography (CT) scan. Patients who were scheduled to undergo conventional EUS were randomly chosen to undergo their procedure with IRGUS. Main outcome measures included feasibility, ease of use, system function, validated task load (TLX) assessment instrument, and IRGUS experience questionnaire. RESULTS: Five patients underwent IRGUS without complication. Localization of pancreatic lesions was accomplished efficiently and accurately (TLX temporal demand 3.7 %; TLX effort 8.6 %). Image synchronization and registration was accomplished in real time without procedure delay. The mean assessment score for endoscopist experience with IRGUS was positive (66.6 ± 29.4). Real-time display of CT images in the EUS plane and echoendoscope orientation were the most beneficial characteristics. CONCLUSIONS: IRGUS appears feasible and safe in human subjects, and efficient and accurate at identification of probe position and image interpretation. IRGUS has the potential to broaden the adoption of EUS techniques and shorten EUS learning curves. Clinical studies comparing IRGUS with conventional EUS are ongoing.