Thermal damage thresholds for multiple-pulse porcine skin laser exposures at 1070 nm.

As solid-state laser technology continues to mature, high-energy lasers operating in the near-infrared (NIR) band have seen increased utilization in manufacturing, medical, and military applications. Formulations of maximum permissible exposure limits establish guidelines for the safe use of these systems for a given set of laser parameters, based on past experimental and analytical studies of exposure thresholds causing injury to the skin and eyes. The purpose of our study is to characterize the skin response to multiple-pulsed laser exposures at the NIR wavelength of 1070 nm, at a constant beam diameter of 1 cm, using anesthetized Yucatan mini-pig subjects. Our study explores three constant total laser-on times of 0.01, 0.1, and 10 s as single- and multiple-pulse sequences. Exposures consisting of 10, 30, and 100 pulses have identical individual pulse durations but different duty cycles in order to include variable degrees of thermal additivity. A plurality of three observers quantifies skin damage with the minimally visible lesion metric, judged at the 1- and 24-h intervals postexposure. Calculation of the median effective dose (ED50) provides injury thresholds for all exposure conditions, based on varying laser power across subjects. The results of this study will provide a quantitative basis for the incorporation of multiple-pulsed laser exposure into standards and augment data contained in the existing ED50 database.

Assessment of Orbital Computed Tomography (CT) Imaging Biomarkers in Patients with Thyroid Eye Disease.

To understand potential orbital biomarkers generated from computed tomography (CT) imaging in patients with thyroid eye disease. This is a retrospective cohort study. From a database of an ongoing thyroid eye disease research study at our institution, we identified 85 subjects who had both clinical examination and laboratory records supporting the diagnosis of thyroid eye disease and concurrent imaging prior to any medical or surgical intervention. Patients were excluded if imaging quality or type was not amenable to segmentation. The images of 170 orbits were analyzed with the developed automated segmentation tool. The main outcome measure was to cross 25 CT structural metrics for each eye with nine clinical markers using a Kendall rank correlation test to identify significant relationships. The Kendall rank correlation test between automatically calculated CT metrics and clinical data demonstrated numerous correlations. Extraocular rectus muscle metrics, such as the average diameter of the superior, medial, and lateral rectus muscles, showed a strong correlation (p < 0.05) with loss of visual acuity and presence of ocular motility defects. Hertel measurements demonstrated a strong correlation (p < 0.05) with volumetric measurements of the optic nerve and other orbital metrics such as the crowding index and proptosis. Optic neuropathy was strongly correlated (p < 0.05) with an increase in the maximum diameter of the superior muscle. This novel method of automated imaging metrics may provide objective, rapid clinical information. This data may be useful for appreciation of severity of thyroid eye disease and recognition of risk factors of visual impairment from dysthyroid optic neuropathy from CT imaging.

Suprathreshold laser injuries in excised porcine skin for millisecond exposures at 1070 nm.

Skin injury response to near-infrared (NIR) laser radiation between the minimum visible lesion threshold and ablation onset is not well understood. This study utilizes a 1070-nm diode-pumped Yb-fiber laser to explore the response of excised porcine skin to high-energy exposures in the suprathreshold injury region without inducing ablation. Concurrent high-speed videography is employed to determine a dichotomous response for three progressive damage categories: observable surface distortion, surface bubble formation due to contained intracutaneous water vaporization, and surface bubble rupture during exposure. Median effective dose (ED50) values are calculated in these categories for 3- and 100-ms pulses with beam diameters (1 / e2) of 3 mm (28, 35, and 49 J / cm2) and 7 mm (96, 141, and 212 J / cm2), respectively. Double-pulse cases are secondarily investigated. Experimental data are compared with the maximum permissible exposure limits and ablation onset simulated by a one-dimensional multiphysics model. Logistic regression analysis predicted injury events with ∼90 % of accuracy. The distinction of skin response into progressive damage categories expands the current understanding of high-energy laser safety while underlining the unique biophysical effects during induced water phase change in tissue. These results prove to be useful in the diagnosis and treatment of NIR laser injuries.

Transorbital target localization with augmented ophthalmologic surgical endoscopy.

PURPOSE: Access to the space behind the eyeball is limited by the position of the globe anteriorly, the neurovascular structures embedded in fat posteriorly, and the tight bony confine of the orbit. These anatomical relationships have impeded application of minimally invasive procedures to the region, such as foreign body removal, tumor biopsy, or the administration of medical therapy directly to the optic nerve. An image-guided system was developed using a magnetically tracked flexible endoscope to navigate behind the eye, with the aim of enabling accurate transorbital surgery to user-specified target locations. METHODS: Targets were defined by microspherical bulbs containing water or gadolinium contrast, with differing visible coloring agent. Six living pigs were anesthetized and two microspheres of differing color and contrast content were implanted in the fat tissue of each orbit. Preoperative T1-weighted MRI volumes were obtained and registered intraoperatively. The system capabilities were tested with a series of targeted surgical interventions. The surgeon was required to navigate the endoscope to each lucent microsphere and identify it by color. For three pigs, 3D/2D registration was performed such that the target's image volume coordinates were used to display its location on real-time endoscope video. RESULTS: The ophthalmologic surgeon was able to correctly identify every target by color, with average intervention time of 24.2 min without enhancement and 3.2 min with enhancement. This difference is highly statistically significant [Formula: see text] for reduction in localization time. CONCLUSIONS: Accurate transorbital target localization is possible in-vivo using image-guided transorbital endoscopy, while endoscopic enhancement through the use of video augmentation significantly reduces procedure time.

Image-guided transorbital procedures with endoscopic video augmentation.

PURPOSE: Surgical interventions to the orbital space behind the eyeball are limited to highly invasive procedures due to the confined nature of the region along with the presence of several intricate soft tissue structures. A minimally invasive approach to orbital surgery would enable several therapeutic options, particularly new treatment protocols for optic neuropathies such as glaucoma. The authors have developed an image-guided system for the purpose of navigating a thin flexible endoscope to a specified target region behind the eyeball. Navigation within the orbit is particularly challenging despite its small volume, as the presence of fat tissue occludes the endoscopic visual field while the surgeon must constantly be aware of optic nerve position. This research investigates the impact of endoscopic video augmentation to targeted image-guided navigation in a series of anthropomorphic phantom experiments. METHODS: A group of 16 surgeons performed a target identification task within the orbits of four skull phantoms. The task consisted of identifying the correct target, indicated by the augmented video and the preoperative imaging frames, out of four possibilities. For each skull, one orbital intervention was performed with video augmentation, while the other was done with the standard image guidance technique, in random order. RESULTS: The authors measured a target identification accuracy of 95.3% and 85.9% for the augmented and standard cases, respectively, with statistically significant improvement in procedure time (Z=-2.044, p=0.041) and intraoperator mean procedure time (Z=2.456, p=0.014) when augmentation was used. CONCLUSIONS: Improvements in both target identification accuracy and interventional procedure time suggest that endoscopic video augmentation provides valuable additional orientation and trajectory information in an image-guided procedure. Utilization of video augmentation in transorbital interventions could further minimize complication risk and enhance surgeon comfort and confidence in the procedure.

Robust Optic Nerve Segmentation on Clinically Acquired CT.

The optic nerve is a sensitive central nervous system structure, which plays a critical role in many devastating pathological conditions. Several methods have been proposed in recent years to segment the optic nerve automatically, but progress toward full automation has been limited. Multi-atlas methods have been successful for brain segmentation, but their application to smaller anatomies remains relatively unexplored. Herein we evaluate a framework for robust and fully automated segmentation of the optic nerves, eye globes and muscles. We employ a robust registration procedure for accurate registrations, variable voxel resolution and image field-of-view. We demonstrate the efficacy of an optimal combination of SyN registration and a recently proposed label fusion algorithm (Non-local Spatial STAPLE) that accounts for small-scale errors in registration correspondence. On a dataset containing 30 highly varying computed tomography (CT) images of the human brain, the optimal registration and label fusion pipeline resulted in a median Dice similarity coefficient of 0.77, symmetric mean surface distance error of 0.55 mm, symmetric Hausdorff distance error of 3.33 mm for the optic nerves. Simultaneously, we demonstrate the robustness of the optimal algorithm by segmenting the optic nerve structure in 316 CT scans obtained from 182 subjects from a thyroid eye disease (TED) patient population.

Robust optic nerve segmentation on clinically acquired computed tomography.

The optic nerve (ON) plays a critical role in many devastating pathological conditions. Segmentation of the ON has the ability to provide understanding of anatomical development and progression of diseases of the ON. Recently, methods have been proposed to segment the ON but progress toward full automation has been limited. We optimize registration and fusion methods for a new multi-atlas framework for automated segmentation of the ONs, eye globes, and muscles on clinically acquired computed tomography (CT) data. Briefly, the multi-atlas approach consists of determining a region of interest within each scan using affine registration, followed by nonrigid registration on reduced field of view atlases, and performing statistical fusion on the results. We evaluate the robustness of the approach by segmenting the ON structure in 501 clinically acquired CT scan volumes obtained from 183 subjects from a thyroid eye disease patient population. A subset of 30 scan volumes was manually labeled to assess accuracy and guide method choice. Of the 18 compared methods, the ANTS Symmetric Normalization registration and nonlocal spatial simultaneous truth and performance level estimation statistical fusion resulted in the best overall performance, resulting in a median Dice similarity coefficient of 0.77, which is comparable with inter-rater (human) reproducibility at 0.73.

Robust Non-Local Multi-Atlas Segmentation of the Optic Nerve.

Labeling or segmentation of structures of interest on medical images plays an essential role in both clinical and scientific understanding of the biological etiology, progression, and recurrence of pathological disorders. Here, we focus on the optic nerve, a structure that plays a critical role in many devastating pathological conditions - including glaucoma, ischemic neuropathy, optic neuritis and multiple-sclerosis. Ideally, existing fully automated procedures would result in accurate and robust segmentation of the optic nerve anatomy. However, current segmentation procedures often require manual intervention due to anatomical and imaging variability. Herein, we propose a framework for robust and fully-automated segmentation of the optic nerve anatomy. First, we provide a robust registration procedure that results in consistent registrations, despite highly varying data in terms of voxel resolution and image field-of-view. Additionally, we demonstrate the efficacy of a recently proposed non-local label fusion algorithm that accounts for small scale errors in registration correspondence. On a dataset consisting of 31 highly varying computed tomography (CT) images of the human brain, we demonstrate that the proposed framework consistently results in accurate segmentations. In particular, we show (1) that the proposed registration procedure results in robust registrations of the optic nerve anatomy, and (2) that the non-local statistical fusion algorithm significantly outperforms several of the state-of-the-art label fusion algorithms.