A new prototype (hardware and software) for monitoring eye movements using a noninvasive technique for gated linac-based stereotactic radiotherapy (SRT) of uveal melanoma was developed. The prototype was tested within the scope of a study for 11 patients. Eye immobilization was achieved by having the patient fixate a light source integrated into the system. The system is used in conjunction with a Head&Neck mask system for immobilization, and uses infrared tracking technology for positioning (both BrainLAB AG Heimstetten/Germany). It was used during CT and MR image acquisition as well as during all of five treatment fractions (6 MeV, 5 x 12 Gy to 80% isodose) to guarantee identical patient setup and eye rotational state during treatment planning and treatment delivery. Maximum temporal and angular deviations tolerated during treatment delivery can be chosen by the physician, the radiation then being interrupted automatically and instantaneously if those criteria are being exceeded during irradiation. A graphical user interface displays life video images of the treated eye and information about the current and previous rotational deviation of the eye from its reference treatment position. The physician thus has online access to data directly linked to the success of the treatment and possible side effects. Mean angular deviations during CT/MR scans and treatment deliveries ranged from 1.61 degrees to 3.64 degrees (standard deviations 0.87 degrees to 2.09 degrees ) which is in accordance with precision requirements for SRT. Typical situations when preset deviation criteria were exceeded are slow drifts (fatigue), sudden large eye movements (irritation), or if patients closed their eyes (fatigue). In these cases radiation was reliably interrupted by the gating system. In our clinical setup the novel system for computer-controlled eye movement gated treatments was well tolerated by all patients. The system yields quantitative real-time information about the eye's rotational state with respect to a reference position (treatment planning situation). Together with the possibility of performing movement-gated treatments of uveal melanoma, the system thus greatly improves the quality of this treatment.
Pupillometry - the study of temporal changes in pupil diameter as a function of external light stimuli or cognitive processing - requires the accurate and gaze-angle independent measurement of pupil dilation. Expected response amplitudes often are only a few percent relative to a pre-stimulus baseline, thus demanding for sub-millimeter accuracy. Video-based approaches to pupil-size measurement aim at inferring pupil dilation from eye images alone. Eyeball rotation in relation to the recording camera as well as optical effects due to refraction at corneal interfaces can, however, induce so-called pupil foreshortening errors (PFE), i.e. systematic gaze-angle dependent changes of apparent pupil size that are on a par with typical response amplitudes. While PFE and options for its correction have been discussed for remote eye trackers, for head-mounted eye trackers such an assessment is still lacking. In this work, we therefore gauge the extent of PFE in three measurement techniques, all based on eye images recorded with a single near-eye camera. We present both real world experimental data as well as results obtained on synthetically generated eye images. We discuss PFE effects at three different levels of data aggregation: the sample, subject, and population level. In particular, we show that a recently proposed refraction-aware approach employing a mathematical 3D eye model is successful in providing pupil-size measurements which are gaze-angle independent at the population level.
Pulsed-wave Doppler (PWD) sonography allows the quantitative measurement of blood flow in vessels if the vessel's diameter and the angle (Doppler angle theta) between the ultrasound beam and the vessel's flow direction are known. In current clinical routine, these parameters are manually determined by the examiner. However the manual determination is time-consuming and a source of error in blood flow measurements because of inaccuracy and variability. To overcome these problems, we present methods for an automated Doppler gate placement and Doppler angle estimation based on image processing algorithms. The Doppler gate is determined by analyzing the intensity profile along the ultrasound beam. To calculate the Doppler angle, we present a multiscale approach which estimates the vessel's flow direction by principal component analysis. A first evaluation shows promising results. Our automated approach yields parameters which match the parameters determined by clinical experts very well.
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