Congenital Nasolacrimal Duct Obstruction: Comparison of Two Different Treatment Algorithms.

PURPOSE: To clarify the most appropriate treatment regimen for congenital nasolacrimal duct obstruction (CNLDO). METHODS: A retrospective observational analysis was performed of patients undergoing probing with or without intubation to treat CNLDO in a single institution (Royal Victoria Hospital, Belfast) from 2006 to 2011. RESULTS: Based on exclusion criteria, 246 eyes of 177 patients (aged 0 to 9.8 years with a mean age of 2.1 years) were included in this study: 187 (76%) eyes had successful outcome at first intervention with primary probing, whereas 56 (23%) eyes underwent secondary intervention. There were no significant differences by gender, age, or obstruction complexity between the successful and unsuccessful patients with first intervention. For those patients requiring secondary intervention, 16 of 24 (67%) eyes had successful probing, whereas 22 of 24 (92%) had successful intubation. Patients with intubation as a secondary procedure were significantly more likely to have a successful outcome (P = .037). Statistical analysis was performed using the Fisher's exact test and Barnard's exact test. CONCLUSIONS: Primary probing for CNLDO has a high success rate that is not adversely affected by increasing age. This study also indicates that if initial probing is unsuccessful, nasolacrimal intubation rather than repeat probing yields a significantly higher success rate. [J Pediatr Ophthalmol Strabismus. 2016;53(5):285-291.].

The use of ensemble empirical mode decomposition with canonical correlation analysis as a novel artifact removal technique.

Biosignal measurement and processing is increasingly being deployed in ambulatory situations particularly in connected health applications. Such an environment dramatically increases the likelihood of artifacts which can occlude features of interest and reduce the quality of information available in the signal. If multichannel recordings are available for a given signal source, then there are currently a considerable range of methods which can suppress or in some cases remove the distorting effect of such artifacts. There are, however, considerably fewer techniques available if only a single-channel measurement is available and yet single-channel measurements are important where minimal instrumentation complexity is required. This paper describes a novel artifact removal technique for use in such a context. The technique known as ensemble empirical mode decomposition with canonical correlation analysis (EEMD-CCA) is capable of operating on single-channel measurements. The EEMD technique is first used to decompose the single-channel signal into a multidimensional signal. The CCA technique is then employed to isolate the artifact components from the underlying signal using second-order statistics. The new technique is tested against the currently available wavelet denoising and EEMD-ICA techniques using both electroencephalography and functional near-infrared spectroscopy data and is shown to produce significantly improved results.

A methodology for validating artifact removal techniques for physiological signals.

Artifact removal from physiological signals is an essential component of the biosignal processing pipeline. The need for powerful and robust methods for this process has become particularly acute as healthcare technology deployment undergoes transition from the current hospital-centric setting toward a wearable and ubiquitous monitoring environment. Currently, determining the relative efficacy and performance of the multiple artifact removal techniques available on real world data can be problematic, due to incomplete information on the uncorrupted desired signal. The majority of techniques are presently evaluated using simulated data, and therefore, the quality of the conclusions is contingent on the fidelity of the model used. Consequently, in the biomedical signal processing community, there is considerable focus on the generation and validation of appropriate signal models for use in artifact suppression. Most approaches rely on mathematical models which capture suitable approximations to the signal dynamics or underlying physiology and, therefore, introduce some uncertainty to subsequent predictions of algorithm performance. This paper describes a more empirical approach to the modeling of the desired signal that we demonstrate for functional brain monitoring tasks which allows for the procurement of a "ground truth" signal which is highly correlated to a true desired signal that has been contaminated with artifacts. The availability of this "ground truth," together with the corrupted signal, can then aid in determining the efficacy of selected artifact removal techniques. A number of commonly implemented artifact removal techniques were evaluated using the described methodology to validate the proposed novel test platform.

Artifact removal in physiological signals--practices and possibilities.

The combination of reducing birth rate and increasing life expectancy continues to drive the demographic shift toward an aging population. This, in turn, places an ever-increasing burden on healthcare due to the increasing prevalence of patients with chronic illnesses and the reducing income-generating population base needed to sustain them. The need to urgently address this healthcare "time bomb" has accelerated the growth in ubiquitous, pervasive, distributed healthcare technologies. The current move from hospital-centric healthcare toward in-home health assessment is aimed at alleviating the burden on healthcare professionals, the health care system and caregivers. This shift will also further increase the comfort for the patient. Advances in signal acquisition, data storage and communication provide for the collection of reliable and useful in-home physiological data. Artifacts, arising from environmental, experimental and physiological factors, degrade signal quality and render the affected part of the signal useless. The magnitude and frequency of these artifacts significantly increases when data collection is moved from the clinic into the home. Signal processing advances have brought about significant improvement in artifact removal over the past few years. This paper reviews the physiological signals most likely to be recorded in the home, documenting the artifacts which occur most frequently and which have the largest degrading effect. A detailed analysis of current artifact removal techniques will then be presented. An evaluation of the advantages and disadvantages of each of the proposed artifact detection and removal techniques, with particular application to the personal healthcare domain, is provided.

A methodology for validating artifact removal techniques for fNIRS.

fNIRS recordings are increasingly utilized to monitor brain activity in both clinical and connected health settings. These optical recordings provide a convenient measurement of cerebral hemodynamic changes which can be linked to motor and cognitive performance. Such measurements are of clinical utility in a broad range of conditions ranging from dementia to movement rehabilitation therapy. For such applications fNIRS is increasingly deployed outside the clinic for patient monitoring in the home. However, such a measurement environment is poorly controlled and motion, in particular, is a major source of artifacts in the signal, leading to poor signal quality for subsequent clinical interpretation. Artifact removal techniques are increasingly being employed with an aim of reducing the effect of the noise in the desired signal. Currently no methodology is available to accurately determine the efficacy of a given artifact removal technique due to the lack of a true reference for the uncontaminated signal. In this paper we propose a novel methodology for fNIRS data collection allowing for effective validation of artifact removal techniques. This methodology describes the use of two fNIRS channels in close proximity allowing them to sample the same measurement location; allowing for the introducing of motion artifact to only one channel while having the other free of contamination. Through use of this methodology, for each motion artifact epoch, a true reference for the uncontaminated signal becomes available for use in the development and performance evaluation of signal processing strategies. The advantage of the described methodology is demonstrated using a simple artifact removal technique with an accelerometer based reference.

Long-term refractive and biometric outcomes following diode laser therapy for retinopathy of prematurity.

PURPOSE: To assess the long-term refractive and biometric outcomes of diode laser-treated eyes in threshold retinopathy of prematurity (ROP). METHODS: Cycloplegic autorefraction and biometry (Zeiss IOLMaster) were performed, at a mean follow-up of 11 years, on 16 laser-treated eyes with threshold ROP and 9 comparison eyes with subthreshold untreated ROP. RESULTS: The laser-treated eyes had a mean spherical equivalent of -2.33 D with a mean astigmatic error of 1.38 D. The comparison eyes had a mean spherical equivalent of +1.07 D with a mean astigmatic error of 0.42 D. This trend toward increased myopia in treated eyes did not achieve statistical significance (p=0.08). The myopia in the laser group appeared to be slowly progressive in nature when compared with earlier refractive data for these patients. The laser-treated eyes had reduced anterior chamber depth (ACD) compared with the subthreshold eyes (p=0.02). When physiologic accommodation was inhibited by cycloplegic drops, the anterior chamber deepened by 0.13 mm in the laser-treated eyes and by 0.06 mm in the comparison eyes. This effect of accommodation on ACD did not differ significantly between the two groups (p=0.23). The laser-treated eyes and the comparison eyes did not differ significantly in terms of axial length, corneal power, corneal diameter, or lens power. However, both groups had steeper corneas, shallower anterior chambers, and shorter axial lengths when compared with historical full-term controls. CONCLUSIONS: Myopia in premature infants requiring laser treatment for ROP is associated with a shallowing of the anterior chamber and a steepening of the cornea. Physiological accommodation is not impaired by laser therapy or by severe ROP.