Safety Assessment of an A-Scan Ultrasonic System for Ophthalmic Use.

OBJECTIVES: This study describes the safety assessment of an A-scan ultrasonic system for ophthalmic use. The system is an investigational medical device for automatic cataract detection and classification. METHODS: The risk management was based on the International Organization for Standardization (ISO) standard DIN EN ISO 14971:2009-10 and International Electrotechnical Commission (IEC) standard IEC 60601-2-37. The calibration of the ultrasonic field was conducted according to the standards IEC 62127-1:2007 and IEC 62359:2010. The uncertainty on measurements was delineated in agreement with the guide JCGM 100:2008. RESULTS: After risk management, all risks were qualitatively classified as acceptable. The mechanical index (0.08 ± 0.05), soft tissue thermal index (0.08 ± 0.08) and spatial-peak temporal-average intensity (0.56 ± 0.59 mW/cm2 ) were under the maximum index values indicated by the US Food and Drug Administration guidance, Marketing Clearance of Diagnostic Ultrasound Systems and Transducers (0.23, 1, and 17 mW/cm2 , respectively). CONCLUSIONS: This study presents a practical approach for the safety assessment of A-scan ultrasonic systems for ophthalmic use. The safety evaluation of a medical device is mandatory before its use in clinical practice. However, the safety monitoring throughout its life cycle should also be considered, since many device components may deteriorate over time and use.

Feasibility assessment of the Eye Scan Ultrasound System for cataract characterization and optimal phacoemulsification energy estimation: protocol for a pilot, nonblinded and monocentre study.

BACKGROUND: Cataracts are lens opacifications that are responsible for more than half of blindness cases worldwide, and the only treatment is surgical intervention. Phacoemulsification surgery, the most frequently performed cataract surgery in developed countries, has associated risks, some of which are related to excessive phacoemulsification energy levels and times. The protocol proposed in herein will be used to evaluate the feasibility of a new experimental medical device, the Eye Scan Ultrasound System (ESUS), for the automatic classification of cataract type and severity and quantitative estimation of the optimal phacoemulsification energy. METHODS: The pilot study protocol will be used to evaluate the feasibility and safety of the ESUS in clinical practice. The study will be conducted in subjects with age-related cataracts and on healthy subjects as controls. The procedures include data acquisition with the experimental ESUS, classification based on the Lens Opacity Classification System III (LOCS III, comparator) using a slit lamp, contrast sensitivity test, optical coherence tomography, specular microscopy and surgical parameters. ESUS works in A-scan pulse-echo mode, with a central frequency of 20 MHz. From the collected signals, acoustic parameters will be extracted and used for automatic cataract characterization and optimal phacoemulsification energy estimation. The study includes two phases. The data collected in the first phase (40 patients, 2 eyes per patient) will be used to train the ESUS algorithms, while the data collected in the second phase (10 patients, 2 eyes per patient) will be used to assess the classification performance. System safety will be monitored during the study. DISCUSSION: The present pilot study protocol will evaluate the feasibility and safety of the ESUS for use in clinical practice, and the results will support a larger clinical study for the efficacy assessment of the ESUS as a diagnostic tool. Ultimately, the ESUS is expected to represent a valuable tool for surgical planning by reducing complications associated with excessive levels of phacoemulsification energy and surgical times, which will have a positive impact on healthcare systems and society. The study is not yet recruiting. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT04461912 , registered on July 8, 2020.

A-scan ultrasound in ophthalmology: A simulation tool.

In the present study, we developed a computational tool for simulating the ophthalmological applications of A-scan ultrasound, including cataract characterisation and biometry. A-scan biometry is used to measure the axial length (AL) of the eye before cataract surgery to calculate the refractive power of the intraocular lens to be implanted. Errors in the measurement of the AL lead to post-surgical refractive errors. The simulation tool was developed using the k-Wave Matlab toolbox, together with a user-friendly interface developed in Matlab. Diverse error sources were evaluated. Constant ultrasound speed assumptions may introduce refractive errors of up to 0.6 D; by contrast, probe positioning errors had a lower impact, of up to 0.11 D. The correct identification of the Bruch's membrane is limited not only by axial resolution constraints but also by the low reflection coefficient at the retina/choroid interface. Regarding cataract characterisation, the amplitudes of the echoes reflected at the lens interfaces are sensitive to diverse cataract types and severities, and a more realistic representation could be obtained by using a higher resolution in the eye grid; however, the required computational times would make simulations impracticable when using personal computers. The simulation tool shows good versatility for evaluating diverse aspects of A-scan biometry.

Syllable structure in dysfunctional Portuguese children's speech.

The goal of this work is to investigate whether children with speech dysfunctions (SD) show a deficit in planning some Portuguese syllable structures (PSS) in continuous speech production. Knowledge of which aspects of speech production are affected by SD is necessary for efficient improvement in the therapy techniques. The case-study is focused on PSS as C1C2V syllable sequences (consonant-consonant-vowel), in which C2 is [l] or [r]. To identify specific speech patterns that are sensitive to SD, coarticulation effects using formant trajectories, intensity, and durational structure are investigated. To explore the characteristics of continuous speech processes in SD speech output, the methodology uses acoustic analysis. Preliminary findings show systematic specific coarticulation in the child with SD when compared to the normal speech (NS) child. This also suggests that the traditional focus on a single word production in the SD assessment needs to be modified to allow more detailed consideration of speech production in continuous speech. It is the purpose of the authors in the future to develop an application that can be an optimal start for SD treatment/counselling programmes. The work reported here proves the importance of clinic linguistic knowledge in that way. This study is the result of a multidisciplinary-team whose work allies linguist, clinical therapy and engineering knowledge.

In-Vivo Automatic Nuclear Cataract Detection and Classification in an Animal Model by Ultrasounds.

OBJECTIVE: To early detect nuclear cataract in vivo and automatically classify its severity degree, based on the ultrasound technique, using machine learning. METHODS: A 20-MHz ophthalmic ultrasound probe with a focal length of 8.9 mm and an active diameter of 3 mm was used. Twenty-seven features in time and frequency domain were extracted for cataract detection and classification with support vector machine (SVM), Bayes, multilayer perceptron, and random forest classifiers. Fifty rats were used: 14 as control and 36 as study group. An animal model for nuclear cataract was developed. Twelve rats with incipient, 13 with moderate, and 11 with severe cataract were obtained. The hardness of the nucleus and the cortex regions was objectively measured in 12 rats using the NanoTest. RESULTS: Velocity, attenuation, and frequency downshift significantly increased with cataract formation ( ). The SVM classifier showed the higher performance for the automatic classification of cataract severity, with a precision, sensitivity, and specificity of 99.7% (relative absolute error of 0.4%). A statistically significant difference was found for the hardness of the different cataract degrees ( P = 0.016). The nucleus showed a higher hardness increase with cataract formation ( P = 0.049 ). A moderate-to-good correlation between the features and the nucleus hardness was found in 23 out of the 27 features. CONCLUSION: The developed methodology made possible detecting the nuclear cataract in-vivo in early stages, classifying automatically its severity degree and estimating its hardness. SIGNIFICANCE: Based on this work, a medical prototype will be developed for early cataract detection, classification, and hardness estimation.