Evaluation of Lens Hardness in Cataract Surgery using High-Frequency Ultrasonic Parameters in Vitro

Huang, Chih-Chung; Ameri, Hossein; DeBoer, Charles; Rowley, Adrian P.; Xu, Xiaochen; Sun, Lei; Wang, Shyh-Hau; Humayun, Mark S.; Shung, K. Kirk

doi:10.1016/j.ultrasmedbio.2007.05.002

Cited by 35 publications

(37 citation statements)

References 13 publications

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“…Severe P>0.05 modulus, a correlation between these two parameters was established, showing that the frequency dependent attenuation can be used to globally estimate the cataractous lens hardness (Huang et al 2007a;2007b;Korte et al 1994;Paunksnis et al 2007; Raitelaitien_ e and Paunksnis 2005;Tabandeh et al 2000;. In this work it was shown that cataract hardness can be characterized non-invasively and classified automatically using acoustical parameters, B-Scan and Nakagami images.…”

Section: P-valuementioning

confidence: 70%

“…In an ex-vivo study, Tabandeh et al (2000) demonstrated that the attenuation of ultrasound waves in human lenses correlates with its hardness. It was also demonstrated by Huang et al (2007a;) that the attenuation increase indicates an increase of cataract hardness. By measuring the Young 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87 89 91 93 95 97 Vel.…”

Section: Discussionmentioning

confidence: 84%

“…The propagation velocity (v) in the lens was calculated considering the average value of 10 A-Scan lines collected from its center portion, according to Huang et al (2007a) and .…”

Section: Data Acquisitionmentioning

confidence: 99%

“…Important tissue physical properties can be inferred from ultrasound scattering, reflection and absorption (Moradi et al 2007;Shung and Thieme 1992). In particular, the ultrasound backscattering signals contain important information about tissues' internal scattering structures and absorption properties (Huang et al 2007a;Onohue et al 2001;Tsui et al 2011). The most common representation for the backscattering signals is the B-Scan image (Szabo 2014).…”

Section: Introductionmentioning

confidence: 99%

“…The most common representation for the backscattering signals is the B-Scan image (Szabo 2014). This technique uses the envelope of the ultrasound echoes from a region of interest (ROI) to create gray-scale images as an intensity mapping (Brand et al 2008;Huang et al 2007a;2007b;Paunksnis et al 2007; Raitelaitien_ e and Paunksnis 2005;Tabandeh et al 2000;. However, due to the processing complexity, B-Scan images commonly used in medical diagnosis contain less information than the original signals (Brand et al 2008;Despotovic et al 2008).…”

Section: Introductionmentioning

confidence: 99%

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Automatic Cataract Hardness Classification Ex Vivo by Ultrasound Techniques

Caixinha

Santos

2016

Ultrasound in Medicine & Biology

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Section: P-valuementioning

confidence: 70%

Section: Discussionmentioning

confidence: 84%

“…The propagation velocity (v) in the lens was calculated considering the average value of 10 A-Scan lines collected from its center portion, according to Huang et al (2007a) and .…”

Section: Data Acquisitionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Automatic Cataract Hardness Classification Ex Vivo by Ultrasound Techniques

Caixinha

Santos

2016

Ultrasound in Medicine & Biology

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Safety Assessment of an A‐Scan Ultrasonic System for Ophthalmic Use

Petrella

Fernandes

Santos

et al. 2020

J of Ultrasound Medicine

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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 AE 0.05), soft tissue thermal index (0.08 AE 0.08) and spatial-peak temporal-average intensity (0.56 AE 0.59 mW/cm 2) 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/cm 2 , 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.

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40‐MHz high‐frequency vector Doppler imaging for superficial venous valve flow estimation

2020

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Purpose: Doppler ultrasound imaging has been used widely for diagnosing vascular diseases. Recently, vector Doppler imaging (VDI) has been proposed for visualizing the blood flow in all directions to yield more detailed information for estimating flow conditions. Increasing the resolution of VDI is important for the structural mapping of superficial vessels with microstructure. However, VDI that operates under a high-frequency ultrasound (HFUS; >30 MHz) is rare. In this study, a 40-MHz high-frequency VDI (HFVDI) based on ultrafast ultrasound imaging was developed to obtain the vector information of blood flow around the superficial venous valve. Methods: The use of HFUS imaging system causes an overload of data acquisition easily. In order to provide sufficient recording time, the frame rate should be reduced. Because the aliasing problem worsens due to a low frame rate when operating Doppler imaging, phase-unwrapping processing methods based on spatial and temporal continuities were applied. Flow phantom experiments were performed to validate the accuracy. In vivo experiments were performed on the valve of superficial veins of healthy volunteers. Results: The experimental results from the phantom study indicated that the error of velocity estimation was <10% in most cases. Dynamic changes of valve movements and flow conditions (including velocity profiles and vector) were observed. Because of the high resolution of HFVDI, the jet and vortex phenomena were observed between the leaflets and in the sinus pocket, respectively. Conclusions: Flow velocities ranging from 2 to 15 mm/s were measured at different locations around the venous valve during the opening and closing phases. All the results indicated that HFVDI has the potential to be a useful tool for vessel duplex scanning.

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Evaluation of Lens Hardness in Cataract Surgery using High-Frequency Ultrasonic Parameters in Vitro

Cited by 35 publications

References 13 publications

Automatic Cataract Hardness Classification Ex Vivo by Ultrasound Techniques

Automatic Cataract Hardness Classification Ex Vivo by Ultrasound Techniques

Safety Assessment of an A‐Scan Ultrasonic System for Ophthalmic Use

40‐MHz high‐frequency vector Doppler imaging for superficial venous valve flow estimation

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