grant

Ultrasound clutter and noise improvements applied to echocardiographic left atrial appendage visualization

Organization VANDERBILT UNIVERSITYLocation Nashville, UNITED STATESPosted 1 Sept 2021Deadline 31 Aug 2026
NIHUS FederalResearch GrantFY2024Accessory SinusesAcousticsAddressAlgorithmsAmericanAtrialAtrial AppendageAtrial FibrillationAtrium AppendageAuditory LocalizationAuricular FibrillationCardiac AtriumCardiac DiseasesCardiac DisordersCardiac ElectroversionCardioversionCell Communication and SignalingCell SignalingChestChronicClinicalClutteringsCodeCoding SystemConsumptionDataDevelopmentDevicesDiagnosisDiagnosticEchocardiogramEchocardiographyEchographyEchotomographyElectric CountershockElectric DefibrillationEnsureEsophagusExclusionFailureGoalsHealth Care SystemsHealthcare SystemsHeartHeart AtriumHeart Atrium AppendageHeart DiseasesImageIncidenceIntracellular Communication and SignalingLeftLeft AtriumLeft atrial structureLengthLinkMR ImagingMR TomographyMRIMRIsMagnetic Resonance ImagingMeasuresMedical Imaging, Magnetic Resonance / Nuclear Magnetic ResonanceMedical UltrasoundMethodsModalityModelingMonitorNMR ImagingNMR TomographyNasal SinusesNasal cavity/ParanasalNasal cavity/Paranasal sinusesNatureNoiseNuclear Magnetic Resonance ImagingParanasal SinusesPatientsPenetrationPerformancePhysiciansPlayProceduresRadiographyRoentgenographyRoleSafetySchemeSensitivity and SpecificitySignal TransductionSignal Transduction SystemsSignalingSinusSound LocalizationSourceSpeedTestingThoraceThoracicThoraxThrombusTimeTrainingTransesophageal EchocardiographyTransmissionTransthoracic EchocardiographyUltrasonicUltrasonic ImagingUltrasonicsUltrasonogramUltrasonographyUltrasound DiagnosisUltrasound Medical ImagingUltrasound TestUnited StatesVariantVariationVisualizationWorkZeugmatographyappendageatriumauricular appendagebiological signal transductionbiomedical implantclinical relevanceclinical translationclinically relevantclinically translatablecostdeep learning based neural networkdeep learning neural networkdeep neural netdeep neural networkdefibrillationdevelopmentaldiagnostic ultrasoundflexibilityflexibleheart auricleheart disorderheart sonographyimage-based methodimagingimaging methodimaging modalityimaging studyimplant deviceimplantable deviceimprovedin silicoin vivoindwelling deviceinnovateinnovationinnovativeinsightmonitoring deviceradiologic imagingradiological imagingreconstructionscreeningscreeningssecond harmonicskillssocial rolesonogramsonographysound measurementstandard of caresuccesstooltransmission processultrasoundultrasound imagingultrasound scanning
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Full Description

Summary
Ultrasonic imaging is the most widely used advanced imaging modality in the United States, and excluding

planar radiography, it represents 44% of all imaging studies. Unfortunately, ultrasound images are often subopti-

mal, and some echocardiography studies show degradation in up to 98% of patients. This rate of degradation and

the freehand nature of clinical ultrasound means that image quality is more dependent on operator skill than other

advanced modalities, but even with the most skilled practitioners, ultrasound completely fails in 11-64% of clinical

tasks. Our overall goal for this application is to fundamentally decrease ultrasound failure rates. Low-quality

ultrasound is particularly problematic in echocardiography because of its role as a first-line tool for diagnosing

and monitoring cardiac disease. When transthoracic echo is inadequate more costly and time-consuming exams

like transesophageal echo or MRI are required. To (1) facilitate the high volumes of transthoracic echo, (2) im-

prove patient comfort and safety (i.e. reduce transesophageal echo), (3) reduce cost and procedure time, and (4)

maximize physician efficiency, it is crucial to have consistently high quality transthoracic echo. To provide this, we

introduce new acquisition and reconstruction solutions for ultrasound imaging.

Echocardiographic imaging of the left atrial appendage is growing in importance in lockstep with the rising

incidence of atrial fibrillation, which currently effects as many as 2-6 million Americans and is expected to grow

to 6-12 million by 2050. In patients with atrial fibrillation, thrombus may appear in as many as 12-26% of left

atria with most appearing in the appendage. Therefore, in patients with current atrial fibrillation the left atrial

appendage must be screened with echocardiography for thrombus before cardioversion can be performed to

return the heart to sinus rhythm. Further, patients receiving a left atrial appendage closure device due to chronic

atrial fibrillation require annual transesophageal echo follow ups to monitor the device. For both cases, the gold-

standard and standard-of-care is transesophageal echocardiography, and while the left atrial appendage can be

visualized transthoracically, is is rarely used because the image quality is considered too unreliable.

Ultrasound image quality is degraded by both clutter and thermal noise, so to make clinically transforma-

tional improvements to ultrasound–and echocardiography specifically–it is necessary to address both the clutter

problem and the noise problem. Addressing both of these issues is becoming increasingly important because

recent developments in beamforming have focused on non-linear algorithms (including deep networks), and the

performance of these methods are more strongly linked to the noise level compared to conventional beamforming

methods. To this end, we introduce both a solution enhancing signal-to-noise ratio using coded excitation and a

comprehensive solution for clutter reduction using deep network beamforming.

Grant Number: 5R01HL156034-04
NIH Institute/Center: NIH

Principal Investigator: Brett Byram

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