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Noninvasive iPhone Measurement of Left Ventricular Ejection Fraction Using Intrinsic Frequency Methodology*

Pahlevan, Niema M. PhD1,2; Rinderknecht, Derek G. PhD3; Tavallali, Peyman PhD3,4; Razavi, Marianne PhD3,5; Tran, Thao T. BS, ARMRIT2; Fong, Michael W. MD6; Kloner, Robert A. MD, PhD, FAHA, FACC6,7; Csete, Marie MD, PhD2,5,8; Gharib, Morteza PhD5,9

doi: 10.1097/CCM.0000000000002459
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Objective: The study is based on previously reported mathematical analysis of arterial waveform that extracts hidden oscillations in the waveform that we called intrinsic frequencies. The goal of this clinical study was to compare the accuracy of left ventricular ejection fraction derived from intrinsic frequencies noninvasively versus left ventricular ejection fraction obtained with cardiac MRI, the most accurate method for left ventricular ejection fraction measurement.

Design: After informed consent, in one visit, subjects underwent cardiac MRI examination and noninvasive capture of a carotid waveform using an iPhone camera (The waveform is captured using a custom app that constructs the waveform from skin displacement images during the cardiac cycle.). The waveform was analyzed using intrinsic frequency algorithm.

Setting: Outpatient MRI facility.

Subjects: Adults able to undergo MRI were referred by local physicians or self-referred in response to local advertisement and included patients with heart failure with reduced ejection fraction diagnosed by a cardiologist.

Interventions: Standard cardiac MRI sequences were used, with periodic breath holding for image stabilization. To minimize motion artifact, the iPhone camera was held in a cradle over the carotid artery during iPhone measurements.

Measurements and Main Results: Regardless of neck morphology, carotid waveforms were captured in all subjects, within seconds to minutes. Seventy-two patients were studied, ranging in age from 20 to 92 years old. The main endpoint of analysis was left ventricular ejection fraction; overall, the correlation between ejection fraction–iPhone and ejection fraction–MRI was 0.74 (r = 0.74; p < 0.0001; ejection fraction–MRI = 0.93 × [ejection fraction–iPhone] + 1.9).

Conclusions: Analysis of carotid waveforms using intrinsic frequency methods can be used to document left ventricular ejection fraction with accuracy comparable with that of MRI. The measurements require no training to perform or interpret, no calibration, and can be repeated at the bedside to generate almost continuous analysis of left ventricular ejection fraction without arterial cannulation.

1Department of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, CA.

2Advanced Imaging and Spectroscopy Center, Huntington Medical Research Institutes, Pasadena, CA.

3Avicena LLC, Los Angeles, CA.

4Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA.

5Medical Engineering Department, California Institute of Technology, Pasadena, CA.

6Division of Cardiovascular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA.

7Cardiovascular Research Institute, Huntington Medical Research Institutes, Pasadena, CA.

8Department of Anesthesiology, Keck School of Medicine, University of Southern California, Los Angeles, CA.

9Graduate Aerospace Laboratory, California Institute of Technology, Pasadena, CA.

*See also p. 1240.

The clinical trial was performed at Huntington Medical Research Institutes (HMRI). Other parts of the study were conducted at California Institute of Technology, HMRI, and University of Southern California.

Supported, in part, by James Boswell Fellowship program of California Institute of Technology and Huntington Medical Research Institutes (to Dr. Pahlevan).

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (http://journals.lww.com/ccmjournal).

Drs. Pahlevan, Rinderknecht, Tavallali, Razavi, Kloner, and Gharib disclosed off-label product use of a noninvasive method for acquiring and analyzing arterial pulse waveforms and how the resulting analysis correlates to ejection fraction measured by cardiac magnetic resonance, where the device in question remains experimental at this time. Dr. Pahlevan received funding from Avicena (equity and consulting), disclosing that he and Drs. Rinderknecht, Tavallali, and Gharib hold equity in Avicena; Drs. Razavi and Tavallali have employment agreements with Avicena; and he and Dr. Rinderknecht have consulting agreements with Avicena. He was American Heart Association (AHA) Postdoctoral Fellowship recipient (Western States Affiliate). Dr. Rinderknecht disclosed that he is the inventor on a patent related to the research in the article (California Institute of Technology is the owner of the intellectual property, and if commercialized, he may receive a royalty. Currently, the patent is licensed by an entity he is employed by and holds an equity stake in). Dr. Tavallali disclosed that he is the inventor on a patent that is related to the research described in this article (Caltech is the owner of this patent, and through Caltech, he has a residual interest in any royalties that Caltech may receive as a result of commercializing the patent. Additionally, the patent has been licensed to an entity in which he has an equity interest and is currently employed by.). Dr. Razavi disclosed that the technique described in this article is the subject of a patent filed and owned by the California Institute of Technology, which has since been licensed to Avicena, where Dr. Razavi is currently employed. Dr. Csete disclosed that Caltech received funding from an AHA postdoctoral research grant for Dr. Pahlevan. Dr. Gharib received other support as an unpaid board member. The remaining authors have disclosed that they do not have any potential conflicts of interest.

For information regarding this article, E-mail: pahlevan@usc.edu

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