Dataset Information

Fast assessment of lipid content in arteries in vivo by intravascular photoacoustic tomography.

ABSTRACT: Intravascular photoacoustic tomography is an emerging technology for mapping lipid deposition within an arterial wall for the investigation of the vulnerability of atherosclerotic plaques to rupture. By converting localized laser absorption in lipid-rich biological tissue into ultrasonic waves through thermoelastic expansion, intravascular photoacoustic tomography is uniquely capable of imaging the entire arterial wall with chemical selectivity and depth resolution. However, technical challenges, including an imaging catheter with sufficient sensitivity and depth and a functional sheath material without significant signal attenuation and artifact generation for both photoacoustics and ultrasound, have prevented in vivo application of intravascular photoacoustic imaging for clinical translation. Here, we present a highly sensitive quasi-collinear dual-mode photoacoustic/ultrasound catheter with elaborately selected sheath material, and demonstrated the performance of our intravascular photoacoustic tomography system by in vivo imaging of lipid distribution in rabbit aortas under clinically relevant conditions at imaging speeds up to 16 frames per second. Ex vivo evaluation of fresh human coronary arteries further confirmed the performance of our imaging system for accurate lipid localization and quantification of the entire arterial wall, indicating its clinical significance and translational capability.

SUBMITTER: Cao Y

PROVIDER: S-EPMC5799328 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Fast assessment of lipid content in arteries in vivo by intravascular photoacoustic tomography.

Cao Yingchun Y Kole Ayeeshik A Hui Jie J Zhang Yi Y Mai Jieying J Alloosh Mouhamad M Sturek Michael M Cheng Ji-Xin JX

Scientific reports 20180205 1

Intravascular photoacoustic tomography is an emerging technology for mapping lipid deposition within an arterial wall for the investigation of the vulnerability of atherosclerotic plaques to rupture. By converting localized laser absorption in lipid-rich biological tissue into ultrasonic waves through thermoelastic expansion, intravascular photoacoustic tomography is uniquely capable of imaging the entire arterial wall with chemical selectivity and depth resolution. However, technical challenges ...[more]

PMID: 29402963

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Project description:Thin-cap fibroatheroma (TCFA) and plaque rupture have been recognized as the most frequent risk factor for thrombosis and acute coronary syndrome. Intravascular optical coherence tomography (IVOCT) can identify TCFA and assess cap thickness, which provides an opportunity to assess plaque vulnerability. We developed an automated method that can detect lipidous plaque and assess fibrous cap thickness in IVOCT images. This study analyzed a total of 4360 IVOCT image frames of 77 lesions among 41 patients. Expert cardiologists manually labeled lipidous plaque based on established criteria. To improve segmentation performance, preprocessing included lumen segmentation, pixel-shifting, and noise filtering on the raw polar (r, θ) IVOCT images. We used the DeepLab-v3 plus deep learning model to classify lipidous plaque pixels. After lipid detection, we automatically detected the outer border of the fibrous cap using a special dynamic programming algorithm and assessed the cap thickness. Our method provided excellent discriminability of lipid plaque with a sensitivity of 85.8% and A-line Dice coefficient of 0.837. By comparing lipid angle measurements between two analysts following editing of our automated software, we found good agreement by Bland-Altman analysis (difference 6.7° ± 17°; mean ~ 196°). Our method accurately detected the fibrous cap from the detected lipid plaque. Automated analysis required a significant modification for only 5.5% frames. Furthermore, our method showed a good agreement of fibrous cap thickness between two analysts with Bland-Altman analysis (4.2 ± 14.6 µm; mean ~ 175 µm), indicating little bias between users and good reproducibility of the measurement. We developed a fully automated method for fibrous cap quantification in IVOCT images, resulting in good agreement with determinations by analysts. The method has great potential to enable highly automated, repeatable, and comprehensive evaluations of TCFAs.

Dataset Information

Fast assessment of lipid content in arteries in vivo by intravascular photoacoustic tomography.

Publications

Fast assessment of lipid content in arteries in vivo by intravascular photoacoustic tomography.

Similar Datasets

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