Dataset Information

Comparative Quantification of Arterial Lipid by Intravascular Photoacoustic-Ultrasound Imaging and Near-Infrared Spectroscopy-Intravascular Ultrasound.

ABSTRACT: Intravascular photoacoustic-ultrasound (IVPA-US) imaging and near-infrared spectroscopy-intravascular ultrasound (NIRS-IVUS) are two hybrid modalities that detect arterial lipid, with comparison necessary to understand the relative advantages of each. We performed in vivo and ex vivo IVPA-US imaging of the iliac arteries of Ossabaw swine with metabolic syndrome (MetS) and lean swine to investigate sensitivity for early-stage atherosclerosis. We repeated imaging ex vivo with NIRS-IVUS for comparison to IVPA-US and histology. Both modalities showed significantly greater lipid in MetS vs. lean swine, but only IVPA-US localized the lipid as perivascular. To investigate late-stage atherosclerosis, we performed ex vivo IVPA-US imaging of a human coronary artery with comparison to NIRS-IVUS and histology. Two advanced fibroatheromas were identified, with agreement between IVPA-measured lipid area and NIRS-derived lipid content. As confirmed histologically, IVPA-US has sensitivity to detect lipid content similar to NIRS-IVUS and provides additional depth resolution, enabling quantification and localization of lipid cores within plaques.

SUBMITTER: Kole A

PROVIDER: S-EPMC6611754 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Comparative Quantification of Arterial Lipid by Intravascular Photoacoustic-Ultrasound Imaging and Near-Infrared Spectroscopy-Intravascular Ultrasound.

Kole Ayeeshik A Cao Yingchun Y Hui Jie J Bolad Islam A IA Alloosh Mouhamad M Cheng Ji-Xin JX Sturek Michael M

Journal of cardiovascular translational research 20181128 3

Intravascular photoacoustic-ultrasound (IVPA-US) imaging and near-infrared spectroscopy-intravascular ultrasound (NIRS-IVUS) are two hybrid modalities that detect arterial lipid, with comparison necessary to understand the relative advantages of each. We performed in vivo and ex vivo IVPA-US imaging of the iliac arteries of Ossabaw swine with metabolic syndrome (MetS) and lean swine to investigate sensitivity for early-stage atherosclerosis. We repeated imaging ex vivo with NIRS-IVUS for compari ...[more]

PMID: 30488332

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Project description:AimsCoronary computed tomography angiography (CCTA) is inferior to intravascular imaging in detecting plaque morphology and quantifying plaque burden. We aim to, for the first time, train a deep-learning (DL) methodology for accurate plaque quantification and characterization in CCTA using near-infrared spectroscopy-intravascular ultrasound (NIRS-IVUS).Methods and resultsSeventy patients were prospectively recruited who underwent CCTA and NIRS-IVUS imaging. Corresponding cross sections were matched using an in-house developed software, and the estimations of NIRS-IVUS for the lumen, vessel wall borders, and plaque composition were used to train a convolutional neural network in 138 vessels. The performance was evaluated in 48 vessels and compared against the estimations of NIRS-IVUS and the conventional CCTA expert analysis. Sixty-four patients (186 vessels, 22 012 matched cross sections) were included. Deep-learning methodology provided estimations that were closer to NIRS-IVUS compared with the conventional approach for the total atheroma volume (ΔDL-NIRS-IVUS: -37.8 ± 89.0 vs. ΔConv-NIRS-IVUS: 243.3 ± 183.7 mm3, variance ratio: 4.262, P < 0.001) and percentage atheroma volume (-3.34 ± 5.77 vs. 17.20 ± 7.20%, variance ratio: 1.578, P < 0.001). The DL methodology detected lesions more accurately than the conventional approach (Area under the curve (AUC): 0.77 vs. 0.67, P < 0.001) and quantified minimum lumen area (ΔDL-NIRS-IVUS: -0.35 ± 1.81 vs. ΔConv-NIRS-IVUS: 1.37 ± 2.32 mm2, variance ratio: 1.634, P < 0.001), maximum plaque burden (4.33 ± 11.83% vs. 5.77 ± 16.58%, variance ratio: 2.071, P = 0.004), and calcific burden (-51.2 ± 115.1 vs. -54.3 ± 144.4, variance ratio: 2.308, P < 0.001) more accurately than conventional approach. The DL methodology was able to segment a vessel on CCTA in 0.3 s.ConclusionsThe DL methodology developed for CCTA analysis from co-registered NIRS-IVUS and CCTA data enables rapid and accurate assessment of lesion morphology and is superior to expert analysts (Clinicaltrials.gov: NCT03556644).

Dataset Information

Comparative Quantification of Arterial Lipid by Intravascular Photoacoustic-Ultrasound Imaging and Near-Infrared Spectroscopy-Intravascular Ultrasound.

Publications

Comparative Quantification of Arterial Lipid by Intravascular Photoacoustic-Ultrasound Imaging and Near-Infrared Spectroscopy-Intravascular Ultrasound.

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