在深度学习OCT上检测钙化斑块,并与光学和超声信号交叉验证:对IVUS-OCT联合导管的补充评估和序言

Jiayue Huang, K. Ninomiya, S. Tu, S. Masuda, J. Dijkstra, Miao Chu, D. Ding, S. Hynes, Neil O'leary, W. Wijns, Y. Onuma, P. Serruys
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Calcified plaque detected by OCT-DL were corroborated by/with optical properties, greyscale (GS)-IVUS, IVUS-VH and echogenicity. The concordance between OCT-DL and other modalities was assessed by kappa statistics. The calcium arc measured by different modalities were compared by orthogonal linear regression. Results: Forty-three calcified plaques were detected by DL in 72 matched anatomic slices, 41 (95%) were confirmed as pure (n = 29) or hybrid calcified plaque (n = 12) by optical properties. Weighted kappa between OCT-DL and GS-IVUS, IVUS-VH and echogenicity were 0.69, 0.60 and 0.60, respectively. After having excluded artifactual optical shadowing (n = 5) generated by guidewire or platinum marker, kappa increased to 0.77, 0.68 and 0.69, with agreement ranging between 90% and 93%. 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引用次数: 0

摘要

背景:光学相干断层扫描(OCT)-深度学习(DL)是一种很有前途的自动斑块表征工具。然而,它的发现还没有与光学和超声信号进行比较。目的:通过综合组织表征技术,包括oct衍生光学特性、血管内超声(IVUS)-虚拟组织学(VH)和回声性,对OCT-DL检测的钙化斑块进行交叉验证。方法:15例生物可吸收支架(BRS)植入术5年后行OCT和IVUS成像。BRS中独特的铂标记物促进了OCT-IVUS的精确联合登记。ct - dl检测到的钙化斑块通过光学性质、灰度(GS)-IVUS、IVUS-VH和回声性证实。运用kappa统计方法评估OCT-DL与其他模式的一致性。采用正交线性回归法比较不同方法测得的钙弧。结果:在72张匹配的解剖切片中,DL检出43个钙化斑块,其中41个(95%)经光学性质证实为纯钙化斑块(n = 29)或杂交钙化斑块(n = 12)。OCT-DL与GS-IVUS、IVUS-VH的加权kappa和回声度分别为0.69、0.60和0.60。排除导丝或铂标记产生的人工光学阴影(n = 5)后,kappa增加到0.77、0.68和0.69,一致性在90%到93%之间。OCT-DL钙弧与GS-IVUS (ICCa = 0.81,差值为1.73±15.25°)、IVUS-VH (ICCa = 0.69,差值为-5.60±21.19°)和回声度(ICCa = 0.65,差值为10.28±18.70°)具有中等相关性和一致性。结论:深度学习增强的OCT与光学和超声信号基本一致。OCT和IVUS的综合评价预示了IVUS-OCT联合置管的潜在诊断价值。
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Calcified plaque detected on OCT with deep learning and cross-validated with optical and ultrasound signals: A complementary appraisal and preamble to combined IVUS-OCT catheter
Background: The optical coherence tomography (OCT)-deep learning (DL) emerged as a promising tool for automated plaque characterization. However, its findings have not been compared with optical and ultrasound signals. Objectives: The objective was to cross-validate the calcified plaque detected by OCT-DL, using comprehensive tissue characterization technologies including OCT-derived optical properties, intravascular ultrasound (IVUS)-virtual histology (VH) and echogenicity. Methods: Five years after bioresorbable scaffold (BRS) implantation, 15 patients underwent OCT and IVUS imaging. The unique platinum markers in BRS facilitated precise OCT-IVUS co-registration. Calcified plaque detected by OCT-DL were corroborated by/with optical properties, greyscale (GS)-IVUS, IVUS-VH and echogenicity. The concordance between OCT-DL and other modalities was assessed by kappa statistics. The calcium arc measured by different modalities were compared by orthogonal linear regression. Results: Forty-three calcified plaques were detected by DL in 72 matched anatomic slices, 41 (95%) were confirmed as pure (n = 29) or hybrid calcified plaque (n = 12) by optical properties. Weighted kappa between OCT-DL and GS-IVUS, IVUS-VH and echogenicity were 0.69, 0.60 and 0.60, respectively. After having excluded artifactual optical shadowing (n = 5) generated by guidewire or platinum marker, kappa increased to 0.77, 0.68 and 0.69, with agreement ranging between 90% and 93%. Calcium arc derived from OCT-DL showed moderate correlation and agreement with GS-IVUS (ICCa = 0.81, difference = 1.73 ± 15.25°), IVUS-VH (ICCa = 0.69, difference = -5.60 ± 21.19°) and echogenicity (ICCa = 0.65, difference = 10.28 ± 18.70°). Conclusion: OCT empowered by deep learning showed substantial agreement with optical and ultrasound signals. The comprehensive assessment provided by OCT and IVUS heralds the potential diagnostic value of combined IVUS-OCT catheters.
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