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使用创新的无监督人工自适应系统对定量冠状动脉造影图像上的新型冠状动脉特征进行评估:一项概念验证研究。

Assessment of New Coronary Features on Quantitative Coronary Angiographic Images With Innovative Unsupervised Artificial Adaptive Systems: A Proof-of-Concept Study.

作者信息

Amato Mauro, Buscema Massimo, Massini Giulia, Maurelli Guido, Grossi Enzo, Frigerio Beatrice, Ravani Alessio L, Sansaro Daniela, Coggi Daniela, Ferrari Cristina, Bartorelli Antonio L, Veglia Fabrizio, Tremoli Elena, Baldassarre Damiano

机构信息

Centro Cardiologico Monzino, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Milan, Italy.

Semeion, Research Centre of Sciences of Communication, Rome, Italy.

出版信息

Front Cardiovasc Med. 2021 Oct 14;8:730626. doi: 10.3389/fcvm.2021.730626. eCollection 2021.

Abstract

The Active Connection Matrixes (ACMs) are unsupervised artificial adaptive systems able to extract from digital images features of interest (edges, tissue differentiation, etc.) unnoticeable with conventional systems. In this proof-of-concept study, we assessed the potentiality of ACMs to increase measurement precision of morphological structures (e.g., stenosis and lumen diameter) and to grasp morphological features (arterial walls) from quantitative coronary angiography (QCA), unnoticeable on the original images. Archive images of QCA and intravascular ultrasound (IVUS) of 10 patients (8 men, age 69.1 ± 9.7 years) who underwent both procedures for clinical reasons were retrospectively analyzed. Arterial features derived from "IVUS images," "conventional QCA images," and "ACM-reprocessed QCA images" were measured in 21 coronary segments. Portions of 1-mm length (263 for lumen and 526 for arterial walls) were head-to-head compared to assess quali-quantitative between-methods agreement. When stenosis was calculated on "ACM-reprocessed QCA images," the bias vs. IVUS (gold standard) did not improve, but the correlation coefficient of the QCA-IVUS relationship increased from 0.47 to 0.83. When IVUS-derived lumen diameters were compared with diameters obtained on ACM-reprocessed QCA images, the bias (-0.25 mm) was significantly smaller ( < 0.01) than that observed with original QCA images (0.58 mm). ACMs were also able to extract arterial wall features from QCA. The bias between the measures of arterial walls obtained with IVUS and ACMs, although significant ( < 0.01), was small [0.09 mm, 95% CI (0.03, 0.14)] and the correlation was fairly good ( = 0.63; < 0.0001). This study provides proof of concept that ACMs increase the measurement precision of coronary lumen diameter and allow extracting from QCA images hidden features that mirror well the arterial walls derived by IVUS.

摘要

主动连接矩阵(ACM)是无监督人工自适应系统,能够从数字图像中提取常规系统难以察觉的感兴趣特征(边缘、组织分化等)。在这项概念验证研究中,我们评估了ACM提高形态结构(如狭窄和管腔直径)测量精度以及从定量冠状动脉造影(QCA)中把握形态特征(动脉壁)的潜力,这些在原始图像上是难以察觉的。回顾性分析了10例(8名男性,年龄69.1±9.7岁)因临床原因同时接受QCA和血管内超声(IVUS)检查的患者的存档图像。在21个冠状动脉节段中测量了源自“IVUS图像”“传统QCA图像”和“ACM重新处理的QCA图像”的动脉特征。对1毫米长度的部分(管腔部分263个,动脉壁部分526个)进行直接比较,以评估方法间的定性定量一致性。当在“ACM重新处理的QCA图像”上计算狭窄程度时,与IVUS(金标准)相比偏差没有改善,但QCA-IVUS关系的相关系数从0.47增加到了0.83。当将IVUS得出的管腔直径与在ACM重新处理的QCA图像上获得的直径进行比较时,偏差(-0.25毫米)明显小于原始QCA图像(0.58毫米)(<0.01)。ACM还能够从QCA中提取动脉壁特征。IVUS和ACM获得的动脉壁测量值之间的偏差虽然显著(<0.01),但很小[0.09毫米,95%CI(0.03,0.14)],且相关性相当好(=0.63;<0.0001)。这项研究提供了概念证明,即ACM提高了冠状动脉管腔直径的测量精度,并允许从QCA图像中提取隐藏特征,这些特征能很好地反映IVUS得出的动脉壁情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a051/8551448/0e64b116ee35/fcvm-08-730626-g0001.jpg

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