AUTHOR=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 

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

JOURNAL=Frontiers in Cardiovascular Medicine

VOLUME=Volume 8 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2021.730626

DOI=10.3389/fcvm.2021.730626

ISSN=2297-055X

ABSTRACT=Background and purpose: 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, lumen-diameter) and to grasp morphological features (arterial walls) from quantitative coronary angiography (QCA), unnoticeable on the original images. 
Methods: Archive images of QCA and intravascular ultrasound (IVUS) of ten patients (8 men, age 69.1±9.7 years) who underwent both procedures for clinical reasons were retrospectively analysed. 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.
Results: 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 (P<0.01) than that observed with original QCA-images (0.58 mm). ACMs were also able to extract arterial walls features from QCA. The bias between the measures of arterial walls obtained with IVUS and ACMs, although significant (P<0.01), was small (0.09 mm, 95% CI (0.03, 0.14)) and the correlation was fairly good (r=0.63; P<0.0001). 
Conclusions: 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.