AIMS: This study aimed to validate automatic intravascular optical coherence tomography (IVOCT) analysis for the evaluation of neointimal coverage in response to stent implantation. METHODS AND RESULTS: Fourteen stented segments in common iliac arteries, acquired from a total of seven adult male New Zealand White rabbits, were interrogated in vivo by IVOCT. Durable polymer everolimus-eluting stents (EES; Xience V, Abbott Vascular, Santa Clara, CA, USA) were used exclusively. Comparison with histology was made in a total of 63 pairs of images, where neointimal thickness over corresponding individual stent struts was assessed. A high correlation coefficient (R = 0.85, P < 0.001) was obtained by comparing automatic IVOCT analysis with histology. Moreover, Bland-Altman statistics showed good limits of agreement (LOAs) of ±45 µm, with an average difference of -10 µm. In addition, manual IVOCT assessment presented very similar results when compared with histology (R = 0.83, P < 0.001 and LOA = ±48 µm with an average difference of -8 µm). Therefore, a very high correlation value was found, comparing manual to automatic IVOCT measurements (R = 0.95, P < 0.001) together with good LOAs (±27 µm) and an average difference of -2 µm. CONCLUSION: The results of the study suggest that automatic IVOCT analysis is a reliable and accurate tool able to speed up current IVOCT analysis procedures. This would potentially allow for a better integration of IVOCT in clinical practice and clinical studies assessing vascular response to stent implantation in a large series of patients.
AIMS: This study aimed to validate automatic intravascular optical coherence tomography (IVOCT) analysis for the evaluation of neointimal coverage in response to stent implantation. METHODS AND RESULTS: Fourteen stented segments in common iliac arteries, acquired from a total of seven adult male New Zealand White rabbits, were interrogated in vivo by IVOCT. Durable polymer everolimus-eluting stents (EES; Xience V, Abbott Vascular, Santa Clara, CA, USA) were used exclusively. Comparison with histology was made in a total of 63 pairs of images, where neointimal thickness over corresponding individual stent struts was assessed. A high correlation coefficient (R = 0.85, P < 0.001) was obtained by comparing automatic IVOCT analysis with histology. Moreover, Bland-Altman statistics showed good limits of agreement (LOAs) of ±45 µm, with an average difference of -10 µm. In addition, manual IVOCT assessment presented very similar results when compared with histology (R = 0.83, P < 0.001 and LOA = ±48 µm with an average difference of -8 µm). Therefore, a very high correlation value was found, comparing manual to automatic IVOCT measurements (R = 0.95, P < 0.001) together with good LOAs (±27 µm) and an average difference of -2 µm. CONCLUSION: The results of the study suggest that automatic IVOCT analysis is a reliable and accurate tool able to speed up current IVOCT analysis procedures. This would potentially allow for a better integration of IVOCT in clinical practice and clinical studies assessing vascular response to stent implantation in a large series of patients.
Authors: Tom Adriaenssens; Giovanni J Ughi; Christophe Dubois; Kevin Onsea; Dries De Cock; Johan Bennett; Stefanus Wiyono; Maarten Vanhaverbeke; Peter Sinnaeve; Ann Belmans; Jan D'hooge; Walter Desmet Journal: Int J Cardiovasc Imaging Date: 2014-03-26 Impact factor: 2.357
Authors: Hong Lu; Juhwan Lee; Martin Jakl; Zhao Wang; Pavel Cervinka; Hiram G Bezerra; David L Wilson Journal: Sci Rep Date: 2020-02-07 Impact factor: 4.379
Authors: Giovanni J Ughi; Miklos G Marosfoi; Robert M King; Jildaz Caroff; Lindsy M Peterson; Benjamin H Duncan; Erin T Langan; Amanda Collins; Anita Leporati; Serge Rousselle; Demetrius K Lopes; Matthew J Gounis; Ajit S Puri Journal: Nat Commun Date: 2020-07-31 Impact factor: 14.919