TY - JOUR
T1 - Adoption of a new automated optical coherence tomography software to obtain a lipid plaque spread-out plot
AU - Isidori, Francesco
AU - Lella, Eugenio
AU - Marco, Valeria
AU - Albertucci, Mario
AU - Ozaki, Yukio
AU - La Manna, Alessio
AU - Biccirè, Flavio Giuseppe
AU - Romagnoli, Enrico
AU - Bourantas, Christos V.
AU - Paoletti, Giulia
AU - Fabbiocchi, Franco
AU - Gatto, Laura
AU - Budassi, Simone
AU - Sticchi, Alessandro
AU - Burzotta, Francesco
AU - Taglieri, Nevio
AU - Calligaris, Giuseppe
AU - Arbustini, Eloisa
AU - Alfonso, Fernando
AU - Prati, Francesco
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Nature B.V.
PY - 2021/11
Y1 - 2021/11
N2 - Purpose: Near infrared spectroscopy–Intravascular ultrasound (NIRS-IVUS) provide a fully automated Lipid Core Burden Index (LCBI). Optical coherence tomography (OCT) is potentially capable of measuring lipid longitudinal extension in a dedicated two-dimensional LCBI spread-out plot. The present study has been designed to validate an automated approach to assess OCT images, able of providing a dedicated LCBI spread-out plot. Methods: We compared results obtained with conventional (manual) OCT, with those obtained with a novel automated OCT algorithm and with NIRS-IVUS in consecutive 40 patients. Our goal was to calculate the lipid core longitudinal extension in a dedicated two-dimensional LCBI spread-out plot. Three groups were identified according to the studied lesions: (1) culprit lesions in ACS patients (n = 16), (2) non-culprit lesions in ACS patients (n = 12) and (3) lesions in stable patients (n = 12). OCT (either manual and automated) and NIRS-IVUS assessment showed for culprit ACS plaques a more complex anatomy. Results: A strong trend for increased LCBI was found in the culprit ACS group, regardless of the adopted imaging modality (either NIRS-IVUS or automated OCT). A fair correlation was obtained for the maximum 4 mm LCBI measured by NIRS-IVUS and automated OCT (r = 0.75). The sensitivity and specificity of automated OCT to detect significant LCBI (> 400) were 90.5 and 84.2 respectively. Conclusion: We developed an OCT automated approach that can provide a dedicated lipid plaque spread-out plot to address plaque vulnerability. The automated OCT software can promote and improve OCT clinical applications for the identification of patients at risk of hard events.
AB - Purpose: Near infrared spectroscopy–Intravascular ultrasound (NIRS-IVUS) provide a fully automated Lipid Core Burden Index (LCBI). Optical coherence tomography (OCT) is potentially capable of measuring lipid longitudinal extension in a dedicated two-dimensional LCBI spread-out plot. The present study has been designed to validate an automated approach to assess OCT images, able of providing a dedicated LCBI spread-out plot. Methods: We compared results obtained with conventional (manual) OCT, with those obtained with a novel automated OCT algorithm and with NIRS-IVUS in consecutive 40 patients. Our goal was to calculate the lipid core longitudinal extension in a dedicated two-dimensional LCBI spread-out plot. Three groups were identified according to the studied lesions: (1) culprit lesions in ACS patients (n = 16), (2) non-culprit lesions in ACS patients (n = 12) and (3) lesions in stable patients (n = 12). OCT (either manual and automated) and NIRS-IVUS assessment showed for culprit ACS plaques a more complex anatomy. Results: A strong trend for increased LCBI was found in the culprit ACS group, regardless of the adopted imaging modality (either NIRS-IVUS or automated OCT). A fair correlation was obtained for the maximum 4 mm LCBI measured by NIRS-IVUS and automated OCT (r = 0.75). The sensitivity and specificity of automated OCT to detect significant LCBI (> 400) were 90.5 and 84.2 respectively. Conclusion: We developed an OCT automated approach that can provide a dedicated lipid plaque spread-out plot to address plaque vulnerability. The automated OCT software can promote and improve OCT clinical applications for the identification of patients at risk of hard events.
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U2 - 10.1007/s10554-021-02323-y
DO - 10.1007/s10554-021-02323-y
M3 - Article
C2 - 34292435
AN - SCOPUS:85110950240
SN - 1569-5794
VL - 37
SP - 3129
EP - 3135
JO - International Journal of Cardiovascular Imaging
JF - International Journal of Cardiovascular Imaging
IS - 11
ER -