Preprocedural physiological assessment of coronary disease patterns to predict haemodynamic outcomes post-PCI

EuroIntervention 2023;19:e-e. DOI: 10.4244/EIJ-D-23-00516

Nozomi Kotoku
Nozomi Kotoku1, MD; Kai Ninomiya1, MD; Shinichiro Masuda1, MD; Neil O’Leary1, PhD; Scot Garg2,3, MD, PhD; Mareka Naito1, MD; Kotaro Miyashita1, MD; Akihiro Tobe1, MD; Shigetaka Kageyama1, MD; Tsung Ying Tsai1, MD; Pruthvi C. Revaiah1, MD; Shengxian Tu4, PhD; Ken Kozuma5, MD, PhD; Hideyuki Kawashima5, MD, PhD; Yuki Ishibashi6, MD, PhD; Gaku Nakazawa7, MD, PhD; Kuniaki Takahashi7, MD, PhD; Takayuki Okamura8, MD, PhD; Yosuke Miyazaki8, MD, PhD; Hiroki Tateishi8,9, MD, PhD; Masato Nakamura10, MD, PhD; Norihiro Kogame10,11, MD, PhD; Taku Asano12, MD, PhD; Shimpei Nakatani13, MD, PhD; Yoshihiro Morino14, MD, PhD; Masaru Ishida14, MD, PhD; Yuki Katagiri15, MD, PhD; Masafumi Ono12, MD, PhD; Hironori Hara16, MD; Yohei Sotomi17, MD, PhD; Kengo Tanabe18, MD, PhD; Yukio Ozaki19, MD, PhD; Takashi Muramatsu20, MD, PhD; Jouke Dijkstra21, PhD; Yoshinobu Onuma1, MD, PhD; Patrick W. Serruys1, MD, PhD
1. Department of Cardiology, University of Galway, Galway, Ireland; 2. Department of Cardiology, Royal Blackburn Hospital, Blackburn, United Kingdom; 3. School of Medicine, University of Central Lancashire, Preston, United Kingdom; 4. School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China; 5. Department of Cardiology, Teikyo University Hospital, Tokyo, Japan; 6. Division of Cardiology, Department of Internal Medicine, St. Marianna University School of Medicine, Kanagawa, Japan; 7. Department of Cardiology, Kindai University Faculty of Medicine, Osaka, Japan; 8. Division of Cardiology, Department of Medicine and Clinical Science, Yamaguchi University, Graduate School of Medicine, Yamaguchi, Japan; 9. Department of Cardiology, Shibata Hospital, Yamaguchi, Japan; 10. Division of Cardiovascular Medicine, Toho University Ohashi Medical Center, Tokyo, Japan; 11. Department of Cardiology, Tokyo Rosai Hospital, Tokyo, Japan; 12. Department of Cardiology, St. Luke’s International Hospital, Tokyo, Japan; 13. Department of Cardiology, JCHO, Hoshigaoka Medical Center, Osaka, Japan; 14. Department of Cardiology, Iwate Medical University Hospital, Iwate, Japan; 15. Department of Cardiology, Sapporo Higashi Tokushukai Hospital, Hokkaido, Japan; 16. Department of Cardiology, The University of Tokyo Hospital, Tokyo, Japan; 17. Department of Cardiovascular Medicine, Osaka University, Graduate School of Medicine, Osaka, Japan; 18. Division of Cardiology, Mitsui Memorial Hospital, Tokyo, Japan; 19. Department of Cardiology, Fujita Health University Okazaki Medical Center, Aichi, Japan; 20. Department of Cardiology, Fujita Health University Hospital, Toyoake, Japan; 21. Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands

Background: Even with intracoronary imaging-guided stent optimisation, suboptimal haemodynamic outcomes post-percutaneous coronary intervention (PCI) can be related to residual lesions in non-stented segments. Preprocedural assessment of pathophysiological coronary artery disease (CAD) patterns could help predict the physiological response to PCI.

Aims: The aim of this study was to assess the relationship between preprocedural pathophysiological haemodynamic patterns and intracoronary imaging findings, as well as their association with physiological outcomes immediately post-PCI.

Methods: Data from 206 patients with chronic coronary syndrome enrolled in the ASET-JAPAN study were analysed. Pathophysiological CAD patterns were characterised using Murray law-based quantitative flow ratio (μQFR)-derived indices acquired from pre-PCI angiograms. The diffuseness of CAD was defined by the pullback pressure gradient (PPG) index. Intracoronary imaging in stented segments after stent optimisation was also analysed.

Results: In the multivariable analysis, diffuse disease − defined by the pre-PCI μQFR-PPG index − was an independent factor for predicting a post-PCI μQFR <0.91 (per 0.1 decrease of PPG index, odds ratio 1.57, 95% confidence interval: 1.07-2.34; p=0.022), whereas the stent expansion index (EI) was not associated with a suboptimal post-PCI μQFR. Among vessels with an EI ≥80% and post-PCI μQFR <0.91, 84.0% of those vessels had a diffuse pattern preprocedure. There was no significant difference in EI between vessels with diffuse disease and those with focal disease. The average plaque burden in the stented segment was significantly larger in vessels with a preprocedural diffuse CAD pattern.

Conclusions: A physiological diffuse pattern preprocedure was an independent factor in predicting unfavourable immediate haemodynamic outcomes post-PCI, even after stent optimisation using intracoronary imaging. Preprocedural assessment of CAD patterns could identify patients who are likely to exhibit superior immediate haemodynamic outcomes following PCI.

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