Effect of high-intensity statin therapy on atherosclerosis (IBIS-4): Manual versus automated methods of IVUS analysis.

Bass, Ronald D; García-García, Héctor M; Ueki, Yasushi; Holmvang, Lene; Pedrazzini, Giovanni; Roffi, Marco; Koskinas, Konstantinos C; Shibutani, Hiroki; Losdat, Sylvain; Ziemer, Paulo G P; Blanco, Pablo J; Levine, Molly B; Bourantas, Christos V; Räber, Lorenz (2023). Effect of high-intensity statin therapy on atherosclerosis (IBIS-4): Manual versus automated methods of IVUS analysis. Cardiovascular revascularization medicine, 54, pp. 33-38. Elsevier 10.1016/j.carrev.2023.04.007

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AIMS

Standard manual analysis of IVUS to study the impact of anti-atherosclerotic therapies on the coronary vessel wall is done by a core laboratory (CL), the ground truth (GT). Automatic segmentation of IVUS with a machine learning (ML) algorithm has the potential to replace manual readings with an unbiased and reproducible method. The aim is to determine if results from a CL can be replicated with ML methods.

METHODS

This is a post-hoc, comparative analysis of the IBIS-4 (Integrated Biomarkers and Imaging Study-4) study (NCT00962416). The GT baseline and 13-month follow-up measurements of lumen and vessel area and percent atheroma volume (PAV) after statin induction were repeated by the ML algorithm.

RESULTS

The primary endpoint was change in PAV. PAV as measured by GT was 43.95 % at baseline and 43.02 % at follow-up with a change of -0.90 % (p = 0.007) while the ML algorithm measured 43.69 % and 42.41 % for baseline and follow-up, respectively, with a change of -1.28 % (p < 0.001). Along the most diseased 10 mm segments, GT-PAV was 52.31 % at baseline and 49.42 % at follow-up, with a change of -2.94 % (p < 0.001). The same segments measured by the ML algorithm resulted in PAV of 51.55 % at baseline and 47.81 % at follow-up with a change of -3.74 % (p < 0.001).

CONCLUSIONS

PAV, the most used endpoint in clinical trials, analyzed by the CL is closely replicated by the ML algorithm. ML automatic segmentation of lumen, vessel and plaque effectively reproduces GT and may be used in future clinical trials as the standard.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Cardiovascular Disorders (DHGE) > Clinic of Cardiology
04 Faculty of Medicine > Pre-clinic Human Medicine > Department of Clinical Research (DCR)

UniBE Contributor:

Ueki, Yasushi, Shibutani, Hiroki, Losdat, Sylvain Pierre, Räber, Lorenz

Subjects:

600 Technology > 610 Medicine & health

ISSN:

1553-8389

Publisher:

Elsevier

Language:

English

Submitter:

Pubmed Import

Date Deposited:

25 Apr 2023 09:37

Last Modified:

17 Apr 2024 00:25

Publisher DOI:

10.1016/j.carrev.2023.04.007

PubMed ID:

37087308

Uncontrolled Keywords:

Coronary artery disease Intravascular ultrasound Lumen segmentation Machine learning Vessel segmentation

BORIS DOI:

10.48350/181937

URI:

https://boris.unibe.ch/id/eprint/181937

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