Low variation and high reproducibility in plaque volume with intravascular ultrasound

Human vs. machine vs. core lab for the assessment of coronary atherosclerosis with lumen and vessel contour segmentation with intravascular ultrasound

A machine learning (ML) algorithm for automatic segmentation of intravascular ultrasound was previously validated. It has the potential to improve efficiency, accuracy and precision of coronary vessel segmentation compared to manual segmentation by interventional cardiology experts. The aim of this study is to compare the performance of human readers to the machine and against the readings from a Core Laboratory. This is a post-hoc, cross-sectional analysis of the IBIS-4 study. Forty frames were randomly selected and analyzed by 10 readers of varying expertise two separate times, 1 week apart. Their measurements of lumen, vessel, plaque areas, and plaque burden were performed in an offline software. Among humans, the intra-observer variability was not statistically significant. For the total 80 frames, inter-observer variability between human readers, the ML algorithm and Core Laboratory for lumen area, vessel area, plaque area and plaque burden were not statistically different. For lumen area, however, relative differences between the human readers and the Core Lab ranged from 0.26 to 12.61%. For vessel area, they ranged from 1.25 to 9.54%. Efficiency between the ML algorithm and the readers differed notably. Humans spent 47 min on average to complete the analyses, while the ML algorithm took on average less than 1 min. The overall lumen, vessel and plaque means analyzed by humans and the proposed ML algorithm are similar to those of the Core Lab. Machines, however, are more time efficient. It is warranted to consider use of the ML algorithm in clinical practice.

Accuracy of electrocardiographic-gated versus nongated volumetric intravascular ultrasound measurements of coronary arterial narrowing

Intravascular ultrasound (IVUS) allows precise measurements of plaque plus media (P+M) volume and neointimal hyperplasia after coronary artery stenting. Conventional IVUS volumetric analysis is performed mostly without electrocardiographically gated acquisition, and the IVUS images are selected at 1-mm intervals, whereas the electrocardiographically gated approach consists of images in end-diastole. The accuracy in the luminal, P+M, and external elastic membrane (EEM) volumes between 2 pullbacks with the electrocardiographically gated and nongated approaches has not previously been compared. In 15 patients, 19 segments were studied with electrocardiographically gated and nongated IVUS systems. Two identical pullbacks were performed with each system using the same IVUS catheter. Volumes of the lumen, EEM, and P+M obtained using the electrocardiographically gated pullback technique did not differ significantly from the corresponding volumes obtained using the nongated pullback technique (lumen: 109.7 +/- 47.7 vs 109.2 +/- 45.0 mm(3), p = NS; EEM: 242.6 +/- 109.2 vs 235.0 +/- 108.1 mm(3), p = NS; P+M: 134.8 +/- 67.7 vs 129.8 +/- 69.1 mm(3), p = NS). No significant differences were seen in changes between 2 electrocardiographically gated and 2 nongated pullbacks (lumen: 0.37 +/- 1.76 vs -0.23 +/- 2.32 mm(3), p = NS; EEM: 0.25 +/- 3.22 vs -0.94 +/- 4.27 mm(3), p = NS; P+M: -0.18 +/- 3.42 vs -0.74 +/- 3.88 mm(3), p = NS). In conclusion, in moderate atherosclerotic or stented coronary arteries, electrocardiographically gated IVUS acquisition is not superior in accuracy to conventional nongated IVUS acquisition.

Effect of Simvastatin on Coronary Lesion Site Remodeling: A Serial Intravascular Ultrasound Study

BACKGROUND

Direct evidence of coronary artery remodeling can be derived only from serial changes in the external elastic membrane (EEM) and plaque area. The aim of the study was to assess the effect of simvastatin on coronary remodeling in serial intravascular ultrasound (IVUS) studies.

METHODS

In 39 male patients ECG-triggered transducer pullback IVUS was performed at baseline, after 3 months on a lipid-lowering diet (control period), and after another 12 months of simvastatin 40 mg/day. The lesion site was the image slice with maximum plaque burden at 3 months.

RESULTS

Absolute changes in the EEM area correlated significantly with changes in plaque area during the control period [B = 0.966, r = 0.792 (95% CI 0.71-1.22); p < 0.001] and during simvastatin treatment [B = 0.945, r = 0.822 (95% CI 0.73-1.16); p < 0.001], but there was no significant difference in the slope (delta EEM/delta plaque) between the two time intervals. After 12 months of simvastatin, there was a significant reduction in the lesion EEM area of 4.6% (p = 0.006) and in the lesion plaque area of 5.9% (p < 0.001), but there was no change in reference measurements. As a result, the remodeling index was reduced by simvastatin from 1.01 +/- 0.12 to 0.95 +/- 0.09 (p < 0.001).

CONCLUSION

Simvastatin decreases the remodeling index by reducing lesion, but not reference plaque and EEM area. However, simvastatin does not affect direct evidence of remodeling (delta EEM/delta plaque) obtained using serial IVUS studies.