Quantitative 3·D Echocardiography of The Heart and The Coronary Vessels

The recognition of the existence of ultrasound is credited to L. Spallanzani (1729- 1799). In recent years, ultrasound has been used as an imaging modality in medicine. I. Edler and C.H. Hertz produced the first ultrasound images of the heart in 1953. In the 1960's great progress was made in the clinical application of ultrasound when real-time two-dimensional ultrasound scanners were developed. In 1968, J. Somer constructed the first electronic phased-array scanner and this technology is still the most widely used in ultrasound equipment. In 1974 F.E. Barber and colleagues produced a duplex scanner which integrated imaging with pulsed-wave Doppler measurements. C. Kasai and colleagues constmcted in 1982 the color-coded Doppler flow imaging system based on autocorrelation detection, providing a noninvasive "angiogram" simulation of normal and abnormal blood flow on a "beat-to-beat" basis. Transesophageal echocardiography became available to clinicians in 1985 due to the developments of 1. Soquet who invented the mono- and biplane electronic phased-array probel Echocardiography has become one of the most commonly used diagnostic imaging techniques in cardiology. The development of commercial 3-D echocardiographic equipment began in the early 1990's. In 1993 a technique allowing acquisition of tomographic parallel sliced data set of echocardiographic images of the heart with a lobster tail TEE probe, was 2 developed by the German based company "TomTec GmbH". The TEE probe had an imaging element which could be controlled by computer applying a stepping motor. They also developed an interface to the patient to record the respiration and R-R intervals. This allowed the acquisition of ultrasound images ECG-triggered and gated, which reduced motion artifacts caused by beat-to-beat and respiratory variations in cardiac dimensions and position. After the acquisition of a tomographic data set, the images were post-processed and with application of software interpolation algorithms, gaps in the data set could be filled. This post-processed data set could then be used to reconstruct 3-D volume rendered images of the heart. 3-D ultrasound provides cardiac images which more closely mimic actual anatomy'than 2-D cross-sectional linages, and may thus be easier to interpret

Dynamic Three-Dimensional Echocardiography Offers Advantages for Specific Site Pacing

We have developed a novel technique for specific site pacing

Evaluation of Four-Year Coronary Artery Response After Sirolimus-Eluting Stent Implantation Using Serial Quantitative Intravascular Ultrasound and Computer-Assisted Grayscale Value Analysis for Plaque Composition in Event-Free Patients

ObjectivesThis study sought to evaluate the long-term arterial response after sirolimus-eluting stent implantation.BackgroundSirolimus-eluting stents are effective in inhibiting neointimal hyperplasia without affecting plaque volume behind the stent struts at six months.MethodsSerial quantitative intravascular ultrasound and computer-assisted grayscale value analysis over four years were performed in 23 event-free patients treated with sirolimus-eluting stents.ResultsIn the first two years, the mean plaque volume (155.5 ± 42.8 mm3post-procedure and 156.8 ± 57.7 mm3at two years, p = 0.86) and plaque compositional change expressed as mean percent hypoechogenic tissue of the plaque behind the stent struts (78.9 ± 8.6% post-procedure and 78.2 ± 8.9% at two years, p = 0.67) did not significantly change. However, significant plaque shrinking (change in plaque volume = −18.4 mm3, p = 0.02) with an increase in plaque echogenicity (change in percent hypoechogenic tissue = −7.8%, p < 0.0001) was observed between two and four years. The mean neointimal volume increased over four years from 0 to 8.4 ± 5.8 mm3(p < 0.0001). However, no further statistically significant change occurred between two and four years (7.0 ± 6.7 mm3vs. 8.4 ± 5.8 mm3, p = 0.25).ConclusionsBetween two and four years after sirolimus-eluting stent implantation, peri-stent tissue shrank with a concomitant increase in echogenicity. These intravascular ultrasound findings suggest that late chronic artery responses may evolve for up to four years after sirolimus-eluting stent implantation. In addition, the fact that the neointima does not significantly change from two to four years may suggest that the biological phenomenon of a delayed healing response has begun to subside

Machine learning-based analysis of non-invasive measurements for predicting intracardiac pressures

Aims: Early detection of congestion has demonstrated to improve outcomes in heart failure (HF) patients. However, there is limited access to invasively haemodynamic parameters to guide treatment. This study aims to develop a model to estimate the invasively measured pulmonary capillary wedge pressure (PCWP) using non-invasive measurements with both traditional statistics and machine learning (ML) techniques. Methods and results: The study involved patients undergoing right-sided heart catheterization at Erasmus MC, Rotterdam, from 2017 to 2022. Invasively measured PCWP served as outcomes. Model features included non-invasive measurements of arterial blood pressure, saturation, heart rate (variability), weight, and temperature. Various traditional and ML techniques were used, and performance was assessed using R2 and area under the curve (AUC) for regression and classification models, respectively. A total of 853 procedures were included, of which 31% had HF as primary diagnosis and 49% had a PCWP of 12 mmHg or higher. The mean age of the cohort was 59 ± 14 years, and 52% were male. The heart rate variability had the highest correlation with the PCWP with a correlation of 0.16. All the regression models resulted in low R2 values of up to 0.04, and the classification models resulted in AUC values of up to 0.59. Conclusion: In this study, non-invasive methods, both traditional and ML-based, showed limited correlation to PCWP. This highlights the weak correlation between traditional HF monitoring and haemodynamic parameters, also emphasizing the limitations of single non-invasive measurements. Future research should explore trend analysis and additional features to improve non-invasive haemodynamic monitoring, as there is a clear demand for further advancements in this field.</p