stenosis

The prognostic impact of microvascular status in patients with high fractional flow reserve (FFR) is not clear. The goal of this study was to investigate the implications of coronary flow reserve (CFR) and the index of microcirculatory resistance (IMR) in patients who underwent FFR measurement. Patients with high FFR (>0.80) were grouped according to CFR (≤2) and IMR (≥23 U) levels: group A, high CFR with low IMR; group B, high CFR with high IMR; group C, low CFR with low IMR; and group D, low CFR with high IMR. Patient-oriented composite outcome (POCO) of any death, myocardial infarction, and revascularization was assessed. The median follow-up was 658 days (interquartile range: 503.8 to 1,139.3 days). A total of 313 patients (663 vessels) were assessed with FFR, CFR, and IMR. Correlation (r = 0.201; p < 0.001) and categorical agreement (kappa value = 0.178; p < 0.001) between FFR and CFR were modest. Low CFR was associated with higher POCO than high CFR (p = 0.034). There...

Ultrasonic Doppler signals are widely used in the detection of cardiovascular pathologies or the evaluation of the degree of stenosis in the femoral arteries. The presence of stenosis can be indicated by disturbing the blood flow in the femoral arteries, causing spectral broadening of the Doppler signal. To analyze these types of signals and determine stenosis index, a number of time-frequency methods have been developed, such as the short-time Fourier transform, the continuous wavelets transform, the wavelet packet transform, and the S-transform Keyword: Continuous wavelet transform Doppler ultrasound SBI Stenosis S-transform The wavelet packet transform 1. INTRODUCTION Fourier analysis is a basic tool in signal processing. It is indispensable in many areas of research; unfortunately it has limitations when implemented beyond the strict framework of its definition: the area of stationary finite energy signals. In Fourier analysis, all the temporal aspects become illegible in the spectrum. The study of non-stationary signals therefore requires either an extension of the Fourier Transform (or stationary methods), introducing a temporal aspect, or the development of specific methods. A first solution, implemented intuitively in the mid-century, corresponds to Fourier analysis sliding window or short time Fourier transform (STFT), which was introduced in 1945 by D. Gabor with the idea of a time-frequency plan where time becomes an additional parameter of frequency [1]. This method shows that a joint exact location in time and frequency is impossible, and introduces the idea of a discrete basis, minimum, resulting in a few coefficients of the signal energy distribution in time-frequency plan. Other methods are used in this work, namely the continuous wavelet transform and wavelet packets. these two variances of the wavelet transform have existed in a latent state in both mathematics and signal processing, but the real expansion began in the early 1980s. The last method used in this work (based on the wavelet transform) is the S-trasform proposed by Stokwellet al.; it is similar to STFT with an exception that the amplitude and width of the analysis window are a function of frequency, as in the wavelet transform [2].

The concept of stenosis of the lumbar spinal canal as a cause of lumbar dysfunction was firmly established by Verbiest His reports have been supplemented by a number of others, which have defined the scope and import of this problem. The basic pathology in stenosis is reduction in the dimension of the container so that the contents are under compression. Although systemic skeletal disorders such as achondroplasia and paget’s disease are often associated with stenosis, most clinical problems result acquired changes included by degenerative disease and its consequences. The implication is that persons with smaller spinal canals are at greater risk of clinical disease. The complaints are accentuated by activity and controlled by ceasing activity. Diagnosis of spinal stenosis requires demonstration of reduced canal dimensions, either centrally or laterally or both. The majority of the patients with lumbar spinal stenosis can be successfully managed without surgery. Definitive therapy fo...

Background: The decrease in fractional flow reserve (FFR) after adenosine administration from baseline FFR value (termed as ΔFFR) may reflect the compensatory capacity of the mi-crovascular circulation and thus may predict significant coronary stenotic lesions. We aimed to investigate whether baseline FFR and ΔFFR can help identify the coronary ischemic lesion and its severity. Materials and Methods: This cross-sectional study was performed on 154 consecutive patients (Mean age 62.42 ± 9.36 years) that underwent coronary angiography and with definitive intermediate coronary lesions at any of the coronary vessels. FFR was calculated by dividing the mean distal intracoronary pressure by the mean arterial pressure. ΔFFR was also defined as the difference between baseline FFR and hyperemic FFR (considering FFR<0.75 as the criteria for ischemia). Results: The area under receiver-operating characteristic curve for baseline FFR was found as 0.933, and for ΔFFR was 0.946 indicated high values of both indices for predicting ischemic lesions. The best cutoff point for baseline FFR and ΔFFR for discriminating ischemic lesions from the normal condition was 89.5 (yielding a sensitivity of 92.2% and a specificity of 68.0%) and 9.5 (yielding a sensitivity of 96.0% and a specificity of 85.3%), respectively. Conclusion: Our study could successfully demonstrate the high value of both baseline FFR and ΔFFR for predicting coronary ischemic lesions with the cutoff values of <89.5 and >9.5, respectively. [GMJ.2020;9:e1528]