A New 3-D automated computational method to evaluate in-stent neointimal hyperplasia in in-vivo intravascular optical coherence tomography pullbacks

Abstract. Detection of stent struts imaged in vivo by optical coherence tomography (OCT) after percutaneous coronary interventions (PCI) and quantification of in-stent neointimal hyperplasia (NIH) are important. In this paper, we present a new computational method to facilitate the physician in this endeavor to assess and compare new (drug-eluting) stents. We developed a new algorithm for stent strut detection and utilized splines to reconstruct the lumen and stent boundaries which provide automatic measurements of NIH thickness, lumen and stent area. Our original approach is based on the detection of stent struts unique characteristics: bright reflection and shadow behind. Furthermore, we present for the first time to our knowledge a rotation correction method applied across OCT cross-section images for 3D reconstruction and visualization of reconstructed lumen and stent boundaries for further analysis in the longitudinal dimension of the coronary artery. Our experiments over OCT cross-sections taken from 7 patients presenting varying degrees of NIH after PCI illustrate a good agreement between the computer method and expert evaluations: Bland-Altmann analysis revealed a mean difference for lumen cross-section area of 0.11 ± 0.70mm2 and for the stent cross-section area of 0.10 ± 1.28mm2

Manifold learning for image-based gating of intravascular ultrasound (IVUS) pullback squences

Intravascular Ultrasound(IVUS) is an imaging technology which provides cross-sectional images of internal coronary vessel structures. The IVUS frames are acquired by pulling the catheter back with a motor running at a constant speed. However, during the pullback, some artifacts occur due to the beating heart. These artifacts cause inaccurate measurements for total vessel and lumen volume and limitation for further processing. Elimination of these artifacts are possible with an ECG (electrocardiogram) signal, which determines the time interval corresponding to a particular phase of the cardiac cycle. However, using ECG signal requires a special gating unit, which causes loss of important information about the vessel, and furthermore, ECG gating function may not be available in all clinical systems. To address this problem, we propose an image-based gating technique based on manifold learning and a novel weighted ultrasound similarity measure. The parameters for our image-based gating technique were chosen based on the experiments performed on 25 different in-vitro IVUS pullback sequences, which were acquired with the help of a special mechanical instrument that oscillates with given length and frequency. Quantitative tests are performed on 12 different patients, 25 different pullbacks and 100 different longitudinal vessel cuts. In order to validate our method, the results of our method are compared to those of ECG-Gating method. In addition, comparison studies against the results obtained from the state of the art methods available in the literature were carried out to demonstrate the effectiveness of the proposed method

Manifold learning for image-based gating of intravascular ultrasound(IVUS) pullback sequences

Intravascular Ultrasound(IVUS) is an imaging technology which provides cross-sectional images of internal coronary vessel struc- tures. The IVUS frames are acquired by pulling the catheter back with a motor running at a constant speed. However, during the pullback, some artifacts occur due to the beating heart. These artifacts cause inaccu- rate measurements for total vessel and lumen volume and limitation for further processing. Elimination of these artifacts are possible with an ECG (electrocardiogram) signal, which determines the time interval cor- responding to a particular phase of the cardiac cycle. However, using ECG signal requires a special gating unit, which causes loss of impor- tant information about the vessel, and furthermore, ECG gating function may not be available in all clinical systems. To address this problem, we propose an image-based gating technique based on manifold learning. Quantitative tests are performed on 3 different patients, 6 different pull- backs and 24 different vessel cuts. In order to validate our method, the results of our method are compared to those of ECG-Gating method

Can mean platelet volume be used as a biomarker for asthma?

Introduction : Platelets play important roles in airway inflammation and are activated in inflammatory lung diseases, including asthma. Aim :We evaluated the mean platelet volume (MPV), used as a marker of platelet activation, in asthmatic patients during asymptomatic periods and exacerbations compared to healthy controls to determine whether MPV can be used as an indicator of inflammation. Material and methods :Our patient group consisted of95 children with exacerbation of asthma who were admitted to our allergy clinic. The control group consisted of 100 healthy children matched for age, gender, and ethnicity. Mean platelet volume values of the patient group obtained during exacerbation of asthma were compared to those of the same group during the asymptomatic period and with the control group. We investigated factors that can affect the MPV values of asthma patients, including infection, atopy, immunotherapy treatment, and severity of asthma exacerbation. Results :The patient group consisted of 50 (52.6%) boys and 45 (47.4%) girls with a mean age of 125 ±38 months old. Mean MPV values in the exacerbation period, the healthy period, and in the control group were 8.1 ±0.8 fl, 8.1 ±1.06 fl, and 8.2 ±0.9 fl, respectively; there were no significant differences between groups (p > 0.05). The severity of asthma, severity of asthma exacerbation, immunotherapy, coinfection, eosinophil count, and IgE level also had no effect on MPV (p > 0.05). Conclusions : Although platelets play a rolein the pathophysiology of asthma, MPV measurement is insufficient to detect inflammation through platelet

Effect of Amygdalin on the treatment and recurrence of endometriosis in an experimental rat study

Background: Endometriosis is an aggressive disorder and associated with infertility, pelvic pain and intra-abdominal adhesions in women of reproductive age. Women with endometriosis has the potential risk of recurrence ranging from 21.5% in two years to 50% in five years after recovery period. Therefore, there is a certain requirement for new drugs as an alternative therapy to the current ones.Aim: The aim of the present study is to compare the effects of amygdalin and leuprolide acetate on endometriosis development and recurrence in rats.Study Design: Animal experimentMethods: A total of 30 adult female rats were enrolled. Induction of endometriosis was performed by implanting endometriotic focci on the peritoneal side of the abdominal wall. Before amygdalin or leuprolide acetate treatment one of the implant was removed for histopathological analysis, and rats were randomly divided into three groups. Saline (Group 1), amygdalin (Group 2), and leuprolide acetate (Group 3) were administered for three weeks. After treatment, one of the remaining three implants was excised for histopathological evaluation, and all treatments were terminated. Estradiol was given after the estradiol induction for the recurrence of endometriosis. Rest of the implanted tissues were removed, then all rats were euthanised. The implant volumes, histopathological injury and fibrosis levels were observed.Results: The endometriotic foci volumes in Group 2 and Group 3 were significantly lower than in Group 1 (p = 0.001, p = 0.002, respectively). The histopathological injury scores and fibrosis levels were not significantly different among the groups (p > 0.05).Conclusion: The present study showed that amygdalin has an evident effect in the treatment of endometriosis.</p