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\n Chronic venous disease (CVD) is an umbrella term for a group of morphological and functional disorders of the venous system. Clinical signs of CVD may range from telangiectasia and reticular veins to active venous ulcers; therefore, earlier diagnosis and management of CVD may delay disease progression and reduce the burden of CVD on patients, caregivers, and healthcare systems. In this podcast discussion, Professor Andrew Nicolaides, Professor Stavros Kakkos, and Dr Gerardo Estrada-Guerrero share the key highlights from their symposium at the 2023 European Venous Forum. This symposium, titled “Chronic venous disease: what if everything started with early care?”, discussed the clinical significance of “functional CVD,” evidence and risk factors for CVD progression, and real-world strategies to facilitate earlier diagnosis and management of CVD. Together, these topics highlight the importance of early care to improve long-term outcomes for people with CVD.Chronic venous disease (CVD) occurs when the blood vessels that carry blood back to the heart are damaged. In the early stages of CVD, people may have visible or swollen veins in their legs and feet, and may feel pain, heaviness, burning, itching, and cramping. Without treatment, people with CVD may develop open sores (ulcers) that are hard to heal and could get infected, so it is important that CVD is diagnosed and treated early. In this podcast, three doctors who specialize in CVD answer questions about a presentation they gave at a recent medical conference. In their presentation, the doctors talked about people who experience feelings of CVD but without any visible signs, and looked at programs that might help doctors diagnose CVD earlier. The doctors agree that it is important to diagnose and treat CVD early, so that people can avoid the long-term effects of this disease. [ABSTRACT FROM AUTHOR]

Background: Studies have indicated that the presence and size of subclinical atherosclerotic plaques improve the prediction of atherosclerotic cardiovascular events (ASCVE) over and above that provided by conventional risk factors alone. However, the relative contribution of different ultrasonographic measurements and sites of measurements on the 10-year ASCVD risk is largely unknown.Objectives: Our aims were to determine the relative performance of carotid intima-media thickness, plaque thickness, and plaque area in 10-year ASCVD prediction when added to conventional risk factors as well as whether the vascular territory of these measurements, carotid or common femoral bifurcation, and the number of bifurcations with plaque (NBP) influence prediction.Methods: We enrolled 985 adults (mean age: 58.1 ± 10.2 years) free of atherosclerotic cardiovascular disease. Conventional risk factors were recorded, and both carotid and common femoral bifurcations were scanned with ultrasonography. The primary endpoint was a composite of first-time fatal or nonfatal ASCVE.Results: Over a mean ± SD follow-up of 13.2 ± 3.7 years, ASCVE occurred in 154 (15.6%) participants. By adding different plaque measurements to conventional risk factors in a Cox model, net reclassification improvement was 10.4% with maximum intima-media thickness, 9.5% with carotid plaque thickness, and 14.2% with carotid plaque area. It increased to 16.1%, 16.6%, and 16.6% (P < 0.0001) by adding measurements from 4 bifurcations: NBP, total plaque thickness, and total plaque area, respectively.Conclusions: NBP, total plaque thickness, or total plaque area from both the carotid and common femoral bifurcations provides a better prediction of future ASCVE than measurements from a single site. The results need to be validated in an independent cohort. [ABSTRACT FROM AUTHOR]

Objective: To assess the clinical efficacy of sulodexide, including a comparison with venoactive drugs (VAD) (micronized purified flavonoid fraction, MPFF; hydroxy-ethyl-rutosides, HR; calcium dobesilate;Ruscus extract combined with hesperidin methyl chalcone and vitamin C, Ruscus+HMC+VitC; horse chestnut seed extract, HCSE) and pentoxifylline in patients with chronic venous disease. Methods: We performed a literature search in MEDLINE, Embase, and Cochrane Library for randomized controlled trials (RCTs) and observational studies. Proportion of patients with complete venous ulcer healing was the primary outcome and lower leg volume, foot volume, ankle circumference and symptoms were the secondary outcomes. Bayesian network meta-analysis (NMA) was perfomed with random effects models using only RCTs. A meta-analysis of observational studies was performed for sulodexide because no RCT could be included in NMA for symptoms or signs. Results: Forty-five RCTs and eighteen observational studies were identified. Sulodexide was included only in a single NMA for the proportion of patients with complete ulcer healing and it showed to have the highest probability of being the best treatment (48%) compared with pentoxifylline (37%) and MPFF (16%). MPFF was the most effective treatment in reducing lower leg volume, CIVIQ-20 score and pain VAS scale while calcium dobesilate and Ruscus+HMC+VitC were the most effective in reducing foot volume and ankle circumference respectively. Meta-analyses of observational studies for sulodexide showed that it improves significantly the scoring of pain, feeling of swelling, heaviness and parasthesiae measured by Likert scales. Conclusions: Sulodexide is at least as effective as pentoxifylline and more effective than MPFF in improving the rate of ulcer healing in patients with CVD. VADs are effective in improving venous symptoms and signs, as was also shown by sulodexide in the meta-analysis of observational studies. The relative effectiveness of sulodexide and VADs needs to be evaluated by an RCT in order to better inform clinical practice. [ABSTRACT FROM AUTHOR]

The article informs about the passing of Michel Perrin, Topics include a prominent vascular surgeon and scientist, who was known for his significant contributions to vascular surgery, including creating the EVF and advancing classification systems in venous disease. It also highlights his personal qualities, such as his passion for food, wine, and history, and his dedication to work and friendships.

An editorial is presented on plaque burden and vulnerable features being at higher risk of cerebrovascular symptoms. Topics include evaluating carotid plaques using computed tomography angiography (CTA) in symptomatic patients with bilateral intraplaque hemorrhage; and computed tomography angiography being quicker and more cost-effective imaging technique than MRI and identifying vulnerable carotid plaque features.

Background and Purpose: Only 1–2% of the internal carotid artery asymptomatic plaques are unstable as a result of >80% stenosis. Thus, unnecessary efforts can be saved if these plaques can be characterized and classified into symptomatic and asymptomatic using non-invasive B-mode ultrasound. Earlier plaque tissue characterization (PTC) methods were machine learning (ML)-based, which used hand-crafted features that yielded lower accuracy and unreliability. The proposed study shows the role of transfer learning (TL)-based deep learning models for PTC. Methods: As pertained weights were used in the supercomputer framework, we hypothesize that transfer learning (TL) provides improved performance compared with deep learning. We applied 11 kinds of artificial intelligence (AI) models, 10 of them were augmented and optimized using TL approaches—a class of Atheromatic™ 2.0 TL (AtheroPoint™, Roseville, CA, USA) that consisted of (i–ii) Visual Geometric Group-16, 19 (VGG16, 19); (iii) Inception V3 (IV3); (iv–v) DenseNet121, 169; (vi) XceptionNet; (vii) ResNet50; (viii) MobileNet; (ix) AlexNet; (x) SqueezeNet; and one DL-based (xi) SuriNet-derived from UNet. We benchmark 11 AI models against our earlier deep convolutional neural network (DCNN) model. Results: The best performing TL was MobileNet, with accuracy and area-under-the-curve (AUC) pairs of 96.10 ± 3% and 0.961 (p < 0.0001), respectively. In DL, DCNN was comparable to SuriNet, with an accuracy of 95.66% and 92.7 ± 5.66%, and an AUC of 0.956 (p < 0.0001) and 0.927 (p < 0.0001), respectively. We validated the performance of the AI architectures with established biomarkers such as greyscale median (GSM), fractal dimension (FD), higher-order spectra (HOS), and visual heatmaps. We benchmarked against previously developed Atheromatic™ 1.0 ML and showed an improvement of 12.9%. Conclusions: TL is a powerful AI tool for PTC into symptomatic and asymptomatic plaques. [ABSTRACT FROM AUTHOR]

We estimated the value of objective, computerized texture analysis of ultrasonic images in distinguishing carotid plaques associated with neurological ipsilateral symptoms (amaurosis fugax [AmF; n = 30], transient ischemic attack [TIA; n = 52], and stroke [n = 55]) from asymptomatic plaques (n = 51). We performed 3 case-control studies (1/symptom with asymptomatic plaques as control). On logistic regression, AmF was independently associated with severity of stenosis, percentage of pixels with gray levels 0 to 10 (PPCS1; measure of echolucency), and spatial gray level dependence matrices (SGLDM) information measure of correlation (IMC-1; texture); TIAs with PPCS1 (echolucency), SGLDM correlation, and skewness (both texture); and stroke with PPCS1, SGLDM correlation, and percentage of pixels with gray levels 11 to 20 (PPCS2; echolucency). The area under the curve of the regression-derived predicted probability for AmF, TIA, and stroke was 0.92, 0.82, and 0.85, respectively (all P < .001). Texture analysis can identify carotid plaques associated with a neurological event, improving the diagnostic value of echolucency measures. Texture analyses could be applied to natural history studies. [ABSTRACT FROM PUBLISHER]

The Cyprus Study is a prospective cohort study of cardiovascular disease (CVD). Its aim is to determine the relationship of intima-media thickness (IMT) of the common carotid (IMTcc), maximum thickness of IMT in the carotid bifurcation (IMTmax), number of carotid and femoral bifurcations with plaque and total plaque thickness (TPT) (sum of the maximum plaque measurements taken from the four bifurcations scanned) with the prevalence of clinical CVD. A total of 767 individuals (46% male) over the age of 40 years were recruited from a mountain village and a town outside the capital Nicosia. In addition to clinical examination, carotid and common femoral bifurcations were scanned with ultrasound. After controlling for conventional risk factors, there was little evidence of an association of IMTcc with CVD prevalence. However, IMTmax and TPT were associated with 2.9-fold (1.22 to 7.07) and 6.87-fold (2.42 to 19.43) increased odds of CVD prevalence, respectively. In conclusion, the TPT and number of bifurcations with plaque are more strongly associated with the prevalence of CVD. These findings warrant investigation in prospective studies to document associations with incident CVD events. [ABSTRACT FROM AUTHOR]

Background: Unstable carotid plaques on subjective, visual, assessment using B-mode ultrasound scanning appear as echolucent and heterogeneous. Although previous studies on computer assisted plaque characterisation have standardised B-mode images for brightness, improving the objective assessment of echolucency, little progress has been made towards standardisation of texture analysis methods, which assess plaque heterogeneity. The aim of the present study was to investigate the influence of image zooming during ultrasound scanning on textural features and to test whether or not resolution standardisation decreases the variability introduced. Methods: Eighteen still B-mode images of carotid plaques were zoomed during carotid scanning (zoom factor 1.3) and both images were transferred to a PC and normalised. Using bilinear and bicubic interpolation, the original images were interpolated in a process of simulating off-line zoom using the same interpolation factor. With the aid of the colour-coded image, carotid plaques of the original, zoomed and two resampled images for each case were outlined and histogram, first order and second order statistics were subsequently calculated. Results: Most second order statistics (21/25, 84%) were significantly (p < 0.05) sensitive to image zooming during scanning, in contrast to histogram and first order statistics (4/25, 16%, p < 0.001, Fisher's exact test). Median (interquartile range) change of those features sensitive to zooming was 18.14% (4.94-28.43). Image interpolation restored these changes, the bicubic interpolation being superior compared to bilinear interpolation (p = 0.036). Conclusion: Texture analysis of ultrasonic plaques should be performed under standardised resolution settings; otherwise a resolution normalisation algorithm should be applied. [ABSTRACT FROM AUTHOR]

This article reviews the mechanisms by which micronized purified flavonoid fraction (MPFF; Dafion 500 mg) acts on symptoms as well as on edema in patients with chronic venous disease, in the light of new advances in the understanding of the pathophysiology of this chronic condition. Deterioration of venous wall tone followed by valve dysfunction leading eventually to varicose veins are the key pathophysiologic features that produce venous hypertension. Both mechanical and biological factors are responsible for the deterioration of the venous wall in large veins. These are decreased shear stress and hypoxia of the media and of the endothelium, which act as triggering factors for biochemical reactions leading to inflammation. There is a body of evidence that inflammation in chronic venous insufficiency (CVI) plays a role right from the early stages of venous dysfunction and venous valve restructuring. The whole process of venous wall stretching and dilation is painful and may present as leg heaviness, a sensation of swelling, and paresthesia. Dafion 500 mg relieves symptoms, edema, and red blood cell aggregation, which cause paresthesia and restless legs. At the level of the microcirculation, dysfunction of microvessels is observed, characterized by an increase in capillary permeability followed by skin changes. The earliest manifestation of microcirculatory disorder is edema. At this level, Daflon 500 mg acts favorably on microcirculatory complications by normalizing the synthesis of prostaglandins and free radicals. It decreases bradykinin-induced microvascular leakage and inhibits leukocyte activation, trapping, and migration. Its efficacy in decreasing CVI edema and ankle swelling has been proven in rigorous studies that are reviewed in this paper. Daflon 500 mg, a well-established oral flavonoid that consists of 90% micronized diosmin and 10% flavonoids expressed as hesperidin, may be prescribed from the very beginning of the disease for the relief of pain... [ABSTRACT FROM AUTHOR]

The current status of superficial thrombophlebitis, including incidence, diagnosis, and management, are reviewed. Treatment options are assessed in the light of data from the main studies reported in the literature. These include compression, ambulation, and nonsteroidal antiinflammatory agents and surgical management with high saphenous ligation (with or without saphenous vein stripping) with or without anticoagulants, ranging from aspirin, unfractionated heparin, warfarin, and low-molecular-weight heparin (LMWH). The advantage of the surgical approach is that by ligation with or without stripping of the superficial veins the underlying pathesis (i.e., varicose veins) is also eradicated. In the presence of deep venous thrombosis (DVT), surgery could be combined with anticoagulants. The extensive current literature for DVT treatment shows that the LMWHs are at least as effective and safe as the unfractionated heparins. On this basis, one could reasonably recommend LMWH for the treatment of superficial thrombophlebitis with involvement of the deep veins. Pentasaccharide, a drug that has been recently explored for the prophylaxis and treatment of DVT could be another option. However, there are as yet no data for recommended dosages or duration of treatment for the latter two options. [ABSTRACT FROM AUTHOR]

Compares the efficacy of endovascular sclerotherapy (ES) with surgery and surgery with sclerotherapy among patients with venous incompetence. Use of color duplex scanning to evaluate incompetence; Difference in cost between surgery alone and ES; Effectiveness of surgery and sclerotherapy for distal vein incompetence.

The authors reflect on the efficacy of statins in the treatment and prevention of venous thromboembolism (VTE). They mention several studies that were conducted to assess the effects of statins in reducing the risk of VTE. They state that the use of statin is safe in the treatment of VTE but there is need to consider the association between adherence to statin treatment and the risk of VTE.

The management of asymptomatic carotid artery stenosis (CAS) has been the subject of extensive debate. Current evidence suggests that the annual risk of stroke in patients with CAS and without previous cerebrovascular symptoms is 1% which makes carotid endarterectomy unjustifiable. Conservative treatment with statins and antiplatelets, the identification of the high risk individuals as well as aggressive life style modifications are considered sufficient measures for the protection of these patients. However, there are reasons to believe that this approach may be less effective than we think. Best medical treatment is only effective when compliance is adequate and lipid or blood pressure target levels are achieved. However this is not always the case and the same applies regarding life style modification changes such as smoking. In addition, there is no consensus regarding the identification of the high risk individuals despite recent encouraging evidence. The introduction of a structured network of risk factor modification clinics in conjunction with the vascular clinics and the identification of ways to objectively risk-stratify patients with asymptomatic CAS could enable us to optimize the management of these patients when we decide to be less radical. [ABSTRACT FROM PUBLISHER]

We propose an approach for providing well-calibrated confidence measures for determining cerebrovascular risk stratification based on characteristics from noninvasive ultrasound imaging of carotid plaques. An important challenge we address is the class imbalance problem inherent in the particular task. The proposed approach is based on a novel framework, called conformal prediction (CP), for developing techniques that output sets of predictions guaranteed to contain the true classification of a new case with a prespecified probability. We follow a modified version of the CP framework, called Label-conditional Mondrian conformal prediction (LCMCP), so that the guarantee provided by CP does not only hold for all instances together, but also hold for the instances of each class independently, thus making prediction sets unbiased. Furthermore, LCMCP is combined with an underbagging ensemble of artificial neural networks so that its outputs are based on unbiased estimates. The important positive properties of the proposed approach are demonstrated experimentally on a dataset of patients that were followed up for eight years and had asymptomatic internal carotid artery stenosis at the baseline. [ABSTRACT FROM AUTHOR]

Objective Patients with SLE have increased prevalence of clinical cardiovascular disease (CVD) and subclinical atherosclerosis. Although 30–40% of patients with SLE have vascular plaque on ultrasound scanning, this study is the first to consider the relationship between total burden of plaque and subsequent CVD risk. Methods One hundred patients with SLE and without any previous clinical CVD underwent vascular ultrasound scans of both carotid and both common femoral bifurcations between 2011 and 2013. Clinical, serological, demographic and treatment data were collected at baseline. Patients were followed till 2020 to identify those who developed new onset coronary disease or stroke. Statistical analysis to identify factors associated with increased risk of developing CVD events was carried out. Results Thirty-six patients had plaque at baseline. During follow-up five patients (all had baseline plaque) developed coronary disease and two, without baseline plaque, developed lacunar strokes. Mean (s. d.) age of these patients was 46.5 (4.5) years. Patients with three or more baseline bifurcations with plaque were 10 times more likely to develop CVD than those with 0–2 bifurcations with plaques (OR 9.9, P  = 0.009). TPA > 16mm2 was associated with six-fold increased risk of CVD (OR = 6.44, P  = 0.028). Patients with disease duration > 14 years were more likely than those with disease duration < 14 years to develop CVD (OR 8.3 P  = 0.043) Conclusions The number of bifurcations with plaque and TPA in patients with SLE may be valuable in assessing risk of CVD and deciding on clinical measures to reduce this risk. [ABSTRACT FROM AUTHOR]

Introduces the clinical research articles from the vascular research group at Chieti University and Pescara (Italy) and from St. Mary's Hospital at Imperial College in London. Contributions of doctors and researchers to an international institution; Studies by the group in Chieti University, Pescara and San Valentino; Legacy with St. Mary's Hospital.

Atherosclerosis has a long preclinical phase, and the risk of cardiovascular (CV) events may be high in asymptomatic subjects. Conventional risk factors provide information for the statistical probability of developing CV events, but they lack precision in asymptomatic subjects. This review aims to summarize the role of some widely publicized indicators of early atherosclerosis in predicting CV events. The earliest measurable indicator of the atherosclerotic process is endothelial dysfunction, measured by flow-mediated dilation (FMD) of the brachial artery. However, reduced FMD is a stronger predictor of future CV events in patients with existing CV disease than in apparently healthy persons. Alternatively, measurement of carotid artery intima-media thickness does not improve the predictive value of risk factor scores, while detection of asymptomatic atherosclerotic plaques in carotid or common femoral arteries by ultrasound indicates high CV risk. Coronary calcium is a robust and validated help in the estimation of vascular changes and risk, which may improve risk stratification beyond traditional risk factors with relatively low radiation exposure. Arterial stiffness of the aorta, measured as the carotid-femoral pulse wave velocity is an independent marker of CV risk at the population level, but it is not recommended as a routine procedure because of measurement difficulties. Low ankle-brachial index (ABI) indicates flow-limiting atherosclerosis in the lower limbs and indicates high CV risk, while normal ABI does not rule out advanced asymptomatic atherosclerosis. Novel circulating biomarkers are associated with the atherosclerotic process. However, because of limited specificity, their ability to improve risk classification at present remains low. [Display omitted] • Traditional risk factors for cardiovascular (CV) disease inform on the probability of developing atherosclerosis and related CV events. • Detecting preclinical atherosclerosis enables the identification of individuals with ongoing atherosclerosis. • Preclinical atherosclerosis can be identified by functional/morphologic deterioration of the arterial wall or by circulating biomarkers. • The predictive value of indicators of preclinical atherosclerosis for future CV events is not completely elucidated. • Ankle-brachial index, calcium score, and asymptomatic plaques may improve risk stratification for CV events beyond traditional risk factors. [ABSTRACT FROM AUTHOR]

Abstract: Introduction: The early identification of the unstable carotid plaque together with the best medical treatment, are two missing parts of the stroke-prevention puzzle. This review summarizes the available evidence on the effects of statins on carotid plaque morphology. Methods: A systematic review of the PubMed, Scopus and Cochrane Library databases was performed. Studies evaluating the effect of statins on plaque imaging features other than intima media thickness as well as on the serum inflammatory profile were eligible for inclusion. Results: Seventeen studies were eligible for inclusion. The majority of the studies used MRI and ultrasound imaging. Plaque composition (fibrous cap and lipid core size), and size (plaque area and volume) were mainly used to evaluate the changes in plaque morphology. All studies showed slower progression, remodelling or even regression of the plaque even after only 1 month of statin administration, although the type, dosage and duration of treatment varied significantly between them. Intensive statin treatment was suggested to have a more pronounced effect on plaque morphology, however, that was mainly associated with maintaining LDL-levels <100mg/mL and not with the intensity of the dosage. Seven studies measured CRP, four of which found significantly decreased levels with statin use. Conclusion: This review suggests that statins may have a beneficial effect on plaque morphology and the inflammatory response. Further validation of whether this is an LDL-associated effect or a separate pleiotropic phenomenon of statins is needed. There are significant inherent limitations to the safe extraction of solid conclusions from the studies due to data heterogeneity and publication bias. [Copyright &y& Elsevier]

The intima-media thickness (IMT) of the common carotid artery (CCA) is widely used as an early indicator of the development of cardiovascular disease (CVD). It was proposed but not thoroughly investigated that the media layer (ML) thickness (MLT), its composition, and its texture may be indicative of cardiovascular risk and for differentiating between patients with high and low risk. In this study, we investigate an automated method for segmenting the ML and the intima layer (IL) and measurement of the MLT and the intima layer thickness (ILT) in ultrasound images of the CCA. The snakes segmentation method was used and was evaluated on 100 longitudinal ultrasound images acquired from asymptomatic subjects, against manual segmentation performed by a neurovascular expert. The mean ± standard deviation (Sd) for the first and second sets of manual and the automated IMT, MLT, and ILT measurements were 0.71 ± 0.17 mm, 0.72 ± 0.17 mm, 0.67 ± 0.12 mm; 0.25 ± 0.12 mm, 0.27 ± 0.14 mm, 0.25 ± 0.11 mm; and 0.43 ± 0.10 mm, 0.44 ± 0.13 mm, and 0.42 ± 0.10 mm, respectively. There was overall no significant difference between the manual and the automated IMC, ML, and IL segmentation measurements. Therefore, the automated segmentation method proposed in this study may be used successfully in the measurement of the MLT and ILT complementing the manual measurements. MLT was also shown to increase with age (for both the manual and the automated measurements). Future research will incorporate the extraction of texture features from the segmented ML and IL bands, which may indicate the risk of future cardiovascular events. However, more work is needed for validating the proposed technique in a larger sample of subjects. [ABSTRACT FROM AUTHOR]

Objectives Patients with SLE have an increased risk of developing cardiovascular disease (CVD). Multiple studies have shown that these patients have increased numbers of carotid plaques and greater intima-media thickness (IMT) than healthy controls. Measures such as total plaque area (TPA) and plaque echogenicity may be more sensitive and more relevant to cardiovascular risk than presence of plaque and IMT alone. Our objective was to produce the first report of TPA and echogenicity in a population of patients with SLE. Methods One hundred patients with SLE and no history of clinical CVD were recruited. Clinical, serological and treatment variables were recorded and serum was tested for antibodies to apolipoprotein A-1 and high-density lipoprotein. Both carotid and both femoral artery bifurcations of each patient were scanned to determine IMT, TPA and echogenicity of plaques. Univariable and multivariable statistical analyses were carried out to define factors associated with each of these outcomes. Results Thirty-six patients had carotid and/or femoral plaque. Increasing age was associated with presence of plaque and increased IMT. Triglyceride levels were associated with presence of plaque. Mean (s. d.) TPA was 60.8 (41.6) mm2. Patients taking prednisolone had higher TPA. Most plaques were echolucent, but increased echogenicity was associated with prednisolone therapy and persistent disease activity. Conclusion TPA and plaque echogenicity in patients with SLE are associated with different factors than those associated with presence of plaque and IMT. Longitudinal studies may show whether these outcome measures add value in the management of cardiovascular risk in SLE. [ABSTRACT FROM AUTHOR]

Recent studies have suggested that textural characteristics of the intima-media complex (IMC) may be more useful than the intima-media thickness (IMT) in evaluating cardiovascular risk. The primary aim of our study was to investigate the association between texture features of the common carotid IMC and prevalent clinical cardiovascular disease (CVD). The secondary aim was to determine whether IMT and IMC texture features vary between the left and right carotid arteries. The study was performed on 2208 longitudinal-section ultrasound images of the left (L) and right (R) common carotid artery (CCA), acquired from 569 men and 535 women out of which 125 had clinical CVD. L and R sides of the IMC were intensity normalized and despeckled. The IMC was semiautomatically delineated for all images using a semiautomated segmentation system, and 61 different texture features were extracted. The corresponding IMT semiautomated measurements (mean±SD) of the L and R sides were 0.73±0.21 mm/0.69±0.19 mm for the normal population and 0.83±0.17 mm/0.79±0.18 mm for those with CVD. IMC texture features did not differ between the right- and left-hand sides. Several texture features were independent predictors of the presence of CVD. The multivariate logistic regression analysis combining age, IMT, and texture features produced a receiver operating characteristic curve with an area under the curve of 89%. A correct classification rate of 77% for separating the normal subject (NOR) versus CVD subjects was achieved using the support vector machine classifier with a combination of clinical features, IMT, and extracted texture features. Texture features provide additional information on the presence of clinical CVD, which is over and above that provided by conventional risk factors or IMT alone. The value of IMC texture features in the prediction of future cardiovascular events should be tested in prospective studies. [ABSTRACT FROM AUTHOR]

Common carotid intima-media thickness (CIMT) is a commonly used marker for atherosclerosis and is often computed in carotid ultrasound images. An analysis of different computerized techniques for CIMT measurement and their clinical impacts on the same patient data set is lacking. Here we compared and assessed five computerized CIMT algorithms against three expert analysts' manual measurements on a data set of 1088 patients from two centers. Inter- and intra-observer variability was assessed, and the computerized CIMT values were compared with those manually obtained. The CIMT measurements were used to assess the correlation with clinical parameters, cardiovascular event prediction through a generalized linear model and the Kaplan-Meier hazard ratio. CIMT measurements obtained with a skilled analyst's segmentation and the computerized segmentation were comparable in statistical analyses, suggesting they can be used interchangeably for CIMT quantification and clinical outcome investigation. To facilitate future studies, the entire data set used is made publicly available for the community at http://dx.doi.org/10.17632/fpv535fss7.1. [ABSTRACT FROM AUTHOR]

The LONFLIT1/2 studies have established that in high-risk subjects after long (> 10 hours) flights the incidence of deep venous thrombosis (DVT) may be between 4% and 6%. The LONFLIT4 study was aimed at evaluating the control of edema and DVT prevention in Iowmedium-risk subjects. In this study prophylaxis of edema with specific travel stockings was evaluated in 2 separate studies involving flights lasting 7 hours and 10-12 hours. Part I. Subjects at Iow-medium risk for DVT were contacted; 55 subjects were excluded for several nonmedical, travel-related problems or inconvenient evaluation time; the remaining 211 were randomized into 2 groups to evaluate prophylaxis with elastic stockings in 7-8-hour, longhaul flights. The control group had no prophylaxis; the treatment group used below-knee, Sigvaris Traveno elastic stockings (Ganzoni, Switzerland, producing 12-18 mm Hg of pressure at the ankle). Color duplex scanning was used to evaluate the possible presence of DVT; edema/swelling were evaluated with a composite score including the presence of edema (with an edema tester), variations in ankle circumference and leg volumetry, subjective swelling, and discomfort (scale ranging from 0 to 10). Results: Of the 103 included subjects in the stockings group and 108 in the control group (total 211), 195 subjects completed the study. Dropouts (16) were due to low compliance or traveling and connection problems. Age, sex distribution, and risk factors distributions were comparable in the 2 groups. Stockings Group: Of 97 subjects none had DVT or superficial thromboses. Control Group: Of 98 subjects none had thrombosis. The level of edema at inclusion was comparable in the 2 groups of subjects. After flights there was an average score of 6.4 (1.3) in the control group, while in the stockings group the score was on average 2.4 (SD 1), 2.6 times lower than in the control group (p < 0.05). In the control group 83% of the subjects had an evident increase in ankle... [ABSTRACT FROM AUTHOR]

Compares the protective effects of low-molecular-weight heparin and aspirin for deep venous thrombosis (DVT) prevention in high-risk subjects in long-haul flights. Risk factors for DVT; Association between prolonged travel, DVT and pulmonary embolism; Percentage of recorded medical episodes in flight; Evidence of mild gastrointestinal symptoms in subjects taking aspirin.

Part III. Presents the management of and the role of several factors on stroke. Information regarding stroke; Discussion on thrombolysis, anticoagulant agents and prophylactic neuroprotection with pharmacologic agents; Relation with carotid endarterectomy, bypass surgery, carotid artery angioplasty and stenting; Treatment of cerebral hemorrhage; Means and possibilities of rehabilitation.

Wilson's disease (WD) is caused by copper accumulation in the brain and liver, and if not treated early, can lead to severe disability and death. WD has shown white matter hyperintensity (WMH) in the brain magnetic resonance scans (MRI) scans, but the diagnosis is challenging due to (i) subtle intensity changes and (ii) weak training MRI when using artificial intelligence (AI). Design and validate seven types of high-performing AI-based computer-aided design (CADx) systems consisting of 3D optimized classification, and characterization of WD against controls. We propose a "conventional deep convolution neural network" (cDCNN) and an "improved DCNN" (iDCNN) where rectified linear unit (ReLU) activation function was modified ensuring "differentiable at zero." Three-dimensional optimization was achieved by recording accuracy while changing the CNN layers and augmentation by several folds. WD was characterized using (i) CNN-based feature map strength and (ii) Bispectrum strengths of pixels having higher probabilities of WD. We further computed the (a) area under the curve (AUC), (b) diagnostic odds ratio (DOR), (c) reliability, and (d) stability and (e) benchmarking. Optimal results were achieved using 9 layers of CNN, with 4-fold augmentation. iDCNN yields superior performance compared to cDCNN with accuracy and AUC of 98.28 ± 1.55, 0.99 (p < 0.0001), and 97.19 ± 2.53%, 0.984 (p < 0.0001), respectively. DOR of iDCNN outperformed cDCNN fourfold. iDCNN also outperformed (a) transfer learning–based "Inception V3" paradigm by 11.92% and (b) four types of "conventional machine learning–based systems": k-NN, decision tree, support vector machine, and random forest by 55.13%, 28.36%, 15.35%, and 14.11%, respectively. The AI-based systems can potentially be useful in the early WD diagnosis. [ABSTRACT FROM AUTHOR]

This study developed an office-based cardiovascular risk calculator using a machine learning (ML) algorithm that utilized a focused carotid ultrasound. The design of this study was divided into three steps. The first step involved collecting 18 office-based biomarkers consisting of six clinical risk factors (age, sex, body mass index, systolic blood pressure, diastolic blood pressure, and smoking) and 12 carotid ultrasound image-based phenotypes. The second step consisted of the design of an ML-based cardiovascular risk calculator-called “AtheroEdge Composite Risk Score 2.0” (AECRS2.0ML) for risk stratification, considering chronic kidney disease (CKD) as the surrogate endpoint of cardiovascular disease. The last step consisted of comparing AECRS2.0ML against the currently utilized office-based CVD calculators, namely the Framingham risk score (FRS) and the World Health Organization (WHO) risk scores. A cohort of 379 Asian-Indian patients with type-2 diabetes mellitus, hypertension, and chronic kidney disease (stage 1 to 5) were recruited for this cross-sectional study. From this retrospective cohort, 758 ultrasound scan images were acquired from the far walls of the left and right common carotid arteries [mean age = 55 ± 10.8 years, 67.28% males, 91.82% diabetic, 86.54% hypertensive, and 83.11% with CKD]. The mean office-based cardiovascular risk estimates using FRS and WHO calculators were 26% and 19%, respectively. AECRS2.0ML demonstrated a better risk stratification ability having a higher area-under-the-curve against FRS and WHO by ~30% (0.871 vs. 0.669) and ~ 20% (0.871 vs. 0.727), respectively. The office-based machine-learning cardiovascular risk-stratification tool (AECRS2.0ML) shows superior performance compared to currently available conventional cardiovascular risk calculators. [ABSTRACT FROM AUTHOR]

The objectives of this study are to (1) examine the "10-year cardiovascular risk" in the common carotid artery (CCA) versus carotid bulb using an integrated calculator called "AtheroEdge Composite Risk Score 2.0" (AECRS2.0) and (2) evaluate the performance of AECRS2.0 against "conventional cardiovascular risk calculators." These objectives are met by measuring (1) image-based phenotypes and AECRS2.0 score computation and (2) performance evaluation of AECRS2.0 against 12 conventional cardiovascular risk calculators. The Asian–Indian cohort (n = 379) with type 2 diabetes mellitus (T2DM), chronic kidney disease (CKD), or hypertension were retrospectively analyzed by acquiring the 1516 carotid ultrasound scans (mean age: 55 ± 10.1 years, 67% males, ∼92% with T2DM, ∼83% with CKD [stage 1-5], and 87.5% with hypertension [stage 1-2]). The carotid bulb showed a higher 10-year cardiovascular risk compared to the CCA by 18% (P <.0001). Patients with T2DM and/or CKD also followed a similar trend. The carotid bulb demonstrated a superior risk assessment compared to CCA in patients with T2DM and/or CKD by showing: (1) ∼13% better than CCA (0.93 vs 0.82, P =.0001) and (2) ∼29% better compared with 12 types of risk conventional calculators (0.93 vs 0.72, P =.06). [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article "Stenting Versus Endarterectomy for Treatment of Carotid-Artery Stenosis," by T. G. Brott, R. W. Hobson II, G. Howard et al. that was published in the July 1, 2010 issue of the "New England Journal of Medicine."

We evaluated the association between automatically measured carotid total plaque area (TPA) and the estimated glomerular filtration rate (eGFR), a biomarker of chronic kidney disease (CKD). Automated average carotid intima–media thickness (cIMTave) and TPA measurements in carotid ultrasound (CUS) were performed using AtheroEdge (AtheroPoint). Pearson correlation coefficient (CC) was then computed between the TPA and eGFR for (1) males versus females, (2) diabetic versus nondiabetic patients, and (3) between the left and right carotid artery. Overall, 339 South Asian Indian patients with either type 2 diabetes mellitus (T2DM) or CKD, or hypertension (stage 1 or stage 2) were retrospectively analyzed by acquiring cIMTave and TPA measurements of their left and right common carotid arteries (CCA; total CUS: 678, mean age: 54.2 ± 9.8 years; 75.2% males; 93.5% with T2DM). The CC between TPA and eGFR for different scenarios were (1) for males and females −0.25 (P <.001) and −0.35 (P <.001), respectively; (2) for T2DM and non-T2DM −0.26 (P <.001) and −0.49 (P =.02), respectively, and (3) for left and right CCA −0.25 (P <.001) and −0.23 (P <.001), respectively. Automated TPA is an equally reliable biomarker compared with cIMTave for patients with CKD (with or without T2DM) with subclinical atherosclerosis. [ABSTRACT FROM AUTHOR]

Today, the 10-year cardiovascular risk largely relies on conventional cardiovascular risk factors (CCVRFs) and suffers from the effect of atherosclerotic wall changes. In this study, we present a novel risk calculator AtheroEdge Composite Risk Score (AECRS1.0), designed by fusing CCVRF with ultrasound image-based phenotypes. Ten-year risk was computed using the Framingham Risk Score (FRS), United Kingdom Prospective Diabetes Study 56 (UKPDS56), UKPDS60, Reynolds Risk Score (RRS), and pooled composite risk (PCR) score. AECRS1.0 was computed by measuring the 10-year five carotid phenotypes such as IMT (ave., max., min.), IMT variability, and total plaque area (TPA) by fusing eight CCVRFs and then compositing them. AECRS1.0 was then benchmarked against the five conventional cardiovascular risk calculators by computing the receiver operating characteristics (ROC) and area under curve (AUC) values with a 95% CI. Two hundred four IRB-approved Japanese patients' left/right common carotid arteries (407 ultrasound scans) were collected with a mean age of 69 ± 11 years. The calculators gave the following AUC: FRS, 0.615; UKPDS56, 0.576; UKPDS60, 0.580; RRS, 0.590; PCRS, 0.613; and AECRS1.0, 0.990. When fusing CCVRF, TPA reported the highest AUC of 0.81. The patients were risk-stratified into low, moderate, and high risk using the standardized thresholds. The AECRS1.0 demonstrated the best performance on a Japanese diabetes cohort when compared with five conventional calculators. Graphical abstract AECRS1.0: Carotid ultrasound image phenotype-based 10-year cardiovascular risk calculator. The figure provides brief overview of the proposed carotid image phenotype-based 10-year cardiovascular risk calculator called AECRS1.0. AECRS1.0 was also benchmarked against five conventional cardiovascular risk calculators (Framingham Risk Score (FRS), United Kingdom Prospective Diabetes Study 56 (UKPDS56), UKPDS60, Reynolds Risk Score (RRS), and pooled composite risk (PCR) score). [ABSTRACT FROM AUTHOR]

The advent of Deep Learning (DL) is poised to dramatically change the delivery of healthcare in the near future. Not only has DL profoundly affected the healthcare industry it has also influenced global businesses. Within a span of very few years, advances such as self-driving cars, robots performing jobs that are hazardous to human, and chat bots talking with human operators have proved that DL has already made large impact on our lives. The open source nature of DL and decreasing prices of computer hardware will further propel such changes. In healthcare, the potential is immense due to the need to automate the processes and evolve error free paradigms. The sheer quantum of DL publications in healthcare has surpassed other domains growing at a very fast pace, particular in radiology. It is therefore imperative for the radiologists to learn about DL and how it differs from other approaches of Artificial Intelligence (AI). The next generation of radiology will see a significant role of DL and will likely serve as the base for augmented radiology (AR). Better clinical judgement by AR will help in improving the quality of life and help in life saving decisions, while lowering healthcare costs. A comprehensive review of DL as well as its implications upon the healthcare is presented in this review. We had analysed 150 articles of DL in healthcare domain from PubMed, Google Scholar, and IEEE EXPLORE focused in medical imagery only. We have further examined the ethic, moral and legal issues surrounding the use of DL in medical imaging. [ABSTRACT FROM AUTHOR]

Manual ultrasound (US)-based methods are adapted for lumen diameter (LD) measurement to estimate the risk of stroke but they are tedious, error prone, and subjective causing variability. We propose an automated deep learning (DL)-based system for lumen detection. The system consists of a combination of two DL systems: encoder and decoder for lumen segmentation. The encoder employs a 13-layer convolution neural network model (CNN) for rich feature extraction. The decoder employs three up-sample layers of fully convolution network (FCN) for lumen segmentation. Three sets of manual tracings were used during the training paradigm leading to the design of three DL systems. Cross-validation protocol was implemented for all three DL systems. Using the polyline distance metric, the precision of merit for three DL systems over 407 US scans was 99.61%, 97.75%, and 99.89%, respectively. The Jaccard index and Dice similarity of DL lumen segmented region against three ground truth (GT) regions were 0.94, 0.94, and 0.93 and 0.97, 0.97, and 0.97, respectively. The corresponding AUC for three DL systems was 0.95, 0.91, and 0.93. The experimental results demonstrated superior performance of proposed deep learning system over conventional methods in literature. Graphical abstract ᅟ. [ABSTRACT FROM AUTHOR]

Motivation: This study presents a novel nonlinear model which can predict 10‐year carotid ultrasound image‐based phenotypes by fusing nine traditional cardiovascular risk factors (ethnicity, gender, age, artery type, body mass index, hemoglobin A1c, hypertension, low‐density lipoprotein, and smoking) with five types of carotid automated image phenotypes (three types of carotid intima‐media thickness (IMT), wall variability, and total plaque area). Methodology: Two‐step process was adapted: First, five baseline carotid image‐based phenotypes were automatically measured using AtheroEdge™ (AtheroPoint™, CA, USA) system by two operators (novice and experienced) and an expert. Second, based on the annual progression rates of cIMT due to nine traditional cardiovascular risk factors, a novel nonlinear model was adapted for 10‐year predictions of carotid phenotypes. Results: Institute review board (IRB) approved 204 Japanese patients' left/right common carotid artery (407 ultrasound scans) was collected with a mean age of 69 ± 11 years. Age and hemoglobin were reported to have a high influence on the 10‐year carotid phenotypes. Mean correlation coefficient (CC) between 10‐year carotid image‐based phenotype and age was improved by 39.35% in males and 25.38% in females. The area under the curves for the 10‐year measurements of five phenotypes IMTave10yr, IMTmax10yr, IMTmin10yr, IMTV10yr, and TPA10yr were 0.96, 0.94, 0.90, 1.0, and 1.0. Inter‐operator variability between two operators showed significant CC (P < 0.0001). Conclusions: A nonlinear model was developed and validated by fusing nine conventional CV risk factors with current carotid image‐based phenotypes for predicting the 10‐year carotid ultrasound image‐based phenotypes which may be used risk assessment. [ABSTRACT FROM AUTHOR]

Background and objective Accurate, reliable, efficient, and precise measurements of the lumen geometry of the common carotid artery (CCA) are important for (a) managing the progression/regression of atherosclerotic build-up and (b) the risk of stroke. The image-based degree of stenosis in the carotid artery and the plaque burden can be predicted using the automated carotid lumen diameter (LD)/inter-adventitial diameter (IAD) measurements from B-mode ultrasound images. The objective of this review is to present the state-of-the-art methods and systems for the measurement of LD/IAD in CCA based on automated or semi-automated strategies. Further, the performance of these systems is compared based on various metrics for its measurements. Methods The automated algorithms proposed for the segmentation of carotid lumen are broadly classified into two different categories as: region-based and boundary-based. These techniques are discussed in detail specifying their pros and cons. Further, we discuss the challenges encountered in the segmentation process along with its quantitative assessment. Lastly, we present stenosis quantification and risk stratification strategies. Results Even though, we have found more boundary-based approaches compared to region-based approaches in the literature, however, the region-based strategy yield more satisfactory performance. Novel risk stratification strategies are presented. On a patient database containing 203 patients, 9 patients are identified as high risk patients, whereas 27 patients are identified as medium risk patients. Conclusions We have presented different techniques for the lumen segmentation of the common carotid artery from B-mode ultrasound images and measurement of lumen diameter and inter-adventitial diameter. We believe that the issue regarding boundary-based techniques can be compensated by taking regional statistics embedded with boundary-based information. [ABSTRACT FROM AUTHOR]

Aim: The study investigated the association of carotid ultrasound echolucent plaque-based biomarker with HbA1c, measured as age-adjusted grayscale median (AAGSM) as a function of chronological age, total plaque area, and conventional grayscale median (GSMconv).Methods: Two stages were developed: (a) automated measurement of carotid parameters such as total plaque area (TPA); (b) computing the AAGSM as a function of GSMconv, age, and TPA. Intra-operator (novice and experienced) analysis was conducted.Results: IRB approved, 204 patients' left/right CCA (408 images) ultrasound scans were collected: mean age: 69 ± 11 years; mean HbA1c: 6.12 ± 1.47%. A moderate inverse correlation was observed between AAGSM and HbA1c (CC of -0.13, P = 0.01), compared to GSM (CC of -0.06, P = 0.24). The RCCA and LCCA showed CC of -0.18, P < 0.01 and -0.08; P < 0.24. Female and males showed CC of -0.29, P < 0.01 and -0.10, P = 0.09. Using the threshold for AAGSM and HbA1c as: low-risk (AAGSM > 100; HbA1c < 5.7%), moderate-risk (40 < AAGSM < 100; 5.7% < HbA1c < 6.5%) and high-risk (AAGSM < 40; HbA1c > 6.5%), the area under the curve showed a better performance of AAGSM over GSMconv. A paired t-test between operators and expert (P < 0.0001); inter-operator CC of 0.85 (P < 0.0001).Conclusions: Echolucent plaque in patients with diabetes can be more accurately characterized for risk stratification using AAGSM compared to GSMconv. [ABSTRACT FROM AUTHOR]

Monitoring of cerebrovascular diseases via carotid ultrasound has started to become a routine. The measurement of image-based lumen diameter (LD) or inter-adventitial diameter (IAD) is a promising approach for quantification of the degree of stenosis. The manual measurements of LD/IAD are not reliable, subjective and slow. The curvature associated with the vessels along with non-uniformity in the plaque growth poses further challenges. This study uses a novel and generalized approach for automated LD and IAD measurement based on a combination of spatial transformation and scale-space. In this iterative procedure, the scale-space is first used to get the lumen axis which is then used with spatial image transformation paradigm to get a transformed image. The scale-space is then reapplied to retrieve the lumen region and boundary in the transformed framework. Then, inverse transformation is applied to display the results in original image framework. Two hundred and two patients' left and right common carotid artery (404 carotid images) B-mode ultrasound images were retrospectively analyzed. The validation of our algorithm has done against the two manual expert tracings. The coefficient of correlation between the two manual tracings for LD was 0.98 (p < 0.0001) and 0.99 (p < 0.0001), respectively. The precision of merit between the manual expert tracings and the automated system was 97.7 and 98.7%, respectively. The experimental analysis demonstrated superior performance of the proposed method over conventional approaches. Several statistical tests demonstrated the stability and reliability of the automated system. [ABSTRACT FROM AUTHOR]

Severe atherosclerosis disease in carotid arteries causes stenosis which in turn leads to stroke. Machine learning systems have been previously developed for plaque wall risk assessment using morphology-based characterization. The fundamental assumption in such systems is the extraction of the grayscale features of the plaque region. Even though these systems have the ability to perform risk stratification, they lack the ability to achieve higher performance due their inability to select and retain dominant features. This paper introduces a polling-based principal component analysis (PCA) strategy embedded in the machine learning framework to select and retain dominant features, resulting in superior performance. This leads to more stability and reliability. The automated system uses offline image data along with the ground truth labels to generate the parameters, which are then used to transform the online grayscale features to predict the risk of stroke. A set of sixteen grayscale plaque features is computed. Utilizing the cross-validation protocol (K = 10), and the PCA cutoff of 0.995, the machine learning system is able to achieve an accuracy of 98.55 and 98.83%corresponding to the carotidfar wall and near wall plaques, respectively. The corresponding reliability of the system was 94.56 and 95.63%, respectively. The automated system was validated against the manual risk assessment system and the precision of merit for same cross-validation settings and PCA cutoffs are 98.28 and 93.92%for the far and the near wall, respectively.PCA-embedded morphology-based plaque characterization shows a powerful strategy for risk assessment and can be adapted in clinical settings. [ABSTRACT FROM AUTHOR]

Background and objectives Standardization of the carotid IMT requires a reference marker in ultrasound scans. It has been shown previously that manual reference marker and manually created carotid segments are used for measuring IMT in these segments. Manual methods are tedious, time consuming, subjective, and prone to errors. Bulb edge can be considered as a reference marker for measurements of the cIMT. However, bulb edge can be difficult to locate in ultrasound scans due to: (a) low signal to noise ratio in the bulb region as compared to common carotid artery region; (b) uncertainty of bulb location in craniocaudal direction; and (c) variability in carotid bulb shape and size. This paper presents an automated system (a class of AtheroEdge™ system from AtheroPoint™, Roseville, CA, USA) for locating the bulb edge as a reference marker and further develop segmental-IMT (sIMT) which measures IMT in 10 mm segments (namely: s1, s2 and s3) proximal to the bulb edge. Methods The patented methodology uses an integrated approach which combines carotid geometry and pixel-classification paradigms. The system first finds the bulb edge and then measures the sIMT proximal to the bulb edge. The system also estimates IMT in bulb region (bIMT). The 649 image database consists of varying plaque (light, moderate to heavy), image resolutions, shapes, sizes and ethnicity. Results Our results show that the IMT contributions in different carotid segments are as follows: bulb-IMT 34%, s1-IMT 29.46%, s2-IMT 11.48%, and s3-IMT 12.75%, respectively. We compare our automated results against reader's tracings demonstrating the following performance: mean lumen-intima error: 0.01235 ± 0.01224 mm, mean media-adventitia error: 0.020933 ± 0.01539 mm and mean IMT error: 0.01063 ± 0.0031 mm. Our system's Precision of Merit is: 98.23%, coefficient of correlation between automated and Reader's IMT is: 0.998 ( p -value < 0.0001). These numbers are improved compared to previous publications by Suri's group which is automated multi-resolution conventional cIMT. Conclusions Our fully automated bulb detection system reports 92.67% precision against ideal bulb edge locations as marked by the reader in the bulb transition zone. [ABSTRACT FROM AUTHOR]

Background and objective Fast intravascular ultrasound (IVUS) video processing is required for calcium volume computation during the planning phase of percutaneous coronary interventional (PCI) procedures. Nonlinear multiresolution techniques are generally applied to improve the processing time by down-sampling the video frames. Methods This paper presents four different segmentation methods for calcium volume measurement, namely Threshold-based, Fuzzy c-Means (FCM), K-means, and Hidden Markov Random Field (HMRF) embedded with five different kinds of multiresolution techniques (bilinear, bicubic, wavelet, Lanczos, and Gaussian pyramid). This leads to 20 different kinds of combinations. IVUS image data sets consisting of 38,760 IVUS frames taken from 19 patients were collected using 40 MHz IVUS catheter (Atlantis® SR Pro, Boston Scientific®, pullback speed of 0.5 mm/sec.). The performance of these 20 systems is compared with and without multiresolution using the following metrics: (a) computational time; (b) calcium volume; (c) image quality degradation ratio; and (d) quality assessment ratio. Results Among the four segmentation methods embedded with five kinds of multiresolution techniques, FCM segmentation combined with wavelet-based multiresolution gave the best performance. FCM and wavelet experienced the highest percentage mean improvement in computational time of 77.15% and 74.07%, respectively. Wavelet interpolation experiences the highest mean precision-of-merit (PoM) of 94.06 ± 3.64% and 81.34 ± 16.29% as compared to other multiresolution techniques for volume level and frame level respectively. Wavelet multiresolution technique also experiences the highest Jaccard Index and Dice Similarity of 0.7 and 0.8, respectively. Multiresolution is a nonlinear operation which introduces bias and thus degrades the image. The proposed system also provides a bias correction approach to enrich the system, giving a better mean calcium volume similarity for all the multiresolution-based segmentation methods. After including the bias correction, bicubic interpolation gives the largest increase in mean calcium volume similarity of 4.13% compared to the rest of the multiresolution techniques. The system is automated and can be adapted in clinical settings. Conclusions We demonstrated the time improvement in calcium volume computation without compromising the quality of IVUS image. Among the 20 different combinations of multiresolution with calcium volume segmentation methods, the FCM embedded with wavelet-based multiresolution gave the best performance. [ABSTRACT FROM AUTHOR]

Background and objective Percutaneous coronary interventional procedures need advance planning prior to stenting or an endarterectomy. Cardiologists use intravascular ultrasound (IVUS) for screening, risk assessment and stratification of coronary artery disease (CAD). We hypothesize that plaque components are vulnerable to rupture due to plaque progression. Currently, there are no standard grayscale IVUS tools for risk assessment of plaque rupture. This paper presents a novel strategy for risk stratification based on plaque morphology embedded with principal component analysis (PCA) for plaque feature dimensionality reduction and dominant feature selection technique. The risk assessment utilizes 56 grayscale coronary features in a machine learning framework while linking information from carotid and coronary plaque burdens due to their common genetic makeup. Method This system consists of a machine learning paradigm which uses a support vector machine (SVM) combined with PCA for optimal and dominant coronary artery morphological feature extraction. Carotid artery proven intima-media thickness (cIMT) biomarker is adapted as a gold standard during the training phase of the machine learning system. For the performance evaluation, K -fold cross validation protocol is adapted with 20 trials per fold. For choosing the dominant features out of the 56 grayscale features, a polling strategy of PCA is adapted where the original value of the features is unaltered. Different protocols are designed for establishing the stability and reliability criteria of the coronary risk assessment system (cRAS). Results Using the PCA-based machine learning paradigm and cross-validation protocol, a classification accuracy of 98.43% (AUC 0.98) with K = 10 folds using an SVM radial basis function (RBF) kernel was achieved. A reliability index of 97.32% and machine learning stability criteria of 5% were met for the cRAS. Conclusions This is the first Computer aided design (CADx) system of its kind that is able to demonstrate the ability of coronary risk assessment and stratification while demonstrating a successful design of the machine learning system based on our assumptions. [ABSTRACT FROM AUTHOR]

Embedding of diagnostic and health care information requires secure encryption and watermarking. This research paper presents a comprehensive study for the behavior of some well established watermarking algorithms in frequency domain for the preservation of stroke-based diagnostic parameters. Two different sets of watermarking algorithms namely: two correlation-based (binary logo hiding) and two singular value decomposition (SVD)-based (gray logo hiding) watermarking algorithms are used for embedding ownership logo. The diagnostic parameters in atherosclerotic plaque ultrasound video are namely: (a) bulb identification and recognition which consists of identifying the bulb edge points in far and near carotid walls; (b) carotid bulb diameter; and (c) carotid lumen thickness all along the carotid artery. The tested data set consists of carotid atherosclerotic movies taken under IRB protocol from University of Indiana Hospital, USA-AtheroPoint™ (Roseville, CA, USA) joint pilot study. ROC (receiver operating characteristic) analysis was performed on the bulb detection process that showed an accuracy and sensitivity of 100 % each, respectively. The diagnostic preservation (DP) for SVD-based approach was above 99 % with PSNR (Peak signal-to-noise ratio) above 41, ensuring the retention of diagnostic parameter devalorization as an effect of watermarking. Thus, the fully automated proposed system proved to be an efficient method for watermarking the atherosclerotic ultrasound video for stroke application. [ABSTRACT FROM AUTHOR]