Search

Previous studies have confirmed the key mechanism by which SARS-CoV-2 enters human cells. It is well established that ACE2 is the receptor that can mark the beginning of the infection. In light of this, the organs that express higher levels of ACE2 are generally considered at higher risk, while those with lower levels should be somehow more protected. This - if related to the scarcity of ace2-expressing cells in the brain - seems to contrast with the presence of a variety of neurological symptoms that follow infection with ace2. The aim of this work was to analyze ACE2 expression in the human brain, focusing on the choroid plexuses.Twenty brain samples were obtained at autopsy from ten human fetuses and from ten adult subjects. All samples were selected to contain the choroid plexus. Specimens were fixed in 10% formalin, routinely processed and paraffin embedded. 5-micron sections were stained with Hematoxylin and Eosin (HE) and immunostained with a commercial anti-human ACE2 rabbit monoclonal antibody at 1:100 dilution.We analyzed 20 samples by immunohistochemistry, and we noted that, as far as fetal samples are concerned, a strong reactivity for ACE2 was detected in the myxoid stroma of the choroid plexuses and in the endothelial cells in fetuses. The complete absence of the ACE2 marker was detected in epithelial cells, neurons and glial cells of the cerebral cortex, both in fetuses and in adults. Whereas a strong but selective reactivity for ACE2 was also detected in adult choroid plexuses, mainly localized in the endothelial cells of the choroid capillaries.Our study shows a strong expression of ACE in the fetal and adult brain choroid plexuses. This new histopathological finding may clarify the susceptibility of the human brain to SARS-COV-2 infection. Our data indicate the choroid plexus as the entry gate of virus for in the human brain; therefore, the entrance of SARS-CoV-2 into the cerebrospinal fluid through the choroid plexuses might represent the mechanism utilized by this coronavirus to cause direct injury to brain cells.

Vaccine-induced immune thrombotic thrombocytopenia (VITT) is a rare new syndrome occurring after the ChAdOx1 nCoV-19 vaccine immunization. Patients with VITT are characterized by a variable clinical presentation, likewise also the outcome of these patients is very variable. Here we report the lung ultrastructural findings in the course of VITT of a 58-year-old male patient. Alveoli were mainly dilated, irregular in shape, and occupied by a reticular network of fibrin, while interalveolar septa appeared thickened. The proliferation of small capillaries gave rise to plexiform structures and pulmonary capillary hemangiomatosis-like features. Near the alveoli occupied by a dense fibrin network, the medium-sized arteries showed a modified wall and an intraluminal thrombus. This scenario looks quite similar to that found during COVID-19, where the lungs suffer from the attack of the antigen-antibodies complexes and the virus respectively. In both diseases, the final outcome is a severe inflammation, activation of the haemostatic system and fibrinolysis.

The ongoing Coronavirus pandemic (COVID-19) showed similar characteristics with the severe acute respiratory syndrome (SARS). In the most compromised cases, COVID-19 infection leads to death due to severe respiratory complications. COVID-19-related acute respiratory distress syndrome (ARDS) is the primary cause of death in these patients. In the present study, we show an ultrastructural analysis on the lungs of a patient affected by COVID-19.Lung specimens obtained at autopsy from a 63-years old patient affected by COVID-19 were fixed in 1% paraformaldehyde. Slices of 300 µm thickness were dehydrated and dried by Critical Point Drying in CO2. Slices were covered with a conductive gold film approximately 30 nm thick and observed at a Zeiss Sigma 300 SEM FEG in the secondary electron (SE) and backscattered electron (BSE) modes. As case control a lung biopsy from a 60-year-old man was considered.At low power in all COVID-19 lung specimens severe changes in the pulmonary architecture were found, due to the collapse of air spaces. Moreover, alveolar cavities were covered by large membranes. At high power, alveolar membranes showed a fibrillar structure, suggestive of a loose network of fibrin. It has been also found that intra-alveolar red blood cells were frequently present in the alveolar spaces, surrounded by a reticular fibrin network, suggestive for fibrin-hemorrhagic alveolitis. Alveolar changes were constantly associated with pathological features related to the pulmonary vessels. Vascular changes were prominent, including endothelial damage and thrombosis of large pulmonary vessels. Fibrinous microthrombi were frequently detected in the inter-alveolar septal capillaries. In addition, it has been frequently detected capillary proliferation in the alveolar septa with finding suggestive for intussusceptive neo-angiogenesis.In conclusion, our electron microscopy analysis showed that COVID-19-related lung disease is characterized by a substantial architectural distortion, with the interactions between alveolar and vascular changes. Intra-alveolar hyaline membranes are associated with macro- and micro-thrombotic angiopathy, ending with capillary proliferation. The new blood vessel formation originates from the septa and extends into the surrounding parenchyma. Our findings confirm previous reports on the specificity of the multiple and complex morphological pattern typical, and apparently specific, of COVID-19-related lung disease.

The risk stratification of young adults between subjects who will develop a mild form of atherosclerosis and subjects who will undergo a severe disease remains inaccurate. In the eighties of the previous century, David JP Barker has demonstrated the relationship between fetal conditions and occurrence of pathologies in adulthood. In this paper, the multiple evidence that might explain the increased susceptibility to severe forms of atherosclerosis, including stroke and cardiac infarct, in subjects who underwent intrauterine growth restriction (IUGR) will be analyzed. Specifically, we will review those inter-connected data indicating an association between a low weight at birth and an adult phenotype which might favor a severe outcome of atherosclerosis. Young and adult subjects born too small (IUGR) or too early (pre-terms) might represent a subgroup of "at risk subjects", more susceptible toward severe forms of atherosclerosis. Given that low birth weight (LBW) may be considered a surrogate of IUGR, this phenotypic feature could be considered among those indispensable clinical data collected in every patient presenting with atherosclerosis, irrespectively of age. According to the hypothesis that structural arterial changes might represent the link between LBW and susceptibility to atherosclerosis later in life, we suggest that the prevention of atherosclerosis should begin at birth. Regenerative and physiological substances such as thymosin Beta-4 could be challenged for a new "arterial regenerative medicine" in the perinatal period. The goal of this new approach should be the reinforcement of the structure of the arterial wall, allowing LBW newborns to avoid the most severe complications of atherosclerosis later in life: a dream that our research could contribute to bringing to life.

Arterial thromboembolic complications reported in patients with COVID-19 infection suggested that SARS-CoV-2 can trigger atherosclerotic plaque vulnerability. While endothelial cells in healthy subjects protect against thrombus formation, after injury they show prothrombotic activity. In addition, it has been hypothesized that "cytokine storm" might stimulate the production of neo-platelets triggering an abnormal "immunothrombosis" responsible for the hypercoagulable state induced in COVID-19 patients. The aim of this study is to report a case of severe COVID-19 infection characterized by the occurrence of microthrombosis in the vasa vasorum of the aorta. A 67-year-old male patient, in good health status and without comorbidities, who underwent a severe COVID-19 infection with fatal outcome, showed scattered aortic atherosclerotic plaques, characterized by multiple occlusive micro-thromboses in the vasa vasorum, spread out lymphocytic infiltrates and foci of endotheliitis and endothelial detachment. This case report confirms the previously described thrombotic involvement of vasa vasorum in COVID-19. The occurrence of the synchronous damage involving both the lumen surface (endothelial dysfunction, endotheliitis and endothelial detachment) and the adventitia (inflammation and occlusive thrombosis of vasa vasorum) could be the key points related to the fatal outcome of the SARS-CoV-2 patients. In our opinion, vasa vasorum thrombosis may thus initiate an atherogenic process that could be characterized by a much more rapid development.

Liver injury has been reported in patients with COVID-19. This condition is characterized by severe outcome and could be related with the ability of SARS-CoV-2 to activate cytotoxic T cells. The purpose of this study is to show the histological and scanning electron microscopy features of liver involvement in COVID-19 to characterize the liver changes caused by the activation of multiple molecular pathways following this infection.Liver biopsies from 4 patients (3 post-mortems and 1 in vivo) with COVID-19 were analyzed with histology and by scanning electron microscopy.The liver changes showed significant heterogeneity. The first case showed ground glass hepatocytes and scattered fibrin aggregates in the sinusoidal lumen. The second evidenced intra-sinusoidal thrombi. The third was characterized by sinusoidal dilatation, atrophy of hepatocytes, Disse's spaces dilatation and intra-sinusoidal aggregates of fibrin and red blood cells. The fourth case exhibited diffuse fibrin aggregates in the dilated Disse spaces and microthrombi in the sinusoidal lumen.In COVID-19-related liver injury, a large spectrum of pathological changes was observed. The most peculiar features were very mild inflammation, intra-sinusoidal changes, including sinusoidal dilatation, thrombotic sinusoiditis and diffuse intra-sinusoidal fibrin deposition. These findings suggested that a thrombotic sinusoiditis followed by a local diffuse intra-vascular (intra-sinusoidal) coagulation could be the typical features of the SARS-CoV-2-related liver injury.

The risk stratification of young adults between subjects who will develop a mild form COVID-19 and subjects who will undergo a severe disease remains inaccurate. In this review, we propose that the Barker hypothesis might explain the increased susceptibility to severe forms of COVID-19 in subjects who underwent intrauterine growth restriction (IUGR). In this paper evidence indicating an association between a low birth weight and an adult phenotype which might favor a severe outcome of SARS-CoV-2 infection are presented: lower lung functional capacity; increased respiratory morbidity; changes in fibrinogen and Factor VII serum levels and dysregulation of the hemostasis and thrombosis system; acquisition of a pro-thrombotic phenotype; low nephron number, with decreased ability to sustain renal function and increased renal morbidity; heart remodeling, with a less efficient cardiac function; endothelial dysfunction, a risk factor for the insurgence of the multiple organ failure; remodeling of arteries, with changes in the elastic properties of the arterial wall, predisposing to the insurgence and progression of atherosclerosis; dysfunction of the innate immune system, a risk factor for immune diseases in adulthood. These data suggest that young and adult subjects born too small (IUGR) or too early (pre-terms) might represent a subgroup of "at risk subjects", more susceptible toward severe forms of COVID-19. Given that LBW may be considered a surrogate of IUGR, this phenotypic marker should be included among the indispensable clinical data collected in every patient presenting with SARS-COV-2 infection, irrespectively of his/her age.

Vaccine-induced immune thrombocytopenia (VITT) is a new syndrome occurring primarily in healthy young adults, with a female predominance, after receiving the first dose of ChAdOx1 nCoV-19 vaccine. We describe VITT syndrome characterized by severe thrombosis and thrombocytopenia found in our patient, with fatal outcome.A 58-year-old man, after 13 days from the first administration of ChAdOx1 nCoV-19 vaccine (AstraZeneca), presented with abdominal pain, diarrhea and vomitus. Laboratory tests revealed a severe thrombocytopenia, low fibrinogen serum levels and marked increase of D-dimer serum levels. The patient quickly developed a multiple organ failure, till death, three days after the hospital admission.At histology, in the lungs, interalveolar septa appeared thickened with microthrombi in the capillaries and veins. Interalveolar septa appeared thickened and showed vascular proliferation. Thrombi were detected in the capillaries of glomerular tufts. In the hearth, thrombi were observed in veins and capillaries. In the liver, voluminous fibrin thrombi were diffusely observed in the branches of the portal vein. Microthrombi were also found in the vasa vasorum of the wall of abdominal aorta. In the brain, microthrombi were observed in the capillaries of the choroid plexuses. Diffuse hemorrhagic necrosis was observed in the intestinal wall with marked congestion of the venous vessels.In our patient, the majority of data necessary for a VITT final diagnosis were present: thrombocytopenia and thrombosis in pulmonary, portal, hepatic, renal and mesenteric veins, associated with a marked increase of D-dimer serum levels. The finding of cerebral thrombosis in choroid plexuses, is a new finding in VITT. These features are suggestive for a very aggressive form of VITT.

Multiple epidemiological studies have suggested that industrialization and progressive urbanization should be considered one of the main factors responsible for the rising of atherosclerosis in the developing world. In this scenario, the role of trace metals in the insurgence and progression of atherosclerosis has not been clarified yet. In this paper, the specific role of selected trace elements (magnesium, zinc, selenium, iron, copper, phosphorus, and calcium) is described by focusing on the atherosclerotic prevention and pathogenesis plaque. For each element, the following data are reported: daily intake, serum levels, intra/extracellular distribution, major roles in physiology, main effects of high and low levels, specific roles in atherosclerosis, possible interactions with other trace elements, and possible influences on plaque development. For each trace element, the correlations between its levels and clinical severity and outcome of COVID-19 are discussed. Moreover, the role of matrix metalloproteinases, a family of zinc-dependent endopeptidases, as a new medical therapeutical approach to atherosclerosis is discussed. Data suggest that trace element status may influence both atherosclerosis insurgence and plaque evolution toward a stable or an unstable status. However, significant variability in the action of these traces is evident: some - including magnesium, zinc, and selenium - may have a protective role, whereas others, including iron and copper, probably have a multi-faceted and more complex role in the pathogenesis of the atherosclerotic plaque. Finally, calcium and phosphorus are implicated in the calcification of atherosclerotic plaques and in the progression of the plaque toward rupture and severe clinical complications. In particular, the role of calcium is debated. Focusing on the COVID-19 pandemia, optimized magnesium and zinc levels are indicated as important protective tools against a severe clinical course of the disease, often related to the ability of SARS-CoV-2 to cause a systemic inflammatory response, able to transform a stable plaque into an unstable one, with severe clinical complications.

BACKGROUND AND PURPOSE: Inflammatory changes in the fat tissue surrounding the coronary arteries have been associated with coronary artery disease and high-risk vulnerable plaques. Our aim was to investigate possible correlations between the presence and degree of perivascular fat density and a marker of vulnerable carotid plaque, namely contrast plaque enhancement on CTA. MATERIALS AND METHODS: One-hundred patients (76 men, 24 women; mean age, 69 years) who underwent CT angiography for investigation of carotid artery stenosis were retrospectively analyzed. Contrast plaque enhancement and perivascular fat density were measured in 100 carotid arteries, and values were stratified according to symptomatic (ipsilateral-to-cerebrovascular symptoms)/asymptomatic status (carotid artery with the most severe degree of stenosis). Correlation coefficients (Pearson ρ product moment) were calculated between the contrast plaque enhancement and perivascular fat density. The differences among the correlation ρ values were calculated using the Fisher r-to-z transformation. Mann-Whitney analysis was also calculated to test differences between the groups. RESULTS: There was a statistically significant positive correlation between contrast plaque enhancement and perivascular fat density (ρ value = 0.6582, P value = .001). The correlation was stronger for symptomatic rather than asymptomatic patients (ρ value = 0.7052, P value = .001 versus ρ value = 0.4092, P value = .001). CONCLUSIONS: There was a positive association between perivascular fat density and contrast plaque enhancement on CTA. This correlation was stronger for symptomatic rather than asymptomatic patients. Our results suggest that perivascular fat density could be used as an indirect marker of plaque instability.

BACKGROUND AND PURPOSE: Our aim was to assess the relationship between volume and percentage of intraplaque hemorrhage measured using CT and the occurrence of cerebrovascular events at the time of CT. MATERIALS AND METHODS: One-hundred-twenty-three consecutive subjects (246 carotid arteries) with a mean age of 69 years who underwent CTA were included in this retrospective study. Plaque volume of components and subcomponents (including intraplaque hemorrhage volume) was quantified with dedicated software. RESULTS: Forty-six arteries were excluded because no plaque was identified. In the remaining 200 carotid arteries, a statistically significant difference was found between presentation with cerebrovascular events and lipid volume (P = .002), intraplaque hemorrhage volume (P = .002), percentage of lipid (P = .002), percentage of calcium (P = .001), percentage of intraplaque hemorrhage (P = .001), percentage of lipid-intraplaque hemorrhage (P = .001), and intraplaque hemorrhage/lipid ratio (P = .001). The highest receiver operating characteristic area under the curve was obtained with the intraplaque hemorrhage volume with a value of 0.793 (P = .001), percentage of intraplaque hemorrhage with an area under the curve of 0.812 (P = .001), and the intraplaque hemorrhage/lipid ratio with an area under the curve value of 0.811 (P = .001). CONCLUSIONS: Results of our study suggest that Hounsfield unit values

BACKGROUND AND PURPOSE: The presence of IPH is considered the most dangerous feature because it is significantly associated with clinical ipsilateral cerebrovascular events. Our aim was to explore the characterization of plaque with CT in symptomatic subjects with bilateral intraplaque hemorrhage. MATERIALS AND METHODS: Three-hundred-forty-three consecutive patients with recent anterior circulation ischemic events (

BACKGROUND AND PURPOSE: Intraplaque hemorrhage is considered a leading parameter of carotid plaque vulnerability. Our purpose was to assess the CT characteristics of intraplaque hemorrhage with histopathologic correlation to identify features that allow for confirming or ruling out the intraplaque hemorrhage. MATERIALS AND METHODS: This retrospective study included 91 patients (67 men; median age, 65 ± 7 years; age range, 41–83 years) who underwent CT angiography and carotid endarterectomy from March 2010 to May 2013. Histopathologic analysis was performed for the tissue characterization and identification of intraplaque hemorrhage. Two observers assessed the plaque9s attenuation values by using an ROI (≥ 1 and ≤2 mm2). Receiver operating characteristic curve, Mann-Whitney, and Wilcoxon analyses were performed. RESULTS: A total of 169 slices were assessed (59 intraplaque hemorrhage, 63 lipid-rich necrotic core, and 47 fibrous); the average values of the intraplaque hemorrhage, lipid-rich necrotic core, and fibrous tissue were 17.475 Hounsfield units (HU) and 18.407 HU, 39.476 HU and 48.048 HU, and 91.66 HU and 93.128 HU, respectively, before and after the administration of contrast medium. The Mann-Whitney test showed a statistically significant difference of HU values both in basal and after the administration of contrast material phase. Receiver operating characteristic analysis showed a statistical association between intraplaque hemorrhage and low HU values, and a threshold of 25 HU demonstrated the presence of intraplaque hemorrhage with a sensitivity and specificity of 93.22% and 92.73%, respectively. The Wilcoxon test showed that the attenuation of the plaque before and after administration of contrast material is different (intraplaque hemorrhage, lipid-rich necrotic core, and fibrous tissue had P values of .006, .0001, and .018, respectively). CONCLUSIONS: The results of this preliminary study suggest that CT can be used to identify the presence of intraplaque hemorrhage according to the attenuation. A threshold of 25 HU in the volume acquired after the administration of contrast medium is associated with an optimal sensitivity and specificity. Special care should be given to the correct identification of the ROI.

This paper overviews one of the most important, interesting, and challenging problems in oncology, early diagnosis of prostate cancer. Developing effective diagnostic techniques for prostate cancer is of great clinical importance and can improve the effectiveness of treatment and increase the patient's chance of survival. The main focus of this study is to overview the different in-vitro and in-vivo technologies for diagnosing prostate cancer. This review discusses the current clinically used in-vitro cancer diagnostic tools, such as biomarker tests and needle biopsies and including their applications, advantages, and limitations. Moreover, the current in-vitro research tools that focus on the role of nanotechnology in prostate cancer diagnosis have been detailed. In addition to the in-vitro techniques, the current study discusses in detail developed in-vivo non-invasive state-of-the-art Computer-Aided Diagnosis (CAD) systems for prostate cancer based on analyzing Transrectal Ultrasound (TRUS) and different types of magnetic resonance imaging (MRI), e.g., T2-MRI, Diffusion Weighted Imaging (DWI), Dynamic Contrast Enhanced (DCE)-MRI, and multi-parametric MRI, focusing on their implementation, experimental procedures, and reported outcomes. Furthermore, the paper addresses the limitations of the current prostate cancer diagnostic techniques, outlines the challenges that these techniques face, and introduces the recent trends to solve these challenges, which include biomarkers used in in-vitro lab-on-a-chip nanotechnology-based methods.

PurposeTo test a computer-aided diagnostic method for differentiating symptomatic from asymptomatic carotid B-mode ultrasonographic images. MethodsOur system (called Atheromatic) automatically computed the intima-media thickness (IMT) of the carotid far wall using AtheroEdge, calculated nonlinear features based on higher order spectra, and used these features and IMT and IMT variability (IMTVpoly) to associate each image to a feature vector that was then labeled as symptomatic or asymptomatic (Sym/Asym) by a multiclassifiers system. We tested this method on a database of 118 carotid artery images from 37 symptomatic and 22 asymptomatic patients ResultsThe highest accuracy (99.1) was obtained by the support vector machine classifier using seven features. These features, relevant to discriminate Sym/Asym, included IMT and IMTVpoly, along with the bispectral entropies of the distal wall image at 77 degrees, 78 degrees, and 79 degrees angles. ConclusionsClassification in Sym/Asym of the far carotid wall is feasible and accurate and could be useful for the early detection of atherosclerosis and to identify patients with higher cardiovascular risk. (c) 2014 Wiley Periodicals, Inc. J Clin Ultrasound 43:302-311, 2015

The selection of carotid atherosclerosis patients for surgery or stenting is a crucial task in atherosclerosis disease management. In order to select only those symptomatic cases who need surgery, we have, in this work, presented a computer-aided diagnostic technique to effectively classify symptomatic and asymptomatic plaques from B-mode ultrasound carotid images. We extracted several grayscale features that quantify the textural differences inherent in the manually delineated plaque regions and selected the most significant among these extracted features. These features, along with the degree of stenosis (DoS), were used to train and test a support vector machine (SVM) classifier using threefold stratified cross-validation using a data set consisting of 160 (50 symptomatic and 110 asymptomatic) images. Using 32 features in an SVM classifier with a polynomial kernel of order 1, we obtained the best accuracy of 90.66%, sensitivity of 83.33%, and specificity of 95.39%. The DoS was found to be a valuable feature in addition to other texture-based features. We have also proposed the plaque risk index (PRI) made up of a combination of significant features such that the PRI has unique ranges for both plaque classes. PRI can be used in monitoring the variations in features over a period of time which will provide evidence on how and which features change as asymptomatic plaques become symptomatic.

The carotid intima-media thickness (IMT) is a validated marker of cerebrovascular disease risk. This paper presents a new parameter, the IMT variability (IMTV), and compares it between symptomatic and asymptomatic patients taken from a cohort of Italian population. One hundred forty-two patients were analyzed (age 59 ± 112 years, 59% males), 42 of these patients suffered from TIA or minor stroke. The lumen-intima (LI) and media-adventitia (MA) interfaces of the far wall were manually traced by a Reader. We also used a computer-based automated system (called AutoEdge) to obtain the LI/MA interfaces. The LI/MA interfaces were used to measure the IMT and the IMTV along the distal wall of the common carotid artery. Wilcoxon and Pearson correlation analyses were performed. The agreement between the Reader's IMT and the AutoEdge IMT values was 98.7% for the symptomatic (0.83 ± 0.44 mm for Reader, 0.82 ± 0.35 mm for AutoEdge) and 94.9% for the asymptomatic patients (0.78 ± 0.45 mm for Reader, 0.74 ± 0.30 mm for AutoEdge). Correlation was 65% for symptomatic and 68% for asymptomatic patients, respectively. The IMT measured using AutoEdge was 1.2% lower compared to manual measurements in symptomatic population, while 5.12% lower in asymptomatic. The IMTV was 11% higher in symptomatic patients compared to asymptomatic when using manual delineations, 8% higher when using AutoEdge. There was no statistical difference between the manual and automated IMTV measurements (Wilcoxon signed rank, P > 0.7). We conclude that the IMT and IMTV values were very similar between Reader and AutoEdge software when studying symptomatic and asymptomatic patients in Italian population.

BACKGROUND AND PURPOSE: CMBs have become increasingly recognized with the widespread use of MR imaging techniques that are sensitive to iron deposits. The purpose of this study was to correlate the presence of CMBs and carotid plaque characteristics. MATERIAL AND METHODS: Seventy consecutive patients (47 men; 23 women; mean age, 65 years) were prospectively analyzed. Carotid arteries were studied using a 16-detector row CT scanner, whereas the brain was explored with an MR imaging 1.5T system. CMBs were studied using a T2*-weighted GRE sequence. CMBs were classified by an ordinal scale and carotid plaques were characterized based on their composition as fatty, mixed, or calcified. Patients were classified as symptomatic and asymptomatic. Chi-square and multiple logistic regression analyses, as well as ROCs, were calculated. RESULTS: The prevalence of CMBs was 30%. A statistically significant difference in CMB prevalence was observed between symptomatic (46%) and asymptomatic (19%) patients (P value = .0021; OR = 3.7). Correlation analysis demonstrated an association between the number of CMBs and the symptoms (P = .0001). A statistically significant association was observed between the presence of fatty plaque and CMBs (P = .0019). CONCLUSIONS: The results of this study suggest an association between the presence of carotid artery fatty plaque, symptoms, and CMBs. Moreover, we found that the presence (and entity) of CMBs may represent an indicator of cerebrovascular symptom severity.

SUMMARY: The purpose of this work was to compare inter- and intraobserver agreement in the analysis of CAWT by using MDCTA. The CAWT in 35 patients was quantified by 4 observers. Bland-Altman statistics were used to measure the agreement between observers. The results of our study demonstrated that the CAWT measured by using MDCTA shows a good reproducibility between observers by considering inter- and intraobserver agreement.

Calcium burden measurement in internal carotid artery (ICA) plaque could play an important role in assessing stroke risk and stenosis quantification in the ICA. We propose an automatic method for labelling calcified plaques in ICA in CT images.Our approach builds upon the mean shift paradigm via an adaptive thresholding strategy. The data consists of single CT slices from 75 patients, with variety of plaque sizes and number of calcium regions. The manual measurements were carried out by a neuroradiologist for benchmarking. The calcium burden was measured as the area of the labelled plaque. Various metrics were employed to compare manual and automated measurements including correlation coefficient (CC), dice similarity (DS), Jacard Index (JI), polyline distance metric (PDM) and precision of merit (PoM).We found that our automated method of calcium area characterization performed accurately compared to manual measurements with CC=0.978, and PoM=0.915. The PDM, DS, and JI, also indicate a good performance with a mean DS=0.85 (SD=0.085), a mean JI=0.747 (SD=0.12), and a mean PDM=0.195 (SD=0.177).The proposed approach for calcium burden measurement, yields reasonably accurate labelling of calcified plaque when benchmarked against manual measurements. The approach is independent of the number and size of calcium regions, and the prototype design shows encouraging results to be adaptable to clinical practice.

Establishing relationship between coronary calcium volumes from Intravascular Ultrasound (IVUS) and automated carotid intima-media thickness (cIMT) helps in understanding the genetic nature of atherosclerosis disease. In this research, we have quantified the detected calcium from IVUS video frames and associated a relationship between coronary calcium volumes computed and automated cIMT from B-mode ultrasound.Coronary calcium volume is computed from IVUS and auto cIMTs are computed using B-mode ultrasound. An automated computer based application is developed and tested on 100 patient volumes (an average of 2549 frames per volume) to calculate lesion area and normalized coronary calcium volume. We use an integrated approach for volume computation which is based on lesion area per frame. We have measured the normalized volume from the calcium detected video frames using proposed integration method. The cIMT of 100 carotids were measured with novel and dedicated automated software analysis (AtheroEdge™ from AtheroPoint™ LLC, Roseville, CA, USA).The computer-based coronary calcium volume (from IVUS) showed a correlation coefficient with respect to cIMT for left and right carotids as 9.1% and 13.9%, respectively.Coronary calcium volume computed from IVUS and auto cIMT are moderately correlated. The association between auto cIMT (right side) vs. computer-based coronary calcium volume (IVUS) is stronger than the association between auto cIMT (left side) vs. computer-based coronary calcium volume.

Carotid intima-media thickness (cIMT) measurements during clinical trials need to have a fixed reference point (also called as bulb edge points) in the anatomy from which the cIMT can be measured. Identification of the bulb edge points in carotid ultrasound images faces the challenge to be detected automatically due to low image quality and variations in ultrasound images, motion artefacts, image acquisition protocols, position of the patient, and orientation of the linear probe with respect to bulb and ultrasound gain controls during acquisition.This paper presents a patented comprehensive methodology for carotid bulb localization and bulb edge detection as a reference point. The method consists of estimating the lumen-intima borders accurately using classification paradigm. Transition points are located automatically based on curvature characteristics. Further we verify and validate the locations of bulb edge points using combination of several local image processing methods such as (i) lumen-intima shapes, (ii) bulb slopes, (iii) bulb curvature, (iv) mean lumen thickness and its variations, and (v) geometric shape fitting.Our database consists of 155 ultrasound bulb images taken from various ultrasound machines with varying resolutions and imaging conditions. Further we run our automated system blindly to spot out the bulbs in a mixture database of 336 images consisting of bulbs and no-bulbs. We are able to detect the bulbs in the bulb database with 100% accuracy having 92% as close as to a neurologists's bulb location. Our mean lumen-intima error is 0.0133 mm with precision against the manual tracings to be 98.92%. Our bulb detection system is fast and takes on an average 9 seconds per image for detection for the bulb edge points and 4 seconds for verification/validation of the bulb edge points.

In this paper, we review the different studies that developed Computer Aided Diagnostic (CAD) for automated classification of thyroid cancer into benign and malignant types. Specifically, we discuss the different types of features that are used to study and analyze the differences between benign and malignant thyroid nodules. These features can be broadly categorized into (a) the sonographic features from the ultrasound images, and (b) the non-clinical features extracted from the ultrasound images using statistical and data mining techniques. We also present a brief description of the commonly used classifiers in ultrasound based CAD systems. We then review the studies that used features based on the ultrasound images for thyroid nodule classification and highlight the limitations of such studies. We also discuss and review the techniques used in studies that used the non-clinical features for thyroid nodule classification and report the classification accuracies obtained in these studies.

Intima-Media Thickness (IMT) is now being considered as an indicator of atherosclerosis. Our group has developed several feature-based IMT measurement algorithms such as CALEX (a class of patented AtheroEdge™ Systems from Global Biomedical Technologies, Inc., CA, USA). These methods are based on the hypothesis that the highest pixel intensities are in the far wall of the Common Carotid Artery (CCA) or the Internal Carotid Artery (ICA). In this work, we verify that this hypothesis holds true for B-mode longitudinal ultrasound images of the carotid wall. This patented methodology consists of generating the composite image (arithmetic sum of images) from the database by first registering the carotid image frames with respect to a nearly straight carotid artery frame from the same database using (a) B-spline based nonrigid registration and (b) affine registration. Prior to registration, we segment the carotid artery lumen using a level set based algorithm followed by morphological image processing. The binary lumen images are registered and the transformations are applied to the original grayscale CCA images. We evaluated our technique using a database of 200 common carotid images of normal and pathologic carotids. The composite image presented the highest intensity distribution in the far wall of the CCA/ICA, validating our hypothesis. We have also demonstrated the accuracy and improvement in IMT segmentation result with our CALEX 3.0 system. The CALEX system, when run on newly acquired ultrasound images, shows the IMT error of about 30 μm. Thus, we have shown that the CALEX algorithm is able to exploit the far wall brightness for accurate IMT measurements

The development of completely automated techniques for arterial wall segmentation and intima-media thickness measurement requires the recognition of the artery in the image frame. Conceptually, automated techniques can be thought of as the combination of two cascades stages: artery recognition and wall segmentation. In this chapter we show three carotid artery recognition systems (CARS) that are fully automated. CARS is a generalized framework for carotid artery recognition in ultrasound images, which can be easily adapted to almost any B-Mode ultrasound vascular image. The first technique is based on first-order derivative Gaussian edge analysis (CARSgd). The second method is based on an integrated approach (CARSia) that combines image feature extractions, fitting, and classification. The third strategy is based on signal analysis (CARSsa). The output of all the three paradigms provides tracing of the far adventitial (ADF). The complete CARS system (consisting of the three strategies named CARSgd, CARSia, and CARSsa) was on a dataset of 365 longitudinal B-Mode carotid images, acquired by different sonographers. Performance evaluation of the carotid recognition process was done in three ways: (1) visual inspection by experts; (2) by measuring the Hausdorff Distance (HD) between far adventitial (ADF) and the manually traced ADF, and (3) by measuring the HD between ADF and the lumen-intima (GTLI) and media-adventitia (GTMA) borders of the arterial walls. The results showed the CARS accuracy in locating the artery in the ultrasound image. The average HD between ADF and the manual ADF was 0.76 ± 0.73 mm for CARSgd, 1.02 ± 2.03 mm for CARSia, and 2.18 ± 3.10 mm for CARSsa. The average HD between GTLI and ADF for CARSgd, CARSia, and CARSsa was 2.16 ± 1.16 mm, 2.71 ± 2.89 mm, and 2.66 ± 1.52 mm, respectively. The average HD between ADF and GTMA for CARSgd, CARSia, and CARSsa was 1.54 ± 1.19 mm, 1.86 ± 2.66 mm, and 1.95 ± 1.64 mm, respectively. Considering a maximum distance of 50 pixels (about 3 mm), CARSgd showed an identification accuracy of 100%, CARSia of 92%, and CARSsa of 96%. These identification accuracies were confirmed by visual inspection. All the three systems work on MATLAB, Windows OS, and on a PC-based cross-platform medical application written in Java called AtheroEdge™ with 1 s per image. CARSgd showed very accurate ADF profiles coupled with a low computational burden and without the need for specific tuning. It can be thought of as a reference technique for carotid localization, to be used in automated intima-media thickness measurement strategies

The purpose of this study was to evaluate whether the automated carotid intima-media thickness (CIMT) identified by using automated software could predict the SYNTAX score for coronary artery disease (CAD) patients.Three-hundred-seventy consecutive patients (males 218; median age 69±11 years) who underwent carotid-ultrasound and coronary angiography were analyzed. Two experienced interventional cardiologists calculated the SYNTAX score from the carotid angiograms. After ultrasonographic examinations were performed, the plaque score (PS) was calculated and automated carotid IMT analysis was obtained by a fully automated algorithm. Correlation and stepwise logistic regression analysis were calculated and also the receiver operating characteristics (ROC) curve analysis was computed.The mean SYNTAX score was 8.1±14.4; the PS was 7.1±14.4 and the mean CIMT was 0.86±0.23 mm (Normality rejected with a P-value of 0.001). A statistically significant correlation was found between the CIMT and SYNTAX score (r=0.323; P=0.0001) and between the PS and SYNTAX score (r=0.583; P=0.0001). The area under the ROC curve (Az) between CIMT and coronary artery disease was 0.648 (P=0.0001) and the CIMT of 1 mm or more was associated with the presence coronary artery disease with a specificity of 90.5%. Logistic regression analysis confirmed the association between CIMT and SYNTAX score (P=0.0002).Results of our study using an automated algorithm showed a statistical significant association between CIMT and SYNTAX score and indicated that CIMT may be considered a reliable parameter for prediction of SYNTAX score in coronary artery disease patient population from Japan.

Epilepsy is a disorder of the brain depicted by recurrent seizures. Electroencephalogram signals can be used to study the characteristics of epileptic seizures. In this study, we propose a method for the automated classification of electroencephalogram into normal, interictal and ictal classes using 6, 12, 18 and 23.6 s of data. We employed discrete wavelet transform to decompose electroencephalogram signals into frequency sub-bands. These discrete wavelet transform coefficients were then subjected to independent component analysis for reducing the data dimension. The independent component analysis features were then fed to six classifiers, namely, decision tree, K-nearest neighbor, probabilistic neural network, fuzzy, Gaussian mixture model and support vector machine to select the best classifier. We observed that the support vector machine classifier with radial basis function kernel function gave the best results with an average accuracy of 96%, sensitivity of 96% and specificity of 97% for 23.6 s of electroencephalogram data. Our results show that as the duration of the data increases, the classification accuracy increases. This proposed technique can be used as an automatic seizure monitoring software to aid the doctors in providing timely quality care for the patients suffering from epilepsy.

In 30% of stroke victims, the cause of stroke has been found to be the stenosis caused by plaques in the carotid artery. Early detection of plaque and subsequent classification of the same into symptomatic and asymptomatic can help the clinicians to choose only those patients who are at a higher risk of stroke for risky surgeries and stenosis treatments. Therefore, in this work, we have proposed a non-invasive computer-aided diagnostic technique to classify the detected plaque into the two classes. Computed tomography (CT) images of the carotid artery images were used to extract Local Binary Pattern (LBP) features and wavelet energy features. Significant features were then used to train and test several supervised learning algorithm based classifiers. The Support Vector Machine (SVM) classifier with various kernel configurations was evaluated using LBP and wavelet features. The SVM classifier presented the highest accuracy of 88%, sensitivity of 90.2%, and specificity of 86.5% for radial basis function (RBF) kernel function. The CT images of the carotid artery provide unique 3D images of the artery and plaque that could be used for calculating percentage of stenosis. Our proposed technique enables automatic classification of plaque into asymptomatic and symptomatic with high accuracy, and hence, it can be used for deciding the course of treatment. We have also proposed a single-valued integrated index ( Atheromatic Index) using the significant features which can provide a more objective and faster prediction of the class.

Hashimoto’s thyroiditis is the most common type of inflammation of the thyroid gland, and accurate diagnosis of Hashimoto’s thyroiditis would be helpful to better manage the disease process and predict thyroid failure. Most of the published computer-based techniques that use ultrasound thyroid images for Hashimoto’s thyroiditis diagnosis are limited by lack of procedure standardization because individual investigators use various initial ultrasound settings. This article presents a computer-aided diagnostic technique that uses grayscale features and classifiers to provide a more objective and reproducible classification of normal and Hashimoto’s thyroiditis-affected cases. In this paradigm, we extracted grayscale features based on entropy, Gabor wavelet, moments, image texture, and higher order spectra from the 100 normal and 100 Hashimoto’s thyroiditis-affected ultrasound thyroid images. Significant features were selected using t-test. The resulting feature vectors were used to build the following three classifiers using tenfold stratified cross validation technique: support vector machine, k-nearest neighbor, and radial basis probabilistic neural network. Our results show that a combination of 12 features coupled with support vector machine classifier with the polynomial kernel of order 1 and linear kernel gives the highest accuracy of 80%, sensitivity of 76%, specificity of 84%, and positive predictive value of 83.3% for the detection of Hashimoto’s thyroiditis. The proposed computer-aided diagnostic system uses novel features that have not yet been explored for Hashimoto’s thyroiditis diagnosis. Even though the accuracy is only 80%, the presented preliminary results are encouraging to warrant analysis of more such powerful features on larger databases.

Among gynecological malignancies, ovarian cancer is the most frequent cause of death. Image mining algorithms have been predominantly used to give the physicians a more objective, fast, and accurate second opinion on the initial diagnosis made from medical images. The objective of this work is to develop an adjunct computer-aided diagnostic technique that uses 3D ultrasound images of the ovary to accurately characterize and classify benign and malignant ovarian tumors. In this algorithm, we first extract features based on the textural changes and higher-order spectra information. The significant features are then selected and used to train and evaluate the decision tree (DT) classifier. The proposed technique was validated using 1,000 benign and 1,000 malignant images, obtained from ten patients with benign and ten with malignant disease, respectively. On evaluating the classifier with tenfold stratified cross validation, the DT classifier presented a high accuracy of 97 %, sensitivity of 94.3 %, and specificity of 99.7 %. This high accuracy was achieved because of the use of the novel combination of the four features which adequately quantify the subtle changes and the nonlinearities in the pixel intensity variations. The rules output by the DT classifier are comprehensible to the end-user and, hence, allow the physicians to more confidently accept the results. The preliminary results show that the features are discriminative enough to yield good accuracy. Moreover, the proposed technique is completely automated, accurate, and can be easily written as a software application for use in any computer.

The aims of this study were: 1) to analyze the interobserver carotid intima-media thickness (CIMT) variability using three different measurement metrics on large multi-institutional databases; 2) to evaluate the three kinds of metrics when comparing completely automated CIMT measurement (Auto Edge CIMT) to two manually derived CIMT (manual CIMT).Two expert sonographers manually analyzed 665 carotid B-Mode ultrasound images collected from five institutions and using four different scanners. The two readers traced the lumen-intima (LI) and media-adventitia (MA) interfaces. The manual CIMT was computed from the LI/MA tracings by using three different distance measurement metrics: the Hausdorff, the PolyLine, and the Centerline distance metrics. The LI/MA tracings of a completely automated method we previously developed were then compared to manual CIMT.The average CIMT values of Readers 1 and 2 were 1.904±0.650 mm and 1.421±0.394 using Hausdorff, 0.808±0.269 mm and 0.790±0.227 mm using Polyline, and 0.762±0.266 mm and 0.782±0.228 mm using Centerline, respectively. The correlation coefficients were 0.14 (0.07-0.22) for Hausdorff, 0.77 (0.74-0.80) for Polyline, and 0.82 (0.79-0.84) for Centerline. The variation coefficients (CV) were equal to 46.4% (Hausdorff), 2.6 % (Polyline), and 14.1% (Centerline). The Auto Edge CIMT values were: 1.655±0.676 mm using Hausdorff, 0.808±0.282 mm using Polyline, and 0.776±0.275 mm using Centerline.Centerline and Polyline yield very close results and are clinically suitable distance measurement techniques for computing the CIMT from LI/MA profiles.

Over the past two decades, intravascular ultrasound (IVUS) image segmentation has remained a challenge for researchers while the use of this imaging modality is rapidly growing in catheterization procedures and in research studies. IVUS provides cross-sectional grayscale images of the arterial wall and the extent of atherosclerotic plaques with high spatial resolution in real time. In this paper, we review recently developed image processing methods for the detection of media-adventitia and luminal borders in IVUS images acquired with different transducers operating at frequencies ranging from 20 to 45 MHz. We discuss methodological challenges, lack of diversity in reported datasets, and weaknesses of quantification metrics that make IVUS segmentation still an open problem despite all efforts. In conclusion, we call for a common reference database, validation metrics, and ground-truth definition with which new and existing algorithms could be benchmarked.

Computer-aided diagnosis (CAD) of carotid atherosclerosis into symptomatic or asymptomatic is useful in the analysis of cardiac health. This paper describes a patented CAD system called Atheromatic™ for symptomatic versus asymptomatic plaque classification in carotid ultrasound images. The system involves two steps: 1) feature extraction using a combination of discrete wavelet transform and averaging algorithms and 2) classification using a support vector machine (SVM) classifier for automated decision making. The CAD system was evaluated using a database consisting of 150 asymptomatic and 196 symptomatic plaque regions which were labeled using the ground truth based on the presence or absence of symptoms. Threefold cross-validation protocol was adapted for developing and testing the classifiers. We observed that the SVM classifier with a polynomial kernel of order 2 was to achieve a classification accuracy of 83.7%.

Intima-media thickness (IMT) is now being considered as an indicator of atherosclerosis. Our group has developed several feature-based IMT measurement algorithms such as the Completely Automated Layer EXtraction (CALEX) (which is a class of patented AtheroEdge Systems from Global Biomedical Technologies, Inc., CA, USA). These methods are based on the hypothesis that the highest pixel intensities are in the far wall of the common carotid artery (CCA) or the internal carotid artery (ICA). In this paper, we verify that this hypothesis holds true for B-mode longitudinal ultrasound (US) images of the carotid wall. This patented methodology consists of generating the composite image (the arithmetic sum of images) from the database by first registering the carotid image frames with respect to a nearly straight carotid-artery frame from the same database using: (1) B-spline-based nonrigid registration and (2) affine registration. Prior to registration, we segment the carotid-artery lumen using a level-set-based algorithm followed by morphological image processing. The binary lumen images are registered, and the transformations are applied to the original grayscale CCA images. We evaluated our technique using a database of 200 common carotid images of normal and pathologic carotids. The composite image presented the highest intensity distribution in the far wall of the CCA/ICA, validating our hypothesis. We have also demonstrated the accuracy and improvement in the IMT segmentation result with our CALEX 3.0 system. The CALEX system, when run on newly acquired US images, shows the IMT error of about 30 μm. Thus, we have shown that the CALEX algorithm is able to exploit the far-wall brightness for accurate IMT measurements.

The carotid plaques characterization is essential to decide about the possibility of surgical intervention (endarterectomy/stenting) on the patient. Soft and unstable plaques represent a major risk for the patient, as they are correlated with an augmented probability of brain infarction and emboli generation. Hence, the minimally-invasive characterization expecially of this type of carotid plaques is crucial in clinical practice. This paper presents an integrated system for the completely user-independent carotid plaque segmentation and characterization, based on ultrasound 2-D images. We show that using a ultrasound contrast agent, it is possible to segment also echolucent plaques with a percentage of misclassified pixels equal to 8%. After segmentation, the enhanced image is used to perform tissue characterization. We tested our system on 5 echolucent plaques and on 5 fibrous/stable plaques, showing that our system is capable of an accurate carotid wall segmentation and proper quantification of the percentages of blood, fat, calcium and fibrous tissue constituting the plaque. The system is very promising and it is being used in a neurology unit on patients already indicated for endarterectomy, with the purpose of correlating its output with histology.

Four cases of histiocytic medullary reticulosis encountered between 1968 and 1972 at the All-India Institute of Medical Sciences Hospital, New Delhi, are reported. One of the cases was diagnosed during life and the other three postmortem. A complete remission was achieved in the former following prednisolone and cyclophosphamide therapy. The histological changes consisted of malignant histiocytosis with erythrophagocytosis in the organs of the reticuloendothelial system. The lymph nodes and the bone marrow were involved in all the cases. The importance of biopsy examination of these organs in making an early diagnosis is emphasised.

Ultrasound has great potential to aid in the differential diagnosis of malignant and benign thyroid lesions, but interpretative pitfalls exist and the accuracy is still poor. To overcome these difficulties, we developed and analyzed a range of knowledge representation techniques, which are a class of ThyroScan™ algorithms from Global Biomedical Technologies Inc., California, USA, for automatic classification of benign and malignant thyroid lesions. The analysis is based on data obtained from twenty nodules (ten benign and ten malignant) taken from 3D contrast-enhanced ultrasound images. Fine needle aspiration biopsy and histology confirmed malignancy. Discrete Wavelet Transform (DWT) and texture algorithms are used to extract relevant features from the thyroid images. The resulting feature vectors are fed to three different classifiers: K-Nearest Neighbor (K-NN), Probabilistic Neural Network (PNN), and Decision Tree (DeTr). The performance of these classifiers is compared using Receiver Operating Characteristic (ROC) curves. Our results show that combination of DWT and texture features coupled with K-NN resulted in good performance measures with the area of under the ROC curve of 0.987, a classification accuracy of 98.9%, a sensitivity of 98%, and a specificity of 99.8%. Finally, we have proposed a novel integrated index called Thyroid Malignancy Index (TMI), which is made up of texture features, to diagnose benign or malignant nodules using just one index. We hope that this TMI will help clinicians in a more objective detection of benign and malignant thyroid lesions.