Lower uterine segment thickness measurement in pregnant women with previous Cesarean section: reliability analysis using two- and three-dimensional transabdominal and transvaginal ultrasound

Objective To evaluate the reliability of two- and three-dimensional ultrasonographic measurement of the thickness of the lower uterine segment (LUS) in pregnant women by transvaginal and transabdominal approaches. Methods This was a study of 30 pregnant women who bad bad at least one previous Cesarean section and were between 36 and 39 weeks` gestation, with singleton pregnancies in cephalic presentation. Sonographic examinations were performed by two observers using both 4-7-MHz transabdominal and 5-8-MHz transvaginal volumetric probes. LUS measurements were performed using two- and three-dimensional ultrasound, evaluating the entire LUS thickness transabdominally and the LUS muscular thickness transvaginally. Each observer measured the LUS four times by each method. Reliability was analyzed by comparing the mean of the absolute differences, the intraclass correlation coefficients, the 95% limits of agreement and the proportion of differences <1 mm. Results Transvaginal ultrasound provided greater reliability in LUS measurements than did transabdominal ultrasound. The use of three-dimensional ultrasound improved significantly the reliability of the LUS muscular thickness measurement obtained transvaginally. Conclusions Ultrasonographic measurement of the LUS muscular thickness transvaginally appears more reliable than does that of the entire LUS thickness transabdominally. The use of three-dimensional ultrasound should be considered to improve measurement reliability. Copyright (c) 2009 ISUOG. Published by John Wiley & Sons, Ltd.

Imaging in osteoarthritis: what have we learned and where are we going?

Osteoarthritis (OA) is a widely prevalent disease of the whole joint including cartilage, bone and soft tissues. Increasing importance of imaging including assessment of all joint structures has been recognized recently. Conventional radiography is still the first and most commonly used imaging technique for evaluation of a patient with a known or suspected diagnosis of OA. However, limitations have been revealed by recent MRI-based knee OA studies. MRI plays a crucial role in understanding the natural history of the disease and in guiding future therapies due to its ability to image the knee as a whole organ and to directly and three-dimensionally assess cartilage morphology and composition. It is crucial to use the appropriate MR pulse sequences to assess various OA features, and thus support from experienced musculoskeletal radiologists should be sought for study design, image acquisition and interpretation. The aim of this article is to describe the roles and limitations of conventional radiography and MRI in imaging of OA, and also to give insight into the use of other modalities such as ultrasound, scintigraphy, computed tomography (CT) and CT arthrography in clinical practice and research in OA, particularly focusing on the assessment of knee OA in the tibiofemoral joint.

LOW-INTENSITY ULTRASOUND APPLICATION IN DISTAL RADIUS METAPHYSEAL BONE DEFECTS OF DOGS

We assessed the repair of transverse, 3-mm wide bone gaps created at the distal radius in 28 dogs that were randomly divided into two 14-animal groups; one was the control group and the other received a daily, 20-min application of low-intensity pulsed ultrasound for 100 days. Sequential radiographs, histomorphometrics, bone fluorescent histology and bone vascularity assessments found that all animals from both groups obtained a stage of hypertrophic-type nonunion with fibrocartilage tissue formation throughout the region of osteotomy. However, treated animals exhibited areas of endochondral ossification within the fibrocartilage region. There was no difference in type of vascularity or the newly formed bone process obtained by tetracycline labeling. Application of low-intensity ultrasound was not capable of significantly changing the reparative process and it may not be sufficiently powerful to overcome a combination of local deleterious effects on bone healing, created by gapping, excessive motion and periosteal resection. (E-mail: jbvolpon@fmrp.usp.br) (C) 2010 World Federation for Ultrasound in Medicine & Biology.

Skeletal effects of low-intensity pulsed ultrasound on the ovariectomized rodent

Growing evidence supports low-intensity pulsed ultrasound (US) as an osteogenic mechanical stimulus. Its effects on isolated bone cells and on fractured bone are established. However, its effects on osteoporosis are not clear. This study examined US effects on ovariectomy (OVX) induced bone changes within the rodent hindlimb (distal femur and proximal tibia), and on normal bone in animals following sham-OVX. Animals were exposed to daily unilateral active-US and contralateral inactive-US for 12 weeks. Bone status was assessed using dual energy X-ray absorptiometry and histomorphometry. Ovariectomy resulted in significant bone changes. Low-intensity pulsed US did not influence these changes. These results suggest that the US dose introduced may not be a beneficial treatment for osteoporosis, and that intact bone may be less sensitive to US than fractured bone and isolated bone cells. This may relate to the biophysical mechanisms of action of US, US-bone interactions and tissue level processes taking place.

Myocardial abnormalities in hypertensive patients with normal and abnormal left ventricular filling: a study of ultrasound tissue characterization and strain

Abnormal left ventricular (LV) filling is common, but not universal, in hypertensive LV hypertrophy (LVH). We sought to elucidate the relative contributions of myocardial structural changes, loading and hypertrophy to LV dysfunction in 113 patients: 85 with hypertensive LVH and 28 controls without LVH and with normal filling. Patients with normal dobutamine stress echocardiography and no history of coronary artery disease were selected, in order to exclude a contribution from ischaemia or scar. Abnormal LV filling was identified in 65 LVH patients, based on Doppler measurement of transmitral filling and annular velocities. All patients underwent grey-scale and colour tissue Doppler imaging from three apical views, which were stored and analysed off line. Integrated backscatter (113) and strain rate imaging were used to detect changes in structure and function; average cyclic variation of 113, strain rate and peak systolic strain were calculated by averaging each segment. Calibrated 113 intensity, corrected for pericardial 113 intensity, was measured in the septum and posterior wall from the parasternal long-axis view. Patients with LVH differed significantly from controls with respect to all backscatter and strain parameters, irrespective of the presence or absence of abnormal LV filling. LVH patients with and without abnormal LV filling differed with regard to age, LV mass and incidence of diabetes mellitus, but also showed significant differences in cyclic variation (P < 0.01), calibrated 113 in the posterior wall (P < 0.05) and strain rate (P < 0.01), although blood pressure, heart rate and LV systolic function were similar. Multivariate logistic regression analysis demonstrated that age, LV mass index and calibrated IB in the posterior wall were independent determinants of abnormal LV filling in patients with LVH. Thus structural and functional abnormalities can be detected in hypertensive patients with LVH with and without abnormal LV filling. In addition to age and LVH, structural (not functional) abnormalities are likely to contribute to abnormal LV filling, and may be an early sign of LV damage. 113 is useful for the detection of myocardial abnormalities in patients with hypertensive LVH.

Routine ultrasound screening in diabetic pregnancies

Objectives To assess the detection rate of congenital fetal malformations and specific problems related to routine ultrasound screening in women with pre-existing diabetes. Methods A retrospective study was carried out to assess the performance of routine ultrasound screening in women with pre-existing diabetes (Types 1 and 2) within a tertiary institution. The incidence, type and risk factors for congenital fetal malformations were determined. The detection rate of fetal anomalies for diabetic women was compared with that for the low-risk population. Factors affecting these detection rates were evaluated. Results During the study period, 12 169 low-risk pregnant women and 130 women with pre-existing diabetes had routine ultrasound screening performed within the institution. A total of 10 major anomalies (7.7%) and three minor anomalies (2.3%) were present in the fetuses of the diabetic women. Central nervous system and cardiovascular system anomalies accounted for 60% of the major anomalies. Peri-conceptional hemoglobin A 1 c of more than 9% was associated with a high prevalence of major anomalies (14311000). Women who had fetuses with major anomalies bad a significantly higher incidence of obesity (78% vs. 37%; P < 0.05). Ultrasound examination of these diabetic pregnancies showed high incidences of suboptimal image quality (37%), incomplete examinations, and repeat examinations (17%). Compared to the 'low-risk' non-diabetic population from the same institution, the relative risk for a major congenital anomaly among the diabetic women was 5.9-fold higher (95% confidence interval, 2.9-11.9). The detection rate for major fetal anomalies was significantly lower for diabetic women (30% vs. 73%; P < 0.01), and the mean body mass index for the diabetic group was significantly higher (29 vs. 23 kg/m(2); P < 0.001). Conclusion The incidence of congenital anomalies is higher in diabetic pregnancies. Unfortunately, the detection rate for fetal anomalies by antenatal ultrasound scan was significantly, worse than that for the low-risk population. This is likely to be related to the maternal body habitus and unsatisfactory examinations. Methods to overcome these difficulties are discussed.

Determination of regional flow by use of intravascular PET tracers: Microvascular theory and experimental validation for pig livers

Today, the standard approach for the kinetic analysis of dynamic PET studies is compartment models, in which the tracer and its metabolites are confined to a few well-mixed compartments. We examine whether the standard model is suitable for modern PET data or whether theories including more physiologic realism can advance the interpretation of dynamic PET data. A more detailed microvascular theory is developed for intravascular tracers in single-capillary and multiple-capillary systems. The microvascular models, which account for concentration gradients in capillaries, are validated and compared with the standard model in a pig liver study. Methods: Eight pigs underwent a 5-min dynamic PET study after O-15-carbon monoxide inhalation. Throughout each experiment, hepatic arterial blood and portal venous blood were sampled, and flow was measured with transit-time flow meters. The hepatic dual-inlet concentration was calculated as the flow-weighted inlet concentration. Dynamic PET data were analyzed with a traditional single-compartment model and 2 microvascular models. Results: Microvascular models provided a better fit of the tissue activity of an intravascular tracer than did the compartment model. In particular, the early dynamic phase after a tracer bolus injection was much improved. The regional hepatic blood flow estimates provided by the microvascular models (1.3 +/- 0.3 mL min(-1) mL(-1) for the single-capillary model and 1.14 +/- 0.14 min(-1) mL(-1) for the multiple-capillary model) (mean +/- SEM mL of blood min(-1) mL of liver tissue(-1)) were in agreement with the total blood flow measured by flow meters and normalized to liver weight (1.03 +/- 0.12 mL min(-1) mL(-1)). Conclusion: Compared with the standard compartment model, the 2 microvascular models provide a superior description of tissue activity after an intravascular tracer bolus injection. The microvascular models include only parameters with a clear-cut physiologic interpretation and are applicable to capillary beds in any organ. In this study, the microvascular models were validated for the liver and provided quantitative regional flow estimates in agreement with flow measurements.

Improving The Robustness Of Interventional 4D Ultrasound Segmentation Through The Use Of Personalized Shape Priors

While fluoroscopy is still the most widely used imaging modality to guide cardiac interventions, the fusion of pre-operative Magnetic Resonance Imaging (MRI) with real-time intra-operative ultrasound (US) is rapidly gaining clinical acceptance as a viable, radiation-free alternative. In order to improve the detection of the left ventricular (LV) surface in 4D ultrasound, we propose to take advantage of the pre-operative MRI scans to extract a realistic geometrical model representing the patients cardiac anatomy. This could serve as prior information in the interventional setting, allowing to increase the accuracy of the anatomy extraction step in US data. We have made use of a real-time 3D segmentation framework used in the recent past to solve the LV segmentation problem in MR and US data independently and we take advantage of this common link to introduce the prior information as a soft penalty term in the ultrasound segmentation algorithm. We tested the proposed algorithm in a clinical dataset of 38 patients undergoing both MR and US scans. The introduction of the personalized shape prior improves the accuracy and robustness of the LV segmentation, as supported by the error reduction when compared to core lab manual segmentation of the same US sequences.

Imaging for radiofrequency ablation

Many solid tumors have a poor response to systemic chemotherapy, local radiotherapy or surgical recession. They are responsible for premature morbidity and decreased patient survival. The radiofrequency ablation is an emerging technique, and is now becoming more widespread throughout the world because it is minimally invasive, image guided, which offers the possibility of an effective and less costly approach. The procedure can be performed percutaneously, guided by several imaging modalities as Ultrasound, Computed Tomography and Magnetic Resonance. This article pretends to demonstrate the state-of-the-art of this technique focusing in the technical aspects and application of radiofrequency ablation.

Global and local detection of liver steatosis from ultrasound

Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. Steatosis is usually a diffuse liver disease, since it is globally affected. However, steatosis can also be focal affecting only some foci difficult to discriminate. In both cases, steatosis is detected by laboratorial analysis and visual inspection of ultrasound images of the hepatic parenchyma. Liver biopsy is the most accurate diagnostic method but its invasive nature suggest the use of other non-invasive methods, while visual inspection of the ultrasound images is subjective and prone to error. In this paper a new Computer Aided Diagnosis (CAD) system for steatosis classification and analysis is presented, where the Bayes Factor, obatined from objective intensity and textural features extracted from US images of the liver, is computed in a local or global basis. The main goal is to provide the physician with an application to make it faster and accurate the diagnosis and quantification of steatosis, namely in a screening approach. The results showed an overall accuracy of 93.54% with a sensibility of 95.83% and 85.71% for normal and steatosis class, respectively. The proposed CAD system seemed suitable as a graphical display for steatosis classification and comparison with some of the most recent works in the literature is also presented.

Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm

PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.

The usefulness of ultrasound in the classification of chronic liver disease

Chronic Liver Disease is a progressive, most of the time asymptomatic, and potentially fatal disease. In this paper, a semi-automatic procedure to stage this disease is proposed based on ultrasound liver images, clinical and laboratorial data. In the core of the algorithm two classifiers are used: a k nearest neighbor and a Support Vector Machine, with different kernels. The classifiers were trained with the proposed multi-modal feature set and the results obtained were compared with the laboratorial and clinical feature set. The results showed that using ultrasound based features, in association with laboratorial and clinical features, improve the classification accuracy. The support vector machine, polynomial kernel, outperformed the others classifiers in every class studied. For the Normal class we achieved 100% accuracy, for the chronic hepatitis with cirrhosis 73.08%, for compensated cirrhosis 59.26% and for decompensated cirrhosis 91.67%.

Chronic liver disease staging classification based on ultrasound, clinical and laboratorial data

In this work the identification and diagnosis of various stages of chronic liver disease is addressed. The classification results of a support vector machine, a decision tree and a k-nearest neighbor classifier are compared. Ultrasound image intensity and textural features are jointly used with clinical and laboratorial data in the staging process. The classifiers training is performed by using a population of 97 patients at six different stages of chronic liver disease and a leave-one-out cross-validation strategy. The best results are obtained using the support vector machine with a radial-basis kernel, with 73.20% of overall accuracy. The good performance of the method is a promising indicator that it can be used, in a non invasive way, to provide reliable information about the chronic liver disease staging.

Diffuse liver disease classification from ultrasound surface characterization, clinical and laboratorial data

In this work liver contour is semi-automatically segmented and quantified in order to help the identification and diagnosis of diffuse liver disease. The features extracted from the liver contour are jointly used with clinical and laboratorial data in the staging process. The classification results of a support vector machine, a Bayesian and a k-nearest neighbor classifier are compared. A population of 88 patients at five different stages of diffuse liver disease and a leave-one-out cross-validation strategy are used in the classification process. The best results are obtained using the k-nearest neighbor classifier, with an overall accuracy of 80.68%. The good performance of the proposed method shows a reliable indicator that can improve the information in the staging of diffuse liver disease.

Fatty liver characterization and classification by ultrasound

Steatosis, also known as fatty liver, corresponds to an abnormal retention of lipids within the hepatic cells and reflects an impairment of the normal processes of synthesis and elimination of fat. Several causes may lead to this condition, namely obesity, diabetes, or alcoholism. In this paper an automatic classification algorithm is proposed for the diagnosis of the liver steatosis from ultrasound images. The features are selected in order to catch the same characteristics used by the physicians in the diagnosis of the disease based on visual inspection of the ultrasound images. The algorithm, designed in a Bayesian framework, computes two images: i) a despeckled one, containing the anatomic and echogenic information of the liver, and ii) an image containing only the speckle used to compute the textural features. These images are computed from the estimated RF signal generated by the ultrasound probe where the dynamic range compression performed by the equipment is taken into account. A Bayes classifier, trained with data manually classified by expert clinicians and used as ground truth, reaches an overall accuracy of 95% and a 100% of sensitivity. The main novelties of the method are the estimations of the RF and speckle images which make it possible to accurately compute textural features of the liver parenchyma relevant for the diagnosis.