Ultrasound shear wave elastography for the evaluation of renal pathological changes in adult patients.

OBJECTIVE: Many studies have conflicting findings in using shear wave elastography (SWE) to assess renal fibrosis. This study reviews the use of SWE to evaluate pathological changes in native kidneys and renal allografts. It also tries to elucidate the confounding factors and care taken to ensure the results are consistent and reliable. METHODS: The review was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Literature search was conducted in Pubmed, Web of Science and Scopus database up to 23 October 2021. To evaluate risk and bias applicability, the Cochrane risk-of bias tool and GRADE was used. The review was registered under PROSPERO CRD42021265303. RESULTS: A total of 2921 articles were identified. 104 full texts were examined and 26 studies included in systematic review. 11 studies performed on native kidneys and 15 studies on transplanted kidney. A wide range of impact factors was found that affect the accuracy of SWE of renal fibrosis in adult patients. CONCLUSIONS: Compared to point SWE, two-dimensional SWE with elastogram could enable better selection of the region of interest in kidneys, leading to reproducible results. Tracking waves were attenuated as the depth from skin to region of interest increased, therefore, SWE is not recommended for overweight or obese patients. Variable transducer forces might also affect SWE reproducibility, thus, training of operators to ensure consistent operator-dependent transducer forces may be helpful. ADVANCES IN KNOWLEDGE: This review provides a holistic insight on the efficiency of using SWE in evaluating pathological changes in native and transplanted kidneys, thereby contributing to the knowledge of its utilisation in clinical practice.

Artificial intelligence, BI-RADS evaluation and morphometry: A novel combination to diagnose breast cancer using ultrasonography, results from multi-center cohorts.

PURPOSE: To develop and validate a machine learning (ML) model for the classification of breast lesions on ultrasound images. METHOD: In the present study, three separate data cohorts containing 1288 breast lesions from three countries (Malaysia, Iran, and Turkey) were utilized for MLmodel development and external validation. The model was trained on ultrasound images of 725 breast lesions, and validation was done separately on the remaining data. An expert radiologist and a radiology resident classified the lesions based on the BI-RADS lexicon. Thirteen morphometric features were selected from a contour of the lesion and underwent a three-step feature selection process. Five features were chosen to be fed into the model separately and combined with the imaging signs mentioned in the BI-RADS reference guide. A support vector classifier was trained and optimized. RESULTS: The diagnostic profile of the model with various input data was compared to the expert radiologist and radiology resident. The agreement of each approach with histopathologic specimens was also determined. Based on BI-RADS and morphometric features, the model achieved an area under the receiver operating characteristic (ROC) curve (AUC) of 0.885, which is higher than the expert radiologist and radiology resident performances with AUC of 0.814 and 0.632, respectively in all cohorts. DeLong's test also showed that the AUC of the ML protocol was significantly different from that of the expert radiologist (ΔAUCs = 0.071, 95%CI: (0.056, 0.086), P = 0.005). CONCLUSIONS: These results support the possible role of morphometric features in enhancing the already well-excepted classification schemes.

Quality Improvement Report: Safety Program for Prevention of Central Line-associated Bloodstream Infections.

The increasing usage of peripherally inserted central catheters (PICCs) in medical imaging departments has led to a corresponding increase in cases of central line-associated bloodstream infection (CLABSI). However, this condition is preventable with proper monitoring and use of aseptic techniques. A Comprehensive Unit-based Safety Program (CUSP) is a quality improvement (QI) measure implemented by health care institutions to reduce the incidence of CLABSI. However, effective strategies have yet to be established. The authors describe a QI project that evaluated the implementation of CUSP at a teaching hospital to reduce PICC-associated bloodstream infection (BSI). The framework consists of a five-step process: understand and train staff on the science of safety, assemble a team, engage senior executives, identify defects through sensemaking, and implement teamwork and communication strategies in a series of related and sequential steps that use QI tools. Targets were identified for improvement from existing processes, and the workflow was reengineered. Nine months after the start of the CUSP intervention, PICC-associated BSI incidence in the hospital had been reduced from 3.4 to 2.7 per 1000 central lines days after intervention. The incidence of BSI was also reduced correspondingly from 8.8% to 5.9%. The QI processes in this study may be adopted by other hospitals, as they involve minimal cost with significant impact on patient safety and well-being. The QI sequential steps described capture the implementation processes that can be modified for use in other department settings where patient safety could be compromised. Online supplemental material is available for this article. ©RSNA, 2022.

Diagnostic Accuracy of Shear Wave Elastography as an Adjunct Tool in Detecting Axillary Lymph Nodes Metastasis.

OBJECTIVES: This study evaluates the diagnostic performance of shear wave elastography (SWE) in differentiating between benign and axillary lymph node (ALN) metastasis in breast carcinoma. MATERIALS AND METHODS: Breast lesions and axillae of 107 patients were assessed using B-mode ultrasound and SWE. Histopathology was the diagnostic gold standard. RESULTS: In metastatic axillary lymph nodes, qualitative SWE using color patterns had the highest area under curve (AUC) value, followed by B-mode Ultrasound (cortical thickening >3 mm) and quantitative SWE using Emax of 15.2 kPa (AUC of 81.3%, 70.1%, and 61.2%, respectively). Qualitative SWE exhibited better diagnostic performance than the other two parameters, with sensitivity of 96.0% and specificity of 56.1%. Combination of B-mode Ultrasound (using cortical thickness of >3 mm as cut-off point) and qualitative SWE (Color patterns of 2 to 4) showed sensitivity of 71.6%, specificity of 95%, PPV of 96%, NPV of 66.7%, and accuracy of 80.4%. CONCLUSION: Qualitative SWE assessment exhibited higher accuracy compared to quantitative values. Qualitative SWE as an adjunct to B-mode ultrasound can further improve the diagnostic accuracy of metastatic ALN in breast cancer.

Desmoid Type Fibromatosis of the Breast Masquerading as Breast Carcinoma: Value of Dynamic Magnetic Resonance Imaging and Its Correlation.

Desmoid type fibromatosis of the breast is a rare stromal tumor that accounts for <0.2% of all breast tumors. Bilateral and multicentric lesions are extremely rare, with only less than ten cases reported in the literature. Although benign, it is locally aggressive with frequent recurrence in up to almost one-third of the cases. We experienced our first case of bilateral multicentric breast fibromatosis in a 19-year-old woman, with a paternal aunt diagnosed with breast cancer at age 30, who presented to our institution with the chief complaint of retracted nipples for 1 year. The patient denied any history of trauma to her chest. Sonography showed suspicious bilateral hypoechoic masses. Magnetic resonance imaging (MRI) was performed for further evaluation because of the extensive involvement of both the breasts. This report aimed to illustrate the main clinical, radiological, and histopathological characteristics of this rare disease to increase awareness of this entity and discuss the role of MRI.

Customised weight-based volume contrast media protocol in CT of chest, abdomen and pelvis examination.

INTRODUCTION: Fixed volume (FV) contrast media administration during CT examination is the standard practice in most healthcare institutions. We aim to validate a customised weight-based volume (WBV) method and compare it to the conventional FV methods, introduced in a regional setting. METHODS: 220 patients underwent CT of the chest, abdomen and pelvis (CAP) using a standard FV protocol, and subsequently, a customised 1.0 mL/kg WBV protocol within one year. Both image sets were assessed for contrast enhancement using CT attenuation at selected regions-of-interest (ROIs). The visual image quality was evaluated by three radiologists using a 4-point Likert scale. Quantitative CT attenuation was correlated with the visual quality assessment to determine the HU's enhancement indicative of the image quality grades. Contrast media usage was calculated to estimate cost-savings from both protocols. RESULTS: Mean patient age was 61 ± 14 years, and weight was 56.1 ± 8.7 kg. FV protocol produced higher contrast enhancement than WBV, p < 0.001. CT images' overall contrast enhancement was negatively correlated with body weight for FV protocol while the WBV protocol produced more consistent enhancement across different body weight. More than 90% of the images from both protocols were graded "Excellent". WBV protocol also enabled a 28% cost reduction with cost savings of US$1238. CONCLUSION: The customised WBV protocol produced CT images which were comparable to FV protocol for CT CAP examinations. A median CT value of 100 HU can be an indicator of good image quality for the WBV protocol.

Diagnostic accuracy of tomosynthesis-guided vacuum assisted breast biopsy of ultrasound occult lesions.

This study aims to evaluate the diagnostic accuracy of digital breast tomosynthesis-guided vacuum assisted breast biopsy (DBT-VABB) of screening detected suspicious mammographic abnormalities comprising of calcifications, asymmetric densities, architectural distortions and spiculated masses. In this institutionally approved study, a total of 170 (n = 170) DBT-VABB were performed, 153 (90%) were for calcifications, 8 (4.7%) for spiculated mass, 5 (2.9%) for asymmetric density and 4 (2.4%) for architectural distortion. All these lesions were not detected on the corresponding ultrasound. Histopathology results revealed 140 (82.4%) benign, 9 (5.3%) borderline and 21 (12.4%) malignant lesions. The total upgrade rate at surgery was 40% for atypical ductal hyperplasia and 5.9% for ductal carcinoma in-situ. 3.6% discordant benign lesions showed no upgrade. DBT-VABB showed 100% specificity, 91.3% sensitivity and 100% positive predictive value (PPV) for detecting malignant lesions. The negative predictive value (NPV) was 80%. 2 (1.2%) patients had mild complications and 1 (0.6%) had severe pain. Our study showed that DBT-VABB was a safe and reliable method, with high sensitivity, specificity, PPV and NPV in the diagnosis of non-palpable benign and malignant breast lesions. Our data also confirmed the accuracy of DBT-VABB in detecting malignant lesions and we suggest further surgical excision in borderline lesions for a more accurate diagnostic evaluation.

Shear wave elastography accurately detects chronic changes in renal histopathology.

AIM: Renal biopsy is the gold standard for the histological characterization of chronic kidney disease (CKD), of which renal fibrosis is a dominant component, affecting its stiffness. The aim of this study was to investigate the correlation between kidney stiffness obtained by shear wave elastography (SWE) and renal histological fibrosis. METHODS: Shear wave elastography assessments were performed in 75 CKD patients who underwent renal biopsy. The SWE-derived estimates of the tissue Young's modulus (YM), given as kilopascals (kPa), were measured. YM was correlated to patients' renal histological scores, broadly categorized into glomerular, tubulointerstitial and vascular scores. RESULTS: Young's modulus correlates significantly with tubulointerstitial score (ρ = 0.442, P < .001) and glomerular score (ρ = 0.375, P = .001). Patients with no glomerular sclerosis showed lower mean YM measurements compared to those with glomerular sclerosis. The mean YM increased as the percentage of interstitial fibrosis and tubular atrophy increased. The area under the receiver operating characteristic curve (ROC) for SWE in differentiating between mildly and moderately impaired kidneys was 0.702. CONCLUSION: Shear wave elastography accurately detects chronic renal damage resulting from glomerular sclerosis, interstitial fibrosis and tubular atrophy, using the optimal cut-off YM value of ≥5.81 kPa.

Comparing point shear wave elastography (ElastPQ) and transient elastography for diagnosis of fibrosis stage in non-alcoholic fatty liver disease.

BACKGROUND AND AIM: Transient elastography (TE) and point shear wave elastography (pSWE) are noninvasive methods to diagnose fibrosis stage in patients with chronic liver disease. The aim of this study is to compare the accuracy of the two methods to diagnose fibrosis stage in non-alcoholic fatty liver disease (NAFLD) and to study the intra-observer and inter-observer variability when the examinations were performed by healthcare personnel of different backgrounds. METHODS: Consecutive NAFLD patients who underwent liver biopsy were enrolled in this study and had two sets each of pSWE and TE examinations by a nurse and a doctor on the same day of liver biopsy procedure. The medians of the four sets of pSWE and TE were used for evaluation of diagnostic accuracy using area under receiver operating characteristic curve (AUROC). Intra-observer and inter-observer variability was analyzed using intraclass correlation coefficients. RESULTS: Data for 100 NAFLD patients (mean age 57.1 ± 10.2 years; male 46.0%) were analyzed. The AUROC of TE for diagnosis of fibrosis stage ≥ F1, ≥ F2, ≥ F3, and F4 was 0.89, 0.83, 0.83, and 0.89, respectively. The corresponding AUROC of pSWE was 0.80, 0.72, 0.69, and 0.79, respectively. TE was significantly better than pSWE for the diagnosis of fibrosis stages ≥ F2 and ≥ F3. The intra-observer and inter-observer variability of TE and pSWE measurements by the nurse and doctor was excellent with intraclass correlation coefficient > 0.96. CONCLUSION: Transient elastography was significantly better than pSWE for the diagnosis of fibrosis stage ≥ F2 and ≥ F3. Both TE and pSWE had excellent intra-observer and inter-observer variability when performed by healthcare personnel of different backgrounds.

Volumetric Liver Fat Fraction Determines Grade of Steatosis More Accurately Than Controlled Attenuation Parameter in Patients With Nonalcoholic Fatty Liver Disease.

BACKGROUND & AIMS: HepaFat-Scan is a magnetic resonance imaging-based method for quantification of hepatic steatosis by volumetric liver fat fraction (VLFF) measurement. We aimed to validate VLFF and to compare it with controlled attenuation parameter (CAP) for determination of hepatic steatosis grade in patients with NAFLD, using histopathology and stereologic analyses of biopsies as the reference standard. METHODS: We performed a prospective study of consecutive adults with NAFLD who were scheduled for a liver biopsy at a tertiary hospital in Malaysia. Patients underwent VLFF and CAP measurements on the same day as their liver biopsy. Histopathology analyses of liver biopsy specimens were reported according to the Nonalcoholic Steatohepatitis Clinical Research Network scoring system. Stereologic analysis was performed using grid-point counting method combined with the Delesse principle. RESULTS: We analyzed data from 97 patients (mean age 57.0 ± 10.1 years; 44.33% male; 91.8% obese; 95.9% centrally obese). Based on histopathology analysis, the area under receiver operating characteristic curve (AUROC) for VLFF in detection of steatosis grade ≥S2 was 0.92 and for CAP the AUROC was 0.65 (P < .001). Based on stereological analysis, the AUROC for VLFF for detection of steatosis grade ≥S2 was 0.92 and for CAP the AUROC was 0.63, (P = .002); for identification of steatosis grade S3, the AUROC for VLFF was 0.92 and for CAP the AUROC was 0.68 (P < .001). CONCLUSIONS: In a prospective study of patients with NAFLD undergoing liver biopsy analysis, we found VLFF to more accurately determine grade of hepatic steatosis than CAP.

Stiffness and Anisotropy Effect on Shear Wave Elastography: A Phantom and in Vivo Renal Study.

Tissue elasticity is related to the pathologic state of kidneys and can be measured using shear wave elastography (SWE). However, SWE quantification has not been rigorously validated. The aim of this study was to evaluate the accuracy of SWE-measured stiffness and the effect of tissue anisotropy on SWE measurements. Point SWE (pSWE), 2-D SWE and dynamic mechanical analysis (DMA) were used to measure stiffness and evaluate the effect of tissue anisotropy on the measurements. SWE and DMA were performed on phantoms of different gelatin concentrations. In the tissue anisotropy study, SWE and DMA were performed on the outer cortex of sheep kidneys. In the in vivo study, 15 patients with different levels of interstitial fibrosis were recruited for pSWE measurements. Another 10 healthy volunteers were recruited for tissue anisotropy studies. SWE imaging revealed a non-linear increase with gelatin concentration. There was a significant correlation between pSWE and 2-D SWE, leading to the establishment of a linear regression equation between the two SWE ultrasound measurements. In the anisotropy study, the median difference in stiffness between shear waves oriented at 0° and 90° towards the pyramid axis was significant. In the in vivo study, there was a strong positive linear correlation between pSWE and the percentage of interstitial fibrosis. There was a significant difference in the Young's modulus (YM) between severities of fibrosis. The mean YM values were lower in control patients than in patients with mild, moderate and severe fibrosis. YM values were also significantly higher when shear waves were oriented at 0° toward the pyramid axis. Tissue stiffness and anisotropy affects SWE measurements. These factors should be recognized before applying SWE for the interpretation of measured values.

Comparison of Shear Wave Elastography and Conventional Ultrasound in Assessing Kidney Function as Measured Using 51Cr-ethylenediaminetetraacetic Acid and 99Tc-Dimercaptosuccinic Acid.

The purpose of this study was to assess the potential of shear wave elastography (SWE) as an indicator of abnormal kidney function defined by radiolabeled glomerular filtration rate (GFR). Fifty-seven patients referred for 51Cr-ethylenediaminetetraacetic acid GFR and 99mTc-dimercaptosuccinic acid renal scintigraphy were included. Young's modulus (YM) measured with SWE and kidney length, volume, cortical thickness and parenchymal echogenicity measured with conventional ultrasound were correlated with patients' GFR and renal scintigraphy results. Spearman correlation coefficients between SWE and GFR were negative for the right (r = -0.635, p < 0.0001) and left (r = -0.817, p < 0.0001) kidneys. Positive correlations between left renal cortical thickness (r = 0.381, p = 0.04) and left kidney volume (r = 0.356, p = 0.019) with GFR were reported. SWE correctly predicted the dominant functioning kidney in 94.7% of cases. The area under the receiver operating characteristic curve for SWE (0.800) was superior to that for conventional ultrasound (0.252-0.415). The cutoff value of ≥5.52 kPa suggested a kidney function ≤60 mL/min/1.73 m2 (82.4% sensitivity and 76.2% specificity). SWE has advantages over conventional ultrasound in assessing kidney function and distinguishing the dominant functioning kidney.

Automated detection and classification of liver fibrosis stages using contourlet transform and nonlinear features.

BACKGROUND AND OBJECTIVE: Liver fibrosis is a type of chronic liver injury that is characterized by an excessive deposition of extracellular matrix protein. Early detection of liver fibrosis may prevent further growth toward liver cirrhosis and hepatocellular carcinoma. In the past, the only method to assess liver fibrosis was through biopsy, but this examination is invasive, expensive, prone to sampling errors, and may cause complications such as bleeding. Ultrasound-based elastography is a promising tool to measure tissue elasticity in real time; however, this technology requires an upgrade of the ultrasound system and software. In this study, a novel computer-aided diagnosis tool is proposed to automatically detect and classify the various stages of liver fibrosis based upon conventional B-mode ultrasound images. METHODS: The proposed method uses a 2D contourlet transform and a set of texture features that are efficiently extracted from the transformed image. Then, the combination of a kernel discriminant analysis (KDA)-based feature reduction technique and analysis of variance (ANOVA)-based feature ranking technique was used, and the images were then classified into various stages of liver fibrosis. RESULTS: Our 2D contourlet transform and texture feature analysis approach achieved a 91.46% accuracy using only four features input to the probabilistic neural network classifier, to classify the five stages of liver fibrosis. It also achieved a 92.16% sensitivity and 88.92% specificity for the same model. The evaluation was done on a database of 762 ultrasound images belonging to five different stages of liver fibrosis. CONCLUSIONS: The findings suggest that the proposed method can be useful to automatically detect and classify liver fibrosis, which would greatly assist clinicians in making an accurate diagnosis.

A case-control study of breast cancer risk factors in 7,663 women in Malaysia.

BACKGROUND: Breast cancer risk factors have been examined extensively in Western setting and more developed Asian cities/countries. However, there are limited data on developing Asian countries. The purpose of this study was to examine breast cancer risk factors and the change of selected risk factors across birth cohorts in Malaysian women. METHODS: An unmatched hospital based case-control study was conducted from October 2002 to December 2016 in Selangor, Malaysia. A total of 3,683 cases and 3,980 controls were included in this study. Unconditional logistic regressions, adjusted for potential confounding factors, were conducted. The breast cancer risk factors were compared across four birth cohorts by ethnicity. RESULTS: Ever breastfed, longer breastfeeding duration, a higher soymilk and soy product intake, and a higher level of physical activity were associated with lower risk of breast cancer. Chinese had the lowest breastfeeding rate, shortest breastfeeding duration, lowest parity and highest age of first full term pregnancy. CONCLUSIONS: Our study shows that breastfeeding, soy intake and physical activity are modifiable risk factors for breast cancer. With the increasing incidence of breast cancer there is an urgent need to educate the women about lifestyle intervention they can take to reduce their breast cancer risk.

Shear wave elastography in the evaluation of renal parenchymal stiffness in patients with chronic kidney disease.

OBJECTIVE: To investigate the use of shear wave elastography (SWE)-derived estimates of Young's modulus (YM) as an indicator to detect abnormal renal tissue diagnosed by estimated glomerular filtration rate (eGFR). METHODS: The study comprised 106 chronic kidney disease (CKD) patients and 203 control subjects. Conventional ultrasound was performed to measure the kidney length and cortical thickness. SWE imaging was performed to measure renal parenchymal stiffness. Diagnostic performance of SWE and conventional ultrasound were correlated with serum creatinine, urea levels and eGFR. RESULTS: Pearson's correlation coefficient revealed a negative correlation between YM measurements and eGFR (r = -0.576, p < 0.0001). Positive correlations between YM measurements and age (r = 0.321, p < 0.05), serum creatinine (r = 0.375, p < 0.0001) and urea (r = 0.287, p < 0.0001) were also observed. The area under the receiver operating characteristic curve for SWE (0.87) was superior to conventional ultrasound alone (0.35-0.37). The cut-off value of less or equal to 4.31 kPa suggested a non-diseased kidney (80.3% sensitivity, 79.5% specificity). CONCLUSION: SWE was superior to renal length and cortical thickness in detecting CKD. A value of 4.31 kPa or less showed good accuracy in determining whether a kidney was diseased or not. Advances in knowledge: On SWE, CKD patients show greater renal parenchymal stiffness than non-CKD patients. Determining a cut-off value between normal and diseased renal parenchyma may help in early non-invasive detection and management of CKD.

Automated diagnosis of focal liver lesions using bidirectional empirical mode decomposition features.

Liver is the heaviest internal organ of the human body and performs many vital functions. Prolonged cirrhosis and fatty liver disease may lead to the formation of benign or malignant lesions in this organ, and an early and reliable evaluation of these conditions can improve treatment outcomes. Ultrasound imaging is a safe, non-invasive, and cost-effective way of diagnosing liver lesions. However, this technique has limited performance in determining the nature of the lesions. This study initiates a computer-aided diagnosis (CAD) system to aid radiologists in an objective and more reliable interpretation of ultrasound images of liver lesions. In this work, we have employed radon transform and bi-directional empirical mode decomposition (BEMD) to extract features from the focal liver lesions. After which, the extracted features were subjected to particle swarm optimization (PSO) technique for the selection of a set of optimized features for classification. Our automated CAD system can differentiate normal, malignant, and benign liver lesions using machine learning algorithms. It was trained using 78 normal, 26 benign and 36 malignant focal lesions of the liver. The accuracy, sensitivity, and specificity of lesion classification were 92.95%, 90.80%, and 97.44%, respectively. The proposed CAD system is fully automatic as no segmentation of region-of-interest (ROI) is required.

Microstructural integrity of white matter tracts amongst older fallers: A DTI study.

OBJECTIVES: This study assesses the whole brain microstructural integrity of white matter tracts (WMT) among older individuals with a history of falls compared to non-fallers. METHODS: 85 participants (43 fallers, 42 non-fallers) were evaluated with conventional MRI and diffusion tensor imaging (DTI) sequences of the brain. DTI metrics were obtained from selected WMT using tract-based spatial statistics (TBSS) method. This was followed by binary logistic regression to investigate the clinical variables that could act as confounding elements on the outcomes. The TBSS analysis was then repeated, but this time including all significant predictor variables from the regression analysis as TBSS covariates. RESULTS: The mean diffusivity (MD) and axial diffusivity (AD) and to a lesser extent radial diffusivity (RD) values of the projection fibers and commissural bundles were significantly different in fallers (p < 0.05) compared to non-fallers. However, the final logistic regression model obtained showed that only functional reach, white matter lesion volume, hypertension and orthostatic hypotension demonstrated statistical significant differences between fallers and non-fallers. No significant differences were found in the DTI metrics when taking into account age and the four variables as covariates in the repeated analysis. CONCLUSION: This DTI study of 85 subjects, do not support DTI metrics as a singular factor that contributes independently to the fall outcomes. Other clinical and imaging factors have to be taken into account.

Evaluation of solid breast lesions with power Doppler: value of penetrating vessels as a predictor of malignancy.

INTRODUCTION: This study aimed to evaluate the vascular pattern of solid breast lesions using power Doppler ultrasonography (PDUS) and assess whether the presence of intratumoural penetrating vessels can predict breast cancer malignancy. METHODS: Greyscale ultrasonography (US) and PDUS were prospectively performed on 91 women in Malaysia with histopathologically proven breast lesions. The diagnostic accuracy of greyscale US, PDUS, and both greyscale US and PDUS was calculated and compared. RESULTS: The 91 women had 102 breast lesions (55 benign, 47 malignant). Of the 47 malignant lesions, 36 demonstrated intratumoural penetrating vessels. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of greyscale US findings in diagnosing malignancy were 100.0%, 71.4%, 74.1% and 100.0%, respectively. The presence of calcification in the breast lesion and the margin, shape and posterior acoustic features of the lesion were significant parameters in predicting malignancy (p < 0.01). The sensitivity, specificity, PPV and NPV of the presence of intratumoural penetrating vessels in predicting malignancy were 76.5%, 80.0%, 76.5% and 80.0%, respectively. When both greyscale US and PDUS were used, there was a significant correlation in predicting malignancy (p < 0.05). The specificity and PPV values of the combined greyscale US and PDUS method (89.0% and 85.7%, respectively) were higher than those of greyscale US or PDUS alone. CONCLUSION: Flow patterns revealed by PDUS can be useful for differentiating benign and malignant breast lesions. The visualisation of penetrating vessels in solid breast lesions can be used to complement greyscale US findings in predicting malignancy.

Automated characterization of fatty liver disease and cirrhosis using curvelet transform and entropy features extracted from ultrasound images.

Fatty liver disease (FLD) is reversible disease and can be treated, if it is identified at an early stage. However, if diagnosed at the later stage, it can progress to an advanced liver disease such as cirrhosis which may ultimately lead to death. Therefore, it is essential to detect it at an early stage before the disease progresses to an irreversible stage. Several non-invasive computer-aided techniques are proposed to assist in the early detection of FLD and cirrhosis using ultrasound images. In this work, we are proposing an algorithm to discriminate automatically the normal, FLD and cirrhosis ultrasound images using curvelet transform (CT) method. Higher order spectra (HOS) bispectrum, HOS phase, fuzzy, Kapoor, max, Renyi, Shannon, Vajda and Yager entropies are extracted from CT coefficients. These extracted features are subjected to locality sensitive discriminant analysis (LSDA) feature reduction method. Then these LSDA coefficients ranked based on F-value are fed to different classifiers to choose the best performing classifier using minimum number of features. Our proposed technique can characterize normal, FLD and cirrhosis using probabilistic neural network (PNN) classifier with an accuracy of 97.33%, specificity of 100.00% and sensitivity of 96.00% using only six features. In addition, these chosen features are used to develop a liver disease index (LDI) to differentiate the normal, FLD and cirrhosis classes using a single number. This can significantly help the radiologists to discriminate FLD and cirrhosis in their routine liver screening.