Single cell multi-omics characterise discrete human tendon cells populations that persist in vitro and on fibrous scaffolds.

Chronic tendinopathy represents a growing healthcare burden in the ageing global population. Curative therapies remain elusive as the mechanisms that underlie chronic inflammation in tendon disease remain unclear. Identifying and isolating key pathogenic and reparative cells is essential in developing precision therapies and implantable materials for improved tendon healing. Multiple discrete human tendon cell populations have been previously described ex vivo. To determine if these populations persist in vitro, healthy human hamstring tenocytes were cultured for 8 d on either tissue culture plastic or aligned electrospun fibres of absorbable polydioxanone. Novel single-cell surface proteomics combined with unbiased single-cell transcriptomics (CITE-Seq) was used to identify discrete tenocyte populations. 6 cell populations were found, 4 of which shared key gene expression determinants with ex vivo human cell clusters: PTX3_PAPPA, POSTN_SCX, DCN_LUM and ITGA7_NES. Surface proteomics found that PTX3_PAPPA cells were CD10+CD26+CD54+. ITGA7_NES cells were CD146+ and POSTN_SCX cells were CD90+CD95+CD10+. Culture on the aligned electrospun fibres favoured 3 cell subtypes (DCN_LUM, POSTN_SCX and PTX3_ PAPPA), promoting high expression of tendon-matrix-associated genes and upregulating gene sets enriched for TNF-a and IL-6/STAT3 signalling. Discrete human tendon cell subpopulations persisted in in vitro culture and could be recognised by specific gene and surface-protein signatures. Aligned polydioxanone fibres promoted the survival of 3 clusters, including pro-inflammatory PTX3-expressing CD10+CD26+CD54+ cells found in chronic tendon disease. These results improved the understanding of preferred culture conditions for different tenocyte subpopulations and informed the development of in vitro models of tendon disease.

Automatic speech analysis to early detect functional cognitive decline in elderly population.

This study aimed at evaluating whether people with a normal cognitive function can be discriminated from subjects with a mild impairment of cognitive function based on a set of acoustic features derived from spontaneous speech. Voice recordings from 90 Italian subjects (age >65 years; group 1: 47 subjects with MMSE>26; group 2: 43 subjects with 20≤ MMSE ≤26) were collected. Voice samples were processed using a MATLAB-based custom software to derive a broad set of known acoustic features. Linear mixed model analyses were performed to select the features able to significantly distinguish between groups. The selected features (% of unvoiced segments, duration of unvoiced segments, % of voice breaks, speech rate, and duration of syllables), alone or in addition to age and years of education, were used to build a learning-based classifier. The leave-one-out cross validation was used for testing and the classifier accuracy was computed. When the voice features were used alone, an overall classification accuracy of 0.73 was achieved. When age and years of education were additionally used, the overall accuracy increased up to 0.80. These performances were lower than the accuracy of 0.86 found in a recent study. However, in that study the classification was based on several tasks, including more cognitive demanding tasks. Our results are encouraging because acoustic features, derived for the first time only from an ecologic continuous speech task, were able to discriminate people with a normal cognitive function from people with a mild cognitive decline. This study poses the basis for the development of a mobile application performing automatic voice analysis on-the-fly during phone calls, which might potentially support the detection of early signs of functional cognitive decline.

Expression of p16 in squamous cell carcinoma of the mobile tongue is independent of HPV infection despite presence of the HPV-receptor syndecan-1.

BACKGROUND: Tongue squamous cell carcinoma (TSCC) is increasing in incidence, especially among young patients and preferably females. Infection with human papilloma virus (HPV) has been suggested as a cause of SCC in the head and neck, and the proportion of oropharyngeal cancers caused by HPV has steadily increased. METHODS: Samples from 109 patients with primary TSCC were analysed for the presence of HPV16 by in situ hybridisation and for expression of its surrogate marker p16 and the HPV receptor syndecan-1 by immunhistochemistry. RESULTS: No evidence of HPV16 DNA was observed in the tumours, although one-third showed p16 staining. There was no difference in the expression of the primary HPV receptor, syndecan-1, between TSCC and a group of tonsil SCC. CONCLUSION: Whereas p16 is expressed in some TSCCs, HPV16 is undetectable, therefore, p16 cannot be used as a surrogate marker for high-risk HPV-infection in this tumour. Despite presence of the HPV-receptor syndecan-1 in TSCC, HPV prefers the tonsillar environment. Lack of p16 associates with worse prognosis primarily in patients aged ⩽40 years with tongue SCC. The improved prognosis seen in p16-positive TSCC can be due to induction of a senescent phenotype or an inherent radiosensitivity due to the ability of p16 to inhibit homologous recombination repair.

Measurement of ultrasonic diaphragmatic motion.

The motion characteristics of the diaphragmatic muscle may provide useful information about normal and abnormal diaphragmatic function and indicate diaphragmatic weakness. The objective of this paper was to introduce a simple system for the quantitative analysis of ultrasonic diaphragmatic motion. The measurements routinely carried out by the experts were computed and these include: (i) excursion, (ii) inspiration time (Tinsp) and (iii) cycle duration (Ttot). The system was evaluated on four simulated videos and one real video. Manual and automated measurements were very close. Further work in a larger number of videos is needed for validating the proposed method.

Prediction of the time period of stroke based on ultrasound image analysis of initially asymptomatic carotid plaques.

Non-invasive ultrasound imaging of carotid plaques can provide information on the characteristics of the arterial wall including the size, morphology and texture of the atherosclerotic plaques. Several studies were carried out that demonstrated the usefulness of these feature sets for differentiating between asymptomatic and symptomatic plaques and their corresponding cerebrovascular risk stratification. The aim of this study was to develop predictive modelling for estimating the time period of a stroke event by determining the risk for short term (less or equal to three years) or long term (more than three years) events. Data from 108 patients that had a stroke event have been used. The information collected included clinical and ultrasound imaging data. The prediction was performed at base line where patients were still asymptomatic. Several image texture analysis and clinical features were used in order to create a classification model. The different features were statistically analyzed and we conclude that image texture analysis features extracted using Spatial Gray Level Dependencies method had the best statistical significance. Several predictive models were derived based on Binary Logistic Regression (BLR) and Support Vector Machines (SVM) modelling. The best results were obtained with the SVM modelling models with an average correct classifications score of 77±7% for differentiating between stroke event occurrences within 3 years versus more than 3 years. Further work is needed in investigating additional multiscale texture analysis features as well as more modelling techniques on more subjects.

Quantitative texture analysis of brain white matter lesions derived from T2-weighted MR images in MS patients with clinically isolated syndrome.

INTRODUCTION: This study investigates the application of texture analysis methods on brain T2-white matter lesions detected with magnetic resonance imaging (MRI) for the prognosis of future disability in subjects diagnosed with clinical isolated syndrome (CIS) of multiple sclerosis (MS). METHODS: Brain lesions and normal appearing white matter (NAWM) from 38 symptomatic untreated subjects diagnosed with CIS as well as normal white matter (NWM) from 20 healthy volunteers, were manually segmented, by an experienced MS neurologist, on transverse T2-weighted images obtained from serial brain MR imaging scans (0 and 6-12 months). Additional clinical information in the form of the Expanded Disability Status Scale (EDSS), a scale from 0 to 10, which provides a way of quantifying disability in MS and monitoring the changes over time in the level of disability, were also provided. Shape and most importantly different texture features including GLCM and laws were then extracted for all above regions, after image intensity normalization. RESULTS: The findings showed that: (i) there were significant differences for the texture futures extracted between the NAWM and lesions at 0 month and between NAWM and lesions at 6-12 months. However, no significant differences were found for all texture features extracted when comparing lesions temporally at 0 and 6-12 months with the exception of contrast (gray level difference statistics-GLDS) and difference entropy (spatial gray level dependence matrix-SGLDM); (ii) significant differences were found between NWM and NAWM for most of the texture features investigated in this study; (iii) there were significant differences found for the lesion texture features at 0 month for those with EDSS≤2 versus those with EDSS>2 (mean, median, inverse difference moment and sum average) and for the lesion texture features at 6-12 months with EDSS>2 and EDSS≤2 for the texture features (mean, median, entropy and sum average). It should be noted that whilst there were no differences in entropy at time 0 between the two groups, significant change was observed at 6-12 months, relating the corresponding features to the follow-up and disability (EDSS) progression. For the NAWM, significant differences were found between 0 month and 6-12 months with EDSS≤2 (contrast, inverse difference moment), for 6-12 months for EDSS>2 and 0 month with EDSS>2 (difference entropy) and for 6-12 months for EDSS>2 and EDSS≤2 (sum average); (iv) there was no significant difference for NAWM and the lesion texture features (for both 0 and 6-12 months) for subjects with no change in EDSS score versus subjects with increased EDSS score from 2 to 5 years. CONCLUSIONS: The findings of this study provide evidence that texture features of T2 MRI brain white matter lesions may have an additional potential role in the clinical evaluation of MRI images in MS and perhaps may provide some prognostic evidence in relation to future disability of patients. However, a larger scale study is needed to establish the application in clinical practice and for computing shape and texture features that may provide information for better and earlier differentiation between normal brain tissue and MS lesions.

Despeckle Filtering for Multiscale Amplitude-Modulation Frequency-Modulation (AM-FM) Texture Analysis of Ultrasound Images of the Intima-Media Complex.

The intima-media thickness (IMT) of the common carotid artery (CCA) is widely used as an early indicator of cardiovascular disease (CVD). Typically, the IMT grows with age and this is used as a sign of increased risk of CVD. Beyond thickness, there is also clinical interest in identifying how the composition and texture of the intima-media complex (IMC) changed and how these textural changes grow into atherosclerotic plaques that can cause stroke. Clearly though texture analysis of ultrasound images can be greatly affected by speckle noise, our goal here is to develop effective despeckle noise methods that can recover image texture associated with increased rates of atherosclerosis disease. In this study, we perform a comparative evaluation of several despeckle filtering methods, on 100 ultrasound images of the CCA, based on the extracted multiscale Amplitude-Modulation Frequency-Modulation (AM-FM) texture features and visual image quality assessment by two clinical experts. Texture features were extracted from the automatically segmented IMC for three different age groups. The despeckle filters hybrid median and the homogeneous mask area filter showed the best performance by improving the class separation between the three age groups and also yielded significantly improved image quality.

Segmentation of atherosclerotic carotid plaque in ultrasound video.

The degree of stenosis of the common carotid artery (CCA) but also the characteristics of the arterial wall including plaque size, composition and elasticity represent important predictors used in the assessment of the risk for future cardiovascular events. This paper proposes and evaluates an integrated system for the segmentation of atherosclerotic carotid plaque in ultrasound video of the CCA based on normalization, speckle reduction filtering (with the hybrid median filter) and parametric active contours. The algorithm is initialized in the first video frame of the cardiac cycle with human assistance and the moving atherosclerotic plaque borders are tracked and segmented in the subsequent frames. The algorithm is evaluated on 10 real CCA digitized videos from B-mode longitudinal ultrasound segments and is compared with the manual segmentations of an expert, for every 20 frames in a time span of 3-5 seconds, covering in general 2 cardiac cycles. The segmentation results are very satisfactory with a true negative fraction (TNF) of 79.3%, a true-positive fraction (TPF) of 78.12%, a false-positive fraction (FPF) of 6.7% and a false-negative fraction (FNF) of 19.6% between the ground truth and the presented plaque segmentations, a Williams index (KI) of 80.3%, an overlap index of 71.5%, a specificity of 0.88±0.09, a precision of 0.86±0.10 and an effectiveness measure of 0.77±0.09. The results show that integrated system investigated in this study could be successfully used for the automated video segmentation of the carotid plaque.

Atherosclerotic plaque ultrasound video encoding, wireless transmission, and quality assessment using H.264.

We propose a unifying framework for efficient encoding, transmission, and quality assessment of atherosclerotic plaque ultrasound video. The approach is based on a spatially varying encoding scheme, where video-slice quantization parameters are varied as a function of diagnostic significance. Video slices are automatically set based on a segmentation algorithm. They are then encoded using a modified version of H.264/AVC flexible macroblock ordering (FMO) technique that allows variable quality slice encoding and redundant slices (RSs) for resilience over error-prone transmission channels. We evaluate our scheme on a representative collection of ten ultrasound videos of the carotid artery for packet loss rates up to 30%. Extensive simulations incorporating three FMO encoding methods, different quantization parameters, and different packet loss scenarios are investigated. Quality assessment is based on a new clinical rating system that provides independent evaluations of the different parts of the video (subjective). We also use objective video-quality assessment metrics and estimate their correlation to the clinical quality assessment of plaque type. We find that some objective quality assessment measures computed over the plaque video slices gave very good correlations to mean opinion scores (MOSs). Here, MOSs were computed using two medical experts. Experimental results show that the proposed method achieves enhanced performance in noisy environments, while at the same time achieving significant bandwidth demands reductions, providing transmission over 3G (and beyond) wireless networks.

Multiscale amplitude-modulation frequency-modulation (AM-FM) texture analysis of ultrasound images of the intima and media layers of the carotid artery.

The intima-media thickness (IMT) of the common carotid artery (CCA) is widely used as an early indicator of cardiovascular disease (CVD). Clinically, there is strong interest in identifying how the composition and texture of the media layer (ML) can be associated with the risk of stroke. In this study, we use 2-D amplitude-modulation frequency-modulation (AM-FM) analysis of the intima-media complex (IMC), the ML, and intima layer (IL) of the CCA to detect texture changes as a function of age and sex. The study was performed on 100 ultrasound images acquired from asymptomatic subjects at risk of atherosclerosis. To investigate texture variations associated with age, we separated them into three age groups: 1) patients younger than 50; 2) patients aged between 50 and 60 years old; and 3) patients over 60 years old. We also separated the patients by sex. The IMC, ML, and IL were segmented manually by a neurovascular expert and also by a snake-based segmentation system. To reject strong edge artifacts, we prefilter with an AM-FM filterbank that is centered along the horizontal frequency axis (parallel to the long axis of the IMC, ML, and IL), while removing the low-pass filter estimates and frequency bands with large, vertical frequency components. To investigate significant texture changes, we extract the instantaneous amplitude (IA) and the magnitude of the instantaneous frequency (IF) over each layer component, for low-, medium-, and high-frequency AM-FM components. We detected significant texture differences between the higher risk age group of >60 years versus the lower risk age group of <50 and the 50-60 group. In particular, between the <50 and >60 groups, we found significant differences in the medium-scale IA extracted from the IMC. Between the >60 and the 50-60 groups, we found significant texture changes in the low-scale IA and high-scale IF magnitude extracted from the IMC, and the low-scale IA extracted from the IL. Also, we noted that the IA for the ML showed significant differences between males and females for all age groups. The AM--FM features provide complimentary information to classical texture analysis features like the gray-scale median, contrast, and coarseness. These findings provide evidence that AM--FM texture features can be associated with the progression of cardiovascular risk for disease and the risk of stroke with age. However, a larger scale study is needed to establish the application in clinical practice.

Multiscale amplitude-modulation frequency-modulation (AM-FM) texture analysis of multiple sclerosis in brain MRI images.

This study introduces the use of multiscale amplitude modulation-frequency modulation (AM-FM) texture analysis of multiple sclerosis (MS) using magnetic resonance (MR) images from brain. Clinically, there is interest in identifying potential associations between lesion texture and disease progression, and in relating texture features with relevant clinical indexes, such as the expanded disability status scale (EDSS). This longitudinal study explores the application of 2-D AM-FM analysis of brain white matter MS lesions to quantify and monitor disease load. To this end, MS lesions and normal-appearing white matter (NAWM) from MS patients, as well as normal white matter (NWM) from healthy volunteers, were segmented on transverse T2-weighted images obtained from serial brain MR imaging (MRI) scans (0 and 6-12 months). The instantaneous amplitude (IA), the magnitude of the instantaneous frequency (IF), and the IF angle were extracted from each segmented region at different scales. The findings suggest that AM-FM characteristics succeed in differentiating 1) between NWM and lesions; 2) between NAWM and lesions; and 3) between NWM and NAWM. A support vector machine (SVM) classifier succeeded in differentiating between patients that, two years after the initial MRI scan, acquired an EDSS ≤ 2 from those with EDSS > 2 (correct classification rate = 86%). The best classification results were obtained from including the combination of the low-scale IA and IF magnitude with the medium-scale IA. The AM-FM features provide complementary information to classical texture analysis features like the gray-scale median, contrast, and coarseness. The findings of this study provide evidence that AM-FM features may have a potential role as surrogate markers of lesion load in MS.

Classification of subtrochanteric femoral fractures.

A review of the literature identified 15 different classification methods for subtrochanteric femoral fractures. Only eight of those classifications defined the area of bone, which constituted a subtrochanteric fracture. The actual length of femur defined as the subtrochanteric zone varied from 3 cm up to the level of the femoral isthmus. There was no agreement between the different classifications regarding the proximal and distal border or for those fractures, which traverse anatomical boundaries. In the various classifications, fractures were subdivided into 2-15 subgroups. The majority of the identified studies were unable to find the classifications useful in either determining treatment or predicting the outcome after treatment. We subdivided subtrochanteric fractures into three types based on the degree of fracture comminution. We examined the inter- and intra-observer agreement of our recommended classification. One orthopaedic consultant, one specialist hip fracture surgeon, two trainee registrar orthopaedic surgeons and one specialty trainee in orthopaedics, on two different occasions, 8 weeks apart, independently classified the radiographs of 20 patients with a subtrochanteric fracture. The mean kappa value for inter- and intra-observer variation was 0.71 and 0.79, respectively, with both showing substantial agreement and, therefore, this simpler classification is recommended. Based on the review of previous classification methods, we also recommend that the subtrochanteric zone be defined as the one in which the fracture line crossing the femur is predominantly within the area of bone extending 5 cm below the lower border of the lesser trochanter.

Robust and efficient ultrasound video coding in noisy channels using H.264.

In this paper we define diagnostic Regions of Interest (ROIs) for carotid ultrasound medical video, which we then use as input for Flexible Macroblock Ordering (FMO) slice encoding. We extend the FMO concept by enabling variable quality slice encoding, tightly coupled by each region's diagnostic importance. Redundant Slices (RS) utilization increases compressed video's resilience over error prone transmission mediums. We evaluate our scheme on a series of five (5) carotid ultrasound videos at QCIF and CIF resolutions, for packet loss rates up to 30%. Quality assessment based on a clinical rating system that provides for independent evaluations of the different parts of the video (subjective), as well as PSNR ratings (objective), shows that encoded videos attain enhanced diagnostic performance under noisy environments, while at the same time achieving significant bandwidth demands reductions.

Avascular necrosis after internal fixation of intracapsular hip fractures; a study of the outcome for 1023 patients.

We prospectively studied 1023 patients who sustained an intracapsular hip fracture that was treated with internal fixation using contemporary methods. The overall incidence of avascular necrosis (AVN) was 6.6%. AVN was less common for undisplaced (4.0%) than for displaced fractures (9.5%) and in men (4.9%) than women (11.4%) who had a displaced fracture. The incidence of AVN for those aged less than 60 years and who sustained a displaced fracture was 20.6%, compared to 12.5% for those aged 60-80 years and 2.5% for those aged more than 80 years. Our study showed an increased risk of AVN with younger age and in females with a displaced fracture. We found no association between the incidence of AVN and the interval between injury to surgery.

Ultrasound image texture analysis of the intima and media layers of the common carotid artery and its correlation with age and gender.

The intima-media thickness (IMT) of the common carotid artery (CCA) is widely used as an early indicator of cardiovascular disease (CVD). It was proposed but not thoroughly investigated that the composition and texture of the media layer (ML) can be used as an indicator for the risk of stroke. In this study, we investigate the application of texture analysis of the ML of the CCA and how texture is affected by age and gender. The study was performed on 100 longitudinal-section ultrasound images acquired from asymptomatic subjects at risk of atherosclerosis. The images were separated into three different age groups, namely below 50, 50-60, and above 60 years old. Furthermore, the images were separated according to gender. A total of 61 different texture features were extracted from the intima layer (IL), the ML, and the intima-media complex (IMC). The ML and the IMC were segmented manually by a neurovascular expert and also automatically by a snakes segmentation system. We have found that male patients tended to have larger media layer thickness (MLT) values as compared to the MLT of female patients of the same age. We have found significant differences among texture features extracted from the IL, ML and IMC from different age groups. Furthermore, for some texture features, we found that they follow trends that correlate with a patient's age. For example, the gray-scale median GSM of the ML falls linearly with increasing MLT and with increasing age. Our findings suggest that ultrasound image texture analysis of the media layer has potential as an assessment biomarker for the risk of stroke.

A systematic review of early versus delayed treatment for type III supracondylar humeral fractures in children.

We performed a systematic review of early versus delayed treatment for type III Gartland supracondylar humeral fractures in children. We identified five non-randomised retrospective studies that fulfilled our criteria. We performed the analysis on 396 patients who sustained a type III supracondylar humeral fracture of which 243 (61.4%) belonged to the early treatment group and 153 (38.6%) belonged to the delayed treatment group. The planned treatment was closed reduction and percutaneous pin fixation. We found that failure of closed reduction and conversion to open reduction was significantly higher in the delayed treatment group (22.9%) as compared with the early treatment group (11.1%). Our study provides evidence that type III supracondylar humeral fractures in children should be treated early within 12h of injury.

Media thickness measurement of the common carotid artery.

The intima-media thickness (IMT) of the common carotid artery (CCA) is widely used as an early indicator of the development of cardiovascular disease (CVD). It was proposed but not thoroughly investigated that the media thickness (MT), its composition and texture may be indicative for identifying the risk of stroke and differentiating between patients with high and low risk. In this study we present an automated method for segmentation of the media layer and measurement of its thickness in ultrasound images of the CCA. The snakes segmentation method was used, and was evaluated on 100 images against manual segmentation. The mean +/- standard deviation (sd) for the manual and the automated IMT measurements were 0.71+/-0.17 mm and 0.67+/-0.12 mm, and for the manual and the automated MT measurements were 0.25+/-0.12 mm and 0.25+/-0.11 mm respectively. There was no significant difference between the manual and the automated measurements. Further research for validating the proposed technique is required and for evaluating it in a larger sample of subjects.

Snakes based segmentation of the common carotid artery intima media.

Ultrasound measurements of the human carotid artery walls are conventionally obtained by manually tracing interfaces between tissue layers. In this study we present a snakes segmentation technique for detecting the intima-media layer of the far wall of the common carotid artery (CCA) in longitudinal ultrasound images, by applying snakes, after normalization, speckle reduction, and normalization and speckle reduction. The proposed technique utilizes an improved snake initialization method, and an improved validation of the segmentation method. We have tested and clinically validated the segmentation technique on 100 longitudinal ultrasound images of the carotid artery based on manual measurements by two vascular experts, and a set of different evaluation criteria based on statistical measures and univariate statistical analysis. The results showed that there was no significant difference between all the snakes segmentation measurements and the manual measurements. For the normalized despeckled images, better snakes segmentation results with an intra-observer error of 0.08, a coefficient of variation of 12.5%, best Bland-Altman plot with smaller differences between experts (0.01, 0.09 for Expert1 and Expert 2, respectively), and a Hausdorff distance of 5.2, were obtained. Therefore, the pre-processing of ultrasound images of the carotid artery with normalization and speckle reduction, followed by the snakes segmentation algorithm can be used successfully in the measurement of IMT complementing the manual measurements. The present results are an expansion of data published earlier as an extended abstract in IFMBE Proceedings (Loizou et al. IEEE Int X Mediterr Conf Medicon Med Biol Eng POS-03 499:1-4, 2004).

Quality evaluation of ultrasound imaging in the carotid artery based on normalization and speckle reduction filtering.

Image quality is important when evaluating ultrasound images of the carotid for the assessment of the degree of atherosclerotic disease, or when transferring images through a telemedicine channel, and/or in other image processing tasks. The objective of this study was to investigate the usefulness of image quality evaluation based on image quality metrics and visual perception, in ultrasound imaging of the carotid artery after normalization and speckle reduction filtering. Image quality was evaluated based on statistical and texture features, image quality evaluation metrics, and visual perception evaluation made by two experts. These were computed on 80 longitudinal ultrasound images of the carotid bifurcation recorded from two different ultrasound scanners, the HDI ATL-3000 and the HDI ATL-5000 scanner, before (NF) and after (DS) speckle reduction filtering, after normalization (N), and after normalization and speckle reduction filtering (NDS). The results of this study showed that: (1) the normalized speckle reduction, NDS, images were rated visually better on both scanners; (2) the NDS images showed better statistical and texture analysis results on both scanners; (3) better image quality evaluation results were obtained between the original (NF) and normalized (N) images, i.e. NF-N, for both scanners, followed by the NF-DS images for the ATL HDI-5000 scanner and the NF-DS on the HDI ATL-3000 scanner; (4) the ATL HDI-5000 scanner images have considerable higher entropy than the ATL HDI-3000 scanner and thus more information content. However, based on the visual evaluation by the two experts, both scanners were rated similarly. The above findings are also in agreement with the visual perception evaluation, carried out by the two vascular experts. The results of this study showed that ultrasound image normalization and speckle reduction filtering are important preprocessing steps favoring image quality, and should be further investigated.

Fluoroscopy and Paget's disease of the breast.

A case report concerning a 36-year-old woman having developed Paget's disease of the breast subsequent to multiple fluoroscopies as a child for the investigation of Fallot's anomaly/pulmonary atresia is presented. This case is discussed with a brief review of the relevant literature regarding current theories as to the pathogenesis of Paget's disease of the breast, ionizing radiation and its role in dysplastic breast disease and their possible interrelation.