Ultrasound accuracy for brachial plexus pathology.

AIM: To determine (a) the accuracy of ultrasound in detecting brachial plexus pathology and (b) outline the advantages and limitations of ultrasound compared to MRI for imaging the brachial plexus. MATERIAL AND METHODS: cases with clinically suspected brachial plexus pathology were evaluated first by ultrasound, followed by MRI. Patients with prior brachial plexus imaging were excluded. The final diagnosis was based on a combination of ultrasound, MRI, clinical follow-up, and surgical findings. The accuracy of the ultrasound was assessed by comparing the ultrasound and the final diagnoses. The mean clinical follow-up time following ultrasound was 1.8 ± 1.4 years. RESULTS: Ninety-two (64%) of the 143 cases had normal brachial plexus ultrasound and MRI examinations. Fifty-one (36%) of 143 cases had brachial plexus pathology on MRI, comprising post-radiation fibrosis (n=25, 49%), nerve sheath tumor (n=11, 21%), traumatic injury (n=7, 14%), inflammatory polyneuropathy (n=4, 8%), malignant infiltration (n=2, 4%), desmoid fibromatosis (n=1,2%), and neuralgic amyotrophy (n=1, 2%). Overall diagnostic accuracy of ultrasound for brachial plexus pathology was 98% (140/143), with three discordant cases (neuralgic amyotrophy n=1, inflammatory neuropathy n=1, postradiation fibrosis n=1) regarded as normal on ultrasound assessment. Sensitivity, specificity, and positive and negative predictive value of ultrasound for identifying brachial plexus pathology were 94%, 100%, 100%, and 97%, respectively. CONCLUSION: Ultrasound identifies brachial plexus pathology with high accuracy and specificity, showing comparable diagnostic efficacy to MRI. Ultrasound can serve as an effective first-line imaging investigation for suspected brachial plexus pathology.

Ultrasound-guided lymph node sampling: accuracy of FNAC, end-cutting (Franseen), and side-cutting (Temno) needle biopsy techniques.

AIM: To compare technical success, diagnostic accuracy, and histological yield of fine-needle aspiration cytology (FNAC), side-cutting (Temno) needle biopsy, and end-cutting (Franseen) needle biopsy for ultrasound-guided sampling of groin and axillary lymph nodes. MATERIALS AND METHODS: A total of 270 abnormal groin and axillary nodes were sampled using one of the three techniques. Nodes with a maximum length of <2.5 cm underwent FNAC or Franseen biopsy, while nodes >2.5 cm underwent Temno biopsy. Mean size of nodes sampled by FNAC (21.2 mm) and Franseen (19.7 mm) were similar while nodes sampled by Temno were larger (34.4 mm, p<0.0001). RESULTS: Technical success rates of FNAC (82/93, 88%), Franseen (105/111, 95%), and Temno (59/66, 89%) biopsies were similar (p>0.05 for all). Lymphoid tissue yield by FNAC (mean total area 1.51 mm2) was less than that by Franseen (7.14 mm2, p=0.002) or Temno biopsy (19.44 mm2, p<0.0001). Diagnostic accuracy for malignancy was lower for FNAC (22/30, 73%) than Franseen (25/26, 96%, p=0.02) or Temno biopsy (32/32, 100%, p=0.002). For malignant nodes, determining the likely organ of origin was also lower for FNAC (7/30, 23%) than Franseen (19/26, 73%, p=0.0002) or Temno biopsy (29/32, 91%, p<0.0001), with a similar pattern observed in the identification of lymphoma. CONCLUSION: For similarly sized nodes, Franseen biopsy provided more lymphoid material, a higher diagnostic accuracy for malignancy including lymphoma, and better identification of the likely organ of origin than FNAC. Routine use of Franseen biopsy is advocated rather than FNAC for percutaneous sampling of lymph nodes not suitable for side-cutting needle biopsy.

Evaluation of organic contamination in urban groundwater surrounding a municipal landfill, Zhoukou, China.

This paper investigates the organic pollution status of shallow aquifer sediments and groundwater around Zhoukou landfill. Chlorinated aliphatic hydrocarbons, monocylic aromatic hydrocarbons, halogenated aromatic hydrocarbons, organochlorine pesticides and other pesticides, and polycyclic aromatic hydrocarbons (PAHs) have been detected in some water samples. Among the detected eleven PAHs, phenanthrene, fluorine, and fluoranthene are the three dominant in most of the groundwater samples. Analysis of groundwater samples around the landfill revealed concentrations of PAHs ranging from not detected to 2.19 µg/L. The results show that sediments below the waste dump were low in pollution, and the shallow aquifer, at a depth of 18-30 m, was heavily contaminated, particularly during the wet season. An oval-shaped pollution halo has formed, spanning 3 km from west to east and 2 km from south to north, and mainly occurs in groundwater depths of 2-4 m. For PAH source identification, both diagnostic ratios of selected PAHs and principal component analysis were studied, suggesting mixed sources of pyro- and petrogenic derived PAHs in the Zhoukou landfill. Groundwater table fluctuations play an important role in the distribution of organic pollutants within the shallow aquifer. A conceptual model of leachate migration in the Quaternary aquifers surrounding the Zhoukou landfill has been developed to describe the contamination processes based on the major contaminant (PAHs). The groundwater zone contaminated by leachate has been identified surrounding the landfill.

Reliability of shear wave ultrasound elastography for neck lesions identified in routine clinical practice.

PURPOSE: To evaluate the reliability of shear wave ultrasound elastography (SWE) in the neck. MATERIALS AND METHODS: 176 neck lesions (40 thyroid, 56 lymph nodes, 46 salivary, 34 miscellaneous) identified in a routine US clinic underwent SWE by one or two blinded radiologists. For this study, SWE required the operator to acquire three 10 second dynamic colour-coded SWE cineloops per lesion, select one static image per cineloop, and place circular regions-of-interest within the entire lesion and stiffest part to generate 3 SWE measurements per static image. For logistical reasons, one radiologist evaluated all 176 lesions and the other evaluated 58 lesions. Both radiologists also reviewed 27 archived cineloops independently to assess SWE excluding practical technique. Reliability was assessed using intraclass correlation coefficients (ICCs) concordance correlation coefficients (CCCs) and coefficients of repeatability (CORs). RESULTS: Test-retest ICCs for the radiologist evaluating 176 lesions were 0.78 - 0.85 (fair-excellent agreement), CCCs were 0.85 - 0.88 (substantial agreement), and CORs were 14.9 - 36.1 kPa. For both radiologists evaluating 58 lesions, intra-rater and inter-rater ICCs were 0.65 - 0.78 and 0.72 - 0.77 respectively. For SWE excluding practical technique, inter-rater ICCs were 0.97 - 0.98 (excellent agreement). ICCs differed according to tissue, being higher in thyroid lesions than lymph nodes (p < 0.001), and higher in benign than malignant lesions (p values < 0.001). CONCLUSION: Intra- and inter-rater reliability of SWE is fair to excellent according to ICCs. SWE reliability is influenced appreciably by acquisition technique. Nevertheless, CORs for SWE are not negligible. To determine whether these results are acceptable clinically, further research is required to establish SWE stiffness values of normal and pathological tissues in the neck.

Image segmentation using fuzzy region competition and spatial/frequency information.

This paper presents a multiphase fuzzy region competition model that takes into account spatial and frequency information for image segmentation. In the proposed energy functional, each region is represented by a fuzzy membership function and a data fidelity term that measures the conformity of spatial and frequency data within each region to (generalized) gaussian densities whose parameters are determined jointly with the segmentation process. Compared with the classical region competition model, our approach gives soft segmentation results via the fuzzy membership functions, and moreover, the use of frequency data provides additional region information that can improve the overall segmentation result. To efficiently solve the minimization of the energy functional, we adopt an alternate minimization procedure and make use of Chambolle's fast duality projection algorithm. We apply the proposed method to synthetic and natural textures as well as real-world natural images. Experimental results show that our proposed method has very promising segmentation performance compared with the current state-of-the-art approaches.

Texture classification using refined histogram.

In this correspondence, we propose a novel, efficient, and effective Refined Histogram (RH) for modeling the wavelet subband detail coefficients and present a new image signature based on the RH model for supervised texture classification. Our RH makes use of a step function with exponentially increasing intervals to model the histogram of detail coefficients, and the concatenation of the RH model parameters for all wavelet subbands forms the so-called RH signature. To justify the usefulness of the RH signature, we discuss and investigate some of its statistical properties. These properties would clarify the sufficiency of the signature to characterize the wavelet subband information. In addition, we shall also present an efficient RH signature extraction algorithm based on the coefficient-counting technique, which helps to speed up the overall classification system performance. We apply the RH signature to texture classification using the well-known databases. Experimental results show that our proposed RH signature in conjunction with the use of symmetrized Kullback-Leibler divergence gives a satisfactory classification performance compared with the current state-of-the-art methods.

Statistical wavelet subband characterization based on generalized gamma density and its application in texture retrieval.

The modeling of image data by a general parametric family of statistical distributions plays an important role in many applications. In this paper, we propose to adopt the three-parameter generalized Gamma density (GGammaD) for modeling wavelet detail subband histograms and for texture image retrieval. The advantage of GGammaD over the existing generalized Gaussian density (GGD) is that it provides more flexibility to control the shape of model which is critical for practical histogram-based applications. To measure the discrepancy between GGammaDs, we use the symmetrized Kullback-Leibler distance (SKLD) and derive a closed form for the SKLD between GGammaDs. Such a distance can be computed directly and effectively via the model parameters, making our proposed scheme particularly suitable for image retrieval systems with large image database. Experimental results on the well-known databases reveal the superior performance of our proposed method compared with the current existing approaches.

Statistical properties of bit-plane probability model and its application in supervised texture classification.

The modeling of wavelet subband histograms via the product Bernoulli distributions (PBD) has received a lot of interest and the PBD model has been applied successfully in texture image retrieval. In order to fully understand the usefulness and effectiveness of the PBD model and its associated signature, namely, the bit-plane probability (BP) signature on image processing applications, we discuss and investigate some of their statistical properties. These properties would help to clarify the sufficiency of the BP signature to characterize wavelet subbands, which, in turn, justifies its use in real time applications. We apply the BP signature on supervised texture classification problem and experimental results suggest that the weighted L(1)-norm (rather than the standard L (1)-norm) should be used for the BP signature. Comparative classification experiments show that our method outperforms the current state-of-the-art Generalized Gaussian Density approaches.

A fast and effective model for wavelet subband histograms and its application in texture image retrieval.

This paper presents a novel, effective, and efficient characterization of wavelet subbands by bit-plane extractions. Each bit plane is associated with a probability that represents the frequency of 1-bit occurrence, and the concatenation of all the bit-plane probabilities forms our new image signature. Such a signature can be extracted directly from the code-block code-stream, rather than from the de-quantized wavelet coefficients, making our method particularly adaptable for image retrieval in the compression domain such as JPEG2000 format images. Our signatures have smaller storage requirement and lower computational complexity, and yet, experimental results on texture image retrieval show that our proposed signatures are much more cost effective to current state-of-the-art methods including the generalized Gaussian density signatures and histogram signatures.

Prognostic significance of serum vascular endothelial growth factor and endostatin in patients with hepatocellular carcinoma.

BACKGROUND: Vascular endothelial growth factor (VEGF) and endostatin stimulate and inhibit tumour angiogenesis respectively. Recent studies have demonstrated the prognostic value of serum levels of both VEGF and endostatin in patients with various types of cancer. Their significance in patients with hepatocellular carcinoma (HCC) remains unclear. METHODS: Serum VEGF and endostatin levels were measured by enzyme immunoassay in 108 patients with HCC before surgical resection and in 20 healthy controls. Preoperative serum VEGF and endostatin levels were correlated with clinicopathological features and long-term survival. RESULTS: Serum VEGF levels in patients with HCC were significantly higher than those in controls, but serum levels of endostatin were similar in the two groups. High serum levels of VEGF, but not endostatin, were significantly associated with venous invasion and advanced tumour stage. Patients with a serum VEGF level higher than median (over 245.0 pg/ml) had significantly worse overall and disease-free survival than those with a lower level (P = 0.012 and P = 0.022 respectively). On multivariate analysis, serum VEGF level was an independent prognostic factor (hazard ratio 1.86 (95 per cent confidence interval 1.10 to 3.92); P = 0.032). Serum endostatin levels did not have significant prognostic influence on overall or disease-free survival. CONCLUSION: A high serum level of VEGF is a predictor of poor outcome after resection of HCC. Serum VEGF, but not endostatin, may be a useful prognostic marker in patients with HCC.

Over-expression of FoxM1 stimulates cyclin B1 expression.

FoxM1 (previously named WIN, HFH-11 or Trident) is a Forkhead box (Fox) transcription factor widely expressed in proliferating cells. Various findings, including a recent analysis of FoxM1 knockout mice, suggest that FoxM1 is required for normal S-M coupling during cell cycle progression. To study the regulatory role of FoxM1 and its downstream regulatory targets, three stably transfected HeLa lines that display doxycycline (dox)-inducible FoxM1 expression were established. Over-expression of FoxM1 by dox induction facilitates growth recovery from serum starvation. Quantitation of cyclin B1 and D1 levels using flow cytometric, Western and Northern analyses reveals that elevated FoxM1 levels lead to stimulation of cyclin B1 but not cyclin D1 expression. Transient reporter assays in the dox-inducible lines and upon co-transfection with a constitutive FoxM1 expression plasmid suggest that FoxM1 can activate the cyclin B1 promoter.

Fast fractal image encoding based on adaptive search.

This paper presents a new adaptive search approach to reduce the computational complexity of fractal encoding. A simple but very efficient adaptive necessary condition is introduced to exclude a large number of unqualified domain blocks so as to speed-up fractal image compression. Furthermore, we analyzed an unconventional affine parameter that has better properties than the conventional luminance offset. Specifically, we formulated an optimal bit allocation scheme for the simultaneous quantizations of the usual scaling and the aforementioned unconventional affine parameter. Experiments on standard images showed that our adaptive search method yields superior performance over conventional fractal encoding.