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Η φωτογραφία μου
Medicine by Alexandros G. Sfakianakis,Anapafseos 5 Agios Nikolaos 72100 Crete Greece,00302841026182,00306932607174,alsfakia@gmail.com, https://plus.google.com/communities/115462130054650919641?sqinv=VFJWaER0c2NCRl9ERzRjZWhxQmhzY09kVV84cjRn , ,https://plus.google.com/u/0/+AlexandrosGSfakianakis , https://www.youtube.com/channel/UCQH21WX8Qn5YSTKrlJ3OrmQ , https://www.youtube.com/channel/UCTREJHxB6yt4Gaqs4-mLzDA , https://twitter.com/g_orl?lang=el, https://www.instagram.com/alexandrossfakianakis/,

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Κυριακή, 18 Μαρτίου 2018

Predictive significance of breast-specific gamma imaging for upstaging core-needle biopsy-detected ductal carcinoma in situ to invasive cancer

Abstract

Objective

We evaluated the significance of breast-specific gamma imaging (BSGI) for determination of upstaging to invasive cancer from preoperative ductal carcinoma in situ (DCIS).

Methods

This study enrolled 168 patients with 175 breast lesions diagnosed as DCIS on core-needle biopsy that subsequently underwent preoperative BSGI between September 2011 and October 2017. Both qualitative and quantitative analyses using tumor-to-normal background ratio (TNR) and coefficient of variation (COV) were performed, and the predictive significance for upstaging to invasive cancer was investigated. We also sought to identify clinicopathological factors associated with upstaging and their relation to BSGI findings.

Results

Fifty-eight lesions (33.1%) were confirmed to be invasive breast cancer after the final surgical approach. On univariate analysis, tumor size based on ultrasonography (US), hormone status, histologic grade, Breast Imaging Reporting and Data System category, comedo-necrosis, Ki-67 expression, and BSGI findings were associated with upstaging to invasive cancer. Tumor size > 2.0 cm (p = 0.005), Ki-67 expression > 8% (p < 0.001), qualitative BSGI findings (p = 0.020), and COV > 30.44 (p = 0.022) were independently associated with upstaging after multiple regression analysis.

Conclusion

BSGI is a useful imaging modality for predicting upstaging to invasive breast cancer from DCIS on core-needle biopsy in conjunction with US tumor size and Ki-67 expression.



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Automatic bladder segmentation from CT images using deep CNN and 3D fully connected CRF-RNN

Abstract

Purpose

Automatic approach for bladder segmentation from computed tomography (CT) images is highly desirable in clinical practice. It is a challenging task since the bladder usually suffers large variations of appearance and low soft-tissue contrast in CT images. In this study, we present a deep learning-based approach which involves a convolutional neural network (CNN) and a 3D fully connected conditional random fields recurrent neural network (CRF-RNN) to perform accurate bladder segmentation. We also propose a novel preprocessing method, called dual-channel preprocessing, to further advance the segmentation performance of our approach.

Methods

The presented approach works as following: first, we apply our proposed preprocessing method on the input CT image and obtain a dual-channel image which consists of the CT image and an enhanced bladder density map. Second, we exploit a CNN to predict a coarse voxel-wise bladder score map on this dual-channel image. Finally, a 3D fully connected CRF-RNN refines the coarse bladder score map and produce final fine-localized segmentation result.

Results

We compare our approach to the state-of-the-art V-net on a clinical dataset. Results show that our approach achieves superior segmentation accuracy, outperforming the V-net by a significant margin. The Dice Similarity Coefficient of our approach (92.24%) is 8.12% higher than that of the V-net. Moreover, the bladder probability maps performed by our approach present sharper boundaries and more accurate localizations compared with that of the V-net.

Conclusion

Our approach achieves higher segmentation accuracy than the state-of-the-art method on clinical data. Both the dual-channel processing and the 3D fully connected CRF-RNN contribute to this improvement. The united deep network composed of the CNN and 3D CRF-RNN also outperforms a system where the CRF model acts as a post-processing method disconnected from the CNN.



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Detoxification of U(VI) by Paecilomyces catenlannulatus investigated by batch, XANES and EXAFS techniques

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Publication date: September 2018
Source:Journal of Environmental Radioactivity, Volume 189
Author(s): Fengbo Li, Xiaoyu Li, Pu Cui
Paecilomyces catenlannulatus (P. catenlannulatus) as a genus of entomogenous fungus presented a variety of surface reactive groups by batch characterizations. The detoxification of U(VI) by P. catenlannulatus was investigated under different water chemistry (pH, incubation time, foreign anions and U(VI) concentration) by batch techniques. Approximately 75% of U(VI) was reduced to U(IV) (i.e., U(IV)O2(s)) by P. catenlannulatus at pH 5.5 and 7 days under glovebox conditions, therefore the formation of precipitates decreased the toxicity of U(VI) for P. catenlannulatus. In addition, phosphate facilitate the U(VI) reduction, whereas carbonate and sulfate inhibited the U(VI) reduction. The activities of catalase (CAT), superoxide dismutase (SOD) and glutathione (GSH) level were stimulated exposure to 1-30 mg/L U(VI), indicating that CAT, SOD and GSH were antagonized for the oxidant stress derived from U(VI) at low concentrations. According to XPS and XANES analysis, the occurrence of U(IV) revealed the reduction of adsorbed U(VI) to U(IV) by P. catenlannulatus. The results of EXAFS analysis indicated that the fitting of U-O and U-U shell for U-loaded P. catenlannulatus was similar to that of U(IV)O2(s)). The formation of U-bearing precipitates decreased the toxicity of U(VI) for P. catenlannulatus. These findings indicated that P. catenlannulatus is capable to detoxify U(VI) by extracellar/intracellar defense systems. Therefore, P. catenlannulatus can be utilized as a promising bioadsorbents for remediation of uranium-contaminated wastewater in environmental cleanup.



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Three-Dimensional Black Blood Contrast Enhanced Magnetic Resonance Imaging in Patients with Acute Ischemic Stroke and Negative Susceptibility Vessel Sign

Publication date: Available online 17 March 2018
Source:European Journal of Radiology
Author(s): Sung Hyun Baik, Hyo Sung Kwak, Seung Bae Hwang, Gyung Ho Chung
PurposeThe purpose of this study was to evaluate the enhancement patterns of three-dimensional (3D) black blood (BB) contrast enhanced magnetic resonance (MR) imaging in acute stroke patients with negative susceptibility vessel sign (SVS).Materials and methodsFrom January 2014 to August 2016 we retrospectively reviewed MR imaging and MR angiography findings of patients who presented with acute stroke symptoms of less than 24 h duration. For the 394 patients enrolled, we assessed the frequency of patients who exhibited negative SVS on susceptibility weighted MR imaging (SWI) and positive enhancement in 3D BB contrast enhanced MR imaging. We subdivided the enrolled group according to whether the MR angiography findings suggested stenosis (stenosis group) or occlusion (occlusion group). Enhancement patterns on BB contrast enhanced MR imaging were compared between the two groups according to several qualitative parameters: intensity (weak or strong), morphology (linear/eccentric or round/concentric), length (focal or segmental) and multiplicity (single or multiple).ResultsSixty-two of 394 patients (15.7%) showed positive findings on BB contrast-enhanced MR imaging with negative SVS. Forty-two patients were classified into the stenosis group, and 20 patients were assigned to the occlusion group. Enhancement patterns of the stenosis group showed weak intensity, linear or eccentric morphology and focal lesion length on BB contrast enhanced MR imaging, compared to the occlusion group (P < 0.001). In contrast, enhancement patterns of the occlusion group showed strong intensity, round or concentric morphology and longer segmental lesion length, compared to the stenosis group (P < 0.001).ConclusionThree-dimensional BB contrast enhanced MR imaging in acute stroke patients with stenotic lesions and negative SVS shows enhancement patterns of linear or eccentric morphology and shorter, more focal lesions.



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