Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.     

A prime-boost concept using a T-cell epitope-driven DNA vaccine followed by a whole virus vaccine effectively protected pigs in the pandemic H1N1 pig challenge model

Influenza A virus (IAV) vaccines in pigs generally provide homosubtypic protection but fail to prevent heterologous infections. In this pilot study, the efficacy of an intradermal pDNA vaccine composed of conserved SLA class I and class II T cell epitopes (EPITOPE) against a homosubtypic challenge was compared to an intramuscular commercial inactivated whole virus vaccine (INACT) and a heterologous prime boost approach using both vaccines. Thirty-nine IAV-free, 3-week-old pigs were randomly assigned to one of five groups including NEG-CONTROL (unvaccinated, sham-challenged), INACT-INACT-IAV (vaccinated with FluSure XP® at 4 and 7 weeks, pH1N1 challenged), EPITOPE-INACT-IAV (vaccinated with PigMatrix EDV at 4 and FluSure XP® at 7 weeks, pH1N1 challenged), EPITOPE-EPITOPE-IAV (vaccinated with PigMatrix EDV at 4 and 7 weeks, pH1N1 challenged), and a POS-CONTROL group (unvaccinated, pH1N1 challenged). The challenge was done at 9 weeks of age and pigs were necropsied at day post challenge (dpc) 5. At the time of challenge, all INACT-INACT-IAV pigs, and by dpc 5 all EPITOPE-INACT-IAV pigs were IAV seropositive. IFNγ secreting cells, recognizing vaccine epitope-specific peptides and pH1N1 challenge virus were highest in the EPITOPE-INACT-IAV pigs at challenge. Macroscopic lung lesion scores were reduced in all EPITOPE-INACT-IAV pigs while INACT-INACT-IAV pigs exhibited a bimodal distribution of low and high scores akin to naïve challenged animals. No IAV antigen in lung tissues was detected at necropsy in the EPITOPE-INACT-IAV group, which was similar to naïve unchallenged pigs and different from all other challenged groups. Results suggest that the heterologous prime boost approach using an epitope-driven DNA vaccine followed by an inactivated vaccine was effective against a homosubtypic challenge, and further exploration of this vaccine approach as a practical control measure against heterosubtypic IAV infections is warranted.     

寰枢椎侧块关节运动轨迹数学模型的探讨

应用最小二乘法拟合得到寰枢椎侧块关节运动轨迹方程 ,左半部是 :S(x) =-2 3 .2 42 9-8.663 1x-0 .45 91x2 ;右半部是 :S(x) =-19.683 8+ 7.15 5 4x-0 .3 5 2 6x2 。     

Real-time refinement of subthalamic nucleus targeting using Bayesian decision-making on the root mean square measure.

The subthalamic nucleus (STN) is a major target for treatment of advanced Parkinson's disease patients undergoing deep brain stimulation surgery. Microelectrode recording (MER) is used in many cases to identify the target nucleus. A real-time procedure for identifying the entry and exit points of the STN would improve the outcome of this targeting procedure. We used the normalized root mean square (NRMS) of a short (5 seconds) MER sampled signal and the estimated anatomical distance to target (EDT) as the basis for this procedure. Electrode tip location was defined intraoperatively by an expert neurophysiologist to be before, within, or after the STN. Data from 46 trajectories of 27 patients were used to calculate the Bayesian posterior probability of being in each of these locations, given RMS-EDT pair values. We tested our predictions on each trajectory using a bootstrapping technique, with the rest of the trajectories serving as a training set and found the error in predicting the STN entry to be (mean +/- SD) 0.18 +/- 0.84, and 0.50 +/- 0.59 mm for STN exit point, which yields a 0.30 +/- 0.28 mm deviation from the expert's target center. The simplicity and computational ease of RMS calculation, its spike sorting-independent nature and tolerance to electrode parameters of this Bayesian predictor, can lead directly to the development of a fully automated intraoperative physiological procedure for the refinement of imaging estimates of STN borders.     

On the synthesis of time‐varying LQG weights and noises along optimal control and state trajectories

A general approach to control non‐linear uncertain systems is to apply a pre‐computed nominal optimal control, and use a pre‐computed LQG compensator to generate control corrections from the on‐line measured data. If the non‐linear model, on which the optimal control and LQG compensator design is based, is of sufficient quality, and when the LQG compensator is designed appropriately, the closed‐loop control system is approximately optimal. This paper contributes to the selection and computation of the time‐varying LQG weighting and noise matrices, which determine the LQG compensator design. It is argued that the noise matrices may be taken time‐invariant and diagonal. Three very important considerations concerning the selection of the time‐varying LQG weighting matrices are turned into a concrete computational scheme. Thereby, the selection of the time‐varying LQG weighting matrices is reduced to selecting three scalar design parameters, each one weighting one consideration. Although the three considerations seem straightforward they may oppose one another. Furthermore, they usually result in time‐varying weighting matrices that are indefinite, rather than positive (semi) definite as required for the LQG design. The computational scheme presented in this paper addresses and resolves both problems. By two numerical examples the benefits of our optimal closed‐loop control system design are demonstrated and evaluated using Monte Carlo simulation. Copyright © 2005 John Wiley & Sons, Ltd.     

The use of 3D surface fitting for robust polyp detection and classification in CT colonography

In this paper we describe the development of a computationally efficient computer-aided detection (CAD) algorithm based on the evaluation of the surface morphology that is employed for the detection of colonic polyps in computed tomography (CT) colonography. Initial polyp candidate voxels were detected using the surface normal intersection values. These candidate voxels were clustered using the normal direction, convexity test, region growing and Gaussian distribution. The local colonic surface was classified as polyp or fold using a feature normalized nearest neighborhood classifier. The main merit of this paper is the methodology applied to select the robust features derived from the colon surface that have a high discriminative power for polyp/fold classification. The devised polyp detection scheme entails a low computational overhead (typically takes 2.20 min per dataset) and shows 100% sensitivity for phantom polyps greater than 5 mm. It also shows 100% sensitivity for real polyps larger than 10 mm and 91.67% sensitivity for polyps between 5 to 10 mm with an average of 4.5 false positives per dataset. The experimental data indicates that the proposed CAD polyp detection scheme outperforms other techniques that identify the polyps using features that sample the colon surface curvature especially when applied to low-dose datasets.     

Food-induced contact urticaria syndrome (CUS) in atopic dermatitis: reproducibility of repeated and duplicate testing with a skin provocation test, the skin application food test (SAFT)

IgE-mediated contact urticaria syndrome (CUS) is one of the manifestations of allergy in childhood atopic dermatitis (AD). Allergens such as foods and animal products penetrate the skin easily. They can then cause urticarial reactions in sensitized individuals. A provocation test system for foods, called the skin application food test (SAFT), has been developed. Over more than 5 years, a group of 175 patients with AD was built-up and investigated in a prospective follow-up study with SAFT. SAFT was more frequently positive in AD children aged 6–2 years than in older children. In several children of this population (Group 1), we repeated SAFT within a period of 1 year. In another unrelated group of children (Group 2–1), we compared the results of 'original' SAFT and SAFT using square chambers (Van der Bend) or Silver patches. In the 3rd group (Group 2–2) we compared'original' SAFT with SAFT using big Finn Chambers. The agreement between the tests was high: in Group 1, we observed 88 to 93% concordant scores, and in Group 2, the scores were 96% to 100%. Statistically, the K coefficient ranged from 0.71–0.87 in Group 1, and from 0.83–1.00 in Group 2. SAFT is therefore highly reproducible. Agreement was at least 88% between the scores (the lowest K value observed was at least 0.71).     

Filter properties of root mean square successive difference (RMSSD) for heart rate

The root mean square successive difference (RMSSD) in heart period series is a time domain measure of heart period variability. The RMSSD is sensitive to high-frequency heart period fluctuations in the respiratory frequency range and has been used as an index of vagal cardiac control. By transfer function simulations, the RMSSD statistic is shown to represent a high-pass filter that effectively captures respiratory sinus arrhythmia but also passes lower frequency fluctuations that can include sympathetic influences. These simulations, together with analysis of actual heart period series, reveal that the RMSSD is biased by basal heart period. Although between-subjects levels of RMSSD covary highly with spectral estimates of high-frequency variability, within-subject RMSSD change scores account for only 50-60% of the variance in spectral estimates. The present findings raise caveats in the applications and interpretation of the RMSSD statistic.     

Direct infant UV light exposure is associated with eczema and immune development

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四格移步试验在平衡功能障碍儿童中的信效度研究

目的 研究四格移步试验在平衡功能障碍的儿童中的信度效度,为儿童平衡功能障碍的临床评估提供试验依据。方法 研究对象为2018年1月-2019年2月在深圳市儿童医院就诊的平衡功能受损129例儿童,所有研究对象在1周内由A、B两名评估员评估3次,A负责第1、3次评估,B负责第2次评估;第1次评估内容为四格移步试验(FSST)、 Berg平衡量表(BBS)、计时起立行走测试(TUG)及10 m步行测试(10MWT),每个试验间休息3~5 min;第2、3次评估仅评估FSST,评估过程中,评估员不互相讨论,各自记录数据;应用Pearson相关性分析法检验FSST、BBS总分、TUG、10MWT评定结果的相关性以反映FSST的信度,分析FSST的评定者间信度及重测信度,应用CDM软件包检测区分度。结果 FSST与BBS、TUG、10MWT结果的相关系数为-0.985(-0.782~-0.605)、0.678(0.572~0.761)、0.721(0.626~0.795)(P＜0.001);FSST的评定者间信度为0.957,重测信度为0.979;不同年龄的患儿区分度(D)为0.801~0.989,不同病因的患儿区分度为(D)0.707~0.824。结论 FSST用于儿童平衡功能评估具较高的平行效度、评定者间一致性信度及重测信度,值得临床推广。