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%.     

An evaluation of numerical integration algorithms for the estimation of the area under the curve (AUC) in pharmacokinetic studies

Six numerical integration algorithms based on linear and log trapezoidal methods as well as four cubic-spline methods were proposed for estimation of area under the curve (AUC). These six different algorithms were implemented using IMSL/IDL^TM command language and evaluated using data simulated under five different dosing conditions and two different sampling conditions. Comparisons between AUC estimations using these six different algorithms and the theoretical results were made in terms of both overall AUC values and the superimposability of the concentration-time profiles. In well designed studies with ample data points, the algorithm based on IMSL/IDL^TM function CSSHAPE with concavity preservation gave the best performance. In contrast, when the frequency of blood collection was limited, the algorithm based on the log trapezoidal rule proved to be stable with reasonable accuracy, and is recommended as the practical method for numerical interpolation and integration in pharmacokinetic studies. Algorithms based on the combination of the log trapezoidal rule and cubic-spline methods using IMSL/IDL^TM function CSSHAPE can be developed to enhance overall performance.     

用ROC曲线评价肿瘤标志物LDH在急性白血病早期诊断中的临床价值

目的 探讨肿瘤标志物乳酸脱氢酶（LDH）在急性白血病早期诊断中的临床价值。方法 应用受试者工作特性曲线（ROC曲线）及其曲线下面积（AUC）抛物线估算法（以金标准计算准确度和敏感度），对51例急性白血病的早期患者及部分经治疗后缓解的患者、61例非急性白血病患者、61例健康体检者进行了LDH的检测及分析。结果 AUC为0．954，其可信区间为0．935－0．973，其下限0．935远离0．5，经治疗缓解的白血病患者LDH检验结果与治疗前数据经t检验证实＜0．0001。结论 LDH对急性白血病的早期诊断以及治疗效果与预后的评估均有着重要及较好的临床价值。     

Interocular mismatch in spatial frequency and directionality characteristics of striate cortical neurones

Summary Spatial-frequency dependence of directional tuning and directional bias was compared, for both eyes, in four previously established discrete classes of binocular feline striate cortical neurones. Two classes (respectively direction-selective or bidirectional at optimal spatial frequency) were directionality invariant at all spatial frequencies. In the remaining two classes, both directionbiased at optimal spatial frequency, directional bias either altered or reversed with change in spatial frequency. In all four classes, the directional tuning of a majority of neurones sharpened at high spatial frequency through either eye, although the bandpass characteristics were sometimes dissimilar for the two eyes. All neurones were of the same type through either eye. Amongst the two classes of direction-biased neurones, the strength of bias was commonly different through the two eyes. Where reversal of bias occurred, that reversal took place at different spatial frequencies for each eye. Thus, the direction and orientation preferences of cortical neurones are fixed at optimal spatial frequency, but their envelope of tuning to a gamut of spatial frequencies is not. These differences are potentially related to binocular coding of visual perspective, including dynamic object rotation in visual space.     

Least-square conformal brain mapping with spring energy

The human brain cortex is a highly convoluted sheet. Mapping of the cortical surface into a canonical coordinate space is an important tool for the study of the structure and function of the brain. Here, we present a technique based on least-square conformal mapping with spring energy for the mapping of the cortical surface. This method aims to reduce the metric and area distortion while maintaining the conformal map and computation efficiency. We demonstrate through numerical results that this method effectively controls metric and area distortion, and is computational efficient. This technique is particularly useful for fast visualization of the brain cortex.     

Binding units (BU) and the area under binding isotherms (AUI) new indices of effector-target conjugation

New methods for simplified quantitation of effector-target conjugation have been developed. The binding unit (BU) is defined as the number of target cells required to bind a specified percentage of effector cells. The number of binding units is determined from binding isotherms in which effector conjugate frequencies are measured by holding constant the number of effector cells and by varying the number of target cells. Alternately, a binding unit can be defined as the number of effector cells required to bind a specified percentage of target cells. In this case, BU is computed from binding isotherms in which target conjugate frequencies are measured at different values of effector cells by holding constant the number of target cells. Also, the area under the curve (AUI) of these isotherms is another index that can be used as an overall measure of the binding capacity in an effector-target system. The experimental values of BU and AUI determined from effector and target isotherms agree well with theoretical predictions based on our previously developed binding model (J. Immunol. Methods (1992) 155, 133–147). The relationship between BU and AUI, and procedures to determine these parameters are shown. The value of these indices to express effector-target conjugation quantitatively has been confirmed by determining the values of BU and AUI for the NK-K562 effector-target system.     

Effects of convergent strabismus on spatio-temporal response properties of neurons in cat area 18

Summary Single-cell recording experiments were carried out to determine whether rearing kittens with surgically induced convergent strabismus (esotropia) alters the development of receptive field (RF) properties of neurons in area 18. In agreement with previous work on kittens with divergent strabismus (exotropia), there was a marked loss of binocularly driven cells in area 18 of esotropic cats. In contrast to the striate cortex of strabismic cats, the spatial properties of area 18 neurons, including receptive-field size and spatial frequency tuning, did not differ from those in normal controls. On the other hand, we found that contrast thresholds, measured at an optimal spatial frequency, were significantly elevated, and that the contrast gain in many cells was reduced in strabismic cats. These deficits were observed in both eyes, though the cells dominated by the deviating eye had a lower response amplitude at all contrasts. Furthermore, temporal frequency tuning curves were abnormal in strabismic cats in that the optimal frequencies and temporal resolutions were shifted to lower values. These effects were also bilateral. Velocity tuning, measured with a high-contrast bar stimulus, revealed that area 18 neurons in strabismic cats were unable to respond to very high velocities compared to normals. This reduced response was more severe when measured with the deviating eye in spite of the bilateral nature of the deficit. Finally, latencies to electrical stimulation of the optic chiasm or the optic radiation were significantly longer in strabismic cats. The magnitude of these effects was virtually the same for both eyes. From these observations, we conclude that the temporal properties of area 18 neurons, particularly the cells abilities to follow fast temporal modulations, are affected by raising kittens with surgically induced convergent strabismus.     

Predicting development of sustained unresponsiveness to milk oral immunotherapy using epitope-specific antibody binding profiles

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Ras homolog gene family H (RhoH) deficiency induces psoriasis-like chronic dermatitis by promoting TH17 cell polarization

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