Although excellent intra- and interscanner reliability and reproducibility could support the feasibility of cross-site pooling of ASL data, pCASL with multiple PLDs may better assess the CBF of the human brain.

PurposeRadiomics, which extract large amount of quantification image features from diagnostic medical images had been widely used for prognostication, treatment response prediction and cancer detection. The treatment options for lung nodules depend on their diagnosis, benign or malignant. Conventionally, lung nodule diagnosis is based on invasive biopsy. Recently, radiomics features, a non-invasive method based on clinical images, have shown high potential in lesion classification, treatment outcome prediction.MethodsLung nodule classification using radiomics based on Computed Tomography (CT) image data was investigated and a 4-feature signature was introduced for lung nodule classification. Retrospectively, 72 patients with 75 pulmonary nodules were collected. Radiomics feature extraction was performed on non-enhanced CT images with contours which were delineated by an experienced radiation oncologist.ResultAmong the 750 image features in each case, 76 features were found to have significant differences between benign and malignant lesions. A radiomics signature was composed of the best 4 features which included Laws_LSL_min, Laws_SLL_energy, Laws_SSL_skewness and Laws_EEL_uniformity. The accuracy using the signature in benign or malignant classification was 84% with the sensitivity of 92.85% and the specificity of 72.73%.ConclusionThe classification signature based on radiomics features demonstrated very good accuracy and high potential in clinical application.

Recent brain imaging studies indicate that empathy for pain relies upon both the affective and/or the sensorimotor nodes of the pain matrix, and empathic neural responses are modulated by stimulus reality, personal experience, and affective link with others. The current work investigated whether and how empathic neural responses are modulated by emotional contexts in which painful stimulations are perceived. Using functional magnetic resonance imaging (fMRI), we first showed that perceiving a painful stimulation (needle penetration) applied to a face with neutral expression induced activation in the anterior cingulate cortex (ACC) relative to nonpainful stimulation (Q-tip touch). However, when observation of the painful stimuli delivered to a neutral face was intermixed with observation of painful or happy faces, the ACC activity decreased while the activity in the face area of the secondary somatosensory cortex increased to the painful stimulation. Moreover, the secondary somatosensory activity associated with the painful stimulation decreased when the painful stimulation was applied to faces with happy and painful expressions. The findings suggest that observing painful stimuli in an emotional context weakens affective responses but increases sensory responses to perceived pain and implies possible interactions between the affective and sensory components of the pain matrix during empathy for pain.

The aim of this study was to explore whether intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) can probe pre-treatment differences or monitor early response in patients with locally advanced breast cancer receiving neoadjuvant chemotherapy (NAC).Thirty-six patients with locally advanced breast cancer were imaged using multiple-b DWI with 12 b values ranging from 0 to 1000 s/mm2 at the baseline, and 28 patients were repeatedly scanned after the second cycle of NAC. Subjects were divided into pathologic complete response (pCR) and nonpathologic complete response (non-pCR) groups according to the surgical pathologic specimen. Parameters (D, D∗, f, maximum diameter [MD] and volume [V]) before and after 2 cycles of NAC and their corresponding change (Δparameter) between pCR and non-pCR groups were compared using the Student t test or nonparametric test. The diagnostic performance of different parameters was judged by the receiver-operating characteristic curve analysis.Before NAC, the f value of pCR group was significantly higher than that of non-pCR (32.40% vs 24.40%, P = 0.048). At the end of the second cycle of NAC, the D value was significantly higher and the f value was significantly lower in pCR than that in non-pCR (P = 0.001; P = 0.015, respectively), whereas the D∗ value and V of the pCR group was slightly lower than that of the non-pCR group (P = 0.507; P = 0.676, respectively). ΔD was higher in pCR (−0.45 × 10–3 mm2/s) than that in non-pCR (−0.07 × 10−3 mm2/s) after 2 cycles of NAC (P < 0.001). Δf value in the pCR group was significantly higher than that in the non-pCR group (17.30% vs 5.30%, P = 0.001). There was no significant difference in ΔD∗ between the pCR and non-pCR group (P = 0.456). The prediction performance of ΔD value was the highest (AUC [area under the curve] = 0.924, 95% CI [95% confidence interval] = 0.759–0.990). When the optimal cut-off was set at −0.163 × 10−3 mm2/s, the values for sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were up to 100% (95% CI = 66.4–100), 73.7% (95% CI = 48.8–90.9), 64.3% (95% CI = 35.6–86.0), and 100% (95% CI = 73.2–99.3), respectively.IVIM-derived parameters, especially the D and f value, showed potential value in the pre-treatment prediction and early response monitoring to NAC in locally advanced breast cancer. ΔD value had the best prediction performance for pathologic response after NAC.

BackgroundIn practice, online health communities have passed the adoption stage and reached the diffusion phase of development. In this phase, patients equipped with knowledge regarding the issues involved in health care are capable of switching between different communities to maximize their online health community activities. Online health communities employ doctors to answer patient questions, and high quality online health communities are more likely to be acknowledged by patients. Therefore, the factors that motivate patients to maintain ongoing relationships with online health communities must be addressed. However, this has received limited scholarly attention.ObjectiveThe purpose of this study was to identify the factors that drive patients to continue their use of online health communities where doctor-patient communication occurs. This was achieved by integrating the information system success model with online health community features.MethodsA Web spider was used to download and extract data from one of the most authoritative Chinese online health communities in which communication occurs between doctors and patients. The time span analyzed in this study was from January 2017 to March 2017. A sample of 469 valid anonymous patients with 9667 posts was obtained (the equivalent of 469 respondents in survey research). A combination of Web mining and structural equation modeling was then conducted to test the research hypotheses.ResultsThe results show that the research framework for integrating the information system success model and online health community features contributes to our understanding of the factors that drive patients' relationships with online health communities. The primary findings are as follows: (1) perceived usefulness is found to be significantly determined by three exogenous variables (ie, social support, information quality, and service quality; R2=0.88). These variables explain 87.6% of the variance in perceived usefulness of online health communities; (2) similarly, patient satisfaction was found to be significantly determined by the three variables listed above (R2=0.69). These variables explain 69.3% of the variance seen in patient satisfaction; (3) continuance use (dependent variable) is significantly influenced by perceived usefulness and patient satisfaction (R2=0.93). That is, the combined effects of perceived usefulness and patient satisfaction explain 93.4% of the variance seen in continuance use; and (4) unexpectedly, individual literacy had no influence on perceived usefulness and satisfaction of patients using online health communities.ConclusionsFirst, this study contributes to the existing literature on the continuance use of online health communities using an empirical approach. Second, an appropriate metric was developed to assess constructs related to the proposed research model. Additionally, a Web spider enabled us to acquire objective data relatively easily and frequently, thereby overcoming a major limitation of survey techniques.

BACKGROUND AND PURPOSE: Current knowledge of the collateral circulation remains sparse, and a noninvasive method to better characterize the role of collaterals is desirable. The aim of our study was to investigate the presence and distal flow of collaterals by using a new MR perfusion territory imaging, vessel-encoded arterial spin-labeling (VE-ASL).

• DWI-derived parameters by different models are related but provide diversified information. • Commonly used ADC by MEM of DWI overestimates the tissue water diffusivity. • DWI processed by BEM could separate blood perfusion from true diffusion effects. • The derived diffusion-related and perfusion-related parameters by BEM are superior to ADC.

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