High performance in risk stratification of intraductal papillary mucinous neoplasms by confocal laser endomicroscopy image analysis with convolutional neural networks (with video).

BACKGROUND AND AIMS: EUS-guided needle-based confocal laser endomicroscopy (EUS-nCLE) can differentiate high-grade dysplasia/adenocarcinoma (HGD-Ca) in intraductal papillary mucinous neoplasms (IPMNs) but requires manual interpretation. We sought to derive predictive computer-aided diagnosis (CAD) and artificial intelligence (AI) algorithms to facilitate accurate diagnosis and risk stratification of IPMNs. METHODS: A post hoc analysis of a single-center prospective study evaluating EUS-nCLE (2015-2019; INDEX study) was conducted using 15,027 video frames from 35 consecutive patients with histopathologically proven IPMNs (18 with HGD-Ca). We designed 2 CAD-convolutional neural network (CNN) algorithms: (1) a guided segmentation-based model (SBM), where the CNN-AI system was trained to detect and measure papillary epithelial thickness and darkness (indicative of cellular and nuclear stratification), and (2) a reasonably agnostic holistic-based model (HBM) where the CNN-AI system automatically extracted nCLE features for risk stratification. For the detection of HGD-Ca in IPMNs, the diagnostic performance of the CNN-CAD algorithms was compared with that of the American Gastroenterological Association (AGA) and revised Fukuoka guidelines. RESULTS: Compared with the guidelines, both n-CLE-guided CNN-CAD algorithms yielded higher sensitivity (HBM, 83.3%; SBM, 83.3%; AGA, 55.6%; Fukuoka, 55.6%) and accuracy (SBM, 82.9%; HBM, 85.7%; AGA, 68.6%; Fukuoka, 74.3%) for diagnosing HGD-Ca, with comparable specificity (SBM, 82.4%; HBM, 88.2%; AGA, 82.4%; Fukuoka, 94.1%). Both CNN-CAD algorithms, the guided (SBM) and agnostic (HBM) models, were comparable in risk stratifying IPMNs. CONCLUSION: EUS-nCLE-based CNN-CAD algorithms can accurately risk stratify IPMNs. Future multicenter validation studies and AI model improvements could enhance the accuracy and fully automatize the process for real-time interpretation.

Effects of acupuncture at Neiguan (PC 6) of the pericardial meridian on blood pressure and heart rate variability.

The aims of this study were to investigate (i) if and when the blood pressure would rise or fall and (ii) the associated changes of human heart rate variability (HRV) by manual stimulation of the Neiguan (PC 6) acupuncture site. In this paper, two groups of six healthy male volunteers with ranges of ages 20-56 and 20-55 and with no neurological diseases participated in this study. In order to minimize artefacts, the electrocardiogram (ECG) and radial arterial pulse pressure wave were collected with the subjects alert but eyes closed before, during, and after sham/manual acupuncture. No statistically significant changes (P > 0.05) were found in the sham acupuncture group. As for the manual acupuncture group, the needle was inserted into the PC 6 acupoint and manually stimulated about 15 to 30 seconds to achieve De Qi sensation. Needles were left in place for 30 min and then removed. Analysis of the data due to acupuncture was then compared with the baseline values. Results indicate that the blood pressures of different subject can either rise (P < 0.01) or fall (P < 0.01). To further determine the indicator for one subject who exhibited both rise and fall of blood pressures, 7 more trials were given conducted with the same protocol until statistically significant results were obtained (P < 0.01). We found that his change of blood pressure was highly correlated (p = -0.94 and -0.99 for rise and fall, respectively) with the ratio of the magnitude of pulse pressure to that of the dicrotic notch in the local radial pulse wave (P < 0.01). As to the heart rate variability (HRV) spectra, significant changes in the low frequency (LF) and very low frequency (VLF) ranges were also detected. These results indicate that the autonomic innervations of heart have been modified. However, the information on the power of LF, high frequency (HF), and LF/HF of HRV are not conclusive to statistically differentiate the sympathetic contribution from that of the parasympathetic nervous systems at present stage.