Technical variety of anastomotic techniques used in proximal gastrectomy with double-tract-reconstruction - a narrative review.

In the past 40 years, the incidence of esophagogastric junction cancer has been gradually increasing worldwide. Currently, surgical resection remains the main radical treatment for early gastric cancer. Due to the rise of functional preservation surgery, proximal gastrectomy has become an alternative to total gastrectomy for surgeons in Japan and South Korea. However, the methods of digestive tract reconstruction after proximal gastrectomy have not been fully unified. At present, the principal methods include esophagogastrostomy, double flap technique, jejunal interposition, and double tract reconstruction. Related studies have shown that double tract reconstruction has a good anti-reflux effect and improves postoperative nutritional prognosis, and it is expected to become a standard digestive tract reconstruction method after proximal gastrectomy. However, the optimal anastomoses mode in current double tract reconstruction is still controversial. This article aims to review the current status of double tract reconstruction and address the aforementioned issues.

Dryopteris crassirhizoma Nakai.: A review of its botany, traditional use, phytochemistry, pharmacological activity, toxicology and pharmacokinetics.

ETHNOPHARMACOLOGICAL RELEVANCE: The Dryopteris crassirhizoma Nakai., a commonly used herb, is known as "Guan Zhong" in China, "Oshida" in Japan and "Gwanjung" in Korea. It has long been used for parasitic infestation, hemorrhages and epidemic influenza. AIM OF THE REVIEW: The present paper aims to provide an up-to-date review at the advancements of the investigations on the traditional use, phytochemistry, pharmacological activity, toxicology and pharmacokinetics of D. crassirhizoma. Besides, possible trends, therapeutic potentials, and perspectives for future research of this plant are also briefly discussed. MATERIALS AND METHODS: Relevant information on traditional use, phytochemistry, pharmacological activity, toxicology and pharmacokinetics of D. crassirhizoma was collected through published materials and electronic databases, including the Chinese Pharmacopoeia, Flora of China, Web of Science, PubMed, Baidu Scholar, Google Scholar, and China National Knowledge Infrastructure. 109 papers included in the article and we determined that no major information was missing after many checks. All authors participated in the review process for this article and all research paper are from authoritative published materials and electronic databases. RESULTS: 130 chemical components, among which phloroglucinols are the predominant groups, have been isolated and identified from D. crassirhizoma. D. crassirhizoma with its bioactive compounds is possessed of extensive biological activities, including anti-parasite, anti-microbial, anti-viral, anti-cancer, anti-inflammatory, anti-oxidant, anti-diabetic, bone protective, immunomodulatory, anti-platelet and anti-hyperuricemia activity. Besides, D. crassirhizoma has special toxicology and pharmacokinetics characterization. CONCLUSIONS: D. crassirhizoma is a traditional Chinese medicine having a long history of application. This review mainly summarized the different chemical components extract from D. crassirhizoma and various reported pharmacological effects. Besides, the toxicology and pharmacokinetics of D. crassirhizoma also be analysed in this review. However, the chemical components of D. crassirhizoma are understudied and require further research to expand its medicinal potential, and it is urgent to design a new extraction scheme, so that the active ingredients can be obtained at a lower cost.

Extraction, purification, structural characteristics, biological activities, and applications of polysaccharides from the genus Lilium: A review.

The genus Lilium (Lilium) has been widely used in East Asia for over 2000 years due to its rich nutritional and medicinal value, serving as both food and medicinal ingredient. Polysaccharides, as one of the most important bioactive components in Lilium, offer various health benefits. Recently, polysaccharides from Lilium plants have garnered significant attention from researchers due to their diverse biological properties including immunomodulatory, anti-oxidant, anti-diabetic, anti-tumor, anti-bacterial, anti-aging and anti-radiation effects. However, the limited comprehensive understanding of polysaccharides from Lilium plants has hindered their development and utilization. This review focuses on the extraction, purification, structural characteristics, biological activities, structure-activity relationships, applications, and relevant bibliometrics of polysaccharides from Lilium plants. Additionally, it delves into the potential development and future research directions. The aim of this article is to provide a comprehensive understanding of polysaccharides from Lilium plants and to serve as a basis for further research and development as therapeutic agents and multifunctional biomaterials.

Acorus tatarinowii Schott: A Review of Its Botany, Traditional Uses, Phytochemistry, and Pharmacology.

Acorus tatarinowii Schott (A. tatarinowii) is a natural medicinal plant. It plays an indispensable role in the treatment of diseases by the empirical medicine system and has achieved remarkable curative effects. A. tatarinowii is often used to treat various diseases, such as depression, epilepsy, fever, dizziness, heartache, stomachache, etc. More than 160 compounds of different structural types have been identified in A. tatarinowii, including phenylpropanoids, terpenoids, lignans, flavonoids, alkaloids, amides, and organic acids. These bioactive ingredients make A. tatarinowii remarkable for its pharmacological effects, including antidepressant, antiepileptic, anticonvulsant, antianxiety, neuroprotective, antifatigue, and antifungal effects, improving Alzheimer's disease, and so on. It is noteworthy that A. tatarinowii has been widely used in the treatment of brain diseases and nervous system diseases and has achieved satisfactory therapeutic effects. This review focused on the research publications of A. tatarinowii and aimed to summarize the advances in the botany, traditional uses, phytochemistry, and pharmacology, which will provide a reference for further studies and applications of A. tatarinowii.

Extraction, Purification, Structural Characteristics, Biological Activity and Application of Polysaccharides from Portulaca oleracea L. (Purslane): A Review.

Portulaca oleracea L. (purslane) is a widely distributed plant with a long history of cultivation and consumption. Notably, polysaccharides obtained from purslane exhibit surprising and satisfactory biological activities, which explain the various benefits of purslane on human health, including anti-inflammatory, antidiabetic, antitumor, antifatigue, antiviral and immunomodulatory effects. This article systematically reviews the extraction and purification methods, chemical structure, chemical modification, biological activity and other aspects of polysaccharides from purslane collected in the Chinese Pharmacopoeia, Flora of China, Web of Science, PubMed, Baidu Scholar, Google Scholar and CNKI databases in the last 14 years, using the keywords "Portulaca oleracea L. polysaccharides" and "purslane polysaccharides". The application of purslane polysaccharides in different fields is also summarized, and its application prospects are also discussed. This paper provides an updated and deeper understanding of purslane polysaccharides, which will provide useful guidance for the further optimization of polysaccharide structures and the development of purslane polysaccharides as a novel functional material, as well as a theoretical basis for its further research and application in human health and manufacturing development.

Extraction, Purification, Structural Characteristics, Biological Activities, and Applications of the Polysaccharides from Zingiber officinale Roscoe. (Ginger): A Review.

Zingiber officinale Roscoe. (ginger) is a widely distributed plant with a long history of cultivation and consumption. Ginger can be used as a spice, condiment, food, nutrition, and as an herb. Significantly, the polysaccharides extracted from ginger show surprising and satisfactory biological activity, which explains the various benefits of ginger on human health, including anti-influenza, anti-colitis, anti-tussive, anti-oxidant, anti-tumor effects. Here, we systematically review the major studies on the extraction and purification of polysaccharides from ginger in recent years, the characterization of their chemical structure, biological activity, and structure-activity relationships, and the applications of ginger polysaccharides in different fields. This article will update and deepen the understanding of ginger polysaccharide and provide a theoretical basis for its further research and application in human health and product development.

Development of an approach to extracting coronary arteries and detecting stenosis in invasive coronary angiograms.

Purpose: In stable coronary artery disease (CAD), reduction in mortality and/or myocardial infarction with revascularization over medical therapy has not been reliably achieved. Coronary arteries are usually extracted to perform stenosis detection. As such, developing accurate segmentation of vascular structures and quantification of coronary arterial stenosis in invasive coronary angiograms (ICA) is necessary. Approach: A multi-input and multiscale (MIMS) U-Net with a two-stage recurrent training strategy was proposed for the automatic vessel segmentation. The proposed model generated a refined prediction map with the following two training stages: (i) stage I coarsely segmented the major coronary arteries from preprocessed single-channel ICAs and generated the probability map of arteries; and (ii) during the stage II, a three-channel image consisting of the original preprocessed image, a generated probability map, and an edge-enhanced image generated from the preprocessed image was fed to the proposed MIMS U-Net to produce the final segmentation result. After segmentation, an arterial stenosis detection algorithm was developed to extract vascular centerlines and calculate arterial diameters to evaluate stenotic level. Results: Experimental results demonstrated that the proposed method achieved an average Dice similarity coefficient of 0.8329, an average sensitivity of 0.8281, and an average specificity of 0.9979 in our dataset with 294 ICAs obtained from 73 patients. Moreover, our stenosis detection algorithm achieved a true positive rate of 0.6668 and a positive predictive value of 0.7043. Conclusions: Our proposed approach has great promise for clinical use and could help physicians improve diagnosis and therapeutic decisions for CAD.

Automatic identification of end-diastolic and end-systolic cardiac frames from invasive coronary angiography videos.

BACKGROUND: Automatic identification of proper image frames at the end-diastolic (ED) and end-systolic (ES) frames during the review of invasive coronary angiograms (ICA) is important to assess blood flow during a cardiac cycle, reconstruct the 3D arterial anatomy from bi-planar views, and generate the complementary fusion map with myocardial images. The current identification method primarily relies on visual interpretation, making it not only time-consuming but also less reproducible. OBJECITVE: In this paper, we propose a new method to automatically identify angiographic image frames associated with the ED and ES cardiac phases. METHOD: A detection algorithm is first used to detect the key points (i.e. landmarks) of coronary arteries, and then an optical flow method is employed to track the trajectories of the selected key points. The ED and ES frames are identified based on all these trajectories. Our method was tested with 62 ICA videos from two separate medical centers. RESULTS: Comparing consensus interpretations by two human expert readers, excellent agreement was achieved by the proposed algorithm: the agreement rates within a one-frame range were 92.99% and 92.73% for the automatic identification of the ED and ES image frames, respectively. CONCLUSION: The proposed automated method showed great potential for being an integral part of automated ICA image analysis.

Three-dimensional Fusion of Myocardial Perfusion SPECT and Invasive Coronary Angiography Guides Coronary Revascularization.

BACKGROUND: SPECT myocardial perfusion imaging (SPECT MPI) and invasive coronary angiography (ICA) provide complementary clinical information in the diagnosis of coronary artery disease (CAD). We have developed an approach for 3D fusion of perfusion data from SPECT MPI and coronary anatomy from ICA. In this study, we aimed to evaluate its clinical value when compared to the traditional side-by-side readings. METHODS: Thirty-six CAD patients who had at least one stenosis ≥ 50% were retrospectively enrolled. Based on the presence of a perfusion defect in a territory subtended by a coronary vessel, all vessels were classified as matched, unmatched, or normal groups via both the fusion and side-by-side analysis. The treatments recommended by the fusion and side-by-side analysis were compared with those that the patients received. Major adverse cardiac events (MACE), defined as all-cause death, myocardial infarction, unstable angina requiring hospitalization, and unplanned revascularization, were assessed. RESULTS: The overall vessel-based concordance was 78.7% between the fusion and side-by-side analysis. Compared with the side-by-side analysis, 23 coronary arteries (29 equivocal segments) of 19 patients were reclassified via fusion of data. In the matched, unmatched, and normal groups, the numbers of vessels with hemodynamically significant stenosis which caused reversible defect were 37 vs 53, 28 vs 14, and 43 vs 41 (P < .01) when comparing the side-by-side analysis with the fusion, and the revascularization ratios per vessel were 69% vs 88%, 29% vs 10%, and 2% vs 2% between them. During the five-year follow-up, 8 patients (22.2%) experienced MACE. Patients who received the same treatment as the guidance of 3D fusion results (n = 22) had superior outcomes when compared with those who did not (n = 14) (P < .01). CONCLUSIONS: Compared with the side-by-side analysis, the 3D fusion of SPECT MPI and ICA provided incremental diagnostic and prognostic value.

3D fusion between fluoroscopy angiograms and SPECT myocardial perfusion images to guide percutaneous coronary intervention.

BACKGROUND: Percutaneous coronary intervention (PCI) in stable coronary artery disease (CAD) is commonly triggered by abnormal myocardial perfusion imaging (MPI). However, due to the possibilities of multivessel disease, serial stenoses and variability of coronary artery perfusion distribution, an opportunity exists to better align anatomic stenosis with perfusion abnormalities to improve revascularization decisions. This study aims to develop a multi-modality fusion approach to assist decision-making for PCI. METHODS AND RESULTS: Coronary arteries from fluoroscopic angiography (FA) were reconstructed into 3D artery anatomy. Left ventricular (LV) epicardial surface was extracted from SPECT. The artery anatomy and epicardial surface were non-rigidly fused. The accuracy of the 3D fusion was evaluated via both computer simulation and real patient data. Simulated FA and MPI were integrated and then compared with the ground truth from a digital phantom. The distance-based mismatch errors between simulated fluoroscopy and phantom arteries were 1.86 ± 1.43 mm for left coronary arteries (LCA) and 2.21 ± 2.50 mm for right coronary arteries (RCA). FA and SPECT images in 30 patients were integrated and then compared with the ground truth from CT angiograms. The distance-based mismatch errors between the fluoroscopy and CT arteries were 3.84 ± 3.15 mm for LCA and 5.55 ± 3.64 mm for RCA. The presence of the corresponding fluoroscopy and CT arteries in the AHA-17-segment model agreed well with a Kappa value of 0.91 (CI 0.89-0.93) for LCA and a Kappa value of 0.80 (CI 0.67-0.92) for RCA. CONCLUSIONS: Our fusion approach is technically accurate to assist PCI decision-making and is clinically feasible to be used in the catheterization laboratory. Future studies are necessary to determine if fusion improves PCI-related outcomes.

Automatic extraction and stenosis evaluation of coronary arteries in invasive coronary angiograms.

BACKGROUND: Coronary artery disease (CAD) is the leading cause of death in the United States (US) and a major contributor to healthcare cost. Accurate segmentation of coronary arteries and detection of stenosis from invasive coronary angiography (ICA) are crucial in clinical decision making. PURPOSE: We aim to develop an automatic method to extract coronary arteries by deep learning and detect arterial stenosis from ICAs. METHODS: In this study, a deep learning model which integrates a feature pyramid with a U-Net++ model was developed to automatically segment coronary arteries in ICAs. A compound loss function which contains Dice loss, dilated Dice loss, and L2 regularization was utilized to train the proposed segmentation model. Following the segmentation, an algorithm which extracts vascular centerlines, calculates the diameters, and measures the stenotic levels, was developed to detect arterial stenosis. RESULTS AND CONCLUSIONS: In the dataset consisting of 314 ICAs obtained from 99 patients, the segmentation model achieved an average Dice score of 0.8899, a sensitivity of 0.8595, and a specificity of 0.9960. In addition, the stenosis detection algorithm achieved a true positive rate of 0.6840 and a positive predictive value of 0.6998 on all types of stenosis, which has great promise to advance to clinical uses and could provide auxiliary suggestions for CAD diagnosis and treatment.

Left-ventricular dyssynchrony in viable myocardium by myocardial perfusion SPECT is predictive of mechanical response to CRT.

OBJECTIVES: Gated myocardial perfusion SPECT (GMPS) provides a one-stop-shop evaluation for cardiac resynchronization therapy (CRT). However, conflicting results have been observed regarding whether the baseline left-ventricular (LV) mechanical dyssynchrony as assessed by phase analysis on GMPS was predictive of therapeutic response to CRT. Since dyssynchrony parameters by phase analysis spuriously increased by scarred myocardium, the purpose of this study was to explore the value of dyssynchrony after stripping off the scar region in correlation to mechanical response to CRT. METHODS: Forty-seven patients following standard indications for CRT received GMPS with phase analysis as pre-CRT evaluation. A decrease of end-systolic volume (ESV) > 15% on follow-up echocardiography after CRT was considered as a mechanical response to CRT. Myocardial regions with less than 50% of maximal activity on GMPS were considered as a scar. The phase standard deviation (PSD) and histogram bandwidth (BW) without or with stripping off scar were assessed by phase analysis of GMPS and were used for evaluation of LV dyssynchrony of all myocardium or only the viable myocardium, respectively. RESULTS: No significant difference was noted between mechanical responders (31 of 47 patients, 66%) and nonresponders ( 16 of 47 patients, 34%) for PSD (48.6° ± 19.4° vs 43.9° ± 20.7°, p = 0.46) and BW (225° ± 91.1° vs 163.5° ± 94.6°, p = 0.38) of the entire myocardium. However, responders had significantly larger PSD (40.5° ± 15.7° vs 30.5° ± 13.2°, p = 0.03) and borderlinely larger BW (215° ± 91.2° vs. 139.5° ± 78.2°, p = 0.05) than non-responders after stripping off scar. Logistic regression analysis showed that scar area and PSD after stripping off scar were independent predictors of mechanical response. CONCLUSIONS: Our result showed that LV dyssynchrony of the entire myocardium did not predict response to CRT. However, LV dyssynchrony only in the viable myocardium was a significant predictor of CRT mechanical response.

Left ventricular systolic and diastolic dyssynchrony to improve cardiac resynchronization therapy response in heart failure patients with dilated cardiomyopathy.

BACKGROUND: The systolic and diastolic dyssynchrony is physiologically related, but measure different left ventricular mechanisms. Left ventricular systolic mechanical dyssynchrony (systolic LVMD) has shown significant clinical values in improving cardiac resynchronization therapy (CRT) response in the heart failure patients with dilated cardiomyopathy (DCM). Our recent study demonstrated that LV diastolic dyssynchrony (diastolic LVMD) parameters have important prognostic values for DCM patients. However, there are a limited number of studies about the clinical value of diastolic LVMD for CRT. This study aims to explore the predictive values of both systolic LVMD and diastolic LVMD for CRT in DCM patients. METHODS: Eighty-four consecutive CRT patients with both DCM and complete left bundle branch block (CLBBB) who received gated resting SPECT MPI at baseline were included in the present study. The phase analysis technique was applied on resting gated short-axis SPECT MPI images to measure systolic LVMD and diastolic LVMD, characterized by phase standard deviation (PSD) and phase histogram bandwidth (PBW). CRT response was defined as ≥ 5% improvement of LVEF at 6-month follow-up. Variables with P < 0.10 in the univariate analysis were included in the multivariate cox analysis. RESULTS: During the follow-up period, 59.5% (50 of 84) patients were CRT responders. The univariate cox regression analysis showed that at baseline QRS duration, non-sustained ventricular tachycardia (NS-VT), systolic PSD, systolic PBW, diastolic PSD, diastolic PBW, scar burden and LV lead in the scarred myocardium were statistically significantly associated with CRT response. The multivariate cox regression analysis showed that QRS duration, NS-VT, systolic PSD, systolic PBW, diastolic PSD, and diastolic PBW were independent predictive factors for CRT response. Furthermore, the rate of CRT response was 94.4% (17 of 18) in patients whose LV lead was in the segments with both the first three late contraction and the first three late relaxation; by contrast, the rate of CRT response was only 6.7% (1 of 15, P < 0.000) in patients whose LV lead was in the segments with neither the first three late contraction nor the first three late relaxation. CONCLUSION: Both systolic LVMD and diastolic LVMD from gated SPECT MPI have important predictive values for CRT response in DCM patients. Pacing at LV segments with both late contraction and late relaxation has potential to increase the CRT response.

A new method to recommend left ventricular lead positions for improved CRT volumetric response and long-term prognosis.

OBJECTIVES: Using ECG-gated single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI), we sought to develop and validate a new method to recommend left ventricular (LV) lead positions in order to improve volumetric response and long-term prognosis after cardiac resynchronization therapy (CRT). METHODS: Seventy-nine patients received gated SPECT MPI at baseline, and echocardiography at baseline and follow-up. The volumetric response referred to a reduction of ≥ 15% in LV end-systolic volume 6 months after CRT. After excluding apical, septal, and scarred segments, there were three levels of recommended segments: (1) the optimal recommendation: the latest contracting viable segment; (2) the 2nd recommendation: the late contracting viable segments whose contraction delays were within 10° of the optimal recommendation; and (3) the 3rd recommendation: the viable segments adjacent to the optimal recommendation when there was no late contracting viable segment. RESULTS: After excluding 11 patients whose LV lead was placed in apical or scarred segments, 75.6% of the patients concordant to recommended LV segments (n = 41) responded to CRT while 51.9% of those with non-recommended LV lead locations (n = 27) were responders (P = .043). Response rates were 76.9%, 76.9% , and 73.3% (P = .967), respectively, when LV lead was implanted in the optimal recommendation (n = 13), the 2nd recommendation (n = 13), and the 3rd recommendation (n = 15). LV leads placed at recommended segments reduced composite events of all-cause mortality or heart failure (HF) rehospitalization compared with pacing at non-recommended segments (log-rank χ2 = 5.623, P = .018). CONCLUSIONS: Pacing in the recommended LV lead segments identified on gated SPECT MPI was associated with improved volumetric response to CRT and long-term prognosis.

Analyze Informant-Based Questionnaire for The Early Diagnosis of Senile Dementia Using Deep Learning.

OBJECTIVE: This paper proposes a multiclass deep learning method for the classification of dementia using an informant-based questionnaire. METHODS: A deep neural network classification model based on Keras framework is proposed in this paper. To evaluate the advantages of our proposed method, we compared the performance of our model with industry-standard machine learning approaches. We enrolled 6,701 individuals, which were randomly divided into training data sets (6030 participants) and test data sets (671 participants). We evaluated each diagnostic model in the test set using accuracy, precision, recall, and F1-Score. RESULTS: Compared with the seven conventional machine learning algorithms, the DNN showed higher stability and achieved the best accuracy with 0.88, which also showed good results for identifying normal (F1-score = 0.88), mild cognitive impairment (MCI) (F1-score = 0.87), very mild dementia (VMD) (F1-score = 0.77) and Severe dementia (F1-score = 0.94). CONCLUSION: The deep neural network (DNN) classification model can effectively help doctors accurately screen patients who have normal cognitive function, mild cognitive impairment (MCI), very mild dementia (VMD), mild dementia (Mild), moderate dementia (Moderate), and severe dementia (Severe).

A learning-based automatic segmentation and quantification method on left ventricle in gated myocardial perfusion SPECT imaging: A feasibility study.

BACKGROUND: The performance of left ventricular (LV) functional assessment using gated myocardial perfusion SPECT (MPS) relies on the accuracy of segmentation. Current methods require manual adjustments that are tedious and subjective. We propose a novel machine-learning-based method to automatically segment LV myocardium and measure its volume in gated MPS imaging without human intervention. METHODS: We used an end-to-end fully convolutional neural network to segment LV myocardium by delineating its endocardial and epicardial surface. A novel compound loss function, which encourages similarity and penalizes discrepancy between prediction and training dataset, is utilized in training stage to achieve excellent performance. We retrospectively investigated 32 normal patients and 24 abnormal patients, whose LV myocardial contours automatically segmented by our method were compared with those delineated by physicians as the ground truth. RESULTS: The results of our method demonstrated very good agreement with the ground truth. The average DSC metrics and Hausdorff distance of the contours delineated by our method are larger than 0.900 and less than 1 cm, respectively, among all 32 + 24 patients of all phases. The correlation coefficient of the LV myocardium volume between ground truth and our results is 0.910 ± 0.061 (P < 0.001), and the mean relative error of LV myocardium volume is - 1.09 ± 3.66%. CONCLUSION: These results strongly indicate the feasibility of our method in accurately quantifying LV myocardium volume change over the cardiac cycle. The learning-based segmentation method in gated MPS imaging has great promise for clinical use.

Prognostic value of left-ventricular systolic and diastolic dyssynchrony measured from gated SPECT MPI in patients with dilated cardiomyopathy.

BACKGROUND: Left-ventricular systolic dyssynchrony (LVSD) has been an important prognostic factor in the patients with dilated cardiomyopathy (DCM). However, the association between the LV diastolic dyssynchrony (LVDD) and clinical outcome is not well established. This study aims to evaluate the prognostic values of both systolic and diastolic dyssynchrony in patients with DCM. METHODS: Fifty-two patients with DCM were enrolled and divided into two groups according to cardiac deaths from the follow-up data. The phase-analysis technique was applied on resting gated short-axis SPECT MPI images to measure LV systolic and diastolic dyssynchrony, including phase standard deviation (PSD), phase histogram bandwidth (PBW), and phase entropy (PE). Variables with P < 0.10 in the univariate analysis were included in the multivariate cox analysis. RESULTS: During the follow-up period (2.9 ± 1.7 years), 18 (34.6%) cardiac deaths were observed. Compared with survivors, patients with cardiac death had lower LVEF (P = 0.011), and more severe LV systolic and diastolic dyssynchrony. The univariate cox regression analysis showed that hypertension, NT-proBNP, LVEF, systolic PSD, systolic PE, and diastolic PBW were statistically significantly associated with cardiac death. The multivariate cox regression analysis showed that systolic PE and diastolic PE were independent predictive factors for cardiac death. Furthermore, the receiver operating characteristic (ROC) analysis, when applied into the combination of systolic PE and diastolic PE for predicting cardiac death, had an area under curve (AUC) of 0.766, a sensitivity of 0.765, and a specificity of 0.722. CONCLUSIONS: Both the LVSD and LVDD parameters from SPECT MPI have important prognostic values for DCM patients. Both systolic PE and diastolic PE are independent prognostic factors for cardiac death.

Mechanical contraction to guide CRT left-ventricular lead placement instead of electrical activation in myocardial infarction with left ventricular dysfunction: An experimental study based on non-invasive gated myocardial perfusion imaging and invasive electroanatomic mapping.

BACKGROUND: Whether the region of the latest electrical activation (LEA) corresponds with the segment of the latest mechanical contraction (LMC) in ischemic cardiomyopathy (ICM) is uncertain. We aimed to investigate the relationship between the left-ventricular (LV) viable segments with LEA and with LMC after myocardial infarction (MI) and analyze the acute hemodynamic responses (dP/dtmax) after cardiac resynchronization therapy (CRT) pacing at different LV sites. METHODS AND RESULTS: Bama suckling pigs (n = 6) were subjected to create MI models. Both gated myocardial perfusion imaging (GMPI) and electroanatomic mapping (EAM) were performed successfully before MI and 4 weeks after MI. LMC was assessed by phase analysis of GMPI, while LEA was evaluated by EAM. The dP/dtmax was measured before CRT and when the CRT LV electrode was implanted in viable segments of LMC, viable segments of lateral wall and scar, respectively. The viable segments of LEA were consistent with the sites of LMC for five in six cases. The dP/dtmax increased significantly compared with that before CRT when the CRT LV electrode was implanted in viable segments of LMC (1103.33 ± 195.76 vs 717.83 ± 80.74 mmHg·s-1, P = .001), which was also significantly higher than in viable segments of lateral wall (751.17 ± 105.62 mmHg·s-1, P = .000) and scar (679.50 ± 60.87 mmHg·s-1, P = .001). CONCLUSIONS: Non-invasive GMPI may be a better option than invasive EAM for guiding LV electrode implantation for CRT in ICM.

Machine Learning for the Preliminary Diagnosis of Dementia.

Objective: The reliable diagnosis remains a challenging issue in the early stages of dementia. We aimed to develop and validate a new method based on machine learning to help the preliminary diagnosis of normal, mild cognitive impairment (MCI), very mild dementia (VMD), and dementia using an informant-based questionnaire. Methods: We enrolled 5,272 individuals who filled out a 37-item questionnaire. In order to select the most important features, three different techniques of feature selection were tested. Then, the top features combined with six classification algorithms were used to develop the diagnostic models. Results: Information Gain was the most effective among the three feature selection methods. The Naive Bayes algorithm performed the best (accuracy = 0.81, precision = 0.82, recall = 0.81, and F-measure = 0.81) among the six classification models. Conclusion: The diagnostic model proposed in this paper provides a powerful tool for clinicians to diagnose the early stages of dementia.

NMD-12: A new machine-learning derived screening instrument to detect mild cognitive impairment and dementia.

INTRODUCTION: Using machine learning techniques, we developed a brief questionnaire to aid neurologists and neuropsychologists in the screening of mild cognitive impairment (MCI) and dementia. METHODS: With the reduction of the survey size as a goal of this research, feature selection based on information gain was performed to rank the contribution of the 45 items corresponding to patient responses to the specified questions. The most important items were used to build the optimal screening model based on the accuracy, practicality, and interpretability. The diagnostic accuracy for discriminating normal cognition (NC), MCI, very mild dementia (VMD) and dementia was validated in the test group. RESULTS: The screening model (NMD-12) was constructed with the 12 items that were ranked the highest in feature selection. The receiver-operator characteristic (ROC) analysis showed that the area under the curve (AUC) in the test group was 0.94 for discriminating NC vs. MCI, 0.88 for MCI vs. VMD, 0.97 for MCI vs. dementia, and 0.96 for VMD vs. dementia, respectively. DISCUSSION: The NMD-12 model has been developed and validated in this study. It provides healthcare professionals with a simple and practical screening tool which accurately differentiates NC, MCI, VMD, and dementia.