Staging of Liver Fibrosis Based on Energy Valley Optimization Multiple Stacking (EVO-MS) Model.

Currently, staging the degree of liver fibrosis predominantly relies on liver biopsy, a method fraught with potential risks, such as bleeding and infection. With the rapid development of medical imaging devices, quantification of liver fibrosis through image processing technology has become feasible. Stacking technology is one of the effective ensemble techniques for potential usage, but precise tuning to find the optimal configuration manually is challenging. Therefore, this paper proposes a novel EVO-MS model-a multiple stacking ensemble learning model optimized by the energy valley optimization (EVO) algorithm to select most informatic features for fibrosis quantification. Liver contours are profiled from 415 biopsied proven CT cases, from which 10 shape features are calculated and inputted into a Support Vector Machine (SVM) classifier to generate the accurate predictions, then the EVO algorithm is applied to find the optimal parameter combination to fuse six base models: K-Nearest Neighbors (KNNs), Decision Tree (DT), Naive Bayes (NB), Extreme Gradient Boosting (XGB), Gradient Boosting Decision Tree (GBDT), and Random Forest (RF), to create a well-performing ensemble model. Experimental results indicate that selecting 3-5 feature parameters yields satisfactory results in classification, with features such as the contour roundness non-uniformity (Rmax), maximum peak height of contour (Rp), and maximum valley depth of contour (Rm) significantly influencing classification accuracy. The improved EVO algorithm, combined with a multiple stacking model, achieves an accuracy of 0.864, a precision of 0.813, a sensitivity of 0.912, a specificity of 0.824, and an F1-score of 0.860, which demonstrates the effectiveness of our EVO-MS model in staging the degree of liver fibrosis.

Design, Synthesis, and Biological Evaluation of Pyrido [1,2-α] Pyrimidinone Mesoionic Derivatives Bearing Propenylbenzene as the Vector Control Insecticide.

A series of novel pyrido [1,2-α] pyrimidinone mesoionic derivatives bearing a propenylbenzene group at the 1-position were synthesized on the basis of the structure of mesoionic insecticides triflumezopyrim and dicloromezotiaz via a rationally conceived pharmacophore model and evaluated for their insecticidal activities against three insect vectors. The bioassay results showed that some compounds exerted remarkable insecticidal activities against M. domestica, Ae. albopictus, and B. germanica. Particularly, compound 26l displayed outstanding insecticidal activity against Ae. Albopictus, with an LC50 value of 0.45 µg/mL, far superior to that of imidacloprid (LC50 = 1.82 µg/mL) and equivalent to that of triflumezopyrim (0.35 µg/mL). Meanwhile, compound 34l presented a broad insecticidal spectrum, with LC50 values of 1.51 µg/g sugar, 0.52 µg/mL and 0.14 µg/adult, which were about 2.88, 3.50, and 1.50 times better than that of imidacloprid (LC50 = 4.35 µg/g sugar, 1.82 µg/mL and 0.21 µg/adult against M. domestica, Ae. albopictus, and B. germanica, respectively) and equivalent to that of triflumezopyrim against M. domestica (1.13 µg/g sugar) and Ae. albopictus (0.35 µg/mL) but lower than the potency against B. germanica (0.06 µg/g sugar). The molecular docking study by energy minimizations revealed that introducing propenylbenzene at the 1-position of compounds 26l and 34l could embed into the binding pocket of nicotinic acetylcholine receptors and form pi-alkyl interaction with LEU306. These results demonstrated that compounds 26l and 34l could be promising candidates for vector control insecticides, which deserved further investigation.

Triangular pulley traction facilitates endoscopic full-thickness resection of exogenous gastric tumor in the fornix of the stomach.

A 65-year-old woman was diagnosed with an exogenous submucosal tumor located in the fornix of the stomach, on the basis of the endoscopic ultrasound and enhanced CT findings. She refused surgery and referred for EFTR. It is difficult to perform EFTR at the gastric fornix and suture the large surgical defect. Therefore, we created technique of triangular pulley traction combined with pre-closure.

Entire traction using clip-and-nylon ring to facilitate endoscopic submucosal dissection of a laterally spreading tumor with fibrosis in the rectum.

A 78-year-old woman with hematochezia underwent a colonoscopy and found a 2 × 2-cm laterally spreading tumor (LST) in the rectum, 3 cm from the anus. Because of the risk related to anus preservation and the potential operative trauma, the patient refused surgery and was referred for ESD treatment. Here, we applied a novel entire traction method to deal with this subset of tumors.

Tooth recognition of 32 tooth types by branched single shot multibox detector and integration processing in panoramic radiographs.

Purpose: The purpose of our study was to analyze dental panoramic radiographs and contribute to dentists' diagnosis by automatically extracting the information necessary for reading them. As the initial step, we detected teeth and classified their tooth types in this study. Approach: We propose single-shot multibox detector (SSD) networks with a side branch for 1-class detection without distinguishing the tooth type and for 16-class detection (i.e., the central incisor, lateral incisor, canine, first premolar, second premolar, first molar, second molar, and third molar, distinguished by the upper and lower jaws). In addition, post-processing was conducted to integrate the results of the two networks and categorize them into 32 classes, differentiating between the left and right teeth. The proposed method was applied to 950 dental panoramic radiographs obtained at multiple facilities, including a university hospital and dental clinics. Results: The recognition performance of the SSD with a side branch was better than that of the original SSD. In addition, the detection rate was improved by the integration process. As a result, the detection rate was 99.03%, the number of false detections was 0.29 per image, and the classification rate was 96.79% for 32 tooth types. Conclusions: We propose a method for tooth recognition using object detection and post-processing. The results show the effectiveness of network branching on the recognition performance and the usefulness of post-processing for neural network output.

Endoscopic retrograde appendicitis therapy for management of acute appendicitis.

BACKGROUND: This study investigated the feasibility of endoscopic retrograde appendicitis therapy (ERAT) for the treatment of acute appendicitis. METHODS: There were 210 patients included who were admitted to our hospital from January 2017 to October 2019 with a diagnosis of acute appendicitis. According to the method of treatment, patients were stratified into the ERAT group, laparoscopic appendectomy (LA) group, or open appendectomy (OA) group for comparison of perioperative information extracted from the medical records of the patients. RESULTS: The operations were successfully completed in all patients. The length of operation in the ERAT group (median: 48 min, range: 34-78 min) was significantly shorter compared to the LA group (median: 67 min, range: 47-90 min) or OA group (median: 85 min, range: 58-120 min). Postoperatively, the length of the hospital stay, the amount of time spent bedridden following surgery, surgery-related complications, and in-patient expenses were all significantly less than those in both the LA and OA groups (all p < 0.05). Moreover, the recurrence rate of appendicitis after ERAT was 2.86% during the first six months of postoperative follow-up. Thirteen patients in the ERAT group were diagnosed with appendicular abscesses, all of which successfully proceeded by colonoscopically incising the most protruding or fluctuating place around the appendix opening without procedure-related complications during the follow-up period. CONCLUSION: ERAT is a safe and effective endoscopic treatment method for acute appendicitis and abscesses of the appendix. The advantages include reduced trauma, faster recovery times, and lower costs in comparison with either OA or LA procedures. ERAT with internal incision and drainage can be safely performed with immediate effect, especially in patients with acute uncomplicated appendicitis accompanied by either fecal stones or stenosis of the appendix cavity, or an abscess within the appendix cavity.

Endoscopic treatment for acute appendicitis with coexistent acute pancreatitis: Two case reports.

BACKGROUND: Appendectomy is the procedure of choice for the treatment of acute appendicitis. However, surgery may not be appropriate for patients with coexisting severe illness or comorbidities such as acute pancreatitis (AP). Endoscopic retrograde appendicitis treatment (ERAT) may be a novel alternative to surgery for treating such patients where existing medical therapies have failed. CASE SUMMARY: We report 2 cases of moderately severe AP who developed acute uncomplicated appendicitis during their hospital stay and did not respond to traditional medical therapy. One patient had moderately severe AP due to hyperlipidemia, while the other patient had a gallstone induced by moderately severe AP. Neither patient was fit to undergo an appendectomy procedure because of the concurrent AP. Therefore, the alternative and minimally invasive ERAT was considered. After written informed consent was collected from the patients, the ERAT procedure was performed. Both patients exhibited fast postoperative recovery after ERAT with minimal surgical trauma. CONCLUSION: ERAT is a safe and effective minimally invasive endoscopic procedure for acute appendicitis in patients with coexistent AP.

Tooth detection and classification on panoramic radiographs for automatic dental chart filing: improved classification by multi-sized input data.

OBJECTIVES: Dental state plays an important role in forensic radiology in case of large scale disasters. However, dental information stored in dental clinics are not standardized or electronically filed in general. The purpose of this study is to develop a computerized system to detect and classify teeth in dental panoramic radiographs for automatic structured filing of the dental charts. It can also be used as a preprocessing step for computerized image analysis of dental diseases. METHODS: One hundred dental panoramic radiographs were employed for training and testing an object detection network using fourfold cross-validation method. The detected bounding boxes were then classified into four tooth types, including incisors, canines, premolars, and molars, and three tooth conditions, including nonmetal restored, partially restored, and completely restored, using classification network. Based on the visualization result, multisized image data were used for the double input layers of a convolutional neural network. The result was evaluated by the detection sensitivity, the number of false-positive detection, and classification accuracies. RESULTS: The tooth detection sensitivity was 96.4% with 0.5 false positives per case. The classification accuracies for tooth types and tooth conditions were 93.2% and 98.0%. Using the double input layer network, 6 point increase in classification accuracy was achieved for the tooth types. CONCLUSIONS: The proposed method can be useful in automatic filing of dental charts for forensic identification and preprocessing of dental disease prescreening purposes.

[Semantic Segmentation of Eight Regions of Upper and Lower Limb Bones Using 3D U-Net in Whole-body CT Images].

PURPOSE: Automated analysis of skeletal muscle in whole-body computed tomography (CT) images uses bone information, but bone segmentation including the epiphysis is not achieved. The purpose of this research was the semantic segmentation of eight regions of upper and lower limb bones including the epiphysis in whole-body CT images. Our targets were left and right upper arms, forearms, thighs, and lower legs. METHOD: We connected two 3D U-Nets in cascade for segmentation of eight upper and lower limb bones in whole-body CT images. The first 3D U-Net was used for skeleton segmentation in whole-body CT images, and the second 3D U-Net was used for eight upper and lower limb bones' segmentation in skeleton segmentation results. Thirty cases of whole-body CT images were used in the experiment, and the segmentation results were evaluated using Dice coefficient with 3-fold cross-validation. RESULT: The mean Dice coefficient was 93% in the left and right upper arms, 89% in the left and right forearms, 95% in the left and right thighs, and 94% in the left and right lower legs. CONCLUSION: Although the accuracy of the segmentation results of relatively small bones remains a challenge, the semantic segmentation of eight regions of upper and lower limb bones including the epiphysis in whole-body CT images has been achieved.