Automated detection and classification of acute vertebral body fractures using a convolutional neural network on computed tomography

BackgroundAcute vertebral fracture is usually caused by low-energy injury with osteoporosis and high-energy trauma. The AOSpine thoracolumbar spine injury classification system (AO classification) plays an important role in the diagnosis and treatment of the disease. The diagnosis and description of vertebral fractures according to the classification scheme requires a great deal of time and energy for radiologists.PurposeTo design and validate a multistage deep learning system (multistage AO system) for the automatic detection, localization and classification of acute thoracolumbar vertebral body fractures according to AO classification on computed tomography.Materials and MethodsThe CT images of 1,217 patients who came to our hospital from January 2015 to December 2019 were collected retrospectively. The fractures were marked and classified by 2 junior radiology residents according to the type A standard in the AO classification. Marked fracture sites included the upper endplate, lower endplate and posterior wall. When there were inconsistent opinions on classification labels, the final result was determined by a director radiologist. We integrated different networks into different stages of the overall framework. U-net and a graph convolutional neural network (U-GCN) are used to realize the location and classification of the thoracolumbar spine. Next, a classification network is used to detect whether the thoracolumbar spine has a fracture. In the third stage, we detect fractures in different parts of the thoracolumbar spine by using a multibranch output network and finally obtain the AO types.ResultsThe mean age of the patients was 61.87 years with a standard deviation of 17.04 years, consisting of 760 female patients and 457 male patients. On vertebrae level, sensitivity for fracture detection was 95.23% in test dataset, with an accuracy of 97.93% and a specificity of 98.35%. For the classification of vertebral body fractures, the balanced accuracy was 79.56%, with an AUC of 0.904 for type A1, 0.945 for type A2, 0.878 for type A3 and 0.942 for type A4.ConclusionThe multistage AO system can automatically detect and classify acute vertebral body fractures in the thoracolumbar spine on CT images according to AO classification with high accuracy

Clinical Efficacy of Including Capecitabine in Neoadjuvant Chemotherapy for Breast Cancer: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

<div><h3>Background</h3><p>Capecitabine has proven effective as a chemotherapy for metastatic breast cancer. Though several Phase II/III studies of capecitabine as neoadjuvant chemotherapy have been conducted, the results still remain inconsistent. Therefore, we performed a meta-analysis to obtain more precise understanding of the role of capecitabine in neoadjuvant chemotherapy for breast cancer patients.</p> <h3>Methods</h3><p>The electronic database PubMed and online abstracts from ASCO and SABCS were searched to identify randomized clinical trials comparing neoadjuvant chemotherapy with or without capecitabine in early/operable breast cancer patients without distant metastasis. Risk ratios were used to estimate the association between capecitabine in neoadjuvant chemotherapy and various efficacy outcomes. Fixed- or random-effect models were adopted to pool data in RevMan 5.1.</p> <h3>Results</h3><p>Five studies were included in the meta-analysis. Neoadjuvant use of capecitabine with anthracycline and/or taxane based therapy was not associated with significant improvement in clinical outcomes including: pathologic complete response in breast (pCR; RR = 1.10, 95% CI 0.87–1.40, p = 0.43), pCR in breast tumor and nodes (tnpCR RR = 0.99, 95% CI 0.83–1.18, p = 0.90), overall response rate (ORR; RR = 1.00, 95% CI 0.94–1.07, p = 0.93), or breast-conserving surgery (BCS; RR = 0.98, 95% CI 0.93–1.04, p = 0.49).</p> <h3>Conclusions</h3><p>Neoadjuvant treatment of breast cancer involving capecitabine did not significantly improve pCR, tnpCR, BCS or ORR. Thus adding capecitabine to neoadjuvant chemotherapy regimes is unlikely to improve outcomes in breast cancer patients without distant metastasis. Further research is required to establish the condition that capecitabine may be useful in breast cancer neoadjuvant chemotherapy.</p> </div

Study of Sensor Layout Acquisition and Application Analysis within Distribution Room

The traditional power distribution room lacks intelligent monitoring business functions, which is not conducive to the requirements of intelligent operation and maintenance. This article takes the intelligent IoT terminal(Internet of Things terminal) as the center, carries out the layout design of the distribution room sensor, combines the intelligent collection of the distribution room, and accesses the sensing equipment to build a smart distribution room, meanwhile, this paper designs the intelligent terminal which adopts the edge computing technology to carry out the environment temperature and humidity assessment, equipment partial discharge analysis and assessment, temperature rise assessment and other micro-applications to provide support for the construction of smart distribution room

The oncological safety and long-term cosmetic effect of free dermal fat graft with epidermis removal for breast defect repair in breast conserving surgery

Background: Free dermal fat grafts (FDFG) are used for immediate breast defect repair in breast-conserving surgery (BCS), and have achieved satisfactory immediate postoperative cosmetic effects (Sawai et al., 2004) [1]. However, the oncologic safety and long-term cosmetic outcomes of these surgical procedures remain unknown. Therefore, t，in this study, we aim to investigate the oncological safety and long-term cosmetic outcomes of FDFG in patients with breast cancer. Methods: This matched retrospective case-control study included patients with non-special types of breast cancer who underwent FDFG for breast defect repair after BCS or BCS alone at two breast cancer research centers in Guangxi Province, China, from January 2016 to December 2019. The patients were divided into either the FDFG or BCS group. Control cases were screened using propensity score matching, and survival analysis and cosmetic evaluations were performed. Results: A total of 442 patients with breast cancer were included in the study. After 1:4 propensity score matching, 53 and 212 patients were included in the FDFG and BCS groups, respectively. The median follow-up time was 49.9 (9.0–76.0) months. The rate of local recurrence in the FDFG group (9.4 %) was significantly higher than that in the BCS group (1.9 %; p < 0.05). The total cosmetic evaluation score was significantly higher in the BCS group 18 months after surgery than in the FDFG group (p < 0.05). Conclusions: In this retrospective study, FDFG was significantly associated with an increased risk of local recurrence. Further prospective studies are required to confirm these results. No significant difference in long-term cosmetic effects were observed for FDFG than for BCS alone for immediate breast defect repair

Flow chart of study selection.

<p>Flow chart of study selection.</p

Forest plot to meta-analyze pCR outcomes for neoadjuvant therapy with or without capecitabine.

<p>Forest plot to meta-analyze pCR outcomes for neoadjuvant therapy with or without capecitabine.</p

Forest plot to meta-analyze tnpCR outcomes for neoadjuvant therapy with or without capecitabine.

<p>Forest plot to meta-analyze tnpCR outcomes for neoadjuvant therapy with or without capecitabine.</p

Data from: Social call divergence in bats: a comparative analysis

Acoustic signals mediate important life history events in a variety of species, providing new vistas for understanding speciation. It has been proposed that animal acoustic signals undergo complex interactions among morphology, ecology, social pressure, and phylogenetic history. Yet, the relative importance of these factors in shaping acoustic divergence is rarely assessed within a comparative framework. Herein, we aim to investigate the key determinants of social call divergence across 31 bat species from 5 families. We compiled a wide data set on bat aggressive calls, body size, foraging habitats, foraging modes, climatic conditions, colony size, and phylogenetic components. We identified remarkable interspecific divergence versus within-species variation in aggressive vocalizations. Despite weak effects of ecological factors, colony size, body size, and phylogenetic components accounted for the majority of variation in call parameters among species. The colony size and body size played a major role in influencing spectral parameters, whereas phylogenetic relationships determined call duration and minimum frequency. Together, our findings constitute convincing evidence that sociality, morphological constraint, and phylogenetic constraint mold social call divergence in bats. This study expands our limited knowledge of the evolution of bat social calls, and highlights the importance of sociality in driving acoustic phenotype diversity

The Impact of Land Use and Landscape Pattern on Ecosystem Services in the Dongting Lake Region, China

Ecosystem services (ES) are directly affected by land use and land cover changes (LUCC); however, the impacts of extended period LUCC on ES are poorly explored. Here, we mapped the 1998–2019 annual land use and land cover in the Dongting Lake Region (China) and explored the spatiotemporal evolution of LUCC and landscape patterns (i.e., composition, shape, and aggregation) and their relationship with ES, including carbon storage, gross primary production (GPP), water conservation capacity, and crop yield in the region. The results showed a significant increase in forest areas and impervious surfaces and a decrease in croplands and bare lands with spatial heterogeneity. Carbon storage was strongly correlated with forest, cropland, waterbody, impervious surface, and bare land, and there was a nonlinear relationship between landscape patterns and ES. The trade-offs and synergies (correlations) among ES varied considerably, with crop yield being significantly synergistic with carbon stocks, GPP, or GPP with carbon stocks. This study revealed the nonlinear relationship between landscape patterns and ES, and the mechanism of landscape characteristics on ES. The findings can provide scientific support for regional land use planning, ES regulation, and landscape optimization in the lake region