Vehicle-Type Recognition Method for Images Based on Improved Faster R-CNN Model

The rapid increase in the number of vehicles has led to increasing traffic congestion, traffic accidents, and motor vehicle crime rates. The management of various parking lots has also become increasingly challenging. Vehicle-type recognition technology can reduce the workload of humans in vehicle management operations. Therefore, the application of image technology for vehicle-type recognition is of great significance for integrated traffic management. In this paper, an improved faster region with convolutional neural network features (Faster R-CNN) model was proposed for vehicle-type recognition. Firstly, the output features of different convolution layers were combined to improve the recognition accuracy. Then, the average precision (AP) of the recognition model was improved through the contextual features of the original image and the object bounding box optimization strategy. Finally, the comparison experiment used the vehicle image dataset of three vehicle types, including cars, sports utility vehicles (SUVs), and vans. The experimental results show that the improved recognition model can effectively identify vehicle types in the images. The AP of the three vehicle types is 83.2%, 79.2%, and 78.4%, respectively, and the mean average precision (mAP) is 1.7% higher than that of the traditional Faster R-CNN model.

The Methodology for Evaluating the Operating State of SF6 HVCBs Based on IDDA

To enhance the precision of evaluating the operational status of SF6 high-voltage circuit breakers (HVCBs) and devise judicious maintenance strategies, this study introduces an operational state assessment method for SF6 HVCBs grounded in the integrated data-driven analysis (IDDA) model. The relative degradation weight (RDW) is introduced as a metric for quantifying the relative significance of distinct indicators concerning the operational condition of SF6 HVCBs. A data-driven model, founded on critical factor stability (CFS), is formulated to convert environmental indicators into quantitative computations. Furthermore, an optimized fuzzy inference (OFI) system is devised to streamline the system architecture and enhance the processing speed of continuous indicators. Ultimately, the efficacy of the proposed model is substantiated through validation, and results from instance analyses underscore that the presented approach not only attains heightened accuracy in assessment compared to extant analytical methodologies but also furnishes a dependable foundation for prioritizing maintenance sequences across diverse components.

Sound Touch Elastography for Noninvasive Assessment of Liver Stiffness in Patients With Chronic Heart Failure

Heart failure (HF) can damage various organs, including the liver, a phenomenon known as "cardiohepatic syndrome." The latter is characterized by liver congestion and hepatic artery hypoperfusion, which can lead to liver damage. In this study, we aimed to assess liver damage quantitatively in chronic HF (CHF) with sound touch elastography (STE). A total of 150 subjects were enrolled, including HF with reduced ejection fraction (HFrEF) groups (left ventricular ejection fraction ≤40%, n = 45), HF with mildly reduced ejection fraction (HFmrEF) groups (left ventricular ejection fraction between 41% and 49%, n = 40), and right-sided HF (RHF) groups (n = 25); normal groups (n = 40). Liver stiffness measurement (LSM) was performed in all subjects by STE. The other hepatic parameters were also measured. The LSM was 5.4 ± 1.1 kPa in normal subjects and increased slightly to 5.9 ± 0.7 kPa in patients with HFmrEF. However, the HFrEF and RHF groups had significantly higher LSMs of 8.4 ± 2.0 kPa and 10.3 ± 2.7 kPa, respectively. The LSM of HFrEF was significantly higher than that of HFmrEF, whereas the increase in LSM in patients with RHF was significant relative to HFmrEF and HFrEF. In addition, the other parameters showed abnormal values in only RHF and HFrEF. In conclusion, STE is a useful clinical technique for the noninvasive evaluation of liver stiffness associated with CHF, which could help patients with CHF manage their treatment regimens.

Risk factors for portal vein system thrombosis after partial splenic embolisation in cirrhotic patients with hypersplenism

AIM

To determine risk factors for portal venous system thrombosis (PVST) after partial splenic artery embolisation (PSAE) in cirrhotic patients with hypersplenism.

MATERIALS AND METHODS

Between March 2014 and February 2022, 428 cirrhotic patients with hypersplenism underwent partial splenic artery embolisation and from these patients 208 were enrolled and 220 were excluded. Medical records of enrolled patients were collected. Computed tomography (CT) images were reviewed by two blinded, independent radiologists. Statistical analyses were performed by using SPSS.

RESULTS

Progressive PVST was observed in 18.75% (39/208) of cirrhotic patients after PSAE. No significant differences in peripheral blood counts, liver function biomarkers, and renal function were observed between the patients with progressive PVST and the patients without progressive PVST. The imaging data showed significant differences in PVST, the diameters of the portal, splenic, and superior mesenteric veins between the progressive PVST group and non-progressive PVST group. Univariate and multivariate analysis demonstrated portal vein thrombosis, spleen infarction percentage, and the diameter of the splenic vein were independent risk factors for progressive PVST. Seventeen of 173 (9.83%) patients showed new PVST; the growth of PVST was observed in 62.86% (22/35) of the patients with pre-existing PVST. Spleen infarction percentage and the diameter of the splenic vein were independent risk factors for new PVST after PSAE.

CONCLUSION

The present study demonstrated portal vein thrombosis, spleen infarction percentage, and the diameter of the splenic vein were independent risk factors for PVST after PSAE in cirrhotic patients with hypersplenism.

An image caption model based on attention mechanism and deep reinforcement learning

Image caption technology aims to convert visual features of images, extracted by computers, into meaningful semantic information. Therefore, the computers can generate text descriptions that resemble human perception, enabling tasks such as image classification, retrieval, and analysis. In recent years, the performance of image caption has been significantly enhanced with the introduction of encoder-decoder architecture in machine translation and the utilization of deep neural networks. However, several challenges still persist in this domain. Therefore, this paper proposes a novel method to address the issue of visual information loss and non-dynamic adjustment of input images during decoding. We introduce a guided decoding network that establishes a connection between the encoding and decoding parts. Through this connection, encoding information can provide guidance to the decoding process, facilitating automatic adjustment of the decoding information. In addition, Dense Convolutional Network (DenseNet) and Multiple Instance Learning (MIL) are adopted in the image encoder, and Nested Long Short-Term Memory (NLSTM) is utilized as the decoder to enhance the extraction and parsing capability of image information during the encoding and decoding process. In order to further improve the performance of our image caption model, this study incorporates an attention mechanism to focus details and constructs a double-layer decoding structure, which facilitates the enhancement of the model in terms of providing more detailed descriptions and enriched semantic information. Furthermore, the Deep Reinforcement Learning (DRL) method is employed to train the model by directly optimizing the identical set of evaluation indexes, which solves the problem of inconsistent training and evaluation standards. Finally, the model is trained and tested on MS COCO and Flickr 30 k datasets, and the results show that the model has improved compared with commonly used models in the evaluation indicators such as BLEU, METEOR and CIDEr.

Intelligent Interactive Deformable Image Registration for Online Adaptive Radiotherapy

PURPOSE/OBJECTIVE(S)

The goal of this study is to streamline the time-consuming contouring process in online adaptive radiotherapy (ART) by utilizing a deep learning-based interactive deformable image registration (DIR) algorithm. The objective is to minimize manual review and editing of automatically generated initial contours of organs-at-risk (OARs) and targets, thereby improving the efficiency and effectiveness of the treatment process.

MATERIALS/METHODS

Our proposed method reforms the current DIR-based contour propagation method in clinical practice through the implementation of a deep learning-based interactive approach. The steps include: 1) generation of an initial deformable vector field (DVF) using a DL model, based on fixed and moving image pairs, resulting in the initial contours of OARs and targets; 2) clinician review/edit one the OAR/target contours as needed; 3) updated contour is sent to DL model to update the DVF and the remaining OARs/targets contours. Repeat this process until satisfactory contour qualities are achieved. We used the Open Access Series of Imaging Studies (OASIS) as the testbed, including 394 (train) and 20 (test) brain T1-weighted MRI scans, each containing 35 annotated organs. The U-Net architecture was employed to update the DVF from fixed/moving images, initial contours, and updated contours. We compared our approach to traditional manual editing without interaction and quantified the effort reduction using the added path length (APL) metric which is supposed to be proportional to the absolute time spent on the contour editing. We conducted paired t-test to show the significance. For comparison purpose, we assumed the clinicians edit the contours with the largest APL, i.e., the contours that require the most editing efforts.

RESULTS

The editing effort, as measured by APL, was reduced by 18.5% to 25.4% with a mean of 23.3%, median of 23.6%, and standard deviation of 1.9%. The significance of the results was confirmed with a p-value of 1.47e-24.

CONCLUSION

Our study demonstrates a significant reduction in editing effort, as measured by APL, compared to traditional manual contour editing. These results demonstrate the potential of our deep learning-based interactive approach to improve the efficiency and accuracy of the contouring process in clinical practice.

Deep Learning-Based Quality Assurance for Auto-Segmentation Masks in Radiotherapy

PURPOSE/OBJECTIVE(S)

Deep learning-based auto-contouring has shown great promise in several disease sites including GU and head and neck. However, quality assurance (QA) is key to identify poor auto-contours which is time consuming. We hypothesis that training a deep learning model to predict contour quality metrics, such as Dice coefficients (DSC) and associated uncertainties for QA.

MATERIALS/METHODS

We trained a 3D U-Net-based DL model for segmenting the target and three clinical-relevant OARs (bladder and rectum). To mimic the slice-by-slice review process in clinical practice, we then trained a 2D ResNet-based DL model to predict the 2D DSC for each 2D slice's contour, generated by the 3D segmentation model. Using the Monte Carlo dropout technique, we made 20 independent predictions per slice, with the final DSC calculated as their average and uncertainty estimated as 95% prediction intervals (PI). The study cohort consisted of 912 prostate cancer patients who received definitive radiotherapy. The 3D auto-segmentation model was trained on 129 patients and validated on 20, before being tested on 763 patients. The 2D DSC prediction model was trained on 293 patients with 11116 slices, validated on 73 patients with 2804 slices, and tested on 366 patients with 14117 slices. Rectum was chosen to test the 2D contour QA model as it is the most challenging OAR. We categorized 2D slices into three groups based on the lower and upper bounds of the prediction intervals. "no/minor edits" (lower bound > = 0.9), "major edits" (lower bound < 0.9 and upper bound > = 0.8), and "not acceptable" (upper bound < 0.8). The model performance was quantified by calculating correlation coefficients between predicted and ground truth DSC and the fraction of cases that were correctly identified in each category.

RESULTS

The results of the study showed that the overall correlation coefficient between predicted, and ground truth DSC was 0.842. The model was able to correctly identify 78.3%, 60.7%, and 53.4% of the "no/minor edits", "major edits", and "not acceptable" cases, respectively.

CONCLUSION

This study provides a valuable tool for clinicians in making quick decisions on the acceptance, rejection, or revision of auto-segmented masks during the radiation therapy planning process by providing quantitative results on predicted DSC and associated uncertainties.

Balancing Quality and Efficiency of Head and Neck Contour Revision for Online Adaptive Radiotherapy

PURPOSE/OBJECTIVE(S)

The number of target and organs-at-risk (OAR) structures requiring contours is a barrier to online adaptive radiotherapy (oART) implementation for head and neck (H&N) cancer. In sharing our experience utilizing a cone beam CT-based oART system featuring automatic contours, we analyzed the system's clinical performance and the dosimetric benefits of human supervision to investigate the optimal balance between contour editing and plan quality.

MATERIALS/METHODS

We analyzed 44 H&N patients and 349 adaptive fractions treated on the oART system. The unsupervised (automatically generated) and supervised (edited by clinicians) target and OAR contours as well as the corresponding adaptive plans were acquired. Dice Similarity Coefficient (DSC) and Hausdorff Distance (HD) used to assess the geometric extent of contour supervision. We mapped the clinically treated adaptive plan to the unsupervised contours to quantify the dosimetric effect of the contour edits, and the adaptive plan optimized from the unsupervised contours to the supervised contours to simulate an unsupervised workflow.

RESULTS

The targets were edited in >80.7% of the sessions, with the most changes seen in the primary GTV (DSC = 0.86 ± 0.09 and HD = 2.77 ± 1.58 mm) and the least in the nodal CTV (DSC = 0.92 ± 0.06, HD = 2.29 ± 1.49 mm). Among OARs, oral cavity was the most frequently edited (49.0%) and brainstem the least (2.2%). In general, OAR edits were minor (mean DSC > 0.95 with std Dosimetric quantification of the edits (Table 1) showed that while the unsupervised targets resulted in significant coverage loss, the change in unsupervised OAR dose was not as pronounced, with 81.5-96.8% still meeting the preplan constraints. Edits corresponding to major dose changes were mostly adjacent to or inside targets. The unsupervised workflow underdosed the targets and overdosed the OARs, and therefore is not recommended.

CONCLUSION

While target contours needed physician supervision in H&N oART, edits to automatic OAR contours were minor. An alternative contour workflow could be adopted to focus on the targets and reduce time spent on the OARs. For OAR close to or overlapping with the targets, strategic cropping could potentially minimize time for editing and improve the robustness of the adapted plan quality.

[Outcome of surgical repair for aortic coarctation with coexisting descending aortic aneurysm in adult patients]

Objective: To evaluate the efficacy of surgical treatment of aortic coarctation combined with descending aortic aneurysm in adult patients. Methods: This is a retrospective cohort study. Adult patients with aortic coarctation who were hospitalized in Beijing Anzhen Hospital from January 2015 to April 2019 were enrolled. The aortic coarctation was diagnosed by aortic CT angiography, and the included patients were divided into the combined descending aortic aneurysm group and the uncomplicated descending aortic aneurysm group based on descending aortic diameter. General clinical data and surgery-related data were collected from the included patients, and death and complications were recorded at 30 days after surgery, and upper limb systolic blood pressure was measured in all patients at discharge. Patients were followed up after discharge by outpatient visit or telephone call for their survival and the occurrence of repeat interventions and adverse events, which included death, cerebrovascular events, transient ischemic attack, myocardial infarction, hypertension, postoperative restenosis, and other cardiovascular-related interventions. Results: A total of 107 patients with aortic coarctation aged (34.1±15.2) years were included, and 68 (63.6%) were males. There were 16 cases in the combined descending aortic aneurysm group and 91 cases in the uncomplicated descending aortic aneurysm group. In the combined descending aortic aneurysm group, 6 cases (6/16) underwent artificial vessel bypass, 4 cases (4/16) underwent thoracic aortic artificial vessel replacement, 4 cases (4/16) underwent aortic arch replacement+elephant trunk procedure, and 2 cases (2/16) underwent thoracic endovascular aneurysm repair. There was no statistically significant difference between the two groups in the choice of surgical approach (all P>0.05). In the combined descending aortic aneurysm group at 30 days after surgery, one case underwent re-thoracotomy surgery, one case developed incomplete paraplegia of the lower extremity, and one case died; and the differences in the incidence of endpoint events at 30 days after surgery were similar between the two groups (P>0.05). Systolic blood pressure in the upper extremity at discharge was significantly lower in both groups compared with the preoperative period (in the combined descending aortic aneurysm group: (127.3±16.3) mmHg vs. (140.9±16.3) mmHg, P=0.030, 1 mmHg=0.133 kPa; in the uncomplicated descending aortic aneurysm group: (120.7±13.2) mmHg vs. (151.8±26.3) mmHg, P=0.001). The follow-up time was 3.5 (3.1, 4.4) years. There were no new deaths in the combined descending aortic aneurysm group, no transient ischemic attack, myocardial infarction or re-thoracotomy surgery, and one patient (1/15) suffered cerebral infarction and 10 patients (10/15) were diagnosed with hypertension. The differences in the occurrence of endpoint events during postoperative follow-up were similar between the two groups (P>0.05). Conclusion: In experienced centers, long-term prognosis of patients with aortic coarctation combined with descending aortic aneurysm is satisfactory post surgical intervention.

A data security scheme based on EEG characteristics for body area networks

Body area network (BAN) is a body-centered network of wireless wearable devices. As the basic technology of telemedicine service, BAN has aroused an immense interest in academia and the industry and provides a new technical method to solve the problems that exist in the field of medicine. However, guaranteeing full proof security of BAN during practical applications has become a technical issue that hinders the further development of BAN technology. In this article, we propose a data encryption method based on electroencephalogram (EEG) characteristic values and linear feedback shift register (LFSR) to solve the problem of data security in BAN. First, the characteristics of human EEG signals were extracted based on the wavelet packet transform method and as the MD5 input data to ensure its randomness. Then, an LFSR stream key generator was adopted. The 128-bit initial key obtained through the message-digest algorithm 5 (MD5) was used to generate the stream key for BAN data encryption. Finally, the effectiveness of the proposed security scheme was verified by various experimental evaluations. The experimental results showed that the correlation coefficient of data before and after encryption was very low, and it was difficult for the attacker to obtain the statistical features of the plaintext. Therefore, the EEG-based security scheme proposed in this article presents the advantages of high randomness and low computational complexity for BAN systems.

[Biomechanical analysis of miniplate fixation systems in restorative laminoplasty for spinal canal reconstruction]

OBJECTIVE

To investigate the biomechanical properties of H-shaped and L-shaped miniplate fixation systems (H-MFS and L-MFS, respectively) in restorative laminoplasty for spinal canal reconstruction (RL-SCR).

METHODS

Laminectomy was performed in a 3D printed L4 vertebral model followed by RL-SCR using H-MFS or L-MFS, and the biomechanical properties of the reconstructed models were evaluated using static and dynamic compression tests. Biomechanical analyses of RL-SCR were also conducted in finite element models of the L3-L5 vertebrae with normal assignment (NA), laminectomy, or fixation with H-MFS or L-MFS, and the range of motion (ROM) of L3-L4 and L4-L5 was evaluated.

RESULTS

In static compression test, the sustained yield load, compression stiffness, yield displacement and axial displacement- axial load were all significantly greater in H-MFS group (P < 0.05). Door closing, lamina collapse and plate breakage occurred in all the models in L-MFS group, and only some models in H-MFS group showed plate cracks and screw loosening. In dynamic compression tests, the peak load in H-MFS group reached 873 N (which was 95% of the average yield load in static compression), significantly greater than that in L-MFS group (P < 0.05). The ultimate load in L-MFS group was only 46.59% of that in H-MFS group (P>0.05). In finite element analysis, the ROM of the L3-L4 and L4- L5 segments were significantly smaller in NA, H-MFS and L-MFS groups than in laminectomy group. Compared with NA group, H-MFS group showed a greater ROM during extension, and L-MFS group showed greater ROM in flexion, extension, bending, and rotation; The overall ROM of the vertebral segments decreased in the order of laminectomy group, L-MFS group, H-MFS group, and NA group.

CONCLUSION

Laminectomy causes structural destruction of the posterior column of the spine to affect its biomechanical stability. RL-SCR can effectively maintain the biomechanical stability of the spine, and H-MFS is superior to L-MFS in maintaining the integrity and biomechanical properties of the reconstructed spinal canal.

Development and verification of radiomics framework for computed tomography image segmentation

BACKGROUND

Radiomics has been considered an imaging marker for capturing quantitative image information (QII). The introduction of radiomics to image segmentation is desirable but challenging.

PURPOSE

This study aims to develop and validate a radiomics-based framework for image segmentation (RFIS).

METHODS

RFIS is designed using features extracted from volume (svfeatures) created by sliding window (swvolume). The 53 svfeatures are extracted from 11 phantom series. Outliers in the svfeature datasets are detected by isolation forest (iForest) and specified as the mean value. The percentage coefficient of variation (%COV) is calculated to evaluate the reproducibility of svfeatures. RFIS is constructed and applied to the gross target volume (GTV) segmentation from the peritumoral region (GTV with a 10 mm margin) to assess its feasibility. The 127 lung cancer images are enrolled. The test-retest method, correlation matrix, and Mann-Whitney U test (p < 0.05) are used to select non-redundant svfeatures of statistical significance from the reproducible svfeatures. The synthetic minority over-sampling technique is utilized to balance the minority group in the training sets. The support vector machine is employed for RFIS construction, which is tuned in the training set using 10-fold stratified cross-validation and then evaluated in the test sets. The swvolumes with the consistent classification results are grouped and merged. Mode filtering is performed to remove very small subvolumes and create relatively large regions of completely uniform character. In addition, RFIS performance is evaluated by the area under the receiver operating characteristic (ROC) curve (AUC), accuracy, sensitivity, specificity, and Dice similarity coefficient (DSC).

RESULTS

30249 phantom and 145008 patient image swvolumes were analyzed. Forty-nine (92.45% of 53) svfeatures represented excellent reproducibility(%COV<15). Forty-five features (91.84% of 49) included five categories that passed test-retest analysis. Thirteen svfeatures (28.89% of 45) svfeatures were selected for RFIS construction. RFIS showed an average (95% confidence interval) sensitivity of 0.848 (95% CI:0.844-0.883), a specificity of 0.821 (95% CI: 0.818-0.825), an accuracy of 83.48% (95% CI: 83.27%-83.70%), and an AUC of 0.906 (95% CI: 0.904-0.908) with cross-validation. The sensitivity, specificity, accuracy, and AUC were equal to 0.762 (95% CI: 0.754-0.770), 0.840 (95% CI: 0.837-0.844), 82.29% (95% CI: 81.90%-82.60%), and 0.877 (95% CI: 0.873-0.881) in the test set, respectively. GTV was segmented by grouping and merging swvolume with identical classification results. The mean DSC after mode filtering was 0.707 ± 0.093 in the training sets and 0.688 ± 0.072 in the test sets.

CONCLUSION

Reproducible svfeatures can capture the differences in QII among swvolumes. RFIS can be applied to swvolume classification, which achieves image segmentation by grouping and merging the swvolume with similar QII.

Multi-modal feature-fusion for CT metal artifact reduction using edge-enhanced generative adversarial networks

Computed Tomography (CT) imaging is one of the most widely-used and cost-effective technology for organ screening and diseases diagnosis. Because of existence of metallic implants in some patients, the CT images acquired from these patients are often corrupted by undesirable metal artifacts, which causes severe problem of metal artifact. Although there have been proposed many methods to reduce metal artifact, reduction is still challenging and inadequate, and results are suffering from symptom variance, second artifact and poor subjective evaluation. To address these problems, we propose a novel metal artifact reduction method based on generative adversarial networks to simultaneously reduce metal artifacts and enhance texture structure of corrected CT images. Specifically, we firstly incorporate interactive information (text) and imaging CT (image) into a comprehensive feature to yield multi-modal feature-fusion representation, which overcomes the representative ability limitation of single-modal data. The incorporation of interaction information constrains the feature generation to ensure symptom consistency between corrected and target CT. Then, we design an edge-enhance sub-network to avoid second artifact and suppress noise. Besides, we invite three professional physicians to evaluate corrected CT image subjectively. In this paper, We achieved average increment of 11.3% PSNR and 12.1% SSIM on DeepLesion dataset. The subjective evaluations by physicians show that ours outperforms over 6.3%, 7.1%, 5.50% and 6.9% in term of sharpness, resolution, invariance and acceptability, respectively. Our proposed method can achieve high-quality metal artifact reduction results.

An Artificial Intelligence Model Based on ACR TI-RADS Characteristics for US Diagnosis of Thyroid Nodules

Background US-based diagnosis of thyroid nodules is subjective and influenced by radiologists' experience levels. Purpose To develop an artificial intelligence model based on American College of Radiology Thyroid Imaging Reporting and Data System characteristics for diagnosing thyroid nodules and identifying nodule characteristics (hereafter, M_TI-RADS) and to compare the performance of M_TI-RADS, radiologists, and a model trained on benign and malignant status based on surgical histopathologic analysis (hereafter, M_Diag). Materials and Methods In this retrospective study, 1588 surgically proven nodules from 636 consecutive patients (mean age, 49 years ± 14 [SD]; 485 women) were included. M_TI-RADS and M_Diag were trained on US images of 1345 nodules (January 2018 to December 2019). The performance of M_TI-RADS was compared with that of M_Diag and radiologists with different experience levels on the test data set (243 nodules, January 2019 to December 2019) with the DeLong method and McNemar test. Results The area under the receiver operating characteristic curve (AUC) and sensitivity of M_TI-RADS were 0.91 and 83% (55 of 66 nodules), respectively, which were not significantly different from those of experienced radiologists (0.93 [P = .45] and 92% [61 of 66 nodules; P = .07]) and exceeded those of junior radiologists (0.78 [P < .001] and 70% [46 of 66 nodules; P = .04]). The specificity of M_TI-RADS (87% [154 of 177 nodules]) was higher than that of both experienced and junior radiologists (80% [141 of 177 nodules; P = .02] and 75% [133 of 177 nodules; P = .001], respectively). The AUC of M_TI-RADS was higher than that of M_Diag (0.91 vs 0.84, respectively; P = .001). In the test set of 243 nodules, the consistency rates between M_TI-RADS and the experienced group were higher than those between M_TI-RADS and the junior group for composition (79% [n = 193] vs 73% [n = 178], respectively; P = .02), echogenicity (75% [n = 183] vs 68% [n = 166]; P = .04), shape (93% [n = 227] vs 88% [n = 215]; P = .04), and smooth or ill-defined margin (72% [n = 174] vs 63% [n = 152]; P = .002). Conclusion The area under the receiver operating characteristic curve (AUC) of an artificial intelligence model based on the American College of Radiology Thyroid Imaging Reporting and Data System (TI-RADS) was higher than that of a model trained on benign and malignant status based on surgical histopathologic analysis. The AUC and sensitivity of the model based on TI-RADS exceeded those of junior radiologists; the specificity of the model was higher than that of both experienced and junior radiologists. © RSNA, 2022.

Dosimetric predictors and Lyman normal tissue complication probability model of hematological toxicity in cervical cancer patients with treated with pelvic irradiation

PURPOSE

To identify dosimetric parameters associated with acute hematological toxicity (HT) and identify the corresponding normal tissue complication probability (NTCP) model in cervical cancer patients receiving helical tomotherapy (Tomo) or fixed-field intensity-modulated radiation therapy (ff-IMRT) in combination with chemotherapy, that is, concurrent chemoradiotherapy (CCRT) using the Lyman-Kutcher-Burman normal tissue complication probability (LKB-NTCP) model.

METHODS

Data were collected from 232 cervical cancer patients who received Tomo or ff-IMRT from 2015 to 2018. The pelvic bone marrow (PBM) (including the ilium, pubes, ischia, acetabula, proximal femora, and lumbosacral spine) was contoured from the superior boundary (usually the lumbar 5 vertebra) of the planning target volume (PTV) to the proximal end of the femoral head (the lower edge of the ischial tubercle). The parameters of the LKB model predicting ≥grade 2 hematological toxicity (Radiation Therapy Oncology Group [RTOG] grading criteria) (TD50 (1), m, and n) were determined using maximum likelihood analyses. Univariate and multivariate logistic regression analyses were used to identify correlations between dose-volume parameters and the clinical factors of HT.

RESULTS

In total, 212 (91.37%) patients experienced ≥grade 2 hematological toxicity. The fitted normal tissue complication probability model parameters were TD50 (1) = 38.90 Gy (95%CI, [36.94, 40.96]), m = 0.13 (95%CI [0.12, 0.16]), and n = 0.04 (95%CI [0.02, 0.05]). Per the univariate analysis, the NTCP (the use of LKB-NTCP with the set of model parameters found, p = 0.023), maximal PBM dose (p = 0.01), mean PBM dose (p = 0.021), radiation dose (p = 0.001), and V16-53 (p < 0. 05) were associated with ≥grade 2 HT. The NTCP (the use of LKB-NTCP with the set of model parameters found, p = 0.023; AUC = 0.87), V16, V17, and V18 ≥ 79.65%, 75.68%, and 72.65%, respectively (p < 0.01, AUC = 0.66∼0.68), V35 and V36 ≥ 30.35% and 28.56%, respectively (p < 0.05; AUC = 0.71), and V47 ≥ 13.43% (p = 0.045; AUC = 0.80) were significant predictors of ≥grade 2 hematological toxicity from the multivariate logistic regression analysis.

CONCLUSIONS

The volume of the PBM of patients treated with concurrent chemoradiotherapy and subjected to both low-dose (V16-18 ) and high-dose (V35,36 and V47 ) irradiation was associated with hematological toxicity, depending on the fractional volumes receiving the variable degree of dosage. The NTCP were stronger predictors of toxicity than V16-18 , V35, 36 , and V47 . Hence, avoiding radiation hot spots on the PBM could reduce the incidence of severe HT.

The Capabilities and Characteristics of Helical Tomotherapy and Co-Planar Dual Arcs Volumetric-Modulated arc Therapy Associated with Hippocampal Sparing During Prophylactic Cranial Irradiation

Objective: To investigate the features of helical tomotherapy and co-planar dual Arcs volumetric-modulated arc therapy during prophylactic cranial irradiation associated with bilateral hippocampal tissue sparing. Materials and methods: Helical tomotherapy and co-planar dual arcs volumetric-modulated arc therapy treatment plans were generated with a dose of 30 Gy/10 fractions in 16 patients treated with prophylactic cranial irradiation. The dose to the bilateral hippocampal tissues, organs at risk, and planning target volume were determined when the average dose of bilateral hippocampal tissues was reduced by approximately 4 Gy as an observation point. Changes in dosimetry when sparing the bilateral hippocampal tissues were determined for both modalities. Results: When bilateral hippocampal tissues were restricted to 8 Gy, D_{40%mean-bilateral hippocampal tissues} = 7.64 ± 0.41 Gy in helical tomotherapy, while D_{40%mean-bilateral hippocampal tissues} = 10.96 ± 0.38 Gy in co-planar dual arcs volumetric-modulated arc therapy volumetric-modulated arc therapy. Helical tomotherapy was associated with significantly lower doses to organs at risk, including D_{mean-bilateral hippocampal tissues} (P = .03), D_{98%-bilateral hippocampal tissues} (P = .01), D_{2%-bilateral hippocampal tissues} (P = .01), D_{mean-inner ear} (P = .02), D_{mean-parotid glands} (P = .02), D_max-lens (P = .02), and D_{max-brainstem} (P = .02), but not D_{max-optic nerves} (P = .87). Helical tomotherapy provided better target coverage, with lower average D_2%-PTV (P = .02), higher average D_98%-PTV (P = .02), and better conformal index (0.87 vs 0.84, P = .02) and homogeneity index (0.15 vs 0.21, P = .05). With smaller bilateral hippocampal tissues doses, the planning target volume dose changed across 3 dosimetry regions for both modalities; the plateau region (>20.0 Gy for helical tomotherapy versus >16.0 Gy for co-planar dual arcs volumetric-modulated arc therapy), gradient region (20.0-12.0 Gy vs 16.0-11.0 Gy), and falling region (<12.0 Gy vs <11.0 Gy). The average delivery duration of helical tomotherapy was almost 7.7 times longer than that of co-planar dual arcs volumetric-modulated arc therapy. Conclusions: Helical tomotherapy was better at sparing the bilateral hippocampal tissues and organs at risk and had better target coverage but a significantly longer treatment duration than co-planar dual arcs volumetric-modulated arc therapy. Further dose decreases in the bilateral hippocampal tissues would yield worse target dose coverage.

Systematic review of the effects of environmental factors on virus inactivation: implications for coronavirus disease 2019

Environmental factors such as temperature and relative humidity can affect the inactivation and transmission of coronaviruses. By reviewing medical experiments on virus survival and virus transmission between infected and susceptible species in different temperature and humidity conditions, this study explores the influence of temperature and relative humidity on the survival and transmission of viruses, and provides suggestions, with experimental evidence, for the environmental control measures of Coronavirus Disease 2019. The results indicated that (1) virus viability and infectivity is increased at a low temperature of 5 ℃ and reduced at higher temperatures. (2) Virus survival and transmission is highly efficient in a dry environment with low relative humidity, and also in a wet environment with high relative humidity, and it is minimal at intermediate relative humidity. Therefore, in indoor environments, the lack of heating in winter or overventilation, leading to low indoor temperature, can help virus survival and help susceptible people being infected. On the contrary, modulating the indoor relative humidity at an intermediate level is conducive to curb epidemic outbreaks.

Improving the Prediction of Benign or Malignant Breast Masses Using a Combination of Image Biomarkers and Clinical Parameters

Background: Breast cancer is one of the leading causes of death in female cancer patients. The disease can be detected early using Mammography, an effective X-ray imaging technology. The most important step in mammography is the classification of mammogram patches as benign or malignant. Classically, benign or malignant breast tumors are diagnosed by radiologists' interpretation of mammograms based on clinical parameters. However, because masses are heterogeneous, clinical parameters supply limited information on mammography mass. Therefore, this study aimed to predict benign or malignant breast masses using a combination of image biomarkers and clinical parameters. Methods: We trained a deep learning (DL) fusion network of VGG16 and Inception-V3 network in 5,996 mammography images from the training cohort; DL features were extracted from the second fully connected layer of the DL fusion network. We then developed a combined model incorporating DL features, hand-crafted features, and clinical parameters to predict benign or malignant breast masses. The prediction performance was compared between clinical parameters and the combination of the above features. The strengths of the clinical model and the combined model were subsequently validated in a test cohort (n = 244) and an external validation cohort (n = 100), respectively. Results: Extracted features comprised 30 hand-crafted features, 27 DL features, and 5 clinical features (shape, margin type, breast composition, age, mass size). The model combining the three feature types yielded the best performance in predicting benign or malignant masses (AUC = 0.961) in the test cohort. A significant difference in the predictive performance between the combined model and the clinical model was observed in an independent external validation cohort (AUC: 0.973 vs. 0.911, p = 0.019). Conclusion: The prediction of benign or malignant breast masses improves when image biomarkers and clinical parameters are combined; the combined model was more robust than clinical parameters alone.

Beam complexity and monitor unit efficiency comparison in two different volumetric modulated arc therapy delivery systems using automated planning

BACKGROUND

To investigate the beam complexity and monitor unit (MU) efficiency issues for two different volumetric modulated arc therapy (VMAT) delivery technologies for patients with left-sided breast cancer (BC) and nasopharyngeal carcinoma (NPC).

METHODS

Twelve left-sided BC and seven NPC cases were enrolled in this study. Each delivered treatment plan was optimized in the Pinnacle3 treatment planning system with the Auto-Planning module for the Trilogy and Synergy systems. Similar planning dose objectives and beam configurations were used for each site in the two different delivery systems to produce clinically acceptable plans. The beam complexity was evaluated in terms of the segment area (SA), segment width (SW), leaf sequence variability (LSV), aperture area variability (AAV), and modulation complexity score (MCS) based on the multileaf collimator sequence and MU. Plan delivery and a gamma evaluation were performed using a helical diode array.

RESULTS

With similar plan quality, the average SAs for the Trilogy plans were smaller than those for the Synergy plans: 55.5 ± 21.3 cm2 vs. 66.3 ± 17.9 cm2 (p < 0.05) for the NPC cases and 100.7 ± 49.2 cm2 vs. 108.5 ± 42.7 cm2 (p < 0.05) for the BC cases, respectively. The SW was statistically significant for the two delivery systems (NPC: 6.87 ± 1.95 cm vs. 6.72 ± 2.71 cm, p < 0.05; BC: 8.84 ± 2.56 cm vs. 8.09 ± 2.63 cm, p < 0.05). The LSV was significantly smaller for Trilogy (NPC: 0.84 ± 0.033 vs. 0.86 ± 0.033, p < 0.05; BC: 0.89 ± 0.026 vs. 0.90 ± 0.26, p < 0.05). The mean AAV was significantly larger for Trilogy than for Synergy (NPC: 0.18 ± 0.064 vs. 0.14 ± 0.037, p < 0.05; BC: 0.46 ± 0.15 vs. 0.33 ± 0.13, p < 0.05). The MCS values for Trilogy were higher than those for Synergy: 0.14 ± 0.016 vs. 0.12 ± 0.017 (p < 0.05) for the NPC cases and 0.42 ± 0.106 vs. 0.30 ± 0.087 (p < 0.05) for the BC cases. Compared with the Synergy plans, the average MUs for the Trilogy plans were larger: 828.6 ± 74.1 MU and 782.9 ± 85.2 MU (p > 0.05) for the NPC cases and 444.8 ± 61.3 MU and 393.8 ± 75.3 MU (p > 0.05) for the BC cases. The gamma index agreement scores were never below 91% using 3 mm/3% (global) distance to agreement and dose difference criteria and a 10% lower dose exclusion threshold.

CONCLUSIONS

The Pinnacle3 Auto-Planning system can optimize BC and NPC plans to achieve the same plan quality using both the Trilogy and Synergy systems. We found that these two systems resulted in different SAs, SWs, LSVs, AAVs and MCSs. As a result, we suggested that the beam complexity should be considered in the development of further methodologies while optimizing VMAT autoplanning.

An Algorithm Based on Text Position Correction and Encoder-Decoder Network for Text Recognition in the Scene Image of Visual Sensors

Text recognition in natural scene images has always been a hot topic in the field of document-image related visual sensors. The previous literature mostly solved the problem of horizontal text recognition, but the text in the natural scene is usually inclined and irregular, and there are many unsolved problems. For this reason, we propose a scene text recognition algorithm based on a text position correction (TPC) module and an encoder-decoder network (EDN) module. Firstly, the slanted text is modified into horizontal text through the TPC module, and then the content of horizontal text is accurately identified through the EDN module. Experiments on the standard data set show that the algorithm can recognize many kinds of irregular text and get better results. Ablation studies show that the proposed two network modules can enhance the accuracy of irregular scene text recognition.

Better view by detachable string magnetically controlled capsule endoscopy for esophageal observation: a retrospective comparative study

Magnetically controlled capsule endoscopy (MCE) system has been used to screen gastric lesions. However, the visualization performance of MCE in the esophagus has not been investigated systematically. String method improved the ability of capsule endoscopy (CE) for esophageal observing; however, the string attachment is complicated and cannot be detached with the CE inside the esophagus. We used a modified string, called detachable string attached to MCE. The aim of the study was to compare the observation performance of MCE with and without the detachable string. A total of 238 participants with upper gastrointestinal symptoms and a healthy check who refused esophagogastroduodenoscopy examination were retrospectively divided into the detachable string MCE group and the MCE alone group from June 2016 to May 2018. A suction cap with a thin, hollow string was attached to the MCE system in the detachable string group. Circumferential visualization of the esophagus including the upper, middle, and lower esophagus and Z-line, and esophageal focal lesion, as well as the recording time, safety and tolerability of the procedure, were assessed. The circumferential visualization of the upper, middle, and lower esophagus and Z-line was more efficient in the detachable string MCE group than in the MCE alone group (P < 0.001). In all, 31 esophageal lesions were detected in the detachable string MCE group, which was more than that in the MCE alone group (10, P < 0.001). The mean recording time was 305 seconds in the string MCE group, which was longer than that in the MCE alone group (48.5 seconds, P < 0.001). In seven participants (6.1%) in the detachable string MCE group, the capsule could not be separated from the string. Detachable string MCE showed better performance in terms of observation of the esophagus. Detachable string MCE can be used to screen for esophageal diseases as an alternative method in the future.

The Feasibility Study of Megavoltage Computed Tomographic (MVCT) Image for Texture Feature Analysis

Purpose: To determine whether radiomics texture features can be reproducibly obtained from megavoltage computed tomographic (MVCT) images acquired by Helical TomoTherapy (HT) with different imaging conditions.

Methods: For each of the 195 textures enrolled, the mean intrapatient difference, which is considered to be the benchmark for reproducibility, was calculated from the MVCT images of 22 patients with early-stage non-small-cell lung cancer. Test–retest MVCT images of an in-house designed phantom were acquired to determine the concordance correlation coefficient (CCC) for these 195 texture features. Features with high reproducibility (CCC > 0.9) in the phantom test–retest set were investigated for sensitivities to different imaging protocols, scatter levels, and motion frequencies using a wood phantom and in-vitro animal tissues.

Results: Of the 195 features, 165 (85%) features had CCC > 0.9. For the wood phantom, 124 features were reproducible in two kinds of scatter materials, and further investigations were performed on these features. For animal tissues, 108 features passed the criteria for reproducibility when one layer of scatter was covered, while 106 and 108 features of in-vitro liver and bone passed with two layers of scatter, respectively. Considering the effect of differing acquisition pitch (AcP), 97 features extracted from wood passed, while 103 and 59 features extracted from in-vitro liver and bone passed, respectively. Different reconstruction intervals (RI) had a small effect on the stability of the feature value. When AcP and RI were held consistent without motion, all 124 features calculated from wood passed, and a majority (122 of 124) of the features passed when imaging with a “fine” AcP with different RIs. However, only 55 and 40 features passed with motion frequencies of 20 and 25 beats per minute, respectively.

Conclusion: Motion frequency has a significant impact on MVCT texture features, and features from MVCT were more reproducibility in different scatter conditions than those from CBCT. Considering the effects of AcP and RI, the scanning protocols should be kept consistent when MVCT images are used for feature analysis. Some radiomics features from HT MVCT images are reproducible and could be used for creating clinical prediction models in the future.

Sustained pain hypersensitivity in the stressed colon: Role of mast cell-derived nerve growth factor-mediated enteric synaptic plasticity

BACKGROUND

Sustained pain hypersensitivity is the hallmark of stressed colon which could be partially explained by central sensitization with synaptic plasticity, the key mechanism of memory. We previously identified that synaptic plasticity of enteric nerve system (ENS) contributed to peripheral pain maintaining in the gut. However, the mechanisms of enteric "memory" formation remain elusive.

METHODS

In this study, rats were exposed to water avoidance stress (WAS) or sham stress (SS), with cromolyn sodium or physiological saline injected intraperitoneally 30 minutes before stress every day. The abdominal withdrawal reflex scores, mesenteric afferent nerve activity, enteric neural c-fos expression, and enteric synaptic plasticity were assessed, and mast cell infiltration and degranulation. Furthermore, colonic mucosal mediators-induced enteric synaptic plasticity and the role of mast cell-derived nerve growth factor (NGF), tryptase, and histamine were investigated via ex vivo longitudinal muscle-myenteric plexus (LMMP) organotypic culture.

KEY RESULTS

It is shown that mast cell stabilizing inhibited WAS-induced visceral hypersensitivity through enhancing visceral pain threshold, decreasing spontaneous and distention-induced mesenteric afferent firing, and downregulating enteric neural activation (c-fos). Importantly, WAS led to evident enteric synaptic plasticity, but decreased by cromolyn. Water avoidance stress-derived mucosal supernatants markedly enhanced the c-fos expression and enteric synaptic plasticity in LMMP tissues, which could be eliminated by mast cell inhibition or NGF neutralization, but not tryptase or histamine blocking.

CONCLUSIONS & INFERENCES

In conclusion, mast cells/NGF pathway may be the key regulator of synaptic plasticity of ENS and participate in the formation of chronic stress-induced sustained visceral hypersensitivity.

Negative impact of hepatitis B surface seroclearance on prognosis of hepatitis B-related primary liver cancer

AIM

To assess the impact of hepatitis B surface (HBsAg) seroclearance on survival outcomes in hepatitis B-related primary liver cancer.

METHODS

Information from patients with hepatitis B-related liver cancer admitted in our hospital from 2008-2017 was retrieved. Cases diagnosed with HBsAg (-) and HBcAb (+) liver cancer were included in the HBsAg seroclearance (SC) group. HBsAg (+) liver cancer patients strictly matched for liver cancer stage (AJCC staging system, 8^th edition), Child-Pugh score, and first diagnosis/treatment method (surgery, ablation and TACE) were assigned to the HBsAg non-seroclearance (NSC) group. Then, clinical, pathological and survival data in both groups were assessed.

RESULTS

The SC and NSC groups comprised of 72 and 216 patients, respectively. Patient age (P < 0.001) and platelet count (P = 0.001) in the SC group were significantly higher than those of the NSC group. SC group patients who underwent surgery had more intrahepatic cholangiocarcinoma (ICC) and combined HCC-CC (CHC) cases than the NSC group, but no significant differences in tumor cell differentiation and history of liver cirrhosis were found between the two groups. The numbers of interventional treatments were similar in both groups (4.57 vs 5.07, P > 0.05). Overall survival was lower in the SC group than the NSC group (P = 0.019), with 1-, 3-, and 5-year survival rates of 82.1% vs 85.1%, 43.2% vs 56.8%, and 27.0% vs 45.2%, respectively. Survival of patients with AJCC stage I disease in the SC group was lower than that of the NSC group (P = 0.029).

CONCLUSION

Seroclearance in patients with hepatitis B-related primary liver cancer has protective effects with respect to tumorigenesis, cirrhosis, and portal hypertension but confers worse prognosis, which may be due to the frequent occurrence of highly malignant ICC and CHC.

Effects of megavoltage computed tomographic scan methodology on setup verification and adaptive dose calculation in helical TomoTherapy

Background

To evaluate the effect of pretreatment megavoltage computed tomographic (MVCT) scan methodology on setup verification and adaptive dose calculation in helical TomoTherapy.

Methods

Both anthropomorphic heterogeneous chest and pelvic phantoms were planned with virtual targets by TomoTherapy Physicist Station and were scanned with TomoTherapy megavoltage image-guided radiotherapy (IGRT) system consisted of six groups of options: three different acquisition pitches (APs) of ‘fine’, ‘normal’ and ‘coarse’ were implemented by multiplying 2 different corresponding reconstruction intervals (RIs). In order to mimic patient setup variations, each phantom was shifted 5 mm away manually in three orthogonal directions respectively. The effect of MVCT scan options was analyzed in image quality (CT number and noise), adaptive dose calculation deviations and positional correction variations.

Results

MVCT scanning time with pitch of ‘fine’ was approximately twice of ‘normal’ and 3 times more than ‘coarse’ setting, all which will not be affected by different RIs. MVCT with different APs delivered almost identical CT numbers and image noise inside 7 selected regions with various densities. DVH curves from adaptive dose calculation with serial MVCT images acquired by varied pitches overlapped together, where as there are no significant difference in all p values of intercept & slope of emulational spinal cord (p = 0.761 & 0.277), heart (p = 0.984 & 0.978), lungs (p = 0.992 & 0.980), soft tissue (p = 0.319 & 0.951) and bony structures (p = 0.960 & 0.929) between the most elaborated and the roughest serials of MVCT. Furthermore, gamma index analysis shown that, compared to the dose distribution calculated on MVCT of ‘fine’, only 0.2% or 1.1% of the points analyzed on MVCT of ‘normal’ or ‘coarse’ do not meet the defined gamma criterion. On chest phantom, all registration errors larger than 1 mm appeared at superior-inferior axis, which cannot be avoided with the smallest AP and RI. On pelvic phantom, craniocaudal errors are much smaller than chest, however, AP of ‘coarse’ presents larger registration errors which can be reduced from 2.90 mm to 0.22 mm by registration technique of ‘full image’.

Conclusions

AP of ‘coarse’ with RI of 6 mm is recommended in adaptive radiotherapy (ART) planning to provide craniocaudal longer and faster MVCT scan, while registration technique of ‘full image’ should be used to avoid large residual error. Considering the trade-off between IGRT and ART, AP of ‘normal’ with RI of 2 mm was highly recommended in daily practice.

Electronic supplementary material

The online version of this article (10.1186/s13014-018-0989-y) contains supplementary material, which is available to authorized users.

Electromigration and morphological changes in Ag nanostructures

Electromigration (EM) as a structuring tool was investigated in Ag nanowires (width 300 nm, thickness 25 nm) and partly in notched and bow-tie Ag structures on a Si(1 0 0) substrate in ultra-high vacuum using a four-tip scanning tunneling microscope in combination with a scanning electron microscope. From simulations of Ag nanowires we got estimates of temperature profiles, current density profiles, EM and thermal migration (TM) mass flux distributions within the nanowire induced by critical current densities of 10⁸ A cm^-2. At room temperature, the electron wind force at these current densities by far dominates over thermal diffusion, and is responsible for formation of voids at the cathode and hillocks at the anode side. For current densities that exceed the critical current densities necessary for EM, a new type of wire-like structure formation was found both at room temperature and at 100 K for notched and bow-tie structures. This suggests that the simultaneous action of EM and TM is structure forming, but with a very small influence of TM at low temperature.

Giant gastrointestinal stromal tumour of the stomach: a case report with surgical treatment

We report a case of giant gastrointestinal stromal tumour of the stomach in a 71-year-old woman, with emphasis on its going through surgical resection. The physical examination and radiological findings revealed that a giant mass occupied most of the abdominal cavity. The patient underwent an en-block resection of the mass, partial resection of the distal stomach and Billroth II gastrojejunostomy. The pathological diagnosis was gastrointestinal stromal tumour. The patient had a long-term disease-free survival. We emphasise that complete surgical resection is the only effective radical treatment approach for giant gastrointestinal stroma of the stomach. In some cases, we still have the opportunity for resection of these tumours because of their expansive growth, even though the lesions are very large.

[Reoperation for residual aneurysm of coronary anastomosis after Bentall procedure]

Objective: To introduce a new operative method for residual aneurysm of coronary anastomosis after Bentall procedure. Methods: Between March 2011 and December 2012, six patients in Beijing Anzhen Hospital with residual aneurysm of coronary anastomosis (CT showed goldfish eye sign at the openings of coronary) after Bentall procedure underwent the operation of concentric circular patch procedure under cardiopulmonary bypass. Femoral artery, right atrium and upper right pulmonary artery cannulation were used for cardiopulmonary bypass, and the artificial vessel was transected after cardiac arrest. A concentric circular patch was pruned, whose outside diameter was slightly larger than the aneurysm and the inside diameter was equal to the openings of coronary. The outer edge of the patch was anastomosed to the outer edge of the aneurysm (opening of artificial vessel in primary surgery) with 4-0 prolene. The inner edge of the patch was anastomosed to the openings of coronary with 5-0 prolene. Results: All patients had clinical recovery. Postoperative CT demonstrated the disappearance of residual aneurysm during follow-up (the goldfish eye sign disappeared). Conclusion: The concentric circular patch procedure is a feasible treatment for residual aneurysm of coronary anastomosis.

[Surgical treatment of aortic dissection with lower extremity ischemia]

Objective: To explore the clinical outcome of the surgical treatment for aortic dissection with lower extremity ischemia. Methods: Between March 2009 and April 2013, 14 patients with type A aortic dissection and lower extremity ischemia underwent Sun's procedure in Beijing Anzhen Hospital. Ascending aorta-iliac artery bypass, ascending aorta-femoral artery bypass, femoral-femoral artery bypass and axillary -femoral artery bypass were performed on some severe patients at the same time. Results: Two death occurred, and the others were improved or recovered from symptoms. Follow-up was complete with an average time of 24 months and no aortic relevant complications occurred. Conclusion: As for patients with type A aortic dissection and lower extremity ischemia, simultaneous radical femoral artery bypass procedure is effective in improving their survival rate and quality of life.

How does four-dimensional computed tomography spare normal tissues in non-small cell lung cancer radiotherapy by defining internal target volume?

BACKGROUND

To investigate how the four-dimensional computed tomography (4DCT) technique spares normal tissues in non-small cell lung cancer (NSCLC) radiotherapy by defining individualized internal target volume (ITV).

MATERIALS AND METHODS

Gross tumor volume (GTV) and clinical target volume (CTV) were contoured on all 10 respiratory phases of 4DCT scans in 10 patients with peripheral NSCLC. Both 3D and 4D treatment plans were performed for each patient using planning target volume (PTV)3D (derived from a single CTV plus conventional margins) and PTV4D (derived from 4D internal target volume, which included all 10 CTVs plus setup margins). Dose volume histogram and normal tissue complication probability (NTCP) values were compared for the lung, heart, and spinal cord between 3D and 4D treatment plans.

RESULTS

The average PTV of the 4D (127.56 ± 70.79) was less than the 3D plans (147.65 ± 76.89). The 4D spared more surrounding normal tissues than the 3D plans, especially in the lung. Compared with 3D plans, V5, V10, V20 and V30 of the total lung decreased from 41.25%, 37.75%, 24.25%, 17.00% to 38.13%, 33.00%, 21.25%, 15.13%, respectively. Without increasing the NTCP of the lung significantly, the 4D plans allowed us to increase the average prescription dose from 60 Gy to 66.00 ± 4.62 Gy.

CONCLUSIONS

4DCT based plans can reduce the target volumes, spare more normal tissues, and allow dose escalation compared with 3D plans in NSCLC radiotherapy.

Genetic analysis of BMP4 gene in Chinese Han female population with premature ovarian insufficiency

The bone morphogenetic protein 4 (BMP4) gene is related to development of female reproductive organs in animal models. However, to date, there has been no consensus on the relationship between mutations in BMP4 and premature ovarian insufficiency (POI) in human beings. To analyze variations in BMP4 in Chinese women with POI, we sequenced two coding regions of BMP4 in 99 Han Chinese women with POI after DNA extraction and amplification by polymerase chain reaction (PCR). We found no any mutation in the BMP4 coding regions. Only one SNP rs17563 was detected among women with POI. However, the allele frequency of rs17563 presented no significant differences between POI patients and the international HapMap Project data for CHB and CHD. Our findings suggest that the BMP4 gene may not represent a risk factor in the development of POI among Chinese Han women.

Electroacupuncture improves burn-induced impairment in gastric motility mediated via the vagal mechanism in rats

BACKGROUND

Delayed gastric emptying (GE) is common in patients with severe burns. This study was designed to investigate effects and mechanisms of electroacupuncture (EA) on gastric motility in rats with burns.

METHODS

Male rats (intact and vagotomized) were implanted with gastric electrodes, chest and abdominal wall electrodes for investigating the effects of EA at ST-36 (stomach-36 or Zusanli) on GE, gastric slow waves, autonomic functions, and plasma interleukin 6 (IL-6) 6 and 24 h post severe burns.

KEY RESULTS

(i) Burn delayed GE (P < 0.001). Electroacupuncture improved GE 6 and 24 h post burn (P < 0.001). Vagotomy blocked the EA effect on GE. (ii) Electroacupuncture improved burn-induced gastric dysrhythmia. The percentage of normal slow waves was increased with EA 6 and 24 h post burn (P = 0.02). (iii) Electroacupuncture increased vagal activity assessed by the spectral analysis of heart rate variability (HRV). The high-frequency component reflecting vagal component was increased with EA 6 (P = 0.004) and 24 h post burn (P = 0.03, vs sham-EA). (iv) Electroacupuncture attenuated burn-induced increase in plasma IL-6 at both 6 (P = 0.03) and 24 h post burn (P = 0.003).

CONCLUSIONS & INFERENCES

Electroacupuncture at ST-36 improves gastric dysrhythmia and accelerates GE in rats with burns. The improvement seems to be mediated via the vagal pathway involving the inflammatory cytokine IL-6.

Trends in seroprevalence of antibodies to pandemic influenza H1N1 (2009) virus among patients seeking care in China

We determined seroprevalence of antibodies to pandemic influenza H1N1 (2009) virus in outpatients in China from December 2009 to March 2010. Serum antibody titers were determined by a hemagglutination-inhibition (HI) assay using the seroprevalence data for 2006-2008 (1.2%) as baseline. The overall seroprevalence was 7.6%, 18.6%, 20.5%, and 20.0% in December 2009, January 2010, February 2010, and March 2010, respectively. In comparison of monthly data, the seroprevalence values for the first three months exhibited statistically significant differences. As for the age-specific seroprevalence, the individuals aged demic virus.