Parallel CNN-Deep Learning Clinical-Imaging Signature for Assessing Pathologic Grade and Prognosis of Soft Tissue Sarcoma Patients.

BACKGROUND: Traditional biopsies pose risks and may not accurately reflect soft tissue sarcoma (STS) heterogeneity. MRI provides a noninvasive, comprehensive alternative. PURPOSE: To assess the diagnostic accuracy of histological grading and prognosis in STS patients when integrating clinical-imaging parameters with deep learning (DL) features from preoperative MR images. STUDY TYPE: Retrospective/prospective. POPULATION: 354 pathologically confirmed STS patients (226 low-grade, 128 high-grade) from three hospitals and the Cancer Imaging Archive (TCIA), divided into training (n = 185), external test (n = 125), and TCIA cohorts (n = 44). 12 patients (6 low-grade, 6 high-grade) were enrolled into prospective validation cohort. FIELD STRENGTH/SEQUENCE: 1.5 T and 3.0 T/Unenhanced T1-weighted and fat-suppressed-T2-weighted. ASSESSMENT: DL features were extracted from MR images using a parallel ResNet-18 model to construct DL signature. Clinical-imaging characteristics included age, gender, tumor-node-metastasis stage and MRI semantic features (depth, number, heterogeneity at T1WI/FS-T2WI, necrosis, and peritumoral edema). Logistic regression analysis identified significant risk factors for the clinical model. A DL clinical-imaging signature (DLCS) was constructed by incorporating DL signature with risk factors, evaluated for risk stratification, and assessed for progression-free survival (PFS) in retrospective cohorts, with an average follow-up of 23 ± 22 months. STATISTICAL TESTS: Logistic regression, Cox regression, Kaplan-Meier curves, log-rank test, area under the receiver operating characteristic curve (AUC)，and decision curve analysis. A P-value <0.05 was considered significant. RESULTS: The AUC values for DLCS in the external test, TCIA, and prospective test cohorts (0.834, 0.838, 0.819) were superior to clinical model (0.662, 0.685, 0.694). Decision curve analysis showed that the DLCS model provided greater clinical net benefit over the DL and clinical models. Also, the DLCS model was able to risk-stratify patients and assess PFS. DATA CONCLUSION: The DLCS exhibited strong capabilities in histological grading and prognosis assessment for STS patients, and may have potential to aid in the formulation of personalized treatment plans. TECHNICAL EFFICACY: Stage 2.

Deep Learning Radiomics Nomogram to Predict Lung Metastasis in Soft-Tissue Sarcoma: A Multi-Center Study.

Objectives: To build and evaluate a deep learning radiomics nomogram (DLRN) for preoperative prediction of lung metastasis (LM) status in patients with soft tissue sarcoma (STS). Methods: In total, 242 patients with STS (training set, n=116; external validation set, n=126) who underwent magnetic resonance imaging were retrospectively enrolled in this study. We identified independent predictors for LM-status and evaluated their performance. The minimum redundancy maximum relevance (mRMR) method and least absolute shrinkage and selection operator (LASSO) algorithm were adopted to screen radiomics features. Logistic regression, decision tree, random forest, support vector machine (SVM), and adaptive boosting classifiers were compared for their ability to predict LM. To overcome the imbalanced distribution of the LM data, we retrained each machine-learning classifier using the synthetic minority over-sampling technique (SMOTE). A DLRN combining the independent clinical predictors with the best performing radiomics prediction signature (mRMR+LASSO+SVM+SMOTE) was established. Area under the receiver operating characteristics curve (AUC), calibration curves, and decision curve analysis (DCA) were used to assess the performance and clinical applicability of the models. Result: Comparisons of the AUC values applied to the external validation set revealed that the DLRN model (AUC=0.833) showed better prediction performance than the clinical model (AUC=0.664) and radiomics model (AUC=0.799). The calibration curves indicated good calibration efficiency and the DCA showed the DLRN model to have greater clinical applicability than the other two models. Conclusion: The DLRN was shown to be an accurate and efficient tool for LM-status prediction in STS.

Proton density fat fraction measurements of rotator cuff muscles: Accuracy, repeatability, and reproducibility across readers and scanners.

PURPOSE: To determine the accuracy, repeatability, and reproducibility of magnetic resonance imaging-based proton density fat fraction (MRI-PDFF) measurements of rotator cuff muscles between two readers and three different scanners. METHODS: Twenty-seven volunteers underwent serial shoulder MRI examinations of both left and right sides on one 1.5-T MRI scanner and two 3.0-T MRI scanners. Two independent readers measured muscular PDFF of the supraspinatus, infraspinatus/teres minor muscle, and subscapularis. MR spectroscopy-based proton density fat fraction (MRS-PDFF) was regarded as the reference standard for assessing accuracy. A "coffee break" examination method was used to test the repeatability of each scanner. Bland-Altman plots, Pearson correlation, and linear regression analysis were used to assess bias and linearity. The Wilcoxon signed-rank test and Friedman test were applied to evaluate repeatability and reproducibility. RESULTS: MRI-PDFF measurements indicated strong linearity (R2 = 0.749) and small bias (-0.18%) in comparison with the MRS-PDFF measurements. A very strong positive Pearson correlation (r = 0.955-0.986) between the PDFF estimates of the two repeat scans indicated excellent repeatability. The PDFF measurements showed high reproducibility, with a strong positive Pearson correlation (r = 0.668-0.698) and a small mean bias (-0.04 to -0.10%) across different scanners. CONCLUSION: MRI-PDFF measurements of rotator cuff muscles were highly accurate, repeatable, and reproducible across different readers and scanners, leading us to the conclusion that PDFF can be a reliable and robust quantitative imaging biomarker for longitudinal or multi-center studies.

A computed tomography-based radiomics signature for predicting expression of programmed death ligand 1 in head and neck squamous cell carcinoma.

OBJECTIVES: Accurate prediction of the expression of programmed death ligand 1 (PD-L1) in head and neck squamous cell carcinoma (HNSCC) before immunotherapy is crucial. This study was performed to construct and validate a contrast-enhanced computed tomography (CECT)-based radiomics signature to predict the expression of PD-L1 in HNSCC. METHODS: In total, 157 patients with confirmed HNSCC who underwent CECT scans and immunohistochemical examination of tumor PD-L1 expression were enrolled in this study. The patients were divided into a training set (n = 104; 62 PD-L1-positive and 42 PD-L1-negative) and an external validation set (n = 53; 34 PD-L1-positive and 19 PD-L1-negative). A radiomics signature was constructed from radiomics features extracted from the CECT images, and a radiomics score was calculated. Performance of the radiomics signature was assessed using receiver operating characteristics analysis. RESULTS: Nine features were finally selected to construct the radiomics signature. The performance of the radiomics signature to distinguish between a PD-L1-positive and PD-L1-negative status in both the training and validation sets was good, with an area under the receiver operating characteristics curve of 0.852 and 0.802 for the training and validation sets, respectively. CONCLUSIONS: A CECT-based radiomics signature was constructed to predict the expression of PD-L1 in HNSCC. This model showed favorable predictive efficacy and might be useful for identifying patients with HNSCC who can benefit from anti-PD-L1 immunotherapy. KEY POINTS: • Accurate prediction of the expression of PD-L1 in HNSCC before immunotherapy is crucial. • A CECT-based radiomics signature showed favorable predictive efficacy in estimation of the PD-L1 expression status in patients with HNSCC.

A CT-based radiomics nomogram for differentiation of squamous cell carcinoma and non-Hodgkin's lymphoma of the palatine tonsil.

OBJECTIVES: Accurate preoperative differentiation between squamous cell carcinoma (SCC) and non-Hodgkin's lymphoma (NHL) in the palatine tonsil is crucial because of their different treatment. This study aimed to construct and validate a contrast-enhanced CT (CECT)-based radiomics nomogram for preoperative differentiation of SCC and NHL in the palatine tonsil. METHODS: This study enrolled 135 patients with a pathological diagnosis of SCC or NHL from two clinical centers, who were divided into training (n = 94; SCC = 50, NHL = 44) and external validation sets (n = 41; SCC = 22, NHL = 19). A radiomics signature was constructed from radiomics features extracted from routine CECT images and a radiomics score (Rad-score) was calculated. A clinical model was established using demographic features and CT findings. The independent clinical factors and Rad-score were combined to construct a radiomics nomogram. Performance of the clinical model, radiomics signature, and nomogram was assessed using receiver operating characteristics analysis and decision curve analysis. RESULTS: Eleven features were finally selected to construct the radiomics signature. The radiomics nomogram incorporating gender, mean CECT value, and radiomics signature showed better predictive value for differentiating SCC from NHL than the clinical model for training (AUC, 0.919 vs. 0.801, p = 0.004) and validation (AUC, 0.876 vs. 0.703, p = 0.029) sets. Decision curve analysis demonstrated that the radiomics nomogram was more clinically useful than the clinical model. CONCLUSIONS: A CECT-based radiomics nomogram was constructed incorporating gender, mean CECT value, and radiomics signature. This nomogram showed favorable predictive efficacy for differentiating SCC from NHL in the palatine tonsil, and might be useful for clinical decision-making. KEY POINTS: • Differential diagnosis between SCC and NHL in the palatine tonsil is difficult by conventional imaging modalities. • A radiomics nomogram integrated with the radiomics signature, gender, and mean contrast-enhanced CT value facilitates differentiation of SCC from NHL with improved diagnostic efficacy.

CT Radiomics Model for Predicting the Ki-67 Index of Lung Cancer： An Exploratory Study.

OBJECTIVE: To establish a radiomics signature and a nomogram model based on enhanced CT images to predict the Ki-67 index of lung cancer. METHODS: From January 2014 to December 2018, 282 patients with lung cancer who had undergone enhanced CT scans and Ki-67 examination within 2 weeks were retrospectively enrolled and analyzed. The clinical data of the patients were collected, such as age, sex, smoking history, maximum tumor diameter and serum tumor markers. Our primary cohort was randomly divided into a training group (n=197) and a validation group (n=85) at a 7:3 ratio. A Ki-67 index ≤ 40% indicated low expression, and a Ki-67 index > 40% indicated high expression. In total, 396 radiomics features were extracted using AK software. Feature reduction and selection were performed using the lasso regression model. Logistic regression analysis was used to establish a multivariate predictive model to identify high and low Ki-67 expression in lung cancer. A nomogram integrating the radiomics score was established based on multiple logistic regression analysis. Area under the curve (AUC) was used to evaluate the prediction efficiency of the radiomics signature and nomogram. RESULTS: The AUC,sensitivity, specificity and accuracy of the radiomics signature in the training and validation groups were 0.88 (95% CI: 0.82~0.93),79.2%,84.3%,81.2% and 0.86 (95% CI: 0.78~0.94),74.6%,88.1%,79.8%, respectively. A nomogram combining radiomics features and clinical risk factors (smoking history and NSE) was developed. The AUC, sensitivity, specificity and accuracy were 0.87 (95% CI: 0.80~0.95), 75.0%, 90.2% and 83.5% in the validation group, respectively. CONCLUSION: The radiomics signature and nomogram based on enhanced CT images provide a way to predict the Ki-67 expression level in lung cancer.

Radiomics Nomograms Based on Multi-Parametric MRI for Preoperative Differential Diagnosis of Malignant and Benign Sinonasal Tumors: A Two-Centre Study.

OBJECTIVES: To investigate the efficacy of multi-parametric MRI-based radiomics nomograms for preoperative distinction between benign and malignant sinonasal tumors. METHODS: Data of 244 patients with sinonasal tumor (training set, n=192; test set, n=52) who had undergone pre-contrast MRI, and 101 patients who underwent post-contrast MRI (training set, n=74; test set, n=27) were retrospectively analyzed. Independent predictors of malignancy were identified and their performance were evaluated. Seven radiomics signatures (RSs) using maximum relevance minimum redundancy (mRMR), and the least absolute shrinkage selection operator (LASSO) algorithm were established. The radiomics nomograms, comprising the clinical model and the RS algorithms were built: one based on pre-contrast MRI (RNWOC); the other based on pre-contrast and post-contrast MRI (RNWC). The performances of the models were evaluated with area under the curve (AUC), calibration, and decision curve analysis (DCA) respectively. RESULTS: The efficacy of the clinical model (AUC=0.81) of RNWC was higher than that of the model (AUC=0.76) of RNWOC in the test set. There was no significant difference in the AUC of radiomic algorithms in the test set. The RS-T1T2 (AUC=0.74) and RS-T1T2T1C (RSWC, AUC=0.81) achieved a good distinction efficacy in the test set. The RNWC and the RNWOC showed excellent distinction (AUC=0.89 and 0.82 respectively) in the test set. The DCA of the nomograms showed better clinical usefulness than the clinical models and radiomics signatures. CONCLUSIONS: The radiomics nomograms combining the clinical model and RS can be accurately, safely and efficiently used to distinguish between benign and malignant sinonasal tumors.

Development and Validation of a Plasma FAM19A5 and MRI-Based Radiomics Model for Prediction of Parkinson's Disease and Parkinson's Disease With Depression.

Background: Prediction and early diagnosis of Parkinson's disease (PD) and Parkinson's disease with depression (PDD) are essential for the clinical management of PD. Objectives: The present study aimed to develop a plasma Family with sequence similarity 19, member A5 (FAM19A5) and MRI-based radiomics nomogram to predict PD and PDD. Methods: The study involved 176 PD patients and 181 healthy controls (HC). Sandwich enzyme-linked immunosorbent assay (ELISA) was used to measure FAM19A5 concentration in the plasma samples collected from all participants. For enrolled subjects, MRI data were collected from 164 individuals (82 in the PD group and 82 in the HC group). The bilateral amygdala, head of the caudate nucleus, putamen, and substantia nigra, and red nucleus were manually labeled on the MR images. Radiomics features of the labeled regions were extracted. Further, machine learning methods were applied to shrink the feature size and build a predictive radiomics signature. The resulting radiomics signature was combined with plasma FAM19A5 concentration and other risk factors to establish logistic regression models for the prediction of PD and PDD. Results: The plasma FAM19A5 levels (2.456 ± 0.517) were recorded to be significantly higher in the PD group as compared to the HC group (2.23 ± 0.457) (P < 0.001). Importantly, the plasma FAM19A5 levels were also significantly higher in the PDD subgroup (2.577 ± 0.408) as compared to the non-depressive subgroup (2.406 ± 0.549) (P = 0.045 < 0.05). The model based on the combination of plasma FAM19A5 and radiomics signature showed excellent predictive validity for PD and PDD, with AUCs of 0.913 (95% CI: 0.861-0.955) and 0.937 (95% CI: 0.845-0.970), respectively. Conclusion: Altogether, the present study reported the development of nomograms incorporating radiomics signature, plasma FAM19A5, and clinical risk factors, which might serve as potential tools for early prediction of PD and PDD in clinical settings.

High-resolution MRI assessment of optic nerve sheath diameter in adults: optic nerve sheath variation and a new diagnostic tool for intracranial hypertension.

BACKGROUND: Assessment of optic nerve sheath diameter (ONSD) is a non-invasive measure of intracranial pressure (ICP). However, it is not clear whether healthy individuals exhibit ONSD variation or whether factors other than ICP affect the ONSD. PURPOSE: To investigate whether ONSD was correlated with age, sex, height, weight, eyeball transverse diameter (ETD), or body mass index (BMI), and to develop a new diagnostic model to increase the diagnostic accuracy of intracranial hypertension (IH). MATERIAL AND METHODS: A total of 145 relatively healthy adults and 40 patients with acute IH who underwent high-resolution magnetic resonance imaging (MRI) were enrolled in this study. Linear regression analyses were used to determine the relationship between ONSD and these variables. If correlations were identified, an index ONSDΔ removing variables effects was calculated. ROC analysis was used to assess the IH predictive value of ONSDΔ in terms of sensitivity and specificity. RESULTS: In relatively healthy adults, there was a correlation between ONSD and BMI (P = 0.002), which can be presented as an index ONSDΔ. The ONSDΔ model better predicted IH than the ONSD model (P = 0.035), with a sensitivity of 70.00%, a specificity of 71.72%, and an AUC of 0.755. CONCLUSION: A correlation between ONSD and body mass index (BMI) was found using high-resolution MRI. This result indicates that the effects of BMI should be considered along with the ONSD during ICP monitoring. Meanwhile, the index ONSDΔ was better than the ONSD in predicting IH and could be used to obtain a more precise estimation of ICP.

A CT-based radiomics nomogram for differentiation of lympho-associated benign and malignant lesions of the parotid gland.

OBJECTIVES: Preoperative differentiation between benign lymphoepithelial lesion (BLEL) and mucosa-associated lymphoid tissue lymphoma (MALToma) in the parotid gland is important for treatment decisions. The purpose of this study was to develop and validate a CT-based radiomics nomogram combining radiomics signature and clinical factors for the preoperative differentiation of BLEL from MALToma in the parotid gland. METHODS: A total of 101 patients with BLEL (n = 46) or MALToma (n = 55) were divided into a training set (n = 70) and validation set (n = 31). Radiomics features were extracted from non-contrast CT images, a radiomics signature was constructed, and a radiomics score (Rad-score) was calculated. Demographics and CT findings were assessed to build a clinical factor model. A radiomics nomogram combining the Rad-score and independent clinical factors was constructed using multivariate logistic regression analysis. The performance levels of the nomogram, radiomics signature, and clinical model were evaluated and validated on the training and validation datasets, and then compared among the three models. RESULTS: Seven features were used to build the radiomics signature. The radiomics nomogram incorporating the clinical factors and radiomics signature showed favorable predictive value for differentiating parotid BLEL from MALToma, with AUCs of 0.983 and 0.950 for the training set and validation set, respectively. Decision curve analysis showed that the nomogram outperformed the clinical factor model in terms of clinical usefulness. CONCLUSIONS: The CT-based radiomics nomogram incorporating the Rad-score and clinical factors showed favorable predictive efficacy for differentiating BLEL from MALToma in the parotid gland, and may help in the clinical decision-making process. KEY POINTS: • Differential diagnosis between BLEL and MALToma in parotid gland is rather difficult by conventional imaging modalities. • A radiomics nomogram integrated with the radiomics signature, demographics, and CT findings facilitates differentiation of BLEL from MALToma with improved diagnostic efficacy.

Computed tomography and magnetic resonance imaging features of cervical chordoma.

Computed tomography (CT) and magnetic resonance imaging (MRI) scans of 11 patients with histologically proven cervical chordoma were retrospectively evaluated. Imaging features assessed included location, morphology, association with adjacent structures, vertebral destruction, status of cortical bone, periosteal reaction, attenuation and calcification by CT, and signal intensity and enhancement pattern by MRI. Of 7 cases with CT, 6 exhibited lytic-sclerotic bone destruction. A total of 5 cases exhibited pressure erosion of outer cortex, 3 of which had spiculated periosteal reaction. Calcification was observed in 3 cases. All cases were heterogeneous and hypodense. MRI T2-weighted images (n=10) revealed heterogeneous hyperintense (n=5), intermediate (n=2) and intermediate-hyperintense signal intensity (n=3). Hypointense septa between lobules (n=5) and stripes (n=3) were observed on T2-weighted images. Post-contrast magnetic resonance images (n=6) demonstrated marked heterogeneous (n=3) and ring-like (n=3) enhancement. CT scanning is valuable in revealing the lytic-sclerotic bone destruction, pressure erosion of outer cortex and calcification. MRI is useful in demonstrating the results of soft tissue mass. The two examinations are necessary for differential diagnosis of patients with suspected cervical chordoma.

Magnetic Resonance Features and Characteristic Vascular Pattern of Alveolar Soft-Part Sarcoma.

OBJECTIVE: The aim of this study was to investigate the magnetic resonance (MR) features of alveolar soft-part sarcoma (ASPS). METHODS: We studied 12 patients with ASPS confirmed by pathology in this retrospective study. MR features were analyzed, especially for the location, morphology, signals, and related enhanced features of the tumor vessels. RESULTS: Flow voids were shown in the central part of the tumor on T2-weighted imaging (T2WI) in all patients; they were arrayed in a radiating mode gathered toward the center (8 cases), designated by us as vascular center-gathered syndrome (VCGS), or scattered like twigs (4 cases). The flow voids were accompanied by high signals in all patients, including tubular (6 cases) and platy (6 cases) signals. Slightly higher signals were shown in the peripheral part of the tumor in all patients. Flow voids in the peripheral part were shown in all patients, and the majority of the flow voids surrounded the tumor (8 cases). The vessels around the tumor in 9 patients showed high signals, and the majority of the vessels were located at the superior and inferior poles (8 cases). 6 patients underwent enhanced scanning, including moderate (5 cases) and significant enhancement (1 case). CONCLUSION: Low signals of radiating flow voids accompanied by high signals of slow blood flow or blood sinuses in the center part have high significance for the diagnosis of ASPS.

Genome-wide methylome and chromatin interactome identify abnormal enhancer to be risk factor of breast cancer.

Enhancer is critical cis regulatory elements in gene expression. To understand whether and how the aberrant enhancer activation may contribute to cancer risk, the differentially methylated enhancers (eDMRs) in normal and malignant breast tissues were identified and analyzed. By incorporating genome-wide chromatin interaction, integrated analysis of eDMRs and target gene expression identified 1,272 enhancer-promoter pairs. Surprisingly, two functionally distinct groups of genes were identified in these pairs, one showing better correlation to enhancer methylation (eRGs) and the other showing better correlation to promoter methylation (pRGs), and the former group is functionally enriched with cancer related genes. Moreover, enhancer methylation based clustering of breast cancer samples is capable of discriminating basal breast cancer from other subtypes. By correlating enhancer methylation status to patient survival, 345 enhancers show the impact on the disease outcome and the majority of their target genes are important regulators of cell survival pathways including known cancer related genes. Together, these results suggest reactivation of enhancers in cancer cells has the add-on effect and contributes to cancer risk in combination.

Morphometric MRI changes in intracranial hypertension due to cerebral venous thrombosis: a retrospective imaging study.

AIM: To evaluate whether some magnetic resonance imaging (MRI) signs suggesting idiopathic intracranial hypertension (IIH) could also be found in intracranial hypertension (IH) due to cerebral venous thrombosis (CVT) and to assess their possible contribution to diagnosing this disorder. MATERIALS AND METHODS: Thirty-one patients with IH due to CVT were evaluated prospectively using MRI. A group of 33 age- and sex-matched healthy volunteers served as controls. The optic nerve and sheath, pituitary gland, and ventricles were assessed. The prevalence of each imaging feature was compared between the two groups. RESULTS: Optic nerve sheath (ONS) dilatation and decreased pituitary gland height were the most valid signs suggesting IH in CVT patients: sensitivity 70.97% and 87.1%, respectively; specificity 96.97% and 72.73%, respectively; area under the curve 0.840 and 0.809, respectively. The MRI finding that showed the strongest association with IH in CVT patients was ONS dilatation (odds ratio 78.5). CONCLUSIONS: The combination of T1-weighted volumetric MRI and magnetic resonance venography could be helpful for diagnosing IH with CVT. Abnormalities of the ONS and the pituitary gland were reliable diagnostic signs for IH due to CVT.

Molecular hydrogen inhibits lipopolysaccharide-triggered NLRP3 inflammasome activation in macrophages by targeting the mitochondrial reactive oxygen species.

The NLRP3 inflammasome, an intracellular multi-protein complex controlling the maturation of cytokine interleukin-1ß, plays an important role in lipopolysaccharide (LPS)-induced inflammatory cascades. Recently, the production of mitochondrial reactive oxygen species (mtROS) in macrophages stimulated with LPS has been suggested to act as a trigger during the process of NLRP3 inflammasome activation that can be blocked by some mitochondria-targeted antioxidants. Known as a ROS scavenger, molecular hydrogen (H2) has been shown to possess therapeutic benefit on LPS-induced inflammatory damage in many animal experiments. Due to the unique molecular structure, H2 can easily target the mitochondria, suggesting that H2 is a potential antagonist of mtROS-dependent NLRP3 inflammasome activation. Here we have showed that, in mouse macrophages, H2 exhibited substantial inhibitory activity against LPS-initiated NLRP3 inflammasome activation by scavenging mtROS. Moreover, the elimination of mtROS by H2 resultantly inhibited mtROS-mediated NLRP3 deubiquitination, a non-transcriptional priming signal of NLRP3 in response to the stimulation of LPS. Additionally, the removal of mtROS by H2 reduced the generation of oxidized mitochondrial DNA and consequently decreased its binding to NLRP3, thereby inhibiting the NLRP3 inflammasome activation. Our findings have, for the first time, revealed the novel mechanism underlying the inhibitory effect of molecular hydrogen on LPS-caused NLRP3 inflammasome activation, highlighting the promising application of this new antioxidant in the treatment of LPS-associated inflammatory pathological damage.

Avalanche process of the fiber-bundle model with stick-slip dynamics and a variable Young modulus.

In order to more accurately describe the fracture process of extensive biological fibers, a fiber-bundle model with stick-slip dynamics and a variable Young modulus is constructed. In this model, the Young modulus of a fiber is assumed to increase or decrease by multiplying with a changing ratio after local sliding events. So, the maximum number of stick-slip events of a single fiber and the changing ratio of the Young modulus are the two key parameters of the model. By means of analytical theory and numerical simulation, the constitutive law, the critical stress, the average size of the largest avalanche, and the avalanche size distribution are shown against the two parameters of the model. From a macroscopic viewpoint, the constitutive curves show different morphologies varying from a local plastic state to a unimodal parabola, while from a microscopic viewpoint, the avalanche size distributions can be well fitted into a power law relationship, which is in accord with the classical fiber-bundle model.

Systematic analysis of genomic organization and structure of long non-coding RNAs in the human genome.

The genomic architecture of several functional elements in animals and plants, such as microRNAs and tRNA, has been better characterized. As yet, there is very little known about genomic organization and structure of lncRNA in animals and plants. Here, we conducted a genome-wide systematic computational analysis of genomic architecture of lncRNAs, and further provided a more comprehensive comparative view of genomic organization between lncRNAs and several other functional elements in the human genome. Our study not only provides comprehensive knowledge for further studies into the correlations between the genomic architecture of lncRNAs and their important functional roles in diverse cellular processes and in disease, but also will be valuable for understanding the origin and evolution of lncRNAs.

Endovascular intervention of intradural hemorrhage from ruptured spontaneous vertebral artery dissection.

OBJECTIVE: To study the therapeutic effect of endovascular treatment for intradural hemorrhage from ruptured spontaneous vertebral artery dissections (SVAD) using Guglielmi detachable coils and mechanical coils. METHODS: The retrospective study was carried out in the Department of Interventional Radiology, Rizhao People`s Hospital, Rizhao, China from January 2008 to December 2011. Twelve patients with intradural hemorrhage from ruptured SVAD underwent endovascular embolization treatment after imaging and clinical evaluation. The aneurysm lumen and the parent artery were embolized with Guglielmi detachable coils and mechanical coils. Guglielmi detachable coils were used to embolize the aneurysm lumen and the parent artery adjacent to the aneurysm. Mechanical coils were used to embolize the parent artery. RESULTS: All lesions were proximal to the posterior inferior cerebellar artery origin. All patients had successful outcomes without any other complications. Angiograms immediately after embolization demonstrated complete occlusions. There were no patient deaths during the study. All cases resulted in complete occlusions, and no rebleeding or ischemia occurred during the 6-36 month follow-up period. CONCLUSION: Endovascular intervention with Guglielmi detachable coils and mechanical coils is a safe and efficacious method for treating intradural hemorrhage from ruptured SVAD.

Pigmented villonodular synovitis of the ankle: radiologic characteristics.

BACKGROUND: Pigmented villonodular synovitis (PVNS) of the ankle is a rare benign proliferative growth of the synovium. Studies of the radiologic characteristics of ankle PVNS are sparse. METHODS: To characterize the radiologic features of ankle PVNS, five patients with histologically proven ankle PVNS were retrospectively studied. The features of their radiographs, computed tomographic scans, and magnetic resonance images were reviewed, with emphasis on the morphological features, extension, margin, bone involvement, signal intensity, and degree of magnetic resonance enhancement. RESULTS: All five lesions were diffuse, affecting the ankle and distal tibiofibular joint; three lesions also involved the subtalar joint. Radiography demonstrated extrinsic bone erosions with marginal sclerosis of the involved joints in all of the patients, but computed tomography identified this much better than did radiography. Magnetic resonance imaging revealed multiple lobulated soft-tissue masses in all of the cases. These soft-tissue masses surrounded the flexor hallux longus tendon and were hypointense on T1-weighted images, with a heterogeneous signal in two cases and homogenous hypointensity in three cases on fat-suppressed T2-weighted images. In one patient who underwent gadolinium-enhanced imaging, the masses showed intense enhancement. CONCLUSIONS: Magnetic resonance imaging is the best way to reveal ankle PVNS. Magnetic resonance imaging findings of predominant hypointensity on all pulse sequences and standard radiography findings of bone erosion with marginal sclerosis are characteristic.

Osteochondral lesions of the talus: comparison of three-dimensional fat-suppressed fast spoiled gradient-echo magnetic resonance imaging and conventional magnetic resonance imaging.

BACKGROUND: Conventional magnetic resonance imaging (MRI) has been demonstrated to be a valuable tool in diagnosing osteochondral lesions of the talus. No previous study, to our knowledge, has evaluated the diagnostic ability of fat-suppressed fast spoiled gradient-echo (FSPGR) MRI in osteochondral lesions of the talus. We sought to compare three-dimensional fat-suppressed FSPGR MRI with conventional MRI in diagnosing osteochondral lesions of the talus. METHODS: Thirty-two consecutive patients with clinically suspected cartilage lesions undergoing three-dimensional fat-suppressed FSPGR MRI and conventional MRI were assessed. Sensitivity, specificity, and accuracy of diagnosis were determined using arthroscopic findings as the standard of reference for the different imaging techniques. The location of the lesion on the talar dome was recorded on a nine-zone anatomical grid on MRIs. RESULTS: Arthroscopy revealed 21 patients with hyaline cartilage defects and 11 with normal ankle joints. The sensitivity, specificity, and accuracy of the two methods for detecting articular cartilage defect were 62%, 100%, and 75%, respectively, for conventional MRI and 91%, 100%, and 94% for three-dimensional fat-suppressed FSPGR MRI. Sensitivity and accuracy were significantly higher for FSPGR imaging than for conventional MRI (P < .05), but there was no difference in specificity between these two methods. According to the nine-zone anatomical grid, the area most frequently involved was the middle of the medial talar dome (16 lesions, 76%). CONCLUSIONS: T1-weighted three-dimensional fat-suppressed FSPGR MRI is more sensitive than is conventional MRI in detecting defects of articular cartilage covering osteochondral lesions of the talus.