Rapid Diagnosis of Pneumocystis jirovecii Pneumonia and Respiratory Tract Colonization by Next-Generation Sequencing.

OBJECTIVES: To describe the epidemiology of Pneumocystis jirovecii pneumonia and colonization diagnosed by next-generation sequencing (NGS) and explore the usefulness of the number of P. jirovecii sequence reads for the diagnosis of P. jirovecii pneumonia. METHODS: We examined the NGS results for P. jirovecii in respiratory samples collected from patients and analysed their clinical, radiological and microbiological characteristics. RESULTS: Among 285 respiratory samples collected over a 12-month period (January to December 2022), P. jirovecii sequences were detected in 56 samples from 53 patients. Fifty (94.3%) of the 53 patients were HIV-negative. Following our case definitions, 37 (69.8%) and 16 (30.2%) of the 53 patients had P. jirovecii infection and colonization respectively. P. jirovecii infection was associated with presence of underlying disease with immunosuppression (94.6% vs 18.8%, P < 0.05), positive serum 1,3-ß-D-glucan (41.2% vs 0%, P < 0.01) and higher number of P. jirovecii sequence reads (P < 0.005). In contrast, P. jirovecii colonization was associated with the male sex (93.8% vs 54.1%, P < 0.01), another definitive infectious disease diagnosis of the respiratory tract (43.8% vs 2.7%, P < 0.001) and higher survival (100% vs 67.6%, P < 0.01). Although P. jirovecii pneumonia was associated with higher number of P. jirovecii reads in respiratory samples, only a sensitivity of 82.14% and a specificity of 68.75% could be achieved. CONCLUSION: Detection of P. jirovecii sequences in respiratory samples has to be interpreted discreetly. A combination of clinical, radiological and laboratory findings is still the most crucial in determining whether a particular case is genuine P. jirovecii pneumonia.

Prediction of response to preoperative neoadjuvant chemotherapy in extremity high-grade osteosarcoma using X-ray and multiparametric MRI radiomics.

PURPOSE: This study aims to evaluate the value of applying X-ray and magnetic resonance imaging (MRI) models based on radiomics feature to predict response of extremity high-grade osteosarcoma to neoadjuvant chemotherapy (NAC). MATERIALS AND METHODS: A retrospective dataset was assembled involving 102 consecutive patients (training dataset, n = 72; validation dataset, n = 30) diagnosed with extremity high-grade osteosarcoma. The clinical features of age, gender, pathological type, lesion location, bone destruction type, size, alkaline phosphatase (ALP), and lactate dehydrogenase (LDH) were evaluated. Imaging features were extracted from X-ray and multi-parametric MRI (T1-weighted, T2-weighted, and contrast-enhanced T1-weighted) data. Features were selected using a two-stage process comprising minimal-redundancy-maximum-relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) regression. Logistic regression (LR) modelling was then applied to establish models based on clinical, X-ray, and multi-parametric MRI data, as well as combinations of these datasets. Each model was evaluated using sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) with a 95% confidence interval (CI). RESULTS: AUCs of 5 models using clinical, X-ray radiomics, MRI radiomics, X-ray plus MRI radiomics, and combination of all were 0.760 (95% CI: 0.583-0.937), 0.706 (95% CI: 0.506-0.905), 0.751 (95% CI: 0.572-0.930), 0.796 (95% CI: 0.629-0.963), 0.828 (95% CI: 0.676-0.980), respectively. The DeLong test showed no significant difference between any pair of models (p > 0.05). The combined model yielded higher performance than the clinical and radiomics models as demonstrated by net reclassification improvement (NRI) and integrated difference improvement (IDI) values, respectively. This combined model was also found to be clinically useful in the decision curve analysis (DCA). CONCLUSION: Modelling based on combination of clinical and radiomics data improves the ability to predict pathological responses to NAC in extremity high-grade osteosarcoma compared to the models based on either clinical or radiomics data.

A deep learning-machine learning fusion approach for the classification of benign, malignant, and intermediate bone tumors.

OBJECTIVES: To build and validate deep learning and machine learning fusion models to classify benign, malignant, and intermediate bone tumors based on patient clinical characteristics and conventional radiographs of the lesion. METHODS: In this retrospective study, data were collected with pathologically confirmed diagnoses of bone tumors between 2012 and 2019. Deep learning and machine learning fusion models were built to classify tumors as benign, malignant, or intermediate using conventional radiographs of the lesion and potentially relevant clinical data. Five radiologists compared diagnostic performance with and without the model. Diagnostic performance was evaluated using the area under the curve (AUC). RESULTS: A total of 643 patients' (median age, 21 years; interquartile range, 12-38 years; 244 women) 982 radiographs were included. In the test set, the binary category classification task, the radiological model of classification for benign/not benign, malignant/nonmalignant, and intermediate/not intermediate had AUCs of 0.846, 0.827, and 0.820, respectively; the fusion models had an AUC of 0.898, 0.894, and 0.865, respectively. In the three-category classification task, the radiological model achieved a macro average AUC of 0.813, and the fusion model had a macro average AUC of 0.872. In the observation test, the mean macro average AUC of all radiologists was 0.819. With the three-category classification fusion model support, the macro AUC improved by 0.026. CONCLUSION: We built, validated, and tested deep learning and machine learning models that classified bone tumors at a level comparable with that of senior radiologists. Model assistance may somewhat help radiologists' differential diagnoses of bone tumors. KEY POINTS: • The deep learning model can be used to classify benign, malignant, and intermediate bone tumors. • The machine learning model fusing information from radiographs and clinical characteristics can improve the classification capacity for bone tumors. • The diagnostic performance of the fusion model is comparable with that of senior radiologists and is potentially useful as a complement to radiologists in a bone tumor differential diagnosis.

Predictive Computed Tomography and Clinical Features for Diagnosis of COVID-19 Pneumonia: Compared With Common Viral Pneumonia.

OBJECTIVE: To determine the predictive computed tomography (CT) and clinical features for diagnosis of COVID-19 pneumonia. METHODS: The CT and clinical data including were analyzed using univariate analysis and multinomial logistic regression, followed by receiver operating characteristic curve analysis. RESULTS: The factors including size of ground grass opacity (GGO), GGO with reticular and/or interlobular septal thickening, vascular enlargement, "tree-in-bud" opacity, centrilobular nodules, and stuffy or runny nose were associated with the 2 groups of viral pneumonia, as determined by univariate analysis (P < 0.05). Only GGO with reticular and/or interlobular septal thickening, centrilobular nodules, and stuffy or runny nose remained independent risk factors in multinomial logistic regression analysis. Receiver operating characteristic curve analysis showed that the area under curve of the obtained logistic regression model was 0.893. CONCLUSION: Computed tomography and clinical features including GGO with reticular and/or interlobular septal thickening, absence of centrilobular nodules, and absence of stuffy or runny nose are potential patients with COVID-19 pneumonia.

CT differential diagnosis of COVID-19 and non-COVID-19 in symptomatic suspects: a practical scoring method.

BACKGROUND: Although typical and atypical CT image findings of COVID-19 are reported in current studies, the CT image features of COVID-19 overlap with those of viral pneumonia and other respiratory diseases. Hence, it is difficult to make an exclusive diagnosis. METHODS: Thirty confirmed cases of COVID-19 and forty-three cases of other aetiology or clinically confirmed non-COVID-19 in a general hospital were included. The clinical data including age, sex, exposure history, laboratory parameters and aetiological diagnosis of all patients were collected. Seven positive signs (posterior part/lower lobe predilection, bilateral involvement, rounded GGO, subpleural bandlike GGO, crazy-paving pattern, peripheral distribution, and GGO +/- consolidation) from significant COVID-19 CT image features and four negative signs (only one lobe involvement, only central distribution, tree-in-bud sign, and bronchial wall thickening) from other non-COVID-19 pneumonia were used. The scoring analysis of CT features was compared between the two groups (COVID-19 and non-COVID-19). RESULTS: Older age, symptoms of diarrhoea, exposure history related to Wuhan, and a lower white blood cell and lymphocyte count were significantly suggestive of COVID-19 rather than non-COVID-19 (p < 0.05). The receiver operating characteristic (ROC) curve of the combined CT image features analysis revealed that the area under the curve (AUC) of the scoring system was 0.854. These cut-off values yielded a sensitivity of 56.67% and a specificity of 95.35% for a score > 4, a sensitivity of 100% and a specificity of 23.26% for a score > 0, and a sensitivity of 86.67% and a specificity of 67.44% for a score >  2. CONCLUSIONS: With a simple and practical scoring system based on CT imaging features, we can make a hierarchical diagnosis of COVID-19 and non-COVID-19 with different management suggestions.

A 3D OPENFOAM BASED FINITE VOLUME SOLVER FOR INCOMPRESSIBLE OLDROYD-B MODEL WITH INFINITY RELAXATION TIME.

In this paper, we develop a Finite Volume solver for a 3D incompressible Oldroyd-B model with infinity relaxation time. The Finite Volume solver is implemented by using a leading open-source computational mechanics software OpenFOAM. We have imposed the divergence free condition as a constraint on the momentum equation to derive a pressure equation and a predictor-corrector procedure is applied when solving the velocity field. Both stability analysis and numerical experiments are given to show the robustness and accuracy of our algorithm. Two concrete examples on a cubical domain and a dumbbell are computed and illustrated.

The CT and MRI features of benign calvarium and skull base osteoblastoma.

OBJECTIVE: We retrospectively reviewed the CT and MRI features of patients with benign osteoblastoma in the calvarium and skull base (CSBOB). METHODS: Nine cases of pathologically confirmed benign CSBOB were analysed retrospectively. The patients had undergone CT and/or MRI. Tumour location, size, and imaging features were reviewed and recorded. RESULTS: The patients included four males and five females with a mean age of 27.0 years (age 14-40 years). The tumours were located in the frontal bone in 3 patients, the occipital bone in 3 patients, and in the parietal bone, sphenoid bone, and skull base in 1 patient each. On CT, the tumours measured 5.1 ± 3.3 (1.8-8.4) cm. Seven tumours were shown to have caused expansile bony destruction with an eggshell appearance and varying degrees of calcification or matrix mineralization. Multiple septa were observed in 5 tumours. Intracranial growth was observed in 5 tumours. On MRI, 7 tumours showed heterogeneous hypo- to isointensity on T1WI. Heterogeneous high signal patterns with low signal rims and septa were observed in 6 tumours on T2WI, and 4 showed a fluid-fluid level. On contrast-enhanced imaging, 6 tumours showed peripheral and septal enhancement, and 2 showed the dural tail sign. CONCLUSIONS: Benign CSBOB is a rare tumour characterized by expansile bony destruction, septa, a sclerotic rim and calcification or matrix mineralization on CT and MRI. ADVANCES IN KNOWLEDGE: The findings from this study contribute to a better understanding of benign CSBOB and provide valuable imaging features that can aid in its diagnosis and differentiation from other tumours in the calvarium and skull base.

Radiomics Analysis of Multiparametric MRI for Prediction of Synchronous Lung Metastases in Osteosarcoma.

Purpose: To establish and verify a predictive model involving multiparameter MRI and clinical manifestations for predicting synchronous lung metastases (SLM) in osteosarcoma. Materials and Methods: Seventy-eight consecutive patients with osteosarcoma (training dataset, n = 54; validation dataset, n = 24) were enrolled in our study. MRI features were extracted from the T1-weighted image (T1WI), T2-weighted image (T2WI), and contrast-enhanced T1-weighted image (CE-T1WI) of each patient. Least absolute shrinkage and selection operator (LASSO) regression and multifactor logistic regression were performed to select key features and build radiomics models in conjunction with logistic regression (LR) and support vector machine (SVM) classifiers. Eight individual models based on T1WI, T2WI, CE-T1WI, T1WI+T2WI, T1WI+CE-T1WI, T2WI+CE-T1WI, T1WI+T2WI+CE-T1WI, and clinical features, as well as two combined models, were built. The area under the receiver operating characteristic curve (AUC), sensitivity and specificity were employed to assess the different models. Results: Tumor size was the most significant univariate clinical indicator (1). The AUC values of the LR predictive model based on T1WI, T2WI, CE-T1WI, T1WI+T2WI, T1WI+CE-T1WI, T2WI+CE-T1WI, and T1WI+T2WI+CE-T1WI were 0.686, 0.85, 0.87, 0.879, 0.736, 0.85, and 0.914, respectively (2). The AUC values of the SVM predictive model based on T1WI, T2WI, CE-T1WI, T1WI+T2WI, T1WI +CE-T1WI, T2WI +CE-T1WI, and T1WI+T2WI+CE-T1WI were 0.629, 0.829, 0.771, 0.879, 0.643, 0.829, and 0.929, respectively (3). The AUC values of the clinical, combined 1 (clinical and LR-radiomics) and combined 2 (clinical and SVM-radiomics) predictive models were 0.779, 0.957, and 0.943, respectively. Conclusion: The combined model exhibited good performance in predicting osteosarcoma SLM and may be helpful in clinical decision-making.

Clinical and imaging features of 112 patients with irregular and flat bone osteosarcoma.

Background: This study evaluated the clinical characteristics and imaging findings of 112 patients with irregular and flat bone osteosarcoma (IFBO). Methods: The age, gender, location, tumor size, density and signal intensity, osteoid matrix, periosteal reaction, and histological subtypes were analyzed for 112 patients with IFBO. Results: A total of 112 patients with IFBO, including 64 males and 48 females, with a mean age of 34.8 years were enrolled in this study. Over half of the tumors (54.5%) were detected in the craniofacial region and the skull (24 in the maxilla bone, 17 in the mandible bone, 11 in the sphenoid bone, 7 in the temporal bone, 1 in the frontal bone, and 1 in the occipital bone). Other tumor locations included the pelvic region (20.5%; 20 in the ilium and 3 in the pubis), the chest (18.8%; 11 in the scapula, 7 in the ribs, and 3 in the clavicle), and the vertebrae (6.3%; 3 in the thoracic spine, 2 in the lumbar spine, 1 in the sacrum, and 1 in the cervical spine). Transarticular extension occurred in 11 of the 23 pelvic cases (47.8%), primarily involving the sacroiliac joint (90.9%; 10 of 11). Six cases (6/7; 85.7%) of vertebral osteosarcoma arose from the transverse process and the pedicle, and 1 (1/7; 14.3%) arose from the sacral tuberosity and the ala, with partial vertebral body involvement. Additionally, 27 patients (24.1%) presented with secondary osteosarcoma related to prior radiotherapy, and 2 (1.8%) were associated with osteoblastoma and fibrous dysplasia. Histological examination revealed high-grade tumors in 88 (78.6%) cases. The tumors presented as soft-tissue masses with a diameter of 7.5±3.2 cm. A total of 91 patients underwent X-ray examination and/or computed tomography (CT) examinations. The osteoid matrix was detected in 84 patients (84/91;92.3%). A periosteal reaction was detected in 56 cases (56/91; 61.5%), including a lamellar periosteal reaction in 10 patients (11.0%) and a spiculated periosteal reaction in 46 cases (50.5%). All 74 cases who underwent magnetic resonance imaging (MRI) examinations presented with heterogeneous masses in the surrounding soft tissue. Enhancement was homogenous in 12 cases (18.5%) and heterogeneous in 53 cases (81.5%). Peripheral rim enhancement was observed in 10 cases (13.5%). Conclusions: IFBO should be considered when diagnosing patients over 30 years of age who exhibit osteoid matrix in bone lesions. Maxillofacial osteosarcoma is commonly associated with a history of radiation exposure. Pelvic osteosarcoma is more likely to invade the sacroiliac joint. Vertebral osteosarcoma frequently arises in the transverse process and pedicle, with partial body involvement.

Seizure as the clinical presentation of massive pulmonary embolism: Case report and literature review.

Massive pulmonary embolism (MPE) is a high-risk medical emergency. Seizure as the clinical presentation of MPE is extremely rare, and to our knowledge, there have been no reports on successful percutaneous, catheter-based treatment of MPE presenting with new-onset seizures and cardiac arrest. In this report, we discuss the case of a 64-year-old woman who presented with an episode of seizure that lasted 5 h. Seizure occurred four times within 12 h after arrival at the hospital, and in the end, she sustained a cardiac arrest. The patient had no past history of seizure or cardiopulmonary disease. Bilateral MPE was detected by a computed tomography pulmonary angiogram, and she was successfully treated with percutaneous, catheter-directed anticoagulant therapy. Pulmonary embolism-related seizures are more difficult to diagnose and have higher mortality rates than seizures. MPE should be suspected in patients presenting with new-onset seizures and hemodynamic instability.

Using Machine Learning to Unravel the Value of Radiographic Features for the Classification of Bone Tumors.

OBJECTIVES: To build and validate random forest (RF) models for the classification of bone tumors based on the conventional radiographic features of the lesion and patients' clinical characteristics, and identify the most essential features for the classification of bone tumors. MATERIALS AND METHODS: In this retrospective study, 796 patients (benign bone tumors: 412 cases, malignant bone tumors: 215 cases, intermediate bone tumors: 169 cases) with pathologically confirmed bone tumors from Nanfang Hospital of Southern Medical University, Foshan Hospital of TCM, and University of Hong Kong-Shenzhen Hospital were enrolled. RF models were built to classify tumors as benign, malignant, or intermediate based on conventional radiographic features and potentially relevant clinical characteristics extracted by three musculoskeletal radiologists with ten years of experience. SHapley Additive exPlanations (SHAP) was used to identify the most essential features for the classification of bone tumors. The diagnostic performance of the RF models was quantified using receiver operating characteristic (ROC) curves. RESULTS: The features extracted by the three radiologists had a satisfactory agreement and the minimum intraclass correlation coefficient (ICC) was 0.761 (CI: 0.686-0.824, P < .001). The binary and tertiary models were built to classify tumors as benign, malignant, or intermediate based on the imaging and clinical features from 627 and 796 patients. The AUC of the binary (19 variables) and tertiary (22 variables) models were 0.97 and 0.94, respectively. The accuracy of binary and tertiary models were 94.71% and 82.77%, respectively. In descending order, the most important features influencing classification in the binary model were margin, cortex involvement, and the pattern of bone destruction, and the most important features in the tertiary model were margin, high-density components, and cortex involvement. CONCLUSIONS: This study developed interpretable models to classify bone tumors with great performance. These should allow radiographers to identify imaging features that are important for the classification of bone tumors in the clinical setting.

Pure and Mixed Tubular Carcinoma of the Breast: Mammographic Features, Clinicopathological Characteristics and Prognostic Analysis.

Objective: To evaluate the mammographic features, clinicopathological characteristics, treatments, and prognosis of pure and mixed tubular carcinomas of the breast. Materials and methods: Twenty-five tubular carcinomas were pathologically confirmed at our hospital from January 2011 to May 2019. Twenty-one patients underwent preoperative mammography. A retrospective analysis of mammographic features, clinicopathological characteristics, treatment, and outcomes was performed. Results: Altogether, 95% of the pure tubular carcinomas (PTCs) and mixed tubular carcinomas (MTCs) showed the presence of a mass or structural distortions on mammography and the difference was not statistically significant (P = .373). MTCs exhibited a larger tumor size than PTCs (P = .033). Lymph node metastasis was more common (P = .005) in MTCs. Patients in our study showed high estrogen receptor and progesterone receptor positivity rates, but low human epidermal growth factor receptor 2 positivity rate. The overall survival rate was 100% in both PTC and MTC groups and the 5-year disease-free survival rates were 100% and 75%, respectively with no significant difference between the groups (P = .264). Conclusion: Tubular carcinoma of the breast is potentially malignant and has a favorable prognosis. Digital breast tomosynthesis may improve its detection. For patients with PTC, breast-conserving surgery and sentinel lymph node biopsy are recommended based on the low rate of lymph node metastasis and good prognosis. MTC has a relatively high rate of lymph node metastasis and a particular risk of metastasis. Axillary lymph node dissection should be performed for MTC even if the tumor is smaller than 2 cm.

Diagnostic performance between CT and initial real-time RT-PCR for clinically suspected 2019 coronavirus disease (COVID-19) patients outside Wuhan, China.

INTRODUCTION: Chest CT is thought to be sensitive but less specific in diagnosing the 2019 coronavirus disease (COVID-19). The diagnostic value of CT is unclear. We aimed to compare the performance of CT and initial RT-PCR for clinically suspected COVID-19 patients outside the epicentre-Wuhan, China. MATERIALS AND METHODS: Patients clinically suspected of COVID-19 infection who underwent initial RT-PCR and chest CT at the same time were retrospectively enrolled. Two radiologists with specific training reviewed the CT images independently and final diagnoses of the presence or absence of COVID-19 was reached by consensus. With serial RT-PCR as reference standard, the performance of initial RT-PCR and chest CT was analysed. A strategy of combining initial RT-PCR and chest CT was analysed to study the additional benefit. RESULTS: 82 patients admitted to hospital between Jan 10, 2020 to Feb 28, 2020 were enrolled. 34 COVID-19 and 48 non-COVID-19 patients were identified by serial RT-PCR. The sensitivity, specificity was 79% (27/34) and 100% (48/48) for initial RT-PCR and 77% (26/34) and 96% (46/48) for chest CT. The image readers had a good interobserver agreement with Cohen's kappa of 0.69. No statistical difference was found in the diagnostic performance between initial RT-PCR and chest CT. The comprehensive strategy had a higher sensitivity of 94% (32/34). CONCLUSIONS: Initial RT-PCR and chest CT had comparable diagnostic performance in identification of suspected COVID-19 patients outside the epidemic center. To compensate potential risk of false-negative PCR, chest CT should be applied for clinically suspected patients with negative initial RT-PCR.

Head and neck osteosarcoma: CT and MR imaging features.

OBJECTIVE: This study aims to assess the CT and MRI features of head and neck osteosarcoma (HNO). METHODS: 37 HNOs were identified, and the following imaging characteristics were reviewed on CT and MRI. RESULTS: A total of 37 patients(age 41.5 ± 15.0 years old; 16 males, 21 females) were included in the study. Tumours occurred in the maxilla (16, 43.2%), mandible (8, 21.6%), skull base (6, 16.2%), calvarium (5, 13.5%), paranasal sinuses (1, 2.7%) and cervical soft tissue (1, 2.7%). 16 patients received radiotherapy for nasopharyngeal carcinoma. Three patients (8.1%) developed osteosarcomas related to a primary bone disease. 16 of the (43.2%) tumours demonstrated lytic density on CT scans, followed by 13 (35.1%) showing mixed density and 7 (18.9%) with sclerotic density. Matrix mineralization was present in 32 (86.5%). 3 out of 24 (12.5%) tumours showed lamellar periosteal reactions, 21 out of 24 (87.5%) showed spiculated periosteal reactions. 12 tumours showed low signal intensities on T1WI, with 16 having heterogeneous signal intensities. 10 tumours showed high signal intensities on T2WI, and 18 showed heterogeneous signal intensities. With contrast-enhanced images, 3 tumours showed homogeneous enhancement (2 osteoblastic and 1 giant cell-rich), 18 tumours showed heterogeneous enhancement (13 osteoblastic, 4 fibroblastic and 1 giant cell-rich), and 7 tumours showed peripheral enhancement (6 chondroblastic and 1 osteoblastic). These tumours were characterized by soft tissue masses with a diameter of 5.6 ± 1.8 cm. CONCLUSIONS: HNO is a rare condition and is commonly associated with previous radiation exposure. This study provides age, sex distribution, location, CT and MRI features of HNO.

CT and MRI features of calvarium and skull base osteosarcoma (CSBO).

OBJECTIVE: This study aims to assess the CT and MRI features of calvarium and skull base osteosarcoma (CSBO). METHODS: The CT and MRI features and pathological characteristics of 12 cases of pathologically confirmed CSBO were analyzed retrospectively. RESULTS: 12 patients (age range 9-67 years; 3 male, 9 female) were included in the study. Tumours occurred in skull base (7, 58.3%), temporal (4, 33.3%) and frontal (1, 8.3%). Among all, six patients received radiotherapy for nasopharyngeal carcinoma. According to pathology, 11 out of 12 tumours were high-grade (91.7%). On CT, all the tumours had soft tissue mass penetrated into cortical bone with invasion of surrounding soft tissue. Six tumours were shown to have lytic density and six were mixed density. Matrix mineralization was present in 10 cases (83.3%). On MRI, tumours presented as soft-tissue masses measuring 5.9 ± 2.4 (3.9-8.0) cm. Five tumours showed low signal intensities on T1 weighted imaging with seven having heterogeneous signal intensities. One showed low signal intensity on T2 weighted imaging, two showed high signal intensities and nine heterogeneous signal intensities. All the tumours showed low signal intensities on diffusion-weighted imaging. On contrast enhanced images, seven cases showed heterogeneous enhancement, three showed peripheral enhancementand and two showed homogeneous enhancement. Dural tail sign were detected in nine cases. CONCLUSION: CSBO is rare, and is commonly associated with previous radiation exposure. A presumptive diagnosis for osteosarcoma should be considered when calvarium and skull base tumours with osteoid matrix and duraltail sign are found. ADVANCES IN KNOWLEDGE: CT and MR features of CSBO have not been reported. The study helps to identify CSBO and other sarcomas.

YTHDF1 rs6090311 A>G polymorphism reduces Hepatoblastoma risk: Evidence from a seven-center case-control study.

Various factors modulate the risk of hepatoblastoma. In this study, we aimed to investigate whether single nucleotide polymorphisms (SNPs) in the YTHDF1 gene could predispose to hepatoblastoma. We used TaqMan assay to genotype two YTHDF1 SNPs (rs6011668 C>T and rs6090311 A>G) in a Chinese population composed of 313 subjects with hepatoblastoma and 1446 controls from seven hospitals. We then evaluated the associations of these two SNPs with hepatoblastoma risk using unconditional logistic regression. We found that rs6090311 G allele exhibited a significant association with decreased hepatoblastoma risk [AG vs. AA: adjusted odds ratio (OR)=0.75; 95% confidence interval (CI)=0.58-0.98, P=0.033; AG/GG vs. AA: adjusted OR=0.76, 95% CI=0.59-0.97, P=0.029]. Furthermore, the combined analysis of protective genotypes revealed that subjects carrying two protective genotypes were less likely to have hepatoblastoma than those with 0-1 protective genotypes (adjusted OR=0.75, 95% CI=0.59-0.96, P=0.022). Subjects ≥17 months of age had decreased hepatoblastoma risk, in case that they carried rs6090311 AG/GG (adjusted OR=0.63, 95% CI=0.44-0.91, P=0.012), or two protective genotypes (adjusted OR=0.63, 95% CI=0.44-0.91, P=0.012). False-positive report probability analysis validated the reliability of the significant results. Preliminary functional annotations revealed that rs6090311 G was correlated with decreased expression of its surrounding genes in the expression quantitative trait locus (eQTL) analysis. In conclusion, our results indicate that the rs6090311 A>G in the YTHDF1 gene is related to decreased hepatoblastoma risk.

[Effect of percutaneous kyphoplasty on lumbar-pelvic correlation in osteoporotic vertebral compressive fractures].

OBJECTIVE: To explore the effect of percutaneous kyphoplasty (PKP) on lumbar-pelvic correlation in osteoporotic vertebral compressive fracture (OVCF). METHODS: According to the inclusion criteria, 63 patients with primary osteoporosis between January 2012 and June 2017 were selected as the control group and 67 patients with single-segment lumbar OVCF receiving PKP and complete clinical data were included as the observation group. There was no significant difference in gender, age, and lumbar spine bone density between the two groups ( P>0.05). The visual analogue scale (VAS) score and Oswestry Disability Index (ODI) score were used to assess lumbar pain and function before operation and at 3 days after operation in the observation group; lumbar lordosis (LL), pelvic incidence (PI), pelvic tilt (PT), and sacral slope (SS) were measured in lumbar lateral X-ray films which were taken before PKP and at 1 month after PKP. The same parameters were measured in the lumbar lateral X-ray films which were taken at the time of initial diagnosis in the control group. RESULTS: All patients were followed up 3-24 months with an average of 5.8 months in the observation group. The VAS score decreased from 5.6±1.8 before PKP to 2.8±1.3 at 3 days after PKP ( t=14.082, P=0.000); ODI decreased from 50.1%±5.0% before PKP to 18.2%±1.8% ( t=47.011, P=0.000). Compared with the control group, the LL, PI, and SS decreased and the PT increased in the observation group, and only the difference in LL between the two groups was significant ( P<0.05). In the observation group, the LL and SS significantly increased ( P<0.05) and PT significantly decreased ( P<0.05) at 1 month after operation when compared with preoperative ones, and PI decreased, but the difference was not significant ( P>0.05). In the control group, LL was positively correlated with PI and SS ( P<0.05); PI was positively correlated with PT and SS ( P<0.05). In the observation group, PI was positively correlated with SS ( P<0.05) before and after PKP. CONCLUSION: OVCF patients lost the specific lumbar-pelvic correlation. PKP can restore lumbar lordosis, but it still can not restore the normal physiological fitting.

[Effect of anterior cervical discectomy and decompression with different fusion segments on sagittal spine-pelvis balance].

Objective: To explore the effect on sagittal spine-pelvis balance of different fusion segments in anterior cervical discectomy and fusion (ACDF). Methods: The clinical data of 326 patients with cervical spondylotic myelopathy, treated by ACDF between January 2010 and December 2016, was retrospectively analysed. There were 175 males and 151 females with an average age of 56 years (range, 34-81 years). Fusion segments included single segment in 69 cases, double segments in 85 cases, three segments in 90 cases, and four segments in 82 cases. Full spine anterolateral X-ray films were performed before operationand at 12 months after operation. The spine-pelvis parameters of fusion segments were measured and compared. The parameters included C 0-2 Cobb angle, C 2-7 Cobb angle, C 2-7 sagittal vertical axis (C 2-7 SVA), T 1 slope (T 1S), thoracic inlet angle (TIA), thoracic kyphosis (TK), lumbar lordosis (LL), pelvic incidence (PI), sacral slope (SS), C 7 sagittal vertical axis (C 7 SVA), T 1 pelvic angle (TPA). The Japanese Orthopaedic Association (JOA) score of cervical spine and visual analogue scale (VAS) scores of pain of cervical spine and upper extremity were compared before operation and at 12 months after operation. Pearson correlation analysis was performed on LL, PI, SS, C 7 SVA, and TPA before and after operation to evaluate the changes of spine-pelvis fitting relationship after ACDF. Results: All 326 patients were followed up 12-32 months (mean, 18.5 months). During the follow-up period, internal fixator was in place, and no spinal cord nerve or peripheral soft tissue injury was found. JOA scores and cervical VAS scores improved significantly at 12 months after operation ( P<0.05), no significant difference was found in VAS scores of upper extremity when compared with preoperative scores ( P>0.05). The preoperative cervical VAS scores and the postoperative JOA scores at 12 months had significant differences between groups ( P<0.05). At 12 months after operation, there was no significant difference in sagittal spine-pelvis parameters in the single segment group compared with preoperative ones ( P>0.05); but the C 0-2 Cobb angle, C 2-7 Cobb angle, C 2-7 SVA, T 1S, TIA, C 7 SVA, and TPA in the double segments, three segments, and four segments groups were significant larger than preoperative ones ( P<0.05). The C 0-2 Cobb angle, C 2-7 Cobb angle, T 1S, C 7 SVA, and TPA among 4 groups had significant differences before operation and at 12 months after operation ( P<0.05). At 12 months after operation, the changes of C 7 SVA and TPA in the double segments, three segments, and four segments groups were significantly larger than those in the single segment group ( P<0.05). PI had positive correlations with LL and SS before and after operation in 4 groups ( P<0.05). Conclusion: Normal fitting relationship between lumbar spine and pelvis in physiological state also exists in patients with cervical spondylotic myelopathy, and ACDF can not change this specific relationship. In patients with cervical spondylotic myelopathy, the sagittal spine-pelvis sequence do not change after ACDF single-level fusion, while the sagittal spine-pelvis balance change after double-level and multi-level fusion.

A Crank-Nicolson collocation spectral method for the two-dimensional telegraph equations.

In this paper, we mainly focus to study the Crank-Nicolson collocation spectral method for two-dimensional (2D) telegraph equations. For this purpose, we first establish a Crank-Nicolson collocation spectral model based on the Chebyshev polynomials for the 2D telegraph equations. We then discuss the existence, uniqueness, stability, and convergence of the Crank-Nicolson collocation spectral numerical solutions. Finally, we use two sets of numerical examples to verify the validity of theoretical analysis. This implies that the Crank-Nicolson collocation spectral model is very effective for solving the 2D telegraph equations.