Response of vertebral fractures to treatment with denosumab in a patient with postpartum osteoporosis: a case report and literature review.

Postpartum osteoporosis (PO) is a rare condition characterized by low bone mineral density (BMD) and an increased risk of vertebral fragility fracture. We encountered a 34-year-old woman who developed back pain 1 week after delivery. Magnetic resonance imaging of the lumbar spine revealed three vertebral compression fractures. Pretreatment BMD evaluation by dual-energy X-ray absorptiometry revealed a low T-score and Z-score (-2.0 and -2.0, respectively; BMD, 0.876 g/cm2) in the affected region of the spine. The patient was diagnosed with PO and treated with subcutaneous injection of denosumab 60 mg (Prolia; Amgen, Inc., Thousand Oaks, CA, USA) every 6 months. After two treatments, the BMD had significantly increased and the back pain was improved; the patient therefore decided to terminate the treatment. Two months later, her back pain worsened and BMD decreased as measured by dual-energy X-ray absorptiometry examination of the lumbar spine. Therefore, the patient resumed treatment with denosumab, and the BMD of the lumbar spine increased after another two treatments. Therefore, we consider denosumab to be promising in the management of PO with respect to increased BMD and decreased pain.

A CT-Based Deep Learning Radiomics Nomogram to Predict Histological Grades of Head and Neck Squamous Cell Carcinoma.

RATIONALE AND OBJECTIVES: Accurate pretreatment assessment of histological differentiation grade of head and neck squamous cell carcinoma (HNSCC) is crucial for prognosis evaluation. This study aimed to construct and validate a contrast-enhanced computed tomography (CECT)-based deep learning radiomics nomogram (DLRN) to predict histological differentiation grades of HNSCC. MATERIALS AND METHODS: A total of 204 patients with HNSCC who underwent CECT scans were enrolled in this study. The participants recruited from two hospitals were split into a training set (n=124, 74 well/moderately differentiated and 50 poorly differentiated) of patients from one hospital and an external test set of patients from the other hospital (n=80, 49 well/moderately differentiated and 31 poorly differentiated). CECT-based manually-extracted radiomics (MER) features and deep learning (DL) features were extracted and selected. The selected MER features and DL features were then combined to construct a DLRN via multivariate logistic regression. The predictive performance of the DLRN was assessed using ROCs and decision curve analysis (DCA). RESULTS: Three MER features and seven DL features were finally selected. The DLRN incorporating the selected MER and DL features showed good predictive value for the histological differentiation grades of HNSCC (well/moderately differentiated vs. poorly differentiated) in both the training (AUC, 0.878) and test (AUC, 0.822) sets. DCA demonstrated that the DLRN was clinically useful for predicting histological differentiation grades of HNSCC. CONCLUSION: A CECT-based DLRN was constructed to predict histological differentiation grades of HNSCC. The DLRN showed good predictive efficacy and might be useful for prognostic evaluation of patients with HNSCC.

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.

Effects of corticospinal tract integrity on upper limb motor function recovery in stroke patients treated with repetitive transcranial magnetic stimulation.

BACKGROUND: The bimodal balance-recovery model predicts that corticospinal tract (CST) integrity in the affected hemisphere influences the partterns of brain recovery after stroke. Repetitive transcranial magnetic stimulation (rTMS) has been used to promote functional recovery of stroke patients by modulating motor cortical excitability and inducing reorganization of neural networks. This study aimed to explore how to optimize the efficiency of repetitive transcranial magnetic stimulation to promote upper limb functional recovery after stroke according to bimodal balance-recovery model. METHODS: 60 patients who met the inclusion criteria were enrolled to high CST integrity group (n = 30) or low CST integrity group (n = 30), and further assigned randomly to receive high-frequency rTMS (HF-rTMS), low-frequency rTMS (LF-rTMS) or sham rTMS in addition to routine rehabilitation, with 10 patients in each group. Outcome measures included Fugl-Meyer scale for upper extremity (FMA-UE), Wolf Motor Function (WMFT) scale and Modified Barthel Index (MBI) scale which were evaluated at baseline and after 21 days of treatment. RESULTS: For patients with high CST integrity, the LF group achieved higher FMA-UE, WMFT and MBI scores improvements after treatment when compared to the HF group and sham group. For patients with low CST integrity, after 21 days treatment, only the HF group showed significant improvements in FMA-UE and WMFT scores. For MBI assessment, the HF group revealed significantly better improvements than the LF group and sham group. CONCLUSIONS: For stroke patients with high CST integrity, low-frequency rTMS is superior to high-frequency rTMS in promoting upper limb motor function recovery. However, only high-frequency rTMS can improve upper limb motor function of stroke patients with low CST integrity.

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.

MRI-Based radiomics nomogram for differentiation of benign and malignant lesions of the parotid gland.

OBJECTIVES: Preoperative differentiation between benign parotid gland tumors (BPGT) and malignant parotid gland tumors (MPGT) is important for treatment decisions. The purpose of this study was to develop and validate an MRI-based radiomics nomogram for the preoperative differentiation of BPGT from MPGT. METHODS: A total of 115 patients (80 in training set and 35 in external validation set) with BPGT (n = 60) or MPGT (n = 55) were enrolled. Radiomics features were extracted from T1-weighted and fat-saturated T2-weighted images. A radiomics signature model and a radiomics score (Rad-score) were constructed and calculated. A clinical-factors model was built based on demographics and MRI findings. A radiomics nomogram model combining the Rad-score and independent clinical factors was constructed using multivariate logistic regression analysis. The diagnostic performance of the three models was evaluated and validated using ROC curves on the training and validation datasets. RESULTS: Seventeen features from MR images were used to build the radiomics signature. The radiomics nomogram incorporating the clinical factors and radiomics signature had an AUC value of 0.952 in the training set and 0.938 in the validation set. Decision curve analysis showed that the nomogram outperformed the clinical-factors model in terms of clinical usefulness. CONCLUSIONS: The above-described radiomics nomogram performed well for differentiating BPGT from MPGT, and may help in the clinical decision-making process. KEY POINTS: • Differential diagnosis between BPGT and MPGT is rather difficult by conventional imaging modalities. • A radiomics nomogram integrated with the radiomics signature, clinical data, and MRI features facilitates differentiation of BPGT from MPGT with improved diagnostic efficacy.

Significant association between long non-coding RNA HOTAIR polymorphisms and cancer susceptibility: a meta-analysis.

HOTAIR, a well-known long non-coding RNA, is involved in carcinogenesis and progression of multiple cancers. Molecular epidemiological studies suggest that HOTAIR polymorphisms may be associated with cancer susceptibility, but the results remain controversial. To derive a more precise evaluation, we performed a meta-analysis focused on the associations between HOTAIR polymorphisms and cancer risk for the first time. PubMed, Embase, China National Knowledge Infrastructure, and Wanfang databases were searched. Odds ratios (ORs) with 95% confidence interval (CI) were applied to assess the association between HOTAIR rs920778 C>T, rs4759314 A>G, rs7958904 G>C, and rs1899663 G>T polymorphisms and cancer susceptibility. Analyses were conducted to detect heterogeneity, sensitivity, and publication bias in order to measure the robustness of our findings. Overall, 13 related studies involving 7,151 patients and 8,740 control samples were analyzed. Significant associations between the HOTAIR rs920778 polymorphism and cancer risk were observed (T vs C: OR =1.33, 95% CI =1.17-1.53; TT vs TC + CC: OR =1.55, 95% CI =1.21-2.00; TC + TT vs CC: OR =1.33, 95% CI =1.11-1.59; TT vs CC: OR =2.02, 95% CI =1.31-3.10) in the total population, as well as in subgroup analyses. For rs4759314 A>G polymorphism, a similarly increased risk was found in the gastric cancer group. However, significant decreases in cancer risk were observed both in the overall population and colorectal cancer group for rs7958904 G>C polymorphism. In addition, no significant association was detected between rs1899663 G>T polymorphism and cancer susceptibility. In conclusion, our meta-analyses suggest that HOTAIR polymorphisms may be associated with the risk of cancer development.

GL-1196 Suppresses the Proliferation and Invasion of Gastric Cancer Cells via Targeting PAK4 and Inhibiting PAK4-Mediated Signaling Pathways.

Gastric cancer, which is the most common malignant gastrointestinal tumor, has jumped to the third leading cause of cancer-related mortality worldwide. It is of great importance to identify novel and potent drugs for gastric cancer treatment. P21-activated kinase 4 (PAK4) has emerged as an attractive target for the development of anticancer drugs in consideration of its vital functions in tumorigenesis and progression. In this paper, we reported that GL-1196, as a small molecular compound, effectively suppressed the proliferation of human gastric cancer cells through downregulation of PAK4/c-Src/EGFR/cyclinD1 pathway and CDK4/6 expression. Moreover, GL-1196 prominently inhibited the invasion of human gastric cancer cells in parallel with blockage of the PAK4/LIMK1/cofilin pathway. Interestingly, GL-1196 also inhibited the formation of filopodia and induced cell elongation in SGC7901 and BGC823 cells. Taken together, these results provided novel insights into the potential therapeutic strategy for gastric cancer.