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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.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).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.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.

To investigate the potential correlation between multifidus muscles (MM) fatty atrophy and MR signs of lumbar spine degeneration in patients with low back pain (LBP). Following IRB approval, lumbar spine MRI of 518 patients (278 females and 240 males; age, 10–92 years) with LBP were retrospectively reviewed by two experienced musculoskeletal radiologists. MM fatty atrophy was graded at L4–5 and L5–S1 levels per modified Goutallier classification. Disc degeneration, herniation was graded according to Pfirrmann classification, and facet joint osteoarthritis was graded according to Fujiwara classification. Gender, age and body mass index (BMI) were recorded as well. Mann–Whitney U test was used to determine whether there was a difference in fatty atrophy between woman and man. Kendall’s tau-b coefficient and ordinal multiple logistic regression were used to evaluate relationship between MM fatty atrophy and signs of lumbar spine degeneration. Intra-observer agreement was tested using weighted Kappa. There was significant difference among the grades of fatty atrophy between woman and man. Both at L4–L5 and L5–S1 levels, correlation between MM fatty atrophy with age, disc degeneration, facet joint osteoarthritis was significant (p

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.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.MRI-PDFF measurements indicated strong linearity (RMRI-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.

Background: Aggressive vertebral hemangiomas (VHs) are uncommon in adults. Although most have typical radiographic features, some present with atypical findings, which makes their diagnosis difficult. Aggressive VHs have a high likelihood of recurrence even after resection.Case presentation: A 52-year-old woman presented with a 3-month history of right lower extremity pain and numbness. On physical examination, the sacrum was tender, her mobility was limited, and right plantar flexion strength was 4/5 on manual muscle testing. Computed tomography (CT) revealed osteolytic bony destruction from S1 to S2. Magnetic resonance imaging (MRI) showed a sacral mass invading the S1 vertebral endplate and compressing the dural sac; the mass was heterogeneously hypointense on T1-weighted imaging, hyperintense on T2-weighted imaging, and heterogeneously enhanced. Six months after surgical resection of the mass, the patient presented with back pain and bilateral extremity numbness. MRI showed lesion recurrence with thecal sac compression.Conclusions: Aggressive VHs may exhibit atypical radiological findings that include osteolytic vertebral bony destruction, spinal canal extension, heterogeneous signal intensity on T1- and T2-weighted imaging, and heterogeneous enhancement. These can make accurate preoperative diagnosis difficult; biopsy may be necessary. Surgical decompression and resection are recommended for aggressive VHs. Nonetheless, recurrence may still occur despite resection.

AIM To determine whether quantitative parameters derived from conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) correlate with the Ki67 proliferation status in musculoskeletal tumours. MATERIALS AND METHODS Twenty-eight patients with musculoskeletal tumours diagnosed via surgical specimen histological analysis who underwent standard DWI, IVIM, and DCE were reviewed retrospectively. The mean standard DWI (apparent diffusion coefficient [ADC]), IVIM (pure diffusion coefficient [D], pseudo-diffusion coefficient [D∗] and perfusion fraction [ƒ]), and DCE (volume transfer constant [Ktrans], rate constant [Kep], and extravascular extracellular volume fraction [Ve]) parameters were measured and correlated with the Ki67 index. The Ki67 value was categorised as high (>20%) or low (≤20%). RESULTS The ADC and D values correlated negatively with the Ki67 index (r=-0.711∼-0.699, p

Background Neoadjuvant radiotherapy plays a vital role in the treatment of malignant bone tumors, and non-invasive imaging methods are needed to evaluate the response to treatment. Purpose To assess the value of diffusion kurtosis imaging (DKI) for monitoring early response to radiotherapy in malignant bone tumors. Material and Methods Treatment response was evaluated in a rabbit VX2 bone tumor model (n = 35) using magnetic resonance imaging (MRI), DKI, and histopathologic examinations. Subjects were divided into three groups: pre-treatment, post-treatment, and control groups. The post-treatment group was subclassified into good response and poor response groups according to the results of histopathologic examination. Apparent diffusion coefficient (ADC) and DKI parameters (mean diffusion coefficient [MD] and mean kurtosis [MK]) were recorded. The relationship between ADC, DKI parameters, and histopathologic changes after radiotherapy was determined using Pearson’s correlation coefficient. The diagnostic performance of these parameters was assessed using receiver operating characteristic analysis. Results MD in the good response group was higher after treatment than before treatment ( P Conclusion The correlations between MD, tumor cell density, and apoptosis suggest that MD could be useful for assessing the early response to radiotherapy in rabbit VX2 malignant bone tumors.

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.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.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.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.

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.

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. 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. 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. The above-described radiomics nomogram performed well for differentiating BPGT from MPGT, and may help in the clinical decision-making process. • 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.

// Xu Liu 1 , Lianghao You 2 , Ruizhi Zhou 2 , Jian Zhang 2 1 Department of Neurology, First Affiliated Hospital of China Medical University, Liaoning, Shenyang 110001, China 2 Department of Cell Biology, Key Laboratory of Cell Biology, Ministry of Public Health, China, Key Laboratory of Medical Cell Biology, Ministry of Education, China Medical University, Shenyang 110122, China Correspondence to: Jian Zhang, email: jzhang@cmu.edu.cn Keywords: microRNA, polymorphism, coronary heart disease, meta-analysis, Pathology Section Received: October 07, 2016 Accepted: November 30, 2016 Published: December 27, 2016 ABSTRACT Molecular epidemiological studies suggest that microRNA polymorphisms may be associated with an increased risk of coronary heart disease (CHD). However, the results of these studies were inconsistent and inconclusive. To derive a more precise evaluation, we performed a meta-analysis focused on the associations between microRNA polymorphisms and CHD risk. PubMed, Embase, CNKI and Wanfang databases were searched. Odds ratios (ORs) with 95% confidence intervals (CIs) were applied to assess the association between microRNA-146a rs2910164, microRNA-196a2 rs11614913, microRNA-499 rs3746444 and microRNA-149 rs71428439 polymorphisms and CHD susceptibility. Heterogeneity, publication bias and sensitivity analysis were conducted to measure the robustness of our findings. A total of thirteen related studies involving 8,120 patients and 8,364 controls were analyzed. Significant associations between microRNA-146a rs2910164 polymorphism and CHD risk were observed in the total population, as well as in subgroup analysis. For microRNA-196a2 rs11614913 and microRNA-499 rs3746444, similarly increased risks were also found. In addition, no significant association was detected between microRNA-149 rs71428439 polymorphism and CHD risk. In conclusion, our meta-analyses suggest that microRNA polymorphisms may be associated with increased risk of CHD development.

Jian Zhang,1 Xu Liu,2 Liang-Hao You,1 Rui-Zhi Zhou1 1Department of Cell Biology, Key Laboratory of Cell Biology, Ministry of Public Health and Key Laboratory of Medical Cell Biology, Ministry of Education,ChinaMedicalUniversity, Shenyang,People’s Republic of China; 2Department of Neurology, First Affiliated Hospital of China Medical University, Shenyang, People’s Republic of China Abstract: 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. Keywords: HOTAIR, polymorphism, cancer susceptibility