OBJECTIVE: The aim of this multicenter, matched-pair study was to compare the outcomes of stereotactic radiosurgery (SRS) and conventional external radiation therapy (RT) when used as a primary treatment in spine metastasis from hepatocellular carcinoma (HCC). METHODS: From 2005 to 2012, 28 patients underwent SRS as the primary treatment in spine metastasis from HCC. Based on sex, age, number of spine metastasis, Child-Pugh classification, interval from original tumor to spine metastasis, and year of treatment, 28 patients who underwent RT were paired. Outcomes of interest were pain relief, progression free survival, toxicities, and further treatment. RESULTS: The perioperative visual analog scale (VAS) decrease was larger in SRS group than in RT group, but the difference was not significant (3.7 vs. 2.8, p=0.13). When pain medication was adjusted, the number of patients with complete (n=6 vs.3) or partial (n=12 vs.13) relief was larger in SRS group than in RT group; however, the difference was not significant (p=0.83). There was no significant difference in progression free survival (p=0.48). In SRS group, 32.1% of patients had 1 or more toxicities whereas the percentage in RT group was 63.0%, a significant difference (p=0.04). Six SRS patients and 7 RT patients received further intervention at the treated segment. CONCLUSION: Clinical and radiological outcome were not significantly different between the two treatments. Toxicities, however, were more prevalent in the RT group.
Carcinoma, Hepatocellular* ; Classification ; Disease-Free Survival ; Humans ; Neoplasm Metastasis* ; Radiosurgery* ; Spine* ; Visual Analog Scale

The purpose of this study was to investigate the therapeutic effects of DA-9801, an optimized extract of Dioscorea species, on diabetic peripheral neuropathy in a type 2 diabetic animal model. In this study, db/db mice were treated with DA-9801 (30 and 100 mg/kg, daily, p.o.) for 12 weeks. DA-9801 reduced the blood glucose levels and increased the withdrawal latencies in hot plate tests. Moreover, it prevented nerve damage based on increased nerve conduction velocity and ultrastructural changes. Decrease of nerve growth factor (NGF) may have a detrimental effect on diabetic neuropathy. We previously reported NGF regulatory properties of the Dioscorea genus. In this study, DA-9801 induced NGF production in rat primary astrocytes. In addition, it increased NGF levels in the sciatic nerve and the plasma of type 2 diabetic animals. DA-9801 also increased neurite outgrowth and mRNA expression of Tieg1/Klf10, an NGF target gene, in PC12 cells. These results demonstrated the attenuation of diabetic peripheral neuropathy by oral treatment with DA-9801 via NGF regulation. DA-9801 is currently being evaluated in a phase II clinical study.
Animals ; Astrocytes ; Blood Glucose ; Diabetes Mellitus, Type 2 ; Diabetic Neuropathies ; Dioscorea* ; Mice* ; Models, Animal ; Nerve Growth Factor ; Neural Conduction ; Neurites ; PC12 Cells ; Peripheral Nervous System Diseases* ; Plasma ; Rats ; RNA, Messenger ; Sciatic Nerve

BACKGROUND AND OBJECTIVES: To evaluate and compare the diagnostic performances of grayscale ultrasound (US) and quantitative parameters obtained from texture analysis of grayscale US and elastography images in evaluating patients with diffuse thyroid disease (DTD). MATERIALS AND METHODS: From September to December 2012, 113 patients (mean age, 43.4±10.7 years) who had undergone preoperative staging US and elastography were included in this study. Assessment of the thyroid parenchyma for the diagnosis of DTD was made if US features suggestive of DTD were present. Nine histogram parameters were obtained from the grayscale US and elastography images, from which ‘grayscale index’ and ‘elastography index’ were calculated. Diagnostic performances of grayscale US, texture analysis using grayscale US and elastography were calculated and compared. RESULTS: Of the 113 patients, 85 (75.2%) patients were negative for DTD and 28 (24.8%) were positive for DTD on pathology. The presence of US features suggestive of DTD showed significantly higher rates of DTD on pathology, 60.7% to 8.2% (p<0.001). Specificity, accuracy, and positive predictive value was highest in US features, 91.8%, 84.1%, and 87.6%, respectively (all ps<0.05). Grayscale index showed higher sensitivity and negative predictive value (NPV) than US features. All diagnostic performances were higher for grayscale index than the elastography index. Area under the curve of US features was the highest, 0.762, but without significant differences to grayscale index or mean of elastography (all ps>0.05). CONCLUSION: Diagnostic performances were the highest for grayscale US features in diagnosis of DTD. Grayscale index may be used as a complementary tool to US features for improving sensitivity and NPV.
Diagnosis ; Elasticity Imaging Techniques* ; Humans ; Pathology ; Sensitivity and Specificity ; Thyroid Diseases* ; Thyroid Gland* ; Ultrasonography

Purpose: This study was conducted to evaluate the diagnostic performance of machine learning in differentiating follicular adenoma from carcinoma using preoperative ultrasonography (US). Methods: In this retrospective study, preoperative US images of 348 nodules from 340 patients were collected from two tertiary referral hospitals. Two experienced radiologists independently reviewed each image and categorized the nodules according to the 2015 American Thyroid Association guideline. Categorization of a nodule as highly suspicious was considered a positive diagnosis for malignancy. The nodules were manually segmented, and 96 radiomic features were extracted from each region of interest. Ten significant features were selected and used as final input variables in our in-house developed classifier models based on an artificial neural network (ANN) and support vector machine (SVM). The diagnostic performance of radiologists and both classifier models was calculated and compared. Results: In total, 252 nodules from 245 patients were confirmed as follicular adenoma and 96 nodules from 95 patients were diagnosed as follicular carcinoma. As measures of diagnostic performance, the average sensitivity, specificity, and accuracy of the two experienced radiologists in discriminating follicular adenoma from carcinoma on preoperative US images were 24.0%, 84.0%, and 64.8%, respectively. The sensitivity, specificity, and accuracy of the ANN and SVM-based models were 32.3%, 90.1%, and 74.1% and 41.7%, 79.4%, and 69.0%, respectively. The kappa value of the two radiologists was 0.076, corresponding to slight agreement. Conclusion Machine learning-based classifier models may aid in discriminating follicular adenoma from carcinoma using preoperative US.