Imaging of supra-thoracic tuberculosis.

Tuberculosis (TB) typically affects the lungs, but may involve many extra-pulmonary sites; with the latter especially prone in patients with human immunodeficiency virus infection. The clinical features of extra-pulmonary TB are often non-specific, mimicking many different disease entities. Application of the most appropriate imaging modality and knowing the imaging findings with clinical context awareness help initiation of further investigations, diagnosis and early treatment. This pictorial essay highlights the imaging spectrum of extra-pulmonary TB affecting the supra-thoracic region, i.e. brain, neck, and ear, nose and throat.

Natural history and treatment outcome of radiotherapy for Kimura's disease.

BACKGROUND: Kimura's disease is a rare inflammatory disease that usually appears in head and neck region. We reported natural history of the disease and treatment outcome of radiotherapy (RT) in Chiang Mai University Hospital. METHODS: A retrospective review was performed for all Kimura's disease patients treated with radiotherapy at our center between 2002 and 2017. RESULTS: A total of 20 patients with Kimura's disease were reviewed. There were 14 men and 6 women. All patients presented with the mass in head and neck region. Eleven patients were treated with a definitive intent with RT, 9 patients were treated with RT after recurrence from other modalities. All patients were treated with local external beam RT with 2 Gy per fraction to a median total dose of 30 Gy (range 30-40). The median follow-up time was 4 years (range 1-16.5 years). One patient died from HIV opportunistic infection after 1.5 year of radiation with complete response of Kimura's disease. Most of the patients responded to radiotherapy and controlled the disease at the time of analysis. Two patients had multiple recurrences at new areas outside radiotherapy field. Skin toxicity grade 1 was the most common late side effect which was found in 8 (44%) patients. We did not find severe late toxicity or second malignancy in this patient cohort. CONCLUSION: : Good local control of Kimura's disease can be achieved, with a radiation dose of 30-40 Gy, with insignificant late toxicities. We suggest that radiotherapy should be one of the treatments of choice for Kimura's disease both in primary or recurrence setting.

Stage-Specific Survival Rate of Breast Cancer Patients in Northern Thailand in Accordance with Two Different Staging Systems.

Objective: This study was attempted to investigate overall survival by stage at diagnosis in female breast cancer patients in Northern Thailand by using 2 different staging systems; namely, American Joint Committee on Cancer (AJCC) Tumor (T), Nodal (N) and Metastatic (M) staging system and Surveillance Epidemiology and End Results (SEER) summary staging system. Methods: We studies female breast cancer patients whose data were registered in Chiang Mai cancer registries between January 2006 and December 2015. Data were recorded in SEER summary staging system. The TNM AJCC staging was searched in the medical records. Results: A total of 3,873 female breast cancer patients were diagnosed from 2006-2015. All data sets were recorded in SEER summary stage 2000. Early stage was the most prevalent stage at the time of diagnosis (58%), followed by loco-regional advanced stage (32%), and metastatic breast cancer (10%). The 5-year overall survival rate of early, loco-regional advanced, and metastatic stages were 85.3%, 66.4%, and 26.2%, respectively. After examining the medical records, we excluded patients who had no data on T, N, and M in their records. Finally, only 3,251 patients were analyzed for AJCC stage-specific survival. The 5-year overall survival rate in stages I, II, III, and IV were 94.4%, 85.0%, 56.6%, and 28.3%, respectively. Conclusion: Comparing to more stable economic countries, the 5-year overall survival rate for a specific stage of breast cancer in Northern Thailand was slightly lower in early stage and stage I-II in accordance with AJCC, but much lower in loco-regional stage and stage III with respect to AJCC. Nevertheless, it was similar in metastatic stage and stage IV according to AJCC.

Optimized multi-level elongated quinary patterns for the assessment of thyroid nodules in ultrasound images.

Ultrasound imaging is one of the most common visualizing tools used by radiologists to identify the location of thyroid nodules. However, visual assessment of nodules is difficult and often affected by inter- and intra-observer variabilities. Thus, a computer-aided diagnosis (CAD) system can be helpful to cross-verify the severity of nodules. This paper proposes a new CAD system to characterize thyroid nodules using optimized multi-level elongated quinary patterns. In this study, higher order spectral (HOS) entropy features extracted from these patterns appropriately distinguished benign and malignant nodules under particle swarm optimization (PSO) and support vector machine (SVM) frameworks. Our CAD algorithm achieved a maximum accuracy of 97.71% and 97.01% in private and public datasets respectively. The evaluation of this CAD system on both private and public datasets confirmed its effectiveness as a secondary tool in assisting radiological findings.

Fusion of spatial gray level dependency and fractal texture features for the characterization of thyroid lesions.

Thyroid is a small gland situated at the anterior side of the neck and one of the largest glands of the endocrine system. The abrupt cell growth or malignancy in the thyroid gland may cause thyroid cancer. Ultrasound images distinctly represent benign and malignant lesions, but accuracy may be poor due to subjective interpretation. Computer Aided Diagnosis (CAD) can minimize the errors created due to subjective interpretation and assists to make fast accurate diagnosis. In this work, fusion of Spatial Gray Level Dependence Features (SGLDF) and fractal textures are used to decipher the intrinsic structure of benign and malignant thyroid lesions. These features are subjected to graph based Marginal Fisher Analysis (MFA) to reduce the number of features. The reduced features are subjected to various ranking methods and classifiers. We have achieved an average accuracy, sensitivity and specificity of 97.52%, 90.32% and 98.57% respectively using Support Vector Machine (SVM) classifier. The achieved maximum Area Under Curve (AUC) is 0.9445. Finally, Thyroid Clinical Risk Index (TCRI) a single number is developed using two MFA features to discriminate the two classes. This prototype system is ready to be tested with huge diverse database.