Two lymphoma histotypes and papillary thyroid carcinoma coexisting on Hashimoto ground: a case report and review of the literature.

BACKGROUND: Papillary carcinoma is the most frequent type of thyroid carcinoma, while primary thyroid lymphoma is uncommon disease. The coexistence of these entities has already been described, and the common risk factor is considered Hashimoto thyroiditis. The two most frequent histotypes of primary thyroid lymphoma are diffuse large B-cell and mucosa-associated lymphoid tissue lymphoma, but the coexistence of both with papillary carcinoma is rarely reported. METHODS: We present a case of a previously healthy 57-years old male with rapidly growing lump on the right side of the neck. Ultrasonography revealed nodules in both thyroid lobes. Fine needle aspiration cytology and pertechnetate scintigraphy were performed. Due to the Bethesda T-5 in the "cold" nodule of the right lobe, surgery with histopathological and immunohistochemistry analysis was indicated. RESULTS: Histopathological and immunohistochemistry methods confirmed concomitant malignancies in the thyroid gland: diffuse large B-cell lymphoma and papillary carcinoma in the right, and mucosa-associated lymphoid tissue lymphoma in the left lobe with Hashimoto thyroiditis in the remaining tissue. Patient underwent therapy procedures and was without signs of local recurrence or metastatic spread on subsequent follow-up. CONCLUSIONS: Sudden appearance of the neck mass in patients with Hashimoto thyroiditis should raise suspicion on primary thyroid lymphoma and be promptly taken in the diagnostic workup, including fine needle aspiration cytology. Pathology with immunohistochemistry is crucial for further clinical decision making. Since the standardized protocol in management of these complex patients is missing, personal approach and close collaboration between cytologist, pathologist, surgeon, haematologist and nuclear medicine specialist is essential.

Application of non-linear automatic optimization techniques for calibration of HSPF.

Development of TMDLs (total maximum daily loads) is often facilitated by using the software system BASINS (Better Assessment Science Integrating point and Nonpoint Sources). One of the key elements of BASINS is the watershed model HSPF (Hydrological Simulation Program Fortran) developed by USEPA. Calibration of HSPF is a very tedious and time consuming task, more than 100 parameters are involved in the calibration process. In the current research, three non-linear automatic optimization techniques are applied and compared, as well an efficient way to calibrate HSPF is suggested. Parameter optimization using local and global optimization techniques for the watershed model is discussed. Approaches to automatic calibration of HSPF using the nonlinear parameter estimator PEST (Parameter Estimation Tool) with its Gauss-Marquardt-Levenberg (GML) method, Random multiple Search Method (RSM), and Shuffled Complex Evolution method developed at the University of Arizona (SCE-UA) are presented. Sensitivity analysis was conducted and the most and the least sensitive parameters were identified. It was noted that sensitivity depends on number of adjustable parameters. As more parameters were optimized simultaneously--a wider range of parameter values can maintain the model in the calibrated state. Impact of GML, RSM, and SCE-UA variables on ability to find the global minimum of the objective function (OF) was studied and the best variables are suggested. All three methods proved to be more efficient than manual HSPF calibration. Optimization results obtained by these methods are very similar, although in most cases RSM outperforms GML and SCE-UA outperforms RSM. GML is a very fast method, it can perform as well as SCE-UA when the variables are properly adjusted, initial guess is good and insensitive parameters are eliminated from the optimization process. SCE-UA is very robust and convenient to use. Logical definition of key variables in most cases leads to the global minimum.