Aim: Thyroid incidentaloma is defined as an unsuspected, asymptomatic thyroid lesion that is discovered on an imaging study. The purpose of this study is to determine incidentally identified thyroid lesions by FDG-PET/CT in cancer patients by virtue of preoperative staging and to pay attention how should be the management of these patients with thyroid lesion.
Methods: From January 2011 to January 2013, 2654 patients underwent FDG-PET/CT in our institution. Among them, 34 patients had thyroid incidentaloma. All patients underwent ultrasonographic (US) examination. If there is a nodul, fine needle aspirations (FNA) were performed to these patients. We did not perform FNA to patients who had diffuse thyroid uptake. Patients were divided into two groups; malign and non-malign patients according to FNA histo-pathologic results. Group 1 (N.=11) diagnosed malignancy in histo-pathologic evaluation, group 2 (N.=23) could not diagnosed malignancy in histo-pathologic, clinic and radiologic evaluation. These two groups were compared statistically in terms of SUV max levels that reached in PET examinations.
Results: Incidentally thyroid lesions were found in 34 patients in the course of FDG-PET/CT examination (25 females and 9 males), mean age 57.7 years. Nodular goitre in 12 patients, hyperthyroidism in 2 patients, sub-clinic hyperthyroidism in 3 patients and hashimoto thyroiditis in 6 patients were diagnosed in non-malignancy group (Group-2). Group 1 included 11 patients with incidentally diagnosed thyroid malignancy. 11 patients malignancy diagnoses were verified by FNA and 9 of them were operated. In PET evaluation thyroid up-take was diffuse in 9 patients, at left lob in 12 patients and at right lop in 13 patients. When we compared the groups according to SUV max levels; we found that malignant thyroid lesions had a significantly higher (P<0.001) SUVmax than benign thyroid lesions. A cut off SUVmax value (>6.2) was found in the study.
Conclusion: The incidental finding of focal thyroid uptake on FDG-PET scanning has an elevated malignancy risk from other thyroid nodules. According to our knowledge diagnose, treatment and follow-up of these patients should be in multidiscipliner approach. Oncology, endocrinology, endocrine surgeon, interventional radiology, pathology and psychiatry should be gathered in multidiscipliner team. For these reason these patients need more careful evaluation.
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Clinics (Sao Paulo)
January 2025
Department of Hematology, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, PR China. Electronic address:
Background: The common drugs used for the treatment of Newly Diagnosed Multiple Myeloma (NDMM) include bortezomib and lenalidomide, but the adverse effects of lenalidomide cannot be ignored, especially when it is used in the initial therapy.
Methods: This retrospective study evaluated the efficacy and safety of a modified DVD regimen (pegylated liposomal doxorubicin, bortezomib, and dexamethasone) followed by lenalidomide in the treatment of NDMM. A total of 40 NDMM patients were treated with a reduced dose of pegylated liposomal doxorubicin (20 mg/m) on day 1, subcutaneous bortezomib (1.
Clinics (Sao Paulo)
January 2025
Department of Otolaryngology and Head and Neck Surgery, The First Affiliated Hospital of Bengbu Medical College, Anhui Province, China. Electronic address:
Objective: TRIB3 has been confirmed to participate in and regulate biological metabolic activities in head and neck tumors such as nasopharyngeal carcinoma and oropharyngeal carcinoma, so the purpose of this study was to explore whether there is a correlation between TRIB3 and Laryngeal Squamous Cell Carcinoma (LSCC) and to preliminarily explore the biological characteristics of TRIB3 in LSCC.
Methods: TRIB3 expression in the LSCC was analyzed based on The Cancer Genome Atlas (TCGA) database. CCK-8 assay, Colony Formation Assay, wound healing assay, and Transwell assay were performed to investigate the roles of TRIB3 in the proliferation, invasion and metastasis of LSCC.
Ann Intern Med
January 2025
Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California (A.B., K.J.C., A.A.K.).
Background: Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG) differ in their effects on body weight and risk for reoperation. However, it is unclear whether long-term health expenditures differ by procedure type in patients with diabetes.
Objective: To compare health expenditures 3 years before and 5.
Ann Intern Med
January 2025
Renal-Electrolyte Division, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (M.C.-P., R.B.M., C.M.P.).
Background: Prior studies indicate that 1% to 4% of Epstein-Barr virus (EBV)-seronegative recipients of EBV-seropositive donor (EBV D+/R-) kidneys develop posttransplant lymphoproliferative disorder (PTLD). However, these estimates are based on limited data that lack granularity.
Objective: To determine the associations between pretransplant EBV D+/R- and recipient EBV-seropositive status (R+) and the outcomes of PTLD and graft and patient survival among adult kidney transplant recipients.
Ann Intern Med
January 2025
Clinical Epidemiology and Research Center (CERC), Department of Biomedical Sciences, Humanitas University, and IRCCS Humanitas Research Hospital, Milan, Italy, and Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Allergology and Immunology, Berlin, Germany (H.J.S.).
Description: Artificial intelligence (AI) has been defined by the High-Level Expert Group on AI of the European Commission as "systems that display intelligent behaviour by analysing their environment and taking actions-with some degree of autonomy-to achieve specific goals." Artificial intelligence has the potential to support guideline planning, development and adaptation, reporting, implementation, impact evaluation, certification, and appraisal of recommendations, which we will refer to as "guideline enterprise." Considering this potential, as well as the lack of guidance for the use of AI in guidelines, the Guidelines International Network (GIN) proposes a set of principles for the development and use of AI tools or processes to support the health guideline enterprise.
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