Malignant Struma Ovarii – A Case Report and Review of the Literature
ABSTRACT Struma ovarii is a rare monodermal ovarian teratoma composed predominantly of mature thyroid tissue. Of these cases, 5-8% are clinically hyperthyroid and 5-10% of these tumors are malignant.
A 53-year-old female presented with a 19 x 5 x 5 cm pelvic mass that was treated with bilateral salpingo-oophorectomy, pelvic and para-aortic lymph node sampling, omentectomy and appendectomy and staging for an ovarian tumor. There was no evidence of distant metastases or lymph node invasion. Re-evaluation of the patient after surgery revealed that she was clinically euthyroid and there was no thyroid malignancy. Histopathology revealed papillary thyroid carcinoma arising in struma ovarii (malignant struma ovarii).
Malignant struma ovarii is a very rare malignant ovarian teratoma. In young patients unilateral oophorectomy and complete surgical staging should be considered when the tumor is confined to the one ovary (stage Ia). Long-term follow-up for the detection of metastases or tumor recurrence by serial serum thyroglobulin and (131)I scan or positron emission tomography/computed tomography may be required in selected patients with this rare tumor.
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ABSTRACT: SOVA has been a practical decoding algorithm for turbo-codes due to its low complexity' and low latency of decoding. However, inaccuracy of soft-decision output could lower the performance of SOVA. In this paper, we propose a modified SOVA by incorporating a corrective function to improve the accuracy of soft decision output. The simulation results show that the modified corrective SOVA algorithm achieves significant performance improvement without the increase of decoding complexity. Implementation of the improved algorithm on DSP is investigated by examining the effects of the degree of quantization and the finite word length on the performance, and speed, as well as memory storage requirement of decoding.Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on; 01/2004
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ABSTRACT: Thyroid cancer (TC) is the commonest endocrine malignancy. In the overwhelming majority of cases, thyroid carcinomas are well-differentiated malignancies that respond favorably to treatment; however, this outcome cannot be absolutely guaranteed. The absence of large prospective randomized clinical trials in TC-due to its low incidence and protracted clinical course in cases with persistent/recurrent metastatic disease-results in considerable debates regarding the optimal treatment and follow-up regimens in this malignancy. Some of these debates originated several decades ago, yet are still ongoing despite interim advancements in other domains of oncology. Here we discuss what we believe are the issues of major controversy in TC; these are mentioned in the following non-exhaustive list: (i) the optimal management of solitary and multiple thyroid nodules; (ii) the role of basal calcitonin measurements in the diagnostic investigation of nodular thyroid disease; (iii) the extent of the initial operation after establishment of the diagnosis of TC; (iv) the intensity and frequency of radioactive iodine (RAI; (131)I) therapies (especially in patients with persistent/recurrent metastatic disease); (v) the degree and duration of long-term thyroid hormone suppression therapy (THST) required for optimal outcomes in TC patients; (vi) the optimal management of patients with RAI-refractory disease or other "high-risk" clinicopathologic features; and, finally, (vii) the optimal algorithm for lifelong follow-up of TC patients after their initial treatment. We present elements of the above controversies as pertinent to the various types of TC. We have opted for breadth rather than depth of commentary, at the same time providing the reader with extended up-to-date bibliography.Hormones (Athens, Greece) 07/2004; 3(3):149-70. DOI:10.14310/horm.2002.11123 · 1.24 Impact Factor
- Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin 08/2004; 445(1):96-7. DOI:10.1007/s00428-004-1022-4 · 2.56 Impact Factor