Media University of Babylon | Discussion of Graduation Research for Arab Board Students

Media University of Babylon - Faculty of Medicine

Discussion of Graduation Research for Arab Board Students

By : Zaynab Kadhim Ameen Awadh

Date : 11/9/2025 15:29:09 AM

Discussion of Graduation Research for Arab Board Students
As part of the requirements for obtaining the degree of Fellow of the Arab Board of Medical Specializations in Surgery, the thesis defense of Arab Board candidate Dr. Roz Alaa Mahdi was held at the Surgery Department Hall in Al-Hilla Teaching Hospital. Her dissertation was entitled:
“Incidence of Thyroid Cancer in Multinodular Goiter Compared to Solitary Thyroid Nodule.”
The examination committee was composed of Professor Dr. Salah Hadi Kazem (Chair), Consultant Dr. Walaa Nouri Majid, Consultant Dr. Diaa Ali Hussein, and Consultant Dr. Mohsen Naif Kazem (Member and Supervisor).
The discussion was attended by the Dean of the College, Professor Dr. Muhannad Abbass Al-Shalah, along with several faculty members, physicians from the Babylon Health Directorate, and Arab Board students.
The researcher explained that thyroid nodules are common surgical conditions, and the risk of malignancy varies significantly depending on the characteristics and number of nodules. Although solitary thyroid nodules are often considered more suspicious for malignancy, recent evidence suggests that multinodular goiters may also harbor occult carcinomas. Accurate preoperative classification using ultrasound-based systems such as TIRADS and BSTHDA is crucial for identifying high-risk patients, especially when deciding on surgical intervention.
The aim of the study was to determine the prevalence of thyroid cancer among patients who underwent thyroid surgery for multinodular goiter compared to solitary thyroid nodules at Imam Al-Sadiq Teaching Hospital.
The study concluded that solitary thyroid nodules are significantly more associated with cancer risk compared to multinodular goiters. It also demonstrated that the TIRADS and BSTHDA classification systems have strong predictive value for thyroid cancer and should be routinely applied in preoperative assessment to improve diagnostic accuracy and guide surgical decision-making.