Saeid Rezaei

An updated exploration of the burden of thyroid cancer across a country is always required for making correct decisions. The objective of this study is to present the thyroid cancer burden and attributed burden to the high Body Mass Index (BMI) in Iran at national and sub-national levels from 1990 to 2019. The data was obtained from the GBD 2019 study estimates. To explain the pattern of changes in incidence from 1990 to 2019, decomposition analysis was conducted. Besides, the attribution of high BMI in the thyroid cancer DALYs and deaths were obtained. The age-standardized incidence rate of thyroid cancer was 1.57 (95% UI: 1.33-1.86) in 1990 and increased 131% (53-191) until 2019. The age-standardized prevalence rate of thyroid cancer was 30.19 (18.75-34.55) in 2019 which increased 164% (77-246) from 11.44 (9.38-13.85) in 1990. In 2019, the death rate, and Disability-adjusted life years of thyroid cancer was 0.49 (0.36-0.53), and 13.16 (8.93-14.62), respectively. These numbers also increased since 1990. The DALYs and deaths attributable to high BMI was 1.91 (0.95-3.11) and 0.07 (0.04-0.11), respectively. The thyroid cancer burden and high BMI attributed burden has increased from 1990 to 2019 in Iran. This study and similar studies' results can be used for accurate resource allocation for efficient management and all potential risks' modification for thyroid cancer with a cost-conscious view.

Abstract Purpose This study evaluated the impact of a commercial AI‐assisted contouring tool on intra‐ and inter‐observer variability in prostate radiation therapy and assessed the dosimetric consequences of geometric contour differences. Methods Two experienced radiation oncologists independently delineated clinical target volume (CTV) and organs at risk (OARs) for prostate cancer patients. Manual contours (C man ) and AI‐generated contours (C AI ) were compared with adjusted AI contours (C AI,adj ). A consensus reference (C ref ) served as the benchmark. To evaluate clinical impact, treatment plans were recalculated and replanned on each contour set under identical beam geometries to assess dose–volume histogram (DVH) parameters. Results AI‐assisted contouring significantly improved both intra‐ and inter‐observer agreement. Inter‐observer analysis revealed that the Dice similarity coefficient (DSCs) for CTV increased from 0.78 (± 0.11) for C man to 0.89 (± 0.09) for C AI, adj . Similarly, intra‐observer analysis revealed that both oncologists showed significantly higher DSCs for C AI, adj compared to C man . A thorough geometric comparison to the C ref revealed that while adjustments to C AI improved accuracy, they generally did not surpass C man for CTV and rectum. Dosimetric analyses demonstrated that, under fixed plan geometry, both C man and C AI,adj contours yielded lower planning target volume (PTV) D95% values compared with C ref , whereas after replanning, all plans met institutional criteria with no clinically significant differences among contour sets. Conclusion AI‐assisted contouring in prostate radiotherapy reduced intra‐ and inter‐observer variability and improved contouring consistency. However, C AI, adj did not consistently surpass C man , especially for the CTV and rectum, where automation bias or selective clinical acceptance may have influenced edits. Fixed‐plan recalculations revealed dose differences from minor geometric deviations. These findings underscore the importance of structured quality assurance (QA) and human oversight to mitigate automation bias while leveraging AI's efficiency. The single‐institution design with two oncologists and one AI software limits generalizability, underscoring the need for multi‐observer validation.

PURPOSE: Treatment outcomes of locally advanced rectal cancer have improved significantly in recent decades. This retrospective study aimed to assess the efficacy of neoadjuvant chemoradiotherapy (nCRT) followed by surgery in patients with T4 rectal cancer and the different outcomes between T4a and T4b patients. MATERIALS AND METHODS: A total of 60 clinically T4 rectal cancer patients who underwent nCRT were included in the analysis. Patient characteristics, treatment regimens, down-staging rates, pathological response, and overall survival (OS) were evaluated. RESULTS: Both T4a and T4b patients experienced down-staging following nCRT (36.6% and 6.2% respectively; p = 0.021). T4a patients exhibited a higher rate of pathological complete response (pCR) than T4b patients (13.3% in T4a vs. 0% in T4b; p = 0.122). After a median follow-up of 36 months, the OS and recurrence-free survival (RFS) of T4a patients were significantly higher compared to T4b patients (hazard ratio [HR] = 2.52, 95% confidence interval [CI] 1.05-6.05, p = 0.038 for OS; HR = 2.32, 95% CI 1.09-4.92, p = 0.025 for RFS). CONCLUSION: This study provides valuable insights into the effectiveness of nCRT in T4 rectal cancer patients. Although down-staging was observed in both T4a and T4b subgroups, achieving a pCR remains a challenge, particularly in T4b patients. Further research is needed to optimize treatment strategies and enhance pCR rates in T4 rectal cancer patients to improve oncologic outcomes.