Tiroit Hastalıklarının Radyoiyot (I-131) Tedavisinde Absorbe ve Efektif Doz Hesaplamaları için Python Yazılım Kodu Geliştirilmesi

Öz

Bu çalışmada, tiroidin benign hastalıklarından hipertiroidizmin tedavisinde tiroid bezini hedefleyen İyot-131 (I-131) radyoizotop tedavisi için doku ve organların absorbe ettikleri dozları ve efektif dozu hesaplamaya yönelik bir Python kodu geliştirilmiştir. Geliştirilen kod, biyokinetik verileri ve organlar arası etkileşimleri hesaba katacak şekilde tasarlanmıştır. Hesaplama sonuçları, MIRDcalc ve IDAC-Dose gibi mevcut dozimetri yazılımlarıyla karşılaştırılmıştır. Araştırmada, tiroid tedavisinde yetişkin hastalara uygulanan 5mCi, 10mCi, 15mCi ve 20mCi dozlarındaki I-131 radyoiyot uygulamalarının cinsiyete göre organ dozları ve efektif dozları hesaplanmıştır. Python kodu ile yapılan hesaplamalar, IDAC-Dose ile ortalama %1.8±0.9 hata marjıyla uyumlu sonuçlar vermiştir. Tiroid dokusu için Python kodu ile IDAC-Dose arasındaki doz sapması %0.7, MIRDcalc ile sapma %1.2 olarak belirlenmiştir. Cinsiyet farklılıkları incelendiğinde, kadınlarda karaciğer absorbsiyonu erkeklere göre %8.3 daha yüksek bulunmuştur. Efektif doz değerleri kadınlarda erkeklere göre daha yüksek kaydedilmiştir. 5-20mCi aralığında efektif doz-artış katsayısı 3.1-4.3 mSv/gCi olarak hesaplanmıştır. Hematopoetik sistem ve gonadlarda kadınlarda %8.3-14.1 daha yüksek absorbsiyon gözlenmiştir. Sonuç olarak, geliştirilen Python kodu, ICRP 103 kriterlerini karşılamakta ve hasta spesifik tedavi optimizasyonunda kullanılabilecek güvenilir bir alternatif olarak önerilmektedir.

Anahtar Kelimeler

• I-131
• Radyoiyot
• Python Kod
• MIRDcalc
• IDAC-Dose

Development of Python Software Code for Absorbed and Effective Dose Calculations in Radioiodine (I-131) Treatment of Thyroid Diseases

Öz

In this study, a Python code was developed to calculate the absorbed doses of tissues and organs and the effective dose for Iodine-131 (I-131) radioisotope therapy targeting the thyroid gland in the treatment of hyperthyroidism, a benign disease of the thyroid. The code has been designed to take into account biokinetic data and inter-organ interactions. The calculation results were then compared with those obtained from existing dosimetry software such as MIRDcalc and IDAC-Dose. The study involved the calculation of organ doses and effective doses of I-131 radioiodine applications to adult patients receiving thyroid treatment. The doses ranged from 5mCi to 20mCi, with the calculations conducted separately for male and female subjects. The Python code calculations yielded results that were consistent with those of IDAC-Dose, with an average error margin of 1.8 ± 0.9%. For thyroid tissue, the dose deviation between Python code and IDAC-Dose was 0.7%, while the deviation with MIRDcalc was 1.2%. A further analysis of gender differences revealed that liver absorption was 8.3% higher in females than in males. Effective dose values were found to be higher in females than males. In the range of 5-20mCi, the effective dose-increase coefficient was calculated as 3.1-4.3 mSv/gCi. Furthermore, an analysis of the haematopoietic system and gonads revealed a 8.3-14.1% higher absorption rate in females. In conclusion, the developed Python code meets the ICRP 103 criteria and is recommended as a reliable alternative for patient-specific treatment optimisation.

Anahtar Kelimeler

• I-131
• Radyoiyot
• Python Kod
• MIRDcacl
• IDAC-Dose

Kaynakça

1. 1. Demir M. Benign tiroit hastalıklarının radyoiyot (I-131) tedavisinde dozimetri. Nucl Med Semin. 2025;11:1-5. doi:10.4274/nts.galenos.2025.32932.
2. 2. Burch H. B, Burman K. D, Cooper D. S. A 2011 survey of clinical practice patterns in the management of Graves' disease. J Clin Endocrinol Metab. 2012;97:4549-4558. Doi:10.1210/jc.2012-2802.
3. 3. ICRP, 1991. 1990 recommendations of the International Commission on Radiological Protection, ICRP Publ. 60, Ann. ICRP 21, 1–201.
4. 4. ICRP, 2007. The 2007 recommendations of the International Commission on Radiological Protection ICRP Publ. 103, Ann. ICRP 37, 1–332.
5. 5. Kesner AL, Carter LM, Ramos JCO, Lafontaine D, Olguin EA, Brown JL, et al. MIRD Pamphlet No. 28, Part 1: MIRDcalc-A software tool for medical internal radiation dosimetry. Journal Nuclear Medicine. 2023; 64(7):1117-1124. doi:10.2967/jnumed.122.264225.
6. 6. Carter LM, Ocampo Ramos JC, Olguin EA, Brown JL, Lafontaine D, Jokisch DW, et al. MIRD Pamphlet No. 28, Part 2: Comparative evaluation of MIRDcalc dosimetry software across a compendium of diagnostic radiopharmaceuticals. Journal of Nuclear Medicine, 2023; 64(8):1295-1303. doi: 10.2967/jnumed.122.264230
7. 7. Andersson M, Johansson L, Eckerman K, Mattsson S. IDAC-Dose 2.1, an internal dosimetry program for diagnostic nuclear medicine based on the ICRP adult reference voxel phantoms. EJNMMI Res. 2017;3;7(1):88. doi: 10.1186/s13550-017-0339-3.
8. 8. Biggs S, Jennings M, Swerdloff S, Chlap S, Lane D, Rembish J, et al. PyMedPhys: A community effort to develop an open, Python-based standard library for medical physics applications. Journal of Open Source Software. 2022;7(78): 4555. doi:10.21105/joss.04555.

9. 9. Castle J. R, Duan J, Feng X, Chen Q. Development of a virtual source model for Monte Carlo-based independent dose calculation for varian linac. Journal of Applied Clinical Medical Physics. 2022; e13556. doi:10.1002/acm2.13556.
10. 10. Gajewski J, Garbacz M, Chang CW, Czerska K, Durante M, Krah N, et al. Commissioning of GPU–accelerated Monte Carlo code FRED for clinical applications in proton therapy. Frontiers in Physics. 2021; 8;403. doi:10.3389/fphy.2020.567300.
11. 11. Galić S, Kovačević M, Lasić I, Brkić H, Faj D. A method of high-resolution radiotherapy delivery fluences with a pair of fields with orthogonal collimator settings: A study on ten head-and-neck cancer patients. Journal of Medical Physics. 2020;45(1):36. doi:10.4103/jmp.JMP_51-19.
12. 12. Lysakovski P, Ferrari A, Tessonnier T, Besuglow J, Kopp B, Mein S, et al. Development and benchmarking of a Monte Carlo dose engine for proton radiation therapy. Frontiers in Physics. 2021;655. doi:10.3389/fphy.2021.741453.
13. 13. Milan T, Grogan G, Ebert MA, Rowshanfarzad P. Evaluation of the impact of the linac MLC and gantry sag in volumetric modulated arc therapy. Medical Physics. 2019;46(5):1984–1994. doi:10.1002/mp.13491.
14. 14. Rodríguez C, López-Fernández A, García-Pinto D. A new approach to radiochromic film dosimetry based on non-local means. Physics in Medicine & Biology. 2020;65(22):225019. doi:10.1088/1361-6560/abb71b.
15. 15. Spezialetti M, Lapenna F, Caianiello P, Fracchiolla F, Muciaccia F, Placidi G, et al. Using deep learning for fast dose refinement in proton therapy. IEEE International Conference on Systems, 2021;Man and Cybernetics (SMC):1783–1789. doi:10.1109/SMC52423.2021.9658879.
16. 16. Tsuneda M, Nishio T, Ezura T, Karasawa K. Plastic scintillation dosimeter with a conical mirror for measuring 3D dose distribution. Medical Physics. 2021;48(10):5639–5650. doi:10.1002/mp.15164.
17. 17. Yang M., Wang X, Guan F, Titt U, Iga K, Jiang D, et al. Adaptation and dosimetric commissioning of a synchrotron-based proton beamline for FLASH experiments. Phys. Med. Biol. 2022;67: 165002. doi:10.1088/1361-6560/ac8269.
18. 18. Baltz GC, Kirsner SM. Validation of spline modeling for calculation of electron insert factors for Varian linear accelerators. Journal of Applied Clinical Medical Physics. 2021;22(11):64–70. doi:10.1002/acm2.13430.
19. 19. Douglass J, Keal JA. DeepWL: Robust EPID based Winston-Lutz analysis using deep learning, synthetic image generation and optical path-tracing. Physica Medica. 2021;89:306–316. doi:10.1016/j.ejmp.2021.08.012.
20. 20. Bert C, Bertholet J, Essers M, Heijmen B, Jornet N, Koutsouveli E, et al. Core curriculum for medical physics experts in radiotherapy 3rd edition. EFORMP, ESTRO. 2021.