Articles Vol. 67 No. Số CĐ12- Bệnh viện Ung bướu Nghệ An (2026) 14/08/2026

IMPACT OF HU-RED CONVERSION DATASETS ON TREATMENT DOSE CALCULATION FOR PATIENTS WITH HYPOPHARYNGEAL AND ESOPHAGEAL CANCER AT NGHE AN ONCOLOGY HOSPITAL

Thai Hoang Huu1, Dang Nguyen Van2, TRung Pham Quang3, Thao Phan Thi Thu4, Dung Nguyen Quang1, Loan Nguyen Huong5
1 Department of Linear Accelerators, Nghe An Oncology Hospital
2 Department of Oncology, Hanoi Medical University
3 Department of Radiotherapy and Radiosurgery, 108 Military Central Hospital
4 Department of Oncology and Nuclear Medicine, Ha Tinh provincial General Hospital
5 Department of Gastroenterology, Vietnam National Cancer Hospital, campus 3
DOI: 10.52163/yhc.v67iCD12.6125
816 Views
0 Downloads
Abstract

Objective: To evaluate differences in dose distribution and the physical characteristics of intensity-modulated radiation therapy (IMRT) plans for patients with hypopharyngeal-esophageal cancer using two CT-to-relative electron density conversion datasets, Nghean2022 and Rocsboard02.

Subjects and methods: This retrospective study included simulation CT data from 23 patients with hypopharyngeal-esophageal cancer whose IMRT plans had originally been generated using the Nghean2022 HU-RED dataset. All plans were recalculated in Monaco version 5.11.03 using the Rocsboard02 dataset while keeping the original treatment parameters unchanged. The evaluated parameters included target coverage (Q), conformity index (CI), homogeneity index (HI), absorbed doses to organs at risk (OARs), monitor units (MU), and beam-on time.

Results: The two HU-RED datasets produced comparable dose distributions for the treatment volumes. Compared with Nghean2022, Rocsboard02 showed a tendency to reduce MU and beam-on time by approximately 1.4%. Differences in absorbed doses to OARs, including the spinal cord, parotid glands, heart, and lungs, were minimal and generally below 2%. No statistically significant differences were observed between the two datasets for any of the evaluated parameters (p > 0.05).

Conclusion: The use of either the Rocsboard02 or Nghean2022 HU-RED dataset for IMRT planning in patients with hypopharyngeal-esophageal cancer resulted in comparable dose distribution quality and physical treatment-plan characteristics.

References
[1]
Ferlay J et al. Cancer statistics for the year 2022: an overview. Int J Cancer, 2023, 149 (4): 778-789. doi: 10.1002/ijc.33588. Google Scholar
[2]
Saw C.B, Loper A et al. Determination of CT-to-density conversion relationship for image-based treatment planning systems. Med Dosim, 2005, 30 (3): 145-148. doi: 10.1016/j.meddos.2005.05.001. Google Scholar
[3]
Shaw E, Kline R et al. Radiation Therapy Oncology Group: radiosurgery quality assurance guidelines. Int J Radiat Oncol Biol Phys, 1993, 27 (5): 1231-9. doi: 10.1016/0360-3016(93)90548-a. Google Scholar
[4]
Zentralbibliothek D. ICRU Report 62. International Commission on Radiation Units and Measurements. Google Scholar
[5]
Paddick I. A simple scoring ratio to index the conformity of radiosurgical treatment plans. Technical note. J Neurosurg, 2000, 93 (Suppl 3): 219-222. doi: 10.3171/jns.2000.93.supplement. Google Scholar
[6]
Wu Q et al. Algorithms and functionality of an intensity modulated radiotherapy optimization system. Med Phys, 2000, 27 (4): 701-11. doi: 10.1118/1.598932. Google Scholar
[7]
Lilenbaum R et al. Phase II trial of combined modality therapy with myeloid growth factor support in patients with locally advanced non-small cell lung cancer. J Thorac Oncol, 2010, 5 (6): 837-40. doi: 10.1097/JTO.0b013e3181d6e141. Google Scholar
[8]
Lee N et al. Intensity-modulated radiation therapy with or without chemotherapy for nasopharyngeal carcinoma: radiation therapy oncology group phase II trial 0225. J Clin Oncol, 2009, 27 (22): 3684-90. doi: 10.1200/JCO.2008.19.9109. Google Scholar
[9]
Benedict S.H et al. Stereotactic body radiation therapy: the report of AAPM Task Group 101. Med Phys, 2010, 37 (8): 4078-4101. doi: 10.1118/1.3438081. Google Scholar
[10]
Mutic S et al. AAPM TG 66. Quality assurance for computed-tomography simulators and the computed-tomography-simulation process. Med Phys, 2003, 30 (66): 2762-2792. Google Scholar