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Updated: Sep 5, 2026

Phase-Resolved Functional Lung MRI for Pulmonary Ventilation and Perfusion (V/Q) Assessment
Published on: August 9, 2024
Discrepancy between collapsed cone and Monte Carlo algorithms in lung inhomogeneity correction
Amir Hossein Karimi1,2, Indra J Das3, Saeedeh Moharramkhani1,2
1Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Abstract:
Stereotactic body radiation therapy (SBRT) is a well-established standard of treatment for non-small cell lung cancer patients. However, SBRT is a double-edged sword and a high degree of accuracy is required for dose calculations. In the presence of inhomogeneity, it should be below 3% and depends strongly on the accuracy of the algorithm used for dose calculation in treatment planning system (TPS). The aim of this study is to evaluate the accuracy of collapsed cone (CC) algorithm for dose calculation in the presence of lung inhomogeneity compared to the Monte Carlo (MC) algorithm as the reference. The study conducted on a wide range of photon fields from 0.5 × 0.5 cm2to 10 × 10 cm2. Monaco® TPS equipped with CC and MC algorithms in 6 MV, 10 MV, and 18 MV photons was employed and the inhomogeneity correction factor and PPDs were calculated inside an in-house inhomogeneous phantom. Finally, the results were compared between two algorithms. For 6 MV photons, gamma index pass rate (GIPR) with (2 mm, 3%) criteria in a 0.5 × 0.5 cm2field is only 71.3%. The CC algorithm will not be able to confidently reproduce the PDDs in this field. For 1 × 1 cm2, 2 × 2 cm2, and 3 × 3 cm2fields, the accuracy of the CC algorithm can increase to above 98%. For SBRT of small lung lesions, the results recommend increasing the minimum segment width to >0.5 cm in IMRT plans if CC algorithm is used. Independent of field size, the accuracy of CC algorithm decreases with increasing energy. For 10 and 18 MV photons, average GIPR under (2 mm, 3%) criteria was 97.9% and 92.0%, respectively, which are not of clinical interest.

