ASSESSMENT OF GEOMETRICAL DISCREPANCIES BETWEEN MRT- AND CT-IMAGES IN RADIOSURGERY PLANNING

MRI (magnetic resonance imaging) plays a crucial role in planning radiosurgical treatment. MRI is used to create a contour of the tumour and critical structures. This imaging method allows the boundaries of the pathological lesion to be defined with high accuracy, but there are certain factors (inhomogeneity of the permanent magnetic field, nonlinearity of the gradient field, etc.) that make MR images more susceptible to spatial distortions compared to images obtained by computed tomography (CT). Determining geometric distortion in MRI images is a critical step in ensuring the accuracy of radiosurgical treatment. One way to determine distortion is to perform MRI and CT scans of a special phantom with plastic rods inside and then analyze the position of the rods on the MRI and CT images. As a rule, MRI and CT images of the phantom are compared visually, which is a rather subjective and inaccurate assessment. The purpose of our work was to develop software to automate the performance of this MRI quality assurance test. The developed software was used to compare MRI in two modes T1 and T2 with CT scans. Magnetic resonance imaging (MRI) is widely used for target delineation in stereotactic radiotherapy treatment planning. The calculated discrepancies between coordinates of the CT, T1 and T2 weighted images exceeded 1 mm in 3.5% and 0.1% of the points, respectively. Discrepancies’ magnitude and directions were assessed. The largest discrepancies between T1 and CT are observed in the lower-right part of the phantom’s axial slice, they are directed primarily to the higher-left part of the slice and reach maximum magnitude of 1.5 mm, the mean discrepancy is 0.5 mm. The discrepancies between T2 and CT are primarily directed to the higher-central part of the slice. These results are acceptable for stereotactic radiosurgery 15 planning. Using this software will speed up the procedure of verifying MRI quality and eliminate visual assessment of the discrepancies.

1. Kostyuchenko V.V. Istoriya razvitiya stereotaksicheskogo oblucheniya. Glavy 1–3 [History of the development of stereotactic irradiation. Chapters 1–3]. Medicinskaya fizika, 2015. Vol. 2 (66). Pр. 52–65 [in Russian].

2. Golanov A.V., Kostyuchenko V.V. Nejroradiohirurgiya na Gamma-nozhe [Neuroradiosurgery using Gamma Knife]. Moskva, IP «T.A. Alekseeva» Publ., 2018. 960 p. [in Russian].

3. Putz F., Mengling V., Perrin R. et al. Magnetic resonance imaging for brain stereotactic radiotherapy // Strahlenther Onkol, 2020. V. 196. Pр. 444–456.

4. Pappas E.P., Seimenis I., Moutsatsos A., Georgiou E., Nomikos P., Karaiskos P. Characterization of system-related geometric distortions in MR images employed in Gamma Knife radiosurgery applications. Physics in Medicine & Biology, 2016. Vol. 61(19). Pp. 6993–7011.

5. Paštyková V., Novotný J. Jr., Veselský T., Urgo-šík D., Liščák R., Vymaza J. Assessment of MR stereotactic imaging and image co-registration accuracy for 3 different MR scanners by 3 different methods/phantoms: phantom and patient study. Journal of Neurosurgery JNS, 2018. Vol. 129 (Suppl. 1). Pp. 125–132.

6. Poetker D.M., Jursinic P.A., Runge-Samuel-son C.L., Wackym P.A. Distortion of Magnetic Resonance Images Used in Gamma Knife Radiosurgery Treatment Planning: Implications for Acoustic Neuroma Outcomes. Otology & Neurotology, 2005. Vol. 26(6). Pр. 1220–1228.

7. Repozitorij MRIphantom [Repository MRIphantom] Available at: https://github.com/Moscow-Gamma-Knife-Center/MRIphantom (accessed 06.11.2023) [in Russian].