Perturbation in Magnetic Resonance Images from Cerebellum Target Stereotactic Radiosurgery

Kaile Li, PhD, Corbin Helis, MD, Esmail Parsai, PhD, Jeremy Karlin, MD

* Correspondence: [email protected]

OPEN ACCESS

PUBLISHED 31 December 2024

CITATION Li, K., Helis, C., et al., 2024. Perturbation in Magnetic Resonance Images from Cerebellum Target Stereotactic Radiosurgery. Medical Research Archives, [online] 12(12). https://doi.org/10.18103/mra.v12i12.6020

DOI https://doi.org/10.18103/mra.v12i12.6020

ISSN 2375-1924

ABSTRACT

Introduction: Stereotactic Radiosurgery (SRS) is an efficacy procedure in treatment of brain disease. The complicated SRS procedure includes simulation, target definition, treatment planning, target localization and dose delivery. The external accuracy verifications of the whole procedure have been investigated with different quality assurance methodologies. However, the final estimation of SRS procedure should be reflected in the disease lesions inside the patient, and this could be done by employing different imaging modalities at different temporal points, but challenges exist in abstracting the weak signal due to radiation in the images. Therefore, in this study, a method was used to estimate the perturbation information in MRIs at different temporal points after a cerebellum target SRS.

Methods and Materials: A cerebellum target was under an SRS with a single ARC small aperture cone on a Linac machine from Varian Medical system. A series of MRIs in different temporal points have been attained, the temporal range was 0 months, 3 months, 6 months, and 9 months. The volume of interested scans were defined by the isodose volume in the dosimetric plan, which included target volume, and isodose volumes which were at different isodose levels including 100%, 90%, 75%, 60%, 30% and 15% of prescription dose. Through image fusion method, these volumes of interest were defined in the MRIs through the function of copy structures to registered image. Then structure property function to attain the structure statistics including minimum Hounsfield Unit (HU), maximum HU, mean HU, and standard deviation (SD) of HU inside the volume of interest. Vectors were used to represent the separate volumes of interest and corresponding statistics in HU. A relative percentage difference method, which was defined to be the ratio between the differences of SD and mean SD divided by the mean SD to separate the technical variation from imaging procedure.

Result: For the selected volumes of interest, the mean SD HUs were 20.8, 20.4, 24.1, and 26.21 for T1 MRIs, and was 35.2, 17.4, 31.9, and 37.1 for T1 MRIs with contrast. And the least difference in SD HU vector elements was at 3 months, and the average absolute SD HUs was about three in magnitude. Moreover, the relative percentage difference showed a time-spatial vector pattern with special characteristics.

Conclusions: Some significant HU variation can be seen from T1 and T1 with contrast MRIs in temporal and volume discrete matrix. Data analysis could be further improved by eliminating the uncertainty due to technical inconsistency, and similar investigation approach could be applied to the MRIs acquired right after radiation irradiated for SRS.

Keywords: Stereotactic Radiosurgery, MRI, Brain Disease, Perturbation

Introduction

Stereotactic Radiosurgery (SRS) is an efficacy procedure in treatment of brain disease. The radiosurgery was initialed by Leksell gamma procedure, and modernized methods have been extended to linear accelerators, Cyberknife and so on. The complicated SRS procedure includes simulation, target definition, treatment planning, target localization and dose delivery. The external accuracy verification of the whole procedure has been investigated with different quality assurance methodologies. However, the final estimation of SRS procedure should be reflected in the disease lesions inside the patient, and this could be done by employing different imaging modalities at different temporal points, but challenges exist in abstracting the weak signal due to radiation in the images. The rationale of this philosophy is to mimic the physics study of a few atomic layers of surface morphology between strong Bragg Peaks. More specifically, the perturbation information could be used to estimate and predict the potential abnormal structure at the phases of pretreatment, during treatment and post treatment Therefore, in this study, a method was used to estimate the perturbation information in MRIs at different temporal points after a cerebellum target SRS, and the targeting to understand the rationale of radiosurgery in target characteristics, dosimetry accuracy, and radiation dose delivery response and improvement of radiosurgery strategy.

Methods and Materials

This radiosurgery plan was generated in an Eclipse Treatment planning system form Varian medical system. The treatment planning system simulated the x-ray beam, which was generated by a linear accelerator. The simulation included the geometric structure of linear accelerator system and with accurately calibration of dosimetry accuracy. After the dosimetry requirement was given, a dose delivery approach was developed as showed in

. Then patient was treated with high precise setup in the treatment room, and accurate dose was delivered to the intended target. Afterward, different imaging modalities could be employed to trace the treatment outcome.

Firstly, a cerebellum target was under an SRS with a single ARC small aperture cone on a Linac machine from Varian Medical system. The SRS plan is shown in

.

In this study, a series of MRIs in different temporal points have been attained, the temporal range were 0 months, 3 months, 6 months, and 9 months. The volume of interested scans were defined by the isodose volume in the dosimetric plan, which included target volume, and isodose volumes which were at different isodose levels including 100%, 90%, 75%, 60%, 30% and 15% of prescription dose, which is shown in

.

Afterwards, through image fusion method, these volumes of interest were defined in the MRIs through the function of copy structures to registered image. Then structure property function to attain the structure statistics including minimum Hounsfield Unit (HU), maximum HU, mean HU, and standard deviation (SD) of HU inside the volume of interest (VOI), and this procedure is shown in

.

Finally, a relative percentage difference method, which was defined to be the ratio between the differences of SD and mean SD divided by the mean SD to separate the technical variation from imaging procedure. The formula below shows this estimation procedure.

𝐻𝑆𝐷𝑉1
⋮
𝐻𝑆𝐷𝑉𝑁 
=
 
𝐻𝑉1
𝑃𝑖
−𝐻𝑉1
𝑁 2 𝑉
1
𝑝
𝑖=1
 𝑁𝑉1
𝑝−1 
⋮
 
𝐻𝑉𝑁
𝑃𝑖
−𝐻𝑉𝑁
𝑁 2 𝑉𝑁
𝑝
𝑖=1
 𝑁𝑉𝑁
𝑝−1 
=
 
𝑆𝐷𝐻𝑆𝐷 =
 
 𝐻𝑆𝐷𝑉𝑖
−𝐻𝑆𝐷𝑉
 
2 𝑁𝐻𝑆𝐷
𝑖=1
 𝑁𝐻𝑆𝐷−1 

Note: HSD (HU Standard Deviation in VOI V. SD (Standard Deviation. N (Number of VOIs or pixels in a VOI) P (Pixel in VOI)

Result

For the selected volumes of interest, the mean SD HUs were 20.8, 20.4, 24.1, and 26.21 for T1 MRIs, and was 35.2, 17.4, 31.9, and 37.1 for T1 MRIs with contrast. And the least difference in SD HU vector elements was at 3 months, and the average absolute SD HUs was about three in magnitude. Moreover, the relative percentage difference showed a time-spatial vector pattern with special characteristics.

In

, the MR T1 with contract image showed a dip in the 3-month time point, and this implied that this imaging setting is sensitive to the treatment lesion response. And in

, the observation perturbation in formula 1 for surface dose volumes at simulation CT and different MRIs were plotted. The comparison showed the obvious variation happen 15% prescription line, which is 3Gy at this treatment. While considering the actual size of the target, this plot showed the optimal sensitivity volume for analysis in this type of study. Then, as another support of this volume of interest selection,

was another support for this range of volume of interest by plotting the T1 and T1C SDHU difference, which is the SDHU of T1 MRI subtracting that of the T1 MRI with contract.

Table 1. T1 and T1 with contrast perturbation for HU standard deviation

Conclusion

In this study, the perturbation philosophy was employed to analyze a temporal series of the MRIs and showed the variation of these perturbation information in response regarding to different volumes of interest in the brain lesion at different dosimetry regions. And the sensitivity of these information was also displayed in different data domains of temporal points. In conclusion, a new outcome analysis tactic was proved to be an effective method for tracing the different abnormal lesions under radiosurgery.

Discussion

As an initial study, some significant HU variation can be seen from T1 and T1 with contrast MRIs in temporal and volume discrete matrix. For better understanding, data analysis could be further improved by eliminating the uncertainty due to technical inconsistency, for example,

shows the variations when directly applying the “copy structures to registered image” function, which could be affected by scanning slice thickness, clinician’s judgement on registration, and so on. Moreover, similar investigation approach could be applied to the MRIs acquired right after radiation irradiated for SRS. Final, the philosophy of this analysis method could be expanded to different imaging scenarios for objects in different physical scales and kinetic response of radiation medicine.

References:

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