1. K Chen1, W Guo2, C Lin3, W Chu3, F Wu4
Applying 4DDSA to Gamma Knife Radiosurgery treatment planning: a feasibility study
Hello, I’m Ko-Kung Chen. I’ll talking to you about “topic name”
K Chen1, W Guo2, C Lin3, W Chu3, F Wu4
1. School of Medicine, National YangMing University, Taipei, Taiwan.
2. Taipei Veterans General Hospital & National Yang Ming University, Taipei, Taiwan.
3. Taipei Veterans General Hospital, Taipei, Taiwan.
4. Siemens Ltd. Taiwan, Taipei, Taipei

2. Disclosure Nothing to disclose personally.
The presentation materials are, in part, from a research collaboration between Taipei Veterans General Hospital, Taiwan and Siemens Healthcare.
In this study, I’m going to talk about patients whose aortic disease influence brain hemodynamics as well. To determine the efficacy of the surgery, we need a robust quantification method to measure the parenchymal lood volume . Also, it’s desired that the whole treatment program be done in single stop for every patient, hence the quantification algorithm must be sufficiently fast as well.
2018/7/21

3. Purpose
Gamma Knife Radiosurgery (GKRS) had been shown to be safe and reliable approach for cerebral arteriovenous malformation (AVM) and intracranial dural ateriovenous fistula (DAVF).
Achieving high conformity between target volume and the planned radiated volume is of top priority in GKRS.
The study aims to investigate the feasibility of applying 4DDSA, developed by Siemens Healthcare, to Leksell Gamma Knife Radiosurgery planning for more panoramic view of AVM nidus/fistula retrospectively.
In this study, I’m going to talk about patients whose aortic disease influence brain hemodynamics as well. To determine the efficacy of the surgery, we need a robust quantification method to measure the parenchymal lood volume . Also, it’s desired that the whole treatment program be done in single stop for every patient, hence the quantification algorithm must be sufficiently fast as well.
2018/7/21

4. (Patient recruitment)
Material and Method-1
(Patient recruitment)
With institutional review board approval, 20 consecutively patients (8 DAVF and 12 AVM, 13 males and 7 females, mean age 45, years. Males aged 48, range years. Females aged 47, range years) who received radiosurgery (November October 2015), using the Gamma Knife® and treatment planning computer GammaPlan® (Elekta, Sweden) were recruited.
To address these issues, we adopt a semi-automatic approach that based on histogram analysis. (“repeat the text”).
3 slices are manually selected from each volume. These slices are then fed to automatic brain extraction program to remove unwanted parts. The post PBV map is then mapped onto the pre PBV map via rigid body motion transformation. A tunable grid is applied on the PBV maps, with circular ROIs placed onto it, histogram is computed for every ROI, and further statistical testing are adopted to test the differences between these local histograms. 4
2018/7/21

5. (Implementation of 4D DSA into GKRS procedure)
Material and Method-2
(Implementation of 4D DSA into GKRS procedure)
To address these issues, we adopt a semi-automatic approach that based on histogram analysis. (“repeat the text”).
3 slices are manually selected from each volume. These slices are then fed to automatic brain extraction program to remove unwanted parts. The post PBV map is then mapped onto the pre PBV map via rigid body motion transformation. A tunable grid is applied on the PBV maps, with circular ROIs placed onto it, histogram is computed for every ROI, and further statistical testing are adopted to test the differences between these local histograms.
From left to right: stereotactic frame & markers as seen on 4D DSA, 2D DSA lateral, and MR TOF (axial & coronal) 5
2018/7/21

6. (Best phase for AVM nidus/fistula depiction)
Material and Method-3
(Best phase for AVM nidus/fistula depiction)
4D DSA 2D DSA
To address these issues, we adopt a semi-automatic approach that based on histogram analysis. (“repeat the text”).
3 slices are manually selected from each volume. These slices are then fed to automatic brain extraction program to remove unwanted parts. The post PBV map is then mapped onto the pre PBV map via rigid body motion transformation. A tunable grid is applied on the PBV maps, with circular ROIs placed onto it, histogram is computed for every ROI, and further statistical testing are adopted to test the differences between these local histograms.
Early phase Middle phase late phase 6
2018/7/21

7. Results - 1
DICOM compatibility between 4D DSA and GammaPlan is resolved by post processing using MATLAB r2013b.
Among 20 initially selected patients, 16 (80%) entered and final analysis of stereotactic registration for planning radiosurgery. Of the other 20%, the markers on the sides of the localization box were partially included in the field of view (FOV) of 4D DSA and failed in registration.
To address these issues, we adopt a semi-automatic approach that based on histogram analysis. (“repeat the text”).
3 slices are manually selected from each volume. These slices are then fed to automatic brain extraction program to remove unwanted parts. The post PBV map is then mapped onto the pre PBV map via rigid body motion transformation. A tunable grid is applied on the PBV maps, with circular ROIs placed onto it, histogram is computed for every ROI, and further statistical testing are adopted to test the differences between these local histograms. 7
2018/7/21

8. coronal Error (mm) (mean/Max)
Results - 2
Comparison of registration errors of 4D DSA and integrated stereotactic imaging
Patient
Alias
4D-DSA error
(mm)
(Mean / Max)
2D-DSA error (mm)
(Max)
MR T1
coronal Error (mm) (mean/Max)
MR T1
Axial Error (mm)
(mean/Max)
MR T2
MR TOF
Error (mm)
Expected
error (mm)
(mean)
DAVF 01
1.4 / 4.8
0.2
0.8 / 1.3
0.3 / 0.9
0.3 / 0.8
0.4 / 1.1
1.01
DAVF 02
0.4 / 0.9
0.8 / 1.6
0.3 / 1.1
0.4 / 1.0
0.5 / 1.4
1.0863
DAVF 03
0.5 / 1
0.9 / 1.6
0.3 / 0.7
0.4 / 1.6
1.0909
DAVF 04
0.5 / 0.9
0.3 / 0.6
1.0583
DAVF 05
0.5 / 1.2
0.8 / 1.5
0.3 / 1.0
0.9747
DAVF 06
0.6 / 1.2
0.3 / 1.2
0.4 / 1.3
DAVF 07
1.0 / 1.7
0.3 / 0.4
0.3 / 0.5
0.4 / 1.3
1.1747
AVM 01
0.6 / 1.9
0.8 / 1.4
0.2 / 0.5
0.8944
AVM 02
0.1
1.044
AVM 03
1.1 / 1.8
1.2329
AVM 04
0.8 / 1.7
1.0392
AVM 05
1.1 / 2.5
1.1916
AVM 06
1.1 / 2.1
0.2 / 0.6
AVM 07
0.7 / 2.1
0.9 / 1.5
0.995
AVM 08
0.4 / 0.6
AVM 09
0.4 / 0.5
0.5 / 1.8
1.0724
The Expected error of current practice of GKRS is computed using:
((2D-DSA error)2 + (MR T1 axial error)2 + (MR T1 coronal error)2 + (MR T2 axial error)2 + (MR TOF error)2)1/2
To address these issues, we adopt a semi-automatic approach that based on histogram analysis. (“repeat the text”).
3 slices are manually selected from each volume. These slices are then fed to automatic brain extraction program to remove unwanted parts. The post PBV map is then mapped onto the pre PBV map via rigid body motion transformation. A tunable grid is applied on the PBV maps, with circular ROIs placed onto it, histogram is computed for every ROI, and further statistical testing are adopted to test the differences between these local histograms.
The error of 4D DSA is larger than the 2D DSA alone, but significantly less than that of integrated stereotactic imaging. 8
2018/7/21

9. A patient with small AVM.
Results - 3
A patient with small AVM.
To address these issues, we adopt a semi-automatic approach that based on histogram analysis. (“repeat the text”).
3 slices are manually selected from each volume. These slices are then fed to automatic brain extraction program to remove unwanted parts. The post PBV map is then mapped onto the pre PBV map via rigid body motion transformation. A tunable grid is applied on the PBV maps, with circular ROIs placed onto it, histogram is computed for every ROI, and further statistical testing are adopted to test the differences between these local histograms.
A patient with small AVM. (A) shows 4D DSA that is overlaied with planned treatment dosage contours. For an small AVM nidus, the 4D DSA provides opacifications better than (B) MR TOF and (C) MR T2 and (D) MR T1. 9
2018/7/21

10. A patient with small AVM.
Results - 4
A patient with small AVM.
To address these issues, we adopt a semi-automatic approach that based on histogram analysis. (“repeat the text”).
3 slices are manually selected from each volume. These slices are then fed to automatic brain extraction program to remove unwanted parts. The post PBV map is then mapped onto the pre PBV map via rigid body motion transformation. A tunable grid is applied on the PBV maps, with circular ROIs placed onto it, histogram is computed for every ROI, and further statistical testing are adopted to test the differences between these local histograms.
A patient with large AVM. (A) shows 4D DSA that is overlaied with planned treatment dosage contours. The red arrow in (A) points a region that is considered to be part of AVM nidus based on MR T2 and T1 findings (B, C, and D). The 4D DSA clearly depicts the region is in fact a portion of normal tissue. 10
2018/7/21

11. A patient with small AVM.
Results - 5
A patient with small AVM.
To address these issues, we adopt a semi-automatic approach that based on histogram analysis. (“repeat the text”).
3 slices are manually selected from each volume. These slices are then fed to automatic brain extraction program to remove unwanted parts. The post PBV map is then mapped onto the pre PBV map via rigid body motion transformation. A tunable grid is applied on the PBV maps, with circular ROIs placed onto it, histogram is computed for every ROI, and further statistical testing are adopted to test the differences between these local histograms.
A patient with DAVF. (A) shows 4D DSA that is overlaied with planned treatment dosage contours. The 4D DSA provides clear opacification of fistula, where (B) MR T2 and (C & D) MR T1 provides almost no opacification. 11
2018/7/21

12. Objective separation of AVM nidus with multiple arterial territories
Results - 6
Objective separation of AVM nidus with multiple arterial territories
To address these issues, we adopt a semi-automatic approach that based on histogram analysis. (“repeat the text”).
3 slices are manually selected from each volume. These slices are then fed to automatic brain extraction program to remove unwanted parts. The post PBV map is then mapped onto the pre PBV map via rigid body motion transformation. A tunable grid is applied on the PBV maps, with circular ROIs placed onto it, histogram is computed for every ROI, and further statistical testing are adopted to test the differences between these local histograms.
An large and complex AVM. Left verterbre artery injection and right internal carotid artery injection were performed separately to reveal the whole picture of AVM nidus.
With selective administrtion of contast medium, the 4D DSA is capable depicts distinct arterial territories of an AVM nidus that are supplied different feeding arteries. 12
2018/7/21

13. Conclusion
Integration of fully time resolved DSA data into the gamma knife radiosurgery system for patients with brain AVM and DAVF is feasible.
The registration error of stereotactic 4D DSA is slightly inferior to that of 2D DSA alone. The errors are, however, significantly smaller than that of integrated stereotactic 2D DSA and MRI/MRA.
Objective territorial separation of intricate AVM nidus, which is supplied by multiple arterial territories, becomes more practical using 4D DSA, a key feature that 2D DSA lacks.
To address these issues, we adopt a semi-automatic approach that based on histogram analysis. (“repeat the text”).
3 slices are manually selected from each volume. These slices are then fed to automatic brain extraction program to remove unwanted parts. The post PBV map is then mapped onto the pre PBV map via rigid body motion transformation. A tunable grid is applied on the PBV maps, with circular ROIs placed onto it, histogram is computed for every ROI, and further statistical testing are adopted to test the differences between these local histograms. 13
2018/7/21

14. References
Guo WY, Pan DH, Wu HM, et al: Radiosurgery as a treatment alternative for dural arteriovenous fistulas of the cavernous sinus. AJNR Am J Neuroradiol 19:1081–1087, 1998
Spiegelmann R, Friedman WA, Bova FJ. Limitations of angiographic target localization in planning radiosurgical treatment. Neurosurgery Apr;30(4):619–623. discussion
Moriki A, Mori T, Makino A, Suzuki K, et al: The successful treatment of two carotid cavernous fistula cases using the Gamma Knife. Acta Neurochir (Wien) 122:140, 1993.
And These are the main references for this study. That’s all, and finally, I’d be happy to answer any questions you have. 14
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