1. CT-based imaging for stereotactical neurosurgery planning
Kharkiv National University of Radioelectronics
Department of Biomedical Engineering
CT-based imaging for stereotactical neurosurgery planning
M. Tymkovych, O. Avrunin, V. Pyatikop
French-CERN-Ukrainian Workshop on Medical Physics and Imaging
Kharkiv 2017

2. Neurosurgical Interventions
– Diseases (Parkinsons, epilepsy, local tumors and other);
– Dangerous;
– Experience;
– Unpredictability.
CT-based imaging for stereotactical neurosurgery planning

3. CT-based imaging for stereotactical neurosurgery planning
Stereotaxy History
Zernov apparatus (1889)
Horsley & Clarke (1908)
CT-based imaging for stereotactical neurosurgery planning

4. CT-based imaging for stereotactical neurosurgery planning
CT Imaging
Axial slice
Siemens CT apparatus
CT-based imaging for stereotactical neurosurgery planning

5. CT-based imaging for stereotactical neurosurgery planning
Modern Stereotaxis
Frame systems
Frameless stereotaxis
CT-based imaging for stereotactical neurosurgery planning

6. Planning Software
Stealth (Medtronic)
Leksell SurgiPlan (Elekta)
Stereotactic Planning Software (BrainLab)
Neuroinspire (Renishaw) 6
CT-based imaging for stereotactical neurosurgery planning

7. Main Stages of Operative Planning
CT-based imaging for stereotactical neurosurgery planning

8. Image processing tasks
Intracerebral landmarks determination;
Cranial landmarks determination;
Brain segmentation.
CT-based imaging for stereotactical neurosurgery planning

9. Intracerebral landmarks
CA – commissura anterior;
CP – commissura posterior ;
V3 – third ventricle;
Om – orbito-metal plane.
CT-based imaging for stereotactical neurosurgery planning

10. Intracerebral landmarks
slices СА СP 10
CT-based imaging for stereotactical neurosurgery planning

11. Segmented Ventricular system
Example
Ventricle
region
Initial slice
Head region
Segmented Ventricular system
Third
ventricle position

12. Densitogram analysis of skull borders
I1,I2 – intensity;
R – sharpness.
Parameter
R, r.u/mm.
Internal border
0.28
External border
0.5
It is advisable to use the inner boundaries of the skull as skull marks 12
CT-based imaging for stereotactical neurosurgery planning

13. CT-based imaging for stereotactical neurosurgery planning
Illustration of the navigation binding of the intracerebral coordinate system to the cranial landmarks 13
CT-based imaging for stereotactical neurosurgery planning

14. Trajectory of surgical access
An trajectory of surgical access
Blood vessel
target 14
CT-based imaging for stereotactical neurosurgery planning

15. The indices of risk of damage (IDSΣ) of anatomical and functional structures
Anatomical or functional structure or region
IDSΣ
External objects of the scan area
(air, navigation marks, the head fixation
elements)
The air in the paranasal sinuses 1
Ventricles, CSF 2
Bone structures 3
Gray and white matter of the cerebral
hemispheres 4
The nuclei of the diencephalon 5
Internal capsule 6
Nucleus of the hypotalamus and brain stem 7
Blood vessels 8 15
CT-based imaging for stereotactical neurosurgery planning

16. Determination of risk indices of damage (IDSΣ)
Slice CTA
Anatomical Atlas
3D map of
Illustration 16
CT-based imaging for stereotactical neurosurgery planning

17. CT-based imaging for stereotactical neurosurgery planning
Anatomical atlases
Item Id
Structure
Emptiness 1
Left Cerebellum.Posterior Lobe.Inferior Semi-Lunar Lobule.Gray Matter 69
Right Cerebellum.Sub-lobar.Fourth Ventricle.Cerebro-Spinal Fluid 71
Left Brainstem.Pons
191
Left Cerebrum.Frontal Lobe.Inferior Frontal Gyrus.Gray Matter.Brodmann area
273
White Matter.Optic Tract
438
Right Brainstem.Midbrain.Thalamus.Gray Matter.Medial Geniculum Body
Talairach atlas
CT-based imaging for stereotactical neurosurgery planning

18. Computed Tomography Angiography
3D Visualization
Axial slice
CT-based imaging for stereotactical neurosurgery planning

19. Slice classification task
CT-based imaging for stereotactical neurosurgery planning

20. Slice classification task
CT-based imaging for stereotactical neurosurgery planning

21. Preliminary traitement
CT-based imaging for stereotactical neurosurgery planning

22. Features extraction for slice classification
а, b – semiaxes of ellipses.
Ellipse model
hr – local histogram of region r;
Fr – feature of region r. Rm
CT-based imaging for stereotactical neurosurgery planning

23. CT-based imaging for stereotactical neurosurgery planning
Feature example
CT-based imaging for stereotactical neurosurgery planning

24. The CT-slices classification scheme
The part of training set
The graphical representation of the position of slices
The graphical representation of state machine for CT-slices classification
CT-based imaging for stereotactical neurosurgery planning

25. Logistic regression with respect to the classification
– logistic function;
θ – vector-column of regression parameters;
x – vector-column of independent paramters (x0=1);
n – number of independent variables.
m – number of elements in the training set;
y(i)– classification answer і from the training set.
– probability of transition from state 1 to 2.
θ regression parameters S1S2 θ0 θ1 θ2 θ3 θ4 θ5 θ6 θ7 θ8 θ9
θ10
θ11
θ12
-0.04
-0.02
-0.31
-0.15
-0.03
0.11
0.28
0.37
-0.01
θ13
θ14
θ15
θ16
θ17
θ18
θ19
θ20
θ21
θ22
θ23
θ24
θ25
0.02
0.03
-0.11
CT-based imaging for stereotactical neurosurgery planning

26. Optimal trajectory calculation
Trajectory of surgical access:
where n – is element of trajectory;
x(n),y(n),z(n) – coordiantes of element-n of trajectory;
xM,yM,zM – coordinates of target;
xT,yT,zT – coordiantes of intact point;
Δt – step.
Invasiveness function:
where m – number of surgical access;
N – count of elements in the trajectory.
Optimal trajectory: 26
CT-based imaging for stereotactical neurosurgery planning

27. 3D Visualization 3D Map of risks
Risk visualization in the form of a hemisphere
– low risk;
– high risk; 27
CT-based imaging for stereotactical neurosurgery planning

28. Surgical Instrument
V – volume of surgical access
l – length of trajectory of surgical access.
Appearance of surgical instrument
Shematic representation of surgical instrument
– access is not possible. 28
CT-based imaging for stereotactical neurosurgery planning

29. Illustration of stereotactic calculations using the trajectory planning tool for neurosurgical interventions
Axial CT cut at zero stereotaxic plane
Axial CT-slice at the level of the surgical intervention
3D Map of Risks
CT-based imaging for stereotactical neurosurgery planning

30. Illustration of stereotactic biopsy of a tumor of thalamic localization
Topogram in the sagittal projection
CT-slice at the distal side of the instrument
3D Map of risks
CT-slices along the surgical instrument
CT-based imaging for stereotactical neurosurgery planning

31. Steps of virtual modelling
Turn the carriage at an angle of 23 ° in the frontal plane
Position of the surgical instrument after penetration by 50 mm
The starting position of surgical instrument
Turn the frame by 11 ° in the sagittal plane
CT-based imaging for stereotactical neurosurgery planning

32. CT-based imaging for stereotactical neurosurgery planning
Conclusion
– CT is an indispensable method for surgical guidance for stereotaxis;
– The development of planning systems requires the use of increasingly sophisticated methods of image analysis;
– Necessary to use: machine learning, computer vision techniques, more training datasets, new methods of imaging...
CT-based imaging for stereotactical neurosurgery planning

33. CT-based imaging for stereotactical neurosurgery planning
Cooperation
Kharkiv National University of Radioelectronics, Department of Biomedical Engineering
Kharkiv National Medical University, Department of Neurosurgery
Kharkiv Regional Clinical Hospital, Depertment of Neurosurgery
CT-based imaging for stereotactical neurosurgery planning

34. Thank you for attention!
Maksym Tymkovych
International
Neuroscience Institute,
Hannover, Germany