Magnetic resonance imaging (MRI) provides advantages over computed tomography (CT) for radiation treatment planning by better demonstrating soft tissues and tumors, depicting physiological motion, and differentiating pathological from normal tissues. However, MRI does not provide electron density information needed for dose calculations. To overcome this, treatment planning systems can fuse MRI and CT images after registration. Image segmentation delineates structures on MRI, while registration matches images from different modalities. After registration, image fusion combines information from MRI and CT for treatment planning.

1. GONO BISHWABIDYALAY
Dept. of Medical Physics and Biomedical engineering
RADIATION TREATMENT PLANNING(MPBME-322)
MAGNETIC RESONANCE IMAGING IN TREATMENT PLANNING
SUBMITTED BY SUBMITTED TO
MOHAMMAD ULLAH SHEMANTO(Roll:328) ABU KAUSAR
MD TARIKUL ISLAM(Roll:327) TEACHING ASSISTANT
MD ROBIUL ISLAM(Roll:329) DEPT. OF MPBME
JANNATUL FERDUSY SOMA(Roll:338) GONO BISHWABIDYALAY

2. Magnetic resonance imaging (MRI) is a type of scan
that uses strong magnetic fields and radio waves to
produce detailed images of the inside of the body. An
MRI scanner is a large tube that contains powerful
magnets. You lie inside the tube during the scan.
MR imaging plays an increasingly more important role
in treatment planning
Magnetic resonance imaging (MRI)

3. Advantage of MRI in treatment planning
The advantage of MRI compared with CT is its ability to
better demonstrate and characterize tumors and soft
tissue.
MR images are primarily used to outline the tumor volume
and organs at risk, but can also provide information on the
excursion of relatively mobile organs and tissues in the
presence of physiological motion.
MR images differentiate pathological tissues from normal
tissues and provide good anatomical delineation.

4. Advantage of MRI in treatment planning
Tumors within the brain stream and tumors centered at bony
prominences such as spinal cord are better defined.
Another feature of MRI is that owing to the method of data acquisition
the slice orientation is not required to be trans axial as it is for CT but
can be sagittal, coronal, or at any oblique angle desired. This enable
images to be better aligned with anatomy. However most radiotherapy
planning software still assumes that images are acquired in the
transverse plane, and it may be a while before this particular feature of
MRI can be optimally utilized.
Contrast between healthy and malignant tissue can be obtained from
differences in the T1 and T2 relaxation times exploited by using the
appropriate imaging sequences.

5. Advantage of MRI in treatment planning
The use of MR contrast agents such as Gadopentetate dimeglumine
may further enhance visualization of the tumor under investigation.
Organs at risk (OARs) such as rectum and bladder are also generally
well delineated, and therefore help identify the regions in which
minimized doses are desired in the radiotherapy plan.
In the CT scan it is hard to identify the boundaries of the prostate,
whereas in the MR image not only the prostate boundary but also a
good deal of the internal structure of peripheral zone and central
gland is observed.
MRI can also provide physiological and biochemical tumor
information.

6. Problems with the use of MRI in treatment planning
ELECTRON DENSITY INFORMATION: MRI does not provide a direct
measurement of electron density. Although the latter can be estimated
from MR images it is most common to perform both MRI and CT
examinations in the treatment position and to fuse both datasets after
registration. The combined CT-MR dataset contains both the information
required for targeting (MRI-based volumes) and for dose calculations (CT-
based electron density).
IMAGING OF BONE: Cortical bone in MRI is shown as regions of very low
signal intensity. Bony boundaries and landmarks are not clearly visible on
MRI, which can limit image registration.
The physical dimensions of the MRI and its accessories may limit the use
of immobilization devices and compromise treatment positions.

7. Problems with the use of MRI in treatment planning
MRI is prone to geometrical artifacts and distortions that may affect the
accuracy of the treatment.
Bone signal is absent and therefore digitally reconstructed radio-graphs
cannot be generated for comparison to portal films.
To overcome these problems, many modern virtual simulation and treatment
planning systems have the ability to combine the information from different
imaging studies using the process of image fusion or co-registration. CT-MR
image co-registration or fusion combines the
• Accurate volume definition from MR with
• Electron density information available from CT.

8. Methods to allow the MRI in treatment planning
The lack of electron density information and the presence of MR distortion have meant that image
processing methods must be employed if MRI is to be utilized for treatment planning. once MR distortion
and radiofrequency non-uniformity effects have been quantified and corrected image segmentation and
image registration for correlation techniques can be used to overcome the lack of electron density data
from MR images .
IMAGE SEGMENTATION: The process of distinguishing structures or volumes from the background by
drawing contours is called segmentation. It is an important technique to differentiate abnormal and normal
tissue in MR image data.
Some MRI Tissue Segmentation Methods
• Point detection
• Line detection
• Edge detection
• Region based segmentation
• Thresholding

9. Example:
3D segmentation of the tumor, organs at risk and patient contour for the
treatment of a brain tumor.

10. MRI image segmentation technique

11. IMAGE REGISTRATION: The process of matching images
obtained from different imaging devices is called image registration
Simple 2D registration procedures include the use of a projection
systems with an appropriate magnification that allows MR images to
be superimposed over simulation films.
Registration methods in 3D are more complex and a multitude
parameters need to be considered.

12. There are a number of algorithms for 3D image registration:
1. Surface matching
2. Point matching
3. Mutual information based information

13. General procedure of image registration:

14. IMAGE FUSION
The next stage after the registration process is the wavelet based image fusion. Wavelets
are finite duration oscillatory functions with a zero average value. They can be described
by two functions the scaling (also known as the father) function, and the wavelet (also
known as the mother) function. A number of basic functions can be used as the mother
wavelet for Wavelet Transformations.

17. THANKS ALL FOR YOUR ATTENTION