Co-registration with MRI: Seeing Is Believing?

Co-registration with MRI: Seeing Is Believing?

Jing Cai, PhD Duke University Medical Center

2013 AAPM 55th Annual Meeting, Educational Course, Therapy Track, MOC SAM Program

Disclosure

I have received research funding from NIH, the

Golfers Against Cancer (GAC) foundation, and

Philips Health System.

Acknowledgements

Fang-Fang Yin, PhD

Brian Czito, MD

Jim Chang, PhD

Oana Craniunescu, PhD

Chris Willett, MD

Junzo Chino, MD

Justus Adamson, PhD

Yun Yang, PhD

Sheridan Meltsner, PhD

Juan Yang, BS

Beverly Steffey, MS

Kevin Kelley, BS

Xiaodong Zhong, PhD

Duke Radiation Oncology Duke Medical Physics Program

Yilin Liu, BS

Xiao Liang, BS

Qijie Huang, BS

Siemens

Mustafa Bashir, MD

Duke Radiology

• Advantages of MRI

Contrast, Motion, Function

• Challenges

Variation of contrast, Low resolution, Distortion

CT/MRI registration (immobilization, BH)

4D-MRI

MRI-MRI registration (pre/post)

MRI-PET, MRI-LINAC

Artifacts in MRI (general, HDR, markers)

Multi-scans

• Future

Items

In this study, co-registration and subsequent 3- dimensional visualization were evaluated for high-resolution CT and MRI of the temporal bone. An iterative, manual, retrospective, intrinsic and rigid approach for co-registration resulted in highly accurate and feasible multimodality images.

consistency registration error was 0.6 mm (95% CI = 0.52–0.68 mm).

An experimental software package (3D-Slicer, Surgical Planning Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, www.slicer.org)7 was used for image co-registration and 3-D data visualization.

Superior Soft-Tissue Contrast

CT MRI-T2

S. A. Schmitz, et al. ACTA RADIOLOGICA, 2006

MRI Simulation

CT MRI – T2-w

CT MRI - LAVA+C

Lung

Liver

Motion

Ca

se

1

Ca

se

2

Motion Verification

4D-MRI: Patient Example

Tumor CNR: 20.1 in 4D-MRI, 2.5 in 4D-CT.

Cord

Liver

Right kidney

ITV4D-

CT

ITV4D-MRI

Tumor ITV: 54.0cc in 4D-MRI and 104.8cc in 4D-CT.

Function-based Planning

Functional Map

Conventional Planning

Function-based Planning

Cai et al. Helical Tomotherapy Planning for Lung Cancer Based on Ventilation Magnetic Resonance Imaging. Medical Dosimetry, Volume 36, Issue 4, Winter 2011, Pages 389–396

Slobodan Devic, Medical Physics, 39 (11), 2012

Generally speaking the image coregistration (sometimes erroneously called image fusion) is the process of transforming different sets of image data into one coordinate system. In the case of the incorporation of the MR images to the RTP process, the MRI dataset has to be transformed into the coordinate system of the CT images. During the process of image coregistration the primary dataset (CT images) stays unchanged and it is the secondary dataset (MR images) that is changed in order to match the anatomy of the primary data set (Fig. 1).

► Manual or interactive image registration is guided by visual indication of image alignment. The conventional visual representation of an 3D images is 2D-based, three orthogonal planar views of cross-section of the volumetric image.

► anatomy-based image, fiducial-based, coordinate-based

► All clinical treatment planning systems utilize this visual representation for checking and adjusting the alignment of two images. In details, there are several means to achieve the visual alignment verification: (1) the chess-box display of two images in alternate boxes; (2) the simultaneous display of two mono-coloured images; and (3) the superimposed display of the two images with an adjustable weighting factor.

► However, reports have shown that this 2D visual-based fusion technique may suffer from (1) large intra- and inter-observer variability; (2) the dependency of user’s cognitive ability; (3) limited precision by the resolution of imaging and image display; and (4) time consuming in verifying and adjusting alignment in three series of planar views in three orthogonal directions

► Although automatic rigid image registration using mutual information has been widely accepted in radiotherapy clinic, the necessity of visual verification of the result prior to clinical use will never change. Several causes for a sub-optimal automatic registration result include (1) changes in patient’s anatomy between scans; (2) incomplete or insufficient anatomy, especially in biological images; (3) poor image quality, and (4) incorrect (local traps) or insensitive (flat surface) registration outcomes. Visual verification and adjustment allow user to check and correct any misalignment in the auto-registered images.

► The 2D visual-based fusion technique has been reported to have large inter-/intraobserver variations, single pixel precision, and time-consuming Our study indicates that the 2D technique tends to produce a sizable, unrealized registration error of 1.8 ±1.2 and 2.0±1.3 mm,

as shown in Table 2.

Li, et al, IJROBP, 2005

Li, et al, IJROBP, 2005

automatic MMI registration

Slobodan Devic, Medical Physics, 39 (11), 2012

Brain SRS, Misregistration

SRS for Acoustic Neuroma: Slightly misregistration between CT and MRI after automatic CT-MRI imaging fusion might lead to possible discrepancy of targeting in Brain SRS for AN

CT-MRI fusion is corrected to ensure precise targeting in Brain SRS for AN

3D Image-guided Brachytherapy

Example of midsagittal CTV motion within 16 min for registration of the bony anatomy between (a) the first and (b) the fourth sagittal scan of a single MRI exam. The CTV is delineated in white on both scans.

Ellen M. Kerkhof et al. Intrafraction motion in patients with cervical cancer: The benefit of soft tissue registration using MRI. Radiotherapy and Oncology Volume 93, Issue 1, October 2009, Pages 115–121

Linda van de Bunt, et al. Motion and deformation of the target volumes during IMRT for cervical cancer: What margins do we need? Radiotherapy and Oncology 88 (2008) 233–240

Fig. 2. (a) The pre-treatment GTV (red) and four GTVs at later time points (week 1: yellow, 2: light blue, 3: green, 4: magenta). The generic PTV is shown around the pretreatment GTV (dark blue); (b) analogous for the CTV.

Phantom Images

Patient Images

Question: Which of the following is NOT an advantage of MRI scan over CT scan?

20%

20%

20%

20%

20% 1. Spatial accuracy

2. Superior soft-tissue contrast

3. No radiation hazard

4. Flexible imaging orientation

5. Richness in various contrast

10

Discussion

References: Slobodan Devic, “MRI simulation for radiotherapy treatment planning.” Medical Physics, 39 (11), 2012. Metcalfe P, Liney GP, Holloway L, Walker A, Barton M, Delaney GP, Vinod S, Tome W. “The Potential for an Enhanced Role For MRI in Radiation-therapy Treatment Planning.” Technol Cancer Res Treat. 2013 Apr 24. [Epub ahead of print]

Correct Answer: 1. Spatial accuracy

Question: Which of the following factors contribute to the distortion of MR images?

20%

20%

20%

20%

20% 1. Magnet field inhomogeneity

2. Patient

3. Nonlinearity of the gradients

4. Localization frame

5. All of above

10

Discussion

Reference: Moerland MA, Beersma R, Bhagwandien R, Wijrdeman HK, Bakker CJG, “Analysis and correction of geometric distortions in 1.5 T magnetic resonance images for use in radiotherapy treatment planning,” Phys. Med. Biol. 40, 1651–1664 (1995).

Correct Answer: 5. All of above

Question: What should be aimed to match when performing the MRI-CT registration in 3D MR-assisted cervical cancer brachytherapy?

20%

20%

20%

20%

20% 1. Anatomy

2. Point A

3. Point B

4. Applicator

5. Bony structures

10

Discussion

Reference: Hellebust TP, Kirisits C, Berger D, Pérez-Calatayud J, De Brabandere M, De Leeuw A, Dumas I, Hudej R, Lowe G, Wills R, Tanderup K; Gynaecological (GYN) GEC-ESTRO Working Group. “Recommendations from Gynaecological (GYN) GEC-ESTRO Working Group: considerations and pitfalls in commissioning and applicator reconstruction in 3D image-based treatment planning of cervix cancer brachytherapy.” Radiother Oncol. 96(2):153-60 (2010).

Correct Answer: 4. Applicator

High Resolution MRI

MRI for Image Guidance

Fully integrated whole body PET/MR system using a split gradient coil. Source: Philips

Siemens introduced its works-in-progress PET/MRI scanner at RSNA 2010

Andreas Boss, et al. Hybrid PET/MRI of Intracranial Masses: Initial Experiences and Comparison to PET/CT, THE JOURNAL OF NUCLEAR MEDICINE • Vol. 51 • No. 8 • August 2010, 1198-1205

The system consisted of an MRI-compatible PET system (BrainPET; Siemens) inserted into a slightly modified 3.0-T whole-body MRI scanner (Magnetom Tim Trio; Siemens Healthcare)

Philips introduced its 510(k)-pending hybrid PET/MRI system Gecombineerde PET-MRI scan in het VUMC in Amsterdam

A Philips PET/MRI scan showing a breast cancer lesion from a study by the University of Geneva.

Source: Habib Zaidi, PhD, head of the PET Instrumentation and Neuroimaging Laboratory, Geneva University Hospital.

World’s first human brain images scanned with a PET/MRI hybrid system.

The work-in-progress PET/MRI system is installed at Siemens: A PET scanner, integrated in a standard Siemens 3T Magnetom Trio MRI unit. The combined system is used for cranial scans and has a spatial resolution of 3mm, an axial FOV of 19 cm and an transaxial FOV of 30 cm.

PET-MRI

Summary

MR has many advantages over CT and is potentially an important modality for RT

Various uncertainties exist in MR-CT co-registration

Understanding root causes and characteristics of these uncertainties is important for successful MR-CT co-registration

Next generation of MRI guidance techniques has the potential to minimize uncertainties