1. Tmaptool3D – T1ρ processing tool Presented by Chetana Bayas Gargi Pednekar Guruprasad Krishnamoorthy

2. Background & AIM What is an MRI? What is cartilage and OA? What is an T1rho weighted imaging? What is new? Why software? http://www.jointimplant.com/patient-education/knee/diagnosing-knee-pain/ http://www.hss.edu/osteoarthritis-diagnosis.asp Borthakur, A., et al. (2006). "Sodium and T1ρ MRI for molecular and diagnostic imaging of articular cartilage." NMR in Biomedicine 19(7): 781-821

3. Background & AIM http://www.jointimplant.com/patient-education/knee/diagnosing-knee-pain/http://www.hss.edu/osteoarthritis-diagnosis.asp Borthakur, A., et al. (2006). "Sodium and T1ρ MRI for molecular and diagnostic imaging of articular cartilage." NMR in Biomedicine 19(7): 781-821 Articular Cartilage (AC) is a thin connective tissue present in Synovial Joints like Knee Osteoarthritis (OA) is degenerative disease that can affect AC. T1rho (Spin-lattice relaxation in rotational frame) is one of the MRI Imaging techniques that can be used to diagnose OA at a very early stage by imaging molecular integrity of the cartilage Our aim is to develop a comprehensive tool to process T1rho weighted MRI images acquired at isotropic resolution SI = M 0 *

4. Processing Pipeline Saved results (Images,.mat files and document) Allow user to view the processed images and fine tune Allow user to draw ROIs on reformatted images and process Create MPR to allow interactive reformatting Read DICOM images from folder Organize Raw data from CD

5. CD sorting and reading DICOM files Saved results (Images,.mat files and document) Allow user to view the processed images and fine tune Allow user to draw ROIs on reformatted images and process Create MPR to allow interactive reformatting Read DICOM images from folder Organize Raw data from CD Important Functions used Uigetdir() Dir() Dicominfo() Sprintf() Makedir() Regexprep() Copyfile() Dicomread()

6. Reformatting and Processing Saved results (Images,.mat files and document) Allow user to view the processed images and fine tune Allow user to draw ROIs on reformatted images and process Create MPR to allow interactive reformatting Read DICOM images from folder Organize Raw data from CD Important Functions used flipud() rot90() imagesc() Line() Roipoly() Imdilate() improfile() Uicontrol properties Axes properties Windows button-down functions MEX file SI = M 0 *

7. Display results and save Saved results (Images,.mat files and document) Allow user to view the processed images and fine tune Allow user to draw ROIs on reformatted images and process Create MPR to allow interactive reformatting Read DICOM images from folder Organize Raw data from CD Important Functions used Fopen() Fprintf() Fclose() Saveas() Imagesc() Ind2rgb() Imadjust() Makedir()

8. Challenges faced and learnings Challenges: Understanding the physics of MR Imaging and workflow Integration of different levels of project Reformatting Understanding the DICOM attributes MATLAB compromises the speed We cannot validate the results as of now due to the novelty Learnings: Image processing technique Designing User Interface Team work!

9. Acknowledgement and References We would like to extend our gratitude towards Prof. Ahmet Sacan for his support and guidance. We would also like to thank Prof Ravinder Reddy, Center for Magnetic Resonance and Optical Imaging, University of Pennsylvania for allowing us to use the facilities and for his guidance.

10. References: Borthakur, A., et al. (2006). "Sodium and T1ρ MRI for molecular and diagnostic imaging of articular cartilage." NMR in Biomedicine 19(7): 781-821. Cohen, Z. A., et al. (1999). "Knee cartilage topography, thickness, and contact areas from MRI: in-vitro calibration and in-vivo measurements." Osteoarthritis and Cartilage 7(1): 95-109. http://dicom.nema.org/ www.mathworks.com/support