The Emerging Technique of Using Diffusion Tensor Imaging to Perform Muscle Fiber Tracking - Report Example

Students’ name: Institution: Date: 1. Discuss the emerging technique of using diffusion tensor imaging (DTI) to perform muscle fibre tracking. 1.1 Briefly describe the basic theory of diffusion tensor MR imaging DT – MRI uses the rate of water diffusion between cells to collect information regarding the internal structures of the human body (Barboriak 2011). The rate of diffusion varies depending on the body structures, with each structure having a definite rate of diffusion. Using this difference, the DT-MRI can be used in collecting various information about various body parts and create a map of various structures within the body. The application of this technology has been mainly applied in the study of brain; however, the applicability can also be extended to different body parts (Osborn 2010). The science used in diffusion tensor imaging is often considered complex, however, it can be simply described as the agitation of molecules using electromagnetic radiation and then records made in response to the release of energy released. The produced data is then analyzed in regards to the known rates of diffusion around different body tissues resulting into a map of structures such as the nerves and muscles among others (Bussmann, Lorenz & Hodler 2012). It thus creates a wiring structure of the entire body allowing for ease visualization of various parts. 1.2 Basic concepts of diffusion tensor visualization techniques Under the paradigms of any biological system, water molecules often undergo a continuous random motion, the rate at which the water particles diffuse across the biological structures can give a sign on the nature of structures within the underlying tissues. The rate of diffusion is in some instances faster in some directions as compared to others (Osborn 2011). Diffusion rate can be calculated using the diffusion weighted MRI; the anatomical scalar field and a 2D diffusion tensor image that are created are often used to calculate seven values at each spatial location (Ciccarelli 2012). The images herein contain several interrelated components hence making it hard to visually represent the images. DT- MRI image (Charles 2008) Majorly, there are two techniques that have always been used in visualizing diffusion tensor data; these are a series of image based method in which case a voxel value represents a local anisotropy measure and a 3D rendering of the images or surface rendering through isosurface. The other method is the use of group symbolic display methods using different types of glyph most of which includes ellipsoid. The recent research has also proved that diffusion tensor imaging of white tissues can best be measured using tractography (Panin et al. 2013). It provides best means and methods for analyzing and visualizing white matter fiber tracts. Illustration of white matter tract in brain (Image courtesy of http://emedicine.medscape.com/article) 1.3 Diffusion-tensor MRI-based skeletal muscle fiber tracking Muscle architecture mostly influences the manner in which the skeletal muscles perform their functions. The geometric properties and the internal organization of these factors are among the most influential aspects that are mostly placed under consideration. The diffusion tensor MRI fiber tracking offers a noninvasive analysis of the muscle structure with the help of 3D sensitivity (Lee 2012). Relatively, there are a number of technological advancements that have been brought in the muscle fiber tracking technology; such changes include definition of seed points to be used in fiber tracking, quantitative characterization of muscle architecture, implementation of denoising procedures and testing of the repeatability and validity of the data. There are three levels of biological organization; these are the in vivo, molecular cellular and the tissue organ. The in vivo scale is often considered the topmost within the muscle structural hierarchy and is often depicted with muscle placement around the body (Lee 2012). Muscles normally extend from their regions or points of origin to the end point which is the point of insertion. The muscles’ forces and line of action are normally defined by the point of origin and the points of insertion (Ciccarelli 2012). The molecular cellular, on the other hand, has properties that make it easy for cell geometry to be made using the measurements obtained from water diffusion. The human skeletal muscle ranges between 4 to 40 cm in length and their cross section takes the shape of oblate polygons with a range of approximately 20 to 90 µm across the sections. Plasma membrane binds them together. Relatively, there are traditional methods that have always been used in the study of muscle architecture. On of these methods is the cadaver dissection which makes it easy to measure the fiber length as well as the muscle mass. After these measurements, an inclusive database is then formed to allow for easy study of the relationship between fascicle length and the structural parameters such as sarcomere length that plays a significant role in the determination of the muscle’s force potential (Demir et al. 2013). While dealing with skeletal muscles, the DTI indices often reflect intercellular space diffusion of water. This is attached to the fact that the intracellular space comprises of nearly 85% of free water signal. This principle, however, holds out in cases where the echo time is short and the T2 of the intracellular water is also short. More studies also suggest that mitochondria and sarcoplasmic instead of the cell membrane are the main intracellular structures which limit disarticulation in orientation dependent manner (Rovaris 2011). Diffusion MRI has been largely used in the study of brain rather than the skeletal muscles. Most studies have been performed using DW-MRI to assess the levels if water distribution in muscles during exercises. Such studies have pointed out that exercises result in increased T2. Moreover, it was also evident from various studies that exercise results in an increase in both the T2 and the ADC values and there is also a fast recovery of T2 vis a vis ADC after exercising the muscles. Looking at the analysis above, it is evident that the role played by DT- MRI in analyzing the skeletal muscle fiber is important and offers a proper and in-depth analysis of the structures under study. 1.4 Limitations of diffusion tensor imaging (DTI) to perform muscle fibre tracking 1.4.1 Advantages Despite the high levels of success in the use of diffusion Tensor imaging has a number of benefits and limitations that could be attributed to its use. Some of the benefits attributed to this type of Magnetic Resonance Imaging include the following: Diffusion tensor imaging provides much information regarding brain than the normal conventional MRI machine (Flanders 2009). This makes it easy to study various aspects of the brain and achieve the desired outcome. Offers in-depth analysis of internal body structures: most body structures are not easy to study using the normal body scanning methods; however, DT- MRI offers an intensive study into the body structures and can easily differentiate between the body structures (Rovaris 2011). Little side effects: since the analysis mainly involves the agitation of water molecules in the body, this method has often been the safest causing least side effects to the patients under study. It is thus safe as compared to other scanning methods such as x-rays that may have adverse effects on the patient gradually. 1.4.2 Limitations Facilities offering the diffusion tensor MRI are not many and, therefore, many patients often find it difficult and costly to access these facilities. As a result, others who cannot afford these services are forced to get other alternatives that in the long run is likely to affect their health. The Diffusion Tensor imaging is only applicable to individuals who do not have metallic substances in their bodies. MRI uses electromagnetic waves that have adverse effects on metallic objects in a patient’s body. Therefore, persons with metallic substances inscribed in their body may not achieve the desired results for analysis of their conditions. The patient is required to be still during the process hence performing the imaging process on young children may not be easy, leading to poor results (Flanders 2009). Images produced may not represent the actual structures required during imaging. 2. Discuss current and emerging MRI techniques used in the imaging of cartilage. Suggest a grading system that could be used to describe cartilage damage. 2.1 The current MRI techniques used in the imaging of cartilage MRI has emerged to be the leading method of acquiring soft tissue images and structures around the body joints. MRI currently applies a number of contrast mechanisms to obtain proper images for the structures under study; some of these mechanisms include the use of Proton density, 2D v or multisliced T1 weighed T2 weighted imaging that has or lacks fat suspension among others. The imaging software and hardware have evolved over time and such include provision of improved radiofrequency coils and gradients, fast spin echo imaging and other techniques such as water the water only excitation (Neri, Caramella &Bartolozzi 2008) Despite the fact that tissue relaxation time and the imaging parameters are the main determinants of the existing contrast between the lipid and the nonlipid tissues, lipid suppression increases the existing contrast between the lipid and the nonlipid containing tissues. Another option that is normally used is the spectral- spatial excitation in which case water is made to spin in the slice and then exited (Yankeelov 2012). 2.1.1 2D fast spin echo imaging In the current scene, the imaging of the musculoskeletal system using MRI is limited to the 2D multi- slice acquisitions got through multiple planes. This MRI, method, is done using the fast spin echo methods. The methods have a history of providing excellent SNR and the existing contrast between these tissues. However, the inherent anisotropic voxels used in the 2D acquisitions need that multiple planes of data be got so as to reduce any partial volume artifacts. These techniques help in provision of excellent results in terms of detection of cartilage lesions (Neri, Caramella &Bartolozzi 2008). There is, therefore, an excellent depiction of structures within the imaging plane, however, evaluation of small structures may be quite challenging. The FSE techniques offer excellent detection of the cartilage lesions hence resulting into quality images. Images showing multiple planes of FSE (Yankeelov 2012) A- Corona T1- weighed fast spin echo imaging presents an image cartilage loss on the medial femoral condoyle. B- Corona T2- Weighed fast spin echo imaging achieved through fat saturation and cartilage loss saturation. C- Represents sagital intermediate weighted FSE picture showing full thickness cartilage loss. D- Represents sagital T2- weighted fast spin echo with fat saturation representing full thickness loss of cartilage. 2.1.2 3D gradient echo technique The 3D gradient echo techniques have the ability to obtain data with more isotropic voxel sizes, however, this approach offers little imaging contrast as compared to the spin echo approaches (Ristow 2011). The 3D SPGR has shown high accuracy in terms of cartilage lesion imaging. This approach, however, has a few disadvantages, which include poor or lack of proper contrast between the fluid and cartilage which reveals the surface outlines and defects. The SPGR also uses radiofrequency and gradient hence reducing the achieve and artifacts near T1; this results in the reduction of the overall signal as compared to the ready state techniques. The SPGR techniques may also be combined together with fat- water separation means like iterative decomposition of fat and water using echo asymmetry estimation (Ma 2008). This fat-water separation offer high quality excellent fat and water images that have high resolution, and may go up to 0.3 x 0.3 x 1.0 mm. The 3d gradient echo techniques have also been observed to be less useful in the diagnosis of the meniscal or ligament tears as compared to the spin echo techniques. However, in the face of all these limitations, 3D SPGR remains to be the standard morphologic cartilage imaging procedure (Ristow 2011). (Ryan 2008) A- Represents a spoiled gradient and shows a dark synovial fluid. B- Represents a gradient recalled echo-image achieved without using radiofrequency hence spoiling results for T1/T2. 2.2 The emerging MRI techniques used in the imaging of cartilage. New MRI techniques are emerging over time, and these techniques are important in improving the quality of imaging produced by the MRI machine. Some of the emerging MRI techniques include the following: 2.2.1 Driven Equilibrium Fourier Transform Imaging (DEFT) DEFT was initially used as a method of enhancing signals in spectroscopy. This utilizes 90 degrees pulse in returning magnetization to the Z axis; in turn, this increases the signal from tissues that have long T1 relaxation times e.g. the synovial fluid (Ryan 2008). Unlike the traditional T1 and T2 MRI, DEFT contrast is dependent T1/T2 ratio of the weighted MRI. As compared to SPGR, DEFT offers a higher cartilage to fluid contrast hence making it a very efficient in imaging. This technique has not yet been fully proven hence not yet applicable in the process of imaging (Majumdar 2010) During musculoskeletal imaging, DEFT often offers a contrast hence improving the signal obtained from the synovial fluid instead of using the signals obtained from the T2 weighted sequences. In the end, a bright synovial fluid is observed at TRs. DEFT has also been observed to great contrast of cartilage to fluid. DEFT imaging has been blended with 3d echo planar to increase its 3D cartilage efficiency; in addition, an image of approximately 512 x 192 x 14 cm can be got in six minutes (Neri, Caramella &Bartolozzi 2008). (DEFT) image with fat saturation (Ryan 2008) 2.2.2 Balanced SSFP imaging This is a high signal and efficient means of obtaining 3D MR images. The efficiency of this method, however, depends mainly on the manufacturer of the MRI scanner. The method is considered fast imaging procedure and offers a balanced field echo. Through the recent advances in magnetic resonance, this method can be applied without any effects from off-resonance or banding. Multiple BSSFP acquisitions may be used in achieving high-resolution imaging but at the cost of extra scanning time (Majumdar 2010). This method is not yet applied, but has been proven possible means of obtaining high-resolution images. However, balanced SSFP imaging is still one of the major problems since TR have a tendency of increasing. The TR is therefore often kept under 10 milliseconds using these techniques and therefore limiting the overall image resolution. (Majumdar 2010) A – Depicts water image B – Depicts fat image 2.2.3 Vastly Interpolated Projection Reconstruction Imaging (VIPR) VIPR was originally meant for the time resolved CE-MRA, and then later on was adapted for BSSFP imaging in the musculoskeletal system. This method allows collection of two radial systems for the TR without time wastage on the frequencies. The radial lines are observed to begin at the k-space and the other line is obtained from the return path leading to the origin. It also offers the optimal TR that is needed to achieve the most efficient linear combination of the bSSFP in the fat water separation, which can as well be achieved while maintaining time for the adequate spatial encoding (Ristow 2011). This method operates on the basis of SSFP, hence using a joint fluid that is bright and giving proper contrast that helps in diagnosing the meniscal tears, cartilage damages and ligament injuries. The contrast occurring between the cartilages and bone is produced by separation of fat and water using linear combination SSFP. Alternatively, single pass method can be used to separate water and fat by in depth analysis of the different phase progressions. Vastly interpolated projection reconstruction (VIPR) (Ryan 2008) A- Corona image with B- Sagittal reformation C- Axial reformation D- VIPR k-space trajectory 2.2.4 3D fast spine echo image (FSE Image). The 3D fast spine imaging is another excellent clinical tool for imaging; however, FSE faces the problem of anisotropic voxels, partial volumes and slice gaps. 3D acquisition using FSE was applied many years ago; this method reduces parallel imaging and blurring hence reducing the imaging time (Ayache 2012). The images obtained from this technique offers a resolution with the ability to bring high quality multiplanar imaging. A recent study has revealed that 3D FSE is equivalent to various combination of 2D FSE planes during the diagnosis of menisci, ligament and cartilage defects (Ryan 2008). (Meyer 2007) A- Coronal image B- Sagittal reformation C- Axial reformation 2.2.4 High –Field MRI There are many centers today that posses the 7-T human MRI, these systems however are entangled with the problems of radiofrequency. Despite the above disadvantage, these systems posses a SNR advantage as compared to the lower strength systems (Ristow 2011). They therefore have the capability to achieve a higher resolution images within the shortest time possible, hence making the process significant in the study of cartilage infrastructure. Image showing high filed MRI (Majumdar 2010) 3.0 The suggestion of the grading system that could be used to describe cartilage damage The international cartilage repair society has developed an arthroscopic grading system, which can be used in assessing cartilage defects, and then ranked (Johnsons 2009). The grading system is as follows: Grade 0 – Healthy cartilage (Normal) Grade 1- Cartilage has soft spot or blisters Grade 2- minor tears in the cartilage Grade 3- presence of deep crevices in the lesions (over 50%) Grade 4 – tear on the cartilage exposes the bone beneath While measuring these defects, those less than 2 cm are considered small (Brown, Mark & Richard 2010). Despite the grading system, it worth noting that the point of damage could also have an influence on the symptoms exhibited. This grading system can be used in the description of cartilage damage and then proper medical interventions instituted in dealing with the cartilage damage (Neri, Caramella &Bartolozzi 2008). Works Cited Ayache, Nicholas. Medical image computing and computer-assisted intervention--MICCAI 2012 15th International Conference, Nice, France, October 1-5, 2012, Proceedings. Berlin: Springer, 2012. Print. Bader, Till R., Richard C. Semelka, Monica S. Pedro, Diane M. Armao, Mark A. Brown, and Paul L. Molina. "Magnetic resonance imaging of pulmonary parenchymal disease using a modified breath-hold 3D gradient-echo technique: Initial observations." Journal of Magnetic Resonance Imaging 15.1 (2012): 31-38. Print. Barboriak, Daniel P. "Imaging of brain tumors with diffusion-weighted and diffusion tensor MR imaging." Magnetic resonance imaging clinics of North America 11.3 (2011): 379-401. Print. Brown, Mark A., and Richard C. Semelka. MRI: basic principles and applications. 4th ed. Hoboken, N.J.: Wiley-Blackwell/John Wiley & Sons, 2010. Print. Bussmann, Lorenz, and Jürg Hodler. Diffusion tensor imaging of the median nerve at 3.0 tesla using different MR scanners: agreement of FA- and ADC-measurements. S.l.: [s.n.], 2012. Print. Ciccarelli, Olga. "Functional MRI, Diffusion Tensor Imaging, and MR Spectroscopy of the Spinal Cord in Multiple Sclerosis." International Journal of Clinical Reviews 13.45 (2012): 11- 17. Print. Demir, A., M. Ries, C. T. W. Moonen, J.-M. Vital, J. Dehais, P. Arne, J.-M. Caille, and V. Dousset. "Diffusion-weighted MR Imaging with Apparent Diffusion Coefficient and Apparent Diffusion Tensor Maps in Cervical Spondylotic Myelopathy." Radiology 229.1 (2013): 37-43. Print. Flanders, A.e.. "Pathogenesis of Normal-appearing White Matter Damage in Neuromyelitis Optica: Diffusion-Tensor MR Imaging." Yearbook of Ophthalmology 16.24 (2009): 204-205. Print. Johnsons, Ryan. "Evaluation of diffusion anisotropy in the human brain using MR diffusion tensor imaging." International Congress Series 1256.67 (2009): 1325. Print. Jung, Kwan-Jin. "Removal of partial volume averaging with free water in MR diffusion tensor imaging using inversion recovery for b0 image." Magnetic Resonance Imaging 3.24 (2014): 14. Print. Lee, Seung-Koo. "Diffusion Tensor and Perfusion Imaging of Brain Tumors in High-Field MR Imaging." Neuroimaging Clinics of North America 22.2 (2012): 123-134. Print. Ma, Jingfei. "A single-point dixon technique for fat-suppressed fast 3D gradient-echo imaging with a flexible echo time." Journal of Magnetic Resonance Imaging 27.4 (2008): 881-890. Print. Majumdar, Sharmila. Advances in MRI of the knee for osteoarthritis. Singapore: World Scientific, 2010. Print. Masutani, Yoshitaka, Shigeki Aoki, Osamu Abe, Naoto Hayashi, and Kuni Otomo. "MR diffusion tensor imaging: recent advance and new techniques for diffusion tensor visualization." European Journal of Radiology 46.1 (2013): 53-66. Print. Neri, E., D. Caramella, and C. Bartolozzi. Image processing in radiology current applications. Berlin: Springer, 2008. Print. Osborn, A.g.. "Distinction between postoperative recurrent glioma and radiation injury using MR diffusion tensor imaging." Yearbook of Diagnostic Radiology 2011 (2011): 305-307. Print. Panin, Vladimir Y, Gengsheng L Zeng, Michel Defrise, and Grant T Gullberg. "Diffusion tensor MR imaging of principal directions: a tensor tomography approach." Physics in Medicine and Biology 47.15 (2012): 2737-2757. Print. Provenzale, J. M., P. Mcgraw, P. Mhatre, A. C. Guo, and D. Delong. "Grading system for cartilage damage: Investigation of the international applicable standards." Cartilage damage 232.2 (2011): 451-460. Print. Ristow, Oliver. Isotropic 3D fast spin echo imaging versus standard 2D imaging at 3.0T of the knee: image quality and diagnostic performance. Lodon: Springer, 2011. Print. Rovaris, Marco, Federica Agosta, Elisabetta Pagani, and Massimo Filippi. "Diffusion Tensor MR Imaging." Neuroimaging Clinics of North America 19.1 (2009): 37-43. Print. Ryan, J. 50 Myocardial signal behaviors of balanced SSFP imaging at 3 T. Lodon: Springer, 2008. Print. Yankeelov, Thomas. Quantitative MRI in cancer. Boca Raton, FL: CRC Press, 2012. Print. Read More

Illustration of white matter tract in brain (Image courtesy of http://emedicine.medscape.com/article) 1.3 Diffusion-tensor MRI-based skeletal muscle fiber tracking Muscle architecture mostly influences the manner in which the skeletal muscles perform their functions. The geometric properties and the internal organization of these factors are among the most influential aspects that are mostly placed under consideration. The diffusion tensor MRI fiber tracking offers a noninvasive analysis of the muscle structure with the help of 3D sensitivity (Lee 2012).

Relatively, there are a number of technological advancements that have been brought in the muscle fiber tracking technology; such changes include definition of seed points to be used in fiber tracking, quantitative characterization of muscle architecture, implementation of denoising procedures and testing of the repeatability and validity of the data. There are three levels of biological organization; these are the in vivo, molecular cellular and the tissue organ. The in vivo scale is often considered the topmost within the muscle structural hierarchy and is often depicted with muscle placement around the body (Lee 2012).

Muscles normally extend from their regions or points of origin to the end point which is the point of insertion. The muscles’ forces and line of action are normally defined by the point of origin and the points of insertion (Ciccarelli 2012). The molecular cellular, on the other hand, has properties that make it easy for cell geometry to be made using the measurements obtained from water diffusion. The human skeletal muscle ranges between 4 to 40 cm in length and their cross section takes the shape of oblate polygons with a range of approximately 20 to 90 µm across the sections.

Plasma membrane binds them together. Relatively, there are traditional methods that have always been used in the study of muscle architecture. On of these methods is the cadaver dissection which makes it easy to measure the fiber length as well as the muscle mass. After these measurements, an inclusive database is then formed to allow for easy study of the relationship between fascicle length and the structural parameters such as sarcomere length that plays a significant role in the determination of the muscle’s force potential (Demir et al. 2013). While dealing with skeletal muscles, the DTI indices often reflect intercellular space diffusion of water.

This is attached to the fact that the intracellular space comprises of nearly 85% of free water signal. This principle, however, holds out in cases where the echo time is short and the T2 of the intracellular water is also short. More studies also suggest that mitochondria and sarcoplasmic instead of the cell membrane are the main intracellular structures which limit disarticulation in orientation dependent manner (Rovaris 2011). Diffusion MRI has been largely used in the study of brain rather than the skeletal muscles.

Most studies have been performed using DW-MRI to assess the levels if water distribution in muscles during exercises. Such studies have pointed out that exercises result in increased T2. Moreover, it was also evident from various studies that exercise results in an increase in both the T2 and the ADC values and there is also a fast recovery of T2 vis a vis ADC after exercising the muscles. Looking at the analysis above, it is evident that the role played by DT- MRI in analyzing the skeletal muscle fiber is important and offers a proper and in-depth analysis of the structures under study. 1.4 Limitations of diffusion tensor imaging (DTI) to perform muscle fibre tracking 1.4.1 Advantages Despite the high levels of success in the use of diffusion Tensor imaging has a number of benefits and limitations that could be attributed to its use.

Some of the benefits attributed to this type of Magnetic Resonance Imaging include the following: Diffusion tensor imaging provides much information regarding brain than the normal conventional MRI machine (Flanders 2009).

Read More