Biomedical+Engineering+-+Potentials+in+3D+Imaging+Technology

=** Introduction **= toc

Biomedical engineering is a relatively new field in the world of engineering.It is essentially the bridge that connects the engineering mindset and the knowledge of the medical field to improve the lives of patients. A key component of biomedical engineering is 3D imaging technology [1]- [4]. General imaging technology has been around for several years, and 2D images have served doctors well during this time. Now, with technology advancing much quicker than in previous decades, 3D imaging systems are being created to seamlessly visualize and construct models needed for medical use [5]-[7]. These 3D imaging systems and methods are being used to create body parts, study tumors, build prosthetics, and so much more. Now that biomedical engineers have begun incorporating these technologies into their studies and inventions, the medical field will continue to advance and improve the health care of its patients. The current research and development of 3D imaging systems happening in the field right now consist of patient-specific heart valve reconstruction, tumor cell analysis, and the building/optimization of prosthetics. It is evident how these biomedical engineering studies have great potential, and are benefitting the health care and overall well-being of patients.

=** Heart Valve Reconstruction **=

One of the main uses of 3D imaging technology in the medical field is to reconstruct patient-specific heart valves [9]. Not every patient with a heart condition will be able to receive a transplant, and even then, only a fraction of these patients’ bodies will accept such a harsh surgery; here, the demand for customizable heart valves is created. With this in mind, biomedical engineers are working to create systems and methods to easily reconstruct patient-specific heart valves utilizing 3D imaging technology, 3D printing, and advanced computational algorithms [9]-[11].

** Current Technologies **
Currently, most computational studies for patient-specific heart valves consist of manual reconstruction, which yields significant human error, and is very time-consuming [9]. The imaging techniques being used include computed tomographic (CT) imaging, echocardiographs, and cardiac resonance imaging. While these methods have served doctors thus far, updated 3D technology allows for much more accurate reconstruction and surgical procedure. There are teams of doctors from all over the world working on improving imaging technology. After several experimental studies, a machine learning-based 3D geometry reconstruction modeling system has been successfully created to eliminate error and increase the likelihood of successful transplants for aortic heart valves [9], [10].

** Machine Learning-based 3D Geometry Reconstruction **
By combining existing technology with 3D imaging capabilities, a method has been created to accurately reconstruct patient specific heart valves [9], [11]. This method takes a CT image and utilizes standard segmentation computer algorithms to clarify the image. User-specific landmarks are then detected on the image, followed by curve detectors modeling leaflet attachment curves. Finally, leaflet curves are fitted to the image [9]. By the end of this process, a workable 3D image is produced with the exact reconstruction of the heart valve (Figure 1). All the algorithms used during the process are implemented in C++ and Matlab. This method allows doctors to effectively plan for operations and transplants, in addition to helping diagnosis and treatment for the patient [10], [11]. The computer algorithms can also show stress vs. strain diagrams for the valves, enabling biomedical engineers and doctors to customize what 3D printing material would be best for each specific patient. Machine methods significantly reduce the make-time of these heart valves compared to using manual reconstruction methods, in turn making this process more realistic for common use in the future.

=** 3D Modeling of Tumors **=

3D modeling is also used to observe tumors, and is extremely beneficial in determining a diagnosis, treatment planning, and treatment delivery [12]. A popular method to examine and study tumors is an MRI, or magnetic resonance imaging, but this does not provide enough information in terms of a tumors exact shape and density. The current procedure to produce a 3D model of a brain tumor requires a Radiologist to manually take 2D MRIs and trace and layer these images to create a final 3D product [12], [13]. Although it’s possible to construct a 3D image, it takes several hours, and is only approximately 85% accurate.

[[image:pic 2.png width="231" height="447" align="left" caption="Figure 2: Converting 2D images to 3D models."]]** From 2D to 3D **
With the advanced 3D capabilities that computers acquire today, systems are being created to semi-automatically segment 2D MRI images and combine them to create a 3D model (Figure 2). This process is made possible with Matlab and a software package called 3D DOCTOR [12]. Ultimately, a computer program will scan several layers of 2D images and create an empty space for 3D volume; next, each image’s x and y coordinates will be transferred into the empty space. The program then recognizes the difference between images and records this as a z coordinate. This process is repeated until all slices are scanned and placed. By the end, a 3D volumetric rendering is complete. A unique feature to this method is the gray-scale intensity that’s produced in the model, better representing the tumor’s density and shape [13].

This approach toward 3D modeling a tumor is very effective. Not only is it nearly 10 times, but it eliminates a substantial amount of human error from manually constructing the model [12]. This method has been cross-examined by Radiologists, and confirms that it is applicable for surgical planning, diagnosis, and detecting tumor growth.

=** Constructing Prosthetics **=

A staple creation within biomedical engineering is prosthetics. Prosthetics are artificial body parts that give patients the opportunity to keep mobility and function if they are missing limbs and parts [14]-[17]. Although prosthetics are not nearly as mobile as actual limbs and body parts, 3D imaging technology is making it possible to fine-tune reconstruction and optimize functionality [14].

** Prosthetic Feet **
In recent years, prosthetic feet have drawn attention to developers. Although current designs provide the basic functions of a foot, their shape is not desirable, and mobility is extremely limited [14]. With the help of 3D imaging technology and 3D printing, testing is now being performed to improve these models. There are three types of prosthetic feet: energy storage and return, passive, or bionic feet [16]. Passive feet do not enhance performance qualities due to its absence of ankle torque, but it is superior with respect to weight, which is a crucial requirement for enabling function and mobility. The general process for improving the passive prosthetic foot (Figure 3) includes forming an initial 3D model based off survey results, and then having it undergo topology optimization and finite element analysis to determine its best design concepts [14]-[17]. In addition, the foot also endures stress and strain testing, and is finally 3D printed to test the finite element analysis results [18], [19]. These passive feet are printed with Polylactic Acid (PLA) to reduce its weight and mimic a real foot [14]. These prosthetic feet have been tested by several subjects, both male and female, and an optimal size and shape has been constructed for each gender. Finally, an optimized model is created that is light, safe, and far more functional than the original base model.

=** Conclusion **=

Biomedical engineering is a field that combines mathematics, science, ingenuity, and the human body all into one profession. A large key feature that contributes to the success of biomedical engineering inventions is 3D imaging technology and all its applications. Using 3D imaging to create methods and systems for medical purposes is being tested every day in more ways than imaginable. While heart valves, cancerous tumors, and prosthetic feet are all fascinating accomplishments, these are just a small fraction of the advances 3D imaging has contributed to.

3D imaging technology allows doctors to study and understand the human body in new ways. By improving this technology, doctors can make diagnosis, plan treatments, and overall operate more efficiently [2], [3], [20]. The biggest benefit that comes from 3D imaging applications is their contribution to improving the health care and quality of life of each patient. This technology enables patients to receive transplants, walk, or just live an easier life.

Behind all applications of biomedical engineering is 3D imaging technology [2]. Recent research suggests that 2D imaging is dying, and all imaging technology is shifting toward 3D [3]. The most important requirement needed before 3D imaging applications are implemented for daily use, is the consistency of studies and models. From stem cell research, to creating new medical devices, and simulating surgical procedures, the potential for 3D imaging technology and biomedical engineering is infinite and influences all topics.

= References =

[1] D. Nadkarni, I. Elhajj, Z. Dawy. “Examining the need & potential for biomedical engineering to strengthen health care delivery for displaced populations & victims of conflict,” Conflict and Health, vol. 11. https://search-proquest-com.colorado.idm.oclc.org/docview/1959462444?pq-origsite=summon&accountid=14503

[2] K.J. Bowman. “Porential impacts of creating biomedical engineering programs on gender distribution within leading engineering colleges,” Journal of Diversity in Higher Education, vol. 4: 51-64. https://search-proquest-com.colorado.idm.oclc.org/docview/860077163?pq-origsite=summon&accountid=14503

[3] G. Sivaradje, R. Nakkeeran, P. Dananjayan. “Extraction of evoked potential and its applications in biomedical engineering,” IETE Technical Review, vol. 22: 229-239. https://www-tandfonline-com.colorado.idm.oclc.org/doi/abs/10.1080/02564602.2005.11657905

[4] R. Magjarevic. (2011). “Biomedical engineering,” Zdravniski Vestnik, vol 80(7-8) https://colorado.idm.oclc.org/login?url=https://search-proquest-com.colorado.idm.oclc.org/docview/1312475244?accountid=14503

[5] J. Provost, C. Papadacci, J.E. Arango, M. Imbault, M. Fink, J. Gennison, M. Tanter, M. Pernot. “3D ultrafast ultrasound imaging in vivo,” Physics in Medicine & Biology. 2013.

[6] A.D> Lantada, P.L. Morgado. “Rapid prototyping for biomedical engineering: current capabilities and challenges,” Annual Review of Biomedical Engineering, vol. 14:73-96. 2012. https://www-annualreviews-org.colorado.idm.oclc.org/doi/10.1146/annurev-bioeng-071811-150112

[7] T.R. Harris, J.D. Bransford, S.P. Brophy. “Roles for learning sciences and learning technologies in biomedical engineering education: a review of recent advances,” Annual Review of Biomedical Engineering, vol 4:29-48. 2002. https://doi.org/10.1146/annurev.bioeng.4.091701.125502

[8] K.R. Foster, R. Koproski. “Machine learning, medical diagnosis, and biomedical engineering research,” Biomedical Engineering Online, vol 13:94. 2014. Doi: 10.1186/1475-925X-13-94

[9] L. Liang, F. Kong, C. Martin. “ Machine learning–based 3 ‐D geometry reconstruction and modeling of aortic valve deformation using 3‐D computed tomography images,” International Journal of Numerical Method Biomedical Engineering, 2017. https://doi-org.colorado.idm.oclc.org/10.1002/cnm.2827

[10] T. Siminak. “3D heart model printing for preparation of percutaneous structural interventions: description of the technology and case report,” National Center for Biotechnical Information, pp. 546-551. doi:10.5603/KP.2014.0119.

[11] R.L. Riha. “Breathe: biomedical engineering in respiratory disorders,” European Respiratory Society, vol. 13:75. 2017. doi: 10.1183/20734735.008617.

[12] S. Resmi, T. Thomas. “A semi-automatic method for segmentation and 3D modeling of glioma tumors from brain MRI,” Journal of Biomedical Science and Engineering, vol. 5: 378-383. 2015. doi: 10.4236/jbise.2012.57048.

[13] M. Alemany-Ribes, C.E. Semino. “Bioengineering 3D environments for cancer models,” Advanced Drug Delivery Review, 79-80. 2014. doi: 10.1016/j.addr.2014.06.004

[14] Z. Tao, H. Ahn, C. Lian. “Design and optimization of prosthetic foot by using polylactic acid 3D printing,” Journal of Mechanical Science and Technology, vol. 31: 2393-2398. 2017. http://dx.doi.org.colorado.idm.oclc.org/10.1007/s12206-017-0436-2

[15] Y. Huang, R. Seelaus, L. Zhao. “Virtual surgical planning and 3D printing in prosthetic orbital reconstruction with percutaneous implants: a technical case report,” International Medical Case Report Journal, vol. 9:341-345. 2016. https://doi.org/10.2147/IMCRJ.S118139

[16] R.E. Guldberg, C.L. Duval, A. Peister. “3D imaging of tissue integration with porous biomaterials,” ScienceDirect, vol. 29: 3757-3761. 2008. https://doi.org/10.1016/j.biomaterials.2008.06.018

[17] E. Engelhaupt. “Scientists use 3D printers to make body parts,” Biodiversity Data Journal, vol. 4. doi: 10.3897/bdj.4.e7720.figure2f

[18] S. Bhatia, S. Sharma. “3D-printed prosthetics roll off the presses,” ProQuest, vol. 10: 28-33. 2014. https://search-proquest-com.colorado.idm.oclc.org/docview/1527475045/fulltext/B28AF025963A4E0APQ/1?accountid=14503

[19] D. Kai, S. Jiang. “Engineering highly stretchable lignin-based elctrospun nanofibers for potential biomedical applications,” Journal of Materials Chemistry B, vol 3: 6194-6204. http://pubs.rsc.org.colorado.idm.oclc.org/en/Content/ArticleLanding/2015/TB/C5TB00765H#!divAbstract

[20] B. Mailey, A. Freel. “Clinical accuracy and reproducibility of portrait 3D surgical simulation platform in breast augmentation,” Aesthetic Surgery Journal, vol. 33:84–92. 2013. https://doi-org.colorado.idm.oclc.org/10.1177/1090820X12469807

[|Importance of 3D Imaging Technology] [|Potentials in Biomedical Engineering] [|3D Heart Valve Reconstruction] [|Tumor Cell Analysis] [|Prosthetic Foot Optimization]