APPLICATION OF DIGITAL TOMOSYNTHESIS IN DIAGNOSING SPINAL TUBERCULOSIS – FIRST CLINICAL EXPERIENCE IN UKRAINE
Diagnosis of tuberculous spondylitis is based on the comparison of clinical-laboratory, bacteriological data and radiological methods. Digital tomosynthesis is a new method of X-ray diagnostics for performing with high-resolution limited-angle tomography at short-pulsed exposures in one pass of the tube with reconstruction of several hundred longitudinal sections of the research object without superposition of tissues. Possibilities of tomosynthesis are studied for various clinical situations.
Aim of research. To study and apply the possibilities of digital tomosynthesis in the diagnosis of tuberculous spondylitis, conduct a comparative analysis with other radiological methods.
Materials and methods. Digital tomosynthesis was performed for 95 patients with various spine diseases (select group 8.4 % with tuberculous spondylitis) at the domestic digital roentgen-diagnostic complex with the mode of digital tomosynthesis after performing digital projectional radiography of spine.
Results and discussion. The benefits of tomosynthesis were shown and a comparative analysis with other visualization methods in the diagnosis of spondylitis was performed. Cases of the first clinical application of the method in Ukraine were demonstrated.
Conclusion. Digital tomosynthesis of the spine is a new promising diagnostic tool by which you can obtain qualitative spine images in the form of numerical thin sections with no exaggeration effect. Results are comparable to CT data for detecting bone destruction at lower radiation load levels. Digital tomosynthesis provides better visualization of the small joints of the spine and the ability to evaluate each anatomical element of the vertebra at different depths, helps to detect pulmonary manifestation of tuberculosis.
Holka, G. G., Vesnin, V. V., Fadeev, O. G., Burlaka, V. V., Oliynyk, A. O., Garkusha, М. А. (2017). Zagalni pryncypy diagnostyky tuberkulosnogo spondylitu. Travma, 8 (3). Available at: http://www.mif-ua.com/archive/article/44806
Skoura, E., Zumla, A., Bomanji, J. (2015). Imaging in tuberculosis. International Journal of Infectious Diseases, 32, 87–93. doi: http://doi.org/10.1016/j.ijid.2014.12.007
Chen, C.-H., Chen, Y.-M., Lee, C.-W., Chang, Y.-J., Cheng, C.-Y., Hung, J.-K. (2016). Early diagnosis of spinal tuberculosis. Journal of the Formosan Medical Association, 115 (10), 825–836. doi: http://doi.org/10.1016/j.jfma.2016.07.001
Jung, N.-Y., Jee, W.-H., Ha, K.-Y., Park, C.-K., Byun, J.-Y. (2004). Discrimination of Tuberculous Spondylitis from Pyogenic Spondylitis on MRI. American Journal of Roentgenology, 182 (6), 1405–1410. doi: http://doi.org/10.2214/ajr.182.6.1821405
Dobbins, J. T., Godfrey, D. J. (2003). Digital x-ray tomosynthesis: current state of the art and clinical potential. Physics in Medicine and Biology, 48 (19), 65–106. doi: http://doi.org/10.1088/0031-9155/48/19/r01
Shutikhina, I. V., Tsybulskaya, Y. A., Smerdin, S. V., Selyukova, N. V., Baturin, O. V., Kokov, L. S. (2016). Capabilities of Combined Application of Multislice Linear Digital X-ray Tomography and Ultrasound Examination in Diagnosing Spinal Tuberculous Lesion. Sovremennye Tehnologii v Medicine, 8 (4), 82–91. doi: http://doi.org/10.17691/stm2016.8.4.11
Machida, H., Yuhara, T., Tamura, M., Ishikawa, T., Tate, E., Ueno, E. et. al. (2016). Whole-Body Clinical Applications of Digital Tomosynthesis. RadioGraphics, 36 (3), 735–750. doi: http://doi.org/10.1148/rg.2016150184
Ha, A. S., Lee, A. Y., Hippe, D. S., Chou, S.-H. S., Chew, F. S. (2015). Digital Tomosynthesis to Evaluate Fracture Healing: Prospective Comparison With Radiography and CT. American Journal of Roentgenology, 205 (1), 136–141. doi: http://doi.org/10.2214/ajr.14.13833
Jiao, D., Yang, H.-S., Yang, D., Tian, W., Wang, H., Ji, H. (2016). Application of digital tomosynthesis in diagnosing spinal tuberculosis. Clinical Imaging, 40 (3), 461–464. doi: http://doi.org/10.1016/j.clinimag.2015.11.003
Dykan, І. М., Bozhok, S. M., Gurando, A. V., Kozarenko, T. M. (2017). Cyfrovyi tomosyntez u diagnostyci zakhvoruvan grudnykh zaloz. Health Of Woman, 8 (124), 108–115.
Sharma, G., Ghode, R. (2016). Tubercular Spondylitis: Prospective Comparative Imaging Analysis on Conventional Radiograph and MRI. International Journal of Anatomy, Radiology and Surgery, 5 (3), 41–46.
Rivas-Garcia, A., Sarria-Estrada, S., Torrents-Odin, C., Casas-Gomila, L., Franquet, E. (2012). Imaging findings of Pott’s disease. European Spine Journal, 22 (4), 567–578. doi: http://doi.org/10.1007/s00586-012-2333-9
Simoni, P., Gérard, L., Kaiser, M.-J., Ribbens, C., Rinkin, C., Malaise, O., Malaise, M. (2015). Use of Tomosynthesis for Detection of Bone Erosions of the Foot in Patients With Established Rheumatoid Arthritis: Comparison With Radiography and CT. American Journal of Roentgenology, 205 (2), 364–370. doi: http://doi.org/10.2214/ajr.14.14120
Joo, Y. B., Kim, T.-H., Park, J., Joo, K. B., Song, Y., Lee, S. (2016). Digital tomosynthesis as a new diagnostic tool for evaluation of spine damage in patients with ankylosing spondylitis. Rheumatology International, 37 (2), 207–212. doi: http://doi.org/10.1007/s00296-016-3627-8
Sechopoulos, I. (2013). A review of breast tomosynthesis. Part II. Image reconstruction, processing and analysis, and advanced applications. Medical Physics, 40 (1), 014302. doi: http://doi.org/10.1118/1.4770281
Siu, A. L. (2016). Screening for Breast Cancer: U.S. Preventive Services Task Force Recommendation Statement. Annals of Internal Medicine, 164 (4), 279–296. doi: http://doi.org/10.7326/m15-2886
Lang, K., Andersson, I., Zackrisson, S. (2014). Breast cancer detection in digital breast tomosynthesis and digital mammography – a side-by-side review of discrepant cases. The British Journal of Radiology, 87 (1040), 20140080. doi: http://doi.org/10.1259/bjr.20140080
Xia, Q. (2007). Dedicated Computed Tomography of the Breast: Image Processing and Its Impact on Breast Mass Detectability. 4.
Smith, A. P., Niklason, L., Ren, B., Wu, T., Ruth, C., Jing, Z.; Astley, S., Brady, M., Rose, C., Zwiggelaar, R. (Eds.) (2006). Lesion Visibility in Low Dose Tomosynthesis. Digital mammography: 8th international workshop, IWDM 2006. Manchester, New York: Springer, 160–166. doi: http://doi.org/10.1007/11783237_23
US Food and Drug Administration (2011). Selenia Dimensions 3D System – P080003.
Dobbins, J. T., McAdams, H. P. (2009). Chest tomosynthesis: Technical principles and clinical update. European Journal of Radiology, 72 (2), 244–251. doi: http://doi.org/10.1016/j.ejrad.2009.05.054
Bertolaccini, L., Viti, A., Tavella, C., Priotto, R., Ghirardo, D., Grosso, M., Terzi, A. (2015). Lung cancer detection with digital chest tomosynthesis: first round results from the SOS observational study. Annals of Translational Medicine, 3 (5), 67. doi: http://doi.org/10.3978/j.issn.2305-5839.2015.03.41
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