Evaluation of the Differences between Normal and Cancerous Prostate Tissue Response to Simple and Vibro-Neural Stimulation
International Clinical Neuroscience Journal,
Vol. 7 No. 2 (2020),
10 March 2020
,
Page 61-65
Abstract
Background: Early detection of prostate cancer has significant benefits for its treatment and can increase the survival chance in patients. In recent years, new methods such as shear wave elastography and vibro-elastography, as well as artificial tactile sensing, have been used to detect a mass in the prostate tissue in-vivo and ex-vivo. This paper aims to investigate the difference between normal and malignant prostate tissue reaction to simple and vibro-neural stimulation for prostate tissue mass detection in order to determine neural stimulation intensity, velocity, and frequency to obtain the best result in detecting the type and location of the tumor.
Methods: This study has utilized neural stimulation devices in normal and cancerous tissues. The stimulation velocity, probe location, and the frequency of neural stimulation considered as the independent variables.
Results: The results show that for superficial masses, although dependent on the probe, the accuracy of detection at the low speed of 5mm/s is 50% higher than other conditions. On the other hand, in deep masses, with increasing mass depth, the accuracy of detection at the medium speed of 8mm/s is 30% higher than the low speed. Finally, the results showed that with increased stimulation frequency, the possibility of tumor detection, and its accuracy increases by 35%.
Conclusion: By improving the accuracy of the neural stimulation device, it can apply to detect hard materials such as tumors and malignant tissues.
- Prostate cancer detection
- Neural stimulation
- Energy dissipation
- Prostate tissue
- Residual displacement.
How to Cite
References
Murphy SL, Xu J, Kochanek KD, Arias E. Mortality in the United States, 2017. NCHS Data Brief. 2018(328):1-8.
Heron M. Deaths: leading causes for 2016. Natl Vital Stat Rep. 2018;67(6):1-77.
Åstrand AP, Andersson BM, Jalkanen V, Ljungberg B, Bergh A, Lindahl OA. Prostate cancer detection with a tactile resonance sensor--measurement considerations and clinical setup. Sensors (Basel). 2017;17(11). doi: 10.3390/s17112453.
Sakr WA, Grignon DJ, Crissman JD, Heilbrun LK, Cassin BJ, Pontes JJ, et al. High grade prostatic intraepithelial neoplasia (HGPIN) and prostatic adenocarcinoma between the ages of 20-69: an autopsy study of 249 cases. In Vivo. 1994;8(3):439- 43.
Karan D, Thrasher JB, Lubaroff D. Prostate cancer: genes, environment, immunity and the use of immunotherapy. Prostate Cancer Prostatic Dis. 2008;11(3):230-6. doi: 10.1038/pcan.2008.3.
Woo S, Kim SY, Cho JY, Kim SH. Shear wave elastography for detection of prostate cancer: a preliminary study. Korean J Radiol. 2014;15(3):346-55. doi: 10.3348/kjr.2014.15.3.346.
Woo S, Suh CH, Kim SY, Cho JY, Kim SH. Shear-wave elastography for detection of prostate cancer: a systematic review and diagnostic meta-analysis. AJR Am J Roentgenol. 2017;209(4):806-14. doi: 10.2214/ajr.17.18056.
Shoji S, Hashimoto A, Nakamura T, Hiraiwa S, Sato H, Sato Y, et al. Novel application of three-dimensional shear wave elastography in the detection of clinically significant prostate cancer. Biomed Rep. 2018;8(4):373-7. doi: 10.3892/ br.2018.1059.
Alizad A, Mehrmohammadi M, Mitri FG, Davis BJ, Sebo TJ, Mynderse LA, et al. Application of vibro-acoustography in prostate tissue imaging. Med Phys. 2013;40(2):022902. doi: 10.1118/1.4773890.
Mitri FG, Urban MW, Fatemi M, Greenleaf JF. Combined Vibro-acoustography (VA) imaging and Shearwave Dispersion Ultrasonic Vibrometry (SDUV) for measuring prostate viscoelastic material properties - An in vitro feasibility study. Proceedings of 20th International Congress on Acoustics, ICA; Sydney, Australia; 2010.
Gholampour S. FSI simulation of CSF hydrodynamic changes in a large population of non-communicating hydrocephalus patients during treatment process with regard to their clinical symptoms. PLoS One. 2018;13(4):e0196216. doi: 10.1371/ journal.pone.0196216.
Gholampour S, Bahmani M, Shariati A. Comparing the efficiency of two treatment methods of hydrocephalus: shunt implantation and endoscopic third ventriculostomy. Basic Clin Neurosci. 2019;10(3):185-98. doi: 10.32598/bcn.9.10.285.
Gholampour S, Deh HHH. The effect of spatial distances between holes and time delays between bone drillings based on examination of heat accumulation and risk of bone thermal necrosis. Biomed Eng Online. 2019;18(1):65. doi: 10.1186/ s12938-019-0686-6.
Gholampour S, Fatouraee N, Seddighi AS, Seddighi A. Numerical simulation of cerebrospinal fluid hydrodynamics in the healing process of hydrocephalus patients. J Appl Mech Tech Phys. 2017;58(3):386-91. doi: 10.1134/ s0021894417030026.
Gholampour S, Fatouraee N, Seddighi AS, Seddighi A. Evaluating the effect of hydrocephalus cause on the manner of changes in the effective parameters and clinical symptoms of the disease. J Clin Neurosci. 2017;35:50-5. doi: 10.1016/j. jocn.2016.09.012.
Gholampour S, Hajirayat K. Minimizing thermal damage to vascular nerves while drilling of calcified plaque. BMC Res Notes. 2019;12(1):338. doi: 10.1186/s13104-019-4381-2.
Gholampour S, Jalali A. Thermal analysis of the dentine tubule under hot and cold stimuli using fluid-structure interaction simulation. Biomech Model Mechanobiol. 2018;17(6):1599- 610. doi: 10.1007/s10237-018-1046-3.
Gholampour S, Taher M. Relationship of morphologic changes in the brain and spinal cord and disease symptoms with cerebrospinal fluid hydrodynamic changes in patients with Chiari malformation type I. World Neurosurg. 2018;116:e830-e9. doi: 10.1016/j.wneu.2018.05.108.
Hajirayat K, Gholampour S, Sharifi I, Bizari D. Biomechanical simulation to compare the blood hemodynamics and cerebral aneurysm rupture risk in patients with different aneurysm necks. J Appl Mech Tech Phys. 2017;58(6):968-74. doi: 10.1134/s0021894417060025.
Taher M, Gholampour S. Effect of ambient temperature changes on blood flow in anterior cerebral artery of patients with skull prosthesis. World Neurosurg. 2019. doi: 10.1016/j. wneu.2019.11.171.
Peng Q, Omata S, Peehl DM, Constantinou CE. Stiffness mapping prostate biopsy samples using a tactile sensor. Conf Proc IEEE Eng Med Biol Soc. 2011;2011:8515-8. doi: 10.1109/iembs.2011.6092101.
Ahn B, Kim Y, Oh CK, Kim J. Robotic palpation and mechanical property characterization for abnormal tissue localization. Med Biol Eng Comput. 2012;50(9):961-71. doi: 10.1007/s11517-012-0936-2.
Ahn B, Lee H, Kim Y, Kim J. Robotic system with sweeping palpation and needle biopsy for prostate cancer diagnosis. Int J Med Robot. 2014;10(3):356-67. doi: 10.1002/rcs.1543.
Sciarra A, Mariotti G, Salciccia S, Autran Gomez A, Monti S, Toscano V, et al. Prostate growth and inflammation. J Steroid Biochem Mol Biol. 2008;108(3-5):254-60. doi: 10.1016/j. jsbmb.2007.09.013.
Vasto S, Carruba G, Candore G, Italiano E, Di Bona D, Caruso C. Inflammation and prostate cancer. Future Oncol. 2008;4(5):637-45. doi: 10.2217/14796694.4.5.637.
Liau J, Goldberg D, Arif-Tiwari H. Prostate Cancer Detection and Diagnosis: Role of Ultrasound with MRI Correlates. Curr Radiol Rep. 2019;7(3):7. doi: 10.1007/s40134-019-0318-8.
- Abstract Viewed: 322 times
- PDF Downloaded: 365 times