Weisi Li1, Barry Belmont2, Joan M Greve2, Adam B Manders2, Brian C Downey2, Xi Zhang2, Zhen Xu2, Dongming Guo3, Albert Shih4. 1. School of Mechanical Engineering, Dalian University of Technology, Dalian, Liaoning 110042, China and Mechanical Engineering Department, University of Michigan, Ann Arbor, Michigan 48109. 2. Biomedical Engineering Department, University of Michigan, Ann Arbor, Michigan 48109. 3. School of Mechanical Engineering, Dalian University of Technology, Dalian, Liaoning 110042, China. 4. Mechanical Engineering Department, University of Michigan, Ann Arbor, Michigan 48109 and Biomedical Engineering Department, University of Michigan, Ann Arbor, Michigan 48109.
Abstract
PURPOSE: The mechanical and imaging properties of polyvinyl chloride (PVC) can be adjusted to meet the needs of researchers as a tissue-mimicking material. For instance, the hardness can be adjusted by changing the ratio of softener to PVC polymer, mineral oil can be added for lubrication in needle insertion, and glass beads can be added to scatter acoustic energy similar to biological tissue. Through this research, the authors sought to develop a regression model to design formulations of PVC with targeted mechanical and multimodal medical imaging properties. METHODS: The design of experiment was conducted by varying three factors-(1) the ratio of softener to PVC polymer, (2) the mass fraction of mineral oil, and (3) the mass fraction of glass beads-and measuring the mechanical properties (elastic modulus, hardness, viscoelastic relaxation time constant, and needle insertion friction force) and the medical imaging properties [speed of sound, acoustic attenuation coefficient, magnetic resonance imaging time constants T1 and T2, and the transmittance of the visible light at wavelengths of 695 nm (Tλ695) and 532 nm (Tλ532)] on twelve soft PVC samples. A regression model was built to describe the relationship between the mechanical and medical imaging properties and the values of the three composition factors of PVC. The model was validated by testing the properties of a PVC sample with a formulation distinct from the twelve samples. RESULTS: The tested soft PVC had elastic moduli from 6 to 45 kPa, hardnesses from 5 to 50 Shore OOO-S, viscoelastic stress relaxation time constants from 114.1 to 191.9 s, friction forces of 18 gauge needle insertion from 0.005 to 0.086 N/mm, speeds of sound from 1393 to 1407 m/s, acoustic attenuation coefficients from 0.38 to 0.61 (dB/cm)/MHz, T1 relaxation times from 426.3 to 450.2 ms, T2 relaxation times from 21.5 to 28.4 ms, Tλ695 from 46.8% to 92.6%, and Tλ532 from 41.1% to 86.3%. Statistically significant factors of each property were identified. The regression model relating the mechanical and medical imaging properties and their corresponding significant factors had a good fit. The validation tests showed a small discrepancy between the model predicted values and experimental data (all less than 5% except the needle insertion friction force). CONCLUSIONS: The regression model developed in this paper can be used to design soft PVC with targeted mechanical and medical imaging properties.
PURPOSE: The mechanical and imaging properties of polyvinyl chloride (PVC) can be adjusted to meet the needs of researchers as a tissue-mimicking material. For instance, the hardness can be adjusted by changing the ratio of softener to PVC polymer, mineral oil can be added for lubrication in needle insertion, and glass beads can be added to scatter acoustic energy similar to biological tissue. Through this research, the authors sought to develop a regression model to design formulations of PVC with targeted mechanical and multimodal medical imaging properties. METHODS: The design of experiment was conducted by varying three factors-(1) the ratio of softener to PVC polymer, (2) the mass fraction of mineral oil, and (3) the mass fraction of glass beads-and measuring the mechanical properties (elastic modulus, hardness, viscoelastic relaxation time constant, and needle insertion friction force) and the medical imaging properties [speed of sound, acoustic attenuation coefficient, magnetic resonance imaging time constants T1 and T2, and the transmittance of the visible light at wavelengths of 695 nm (Tλ695) and 532 nm (Tλ532)] on twelve soft PVC samples. A regression model was built to describe the relationship between the mechanical and medical imaging properties and the values of the three composition factors of PVC. The model was validated by testing the properties of a PVC sample with a formulation distinct from the twelve samples. RESULTS: The tested soft PVC had elastic moduli from 6 to 45 kPa, hardnesses from 5 to 50 Shore OOO-S, viscoelastic stress relaxation time constants from 114.1 to 191.9 s, friction forces of 18 gauge needle insertion from 0.005 to 0.086 N/mm, speeds of sound from 1393 to 1407 m/s, acoustic attenuation coefficients from 0.38 to 0.61 (dB/cm)/MHz, T1 relaxation times from 426.3 to 450.2 ms, T2 relaxation times from 21.5 to 28.4 ms, Tλ695 from 46.8% to 92.6%, and Tλ532 from 41.1% to 86.3%. Statistically significant factors of each property were identified. The regression model relating the mechanical and medical imaging properties and their corresponding significant factors had a good fit. The validation tests showed a small discrepancy between the model predicted values and experimental data (all less than 5% except the needle insertion friction force). CONCLUSIONS: The regression model developed in this paper can be used to design soft PVC with targeted mechanical and medical imaging properties.
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