(E-185) Rotation Device to Improve Accuracy of Tissue Alignment Characterization via Polarized Raman Spectroscopy

Mechanical behavior and functional properties of tissues can be further understood through the temporal and spatial measurement of protein alignment. In recent studies, we developed a technique that uses Polarized Raman Spectroscopy (PRS) to determine the alignment of tissue fibers in biological and engineered tissue constructs. In this approach, PRS is used to observe changes in spectral intensity as the tissue sample is manually rotated in increments of 30 degrees under the microscope, with respect to the fixed angle of the PRS polarization filter [1,2]. To establish an accurate alignment metric, it is necessary to verify that the tissue sample is precisely rotated to the intended polarization angle––however, recent testing has indicated potential inaccuracies in our sample angle alignment method [2]. To address this, we developed a rotation device that enables fixed rotation of the tissue sample around a calibrated center of rotation. A MATLAB program was also developed to expedite the relocation of a region of interest on the PRS microscope software. It is proposed that the device and program will greatly reduce the time spent between spectral acquisitions and improve the precision of sample alignment with the desired polarization angle.

The current alignment characterization method involves three major steps (Figure 1). In our new approach, we’ve integrated the rotation device and MATLAB program into the spectral acquisition phase. The rotation device, designed using SOLIDWORKS and 3D printed with eSun ABS filament, consists of two main components: top and bottom (Figure 2). The top securely holds the tissue sample within one of two-sized Petri dishes, along with a calibration slide used with the ROI locator program. Grooves were incorporated to accommodate these features (Figure 2). To enable stable sample rotation with minimal vertical movement, we integrated a 22mm 608-2R Ball Bearing. The bottom has ridges every 10 degrees on the outer cylindrical wall, indicating the polarized angle. Additionally, an O-ring was added to increase resistance between the cylindrical walls of the two components, reducing unwanted rotation.

To determine the ROI’s location after rotation, we need to know the coordinates of the center of rotation (COR). Our device was calibrated by calculating the COR’s relative position to the microscope’s coordinate system (Figure 3) [4,5]. After rotation, our MATLAB program created for the device used the COR coordinates, the ROI coordinates at 0 degrees, and the polarization angle to calculate the new ROI coordinates (Figure 3) [6]. To assess the accuracy of our original angle alignment method, we calculated the experimental polarization angles with respect to the direction of the polarizing filter on MATLAB. This was done by calculating the angle between vectors for a ROI. The data was averaged and reported with a standard deviation.

In total, four prototypes of the rotation device were printed, ending with the current prototype shown in figure 4. To determine the accuracy of the polarization angle alignment without the use of the device, the experimental polarization angles from a tissue sample were calculated using the coordinates of the spectral acquisition vectors for the ROIs (Figure 5). Results revealed inherent errors in the manual sample rotation and alignment method. To address this issue, a rotation device was designed to facilitate precise control over the polarization angles, allowing measurements with finer increments, and thus reducing inaccuracies. Determining the precise direction of fiber alignment holds significant promise in obtaining more accurate mechanical properties and ultimately enabling the design of more precise engineered tissue constructs.

In ongoing studies, the rotation device and MATLAB program will replace the manual rotation and relocation of the region of interest on a tissue sample for our tissue characterization methods. The accuracy of the rotation device will then be determined using the same analytical methods that produced the results presented in Figure 5. Future research involves the possibility of motorizing the device with a micro servo or stepper motor to further reduce human error.

Funded by the UF SURF and NSF REU Site: Engineering for Healthcare (NSF Award 1757128).

[1] Hui Zhou, Janny Piñeiro Llanes, Malisa Sarntinoranont, Ghatu Subhash, Chelsey S. 

Simmons, “Label-free quantification of soft tissue alignment by polarized Raman 

spectroscopy”, Acta Biomaterialia, Volume 136, December 2021, Pages 363-374, 

https://doi.org/10.1016/j.actbio.2021.09.015.

[2] Hui Zhou, Janny Piñeiro Llanes, Maedeh Lotfi, Malisa Sarntinoranont, Chelsey S. 

Simmons, Ghatu Subhash, “Label-Free Quantification of Microscopic Alignment in 

Engineered Tissue Scaffolds by Polarized Raman Spectroscopy”, ACS Biomaterials 

Science & Engineering, May 2023, Pages 3206-3218, DOI: 

10.1021/acsbiomaterials.3c00242.

[3] Maedeh Lotfi, Hui Zhou, Janny Pineiro Llanes, Chelsey Simmons, Ghatu Subhash, 

Malisa Sarntinoranont, “Measuring Variation of Alignment in Engineered Tissue Constructs Using Polarized Raman Spectroscopy”, Society of Experimental Mechanics, June 2023, PowerPoint.

[4] “Circle-Circle Intersection”, Wolfram MathWorld, Wolfram Research, Inc. 

https://mathworld.wolfram.com/Circle-CircleIntersection.html

[5] Mathematics Stack Exchange. 

https://math.stackexchange.com/questions/543961/determine-third-point-of-triangle-when-two-points-and-all-sides-are-known

[6] “New coordinates by rotation of points,” High Accuracy Calculation for Life or Science. 

https://keisan.casio.com/exec/system/1496886458