**3. Results**

Using the calibration algorithm, the PA channel data was corrected before image reconstruction. Four randomly selected channel data are shown in Figure 3. Before calibration, each channel data consists of three reference signals: (i) the signal representing the transducer response, (ii) the PA signal coming from the imaging target and (iii) the PA signal coming from the tape. After calibration (blue solid), the PA signal from the imaging target is aligned. The reason that the PA signals are not located at the same sample number, is due to the non-uniform structure of the phantom. The improvement in the reconstructed image is evident in Figure 3e,j.

**Figure 3.** PA signal correction based on the calibration algorithm. (**<sup>a</sup>**–**d**) PA signals of (i) transducer response, (ii) PA from imaging object, (iii) PA from calibration tape, (**e**) distorted image before data correction. (**f**–**i**) PA signals from the imaging object, (**j**) image after data correction.

We initially performed a resolution analysis on a 2-legged phantom with 0.2 mm diameter lead as shown in Figure 4a. As the diameter of the lead is expected to be below the spatial resolution of the system, the width of the reconstructed image will spread to the resolution of the system. The length of each of the two branches was 6 mm. A 2D reconstructed image of the phantom is shown in Figure 4b. Taking a 1D intensity profile across the diameter of the object followed by a Gaussian fitting to the pixel values and calculating the full width at half maximum (FWHM) approximates the spatial resolution of the system. In Figure 4c, the FWHM is estimated to be 240 μm.

**Figure 4.** Resolution analysis results. (**a**) Image of the resolution phantom, (**b**) reconstructed image, (**c**) intensity profile across the diameter of the resolution phantom with a Gaussian fit (FWHM = 240 μm).

**Figure 5.** Imaging of an 8-leg phantom. (**a**) Experimental setup. (**b**) a photograph of the 8-leg phantom, and (**c**) a 2D reconstructed image of the phantom using 16- element PACT system (image acquired in 1.5 s).

Next, the system was used to image a complex phantom comprised of 0.5 mm diameter lead with 8 branches (~7 mm in length). Figure 5a shows an image of the phantom positioned and aligned at the center of the ring. The phantom dimensions are shown in Figure 5b. The reconstructed image of the phantom is shown in Figure 5c.

Among different configurations of PAI, photoacoustic computed tomography is favored for small animal studies, e.g., hemodynamic brain imaging, whole body imaging, mainly due to its fast image acquisition. However the high-cost of the system has prevented the full establishment and wide utility of the device. Here we introduced a fast, low cost PACT system by replacing the sophisticated expensive ring array with a moving ultrasound sparse array. We demonstrated, by imaging sophisticated phantoms, that the system can produce images with a temporal resolution of 1.5 s and spatial resolution of 240 μm. This system promises a higher sensitivity in comparison to a commercial ring array due to the much larger number of view angles it uses and larger element size of the transducers. The cost of the proposed system compared to a full-ring array PACT is given in the table below (Table 3).


**Table 3.** Cost comparison between proposed and full-ring array based PACT system.

#### **4. Conclusions and Future Work**

Although PAI has demonstrated grea<sup>t</sup> potential in preclinical and clinical applications, it is still in its early stage of development compared to already established medical imaging modalities such as MRI, CT, PET, and ultrasound imaging. Among several limitations preventing the wide application of PACT, manufacturing cost is the major one. Here, we explained the development of a fast, low-cost PACT system with only 16 single element transducers and a novel mechanical scanning design. Such configuration reduces the cost of the ring array PACT system drastically. A correction algorithm has been developed and applied to the acquired signals to make the transducers' data equidistant from the imaging target. We have demonstrated that the system can produce images with a temporal resolution of 1.5 s and spatial resolution of 240 μm.

The system developed in this study will eventually be used for functional small animal brain imaging. We are currently developing a new system, using the same concept but smaller in size with 32 transducers, and an amplifier unit, to make a faster, compact PACT system with improved isotropic resolution.

**Author Contributions:** Conceptualization, M.Z. and M.A.; Methodology, M.Z. and M.A.; Software, M.Z., K.K., and R.M.; Validation, R.M. and K.K.; Formal Analysis, R.M., K.K., and M.Z.; Investigation R.M., K.K., and M.Z.; Writing–Original Draft Preparation, M.Z., and K.K.; Writing–Review and Editing, R.M.; Visualization, R.M.; Supervision, M.A.

**Funding:** This research was partially funded by the American Cancer Society, Research Grant number 14-238-04-IRG and the Albert and Goldye J. Nelson grant.

**Acknowledgments:** We are grateful to have constructive discussion with Jun Xia from University of Buffalo, NY regarding the reconstruction algorithm.

**Conflicts of Interest:** The authors declare no conflict of interest.
