Fig. 1. System schematic and principle of HA-PAM. (a) Experimental setup of the HA-PAM system. L1, L2, achromatic doublet; PH, pinhole; HSF, high-speed focuser; OL, objective lens; GVS, galvanometer scanner; WC, water cube; G, glass; UT, ultrasound transducer; DAQ, data acquisition. (b) HA-PAM scanning scheme. Volumetric imaging is achieved by two-dimensional rotary scanning. (c) Synchronization sequences of laser excitation, data acquisition, and high-speed focuser. (d) The principle of adaptive focusing.

Fig. 2. Experimental demonstration of a high spatiotemporal resolution, large FOV, and an ultrahigh sensitivity of HA-PAM. (a) The imaging FOV and individual spot sizes within the FOV. (b) Simulation of resolution distribution using Zemax. (c) Lateral resolutions measured by imaging a sharp edge. The lateral resolution of the calibrated focal plane in the center (top) and edge (bottom) areas. Exp, experimental data; ESF, edge spread function; LSF, line spread function. (d) Depth-resolved imaging of the phantom with curved surfaces from conventional PAM and HA-PAM. Scale bars, 1 mm. (e) Close-up MAP images of the red box region in (d). The region II of the image corresponds to the areas surrounding the optical focal plane, which exhibits a higher SNR and a better resolution compared to the out-of-focus areas (region I). (f) Black ink flows in a microfluidic channel. Scale bars, 1 mm. (g) The image of the carbon fibers obtained using conventional PAM and HA-PAM with simulated brain pulsation. (h) Close-up images of the area indicated by the red box in (g) show the difference between conventional PAM and HA-PAM. Massive missing features of the conventional PAM image are marked by the yellow arrows. (i) Variation curves of the average signal amplitude of a selected ROI for different time spots using conventional PAM and HA-PAM, respectively. Scale bars, 1 mm.

Fig. 3. HA-PAM and conventional PAM of mice subcutaneous tumors, rabbit kidneys, and mouse brains. (a), (d), and (g) Images of a subcutaneous mice tumor (a), the venous system of a resected rabbit kidney (d), and a mouse brain (g) using HA-PAM. Scale bars, 1 mm. (b) Close-up images of the area indicated by the white dashed box in (a) show the differences between HA-PAM and conventional PAM. (c) Close-up images of the representative area using conventional PAM (left) and HA-PAM (right). (e) Close-up images of the area indicated by the white dashed box in (d) show the blurred microvasculature due to the out-of-focus issue. (f) Close-up images of the representative area show that HA-PAM (right) had a better resolution than conventional PAM (left). (h) Close-up images of the area indicated by the white dashed box in (g) using HA-PAM and conventional PAM. (i) Comparison of close-up conventional PAM image (left) with close-up HA-PAM image (right). The cross-sectional profiles of the vessels marked by the lines in (c), (f), and (i) show the well-maintained resolution in the corresponding areas using HA-PAM.

Fig. 4. Conventional PAM and HA-PAM for in vivo imaging with simulated breathing and brain pulsation. (a) The images of a mouce brain obtained using conventional PAM and HA-PAM. Scale bar, 1 mm. (b) Close-up images of the area indicated by the blue box in (a). (c) Cross-sectional profiles of the representative mice brain marked by the lines in (b). (d) The derived branch and end points of the vascular network. (e), (f) Variation curves of the branch and averaged amplitude in the close-up region at different time spots. (g) The segmentation mask for the vascular network. (h) Temporal variation of the CHbT (ΔA/A¯, A is the PA signal amplitude) in five selected areas marked by blue circles in (g). The green areas indicate the simulated movement by the motor. (i) Temporal variation of the vessel diameter (Δd/d¯, d is the vessel diameter) of the marked I and II in (g).

Fig. 5. Simulation of the laser beam spot size per scan point using Zemax.

Fig. 6. Simulation of the system focal plane and resolution. (a) The scheme of correcting the focal plane. (b) The average optical transfer function at different sub-FOVs from edge to middle of the whole imaging domain.

Fig. 7. Experimental demonstration of a large DOF using HA-PAM. (a) Schematic representation of the inclined pencil lead inserted into an agarose phantom. (b) MAP images of the tilted pencil lead using conventional PAM at different focal planes and HA-PAM, respectively. Scale bar, 1 mm.

Fig. 8. Schematic of the dynamic out-of-focus phantom experiment. (a) Simulation of dynamic out-of-focus. The contraction and expansion of the carbon fiber layer are achieved by injecting or withdrawing air into the sealed cavity to simulate the physiological activity of brain pulses. (b) Fabrication of the multilayer chip.

Fig. 9. Conventional PAM imaging of (a) typical mouse subcutaneous tumor, (b) the venous system of a resected rabbit kidney, and (c) a mouse brain.

Fig. 10. Schematic of the dynamic out-of-focus in in vivo experiment. (a) Simulation of dynamic out-of-focus. The mouse is driven up and down in the direction perpendicular to the imaging surface by a one-dimensional motor to simulate the defocus due to physiological activities. (b) Synchronization sequences of data acquisition and motor movement. During the imaging process, the motor makes random movements. According to the adaptive focusing algorithm, the high-speed focuser (HSF) will follow the corresponding movement of the motor to achieve that the light focus always coincides with the imaging object.