Remote photoacoustic sensing using speckle-analysis

Abstract

Laser surgery is a rising surgical technique, which offers several advantages compared to the traditional scalpel. However, laser surgery lacks a contact-free feedback system which offers high imaging contrast to identify the tissue type ablated and also a high penetration depth. Photoacoustic imaging has the potential to fill this gap. Since photoacoustic detection is commonly contact based, a new non-interferometric detection technique based on speckle-analysis for remote detection is presented in this work. Phantom and ex-vivo experiments are carried out in transmission and reflection-mode for proof of concept. In summary, the potential of the remote speckle sensing technique for photoacoustic detection is demonstrated. In future, this technique might be applied for usage as a remote feedback system for laser surgery, which could help to broaden the applications of lasers as smart surgical tools.

Figure 1

The temporal vibration profile of the phantom surfaces measured in transmission-mode is shown. Negative time points are related to measurements before the photoacoustic excitation. For the three phantoms, the initial peak which is generated by the photoacoustic signal is marked.

Figure 2

The phantom measurements in transmission-mode are verified using a contact ultrasound transducer (UST). For the three phantoms the first peak of the photoacoustic signal is marked which show the initial generated photoacoustic signal at the lower absorber surface.

Figure 3

Box plot of the photoacoustic detection times using speckle sensing for the phantoms. The corresponding photoacoustic detection times using an ultrasound transducer are marked with an rectangle. This state of the art measurements match the time interval for speckle sensing.

Figure 4

(a,b) The ultrasound transducer measurements in transmission-mode are shown with the corresponding detection times of the photoacoustic and laser induced ultrasound signal. (b) For the marked surface, the laser induced ultrasound signal is stronger than the photoacoustic signal. (c) Detection times using speckle sensing and its standard deviation for the photacoustic signal and for the laser induced ultrasound signal at the phantom surface. The state of the art measurement using the ultrasound transducer matches the time interval for speckle sensing.

Figure 5

Detection times using speckle sensing and its standard deviation for the photoacoustic measurements. The theoretical arrival time of the photoacoustic signal matches the time interval for speckle sensing.

Figure 6

The generated photoacoustic signal of the absorbing object leads to a surface tilt α. This angle leads to a shift of the primary speckle pattern in the observation plane with distance Z to the object surface. By using a camera system, the secondary speckle pattern shift x_s can be calculated and it is possible to recover the surface tilt α.

Figure 7

The PVCP phantoms used in this work consist of an absorbing hemisphere with a surrounding scattering matrix. The distance x₁ between the hemisphere and the phantom surface is varied. The ex-vivo sample consists of an absorbing cylinder made of PVCP surrounded with fat tissue.

Figure 8

(a) Optical Setup for remote photoacoustic sensing in transmission-mode using speckle analysis. The detection unit consists of a high speed camera (1), lens (2), aperture (3), bandpass-filter (4) and microscope objective (5). The speckle pattern is generated by cw-laser beam (6) which is focused on the phantom surface (9) using a lens (7). The sample is excited with a short laser pulse aiming at the phantom centre (8) which triggers the high speed camera. (b) Optical Setup for remote photoacoustic sensing in reflection-mode. Excitation and sensing take place on the same object side. (c) The resolution of the imaging system was measured at 2.76 μm (Group 7, Element 4) using a USAF 1951 Test Target. (d) Example of a speckle image captured with the imaging setup (128 × 16 pixel). The scales are added using the resolution, pixel size and the optical magnification $M=10$.