Digital parallel frequency-domain spectroscopy for tissue imaging

Abstract

Near-infrared (NIR) (650 to 1000 nm) optical properties of turbid media can be quantified accurately and noninvasively using methods based on diffuse reflectance or transmittance, such as frequency-domain photon migration (FDPM). Conventional FDPM techniques based on white-light steady-state (SS) spectral measurements in conjunction with the acquisition of frequency-domain (FD) data at selected wavelengths using laser diodes are used to measure broadband NIR scattering-corrected absorption spectra of turbid media. These techniques are limited by the number of wavelength points used to obtain FD data and by the sweeping technique used to collect FD data over a relatively large range. We have developed a method that introduces several improvements in the acquisition of optical parameters, based on the digital parallel acquisition of a comb of frequencies and on the use of a white laser as a single light source for both FD and SS measurements. The source, due to the high brightness, allows a higher penetration depth with an extremely low power on the sample. The parallel acquisition decreases the time required by standard serial systems that scan through a range of modulation frequencies. Furthermore, all-digital acquisition removes analog noise, avoids the analog mixer, and does not create radiofrequency interference or emission.

Fig. 1

Steps for the determination of broadband ${\mu }_a$ spectrum. (a) Measured SS reflectance spectrum; (b) amplitude calibration of the measured SS reflectance spectrum through the determination of the instrumental factor $k$; (c) SS reflectance spectrum scaled to fit the discrete FD reflectance values; (d) least-squares power-law fit to the ${\mu }_s^{\prime }$ values measured by the FD; (e) actual broadband ${\mu }_a$ spectrum.

Fig. 2

Frequency response of the system components: FLIMbox, detector, laser source, and tissue. Harmonic intensities are normalized with respect to the DC value (at $f=0$). Data are processed for values above the threshold (dashed line).

Fig. 3

(a) Schematic of the hand-held probe used for the measurements, (b) showing the two PMTs and the available source-detector distances. (c) Picture of the actual probe with the relative distances employed during the measurements presented in this paper.

Fig. 4

Illustration of the digital heterodyning principle, with exaggerated heterodyning such that the cross-correlation frequency (fcc) is $5/8$ of the sampling frequency (fs) instead of fcc $5\mathrm{fs}/256$, which was used in our implementation. Arriving photons (dots) are assigned to one of four sampling windows according to their arrival time. In the real case, the sampling windows slide through the entire period of the emission response due to the slight difference in frequencies, for a total of 256 steps.

Fig. 5

(a) Picture of the A320 module housing the actual FPGA where the FLIMbox circuit is implemented. (b) Schematic of the modules inside the FLIMbox unit, showing the preamplifiers, constant fraction discriminators, the FPGA card, and the synchronization for the external laser.

Fig. 6

Schematic of the electronics and optical components of the digital FD parallel spectroscopy instrument. The flow of the signals is shown: the optical path (dashed line) goes from the white laser to the phantom and the electrical paths (solid lines) from the detectors to the FLIMbox to the computer.

Fig. 7

Phase shift and demodulation at one wavelength obtained from a phantom with known optical properties.

Fig. 8

Chi-squared surfaces of fits performed using different pair functions: (a) $\varphi$ and $M$, (b) $\varphi$ and $Y$, (c) $\varphi$ and $ac$, and (d) slope $\varphi$ and slope $ac$.

Fig. 9

Comparison of FDPM fits with two different model function pairs: (a) $\varphi$ and $M$, (b) $\varphi$ and $ac$.

Fig. 10

(a) Absorption and scattering obtained from FDPM measurements. (b) Scattering from FDPM measurements overlapped by the scattering fit (power law) and scattering-corrected absorption. (c) Spectrometer spectrum, correction factor and corrected spectrum. (d) Comparison between spectrometer corrected spectrum and FDPM spectrum.

Fig. 11

Phase (dots) and modulation (squares) measurements showing the absence of noise. The uncertainty is smaller than the size of the symbols.