Sequential weighted Wiener estimation for extraction of key tissue parameters in color imaging: a phantom study

Spectral diffuse reflectance and autofluorescence imaging can perform early prediction of blood vessel occlusion in skin flaps

Flap transfer has become a common technique in reconstructive surgery. However, a significant number of compromised skin flaps are not successfully salvaged because the current clinical method for flap assessment relies heavily on the clinician's experience. Vascular occlusion is the major reason for flap failure, thus the accurate and objective early prediction of blood vessel occlusion is vitally important. Our parallel point measurement study has demonstrated the great potential of joint diffuse reflectance and autofluorescence spectroscopy in the early detection and differentiation of venous and arterial occlusion in skin flaps. Unfortunately, the technique of point measurements is not suitable to examine a large skin flap when a high spatial resolution is required. In this study, we attempted to overcome this problem by performing spectral diffuse reflectance and autofluorescence imaging on a rat skin flap model. Both imaging data and reconstructed spectra were used to statistically differentiate control flaps, arterially occluded flaps and venously occluded flaps. Our preliminary results suggest that the technique of joint diffuse reflectance and autofluorescence spectroscopic imaging can achieve high classification accuracy thus could be used to detect and differentiate flaps with venous and arterial occlusion accurately at an early time point in a large skin flap. Typical reconstructed spectra of (a) diffuse reflectance and (b) autofluorescence after normalization.

Stepwise method based on Wiener estimation for spectral reconstruction in spectroscopic Raman imaging

Raman spectroscopy has demonstrated great potential in biomedical applications. However, spectroscopic Raman imaging is limited in the investigation of fast changing phenomena because of slow data acquisition. Our previous studies have indicated that spectroscopic Raman imaging can be significantly sped up using the approach of narrow-band imaging followed by spectral reconstruction. A multi-channel system was built to demonstrate the feasibility of fast wide-field spectroscopic Raman imaging using the approach of simultaneous narrow-band image acquisition followed by spectral reconstruction based on Wiener estimation in phantoms. To further improve the accuracy of reconstructed Raman spectra, we propose a stepwise spectral reconstruction method in this study, which can be combined with the earlier developed sequential weighted Wiener estimation to improve spectral reconstruction accuracy. The stepwise spectral reconstruction method first reconstructs the fluorescence background spectrum from narrow-band measurements and then the pure Raman narrow-band measurements can be estimated by subtracting the estimated fluorescence background from the overall narrow-band measurements. Thereafter, the pure Raman spectrum can be reconstructed from the estimated pure Raman narrow-band measurements. The result indicates that the stepwise spectral reconstruction method can improve spectral reconstruction accuracy significantly when combined with sequential weighted Wiener estimation, compared with the traditional Wiener estimation. In addition, qualitatively accurate cell Raman spectra were successfully reconstructed using the stepwise spectral reconstruction method from the narrow-band measurements acquired by a four-channel wide-field Raman spectroscopic imaging system. This method can potentially facilitate the adoption of spectroscopic Raman imaging to the investigation of fast changing phenomena.

Optimization of advanced Wiener estimation methods for Raman reconstruction from narrow-band measurements in the presence of fluorescence background

Raman spectroscopy has shown great potential in biomedical applications. However, intrinsically weak Raman signals cause slow data acquisition especially in Raman imaging. This problem can be overcome by narrow-band Raman imaging followed by spectral reconstruction. Our previous study has shown that Raman spectra free of fluorescence background can be reconstructed from narrow-band Raman measurements using traditional Wiener estimation. However, fluorescence-free Raman spectra are only available from those sophisticated Raman setups capable of fluorescence suppression. The reconstruction of Raman spectra with fluorescence background from narrow-band measurements is much more challenging due to the significant variation in fluorescence background. In this study, two advanced Wiener estimation methods, i.e. modified Wiener estimation and sequential weighted Wiener estimation, were optimized to achieve this goal. Both spontaneous Raman spectra and surface enhanced Raman spectra were evaluated. Compared with traditional Wiener estimation, two advanced methods showed significant improvement in the reconstruction of spontaneous Raman spectra. However, traditional Wiener estimation can work as effectively as the advanced methods for SERS spectra but much faster. The wise selection of these methods would enable accurate Raman reconstruction in a simple Raman setup without the function of fluorescence suppression for fast Raman imaging.