RESUMO
Intraoperative fluorescence imaging informs decisions regarding surgical margins by detecting and localizing signals from fluorescent reporters, labeling targets such as malignant tissues. This guidance reduces the likelihood of undetected malignant tissue remaining after resection, eliminating the need for additional treatment or surgery. The primary challenges in performing open-air intraoperative fluorescence imaging come from the weak intensity of the fluorescence signal in the presence of strong surgical and ambient illumination, and the auto-fluorescence of non-target components, such as tissue, especially in the visible spectral window (400-650 nm). In this work, a multispectral open-air fluorescence imaging system is presented for translational image-guided intraoperative applications, which overcomes these challenges. The system is capable of imaging weak fluorescence signals with nanomolar sensitivity in the presence of surgical illumination. This is done using synchronized fluorescence excitation and image acquisition with real-time background subtraction. Additionally, the system uses a liquid crystal tunable filter for acquisition of multispectral images that are used to spectrally unmix target fluorescence from non-target auto-fluorescence. Results are validated by preclinical studies on murine models and translational canine oncology models.
Assuntos
Microscopia de Fluorescência/métodos , Neoplasias/diagnóstico por imagem , Imagem Óptica/métodos , Animais , Cães , Corantes Fluorescentes , Humanos , Cristais LíquidosRESUMO
We present a method for reduction of image artifacts induced by the optical heterogeneities of tissue in fluorescence molecular tomography (FMT) through identification and compensation of image regions that evidence propagation of emission light through thin or low-absorption tunnels in tissue. The light tunneled as such contributes to the emission image as spurious components that might substantially overwhelm the desirable fluorescence emanating from the targeted lesions. The proposed method makes use of the strong spatial correlation between the emission and excitation images to estimate the tunneled components and yield a residual image that mainly consists of the signal due to the desirable fluorescence. This residual image is further refined using a coincidence mask constructed for each excitation-emission image pair. The coincidence mask is essentially a map of the "hot spots" that occur in both excitation and emission images, as such areas are often associated with tunneled emission. In vivo studies are performed on a human colon adenocarcinoma xenograft tumor model with subcutaneous tumors and a murine breast adenocarcinoma model with aggressive tumor cell metastasis and growth in the lungs. Results demonstrate significant improvements in the reconstructions achieved by the proposed method.