Multispectral open-air intraoperative fluorescence imaging.

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.

Automated Quantitative Bone Analysis in In Vivo X-ray Micro-Computed Tomography.

Measurement and analysis of bone morphometry in 3D micro-computed tomography volumes using automated image processing and analysis improve the accuracy, consistency, reproducibility, and speed of preclinical osteological research studies. Automating segmentation and separation of individual bones in 3D micro-computed tomography volumes of murine models presents significant challenges considering partial volume effects and joints with thin spacing, i.e., 50 to [Formula: see text]. In this paper, novel hybrid splitting filters are presented to overcome the challenge of automated bone separation. This is achieved by enhancing joint contrast using rotationally invariant second-derivative operators. These filters generate split components that seed marker-controlled watershed segmentation. In addition, these filters can be used to separate metaphysis and epiphysis in long bones, e.g., femur, and remove the metaphyseal growth plate from the detected bone mask in morphometric measurements. Moreover, for slice-by-slice stereological measurements of long bones, particularly curved bones, such as tibia, the accuracy of the analysis can be improved if the planar measurements are guided to follow the longitudinal direction of the bone. In this paper, an approach is presented for characterizing the bone medial axis using morphological thinning and centerline operations. Building upon the medial axis, a novel framework is presented to automatically guide stereological measurements of long bones and enhance measurement accuracy and consistency. These image processing and analysis approaches are combined in an automated streamlined software workflow and applied to a range of in vivo micro-computed tomography studies for validation.

Compensation of optical heterogeneity-induced artifacts in fluorescence molecular tomography: theory and in vivo validation.

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.