Calibration of fluorescence imaging for tumor surgical margin delineation: multistep registration of fluorescence and histological images

2019 
Although a greater extent of tumor resection is important for patients’ survival, complete tumor removal, especially tumor margins, remains challenging due to the lack of sensitivity and specificity of current surgical guidance techniques at the margins. Intraoperative fluorescence imaging with targeted fluorophores is promising for tumor margin delineation. To verify the tumor margins detected by the fluorescence images, it is necessary to register fluorescence with histological images, which provide the ground truth for tumor regions. However, current registration methods compare fluorescence images to a single-layer histological slide, which is selected subjectively and represents a single plane of the three-dimensional tumor. A multistep pipeline is established to correlate fluorescence images to stacked histological images, including fluorescence calibration and multistep registration. Multiple histological slices are integrated as a two-dimensional (2-D) tumor map using optical attenuation model and average intensity projection. A BLZ-100-labeled medulloblastoma mouse model is used to test the whole framework. On average, the synthesized 2-D tumor map outperforms the selected best slide as ground truth [Dice similarity coefficient (DSC): 0.582 versus 0.398, with significant differences; mean area under the curve (AUC) of the receiver operating characteristic curve: 88% versus 85.5%] and the randomly selected slide as ground truth (DSC: 0.582 versus 0.396 with significant differences; mean AUC: 88% versus 84.1% with significant differences), which indicates our pipeline is reliable and can be applied to investigate targeted fluorescence probes in tumor margin detection. Following this proposed pipeline, BLZ-100 shows enhancement in both tumor cores and tumor margins (mean target-to-background ratio: 8.64  ±  5.76 and 4.82  ±  2.79, respectively).
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    45
    References
    3
    Citations
    NaN
    KQI
    []
    Baidu
    map