Speckle Contrast Diffuse Correlation Tomography (scDCT)
Speckle contrast diffuse correlation tomography (scDCT; U.S. Patent #9,861,319, 2018) system enables depth-sensitive imaging of blood flow in deep tissues with complex geometries. By integrating galvo-mirror–scanned near-infrared light with CMOS-based speckle contrast imaging, scDCT acquires and reconstructs high-resolution 2D and 3D blood flow maps. This technology has been successfully used for continuous and longitudinal imaging of cerebral hemodynamics in rodents, neonatal piglets, and human newborns, and has also been applied to mastectomy skin flaps as well as burned and wounded tissues.
Fig. 1: (a) Instrument design. (b) Optical design.
(Rabienia Haratbar, Samaneh, et al. “Noncontact diffuse optical imaging of blood flow and oxygenation distributions in reconstructive rat skin flaps.” Biomedical Optics Express 16.9 (2025): 3740-3758.)
Fig. 2: Effect of sampling density on spatial resolution of DSCT. (a)–(d) Numbers of source locations on the UK logo phantom with a top layer thickness of 1 mm: 100 (10 × 10), 225 (15 × 15), 400 (20 × 20), and 900 (30 × 30). (e)–(h) Resulting 2D flow maps at the depth of 2 mm with the source
numbers of 100, 225, 400, and 900, respectively. Five sequential flow maps were averaged to improve the SNR.（Mohtasebi, Mehrana, et al. “Depth-sensitive diffuse speckle contrast topography for high-density mapping of cerebral blood flow in rodents.” Neurophotonics 10.4 (2023): 045007-045007.）
Fig. 3: (a) The rat was anesthetized
with 1% to 2% isoflurane and placed on a heating blanket with its head fixed on a stereotaxic frame.
The hybrid instrument was set up overhead for 2D mapping of CBF distributions. (b) Optical design
of DSCT. (c) NIR point source was focused on the exposed skull for DSCT measurements.（Mohtasebi, Mehrana, et al. “Depth-sensitive diffuse speckle contrast topography for high-density mapping of cerebral blood flow in rodents.” Neurophotonics 10.4 (2023): 045007-045007.）
Fig. 4: The schematic of MW-scDCT system for imaging of rat flaps. (a) Instrument
design. (b)Reconstructed 2D maps of rBFI, ∆[HbO2], and ∆[Hb] over 7 days, consistent with the visual boservations in color photos.(Rabienia Haratbar, Samaneh, et al. “Noncontact diffuse optical imaging of blood flow and oxygenation distributions in reconstructive rat skin flaps.” Biomedical Optics Express 16.9 (2025): 3740-3758.)
Fig. 5: Intraoperative Imaging of Mastectomy Skin Flaps.
(a) The upgraded scDCT for noncontact 3D imaging of blood flow distributions in
mastectomy skin flaps. (b) Using a single sCMOS camera to measure both blood flow
distribution (by scDCT) and tissue surface geometry (by PST). Movement of red blood
cells in the measured tissue volume (“banana-shape”) produces continuous laser speckle
fluctuations on the tissue surface, which is captured by the sCMOS camera. These
boundary data from multiple sources (e.g., S 1, S 2…) and multiple pixel-windows/detectors (e.g., D1, D2…) are input into the FEM-based program for reconstruction of blood flow distributions. (c) The S-D distribution on the X-Y plane. (d) The scDCT and SPY-PHI measurements during mastectomy in the operating room.(Mazdeyasna, Siavash, et al. “Intraoperative optical and fluorescence imaging of blood flow distributions in mastectomy skin flaps for identifying ischemic tissues.” Plastic and reconstructive surgery 150.2 (2022): 282-287.)
Fig. 6: Steps and Corresponding Results to Compare the scDCT and SPY-PHI Measurements in P12 (a) The original ICG map obtained by SPY-PHI. The dashed red ellipses show high
intensity perfusions as artifacts due to ICG augmentations. The dashed yellow box
represents the selected ROI of 80 × 80 cm 2 for scDCT. (b) A square area of 20 × 20 mm 2
was superimposed on top of the ICG map at the ischemic region with the lowest blood flow
value detected by the scDCT. (c) The area of 20 × 20 mm 2 was segmented into 8
regions/contours based on ICG perfusion levels. (d) For illustrative clarity, a morphologic
filter was applied on Figure 1d to show the 8 regions/contours (C1 to C8). (e) A top view
of blood flow distribution reconstructed by the scDCT. (f) A cube of 20 × 20 × 20 mm 3
was selected at the ischemic area with the lowest blood flow. (g) The cube of 20 × 20 × 20
mm 3 was segmented into 8 volumes/contours based on blood flow levels. Only 4 contours
(C2, C4, C6, and C8) out of 8 are shown to facilitate better illustration.(Mazdeyasna, Siavash, et al. “Intraoperative optical and fluorescence imaging of blood flow distributions in mastectomy skin flaps for identifying ischemic tissues.” Plastic and reconstructive surgery 150.2 (2022): 282-287.)