Imaging Breast Tissue Pathologies with Sub-Diffuse Scattering in
the Spatial Frequency Domain
David M. McClatchy III1*
1
1
Thayer School of Engineering, Dartmouth College, 14 Engineering Drive, Hanover, NH 03755
Introduction
Spectroscopic elastic scattering measurements can provide sensitivity over multiple size scales ranging from
nanometers to millimeters as tradeoffs in Rayleigh and Mie scatterers yield a unique scattering spectrum. Changes in
tissue morphology and cellular ultrastructure have been detected using spectroscopic scattering information,
validating the clinical potential of elastic scattering as an endogenous, label-free contrast mechanism1,2,3. However,
strong multiple scattering dramatically decreases scattering contrast and sensitivity, as remitted scattering spectra
will have averaged contributions over longer photon path lengths and larger light sampling volumes. Many
techniques, such as single-fiber spectroscopy4 and dark field microscopy1, have been used to limit the light transport
to a sub-diffusive regime by collecting photons at or near the source. But these techniques require raster scanning in
order to produce a wide field (multiple centimeters) image.
Spatial frequency domain imaging (SFDI) is a wide field imaging technique that involves spatially modulating
planar photon density waves to control the effective penetration depth, and inverting the demodulated images with a
diffusion model to map optical properties5. Previous studies have utilized SFDI to create diffuse spectroscopic
scattering maps of breast lumpectomy specimens, which were shown to correlate to breast tissue histopathology2.
With the wide field imaging capability and sensitivity to breast tissue pathology, SFDI is an ideal candidate for
intraoperative breast tumor margin assessment. However, diffuse scattering limits resolution and sensitivity to
localized changes in tissue morphology, but recently sub-diffusive SFDI has been demonstrated utilized high spatial
frequency modulation patterns3. This work focuses on both quantifying scattering in a sub-diffusive regime, imaging
these changes with SFDI, and also translating this technology for intraoperative breast tumor margin assessment.
2
Quantitative Sub-Diffusive Scatter Imaging
Barring the effects of interference and polarization, multiple elastic light scattering through turbid media can be
described by frequency of scattering events, given by the scattering coefficient 𝜇! , the probability of the scattered
angle, given by the scattering phase function, 𝑃(𝜃), and the scattering anisotropy or the cosine expected of the
scattered angle, given by the first moment of 𝑃(cos (𝜃)) as 𝑔! = < cos 𝜃 >. In the diffuse regime, these parameters
are lumped into a single scattering parameter 𝜇!! = 𝜇! 1 − 𝑔! , which describes the frequency of scattering events
on diffuse scattering path lengths where scattering appears isotropic after a sufficient amount of smaller scattering
events. To be in the diffuse regime, there must be a source detector separation of multiple reduced mean free paths.
But, measurements that sample sub-diffusive light with source detector separations less than one reduced mean free
path, need to account for large backscattering angles of photons that will likely escape the medium and be collected.
Previous single fiber reflectance studies have shown that a weighted ratio of the first two Legendre moments of the
phase function, 𝛾 =
!!!!
!!!!
, can be used to accurately model reflectance in a sub-diffusive regime4.
In the spatial frequency domain, Cuccia et al. 2009 highlighted that by relating the inverse of the spatial
frequency, 𝑓!!! , to a source detector saturation, one can approximate the maximum spatial frequency where there is
diffuse sample, which is 𝑓! ≤ 0.33𝜇!" 5. Spatial frequencies higher than this limit are only sensitive to a very
superficial volume, where there is sub-diffusive transport. Therefore imaging beyond this limit yields sensitivity to
the phase function and also can produce higher contrast scattering images with limited multiple scattering. Recently,
Kanick, McClatchy et al. 2014 demonstrated quantitatively imaging higher order moments of the phase function
using high spatial frequencies, by inverting the demodulated images to a sub-diffusive reflectance model3. One
application of this is shown in Fig 1 (a-d), where a sub-diffusive demodulated image (b) of a hand reveals a scar due
to morphological changes in the collagen, and this is also seen in the quantitative map of gamma (d). However, this
contrast is not seen in the diffuse image (a) or in the reduced scattering coefficient map (c). Results of a new study is
shown in Fig. 1 (e-k), where tissue simulating phantoms were made with the same reduced scattering coefficient
!
(𝜇! (!"# !")
= 1.6 mm-1) but different fractal distributions (Df = 3.6 to 4.6) of polystyrene spheres of diameters
ranging from 99 nm to 20 𝜇m6. A white light image is shown in (e) and a sub-diffusive demodulated image at 658
1
nm is shown in (f), which demonstrates signal contrast between the different phantoms arising from the unique
phase function for each fractal distribution. Estimated versus known reduced scattering coefficients (j) and gamma
(k) are shown for each phantom over multiple wavelengths (658, 730, and 850 nm). Fig. 1 (g-i) show estimated
gamma values versus fractal dimension for 658, 730, and 850 nm respectively, which shows a linear relationship
between gamma and fractal dimension. This work demonstrates a capability to perform quantitative wide field
imaging of microscopic alterations in morphology and sensitivity to the scattering phase function.
Figure 1. (a-d) Sub-diffusive imaging of a hand with a scar in the spatial frequency domain at 730 nm. (e-k) Tissue simulating
phantom experiments using different fractal distributions of polystyrene spheres to obtain a known phase function using Mie
theory. It should be highlighted that in the sub-diffusive demodulated image at 658 nm (f), every phantoms has the same reduced
scattering and absorption coefficient and so the contrast is arising from differences in phase function between the phatoms.
3
Intraoperative Breast Tumor Margin Assessment
Due to improvements in breast cancer screening technologies and also with the adoption of neoadjuvent
chemotherapy, an increasing number of patients are receiving breast conserving surgery (BCS) instead of a full
mastectomy. While this is favorable for this patient, this puts additional burden on the surgeon, as many of these
tumors will be non-palpable and difficult to see on radiographic imaging making it very hard for the surgeon to
delineate the boundaries of the tumor. As a result, residual tumor is often left in the surgical cavity and re-excision
rates are in the range of 20-40% depending on the protocol used to define a positive margin7. Therefore,
intraoperative surgical guidance to determine if the margins are free of cancer is very much needed to curb reexcision rates.
Previously, a raster scanning confocal dark field microscope demonstrated very powerful sensitivity to different
breast tissue pathologies, but could only scan a small area and therefore not ideal for clinical translation1. SFDI was
also studied, and the diffuse spectroscopic scattering power showed good sensitivity while providing wide field
imaging, but lacked the local sensitivity and resolution provided by the scanning microscope2. However, subdiffusive SFDI is able to provide both microscopic sensitivity and also wide field imaging capabilities needed for
real time decision making during a BCS procedure.
A pilot study was conducted to demonstrate the ability of sub-diffusive SFDI to image during a BCS procedure
without interfering with the current clinical protocols8. One such protocol is inking the margins of the specimen as it
is excised to preserve its orientation, as the specimens are very amorphous with no landmarks on its surface. To
overcome this, a two-step inking protocol was created where the specimen was first marked with food dye, which
has negligible scattering and absorption in the NIR, then imaged with the SFDI system, and then marked with
traditional surgical inks over the dyes8. This allowed for intraoperative imaging of the specimen margins, without
comprising the surgeon’s ability to ink the margins as he or she normally would. In Fig. 2 (a) one can see white light
images of all the margins of a specimen after being marked with the food dye, in (b) the same specimen is
illuminated with an 850 nm LED showing minimal effects of the food dye, and in (c) is a sub-diffusive demodulated
image (fx = 0.5 mm-1) showing scattering contrast. Also a cross section of a mastectomy was imaged to show the
high-resolution scattering contrast from sub-diffusive SFDI in Fig. 2 (d-g). In Fig 2 (d), a white light image of the
2
mastectomy cross section is shown, and in (e) a diffuse image at 658 nm showing minimal contrast due to very
strong multiple light scattering. In Fig. 2 (f) is a demodulated image at fx = 0.15 mm-1 showing increased contrast
with a more superficial signal. However, the image in (f) represent a diffuse signal, but in Fig. 2 (g) one can see a
great increase in contrast and resolution with a sub-diffusive sampling volume at fx = 0.5 mm-1. It should also be
noted that with a more sensitive CCD and higher power illumination, it would possible to image at even higher
spatial frequencies, but with the current system higher spatial frequencies result in increased noise and poorer SNR.
Figure 2. (a) White light image of a lumpectomy specimen full marked with food dye. (b) A diffuse (fx = 0 mm-1) image at 850
nm of the same specimen, and (c) a demodulated image at fx = 0.5 mm-1. (d) A white light image of a cross section of a
mastectomy and demodulation images at (e) fx = 0 mm-1, (f) fx = 0.15 mm-1, and (g) fx = 0.5 mm-1.
4
Ongoing and Future Research
Currently, we are conducting an experimental protocol for imaging freshly resected breast cancer tissue specimens,
which has been deemed appropriate for the tissue bank. After imaging, the tissue will immediately go back to
pathology for standard histopathological processing, but we will receive a full H&E stained gross section for the
specimen and also histopathological analysis and diagnoses over the entire section. This will allow us to create a
database of spectroscopic scattering images co-registered to breast tissue diagnoses and determine the most sensitive
scattering parameters for breast tissue classification.
References
1. A. M. Laughney et al., "Scatter spectroscopic imaging distinguishes between breast pathologies in tissues relevant to surgical margin assessment," Clin Cancer Res 18(22), 6315-­‐6325 (2012). 2. A. M. Laughney et al., "Spectral discrimination of breast pathologies in situ using spatial frequency domain imaging," Breast Cancer Res 15(4), R61 (2013). 3. S. C. Kanick et al., "Sub-­‐diffusive scattering parameter maps recovered using wide-­‐field high-­‐frequency structured light imaging," Biomed Opt Exp 5(10), 3376-­‐3390 (2014). 4. U. A. Gamm et al., "Quantification of the reduced scattering coefficient and phase-­‐function-­‐dependent parameter gamma of turbid media using multidiameter single fiber reflectance spectroscopy: experimental validation," Optics letters 37, 1838-­‐1840 (2012). 5. D. J. Cuccia et al., "Quantitation and mapping of tissue optical properties using modulated imaging," J Biomed Opt 14(2), 024012 (2009). 6. McClatchy et al., “Sub-­‐diffusive spatial frequency domain imaging of fractal distributions of spheres: recovering reduced scattering coefficent and phase function gamma parameter”. In Preparation, 2015. 7. R. G. Pleijhuis et al., "Obtaining adequate surgical margins in breast-­‐conserving therapy for patients with early-­‐stage breast cancer: current modalities and future directions," Ann Surg Oncol 16(10), 2717-­‐2730 (2009). 8. McClatchy et al., “Molecular dyes used for surgical specimen margin orientation allow for intraoperative optical assessment during breast conserving surgery”. Under Review -­‐ J Biomed Opt, 2015. 3