Differentiating retroperitoneal liposarcoma tumors with optical coherence tomography Dina Lev1, Stepan A. Baranov2*, Esteban F. Carbajal2, Eric D. Young1, Raphael E. Pollock1 and Kirill V. Larin2,3,4† 1

Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, 8515 Fannin St, Houston, TX 77054, USA 2 Department of Biomedical Engineering, University of Houston, 3605 Cullen Blvd SERC bldg, Houston, TX 77204, USA 3 Department of Physiology and Biophysics, Baylor College of Medicine One Baylor Plaza, Houston, TX 77030, USA 4 Institute of Optics and Biophotonics, Saratov State University, Saratov 410012, Russia ABSTRACT

Liposarcoma (LS) is a rare and heterogeneous group of malignant mesenchymal neoplasms exhibiting characteristics of adipocytic differentiation. Currently, radical surgical resection represents the most effective and widely used therapy for patients with abdominal/retroperitoneal LS, but the presence of contiguous essential organs, such as the kidney, pancreas, spleen, adrenal glands, esophagus or colon, as well as often reoccurrence of LS in A/RP calls for the enhancement of surgical techniques to minimize resection and avoid LS reoccurrences. Difficulty in detecting the margins of neoplasms due to their affinity to healthy fat tissue accounts for the high reoccurrence of LS within A/RP. Nowadays, the microscopic detection of margins is possible only by use of biopsy, and the minimization of surgical resection of healthy tissues is challenging. In this presentation we’ll demonstrate the initial OCT results for the imaging and distinction of LS and normal human fat tissues and clear detection of tumor boundaries. Keywords: cancer, imaging, liposarcoma, optical coherence tomography.

1. INTRODUCTION Liposarcoma (LS) is the most common retroperitoneal sarcoma histological subtype.1 Frequently growing to massive (>15 cm) size prior to detection, surgical resection remains the mainstay of therapy. However, the relative inability to intraoperatively assess margins of resection coupled with the frequent necessity to resect adjacent organs accounts for unacceptably high rates of postoperative morbidity, impairments in quality of life, recurrence, and diseasespecific mortality.2,3 To address these concerns, improved intraoperative approaches to accurately assess LS margins of resection are needed, thereby hopefully resulting in a higher incidence of final margin negativity while potentially sparing adjacent organs from being resected, hence our interest in developing and applying such technologies. Pertinently, lessons learned may be applicable to more common solid tumors as well as their surgical management. Traditional imaging method like ultrasonography (US), conventional radiography, X-ray fluoroscopy, computed tomography (CT), and magnetic resonance imaging (MRI) has significant limitations for applications in surgical procedures due to insufficient resolution, long imaging time, and requirements for contrast agents to be introduced to the tissues. The standard option in all operating rooms (ORs) is having samples of the tissue stained with H&E and then viewed under a microscope. From studying the tissue structure, a pathologist can determine whether or not that sample has any cancerous tissues. The downside of this option is the time needed for the process which could take up to an hour. Therefore, there is a great need for a method for the surgeon to immediately classify the tissue in the areas of tumor * †

Currently with Bioptigen Inc, NC Contact email: [email protected] Advanced Biomedical and Clinical Diagnostic Systems IX, edited by Anita Mahadevan-Jansen, Tuan Vo-Dinh, Warren S. Grundfest, Proc. of SPIE Vol. 7890, 78900U · © 2011 SPIE · CCC code: 1605-7422/11/$18 doi: 10.1117/12.875085 Proc. of SPIE Vol. 7890 78900U-1 Downloaded from SPIE Digital Library on 01 Mar 2011 to 66.162.15.212. Terms of Use: http://spiedl.org/terms

boundaries. Here we demonstrate preliminary results from development of such a method based on high resolution realtime 3D imaging to assess the area where the normal and cancerous fatty tissues meet using Optical Coherence Tomography (OCT) technique. The OCT-based method for real-time assessment of LS margins has the following advantages: it is nondestructive, noninvasive, has high spatial resolution, able to assess tissue in real time, and, most importantly, has ability to be incorporated into standard OR environment. It also could be easily combined with handheld optical probe for the intra-operative imaging.

2. MATERIALS AND METHODS 2.1 Imaging System A spectral-domain OCT (SD-OCT) system (Fig 1) was used in this study. The system utilize a high power (~20 mW) Superluminescent Laser Source (Superlum Inc, Russia) with a central wavelength λ0 = 840 nm and bandwidth ∆λ = 49 nm which corresponds to an axial resolution of 6µm. A fiber-based 50/50 Michelson interferometer is used to direct the interference signal to a grating-based spectrometer. The spectrometer consists of an achromatic doublet lens with focal length f= 150 mm that collimates the beam to fall on a grating which has 1200 grooves per mm and another achromatic lens with f= 150 mm that causes the spectrum to fall on the CCD of a Line Scan Camera (L104k-2k Basler camera). The camera has a 2k resolution with a maximum line rate of 29.2 kHz. The acquired data are captured using a PCI 1428 (National Instruments) frame grabber interface card. OCT A-scans (1D depth profiles) were obtained by computing the Discrete Fourier Transformation of the interferograms detected by the spectrometer, after converting the data to linear k-space using laser spectra information, and 2D images (B-scans) and 3D structures (C-scans) were constructed by lateral scanning which was performed by the galvanometer mirrors mounted in the sample arm over the area of up to 3 mm × 3 mm. The full imaging depth was about 3.4 mm in air and about 2.2 mm in tissue.

Reference arm

Broadband source Beamsplitter 50/50

Grating

CCD

IMAQ

Computer

Sample arm

Fig 1: Experimental setup

2.2 Tissue Preparation and Imaging Tumor samples were taken after surgical resection at the University of Texas M. D. Anderson Cancer Center (UTMDACC) hospital and were kept in sterile phosphate buffered saline until they were imaged on the same day using the SD-OCT system. Protocols for tissue processing were approved by the UTMDACC and University of Houston Biosafety Committees. After imaging all tissue samples were formalin fixed and paraffin embedded, then prepared by routine methods for histological analysis. The region imaged using OCT was matched to the corresponding region on an H&E-stained slide. Histologic diagnosis and classification of samples was performed by a UTMDACC sarcoma pathologist.

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3. RESUL LTS AND DIS SCUSSION Fig 2 shows a reepresentative gross g image off a LS samplee. Fig 3 show ws a representaative result froom OCT L that illustratte the contrast difference d betw ween the norm mal and canceroous tissue in thee boundary reggion. Fig imaging of LS 4 depicts a liposarcoma l tisssue sample with w correspondding histologyy image. The difference d betw ween the two types of tissues can bee clearly seen in i the OCT image.

Fig 2: Representativee gross image off LS tissue showiing normal and LS L tissue regionns.

Fig 3: OCT images of the boundary betweeen normal and LS S clearly show thhe presence of tw wo areas with diistinct optical prooperties. The dotted arrrow points to no ormal fatty tissuue with characterristic porous apppearance due to large l fat globuless. The solid arroow is the tum mor area that is more m optically homogeneous. h

Fig 4: a) 2D structural imaage of a well-diff fferentiated lipossarcoma tissue im maged with OCT T. b) Correspondding histology im mage of the strucctural image at 50X.

These preliminary data d demonstraate that OCT im mages of norm mal tissues has characteristic porous p appearaance due to large fat globules g whilee the tumor areea is more opttically homogeeneous and deense -- a propeerty well-attribbuted for

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cancerous tissues. However, additional studies are needed to understand the accuracy of OCT-based method to assess normal, well-differentiated liposarcomas (WD-LS, characterized as low-grade malignances and neoplasms predominantly composed of cancer fat cells and often contain enlarged adipocytes that show greater variation in size, atypical hyperchromatic cells with angular nuclei, and lipoblasts), and dedifferentiated LS (DD-LS, usually high-grade tumors and include mostly nonlipogenic components and resemble malignant fibrous histiocytoma or fibrosarcoma). Therefore, the structural difference between normal fat and WD-LS tissues might not be as obvious as in the case with DD-LS, and, thus, additional algorithms of tissue analysis should be employed. One of the methods for quantitative analysis of OCT data is based on the evaluation of 1D depth profiles (Ascans) from within the tissues. In the first approximation, the slope of light attenuation in tissues as a function of depth (i.e. slope of OCT A-scans, plotted in logarithmic scale, OCTSS) is proportional to total attenuation coefficient of the tissues, µt: , where µs and µa are the scattering and absorption coefficients, respectively, and approximated as 4:

.

in the NIR spectral range. In a simple model of scattering spheres, µs can be .

1

.

, where g is the tissue anisotropy factor, r is the radius of

and nISF the scattering centers, ρs the volume density of the scatterers, λ the wavelength of the incident light, and refractive indices of the scatterers and surrounding medium, respectively. Tumor invasion is increasing the volume density of the cells (ρs), and, hence, the scattering coefficient is also increased: 1

.

, where

.

.

is the time-dependent increase in the cell density due to tumor growth. Therefore, increasing the

volume density of the cells in the tissue will raise µs. Since the OCT technique measures the in-depth light distribution with high resolution, changes in the in-depth distribution of tissue scattering coefficient is reflected in changes in the OCT signal slope. Previously, we have utilized this property of OCTSS dependence on changes in tissues scattering for noninvasive assessment of molecular diffusion 5-16, development of novel methods for early diagnostics of cardiovascular diseases 7,17,18, and development of a novel noninvasive OCT-based blood glucose biosensor 6,8,16,19-22. Therefore, this analysis might provide an additional metric for tissue classification.

4. CONCLUSIONS Currently, radical surgical resection represents the most effective and widely used therapy for patients with abdominal/retroperitoneal liposarcomas, but the presence of contiguous essential organs, such as the kidney, pancreas, spleen, adrenal glands, esophagus or colon, as well as often reoccurrence calls for the enhancement of surgical techniques. Nowadays, the microscopic detection of margins is possible only by use of biopsy, and the minimization of surgical resection of healthy tissues is challenging. In this paper we demonstrated the initial OCT results for the imaging and distinction of LS and normal human fat tissues and clear detection of tumor boundaries.

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