Optimization of a Widefield Structured Illumination Microscope for Non-Destructive Assessment and Quantification of Nuclear Features in Tumor Margins of a Primary Mouse Model of Sarcoma
Cancer is associated with specific cellular morphological changes, such as increased nuclear size and crowding from rapidly proliferating cells. In situ tissue imaging using fluorescent stains may be useful for intraoperative detection of residual cancer in surgical tumor margins. We developed a widefield fluorescence structured illumination microscope (SIM) system with a single-shot FOV of 2.1×1.6 mm (3.4 mm2) and sub-cellular resolution (4.4 μm). The objectives of this work were to measure the relationship between illumination pattern frequency and optical sectioning strength and signal-to-noise ratio in turbid (i.e. thick) samples for selection of the optimum frequency, and to determine feasibility for detecting residual cancer on tumor resection margins, using a genetically engineered primary mouse model of sarcoma. The SIM system was tested in tissue mimicking solid phantoms with various scattering levels to determine impact of both turbidity and illumination frequency on two SIM metrics, optical section thickness and modulation depth. To demonstrate preclinical feasibility, ex vivo 50 μm frozen sections and fresh intact thick tissue samples excised from a primary mouse model of sarcoma were stained with acridine orange, which stains cell nuclei, skeletal muscle, and collagenous stroma. The cell nuclei were segmented using a high-pass filter algorithm, which allowed quantification of nuclear density. The results showed that the optimal illumination frequency was 31.7 μm？1 used in conjunction with a 4×0.1 NA objective ( = 0.165). This yielded an optical section thickness of 128 μm and an 8.9×contrast enhancement over uniform illumination. We successfully demonstrated the ability to resolve cell nuclei in situ achieved via SIM, which allowed segmentation of nuclei from heterogeneous tissues in the presence of considerable background fluorescence. Specifically, we demonstrate that optical sectioning of fresh intact thick tissues performed equivalently in regards to nuclear density quantification, to physical frozen sectioning and standard microscopy.
References
[1]
Muldoon TJ, Pierce MC, Nida DL, Williams MD, Gillenwater A, et al. (2007) Subcellular-resolution molecular imaging within living tissue by fiber microendoscopy. Opt Express 15: 16413–16423.
[2]
Gareau DS (2009) Feasibility of digitally stained multimodal confocal mosaics to simulate histopathology. J Biomed Opt 14: 034050.
[3]
Gareau DS, Abeytunge S, Rajadhyaksha M (2009) Line-scanning reflectance confocal microscopy of human skin: comparison of full-pupil and divided-pupil configurations. Optics Letters 34: 3235–3237.
[4]
Muldoon TJ, Anandasabapathy S, Maru D, Richards-Kortum R (2008) High-resolution imaging in Barrett’s esophagus: a novel, low-cost endoscopic microscope. Gastrointest Endosc 68: 737–744.
[5]
Muldoon TJ, Thekkek N, Roblyer D, Maru D, Harpaz N, et al. (2010) Evaluation of quantitative image analysis criteria for the high-resolution microendoscopic detection of neoplasia in Barrett’s esophagus. J Biomed Opt 15: 026027.
[6]
Srivastava S, Rodriguez JJ, Rouse AR, Brewer MA, Gmitro AF (2008) Computer-aided identification of ovarian cancer in confocal microendoscope images. J Biomed Opt 13: 024021.
[7]
Tanbakuchi AA, Rouse AR, Udovich JA, Hatch KD, Gmitro AF (2009) Clinical confocal microlaparoscope for real-time in vivo optical biopsies. J Biomed Opt 14: 044030.
[8]
Udovich JA, Besselsen DG, Gmitro AF (2009) Assessment of acridine orange and SYTO 16 for in vivo imaging of the peritoneal tissues in mice. J Microsc 234: 124–129.
[9]
Tanbakuchi AA, Udovich JA, Rouse AR, Hatch KD, Gmitro AF (2010) In vivo imaging of ovarian tissue using a novel confocal microlaparoscope. Am J Obstet Gynecol 202: 90 e91–99.
[10]
Huston TL, Pigalarga R, Osborne MP, Tousimis E (2006) The influence of additional surgical margins on the total specimen volume excised and the reoperative rate after breast-conserving surgery. Am J Surg 192: 509–512.
[11]
Mendez JE, Lamorte WW, de Las Morenas A, Cerda S, Pistey R, et al. (2006) Influence of breast cancer margin assessment method on the rates of positive margins and residual carcinoma. Am J Surg 192: 538–540.
[12]
Balch GC, Mithani SK, Simpson JF, Kelley MC (2005) Accuracy of intraoperative gross examination of surgical margin status in women undergoing partial mastectomy for breast malignancy. Am Surg 71: 22–27; discussion 27–28.
[13]
Kotwall C, Ranson M, Stiles A, Hamann MS (2007) Relationship between initial margin status for invasive breast cancer and residual carcinoma after re-excision. Am Surg 73: 337–343.
[14]
Dillon MF, Mc Dermott EW, O’Doherty A, Quinn CM, Hill AD, et al. (2007) Factors affecting successful breast conservation for ductal carcinoma in situ. Ann Surg Oncol 14: 1618–1628.
[15]
Jacobs L (2008) Positive margins: the challenge continues for breast surgeons. Ann Surg Oncol 15: 1271–1272.
[16]
Cox CE, Ku NN, Reintgen DS, Greenberg HM, Nicosia SV, et al. (1991) Touch preparation cytology of breast lumpectomy margins with histologic correlation. Arch Surg 126: 490–493.
[17]
McLaughlin SA, Ochoa-Frongia LM, Patil SM, Cody HS, 3rd, Sclafani LM (2008) Influence of frozen-section analysis of sentinel lymph node and lumpectomy margin status on reoperation rates in patients undergoing breast-conservation therapy. J Am Coll Surg 206: 76–82.
[18]
Brown JQ, Bydlon TM, Kennedy SA, Geradts J, Wilke LG, et al. (2010) Assessment of breast tumor margins via Quantitative Diffuse Reflectance Imaging. Biomedical Applications of Light Scattering IV Proc. SPIE Vol. 7573: 75730O.
[19]
Bydlon TM, Kennedy SA, Richards LM, Brown JQ, Yu B, et al. (2010) Performance metrics of an optical spectral imaging system for intra-operative assessment of breast tumor margins. Optics Express 18: 8058–8076.
[20]
Yu CC, Lau C, O’Donoghue G, Mirkovic J, McGee S, et al. (2008) Quantitative spectroscopic imaging for non-invasive early cancer detection. Opt Express 16: 16227–16239.
[21]
Krishnaswamy V, Hoopes PJ, Samkoe KS, O’Hara JA, Hasan T, et al. (2009) Quantitative imaging of scattering changes associated with epithelial proliferation, necrosis, and fibrosis in tumors using microsampling reflectance spectroscopy. J Biomed Opt 14: 014004.
[22]
Laughney AM, Krishnaswamy V, Garcia-Allende PB, Conde OM, Wells WA, et al. (2010) Automated classification of breast pathology using local measures of broadband reflectance. J Biomed Opt 15: 066019.
[23]
Lue N, Kang JW, Yu CC, Barman I, Dingari NC, et al. (2012) Portable optical fiber probe-based spectroscopic scanner for rapid cancer diagnosis: a new tool for intraoperative margin assessment. PLoS One 7: e30887.
[24]
Valdes PA, Fan X, Ji S, Harris BT, Paulsen KD, et al. (2010) Estimation of brain deformation for volumetric image updating in protoporphyrin IX fluorescence-guided resection. Stereotact Funct Neurosurg 88: 1–10.
[25]
Themelis G, Harlaar NJ, Kelder W, Bart J, Sarantopoulos A, et al. (2011) Enhancing surgical vision by using real-time imaging of alphavbeta3-integrin targeted near-infrared fluorescent agent. Ann Surg Oncol 18: 3506–3513.
[26]
Mito JK, Ferrer JM, Brigman BE, Lee CL, Dodd RD, et al. (2012) Intraoperative detection and removal of microscopic residual sarcoma using wide-field imaging. Cancer 118: 5320–5330.
[27]
Puvanakrishnan P, Diagaradjane P, Kazmi SM, Dunn AK, Krishnan S, et al. (2012) Narrow band imaging of squamous cell carcinoma tumors using topically delivered anti-EGFR antibody conjugated gold nanorods. Lasers Surg Med 44: 310–317.
[28]
Nguyen FT, Zysk AM, Chaney EJ, Kotynek JG, Oliphant UJ, et al. (2009) Intraoperative evaluation of breast tumor margins with optical coherence tomography. Cancer Res 69: 8790–8796.
[29]
Gareau D, Bar A, Snaveley N, Lee K, Chen N, et al. (2012) Tri-modal confocal mosaics detect residual invasive squamous cell carcinoma in Mohs surgical excisions. J Biomed Opt 17: 066018.
[30]
Neil MAA, Juskaitis R, Wilson T (1997) Method of obtaining optical sectioning by using structured light in a conventional microscope. Optics Letters 22: 1905–1907.
[31]
Chasles F, Dubertret B, Boccara AC (2007) Optimization and characterization of a structured illumination microscope. Opt Express 15: 16130–16140.
[32]
Hagen N, Gao L, Tkaczyk TS (2012) Quantitative sectioning and noise analysis for structured illumination microscopy. Opt Express 20: 403–413.
[33]
Gustafsson MGL (2000) Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy. Journal of Microscopy-Oxford 198: 82–87.
[34]
Mertz J (2011) Optical sectioning microscopy with planar or structured illumination. Nature Methods 8: 811–819.
[35]
Cole MJ, French PMW, Siegel J, Webb SED, Jones R, et al. (2001) Time-domain whole-field fluorescence lifetime imaging with optical sectioning. Journal of Microscopy-Oxford 203: 246–257.
[36]
Neil MAA, Wilson T, Juskaitis R (1998) A light efficient optically sectioning microscope. Journal of Microscopy-Oxford 189: 114–117.
[37]
Hanley QS, Verveer PJ, Gemkow MJ, Arndt-Jovin D, Jovin TM (1999) An optical sectioning programmable array microscope implemented with a digital micromirror device. J Microsc 196: 317–331.
[38]
Elson DS, Siegel J, Webb SED, Leveque-Fort S, Parsons-Karavassilis D, et al. (2002) Wide-field fluorescence lifetime imaging with optical sectioning and spectral resolution applied to biological samples. Journal of Modern Optics 49: 985–995.
[39]
Santos S, Chu KK, Lim D, Bozinovic N, Ford TN, et al. (2009) Optically sectioned fluorescence endomicroscopy with hybrid-illumination imaging through a flexible fiber bundle. J Biomed Opt 14: 030502.
[40]
Lim D, Ford TN, Chu KK, Mertz J (2011) Optically sectioned in vivo imaging with speckle illumination HiLo microscopy. J Biomed Opt 16: 016014.
[41]
Mazhar A, Cuccia DJ, Gioux S, Durkin AJ, Frangioni JV, et al.. (2010) Structured illumination enhances resolution and contrast in thick tissue fluorescence imaging. J Biomed Opt 15: -.
[42]
Karadaglic D, Wilson T (2008) Image formation in structured illumination wide-field fluorescence microscopy. Micron 39: 808–818.
[43]
Stokseth PA (1969) Properties of a Defocused Optical System. Journal of the Optical Society of America 59: 1314–&.
[44]
Kirsch DG, Dinulescu DM, Miller JB, Grimm J, Santiago PM, et al. (2007) A spatially and temporally restricted mouse model of soft tissue sarcoma. Nat Med 13: 992–997.
[45]
Schondorf H, Naujoks H (1985) Determining the nuclear area in normal breast epithelia and in the nuclei of mammary carcinomas. J Cancer Res Clin Oncol 109: 241–244.
[46]
Brown JQ, Bydlon TM, Richards LM, Yu B, Kennedy SA, et al. (2010) Optical assessment of tumor resection margins in the breast. IEEE J Sel Top Quantum Electron 16: 530–544.
[47]
Parthasarathy AB, Tom WJ, Gopal A, Zhang X, Dunn AK (2008) Robust flow measurement with multi-exposure speckle imaging. Opt Express 16: 1975–1989.
[48]
Mito JK, Min HD, Ma Y, Carter JE, Brigman BE, et al. (2013) Oncogene-dependent control of miRNA biogenesis and metastatic progression in a model of undifferentiated pleomorphic sarcoma. J Pathol 229: 132–140.
