Structured Illumination Microscopy and a Quantitative Image Analysis for the Detection of Positive Margins in a Pre-Clinical Genetically Engineered Mouse Model of Sarcoma.

Henry L Fu,David G Kirsch,Rebecca M Willett,Nimmi Ramanujam,Melodi J Whitley,J Quincy Brown,Diana M Cardona,Jenna L Mueller

doi:10.1371/journal.pone.0147006

Abstract

Intraoperative assessment of surgical margins is critical to ensuring residual tumor does not remain in a patient. Previously, we developed a fluorescence structured illumination microscope (SIM) system with a single-shot field of view (FOV) of 2.1×1.6 mm (3.4 mm2) and sub-cellular resolution (4.4 μm). The goal of this study was to test the utility of this technology for the detection of residual disease in a genetically engineered mouse model of sarcoma. Primary soft tissue sarcomas were generated in the hindlimb and after the tumor was surgically removed, the relevant margin was stained with acridine orange (AO), a vital stain that brightly stains cell nuclei and fibrous tissues. The tissues were imaged with the SIM system with the primary goal of visualizing fluorescent features from tumor nuclei. Given the heterogeneity of the background tissue (presence of adipose tissue and muscle), an algorithm known as maximally stable extremal regions (MSER) was optimized and applied to the images to specifically segment nuclear features. A logistic regression model was used to classify a tissue site as positive or negative by calculating area fraction and shape of the segmented features that were present and the resulting receiver operator curve (ROC) was generated by varying the probability threshold. Based on the ROC curves, the model was able to classify tumor and normal tissue with 77% sensitivity and 81% specificity (Youden’s index). For an unbiased measure of the model performance, it was applied to a separate validation dataset that resulted in 73% sensitivity and 80% specificity. When this approach was applied to representative whole margins, for a tumor probability threshold of 50%, only 1.2% of all regions from the negative margin exceeded this threshold, while over 14.8% of all regions from the positive margin exceeded this threshold.

Highlights

Cancer is a complex and devastating disease that is continually among the top causes of death worldwide
The results of this study demonstrate that structured illumination microscope (SIM), in conjunction with maximally stable extremal regions (MSER), effectively isolates nuclear features in heterogeneous thick tissues that are significantly more prevalent in cancer-positive compared to cancer-negative tumor margins
Visual inspection of SIM images acquired on acridine orange (AO)-stained tissue clearly revealed that prominent features appeared as small local intensity maxima

Summary

Introduction

Cancer is a complex and devastating disease that is continually among the top causes of death worldwide. One example is the resection of extremity soft tissue sarcomas where surgeons seek to remove the entire tumor while preserving limb function. Microscopic disease left at the surgical site causes local recurrence in up to 31% of sarcoma patients [2, 3]. Another example is breast cancer, the most commonly occurring cancer type in women [4]. Breast conserving surgery (BCS) is a surgical procedure where the surgeon attempts to remove only cancerous tissues as opposed to the more radical mastectomy operation, where the entire breast is removed [5]. Surgeons typically have limited feedback on whether disease has been completely removed at the time of surgery

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