The Sentinel Margin: Intraoperative ex-vivo Specimen Mapping Using Relative Fluorescence Intensity

Abstract

Purpose

Despite major advancements in surgical oncology, the positive margin rate for primary head and neck cancer resection remains around 15–30%. In particular, the deep surface margin is the most challenging to adequately assess. Inadequate margins are directly correlated to poor survival, and as such, mitigation of these rates is critical to improve patient outcomes. We have developed an ex vivo imaging strategy that utilizes fluorescence intensity-peaks (relative to background signal) of an injected anti-epidermal growth factor receptor antibody conjugated to a fluorescent probe to locate potential close or positive margins on the deep surface of the resected tumor specimen.

Experimental Design

Twelve patients with head and neck cancer scheduled for surgery received systemic administration of a tumor-specific contrast-agent (panitumumab-IRDye800). After surgical resection, the tumor specimen was imaged using a fluorescence imager. The three highest fluorescence intensity-peaks on the deep surface of the specimen were isolated and correlated to histology to determine the margin distance at these regions.

Results

Relative fluorescence peak-intensities identified the closest margin on the deep surface of the specimen within 2.5 minutes. The highest intensity-peak consistently (100%) detected the closest margin to the tumor. The difference in tumor margin distance between the first and second highest fluorescence intensity-peak averaged 2.1±1.4mm. The tumor-margin difference between the second and third highest peak averaged 1.6±0.6mm.

Conclusion

Fluorescence intensity-peaks can identify the region on the specimen where tumor is closest to specimen’s edge on the deep surface. This technique could have broad applications in obtaining adequate margins in oncological surgery.

Introduction

Surgical resection is the primary curative treatment for the majority of solid tumors. In the management of head and neck squamous cell carcinoma, resection of the primary tumor is considered adequate or clear when the surgical margins are >5mm and inadequate if <5mm, on final histology (1–3). Failure to obtain clear surgical margins is associated with locoregional recurrence and poor overall survival rates (4) and may necessitate additional therapy such as chemotherapy, radiotherapy, and/or revision surgeries (5). Unfortunately, the highest overall inadequate margins rates (15–30%) in all of surgical oncology are found in head and neck cancer (6). Despite the introduction of many novel technologies, inadequate margin rates have not changed over the past 30 years as surgeons cannot successfully differentiate healthy from diseased tissue (6,7). The most commonly used method for intraoperative margin control is frozen section analysis (FSA); however, this technique suffers from sampling errors as surgeons often struggle to identify which suspicious regions should be sent for histopathological assessment (8). This makes FSA not only a time-intensive technique (15–20 min per section), but also a subjective evaluation method (9).

After resection, the tumor specimen is anatomically divided into the peripheral surface (i.e. epithelial or mucosal surface) and the deep surface. The term deep surface describes the non-epithelial margin of the tumor specimen which is exposed after surgical resection. In general, intraoperative margin assessment of the deep surface is more challenging compared to the visible and palpable peripheral margins (10). The lack of visual feedback makes the deep surface more at risk for having inadequate margins (11). This is illustrated by Woolgar et al. who evaluated 301 oral cancer patients and showed that 87% of inadequate margins were located on the deep surface compared to 16% on the peripheral surface (1).

To address the challenges hindering effective intraoperative margin assessment (and in particular the deep margin), we propose a novel methodology for rapid and accurate identification of the closest surgical margin on the specimen. We investigated real-time margin detection assessment using relative fluorescence intensity-peaks after injection of a targeted fluorescent agent to identify positive and close margins (tumor < 5 mm). This methodology can assist the surgeon to take immediate corrective action during the procedure (12).

Materials and method

Study design

A Phase I study evaluating panitumumab-IRDye800CW was approved by the Stanford Institutional Review Board (IRB-35064; ) and the FDA (), written informed consent was obtained from all patients. The study was performed in accordance with the Declaration of Helsinki, FDA’s ICH-GCP guidelines, and United States Common Rule. More details on the safety and pharmacokinetics of the phase I study can be found in Gao et al. (13). Briefly, consenting patients (n=16) were infused 1–5 days prior to surgery with panitumumab-IRDye800CW (excitation/emission max: 774/789nm; dose: 25mg/50mg flat-dose; half-life: 24 hours (13)). The dosing was not weight-based: subjects received either a 25mg (n=5) or a 50mg (n=11) flat-dose of panitumumab-IRdye800. After resection, the deep surface of the tumor specimen was imaged using a closed-field fluorescence imaging device (PEARL, LI-COR biosciences) before being sent to pathology for standard-of-care histological assessment. A closed-field device is a small animal imaging platform that was repurposed for near-infrared fluorescence imaging on the back table in the operation room. This device is particularly valuable for ex vivo tissue specimen imaging as it has a wide dynamic range and is ‘closed’ which allows for controlled imaging environment, including elimination of ambient light (12,17). At pathology, the specimens were formalin-fixed and sectioned into 5mm tissue sections. Subsequently, the tissue sections were paraffin-embedded, and a representative 5μm section was cut for routine hematoxylin and eosin (H&E) staining and diagnosis. On the acquired histological H&E sections, areas with invasive or in situ squamous cell carcinoma were outlined by a board-certified pathologist. The slides were then digitized and analyzed for study purposes. In addition, epidermal growth factor receptor (EGFR) expression of all patients was assessed through immunohistochemistry (IHC) of two representative tissue sections and results were scored as previously described (17).

Fluorescence Intensity-peak Isolation and Background Reference

The fluorescence signal of the entire deep surface of the specimen was plotted using an interactive 3D signal-mapping plug-in (ImageJ plugin, interactive 3D surface plot, Berlin, Germany) for ImageJ (version 1.50i, National Institute of Health, Washington D.C., Maryland, USA). Utilizing this 3D signal-mapping tool, we were able to isolate high intensity regions, further described as intensity-peaks, from background signal (Figure 1). By scaling of the threshold of fluorescent signal a fluorescence signal surface map was generated from which multiple intensity-peaks could be isolated. The highest intensity-peaks (relative to background) were numbered, whereby the highest intensity peak (which appears first upon scaling) was assigned as the first peak, followed by the second and third peaks (Figure 1D–G). Further isolation than the third intensity-peak region was deemed unnecessary given the objective to find the closest tumor margin on the deep surface. Patients were used as their own internal control by assigning background regions located 10–15mm from each intensity-peak on the same specimen. For the statistical analysis of the fluorescence signal differences between intensity-peaks and background regions on the same specimen, we quantified the signal at these regions by drawing circular (5mm diameter) regions of interests (ROIs) to extract the mean fluorescence intensity (MFI) in arbitrary units (a.u.).

Figure 1.

Overview of workflow. (a + b) representative brightfield (a) and fluorescence image (b) of a specimen’s deep margin. Number 1–3 allocate the fluorescence peaks in order of first appearance throughout the whole figure. (c) Side view on the entire fluorescence surface map of deep margin (white arrow image b indicates angle). (d-f) Identification of highest fluorescence intensity-peaks on the deep surface (with color bar). The white dotted lines and asterisks (red/blue) indicate the orientation in which the hematoxylin & eosin (H&E) slides where cut. (g-i) H&E slides with delineated tumor (black line) on which the margin distance was measured (white box). T: tumor.

Correlation of Fluorescence Signal with Margin Distance

For each intensity-peak and background region we measured the margin distance, which is defined as the distance in millimeters between the tumor edge and the specimen edge on the histological sections. First, to validate our method, we evaluated if the margin distance at the intensity-peaks would be significantly less when compared to the margin distance at the background regions. Second, to evaluate whether the first intensity-peak would accurately predict the closest margin, we determined whether the margin distance at the first peak would be less when compared to the second peak, and whether the margin distance at the second peak was less than the margin distance at the third peak.

In order to correlate the histological sections to the appropriate intensity-peaks or background regions on the deep surface, the specimens were reconstructed from the 5mm tissue sections. This process, described by others (14), allowed us to register the margin distance measurements performed on histological sections, to the fluorescence intensity-peaks (and background regions) located on the deep surface of the specimen, within a 1–2mm margin of error. The margin distance was measured five times on each histological section and averaged, using ImageJ.

Statistical Analysis

Per specimen, mean fluorescence intensity [a.u.] and margin distance [mm] between the intensity-peaks and background regions were compared using the Wilcoxon Signed Rank Test. To compare MFI between the intensity-peaks and background regions, the median signal intensity of the first, second and third intensity-peaks was compared to the median signal of the corresponding background regions (i.e. one per intensity-peak) for each specimen. To compare margin distances for the first, second, and third intensity-peak, the Wilcoxon Signed Rank Test was used. P-values of 0.05 or less were considered statistically significant. GraphPad Software (Version 8.0c, La Jolla, California, USA) was used for statistical analysis. The median is used since it is a more robust summary measure to outliers compared to the mean.

Results

Patient Enrollment

A total of 16 patients underwent fluorescent evaluation of their primary specimen after systemic infusion of panitumumab-IRDye800. Primary tumor specimens were imaged with a closed-field back table device to assess the fluorescence intensity-peaks of the deep surface. The process of imaging acquisition (30s per image) and peak-intensity isolation (120s) of a single specimen took approximately 2.5 minutes on average. Patient characteristics are summarized in Supplemental Table 1. Four patients with specimen involving bone were excluded from analysis because histological reconstruction of the specimen could not be performed after the decalcification process. In one excluded case, shown in Supplemental Figure 1, the intensity-peak region could successfully be correlated to the corresponding H&E slide due to demarcation using a suture. For the remaining 12 patients, a total of 36 intensity-peaks and 36 background regions were analyzed. Furthermore, using IHC we have identified high levels of EGFR expression in all resected tumors, as previously reported in this population (17).

Intensity-peaks: higher signal, closer margin distance

First, the method was validated to determine if intensity-peaks would indeed have higher fluorescence signal and lower margin distance when compared to background regions of the same specimen. Using all specimens, the median signal for the intensity-peak regions had a significantly higher MFI compared to the median signal for the background regions (p<0.05, n=24; Figure 2a). Figure 2b shows the difference in margin distance of the intensity-peaks compared to background regions for each patient. The overall margin distance at the intensity-peaks was significantly less than the background regions in all cases (p<0.05, n=24).

Figure 2.

Comparison of intensity peaks versus background. First graph indicates the relative increase in MFI of all background regions to intensity-peak regions per patient. The second graph illustrates the difference in margin distance for background and intensity-peak regions per patient. MFI: mean fluorescence Intensity; a.u.: arbitrary units

In all specimens, the distance from margin to tumor (i.e. margin distance) was lower at the location of the first fluorescence intensity-peak when compared to the second highest peak (Figure 3). Similarly, the second highest peak intensity had a closer margin distance in 83% of samples when compared to the third highest fluorescence peak. The first fluorescence intensity peak had a significantly closer margin distance (by 2.1mm, p<0.05, n=24) than the second intensity peak. In all 12 cases evaluated, the first intensity-peak identified the area that harbored tumor closest to the deep surface when compared to all subsequent intensity-peaks (p<0.05, n=36). The average increase in distance between the tumor and the specimen surface was 1.6mm when comparing the second and third intensity-peaks. It is worth noting that there were two instances where the distance from the tumor to the specimen surface did not increase between the second and third intensity-peak. However, in both of these cases, the difference between the second and third intensity-peak was not substantially different: the peaks were found to correlate with a margin distance that was within the margin of error (5.8±0.1mm versus 5.6±0.4mm; and 11.4±0.6mm versus 10.2±0.6mm).

Figure 3.

Intensity-peak versus margin distance (a + b) Representative brightfield (a) and fluorescence image (b) of the deep margin (with color bar). (c) Identification of highest fluorescence intensity-peaks on the deep surface. Number 1–3 allocate the fluorescence peaks in order of first appearance. (d) Graph showing the margin distance at the 1^st, 2^nd and 3^th intensity-peak region per patient.

Discussion

In this study we showed that after systemic administration of a targeted fluorescent agent, surgical specimens can be non-invasively imaged to objectively determine where tumor is located closest to the deep surface of the specimen. Since this process can be performed intraoperatively, the surgeon could use this information to immediately resect additional tissue or send a tissue sample of a suspicious region for further assessment with FSA.

Despite many advances in the field of surgical oncology, exact and reliable prediction of positive of close tumor margins remains a significant challenge, with subjective and often inaccurate use of FSA as standard of care. Thus, there is an important need to develop new technologies to facilitate improved intraoperative margin assessment. Here, we describe utilizing detection of a conjugated fluorescent antibody to rapidly and accurately assess intraoperative tumor margins. We have termed the margin segment with the highest fluorescence intensity as the sentinel margin - the location where the closest margin is mostly likely to be located. Analogous to sentinel lymph node assessment (where intraoperative mapping with an injected agent allows for identification of the lymph node at highest risk for metastasis), the sentinel margin may be analyzed using our described technique to identify the margin most at risk to be close or positive in a tumor specimen. This approach has significant implications in accurately and efficiently determining margin status intraoperatively.

Currently, multiple samples, sometimes upwards of 15, are subjectively obtained and sent for FSA, averaging 30 minutes per sample for analysis (9,15). The process of sentinel margin analysis takes approximately 2.5 minutes and provides an objective sampling strategy that could save a great amount of time by reducing the number of samples sent for FSA, while improving accuracy. In addition, as the process of imaging acquisition and sentinel margin analysis takes place on the back-table in parallel with the operation, it does not delay or add time to the surgery

The success of this ex vivo specimen mapping method relies on several key optical principles. First, as a direct result of light absorption and scattering, the NIR signal is not detectable when it is obscured by 6mm of tissue or more. This results in a consistently low fluorescent signal after the margin distance exceeds 5mm, an important clinical distance in several cancer types (including head and neck cancer) as 5mm denotes a clear margin. Historically, it has not been common to have close margins (1–5mm) since it can be difficult to assess how much normal tissue exists between a cancer and the surgical margin. This issue can be successfully addressed utilizing this technology. Second, the optical signal intensifies as the tumor comes closer to the specimen surface. The region that has the strongest fluorescent signal (namely, the highest fluorescence intensity-peak), will be easily identified at any thresholding level since the specimen fluorescence is relative to adjacent tissue of the same specimen. Ultimately, the surgeon may be able to correlate this information with clinical judgement to facilitate frozen section assessment and/or re-resection (16). If infiltrative tumor tissue is found closer than 5mm to the deep surface using frozen section analysis, the surgeon has the opportunity to resect additional tissue from the wound cavity using the fluorescence intensity-peaks as guidance. A clear overview of the proposed intraoperative workflow is shown in Figure 4.

Figure 4.

Proposed workflow.

In previous studies, we have shown that fluorescence surface-mapping is highly sensitive for detection of cancer within 5mm of the surgical margin using an absolute intensity value (12,17). However, this approach is limited as the absolute fluorescence intensity will differ between patients as a result of variance in dose and infusion-to-surgery time (17). The current study, however, uses relative values; with intensity compared to background regions on the same specimen and each patient serving as his or her own internal control. Ultimately, we show that in each individual specimen we can identify the sentinel margin, and that this consistently identifies the location with the closest margin. Although we recognize that a ratio between normal and tumor tissue varies with dose, timing and EGFR expression (17), the proposed tumor-to-tumor ratio measures relative intensity of fluorescence between different regions of the same specimen, which we hypothesize varies with the amount of overlying soft tissue (i.e. the margin distance). The data presented here provides empirical evidence that this measurement identifies the smallest (sentinel) margin of the specimen.

We have previously demonstrated that expression of epidermal growth factor receptor (EGFR), which is overexpressed in more than 90% of HNSCC, positively correlates with fluorescence intensity (17,18). Besides the fact that fluorescence can be localized to tumor cells and varies with the level of EGFR expression, we also acknowledge that enhanced permeability and retention (EPR) effect may contribute to the accumulation of panitumumab-IRDye800 within the tumor.

Although squamous cell carcinoma is known to have a heterogeneous EGFR pattern (18,19), overall expression appears to be high enough for successful detection of the sentinel margin in the current study. It is possible however, that significant heterogeneity of EGFR expression within the tumor may influence the tumor-to-tumor ratio more than the overlying soft tissue margin. Despite this possibility, the findings in this study suggest that sentinel margin assessment should be compatible with any fluorescent probe as well as different imaging systems as long as the probe has a similar distribution pattern as panitumumab-IRDye800, and the device is capable of signal quantification and threshold scaling for isolation purposes.

Although the study included a range of tumor subsites in the head and neck region and used many data points for each specimen, the sample size limits the conclusions that can be drawn. An additional challenge is the decalcification process, although this methodology works excellent for the analysis of soft-tissue tumors, limitations presented with bone involvement will necessitate alternative research strategies.

The current standard of care for analysis of surgical margins remains controversial – should samples for frozen section analysis be obtained from the patient or from the specimen (20)? Our proposed strategy may help standardize specimen driven sampling and obtaining perpendicular margins to measure tumor distance (20).

Notably, our proposed sentinel margin analysis technique can be performed in all patients undergoing tumor resection with a fluorescent contrast agent and could therefore potentially improve poor margin control in other fields where wide local excision is required, such as melanoma, colon cancer and vulvar cancer.

Conclusion

Fluorescently labeled antibodies in combination with intraoperative fluorescence imaging can successfully identify the closest margin in head and neck cancer specimen. This technique could potentially assist intraoperative decision-making for oncologically sound resections.

Supplementary Material

1

Supplemental Figure 1 Annotation of suspicious area by suture. (a + b) Bright field (a) and corresponding fluorescence image (b) of the specimen’s deep margin after maxillectomy. White solid line indicates peak intensity area in a. and b. White dotted line delineates the infiltrated left concha inferior (nasal cavity). (d) Isolated fluorescence intensity-peak area where suture was placed (with color bar). (c) Hematoxylin & eosin slide of suture marked area. Black solid line delineates tumor from healthy tissue.

Statement of Translational Relevance.

Surgical excision is an integral part of treatment for most solid tumors. An inadequate surgical margin occurs when cancer cells are near or present at the edge of the resected specimen. Inadequate margins correlate with a significantly worse survival and often warrant additional treatments, which result in patient morbidity and increase in healthcare cost. Despite new and costly operating room technologies and advanced training in surgical oncology, the rate at which patients leave the operating room with inadequate margins has not improved in the last three decades. Here we present the results of a novel technique that enables surgeons to assess tumor at the deep surgical margin, which may be used to improve the rates of overall oncologically sound resections.