Real-Time Intraoperative Detection of Margins for Oral Cavity Squamous Cell Carcinoma.

Obtaining negative surgical cancer margins is the strongest predictor for the long-term survival of oral cavity squamous cell carcinoma patients. To verify that the tumor has been completely removed, surgeons rely on pathologic evaluation of frozen sections to determine surgical margins, which can be time-consuming and subjective. Herein, we detail the real-time intraoperative use of dynamic optical contrast imaging (DOCI), a novel imaging modality that rapidly distinguishes head and neck cancer from healthy adjacent tissues based on fluorescence decay information from spectral bands in the UV-VIS range. Analysis of DOCI revealed microscopic characterization sufficient for tissue type identification consistent with histology (p < .05). DOCI delivers a clinically relevant tool that may better inform and drive precision surgery, directly impacting surgical outcomes and improving overall survival for our patients.

Label-free, real-time detection of perineural invasion and cancer margins in a murine model of head and neck cancer surgery.

Surgical management of head and neck cancer requires a careful balance between complete resection of malignancy and preservation of function. Surgeons must also determine whether to resect important cranial nerves that harbor perineural invasion (PNI), as sacrificing nerves can result in significant morbidity including facial paralysis. Our group has previously reported that Dynamic Optical Contrast Imaging (DOCI), a novel non-invasive imaging system, can determine margins between malignant and healthy tissues. Herein, we use an in vivo murine model to demonstrate that DOCI can accurately identify cancer margins and perineural invasion, concordant with companion histology. Eight C3H/HeJ male mice were injected subcutaneously into the bilateral flanks with SCCVIISF, a murine head and neck cancer cell line. DOCI imaging was performed prior to resection to determine margins. Both tumor and margins were sent for histologic sectioning. After validating that DOCI can delineate HNSCC margins, we investigated whether DOCI can identify PNI. In six C3H/HeJ male mice, the left sciatic nerve was injected with PBS and the right with SCCVIISF. After DOCI imaging, the sciatic nerves were harvested for histologic analysis. All DOCI images were acquired intraoperatively and in real-time (10 s per channel), with an operatively relevant wide field of view. DOCI values distinguishing cancer from adjacent healthy tissue types were statistically significant (P < 0.05). DOCI imaging was also able to detect perineural invasion with 100% accuracy compared to control (P < 0.05). DOCI allows for intraoperative, real-time visualization of malignant and healthy tissue margins and perineural invasion to help guide tumor resection.

Ex vivo hypercellular parathyroid gland differentiation using dynamic optical contrast imaging (DOCI).

Primary hyperparathyroidism, often caused by a single adenoma (80-85%) or four-gland hyperplasia (10-15%), can lead to elevated parathyroid hormone (PTH) levels and resultant hypercalcemia. Surgical excision of offending lesions is the standard of care, as the removal of pathologic adenomas reduces PTH and calcium values to baseline. The small size, variable location, and indistinct external features of parathyroid glands can make their identification quite challenging intraoperatively. Our group has developed the dynamic optical contrast imaging (DOCI) technique, a novel realization of dynamic temporally dependent measurements of tissue autofluorescence. In this study, we evaluated the efficacy of using the DOCI technique and normalized steady-state fluorescence intensity data for differentiating types of human parathyroid and thyroid tissues. We demonstrate that the DOCI technique has the capability to distinguish normal parathyroid tissue from diseased parathyroid glands as well as from adjacent healthy thyroid and adipose tissue across 8 different spectral channels between 405nm-600nm (p<0.05). Patient tissue DOCI data was further analyzed with a logistic regression classifier trained across the 8 spectral channels. After computer training, the computer-aided identification was able to accurately locate hypercellular parathyroid tissue with 100% sensitivity and 98.8% specificity within the captured DOCI image.

A Tool to Locate Parathyroid Glands Using Dynamic Optical Contrast Imaging.

OBJECTIVES/HYPOTHESIS: Identification of parathyroid glands and adjacent tissues intraoperatively can be quite challenging because of their small size, variable locations, and indistinct external features. The objective of this study is to test the efficacy of the dynamic optical contrast imaging (DOCI) technique as a tool in specifically differentiating parathyroid tissue and adjacent structures, facilitating efficient and reliable tissue differentiation. STUDY DESIGN: Prospective study. METHODS: Both animal and human tissues were included in this study. Fresh specimens were imaged with DOCI and subsequently processed for hematoxylin and eosin (H&E) stain. The DOCI images were analyzed and compared to the H&E results as ground truth. RESULTS: In both animal and human experiments, significant DOCI contrast was observed between parathyroid glands and adjacent tissue of all types. Region of interest analysis revealed most distinct DOCI values for each tissue when using 494 and 572 nm-specific band pass filter for signal detection (P < .005 for porcine tissues, and P = .02 for human specimens). Linear discriminant classifier for tissue type prediction based on DOCI also matched the underlying histology. CONCLUSIONS: We demonstrate that the DOCI technique reliably facilitates specific parathyroid gland localization. The DOCI technique constitutes important groundwork for in vivo precision endocrine surgery. LEVEL OF EVIDENCE: 4 Laryngoscope, 131:2391-2397, 2021.

Dynamic Optical Contrast Imaging.

The variable location and indistinct features of parathyroid glands can make their intraoperative identification challenging. Currently, there exists no routine use of localization methods during surgery. Dynamic optical contrast imaging (DOCI) leverages a novel realization of temporally dependent measurements of tissue autofluorescence that allows the acquisition of specific tissue properties. A prospective series of patients with primary hyperparathyroidism was examined. Parathyroid lesions and surrounding tissues were collected; fluorescence decay images were acquired via DOCI. Ex vivo samples (81 patients) were processed for histologic assessment. DOCI extracts relative fluorescence decay information in a surgically relevant field of view with a clinically accessible acquisition time <2 minutes. Analysis of DOCI revealed microscopic characterization sufficient for tissue type identification consistent with histology ( P < .05). DOCI is capable of efficiently distinguishing parathyroid tissue from adjacent tissues. Such an intraoperative tool would be transformative, helping surgeons to identify lesions, preserve healthy tissue, and improve patient outcomes.

Dynamic optical contrast imaging as a novel modality for rapidly distinguishing head and neck squamous cell carcinoma from surrounding normal tissue.

BACKGROUND: Head and neck squamous cell carcinomas (HNSCCs) are debilitating diseases for which a patient's prognosis depends heavily on complete tumor resection. Currently, the surgeon's fingers determine the location of tissue margins. This study evaluated the diagnostic utility of a novel imaging modality, dynamic optical contrast imaging (DOCI), in the detection of HNSCC. This system generates contrast by illuminating the tissue with pulsed light and detecting variations in endogenous fluorophore lifetimes. METHODS: A total of 47 fresh ex vivo samples from 15 patients were imaged with the DOCI system immediately after surgical resection. DOCI maps were analyzed to determine the statistical significance of contrast between tumors and adjacent nonmalignant tissue. Pilot intraoperative clinical data were also acquired. RESULTS: Statistical significance (P < .05) between muscle and tumor was established for 10 of 10 emission wavelengths, between collagen and tumor for 8 of 10 emission wavelengths, and between fat and tumor for 2 of 10 wavelengths. The system extracted relative fluorescence decay information in a surgically relevant field of view in <2 minutes. CONCLUSIONS: This study demonstrates the feasibility of using DOCI to rapidly and accurately distinguish HNSCC from surrounding normal tissue. An analysis of DOCI images revealed microscopic characterization sufficient for tissue-type identification consistent with histology. Such an intraoperative tool would be transformative by allowing the rapid delineation of tumor tissue from nontumor tissue and thus maximizing the efficacy of resection and improving patient outcomes. Cancer 2017;123:879-86. © 2016 American Cancer Society.

Optical imaging for brain tissue characterization using relative fluorescence lifetime imaging.

An autofluorescence lifetime wide-field imaging system that can generate contrast in underlying tissue structures of normal and malignant brain tissue samples with video rate acquisition and processing time is presented. Images of the investigated tissues were acquired with high resolution (∼35 µm) using an algorithm to produce contrast based on differences in relative lifetimes. Sufficient contrast for delineation was produced without the computation of fluorescence decay times or Laguerre coefficients. The imaged tissues were sent for histological analysis that confirmed the detected imaged tissues morphological findings and correlations between relative lifetime maps and histology identified.