Optical coherence tomography in the assessment of oral squamous cell carcinoma resection margins

Hamdoon, Zaid; Jerjes, Waseem; McKenzie, Gordon; Jay, Amrita; Hopper, Colin

doi:10.1016/j.pdpdt.2015.07.170

Cited by 63 publications

(71 citation statements)

References 23 publications

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“…The diagnostic accuracy of OCT was 82.6% using histological analysis as the gold standard. Similarly, Hamdoon et al used a commercial OCT probe developed by Michelson Diagnostics to assess oral cancer resection margins [199]. The researchers imaged 112 specimens from 28 patients and determined that OCT could identify positive and negative margins with a diagnostic accuracy of 88%.…”

Section: Human Anterior Eye Surgerymentioning

confidence: 99%

Review of intraoperative optical coherence tomography: technology and applications [Invited]

Carrasco-Zevallos

Viehland

Keller

et al. 2017

Biomed. Opt. Express

135

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During microsurgery, en face imaging of the surgical field through the operating microscope limits the surgeon's depth perception and visualization of instruments and subsurface anatomy. Surgical procedures outside microsurgery, such as breast tumor resections, may also benefit from visualization of the sub-surface tissue structures. The widespread clinical adoption of optical coherence tomography (OCT) in ophthalmology and its growing prominence in other fields, such as cancer imaging, has motivated the development of intraoperative OCT for real-time tomographic visualization of surgical interventions. This article reviews key technological developments in intraoperative OCT and their applications in human surgery. We focus on handheld OCT probes, microscope-integrated OCT systems, and OCT-guided laser treatment platforms designed for intraoperative use. Moreover, we discuss intraoperative OCT adjuncts and processing techniques currently under development to optimize the surgical feedback derivable from OCT data. Lastly, we survey salient clinical studies of intraoperative OCT for human surgery.

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Section: Human Anterior Eye Surgerymentioning

confidence: 99%

Review of intraoperative optical coherence tomography: technology and applications [Invited]

Carrasco-Zevallos

Viehland

Keller

et al. 2017

Biomed. Opt. Express

135

View full text Add to dashboard Cite

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“…Whilst the positive predictive value was 61.5% and the negative predictive value was 95%. The authors reported that positive margins could be identified by architectural changes and an increase in epithelial layer thickness with OCT technology [19] . The use of OCT for intraoperative margin detection remains investigational and several advancements such as polarization-sensitive OCT, or contrast enhances OCT (gold nanoparticles) may offer superior imaging characteristics for this application in the future [20,55,57,58] .…”

Section: Optical Coherence Tomography (Oct)mentioning

confidence: 99%

How Close Are We to Real Time Optical Margin Control in Head and Neck Oncologic Surgery?

Miles

2016

Cancer Cell Microenviron

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The quest for negative margins during head and neck oncologic surgery continues to challenge surgeons worldwide. Current technological advances offer significant promise to advance the field and improve operative margin detection. This review focuses on current optical technology, which has been evaluated for intraoperative margin control in head and neck oncologic surgery. Many of the current systems have technical limitations and there is no current standard technology being applied in the field of head and neck oncology to enhance intraoperative margin control. Surgeons continue to rely on intraoperative frozen section analysis, however many optical systems have shown high rates of sensitivity and specificity when discriminating benign from malignant tissue. These technologies shows significant promise for intraoperative margin control and may be enhanced by targeted molecular imaging, or spectral analysis, in the future. Translational trials are rare and are the key to the path of independence from frozen section analysis.

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“…Thus, only a small sample of the true margin can be evaluated, leading to potential sampling error. Despite negative frozen sections, 27& to 40% of surgically treated HNSCC develop cancer recurrence . This could be partially accounted for by the limitations and sampling error in the frozen biopsy sections along with artifact that occurs during sample preparation particularly in specimens with complex topology such as at the base of tongue and larynx.…”

Section: Introductionmentioning

confidence: 99%

“…Noninvasive imaging modalities such as: optical coherence tomography (OCT), fluorescence and fluorescence lifetime imaging, high‐resolution microendoscopy, elastic scattering spectroscopy and Raman spectroscopy may aid in the noninvasive assessment of tumor margins. These technologies could potentially be used in situ, as well as in specimens that have been freshly resected . Of the aforementioned imaging modalities, OCT is unique in that it provides real‐time cross‐sectional images at near histopathological resolution.…”

Section: Introductionmentioning

confidence: 99%

The use of optical coherence tomography and convolutional neural networks to distinguish normal and abnormal oral mucosa

Heidari

Pham

Ifegwu

et al. 2020

Journal of Biophotonics

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Incomplete surgical resection of head and neck squamous cell carcinoma (HNSCC) is the most common cause of local HNSCC recurrence. Currently, surgeons rely on preoperative imaging, direct visualization, palpation and frozen section to determine the extent of tissue resection. It has been demonstrated that optical coherence tomography (OCT), a minimally invasive, nonionizing near infrared mesoscopic imaging modality can resolve subsurface differences between normal and abnormal head and neck mucosa. Previous work has utilized two‐dimensional OCT imaging which is limited to the evaluation of small regions of interest generated frame by frame. OCT technology is capable of performing rapid volumetric imaging, but the capacity and expertise to analyze this massive amount of image data is lacking. In this study, we evaluate the ability of a retrained convolutional neural network to classify three‐dimensional OCT images of head and neck mucosa to differentiate normal and abnormal tissues with sensitivity and specificity of 100% and 70%, respectively. This method has the potential to serve as a real‐time analytic tool in the assessment of surgical margins.

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Optical coherence tomography in the assessment of oral squamous cell carcinoma resection margins

Cited by 63 publications

References 23 publications

Review of intraoperative optical coherence tomography: technology and applications [Invited]

Review of intraoperative optical coherence tomography: technology and applications [Invited]

How Close Are We to Real Time Optical Margin Control in Head and Neck Oncologic Surgery?

The use of optical coherence tomography and convolutional neural networks to distinguish normal and abnormal oral mucosa

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