Abstract
.For patients undergoing surgical cancer resection of squamous cell carcinoma (SCCa), cancer-free surgical margins are essential for good prognosis. We developed a method to use hyperspectral imaging (HSI), a noncontact optical imaging modality, and convolutional neural networks (CNNs) to perform an optical biopsy of ex-vivo, surgical gross-tissue specimens, collected from 21 patients undergoing surgical cancer resection. Using a cross-validation paradigm with data from different patients, the CNN can distinguish SCCa from normal aerodigestive tract tissues with an area under the receiver operator curve (AUC) of 0.82. Additionally, normal tissue from the upper aerodigestive tract can be subclassified into squamous epithelium, muscle, and gland with an average AUC of 0.94. After separately training on thyroid tissue, the CNN can differentiate between thyroid carcinoma and normal thyroid with an AUC of 0.95, 92% accuracy, 92% sensitivity, and 92% specificity. Moreover, the CNN can discriminate medullary thyroid carcinoma from benign multinodular goiter (MNG) with an AUC of 0.93. Classical-type papillary thyroid carcinoma is differentiated from MNG with an AUC of 0.91. Our preliminary results demonstrate that an HSI-based optical biopsy method using CNNs can provide multicategory diagnostic information for normal and cancerous head-and-neck tissue, and more patient data are needed to fully investigate the potential and reliability of the proposed technique.
Highlights
Cancers of the head and neck are the sixth most common cancer worldwide, including cancers that are predominantly of squamous cell origin, for instance the oral cavity, nasopharynx, pharynx, and larynx, and others such as carcinomas of the thyroid gland.[1]
This study aims to investigate the ability of hyperspectral imaging (HSI) to classify tissues from the thyroid and upper aerodigestive tract using convolutional neural networks (CNNs)
Using a leave-one-patient-out cross-validation paradigm with HSI obtained from different patients, the CNN can distinguish squamous cell carcinoma (SCCa) from normal oral tissues with an area under the receiver operator curve (AUC) of 0.82, 81% accuracy, 81% sensitivity, and 80% specificity
Summary
Cancers of the head and neck are the sixth most common cancer worldwide, including cancers that are predominantly of squamous cell origin, for instance the oral cavity, nasopharynx, pharynx, and larynx, and others such as carcinomas of the thyroid gland.[1] Major risk factors include consumption of tobacco and alcohol, exposure to radiation, and infection with human papilloma virus.[2,3] Approximately 90% of cancer at sites including the lips, gums, mouth, hard, and soft palate, and anterior two-thirds of the tongue are squamous cell carcinoma (SCCa).[4] The diagnostic procedure of SCCa typically involves physical examination and surgical evaluation by a physician, tissue biopsy, and diagnostic imaging, such as PET, MRI, or CT. Patients with SCCa tend to present with advanced disease, with about 66% presenting as stage III or IV disease, which requires more procedures for successful treatment of the patient.[5] The standard treatment for these cancers usually involves surgical cancer resection with potential adjuvant therapy, such as chemotherapy or radiation, depending on the extent, stage, and location of the lesion.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
