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Hyperspectral Imaging of Head and Neck Squamous Cell Carcinoma for Cancer Margin Detection in Surgical Specimens from 102 Patients Using Deep Learning. | LitMetric

AI Article Synopsis

  • Surgical resection of head and neck squamous cell carcinoma (SCC) often results in inadequate cancer margins in 10-20% of cases, prompting this study to explore advanced imaging techniques for better detection.
  • The study utilized label-free hyperspectral imaging (HSI) and autofluorescence imaging on 293 tissue specimens from 102 patients, comparing their performance against fluorescent dyes and analyzing results using deep learning tools.
  • Findings showed HSI and autofluorescence provided high accuracy in detecting SCC margins, with AUC scores ranging from 0.82 to 0.99, indicating their potential as effective tools for rapid cancer margin assessment during surgeries.

Article Abstract

Surgical resection of head and neck (H and N) squamous cell carcinoma (SCC) may yield inadequate surgical cancer margins in 10 to 20% of cases. This study investigates the performance of label-free, reflectance-based hyperspectral imaging (HSI) and autofluorescence imaging for SCC detection at the cancer margin in excised tissue specimens from 102 patients and uses fluorescent dyes for comparison. Fresh surgical specimens ( = 293) were collected during H and N SCC resections ( = 102). The tissue specimens were imaged with reflectance-based HSI and autofluorescence imaging and afterwards with two fluorescent dyes for comparison. A histopathological ground truth was made. Deep learning tools were developed to detect SCC with new patient samples (inter-patient) and machine learning for intra-patient tissue samples. Area under the curve (AUC) of the receiver-operator characteristic was used as the main evaluation metric. Additionally, the performance was estimated in mm increments circumferentially from the tumor-normal margin. In intra-patient experiments, HSI classified conventional SCC with an AUC of 0.82 up to 3 mm from the cancer margin, which was more accurate than proflavin dye and autofluorescence (both < 0.05). Intra-patient autofluorescence imaging detected human papilloma virus positive (HPV+) SCC with an AUC of 0.99 at 3 mm and greater accuracy than proflavin dye ( < 0.05). The inter-patient results showed that reflectance-based HSI and autofluorescence imaging outperformed proflavin dye and standard red, green, and blue (RGB) images ( < 0.05). In new patients, HSI detected conventional SCC in the larynx, oropharynx, and nasal cavity with 0.85-0.95 AUC score, and autofluorescence imaging detected HPV+ SCC in tonsillar tissue with 0.91 AUC score. This study demonstrates that label-free, reflectance-based HSI and autofluorescence imaging methods can accurately detect the cancer margin in ex-vivo specimens within minutes. This non-ionizing optical imaging modality could aid surgeons and reduce inadequate surgical margins during SCC resections.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6769839PMC
http://dx.doi.org/10.3390/cancers11091367DOI Listing

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