Multiparametric radiomics for predicting the aggressiveness of papillary thyroid carcinoma using hyperspectral images

Edwards, Ka'toria; Halicek, Martin; Little, James V.; Chen, Amy Y.; Fei, Baowei

doi:10.1117/12.2582147

Cited by 3 publications

(1 citation statement)

References 19 publications

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“…They reached a sensitivity and specificity of 83% and 76%, respectively, to distinguish tumor from normal tongue musculature. Edwards et al [23] used HSI to analyze specimens of papillary thyroid carcinoma, i.e. a head and neck cancer type outside the focus of the article.…”

Section: Hyperspectral Imaging In Head and Neck Cancer Pathologymentioning

confidence: 99%

Hyperspectral imaging and evaluation of surgical margins: where do we stand?

Pertzborn,

Bali,

Mühlig

et al. 2024

Current Opinion in Otolaryngology &Amp; Head &Amp; Neck Surgery

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Purpose of review To highlight the recent literature on the use of hyperspectral imaging (HSI) for cancer margin evaluation ex vivo, for head and neck cancer pathology and in vivo during head and neck cancer surgery. Recent findings HSI can be used ex vivo on unstained and stained tissue sections to analyze head and neck tissue and tumor cells in combination with machine learning approaches to analyze head and neck cancer cell characteristics and to discriminate the tumor border from normal tissue. Data on in vivo applications during head and neck cancer surgery are preliminary and limited. Even now an accuracy of 80% for tumor versus nonneoplastic tissue classification can be achieved for certain tasks, within the current in vivo settings. Summary Significant progress has been made to introduce HSI for ex vivo head and neck cancer pathology evaluation and for an intraoperative use to define the tumor margins. To optimize the accuracy for in vivo use, larger HSI databases with annotations for head and neck cancer are needed.

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Section: Hyperspectral Imaging In Head and Neck Cancer Pathologymentioning

confidence: 99%