Deep Learning Pipeline for Automated Assessment of Distances Between Tonsillar Tumors and the Internal Carotid Artery

Aseem Jain; Ameen Amanian; Nimesh Nagururu; Francis X. Creighton; Eitan Prisman

doi:10.1002/hed.28200

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Deep Learning Pipeline for Automated Assessment of Distances Between Tonsillar Tumors and the Internal Carotid Artery

Journal article

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Peer reviewed

Deep Learning Pipeline for Automated Assessment of Distances Between Tonsillar Tumors and the Internal Carotid Artery

Aseem Jain, Ameen Amanian, Nimesh Nagururu, Francis X. Creighton and Eitan Prisman

Head & neck, Vol.47(10), pp.2835-2844

10/2025

DOI: 10.1002/hed.28200

PMCID: PMC12434563

PMID: 40458868

Appears in UI Libraries Support Open Access

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Abstract

Background: Evaluating the minimum distance (dTICA) between the internal carotid artery (ICA) and tonsillar tumors (TT) on imaging is essential for preoperative planning; we propose a tool to automatically extract dTICA. Methods: CT scans of 96 patients with TT were selected from the cancer imaging archive. nnU-Net, a deep learning framework, was implemented to automatically segment both the TT and ICA from these scans. Dice similarity coefficient (DSC) and average hausdorff distance (AHD) were used to evaluate the performance of the nnU-Net. Thereafter, an automated tool was built to calculate the magnitude of dTICA from these segmentations. Results: The average DSC and AHD were 0.67, 2.44 mm, and 0.83, 0.49 mm for the TT and ICA, respectively. The mean dTICA was 6.66 mm and statistically varied by tumor T stage (p = 0.00456). Conclusion: The proposed pipeline can accurately and automatically capture dTICA, potentially assisting clinicians in preoperative evaluation.

Medical Imaging

deep learning

internal carotid artery

tonsillar carcinoma

transoral robotic surgery

UIOWA OA Agreement

Details

Title: Subtitle: Deep Learning Pipeline for Automated Assessment of Distances Between Tonsillar Tumors and the Internal Carotid Artery
Creators: Aseem Jain - University of Iowa
Ameen Amanian - University of British Columbia
Nimesh Nagururu - Johns Hopkins Medicine
Francis X. Creighton - Johns Hopkins Medicine
Eitan Prisman - University of British Columbia
Resource Type: Journal article
Publication Details: Head & neck, Vol.47(10), pp.2835-2844
DOI: 10.1002/hed.28200
PMID: 40458868
PMCID: PMC12434563
NLM abbreviation: Head Neck
ISSN: 1043-3074
eISSN: 1097-0347
Publisher: Wiley
Number of pages: 10
Language: English
Electronic publication date: 06/03/2025
Date published: 10/2025
Academic Unit: Otolaryngology
Record Identifier: 9984948245302771

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