Evidence map›Paper›PMID 40201771›Full record

ArticleHead and Neck Tumor Segmentation for MR-Guided Applications : First MICCAI Challenge, HNTS-MRG 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 17, 2024, proceedings2025

Gradient Map-Assisted Head and Neck Tumor Segmentation: A Pre-RT to Mid-RT Approach in MRI-Guided Radiotherapy.

Jintao Ren, Kim Hochreuter, Mathis Ersted Rasmussen, Jesper Folsted Kallehauge, Stine Sofia Korreman

Abstract read
In one paragraph

Article in Head and Neck Tumor Segmentation for MR-Guided Applications : First MICCAI Challenge, HNTS-MRG 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 17, 2024, proceedings, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Overview of the Head and Neck Tumor Segmentation for Magnetic Resonance Guided Applications (HNTS-MRG) 2024 Challenge.Head and Neck Tumor Segmentation for MR-Guided Applications : First MICCAI Challenge, HNTS-MRG 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 17, 2024, proceedings · 2025
    Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jintao RenDepartment of Clinical Medicine, Aarhus University, Nordre Palle Juul-Jensens, Blvd. 11, 8200 Aarhus, Denmark.ORCID 0000-0002-1558-7196
Kim HochreuterDepartment of Clinical Medicine, Aarhus University, Nordre Palle Juul-Jensens, Blvd. 11, 8200 Aarhus, Denmark.ORCID 0009-0000-7347-1688
Mathis Ersted RasmussenDepartment of Clinical Medicine, Aarhus University, Nordre Palle Juul-Jensens, Blvd. 11, 8200 Aarhus, Denmark.ORCID 0000-0002-7853-3531
Jesper Folsted KallehaugeDepartment of Clinical Medicine, Aarhus University, Nordre Palle Juul-Jensens, Blvd. 11, 8200 Aarhus, Denmark.ORCID 0000-0003-3705-5390
Stine Sofia KorremanDepartment of Clinical Medicine, Aarhus University, Nordre Palle Juul-Jensens, Blvd. 11, 8200 Aarhus, Denmark.ORCID 0000-0002-3523-382X

Funding

Development of functional magnetic resonance imaging-guided adaptive radiotherapy for head and neck cancer patients using novel MR-Linac deviceR01DE028290 · NIDCR · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI CHRISTODOULEAS, JOHN PAUL, FULLER, CLIFTON DAVID · 2019 to 2023
$4.3M
SCH: Personalized Rescheduling of Adaptive Radiation Therapy for Head & Neck CancerR01CA257814 · NCI · RICE UNIVERSITY · PI FULLER, CLIFTON DAVID, SCHAEFER, ANDREW J · 2021 to 2024
$1.8M
NCI NIH HHS R01 CA257814NIDCR NIH HHS R01 DE028290
6 · The paper itself

Abstract

Radiation therapy (RT) is a vital part of treatment for head and neck cancer, where accurate segmentation of gross tumor volume (GTV) is essential for effective treatment planning. This study investigates the use of pre-RT tumor regions and local gradient maps to enhance mid-RT tumor segmentation for head and neck cancer in MRI-guided adaptive radiotherapy. By leveraging pre-RT images and their segmentations as prior knowledge, we address the challenge of tumor localization in mid-RT segmentation. A gradient map of the tumor region from the pre-RT image is computed and applied to mid-RT images to improve tumor boundary delineation. Our approach demonstrated improved segmentation accuracy for both primary GTV (GTVp) and nodal GTV (GTVn), though performance was limited by data constraints. The final DSC

Indexed as

Deep learningHead and Neck CancerMRIPrior knowledgeTumor Segmentation

Identifiers

PMID40201771
PMCPMC11977786

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.