Evidence map›Paper›PMID 38549835›Full record

ArticleJournal of medical imaging (Bellingham, Wash.)2024

Prognostic value of different discretization parameters in

Breylon A Riley, Jack B Stevens, Xiang Li, Zhenyu Yang, Chunhao Wang, Yvonne M Mowery, David M Brizel, Fang-Fang Yin, Kyle J Lafata

Registry-linked trialOpen access · greenAbstract read
In one paragraph

Article in Journal of medical imaging (Bellingham, Wash.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01908504 (F Fluorodeoxyglucose Positron Emission Tomography), which is not on this map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.8field-weighted citation impact, top 29% of its field
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.

NCT01908504 nacompletednot on this map

F Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) for the Delivery of Adaptive Radiation Therapy

TypeinterventionalSponsorDuke UniversityRan2012 to 2016Enrolled271ConditionsHead and Neck Cancers, Lung and Esophagus Cancers, Anal, Cervix, Vulvar, Vaginal, and Endometrium CancersArmsPET-CT
3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

9 authors at 1 institution in 1 country.

Breylon A RileyDuke University, Medical Physics Graduate Program, Durham, North Carolina, United States.
Jack B StevensDuke University, Medical Physics Graduate Program, Durham, North Carolina, United States.
Xiang LiDuke University Pratt School of Engineering, Department of Electrical and Computer Engineering, Durham, North Carolina, United States.
Zhenyu YangDuke University, Medical Physics Graduate Program, Durham, North Carolina, United States.
Chunhao WangDuke University, Medical Physics Graduate Program, Durham, North Carolina, United States.
Yvonne M MoweryDuke University, Department of Radiation Oncology, Durham, North Carolina, United States.
David M BrizelDuke University, Department of Radiation Oncology, Durham, North Carolina, United States.
Fang-Fang YinDuke University, Medical Physics Graduate Program, Durham, North Carolina, United States.
Kyle J LafataDuke University, Medical Physics Graduate Program, Durham, North Carolina, United States.
Duke University · US

Funding

Employing Novel Primary Mouse Models of Head and Neck Cancer to Overcome Chemoradiation ResistanceK08DE029887 · NIDCR · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI MOWERY, YVONNE MARIE · 2020 to 2024
$804k
NIDCR NIH HHS K08 DE029887
6 · The paper itself

Abstract

Purpose: We aim to interrogate the role of positron emission tomography (PET) image discretization parameters on the prognostic value of radiomic features in patients with oropharyngeal cancer. Approach: A prospective clinical trial (NCT01908504) enrolled patients with oropharyngeal squamous cell carcinoma ( Results: FBN outperformed FBS in predicting residual and/or recurrent disease. The four FBN models achieved AUC values of 0.63, 0.61, 0.65, and 0.62 for 32, 64, 128, and 256 gray levels, respectively. By contrast, the average AUC of the four FBS models was 0.53. The parameter-optimized model, comprising features joint entropy (FBN = 64) and information measure correlation 1 (FBN = 128), achieved an AUC of 0.70. Kaplan-Meier analyses identified these features to be associated with disease-free survival ( Conclusions: Our findings suggest that the prognostic value of individual radiomic features may depend on feature-specific discretization parameter settings.

Indexed as

discretizationhead and neck squamous cell carcinomaradiation therapyradiomics

Identifiers

PMID38549835
PMCPMC10966359
OpenAlexW4393220041

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.