Evidence map›Paper›PMID 38732355›Full record

ArticleDiagnostics (Basel, Switzerland)2024

Utility of CT Radiomics and Delta Radiomics for Survival Evaluation in Locally Advanced Nasopharyngeal Carcinoma with Concurrent Chemoradiotherapy.

Yen-Cho Huang, Shih-Ming Huang, Jih-Hsiang Yeh, Tung-Chieh Chang, Din-Li Tsan, Chien-Yu Lin, Shu-Ju Tu

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Application of delta radiomics based on cone-beam computed tomography in predicting radiotherapy efficacy for nasopharyngeal carcinoma.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026
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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

7 authors.

Yen-Cho HuangDepartment of Radiation Oncology, Keelung Chang Gung Memorial Hospital, Keelung 20445, Taiwan.ORCID 0009-0007-7905-4958
Shih-Ming HuangDepartment of Radiation Oncology, Keelung Chang Gung Memorial Hospital, Keelung 20445, Taiwan.
Jih-Hsiang YehDepartment of Radiation Oncology, Keelung Chang Gung Memorial Hospital, Keelung 20445, Taiwan.
Tung-Chieh ChangDepartment of Radiation Oncology, Linkuo Chang Gung Memorial Hospital, Tao-Yuan 33305, Taiwan.
Din-Li TsanDepartment of Radiation Oncology, Linkuo Chang Gung Memorial Hospital, Tao-Yuan 33305, Taiwan.
Chien-Yu LinDepartment of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Tao-Yuan 33302, Taiwan.
Shu-Ju TuDepartment of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Tao-Yuan 33302, Taiwan.ORCID 0000-0003-2545-1062

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA high incidence rate of nasopharyngeal carcinoma (NPC) has been observed in Southeast Asia compared to other parts of the world. Radiomics is a computational tool to predict outcomes and may be used as a prognostic biomarker for advanced NPC treated with concurrent chemoradiotherapy. Recently, radiomic analysis of the peripheral tumor microenvironment (TME), which is the region surrounding the gross tumor volume (GTV), has shown prognostic usefulness. In this study, not only was gross tumor volume (GTVt) analyzed but also tumor peripheral regions (GTVp) were explored in terms of the TME concept. Both radiomic features and delta radiomic features were analyzed using CT images acquired in a routine radiotherapy process.

methodsA total of 50 patients with NPC stages III, IVA, and IVB were enrolled between September 2004 and February 2014. Survival models were built using Cox regression with clinical factors (i.e., gender, age, overall stage, T stage, N stage, and treatment dose) and radiomic features. Radiomic features were extracted from GTVt and GTVp. GTVp was created surrounding GTVt for TME consideration. Furthermore, delta radiomics, which is the longitudinal change in quantitative radiomic features, was utilized for analysis. Finally, C-index values were computed using leave-one-out cross-validation (LOOCV) to evaluate the performances of all prognosis models.

resultsModels were built for three different clinical outcomes, including overall survival (OS), local recurrence-free survival (LRFS), and progression-free survival (PFS). The range of the C-index in clinical factor models was (0.622, 0.729). All radiomics models, including delta radiomics models, were in the range of (0.718, 0.872). Among delta radiomics models, GTVt and GTVp were in the range of (0.833, 0.872) and (0.799, 0.834), respectively.

conclusionsRadiomic analysis on the proximal region surrounding the gross tumor volume of advanced NPC patients for survival outcome evaluation was investigated, and preliminary positive results were obtained. Radiomic models and delta radiomic models demonstrated performance that was either superior to or comparable with that of conventional clinical models.

Indexed as

clinical outcomeCox regressiondelta radiomicsnasopharyngeal carcinomaradiomics

Identifiers

PMID38732355
PMCPMC11083477

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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.