Evidence map›Paper›PMID 34865190›Full record

SynthesisLa Radiologia medica2021

Delta radiomics: a systematic review.

Valerio Nardone, Alfonso Reginelli, Roberta Grassi, Luca Boldrini, Giovanna Vacca, Emma D'Ippolito, Salvatore Annunziata, Alessandra Farchione, Maria Paola Belfiore, Isacco Desideri and 1 more

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in La Radiologia medica, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 138 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
138citing papers in PubMed, 6 pooled it
–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

138 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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  7. 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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78 more citing papers are in PubMed but not listed here.

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

11 authors.

Valerio NardoneDepartment of Precision Medicine, University of Campania "L. Vanvitelli", 80138, Naples, Italy.
Alfonso ReginelliDepartment of Precision Medicine, University of Campania "L. Vanvitelli", 80138, Naples, Italy. alfonsoreginelli@hotmail.com.ORCID http://orcid.org/0000-0003-4809-6235
Roberta GrassiDepartment of Precision Medicine, University of Campania "L. Vanvitelli", 80138, Naples, Italy.
Luca BoldriniDipartimento Di Diagnostica Per Immagini, Radioterapia Oncologica Ed Ematologia - Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy.
Giovanna VaccaDepartment of Precision Medicine, University of Campania "L. Vanvitelli", 80138, Naples, Italy.
Emma D'IppolitoDepartment of Precision Medicine, University of Campania "L. Vanvitelli", 80138, Naples, Italy.
Salvatore AnnunziataDipartimento Di Diagnostica Per Immagini, Radioterapia Oncologica Ed Ematologia - Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy.
Alessandra FarchioneDipartimento Di Diagnostica Per Immagini, Radioterapia Oncologica Ed Ematologia - Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy.
Maria Paola BelfioreDepartment of Precision Medicine, University of Campania "L. Vanvitelli", 80138, Naples, Italy.
Isacco DesideriDepartment of Biomedical, Experimental and Clinical Sciences "M. Serio", University of Florence, Florence, Italy.
Salvatore CappabiancaDepartment of Precision Medicine, University of Campania "L. Vanvitelli", 80138, Naples, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRadiomics can provide quantitative features from medical imaging that can be correlated with various biological features and clinical endpoints. Delta radiomics, on the other hand, consists in the analysis of feature variation at different acquisition time points, usually before and after therapy. The aim of this study was to provide a systematic review of the different delta radiomics approaches.

methodsEligible articles were searched in Embase, PubMed, and ScienceDirect using a search string that included free text and/or Medical Subject Headings (MeSH) with three key search terms: "radiomics", "texture", and "delta". Studies were analysed using QUADAS-2 and the RQS tool.

resultsForty-eight studies were finally included. The studies were divided into preclinical/methodological (five studies, 10.4%); rectal cancer (six studies, 12.5%); lung cancer (twelve studies, 25%); sarcoma (five studies, 10.4%); prostate cancer (three studies, 6.3%), head and neck cancer (six studies, 12.5%); gastrointestinal malignancies excluding rectum (seven studies, 14.6%), and other disease sites (four studies, 8.3%). The median RQS of all studies was 25% (mean 21% ± 12%), with 13 studies (30.2%) achieving a quality score < 10% and 22 studies (51.2%) < 25%.

conclusionsDelta radiomics shows potential benefit for several clinical endpoints in oncology (differential diagnosis, prognosis and prediction of treatment response, and evaluation of side effects). Nevertheless, the studies included in this systematic review suffer from the bias of overall low quality, so that the conclusions are currently heterogeneous, not robust, and not replicable. Further research with prospective and multicentre studies is needed for the clinical validation of delta radiomics approaches.

Indexed as

Diagnostic ImagingHumansImage Interpretation, Computer-AssistedNeoplasmsDelta radiomicsMeta-analysisOncologyPrecision medicineRadiomicsRadiotherapyTexture analysis

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.