Paper · 42938162

Radiomics-Based Outcome Prediction in Transarterial Radioembolization (TARE) of Hepatic Malignancies: A Systematic Review and Quality Appraisal.

Grainger RT and 11 others. Diagnostics (Basel), 2026.

11 sourcespapers-2026-11-12-0.1.0

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ConductScience Library. Radiomics-Based Outcome Prediction in Transarterial Radioembolization (TARE) of Hepatic Malignancies: A Systematic Review and Quality Appraisal. Papers, record 42938162. Release papers-2026-11-12-0.1.0, 12 Nov 2026. https://conductscience.org/library/papers/42938162

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Title: Radiomics-Based Outcome Prediction in Transarterial Radioembolization (TARE) of Hepatic Malignancies: A Systematic Review and Quality Appraisal.
Journal: Diagnostics (Basel)
Year: 2026
Publication types: Journal Article, Review
PubMed: https://pubmed.ncbi.nlm.nih.gov/42938162/
DOI: https://doi.org/10.3390/diagnostics16203322
PMC: https://pmc.ncbi.nlm.nih.gov/articles/PMC13703477/
The journal: https://conductscience.org/library/journal-index/101658402
Revised in PubMed: 2026-10-28

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Authors12

The authors in the order PubMed's record lists them, with the ORCID iDs it states.

Order	Author	Forename	ORCID iD
1	Grainger RT	Richard T
2	Temperley HC	Hugo C	https://orcid.org/0000-0001-9151-3431
3	Saadeh OA	Omar Abu
4	O'Sullivan NJ	Niall J	https://orcid.org/0000-0002-6241-7819
5	Mac Curtain BM	Benjamin M
6	Sheahan KP	Kevin P	https://orcid.org/0000-0001-7034-2688
7	Brennan I	Ian
8	Ng ZQ	Zi Qin	https://orcid.org/0000-0002-6272-4640
9	Mitchell T	Tim
10	Kelly ME	Michael E	https://orcid.org/0000-0002-0757-6411

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References53

The papers the reference list in PubMed's record names, those in our copy of PubMed, in the list's order.

Order	PMID	Title	Journal	Year	In Papers	Source
1	35,183,483	Comparison of MRI-based response criteria and radiomics for the prediction of early response to transarterial radioembolization in patients with hepatocellular carcinoma.	Diagn Interv Imaging	2022	https://conductscience.org/library/papers/35183483	PubMed
2	41,604,060	18F-FDG PET radiomics model for predicting TARE response in patients with colorectal cancer liver metastases.	Jpn J Radiol	2026	https://conductscience.org/library/papers/41604060	PubMed
3	34,628,667	A deep-learning-based prediction model for the biodistribution of 90 Y microspheres in liver radioembolization.	Med Phys	2021	https://conductscience.org/library/papers/34628667	PubMed
4	28,994,423	Cholangiocarcinoma - evolving concepts and therapeutic strategies.	Nat Rev Clin Oncol	2018	https://conductscience.org/library/papers/28994423	PubMed
5	42,022,735	Prognostic and predictive value of radiomics-based imaging features in patients with colorectal liver metastasis receiving radioembolisation in first-line setting.	Eur J Radiol Open	2026	https://conductscience.org/library/papers/42022735	PubMed
6	23,811,303	Radiation lobectomy: time-dependent analysis of future liver remnant volume in unresectable liver cancer as a bridge to resection.	J Hepatol	2013	https://conductscience.org/library/papers/23811303	PubMed
7	34,485,629	Prediction of treatment response to transarterial radioembolization of liver metastases: Radiomics analysis of pre-treatment cone-beam CT: A proof of concept study.	Eur J Radiol Open	2021	https://conductscience.org/library/papers/34485629	PubMed
8	32,227,266	Radiomics of cholangiocarcinoma on pretreatment CT can identify patients who would best respond to radioembolisation.	Eur Radiol	2020	https://conductscience.org/library/papers/32227266	PubMed
9	29,881,933	Assessment of Therapy Response to Transarterial Radioembolization for Liver Metastases by Means of Post-treatment MRI-Based Texture Analysis.	Cardiovasc Intervent Radiol	2018	https://conductscience.org/library/papers/29881933	PubMed
10	38,220,040	Radiomics Features Extracted From Pre- and Postprocedural Imaging in Early Prediction of Treatment Response in Patients Undergoing Transarterial Radioembolization of Hepatic Lesions: A Systematic Review, Meta-Analysis, and Quality Appraisal Study.	J Am Coll Radiol	2024	https://conductscience.org/library/papers/38220040	PubMed

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PubMed: 2026-11-06; PubMed
iCite: 2026-11-05; iCite
PMC's ID file: 2026-11-05; PMC's ID file
NIH RePORTER's grant and paper links: 2026-11-01; NIH RePORTER's grant and paper links
Trials: 2026-11-12
Gene search: 2026-11-11
Pipelines: 2026-09-18

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iCiteCC BY 4.0
NCBI GenePublic domain (US government)
NIH RePORTER's grant and paper linksPublic domain
Open TargetsCC0 1.0
PMC's ID filePublic domain (US government)
PubMedNLM's terms
PubTator 3Public domain
UniProtCC BY 4.0

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ChEMBL, through Open TargetsCC BY-SA 3.0, for the parts from ChEMBL. Read on 8 Nov 2026 at https://platform-docs.opentargets.org/licence
ClinicalTrials.govnone stated
HGNCCC0: https://www.genenames.org/about/license/
iCiteCC BY 4.0
NCBI GeneNone named for the file. NCBI says information created by or for the US government on its site is in the public domain, and asks that NLM be acknowledged: https://www.ncbi.nlm.nih.gov/home/about/policies/
NIH RePORTER's grant and paper linksPublic domain (NIH RePORTER)
Open TargetsCC0 1.0. Open Targets asks that users cite its latest paper: Buniello et al. 2025, Open Targets Platform: facilitating therapeutic hypotheses building in drug discovery, Nucleic Acids Research 53(D1):D1467, PMID 39657122. Read on 8 Nov 2026 at https://platform-docs.opentargets.org/licence
PMC's ID fileNone named for the file. NCBI says information created by or for the US government on its site is in the public domain, and asks that NLM be acknowledged: https://www.ncbi.nlm.nih.gov/home/about/policies/
PubMedNLM's terms
PubTator 3Public domain
UniProtCC BY 4.0. UniProt's licence file: "All databases and documents in the UniProt FTP directory may be copied and redistributed freely, without advance permission, provided that this copyright statement is reproduced with each copy." UniProt asks that users cite its latest paper: The UniProt Consortium, UniProt: the Universal Protein Knowledgebase in 2025, Nucleic Acids Research 53:D609-D617, https://doi.org/10.1093/nar/gkae1010. Read on 9 Nov 2026 at https://www.uniprot.org/help/license

ClinicalTrials.gov's data carry an international copyright outside the United States: https://clinicaltrials.gov/about-site/terms-conditions.

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