Clinical trial · Observational
Influence of PET/CT Radiomic Features on the Outcome of Lung Cancer Patients
NCT03648151CI-TRIAL-00046111completedClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
Radiomics is an attractive field in objectively quantifying image features, and may overcome the subjectivity of visually interpreting computed tomography (CT), or positron emission tomography (PET). It is reported that the features related to treatment response, outcomes, tumor staging, tissue identification, and cancer genetics. Therefore, the investigators try to explore the key features for the outcome of lung cancer patients.
Conditions
Conditions (2)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Image, Body | — | UNRESOLVED | — |
| Lung Cancer | Malignant Lung Neoplasm | CURATED_EXACT | 0.92 |
Interventions
Interventions (0)
Data not yet available
No intervention recorded.
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (1)
- measure
- Overall survival (OS) of lung cancer patients
- timeFrame
- The patients were followed to December 31, 2019
- description
- The time from the scan date to death for any reason
Eligibility
Eligibility (as posted)
- Sex
- All
Show eligibility criteria text
Inclusion Criteria: 1. Pathologically diagnosed as lung caner. 2. Accepted PET/CT scans at the hospitals either affiliated to Shanxi Medical University or Anhui Medical University 3. Both PET and CT serials can be obtained 4. Can be followed for treatment modalities (including chemotherapy regimens, radiotherapy dose, and et al), survival time and status, and other related information. Exclusion Criteria: 1. Simultaneously suffering from the cancers from other tissues and organs 2. Have a history of diabetes, chronic heart diseases, or chronic renal failure
References
Publications (7)
- BACKGROUNDGaneshan B, Skogen K, Pressney I, Coutroubis D, Miles K. Tumour heterogeneity in oesophageal cancer assessed by CT texture analysis: preliminary evidence of an association with tumour metabolism, stage, and survival. Clin Radiol. 2012 Feb;67(2):157-64. doi: 10.1016/j.crad.2011.08.012. Epub 2011 Sep 23. PMID 21943720
- BACKGROUNDGiesel FL, Schneider F, Kratochwil C, Rath D, Moltz J, Holland-Letz T, Kauczor HU, Schwartz LH, Haberkorn U, Flechsig P. Correlation Between SUVmax and CT Radiomic Analysis Using Lymph Node Density in PET/CT-Based Lymph Node Staging. J Nucl Med. 2017 Feb;58(2):282-287. doi: 10.2967/jnumed.116.179648. Epub 2016 Sep 22. PMID 27660141
- BACKGROUNDAerts HJ, Velazquez ER, Leijenaar RT, Parmar C, Grossmann P, Carvalho S, Bussink J, Monshouwer R, Haibe-Kains B, Rietveld D, Hoebers F, Rietbergen MM, Leemans CR, Dekker A, Quackenbush J, Gillies RJ, Lambin P. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun. 2014 Jun 3;5:4006. doi: 10.1038/ncomms5006. PMID 24892406
- BACKGROUNDYip SS, Kim J, Coroller TP, Parmar C, Velazquez ER, Huynh E, Mak RH, Aerts HJ. Associations Between Somatic Mutations and Metabolic Imaging Phenotypes in Non-Small Cell Lung Cancer. J Nucl Med. 2017 Apr;58(4):569-576. doi: 10.2967/jnumed.116.181826. Epub 2016 Sep 29. PMID 27688480
- BACKGROUNDYip SS, Aerts HJ. Applications and limitations of radiomics. Phys Med Biol. 2016 Jul 7;61(13):R150-66. doi: 10.1088/0031-9155/61/13/R150. Epub 2016 Jun 8. PMID 27269645
- BACKGROUNDSollini M, Cozzi L, Antunovic L, Chiti A, Kirienko M. PET Radiomics in NSCLC: state of the art and a proposal for harmonization of methodology. Sci Rep. 2017 Mar 23;7(1):358. doi: 10.1038/s41598-017-00426-y. PMID 28336974
- DERIVEDHongwei S, Xinzhong H, Huiqin X, Shuqin X, Ruonan W, Li L, Jianzhong C, Sijin L. Standard deviation of CT radiomic features among malignancies in each individual: prognostic ability in lung cancer patients. J Cancer Res Clin Oncol. 2023 Aug;149(10):7165-7173. doi: 10.1007/s00432-023-04649-7. Epub 2023 Mar 8.