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Radiomics for prEdiction of lunG cAncer biologY

Prediction of Lung Cancer Characteristics Using PET/CT Radiomics

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT05819905
Enrollment
600
Registered
2023-04-19
Start date
2023-01-01
Completion date
2024-01-01
Last updated
2023-04-19

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Gene Mutation-Related Cancer, Non Small Cell Lung Cancer, PD-L1, PET/CT

Brief summary

Therapeutic progress for subgroups of Non Small Cell Lung Cancer can largely be attributed to the accumulation of molecular knowledge and the development of new drugs that specifically target molecular abnormalities. An understanding of the immune landscape of tumors, including immune-evasion strategies, has also led to breakthrough therapeutic advances.These new options require prior treatment tumoral sampling to identify patients who have neoplasms with specific genomic aberrations or favorable immune environment. Medical imaging and radiomic approach may provides surrogate markers non invasively.The objective of the present retrospective study is to build and validate a predictive model of common molecular alterations and PD-L1 expression in NSCLC using pre treatment PET/CT derived radiomics.

Interventions

DIAGNOSTIC_TESTPET/CT

Pre treatment staging 18F-FDG PET/CT

Sponsors

Poitiers University Hospital
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
RETROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* Histologically proven NSCLCC * pre treatment 18F FDG PET/CT * available molecular biology and histology results

Exclusion criteria

* non available PET/CT images

Design outcomes

Primary

MeasureTime frameDescription
prediction of PDL1 expression1 monthEvaluation of the performances of PET/CT derived radiomics to predict PDL1 expression \>1% (PDL1 : Programmed death-ligand 1 as previously determined on routine tumoral biopsy): area under the receiver operating characteristics curve (AUC), accuracy, sensitivity and specificity.
prediction of EGFR genomic alteration1 monthEvaluation of the performances of PET/CT derived radiomics to predict the presence of EGFR mutation (EGFR: epidermal growth factor receptor, presence /or not of EGFR alteration as previously determined on routine tumoral biopsy): area under the receiver operating characteristics curve (AUC), accuracy, sensitivity and specificity.

Secondary

MeasureTime frameDescription
Prediction of KRAS alteration1 monthEvaluation of the performances of PET/CT derived radiomics to predict the presence of KRAS mutation (KRAS : Kirsten rat sarcoma viral oncogene : presence/or not of KRAS alteration as previously determined on routine tumoral biopsy): area under the receiver operating characteristics curve (AUC), accuracy, sensitivity and specificity.
Prediction of BRAF mutation1 monthEvaluation of the performances of PET/CT derived radiomics to predict the presence of BRAF mutation (BRAF : raf murine sarcoma viral oncogene homolog B, presence/or not of BRAF mutation as previously determined on routine tumoral biopsy): area under the receiver operating characteristics curve (AUC), accuracy, sensitivity and specificity.
Prediction of ALK/ROS translocation1 monthEvaluation of the performances of PET/CT derived radiomics to predict the presence of ALK/ROS translocation (ALK : anaplastic lymphoma receptor tyrosine kinase, ROS : c-ROS protooncogene 1; presence /or not of ALK and ROS alteration as previously determined on routine tumoral biopsy): area under the receiver operating characteristics curve (AUC), accuracy, sensitivity and specificity.

Countries

France

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026