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Molecular Imaging Visualization of Tumor Heterogeneity in Non-small Cell Lung Cancer

11. september 2020 oppdatert av: The First Affiliated Hospital of Xiamen University
To assess the potential usefulness of radiogenomics for tumor driving genes heterogeneity in non-small cell lung cancer.

Studieoversikt

Status

Ukjent

Forhold

Intervensjon / Behandling

Detaljert beskrivelse

Patients with advanced NSCLC underwent 18F-FDG PET/CT and PET/CT-guided synchronous targeted biopsy of primary and distant metastatic tumors. The LIFEx package was used to extract PET and CT radiomic features from primary and metastatic lesions. The radiomic ROI sites of primary and distant metastatic tumors were point-to-point corresponding to the PET/ CT-guided targeted biopsy sites. Whole exon sequencing of primary and distant metastatic tumor samples obtained by PET/CT-guided targeted biopsy was used to get genomic data of primary and distant metastatic tumor. Predictive radiogenomics models were established and validation.

Studietype

Intervensjonell

Registrering (Forventet)

150

Fase

  • Ikke aktuelt

Kontakter og plasseringer

Denne delen inneholder kontaktinformasjon for de som utfører studien, og informasjon om hvor denne studien blir utført.

Studiesteder

  • Kina
    • Fujian
      • XiaMen, Fujian, Kina, 0086-361000
        • Rekruttering
        • First Affiliated Hospital of Xiamen University
        • Ta kontakt med:

Deltakelseskriterier

Forskere ser etter personer som passer til en bestemt beskrivelse, kalt kvalifikasjonskriterier. Noen eksempler på disse kriteriene er en persons generelle helsetilstand eller tidligere behandlinger.

Kvalifikasjonskriterier

Alder som er kvalifisert for studier

18 år til 90 år (Voksen, Eldre voksen)

Tar imot friske frivillige

Nei

Kjønn som er kvalifisert for studier

Alle

Beskrivelse

Criteria: Inclusion Criteria:

  • (i) adult patients (aged 18 years or order);
  • (ii) patients with suspected or newly diagnosed or previously treated malignant tumors (supporting evidence may include magnetic resonance imaging (MRI), CT, tumor markers and pathology report);
  • (iii) patients who had scheduled both 18F-FDG PET/CT scans and PET/CT guided biopsy;
  • (iv) patients who were able to provide informed consent (signed by participant, parent or legal representative) and assent according to the guidelines of the Clinical Research Ethics Committee.

Exclusion Criteria:

  • (i) patients with non-malignant lesions;
  • (ii) patients with pregnancy;
  • (iii) the inability or unwillingness of the research participant, parent or legal representative to provide written informed consent.

Studieplan

Denne delen gir detaljer om studieplanen, inkludert hvordan studien er utformet og hva studien måler.

Hvordan er studiet utformet?

Designdetaljer

  • Primært formål: Diagnostisk
  • Tildeling: N/A
  • Intervensjonsmodell: Enkeltgruppeoppdrag
  • Masking: Ingen (Open Label)

Våpen og intervensjoner

Deltakergruppe / Arm
Intervensjon / Behandling
Eksperimentell: 8F-FDG PET/CT and PET/CT-guide targeted biopsy
Each subject receive a single intravenous injection of 18F-FDG PET/CT and PET/CT-guide targeted biopsy within the specified time.
Diagnostisk test: 18F-FDG PET/CT and PET/CT-guide targeted biopsy in another group of participants
Each subject receive a single intravenous injection of 18F-FDG PET/CT and PET/CT-guide targeted biopsy within the specified time

Hva måler studien?

Primære resultatmål

Resultatmål
Tiltaksbeskrivelse
Tidsramme
Radiomic feature selection and model establishment
Tidsramme: 3 years
In this study, the investigators first selected the features with significant differences between genes mutant and wild type in the training set using the Mann-Whitney U test, obtaining a total of 53 features with p value < 0.05. Then, the least absolute shrinkage and selection operator (LASSO) algorithm was used to select the optimal predictive features among the 53 selected in the training set. The LASSO algorithm adds a L1 regularization term to a least square algorithm to avoid overfitting. A prediction model was established by logistic regression, and the radiomics signature score (rad-score) for each participant was calculated based on the selected discriminating radiomic features. The model performance was tested in the validation set. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used to evaluate the model performance in the training and validation sets.
3 years

Sekundære resultatmål

Resultatmål
Tiltaksbeskrivelse
Tidsramme
Genes mutation detection
Tidsramme: 30 days
Genes mutation detection was performed on histological specimens obtained by surgical resection or puncture. Genes mutation detection was conducted by the examination of the whole-exome sequencing. The whole-exome sequencing is performed by the Novogene company (www.novogene.com). If any genes mutation in the whole-exome sequencing was detected, the tumor was considered genes mutant. Otherwise, the tumor was classified as no mutant of genes type.
30 days
Image acquisition
Tidsramme: 30 days
The imaging acquisition protocol was established following the Image Biomarker Standardisation Initiative (IBSI) reporting guidelines. All the details of the procedures are provided in the electronic supplementary material. 18F-FDG PET/CT (Discovery MI, GE Healthcare, Milwaukee, WI, USA) examination was performed within 1 month before treatment. Briefly, 18F-FDG PET/CT images were acquired 60 ± 5 min after 18F-FDG injection in accordance with the European Association of Nuclear Medicine (EANM) guidelines, version 1.0 (version 2.0 from February 2015). A 3D LOR reconstruction algorithm was used to reconstruct the PET images. The attenuation correction of PET images was carried out with CT data, and the corrected PET images were fused with CT images.
30 days
Radiomic feature extraction
Tidsramme: 30 days
The LIFEx package (version 4.00, http://www.lifexsoft.org) was used to extract the texture features of PET/CT images of lesions in the same VOI. The PET/CT image of the patient in the DICOM format was imported into the software. Two experienced PET/CT diagnostic physicians semi-automatically delineated the region of interest of the target lesion using a threshold of 40% of the maximum standardized uptake value (SUVmax). Then, the software program automatically calculates and extracts 47 PET radiomic features and 45 CT radiomic features.
30 days

Samarbeidspartnere og etterforskere

Det er her du vil finne personer og organisasjoner som er involvert i denne studien.

Sponsor

The First Affiliated Hospital of Xiamen University

Etterforskere

  • Hovedetterforsker: Long Sun, PhD, The First Affiliated Hospital of Xiamen University

Studierekorddatoer

Disse datoene sporer fremdriften for innsending av studieposter og sammendragsresultater til ClinicalTrials.gov. Studieposter og rapporterte resultater gjennomgås av National Library of Medicine (NLM) for å sikre at de oppfyller spesifikke kvalitetskontrollstandarder før de legges ut på det offentlige nettstedet.

Studer hoveddatoer

Studiestart (Faktiske)

1. oktober 2019

Primær fullføring (Forventet)

1. oktober 2022

Studiet fullført (Forventet)

1. oktober 2022

Datoer for studieregistrering

Først innsendt

30. juli 2020

Først innsendt som oppfylte QC-kriteriene

11. september 2020

Først lagt ut (Faktiske)

17. september 2020

Oppdateringer av studieposter

Sist oppdatering lagt ut (Faktiske)

17. september 2020

Siste oppdatering sendt inn som oppfylte QC-kriteriene

11. september 2020

Sist bekreftet

1. juli 2020

Mer informasjon

Begreper knyttet til denne studien

Nøkkelord

Ytterligere relevante MeSH-vilkår

Andre studie-ID-numre

  • KYH2019-039

Plan for individuelle deltakerdata (IPD)

Planlegger du å dele individuelle deltakerdata (IPD)?

NEI

Legemiddel- og utstyrsinformasjon, studiedokumenter

Studerer et amerikansk FDA-regulert medikamentprodukt

Nei

Studerer et amerikansk FDA-regulert enhetsprodukt

Nei

Denne informasjonen ble hentet direkte fra nettstedet clinicaltrials.gov uten noen endringer. Hvis du har noen forespørsler om å endre, fjerne eller oppdatere studiedetaljene dine, vennligst kontakt register@clinicaltrials.gov. Så snart en endring er implementert på clinicaltrials.gov, vil denne også bli oppdatert automatisk på nettstedet vårt. .

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