An observational study in Lung Cancer Squamous Cell, CT and Genes, sponsored by Henan Cancer Hospital. Status unknown at 1 site in China. Open to participants aged 18 Years to 80 Years. Per ClinicalTrials.gov, last updated 2020-04-01.
Sponsored by Henan Cancer Hospital · Observational
Lung cancer is one of the leading causes of cancer-related deaths in China. Despite advances in systemic therapy and improvement nonsurvival rates for patients with advanced lung cancer, morbidity and mortality remain high.
Recently, many studies reported that patients with positive driving genes such as EGFR(epidermal growth factor receptor,EGFR), ALK(anaplastic lymphoma kinase,ALK), ROS1(c-ros oncogene 1 receptor,ROS1), BRAF (V-raf murine sarcoma viral oncogene homolog B1, BRAF)and so on have clearly targeted drugs, which bring survival benefits to patients. However, about half of patients still lack a clear driving gene target, which may have improved survival due to higher response rates to radiation therapy and other chemotherapy medications.
Development of noninvasive imaging biomarkers such as CT (computed tomography,CT)and MRI (magnetic resonance imaging,MRI)may not only evaluate the response to therapy ,but also could predict the efficacy of drug therapy and whether the driving gene is positive or not, through analysing the relationship between clinical related data and imaging features to find the imaging characteristics for making clinical decisions, and, consequently, contribute to an improved prognosis.
To explore the value of CT and MR using multiple sequences, including T2-TSE-BLADE, T2 maps StarVIBE, and iShim-DWI in evaluating the driving genes and prediction of response to therapy and OS in patients with lung cancer.
Patients with biopsy-proven lung cancer were prospectively enrolled for imaging on CT and a 3T MRI scanner . The MRI protocol included T2-TSE-BLADE, T2 maps,iShim-DWI and StarVIBE sequences, and so on. Patients received treatment according to NCCN( National Comprehensive Cancer Network) guideline. CT and MRI features were analyzed to find the correlation between pretreatment imaging features and driving genes and therapy response. The study will include 400 patients. Inter-reader agreements of TN staging were analyzed excellent for CT and MRI. Diagnostic accuracy of CT and MRI will be calculated separately.
7,243 studies on the registry are indexed under Lung Neoplasms; 1,557 are open to participants now.
This study's planned enrollment of 400 is above the median of 189 across 1,514 observational studies indexed under Lung Neoplasms.
Browse Lung Neoplasms studies →Henan Cancer Hospital is the lead sponsor of 228 studies on the registry; 130 are open to participants now.
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Subjects with biopsy-proven lung cancer will receive treatment
Exclusion Criteria:
No intervention
Study of relationship between clinical related data(driving genes and response) and imaging features(MSCT and MRI) in lung Cancer
Retrospectively reviewed data for patients diagnosed with lung cancer . All patients had received a histopathologic diagnosis of lung cancer based on bronchoscopic, percutaneous needle-guided, or surgical biopsies and had undergone gene mutation studies. Analysed the relationship between clinical related data(driving genes and response) and imaging features.
Time frame: up to 2 year
MSCT and MRI prediction of prognosis in lung cancer
To construct a model,a depth convolution neural network based on MSCT and multi-modal MR quantitative images which can automatically mine key images characterization, combined with imaging features,driving genes and prognosis,could further help to improve the prediction of response and OS of lung cancer treated with systematic therapy .
Time frame: up to 2 year
Plan to share: Undecided
This study is status unknown, as verified in Jul 2019. You cannot join it, but the record below documents what was studied.
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Henan Cancer Hospital