Lung Cancer Squamous CellNCT04034667
Study of CT and MR in the Lung Cancer
An observational study of Lung Cancer Squamous Cell and CT, run by Henan Cancer Hospital at 1 site in China.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 to 80 years
- Conditions the study is for
- Lung Cancer Squamous Cell, CT, Genes
- How many people
- 400 participants
- Where
- 1 siteChina
- Study dates
- 1 Sep 2019to 1 Dec 2023
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 80 years
- All sexes
- Adult, Older adult
Study population: Subjects with biopsy-proven lung cancer will receive treatment
Who may be able to join
- Consecutive patients with preoperative pathologically con-firmed lung cancer by endoscopy and preoperative imaging data were included.
- No contraindications for MRI examination. No contraindications for iodinated contrast.
- The patients participate in this study with informed consent.
Who cannot join
- The patients couldn't performed MSCT or MR scanning or artefacts affect the evaluation.
- The patients are extremely anxious and uncooperative about surgery or neoadjuvant therapy .
- PatientsThe patients refuse to participate in the project.
- Other situations considered by investigators not meet the inclusion criteria.
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Henan Cancer Hospital
Zhengzhou
Baoxia He, MD, 8637165588007, hnszlyygcp@163.com
About this study
Official title: Clinical Study of CT and MR in Prediction of Driving Genes and Response in Patients With Lung Cancer
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.
Read the detailed description
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.
- Conditions
- Lung Cancer Squamous Cell, CT, Genes, Response, MRI
- Being tested
- No intervention
- Keywords
- Lung Cancer, Imaging features, Driving genes, Prediction, Therapy response
- Medical subject headings
- Lung Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
No interventionOther
No intervention
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 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 .
Measured: up to 2 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Jul 2019
- Study start1 Sep 2019
- Primary completion1 Dec 2023 (estimated)
- Study completion1 Dec 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (5)Papers the sponsor has linked to this study.
- Other trials for Lung Cancer Squamous CellStudies of the same condition, open and under way.
- More trials run by Henan Cancer HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Prospective
- Enrolment
- 400 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Henan Cancer Hospital
- Sponsor type
- Other government
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04034667
- Sponsor's protocol ID
- FSK003
- Status last verified
- Jul 2019
- First submitted
- 17 Jul 2019
- Last updated
- 1 Apr 2020
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Publications
Shi L, Rong Y, Daly M, Dyer B, Benedict S, Qiu J, Yamamoto T. Cone-beam computed tomography-based delta-radiomics for early response assessment in radiotherapy for locally advanced lung cancer. Phys Med Biol. 2020 Jan 10;65(1):015009. doi: 10.1088/1361-6560/ab3247.
PubMed 31307024Lee G, Lee HY, Park H, Schiebler ML, van Beek EJR, Ohno Y, Seo JB, Leung A. Radiomics and its emerging role in lung cancer research, imaging biomarkers and clinical management: State of the art. Eur J Radiol. 2017 Jan;86:297-307. doi: 10.1016/j.ejrad.2016.09.005. Epub 2016 Sep 10.
PubMed 27638103Akinci D'Antonoli T, Farchione A, Lenkowicz J, Chiappetta M, Cicchetti G, Martino A, Ottavianelli A, Manfredi R, Margaritora S, Bonomo L, Valentini V, Larici AR. CT Radiomics Signature of Tumor and Peritumoral Lung Parenchyma to Predict Nonsmall Cell Lung Cancer Postsurgical Recurrence Risk. Acad Radiol. 2020 Apr;27(4):497-507. doi: 10.1016/j.acra.2019.05.019. Epub 2019 Jul 6.
PubMed 31285150Seki S, Fujisawa Y, Yui M, Kishida Y, Koyama H, Ohyu S, Sugihara N, Yoshikawa T, Ohno Y. Dynamic Contrast-enhanced Area-detector CT vs Dynamic Contrast-enhanced Perfusion MRI vs FDG-PET/CT: Comparison of Utility for Quantitative Therapeutic Outcome Prediction for NSCLC Patients Undergoing Chemoradiotherapy. Magn Reson Med Sci. 2020 Feb 10;19(1):29-39. doi: 10.2463/mrms.mp.2018-0158. Epub 2019 Mar 18.
PubMed 30880291Ciliberto M, Kishida Y, Seki S, Yoshikawa T, Ohno Y. Update of MR Imaging for Evaluation of Lung Cancer. Radiol Clin North Am. 2018 May;56(3):437-469. doi: 10.1016/j.rcl.2018.01.005.
PubMed 29622078
Study at a glance
From the registry record, last updated by the sponsor on 1 Apr 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Clinical Study of CT and MR in Prediction of Driving Genes and Response in Patients With Lung Cancer
- ClinicalTrials.gov ID
- NCT04034667
- Acronym / sponsor ID
- FSK003
- Conditions
- Lung Cancer Squamous Cell, CT, Genes, Response, MRI
- Keywords
- Lung Cancer, Imaging features, Driving genes, Prediction, Therapy response
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 400 participants (estimated)
- Lead sponsor
- Henan Cancer HospitalOther government
- Study start
- 1 Sep 2019 (actual)
- Primary completion
- 1 Dec 2023 (estimated)
- Study completion
- 1 Dec 2023 (estimated)
- First posted
- 26 Jul 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
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.
Study design
- Observational model
- Case-control
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- Subjects with biopsy-proven lung cancer will receive treatment
Key inclusion criteria (3 listed)
- Consecutive patients with preoperative pathologically con-firmed lung cancer by endoscopy and preoperative imaging data were included.
- No contraindications for MRI examination. No contraindications for iodinated contrast.
- The patients participate in this study with informed consent.
Key exclusion criteria (4 listed)
- The patients couldn't performed MSCT or MR scanning or artefacts affect the evaluation.
- The patients are extremely anxious and uncooperative about surgery or neoadjuvant therapy .
- PatientsThe patients refuse to participate in the project.
- Other situations considered by investigators not meet the inclusion criteria.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| No interventionNo intervention | Other | – |
Primary outcome
Study of relationship between clinical related data(driving genes and response) and imaging features(MSCT and MRI) in lung Cancer
Time frame: up to 2 year
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.
MSCT and MRI prediction of prognosis in lung cancer
Time frame: up to 2 year
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 .
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 1 Apr 2020.
- Background: PubMed 31307024Shi L, Rong Y, Daly M, Dyer B, Benedict S, Qiu J, Yamamoto T. Cone-beam computed tomography-based delta-radiomics for early response assessment in radiotherapy for locally advanced lung cancer. Phys Med Biol. 2020 Jan 10;65(1):015009. doi: 10.1088/1361-6560/ab3247.
- Background: PubMed 27638103Lee G, Lee HY, Park H, Schiebler ML, van Beek EJR, Ohno Y, Seo JB, Leung A. Radiomics and its emerging role in lung cancer research, imaging biomarkers and clinical management: State of the art. Eur J Radiol. 2017 Jan;86:297-307. doi: 10.1016/j.ejrad.2016.09.005. Epub 2016 Sep 10.
- Background: PubMed 31285150Akinci D'Antonoli T, Farchione A, Lenkowicz J, Chiappetta M, Cicchetti G, Martino A, Ottavianelli A, Manfredi R, Margaritora S, Bonomo L, Valentini V, Larici AR. CT Radiomics Signature of Tumor and Peritumoral Lung Parenchyma to Predict Nonsmall Cell Lung Cancer Postsurgical Recurrence Risk. Acad Radiol. 2020 Apr;27(4):497-507. doi: 10.1016/j.acra.2019.05.019. Epub 2019 Jul 6.
- Background: PubMed 30880291Seki S, Fujisawa Y, Yui M, Kishida Y, Koyama H, Ohyu S, Sugihara N, Yoshikawa T, Ohno Y. Dynamic Contrast-enhanced Area-detector CT vs Dynamic Contrast-enhanced Perfusion MRI vs FDG-PET/CT: Comparison of Utility for Quantitative Therapeutic Outcome Prediction for NSCLC Patients Undergoing Chemoradiotherapy. Magn Reson Med Sci. 2020 Feb 10;19(1):29-39. doi: 10.2463/mrms.mp.2018-0158. Epub 2019 Mar 18.
- Background: PubMed 29622078Ciliberto M, Kishida Y, Seki S, Yoshikawa T, Ohno Y. Update of MR Imaging for Evaluation of Lung Cancer. Radiol Clin North Am. 2018 May;56(3):437-469. doi: 10.1016/j.rcl.2018.01.005.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Lung Cancer Squamous Cell and CT, run by Henan Cancer Hospital at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 1 Apr 2020. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Each site lists its own contact: choose the nearest one under Trial locations. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Study of relationship between clinical related data(driving genes and response) and imaging features(MSCT and MRI) in lung Cancer (time frame: up to 2 year). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04034667, which also lists 5 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 1 Apr 2020.