Lung CancerNCT03954847
Clinical Significance of Computer Aided Image Analysis in Treatment Response Evaluation of Lung Cancer
An observational study of Lung Cancer, run by Union Hospital, Tongji Medical College, Huazhong University of Science and Technology at 1 site in China.
Trial summary
The investigators will evaluate the utility of computer aided image analysis in lung cancer with the aim of predicting treatment response and prognosis. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Lung Cancer
- How many people
- 1,000 participants
- Where
- 1 siteChina
- Study dates
- 1 Jan 2012to 31 Dec 2020
- 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 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Lung cancer patients with PET/CT or CT examination before any cancer-specific treatment
Who may be able to join
- Patients >= 18 years old
- Pathological diagnosis of NSCLC between 2012 and 2019;
- PET/CT or CT examination before any cancer-specific treatment;
Who cannot join
- A time interval between treatment and image examination greater than 1 month;
- A history of other malignancies
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
Wuhan, Hubei, 430000
Yang Jin, MD
About this study
The investigators will evaluate the utility of computer aided image analysis in lung cancer with the aim of predicting treatment response and prognosis.
Read the detailed description
Tumor biological behavior is the fundamental cause of heterogeneous prognosis. The features found on medical images are also reflections of the tumor biological behavior. However, the limitations in spatial and intensity resolution of the naked eye are two inevitable shortcomings of image interpretation by naked eyes, resulting in subjective and limited analyses of images. Computer aided image analyses such as radiomic analysis and machine learning methods are emerging as promising image interpretation methods. The natural advantage of the unlimited spatial and intensity resolution of computers can overcome the shortcomings of visual inspection with the naked eye. Moreover, the massive computing power of computer is also far greater than that of humans. This study will focus on the application of computer aided analysis in predicting treatment response and prognosis in lung cancer.
- Conditions
- Lung Cancer
- Keywords
- Lung cancer, Image, Treatment response, Prognosis, Radiomic, Deep learning
- Medical subject headings
- Lung Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Lung cancer patients | Lung cancer patients with PET/CT or CT examination before any cancer-specific treatment |
What is being measured
The primary outcome is the main question the study is designed to answer.
Overall survival
The interval between the date of diagnosis and death
Measured: 2012-2021
Secondary outcomes (1)
Progression free survival
The interval between the date of treatment initiation and disease progression
Measured: 2012-2021
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted17 May 2019
- Study start1 Jan 2012
- Primary completion31 Dec 2020 (estimated)
- Study completion31 Dec 2020 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Lung CancerStudies of the same condition, open and under way.
- More trials run by Union Hospital, Tongji Medical College, Huazhong University of Science and TechnologyThe 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
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 1,000 participants (estimated)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Yang Jin, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03954847
- Sponsor's protocol ID
- WuhanUH-V1.2
- Status last verified
- May 2019
- First submitted
- 16 May 2019
- Last updated
- 17 May 2019
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 17 May 2019. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Clinical Significance of Computer Aided Image Analysis in Treatment Response Evaluation of Lung Cancer
- ClinicalTrials.gov ID
- NCT03954847
- Acronym / sponsor ID
- WuhanUH-V1.2
- Conditions
- Lung Cancer
- Keywords
- Lung cancer, Image, Treatment response, Prognosis, Radiomic, Deep learning
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 1,000 participants (estimated)
- Lead sponsor
- Union Hospital, Tongji Medical College, Huazhong University of Science and TechnologyUniversity, hospital or other
- Study start
- 1 Jan 2012 (actual)
- Primary completion
- 31 Dec 2020 (estimated)
- Study completion
- 31 Dec 2020 (estimated)
- First posted
- 17 May 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.
The investigators will evaluate the utility of computer aided image analysis in lung cancer with the aim of predicting treatment response and prognosis.
Detailed description
Tumor biological behavior is the fundamental cause of heterogeneous prognosis. The features found on medical images are also reflections of the tumor biological behavior. However, the limitations in spatial and intensity resolution of the naked eye are two inevitable shortcomings of image interpretation by naked eyes, resulting in subjective and limited analyses of images. Computer aided image analyses such as radiomic analysis and machine learning methods are emerging as promising image interpretation methods. The natural advantage of the unlimited spatial and intensity resolution of computers can overcome the shortcomings of visual inspection with the naked eye. Moreover, the massive computing power of computer is also far greater than that of humans. This study will focus on the application of computer aided analysis in predicting treatment response and prognosis in lung cancer.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Lung cancer patients | – | –Lung cancer patients with PET/CT or CT examination before any cancer-specific treatment |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Lung cancer patients with PET/CT or CT examination before any cancer-specific treatment
Key inclusion criteria (3 listed)
- Patients >= 18 years old
- Pathological diagnosis of NSCLC between 2012 and 2019;
- PET/CT or CT examination before any cancer-specific treatment;
Key exclusion criteria (2 listed)
- A time interval between treatment and image examination greater than 1 month;
- A history of other malignancies
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Overall survival
Time frame: 2012-2021
The interval between the date of diagnosis and death
1 secondary outcome
Progression free survival
Time frame: 2012-2021
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 17 May 2019.
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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, run by Union Hospital, Tongji Medical College, Huazhong University of Science and Technology 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 2 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 17 May 2019. 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?
Contact Yang Jin, MD (027-85755457, whuhjy@126.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Overall survival (time frame: 2012-2021). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 17 May 2019.