Lung CancerNODU-MRNCT06825078
Performance of Lung MRI Combined to Synthetic CT in the Follow-up of Lung Nodules
A study testing multiparametric MRI in people with Lung Cancer, run by University Hospital, Bordeaux at 1 site in France.
Trial summary
Lung cancer screening trials using low-dose chest CT scans have shown a significant reduction of cancer related mortality in subjects at high risk of lung cancer. However, high rate of false positives and overdiagnosis have led to invasive methods, which are not without risks. Read more about this study
- Who is it for?
- Ages 55 to 74 years
- Conditions the study is for
- Lung Cancer
- What is being tested?
- multiparametric MRI
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 50 participants
- Where
- 1 siteFrance
- Study dates
- 12 Feb 2025to Feb 2029
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
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 55 to 74 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Subject aged between 55 and 74 years
- High risk of developing lung cancer: by a combination of exposure to lung carcinogens and smoking (exposure to tobacco at the rate of 30 packs/year or cessation < 15 years)
- Presence of at least one lung solid nodule ≥ 5mm on the initial scan.
- Subject able and willing to complete all scheduled visits and assessments.
- Subject with health insurance.
- Signed informed consent.
Who cannot join
- Subject with signs of lung cancer
- Subject with history of lung cancer
- Presence of severe life-threatening comorbidities at 6 months (recent CVA, recent discovery of advanced stage cancer)
- Subject who had already undergone a chest scan less than a year previously
- No exposure to occupational lung carcinogens according to the predefined criteria.
- No exposure to tobacco or insufficient exposure to tobacco or cessation > 15 years.
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- Contra-indication to MRI (Pace maker, implants, claustrophobia…)
- Pregnant or breastfeeding woman
- Poor understanding of French
- Subject under legal protection
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
France1 site, 1 recruiting
- Recruiting
CHU Bordeaux
Pessac
Ilyes Benlala, MD, +335 57 65 65 42, ilyes.ben-lala@chu-bordeaux.fr
About this study
Lung cancer screening trials using low-dose chest CT scans have shown a significant reduction of cancer related mortality in subjects at high risk of lung cancer. However, high rate of false positives and overdiagnosis have led to invasive methods, which are not without risks. Evaluation of lung nodules using lung MRI with ultra short echo time sequences (UTE) has been found comparable to chest CT scans. Moreover, MRI has the advantage of multiparametric characterization of lesions using different tissue contrasts. Following the recommendation of the French National Authority for Health (HAS) to evaluate new methods of lung cancer screening, this prospective single center pilot study is designed to evaluate the performance of multiparametric lung MRI combined to synthetic CT in the diagnosis of lung cancer in heavily smokers or ex-smokers professionally exposed to carcinogens
Read the detailed description
Lung cancer is the leading cause of cancer-related deaths worldwide. In France, its incidence was estimated at 46,300 in 2018. In most cases, the diagnosis is initially made by the detection of a nodule or mass on chest X-ray or CT scan. Thus, most often non-invasive follow-up by chest CT scans is recommended. More expensive and invasive methods may also be proposed. However, patients with benign nodules may undergo diagnostic methods that are not without risks (exposure to ionizing radiation, complications related to trans-thoracic or surgical biopsy, etc.).
Lung Cancer Screening Trials (NLST, NELSON) have shown that lung cancer related mortality is reduced in subjects with high risk of lung cancer screened by using low-dose chest CT. Nevertheless, published systematic reviews and meta-analyses report a number of side effects of screening related to false positives and over diagnosis. In addition, the assessment of the risks related to the cumulative dose of exposure to ionising radiation during successive rounds of screening remains unknown. Consequently, the French National Authority for Health (HAS) recommends that pilot programs to be conducted to evaluate the different modalities for the organization of a national lung cancer screening program.
The spatial resolution of magnetic resonance imaging (MRI) of the lung has been significantly improved in the last decade, thanks to the development of ultra-short echo time (UTE) sequences. The advantage of MRI, in addition of being a free-radiation imaging technique, lies in its multiparametric nature with T1-weighted, T2-weighted and diffusion-weighted imaging providing images of different contrasts allowing the characterization of lesions. However, the follow-up of lung nodules, especially with the calculation of the volume doubling time (VDT) on UTE MRI, has not been evaluated. In addition, the performance of multiparametric MRI combining T2 signal, apparent diffusion coefficient (ADC) and nodule volume in determining nodule malignancy remains to be assessed. Recently, the development of artificial intelligence (AI) techniques with generative adversarial networks (GANs) has made it possible to generate CT-like imaging from MRI images. A very recent work demonstrated that AI model is able to generate from UTE lung MRI images, a high resolution synthetic CT image with a very similar texture to the standard CT and better quality than UTE alone. Therefore, the present sudy hypothesis is that multiparametric MRI combined with synthetic CT could have a complementary role with low-dose CT in lung cancer screening to reduce the false positive rate and to perform a free-radiation follow-up of lung nodules
- Conditions
- Lung Cancer
- Being tested
- multiparametric MRI
- Keywords
- lung cancer screening, nodule, multiparametric lung MRI, low-dose chest CT, artificial intelligence
- Medical subject headings
- Lung Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
multiparametric MRIDevice
An MRI scan will be performed within 2 weeks of the discovery of a solid lung nodule ≥ 5mm on the screening scan.
When a follow-up scan is indicated, an MRI will be repeated on the same day as the follow-up scan.
The MRI sequences that will be performed are: SpiraleVibe UTE, T1map, T2 map and Diffusion.
A synthetic scanner image will be generated from the UTE morphological MRI image using a generative artificial intelligence (GAN) model.
| Study group | Role | What they receive |
|---|---|---|
| multiparametric MRI | Experimental | An MRI scan will be performed within 2 weeks of the discovery of a solid lung nodule ≥ 5mm on the screening scan.
When a follow-up scan is indicated, an MRI will be repeated on the same day as the follow-up scan.
The MRI sequences that will be performed are: SpiraleVibe UTE, T1map, T2 map and Diffusion.
A synthetic scanner image will be generated from the UTE morphological MRI image using a generative artificial intelligence (GAN) model. Receives: Device: multiparametric MRI |
What is being measured
The primary outcome is the main question the study is designed to answer.
Positivity threshold
Positivity threshold of the combined score to obtain a specificity of at least 90%, and diagnostic performance parameters associated with this threshold (sensitivity, positive and negative predictive values).
Measured: Baseline, Month 3, Month 12
Secondary outcomes (3)
Area under the ROC curve
Area under the ROC curve (AUROC) of each of the radiological parameters (nodule volume in mm3 measured on UTE images, nodule mean T1/T2 signal in msec and mean of nodule ADC in mm2/s) and of the combined multiparametric MRI score (i.e., volume and signal) in predicting nodule progression (benign vs. malignant) Area under the ROC curve (AUROC) of each of the radiological parameters (nodule volume in mm3 measured on UTE images, nodule mean T1/T2 signal in msec and mean of nodule ADC in mm2/s) and of the combined multiparametric MRI score (i.e., volume and signal) in predicting nodule progression (benign vs. malignant)
Measured: Baseline, Month 3, Month 12
Intraclass correlation coefficient between CT and synthetic CT
Intraclass correlation coefficient between measurements performed using standard CT and synthetic CT generated from UTE MRI.
Measured: Baseline, Month 3, Month 12
multiparametric MRI characteristics
Description of the multiparametric MRI characteristics of the different histological types of the malignant nodule.
Measured: Baseline, Month 3, Month 12
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Feb 2025
- Study start12 Feb 2025
- Primary completionFeb 2029 (estimated)
- Study completionFeb 2029 (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 University Hospital, BordeauxThe 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
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 50 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University Hospital, Bordeaux
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06825078
- Sponsor's protocol ID
- CHUBX 2023/44
- Acronym
- NODU-MR
- Status last verified
- Jul 2026
- First submitted
- 31 Jan 2025
- Last updated
- 9 Jul 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 9 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Performance of Lung MRI Combined to Synthetic CT in the Follow-up of Lung Nodules
- ClinicalTrials.gov ID
- NCT06825078
- Acronym / sponsor ID
- NODU-MR / CHUBX 2023/44
- Conditions
- Lung Cancer
- Keywords
- lung cancer screening, nodule, multiparametric lung MRI, low-dose chest CT, artificial intelligence
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 50 participants (estimated)
- Lead sponsor
- University Hospital, BordeauxUniversity, hospital or other
- Study start
- 12 Feb 2025 (actual)
- Primary completion
- Feb 2029 (estimated)
- Study completion
- Feb 2029 (estimated)
- First posted
- 13 Feb 2025 (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 screening trials using low-dose chest CT scans have shown a significant reduction of cancer related mortality in subjects at high risk of lung cancer. However, high rate of false positives and overdiagnosis have led to invasive methods, which are not without risks. Evaluation of lung nodules using lung MRI with ultra short echo time sequences (UTE) has been found comparable to chest CT scans. Moreover, MRI has the advantage of multiparametric characterization of lesions using different tissue contrasts. Following the recommendation of the French National Authority for Health (HAS) to evaluate new methods of lung cancer screening, this prospective single center pilot study is designed to evaluate the performance of multiparametric lung MRI combined to synthetic CT in the diagnosis of lung cancer in heavily smokers or ex-smokers professionally exposed to carcinogens
Detailed description
Lung cancer is the leading cause of cancer-related deaths worldwide. In France, its incidence was estimated at 46,300 in 2018. In most cases, the diagnosis is initially made by the detection of a nodule or mass on chest X-ray or CT scan. Thus, most often non-invasive follow-up by chest CT scans is recommended. More expensive and invasive methods may also be proposed. However, patients with benign nodules may undergo diagnostic methods that are not without risks (exposure to ionizing radiation, complications related to trans-thoracic or surgical biopsy, etc.).
Lung Cancer Screening Trials (NLST, NELSON) have shown that lung cancer related mortality is reduced in subjects with high risk of lung cancer screened by using low-dose chest CT. Nevertheless, published systematic reviews and meta-analyses report a number of side effects of screening related to false positives and over diagnosis. In addition, the assessment of the risks related to the cumulative dose of exposure to ionising radiation during successive rounds of screening remains unknown. Consequently, the French National Authority for Health (HAS) recommends that pilot programs to be conducted to evaluate the different modalities for the organization of a national lung cancer screening program.
The spatial resolution of magnetic resonance imaging (MRI) of the lung has been significantly improved in the last decade, thanks to the development of ultra-short echo time (UTE) sequences. The advantage of MRI, in addition of being a free-radiation imaging technique, lies in its multiparametric nature with T1-weighted, T2-weighted and diffusion-weighted imaging providing images of different contrasts allowing the characterization of lesions. However, the follow-up of lung nodules, especially with the calculation of the volume doubling time (VDT) on UTE MRI, has not been evaluated. In addition, the performance of multiparametric MRI combining T2 signal, apparent diffusion coefficient (ADC) and nodule volume in determining nodule malignancy remains to be assessed. Recently, the development of artificial intelligence (AI) techniques with generative adversarial networks (GANs) has made it possible to generate CT-like imaging from MRI images. A very recent work demonstrated that AI model is able to generate from UTE lung MRI images, a high resolution synthetic CT image with a very similar texture to the standard CT and better quality than UTE alone. Therefore, the present sudy hypothesis is that multiparametric MRI combined with synthetic CT could have a complementary role with low-dose CT in lung cancer screening to reduce the false positive rate and to perform a free-radiation follow-up of lung nodules
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| multiparametric MRI | Experimental | Device: multiparametric MRIAn MRI scan will be performed within 2 weeks of the discovery of a solid lung nodule ≥ 5mm on the screening scan. When a follow-up scan is indicated, an MRI will be repeated on the same day as the follow-up scan. The MRI sequences that will be performed are: SpiraleVibe UTE, T1map, T2 map and Diffusion. A synthetic scanner image will be generated from the UTE morphological MRI image using a generative artificial intelligence (GAN) model. |
Who may qualify
- Ages
- 55 to 74 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (6 listed)
- Subject aged between 55 and 74 years
- High risk of developing lung cancer: by a combination of exposure to lung carcinogens and smoking (exposure to tobacco at the rate of 30 packs/year or cessation < 15 years)
- Presence of at least one lung solid nodule ≥ 5mm on the initial scan.
- Subject able and willing to complete all scheduled visits and assessments.
- Subject with health insurance.
Key exclusion criteria (10 listed)
- Subject with signs of lung cancer
- Subject with history of lung cancer
- Presence of severe life-threatening comorbidities at 6 months (recent CVA, recent discovery of advanced stage cancer)
- Subject who had already undergone a chest scan less than a year previously
- No exposure to occupational lung carcinogens according to the predefined 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 |
|---|---|---|
| multiparametric MRIAn MRI scan will be performed within 2 weeks of the discovery of a solid lung nodule ≥ 5mm on the screening scan. When a follow-up scan is indicated, an MRI will be repeated on the same day as the follow-up scan. The MRI sequences that will be performed are: SpiraleVibe UTE, T1map, T2 map and Diffusion. A synthetic scanner image will be generated from the UTE morphological MRI image using a generative artificial intelligence (GAN) model. | Device | multiparametric MRI |
Primary outcome
Positivity threshold
Time frame: Baseline, Month 3, Month 12
Positivity threshold of the combined score to obtain a specificity of at least 90%, and diagnostic performance parameters associated with this threshold (sensitivity, positive and negative predictive values).
3 secondary outcomes
Area under the ROC curve
Time frame: Baseline, Month 3, Month 12
Intraclass correlation coefficient between CT and synthetic CT
Time frame: Baseline, Month 3, Month 12
multiparametric MRI characteristics
Time frame: Baseline, Month 3, Month 12
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 9 Jul 2026.
- Individual participant dataSharing planned: No
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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.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing multiparametric MRI in people with Lung Cancer, run by University Hospital, Bordeaux at 1 site in France.
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 6 inclusion and 10 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: looking for participants now, as of the sponsor's last update on 9 Jul 2026. 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 France. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Ilyes Benlala, MD (+335 57 65 65 42, ilyes.ben-lala@chu-bordeaux.fr), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Positivity threshold (time frame: Baseline, Month 3, Month 12). 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 9 Jul 2026.