High Risk CancerRELIVENCT06751576
Retrospective Clinical Trial Comparing Radiologists' Diagnosis Accuracy in Lung Cancer Screening Population With and Without the Help of an AI/ML Tech-based SaMD
An observational study of High Risk Cancer and Lung Cancer, run by Median Technologies at 5 sites in 2 countries.
Trial summary
This is a two arm, randomized, controlled, blinded, multi-case multi reader (MRMC), retrospective study for the evaluation of the efficacy and safety of an AI/ML technology-based CADe/x developed to detect, localize and characterize malignancy score of pulmonary nodules on LDCT chest scans taken as part of a lung… Read more about this study
- Who is it for?
- Ages 50 to 80 yearsHealthy volunteers can take part
- Conditions the study is for
- High Risk Cancer, Lung Cancer
- What is being tested?
- Median LCS
- Type of treatment
- Medical device
- How many people
- 480 participants
- Where
- 5 sitesin 2 countries
- Study dates
- 21 Sep 2022to 12 Mar 2025
- 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 50 to 80 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: High risk lung cancer population from Radiology or Pneumology hospital departments. Patients enrolled in this study were retrospectively collected from centers across the EU and USA where they were enlisted into lung cancer screening due to high risk of lung cancer according to established lung cancer screening guidelines. The cohort used for testing the efficacy and safety of the device will be an "enriched cohort" with a 1:2 distribution of cancer positive and benign patients
Who may be able to join
- ≥50-80 Years of age;
- Current or ex-smoker (>=20 pack years);
- Patient screened and surveilled for lung cancer screening following lung cancer screening guidelines (equivalent to United States Preventive Services Task Force (USPSTF) 2021 Criteria);
- Received LDCT due to inclusion in high-risk category for lung cancer.
Who cannot join
- Prior lung resection;
- Pacemaker or other indwelling metallic medical devices in the thorax that interfere with CT acquisition;
- Patients/images used during AI model development;
- Patients with only hilar and/or mediastinal cancer(s);
- Patients with only ground glass cancer(s);
- Patients with nodules, solid or part-solid >30mm (masses);
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- Patients that are not accompanied with the required clinical information;
- Patients with imaging with any of the following: missing slices, slice thickness >3mm;
- Partial cover of the lung.
Trial locations and contacts
5 sites in 2 countries.
5 sites in 2 countries
United States3 sites
The University of Texas M.D. Anderson Cancer Center
Houston, Texas, 77030
Baptist Clinical Research Institute
Memphis, Tennessee, 38120
University of Pennsylvania - Penn Center for Innovation
Philadelphia, Pennsylvania, 19104
Spain2 sites
Fundacion instituto de investigacion sanitaria de la fundacion jimenez diaz (FJD)
Madrid, 28040
Universidad de Navarra
Pamplona, 31009
About this study
Official title: A Multi-Reader Multi-Case Controlled Clinical Trial to Evaluate the Comparative Accuracy Of Readers Assisted By an AI/ML Technology-Based End-To-End CADe/CADx SaMD Versus Alone in the Detection, Localization and Characterization of Pulmonary Nodules in Populations With High Risk of Lung Cancer (RELIVE)
This is a two arm, randomized, controlled, blinded, multi-case multi reader (MRMC), retrospective study for the evaluation of the efficacy and safety of an AI/ML technology-based CADe/x developed to detect, localize and characterize malignancy score of pulmonary nodules on LDCT chest scans taken as part of a lung cancer screening program.
LDCT DICOM images of patients who underwent routine lung cancer screening will be selected and enrolled into the study. Enrolled scans analyzed by radiologists with the assistance of the Median LCS (formerly iBiopsy) device are compared to the analysis by radiologists without the assistance of the Median LCS device.
Figures of merit for patient level and lesion level detection and diagnostic efficacy will be calculated and compared, sub-class analysis will be performed to ensure device generalizability.
- Conditions
- High Risk Cancer, Lung Cancer
- Being tested
- Median LCS
- Medical subject headings
- Lung Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Median LCSDevice
Also called eyonis LCS
End-to-end processing of chest LDCT DICOM images by an AI/ML tech-based SaMD to detect, localize, and characterize (assign a malignancy score) each detected pulmonary nodule. The output of the device is a DICOM File (Median LCS result report) summarizing results per patient.
| Study group | Role | What they receive |
|---|---|---|
| Control arm | low-dose CT scan image readings performed by radiologists without the assistance of Median LCS | |
| Test arm | low-dose CT scan image readings performed by radiologists with the assistance of Median LCS. Receives: Device: Median LCS |
What is being measured
The primary outcome is the main question the study is designed to answer.
∆ AUC of ROCs > 0. Delta Area between the Response operating curve (AUROC) value with Median LCS and AUROC without Median LCS at patient level data is superior to 0.
Demonstrate that patient diagnosis with Median LCS is improved compared to without Median LCS.
Measured: 12 months
Secondary outcomes (6)
Sensitivity at max Youden
Demonstrate that Median LCS aided sensitivity is non inferior (H2) , superior (H8) to radiologist alone.
(Sensitivity with Median LCS-Patient) non inferior using non-inferiority margin delta = 0.1 to (Sensitivity Control Arm-Patient).
First, non-inferiority. If passed, superiority will be performed.
Measured: 12 months
Specificity at max Youden
Demonstrate that Median LCS assisted specificity is not inferior (H3), superior (H9) to radiologist alone.
(Sensitivity with Median LCS-Patient) non inferior using non-inferiority margin delta = 0.1 to (Sensitivity Control Arm-Patient).
First, non-inferiority. If passed, superiority will be performed.
Measured: 12 months
∆ AUC of LROC > 0
Demonstrate that Median LCS improves clinician's performance in finding detection and diagnosis.
Measured: 12 months
Recall rates for non-cancer patients (Specificity)
Demonstrate that Median LCS aids to rule out non-cancer patients compared to radiologist alone.
"Non-Cancer-Recall-Rate will be calculated and compared between the two modalities using margin of 10%". First, non-inferiority. If passed, superiority will be performed.
Measured: 12 months
Recall rates for cancer patients (Sensitivity)
Demonstrate that Median LCS aid to diagnose cancer patients compared to radiologist alone.
"Cancer-Recall-Rate will be calculated and compared between the two modalities using margin of 10%". First, non-inferiority. If passed, superiority will be performed.
Measured: 12 months
Time analysis
Demonstrate that Median LCS decreases the time of analysis per patient.
Measured: 12 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted30 Dec 2024
- Study start21 Sep 2022
- Primary completion31 Jan 2025
- Study completion12 Mar 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for High Risk CancerStudies of the same condition, open and under way.
- 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
- 480 participants (actual)
Sponsor and investigators
- Lead sponsor
- Median Technologies
- Sponsor type
- Industry (pharma, biotech, devices)
- Responsible party
- Sponsor
- Investigators
- Anil VACHANI, MD, Principal investigator, University of Pennsylvania
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06751576
- Sponsor's protocol ID
- MT-LCS-004
- Acronym
- RELIVE
- Status last verified
- May 2025
- First submitted
- 20 Dec 2024
- Last updated
- 6 May 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
Study at a glance
From the registry record, last updated by the sponsor on 6 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Multi-Reader Multi-Case Controlled Clinical Trial to Evaluate the Comparative Accuracy Of Readers Assisted By an AI/ML Technology-Based End-To-End CADe/CADx SaMD Versus Alone in the Detection, Localization and Characterization of Pulmonary Nodules in Populations With High Risk of Lung Cancer (RELIVE)
- ClinicalTrials.gov ID
- NCT06751576
- Acronym / sponsor ID
- RELIVE / MT-LCS-004
- Conditions
- High Risk Cancer, Lung Cancer
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 480 participants (actual)
- Lead sponsor
- Median TechnologiesIndustry (pharma, biotech, devices)
- Study start
- 21 Sep 2022 (actual)
- Primary completion
- 31 Jan 2025 (actual)
- Study completion
- 12 Mar 2025 (actual)
- First posted
- 30 Dec 2024 (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.
This is a two arm, randomized, controlled, blinded, multi-case multi reader (MRMC), retrospective study for the evaluation of the efficacy and safety of an AI/ML technology-based CADe/x developed to detect, localize and characterize malignancy score of pulmonary nodules on LDCT chest scans taken as part of a lung cancer screening program.
LDCT DICOM images of patients who underwent routine lung cancer screening will be selected and enrolled into the study. Enrolled scans analyzed by radiologists with the assistance of the Median LCS (formerly iBiopsy) device are compared to the analysis by radiologists without the assistance of the Median LCS device.
Figures of merit for patient level and lesion level detection and diagnostic efficacy will be calculated and compared, sub-class analysis will be performed to ensure device generalizability.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Control arm | – | –low-dose CT scan image readings performed by radiologists without the assistance of Median LCS |
| Test arm | – | Device: Median LCSlow-dose CT scan image readings performed by radiologists with the assistance of Median LCS. |
Who may qualify
- Ages
- 50 to 80 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- High risk lung cancer population from Radiology or Pneumology hospital departments. Patients enrolled in this study were retrospectively collected from centers across the EU and USA where they were enlisted into lung cancer screening due to high risk of lung cancer according to established lung cancer screening guidelines. The cohort used for testing the efficacy and safety of the device will be an "enriched cohort" with a 1:2 distribution of cancer positive and benign patients
Key inclusion criteria (4 listed)
- ≥50-80 Years of age;
- Current or ex-smoker (>=20 pack years);
- Patient screened and surveilled for lung cancer screening following lung cancer screening guidelines (equivalent to United States Preventive Services Task Force (USPSTF) 2021 Criteria);
- Received LDCT due to inclusion in high-risk category for lung cancer.
Key exclusion criteria (9 listed)
- Prior lung resection;
- Pacemaker or other indwelling metallic medical devices in the thorax that interfere with CT acquisition;
- Patients/images used during AI model development;
- Patients with only hilar and/or mediastinal cancer(s);
- Patients with only ground glass cancer(s);
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 |
|---|---|---|
| Median LCSAlso: eyonis LCSEnd-to-end processing of chest LDCT DICOM images by an AI/ML tech-based SaMD to detect, localize, and characterize (assign a malignancy score) each detected pulmonary nodule. The output of the device is a DICOM File (Median LCS result report) summarizing results per patient. | Device | Test arm |
Primary outcome
∆ AUC of ROCs > 0. Delta Area between the Response operating curve (AUROC) value with Median LCS and AUROC without Median LCS at patient level data is superior to 0.
Time frame: 12 months
Demonstrate that patient diagnosis with Median LCS is improved compared to without Median LCS.
6 secondary outcomes
Sensitivity at max Youden
Time frame: 12 months
Specificity at max Youden
Time frame: 12 months
∆ AUC of LROC > 0
Time frame: 12 months
Recall rates for non-cancer patients (Specificity)
Time frame: 12 months
Recall rates for cancer patients (Sensitivity)
Time frame: 12 months
Time analysis
Time frame: 12 months
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 May 2025.
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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.
Anil VACHANI, MD principal investigator
University of Pennsylvania
5 sites in 2 countries: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of High Risk Cancer and Lung Cancer, run by Median Technologies at 5 sites in 2 countries.
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 4 inclusion and 9 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: finished, as of the sponsor's last update on 6 May 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 5 sites in United States, Spain. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
∆ AUC of ROCs > 0. Delta Area between the Response operating curve (AUROC) value with Median LCS and AUROC without Median LCS at patient level data is superior to 0. (time frame: 12 months). 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 6 May 2025.