High Risk CancerREALITYNCT06576232
Standalone Observational Study Assessing the Performance of an AI/ML Tech-based SaMD on Chest LDCT Images (REALITY)
An observational study of High Risk Cancer, run by Median Technologies at 5 sites in 2 countries.
Trial summary
This is a Multinational, Multicenter, retrospective study for the evaluation of the standalone efficacy and safety of an Artificial Intelligence/Machine Learning (AI/ML) technology-based end-to-end Computer assisted Detection/Computer Assisted Diagnosis (CADe/CADx) Software as a Medical Device (SaMD) developed to… 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
- What is being tested?
- Median LCS
- Type of treatment
- Medical device
- How many people
- 1,147 participants
- Where
- 5 sitesin 2 countries
- Study dates
- 21 Sep 2022to 21 Aug 2024
- 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);
Show all 9Show fewer
- 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: Multinational, Multicenter, Retrospective Study to Evaluate an AI/ML Technology-Based End-to-End CADe/CADx SaMD, Which Allows Detection, Localization and Characterization of Pulmonary Nodules (REALITY)
This is a Multinational, Multicenter, retrospective study for the evaluation of the standalone efficacy and safety of an Artificial Intelligence/Machine Learning (AI/ML) technology-based end-to-end Computer assisted Detection/Computer Assisted Diagnosis (CADe/CADx) Software as a Medical Device (SaMD) developed to detect, localize and characterize malignant, and suspicious for lung cancer nodules on Low Dose Computed Tomography (LDCT) scans taken as part of a Lung Cancer Screening (LCS) program.
LDCT Digital Imaging and Communications in Medicine (DICOM) images of patients who underwent lung cancer screening were selected and included into the study. Selected scans will then be analyzed by the CADe/CADx SaMD and compared to radiologist generated reference standards including lesions localization and lesion cancer diagnosis.
Figures of merit at patient level and lesion level detection and diagnostic efficacy will be calculated as well as sub-class analysis to ensure algorithm performance generalizability.
- Conditions
- High Risk Cancer
- Being tested
- Median LCS
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.
What is being measured
The primary outcome is the main question the study is designed to answer.
AUROC (Area under ROC curve) at patient level
AUROC that measures Median LCS performance at patient level is strictly superior to 0.8.
Support for Primary Endpoint: Derived from the patient level AUROC at the product fixed operating point : Sensitivity, Specificity, PPV, NPV.
Measured: 12 months
Secondary outcomes (9)
Sensitivity > 70% when Specificity=70%
Measured: 12 months
Specificity > 70% when Sensitivity=70%
Measured: 12 months
AUC of LROC > 0.75
In contrast to the receiver operating characteristic (ROC) assessment paradigm, localization ROC (LROC) analysis provides a means to jointly assess the accuracy of localization and detection in an observational study.
Measured: 12 months
Detection sensitivity>0.8 with average FP rate per scan<1
Measured: 12 months
ICC>0.8 for average diameter
Intraclass Correlation Coefficient (ICC), is a descriptive statistic that can be used when quantitative measurements are made on units that are organized into groups. It describes how strongly units in the same group resemble each other.
Measured: 12 months
ICC>0.8 for long axis diameter
Measured: 12 months
ICC>0.8 for short axis diameter
Measured: 12 months
ICC>0.75 for Volume
Measured: 12 months
DICE Coefficient >0.7
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 posted28 Aug 2024
- Study start21 Sep 2022
- Primary completion24 Jul 2024
- Study completion21 Aug 2024
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
- 1,147 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
- NCT06576232
- Sponsor's protocol ID
- MT-LCS-002
- Acronym
- REALITY
- Status last verified
- Aug 2024
- First submitted
- 23 Aug 2024
- Last updated
- 28 Aug 2024
- 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 28 Aug 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Multinational, Multicenter, Retrospective Study to Evaluate an AI/ML Technology-Based End-to-End CADe/CADx SaMD, Which Allows Detection, Localization and Characterization of Pulmonary Nodules (REALITY)
- ClinicalTrials.gov ID
- NCT06576232
- Acronym / sponsor ID
- REALITY / MT-LCS-002
- Conditions
- High Risk Cancer
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 1,147 participants (actual)
- Lead sponsor
- Median TechnologiesIndustry (pharma, biotech, devices)
- Study start
- 21 Sep 2022 (actual)
- Primary completion
- 24 Jul 2024 (actual)
- Study completion
- 21 Aug 2024 (actual)
- First posted
- 28 Aug 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 Multinational, Multicenter, retrospective study for the evaluation of the standalone efficacy and safety of an Artificial Intelligence/Machine Learning (AI/ML) technology-based end-to-end Computer assisted Detection/Computer Assisted Diagnosis (CADe/CADx) Software as a Medical Device (SaMD) developed to detect, localize and characterize malignant, and suspicious for lung cancer nodules on Low Dose Computed Tomography (LDCT) scans taken as part of a Lung Cancer Screening (LCS) program.
LDCT Digital Imaging and Communications in Medicine (DICOM) images of patients who underwent lung cancer screening were selected and included into the study. Selected scans will then be analyzed by the CADe/CADx SaMD and compared to radiologist generated reference standards including lesions localization and lesion cancer diagnosis.
Figures of merit at patient level and lesion level detection and diagnostic efficacy will be calculated as well as sub-class analysis to ensure algorithm performance generalizability.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
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 | – |
Primary outcome
AUROC (Area under ROC curve) at patient level
Time frame: 12 months
AUROC that measures Median LCS performance at patient level is strictly superior to 0.8. Support for Primary Endpoint: Derived from the patient level AUROC at the product fixed operating point : Sensitivity, Specificity, PPV, NPV.
9 secondary outcomes
Sensitivity > 70% when Specificity=70%
Time frame: 12 months
Specificity > 70% when Sensitivity=70%
Time frame: 12 months
AUC of LROC > 0.75
Time frame: 12 months
Detection sensitivity>0.8 with average FP rate per scan<1
Time frame: 12 months
ICC>0.8 for average diameter
Time frame: 12 months
ICC>0.8 for long axis diameter
Time frame: 12 months
ICC>0.8 for short axis diameter
Time frame: 12 months
ICC>0.75 for Volume
Time frame: 12 months
DICE Coefficient >0.7
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 28 Aug 2024.
Related trials for High Risk Cancer
Active, not recruitingPhase 1/2
A Beta-only IL-2 ImmunoTherapY Study
Advanced Solid Tumor, Unresectable Solid Tumor
RecruitingPhase 3
A Clinical Trial of Adjuvant Intismeran (V940) With or Without Pembrolizumab Coformulated With Berahyaluronidase Alfa (MK-3475A) in High-Risk Stage I Non-Small Cell Lung Cancer (V940-014)
Non-small Cell Lung Cancer
Active, not recruitingPhase 1/2
Tafasitamab, Retifanlimab, and Rituximab in Combination With Standard Therapy for the Treatment of Diffuse Large B-cell Lymphoma
Diffuse Large B-Cell Lymphoma, Grade 3b Follicular Lymphoma
RecruitingPhase 2
Relugolix and Enzalutamide in Combination With Radiation Therapy for the Treatment of Very High Risk Prostate Cancer, OPTIMAL Trial
Prostate Adenocarcinoma
Active, not recruitingPhase 2
Olaparib in Men With High-Risk Biochemically-Recurrent Prostate Cancer Following Radical Prostatectomy, With Integrated Biomarker Analysis
Prostate
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, 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 28 Aug 2024. 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?
AUROC (Area under ROC curve) at patient level (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 28 Aug 2024.