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NCT05385718: FasterScan
Ezra Faster Scan Study
trial testing Magnetic Resonance Imaging in Medical Oncology in 694 participants. Completed in 24 February 2025.
24 February 2025
Quick facts
| Lead sponsor | Ezra AI, Inc. |
|---|---|
| Status | Completed |
| Study type | OBSERVATIONAL |
| Enrollment | 694 |
| Start date | 1 June 2022 |
| Primary completion | 24 February 2025 |
| Estimated completion | 24 February 2025 |
| Sites | 5 locations across United States |
Drugs / interventions tested
- Magnetic Resonance Imaging
Conditions studied
- Medical Oncology — all drugs for Medical Oncology →
- Cancer — all drugs for Cancer →
- Healthy — all drugs for Healthy →
Sponsor
Ezra AI, Inc.
Who can join
18 and older, any sex, with Medical Oncology or Cancer. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
The Ezra Faster Scan study uses non-invasive magnetic resonance imaging (MRI) technology that can "visually" detect early and late-stage cancer, and other pathologies. MRIs use a magnetic field and radio waves to create a 3-dimensional (3D) image of an individual's body without using ionizing radiation. The purpose of this research is to decrease the amount of time required by an individual to complete an early cancer screening comprehensive magnetic resonance imaging (MRI) scan, such as the Ezra Full Body MRI imaging scan. If the time required to conduct a comprehensive scan is reduced, the cost of the scan may also decrease. By decreasing consumer costs and time, more individuals may be able to afford MRI-based early cancer screening technology. Participants in this study will undergo a minimum 30-minute MRI session. These sessions will be used to evaluate new MRI "instructions" that allow for a faster MRI scan time. The images will also be used to develop mathematical models or machine learning tools that allow images to be enhanced. By enhancing images using machine learning, they may be restored to a quality typically observed in MRI sessions with longer scan (acquisition) times. To read more about the study, potential participants may review the informed consent form located below in the References section. Potential participants may email research.fasterscan@ezra.com, or call 516.340.1221. See study Eligibility Criteria below.
Publications & conference data
2 peer-reviewed publications reference this trial (live from Europe PMC):
-
Artificial Intelligence in Oncology: A 10-Year ClinicalTrials.gov-Based Analysis Across the Cancer Control Continuum.
Verma H, Mistry S, Jayam KV, Shrestha P, et al · · 2025 · PMID 41228330 · DOI 10.3390/cancers17213537 -
An image-domain deep-learning denoising technique for accelerated parallel brain MRI: prospective clinical evaluation.
Onac L, Dobai L, Mouraviev A, Badila MA, et al · · 2024 · PMID 41058863 · DOI 10.1093/radadv/umae022
Verify or expand the search:
- PubMed search for NCT05385718
- Europe PMC full search
- ASCO Meeting Library
- ESMO Meeting Library
- bioRxiv preprints
- medRxiv preprints
- Google Scholar
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Other recruiting trials for Medical Oncology
Currently open trials in the same condition.
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Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT05385718 (US National Library of Medicine, public domain)
- Publications: Europe PMC API search by NCT ID, retrieved 10 June 2026
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by Ezra AI, Inc.
- Last refreshed: 3 March 2025
Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT05385718.
Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing