Bone LesionIATOSNCT06281015
Artificial Intelligence and Bone Tomoscintigraphies Achieved With CZT Camera
An observational study of Bone Lesion, run by Central Hospital, Nancy, France at 1 site in France.
Trial summary
This study aimed to determine whether the whole-body bone Single Photon Emission Computed Tomography (SPECT) recording times of around 10 minutes, routinely provided by a high-sensitivity 360 degrees cadmium and zinc telluride (CZT) camera, can be further reduced by a deep learning noise reduction (DLNR) algorithm. Read more about this study
- Who is it for?
- Ages 18 to 95 years
- Conditions the study is for
- Bone Lesion
- What is being tested?
- Whole-body bone single photon emission tomography (SPECT) for detection or follow-up of bone metastasis
- How many people
- 19 participants
- Where
- 1 siteFrance
- Study dates
- 30 Aug 2023to 30 Oct 2023
- 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 to 95 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Nineteen cancer patients (8 women, 11 men) referred to fast whole-body bone single photon emission tomography for detection or follow-up of bone metastasis were retrospectively included in this study.
Who may be able to join
- patients referred to fast whole-body bone single photon emission tomography for detection or follow-up of bone metastasis
Who cannot join
None listed.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Ultra-Fast Whole-Body Bone Tomoscintigraphies Achieved With a High-Sensitivity 360° CZT Camera and a Dedicated Deep Learning Noise Reduction Algorithm
This study aimed to determine whether the whole-body bone Single Photon Emission Computed Tomography (SPECT) recording times of around 10 minutes, routinely provided by a high-sensitivity 360 degrees cadmium and zinc telluride (CZT) camera, can be further reduced by a deep learning noise reduction (DLNR) algorithm.
Read the detailed description
This study aimed to determine the extent to which fast whole-body bone-SPECT recording times, routinely obtained with a high-sensitivity 360 degrees CZT-camera and rather low injected activities, can be further reduced using the DLNR algorithm.
- Conditions
- Bone Lesion
- Being tested
- Whole-body bone single photon emission tomography (SPECT) for detection or follow-up of bone metastasis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Whole-body bone single photon emission tomography (SPECT) for detection or follow-up of bone metastasisDiagnostic test
Cancer patients referred to fast whole-body bone for detection or follow-up of bone metastasis were retrospectively included in this study.
What is being measured
The primary outcome is the main question the study is designed to answer.
Assess a dedicated deep learning noise reduction algorithm
A deep learning noise reduction algorithm was applied on whole-body images recorded
Measured: one day
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Feb 2024
- Study start30 Aug 2023
- Primary completion10 Sep 2023
- Study completion30 Oct 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Bone LesionStudies 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
- Other
- Time perspective
- Retrospective
- Enrolment
- 19 participants (actual)
Sponsor and investigators
- Lead sponsor
- Central Hospital, Nancy, France
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Achraf BAHLOUL, Central Hospital, Nancy, France
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06281015
- Sponsor's protocol ID
- 2023PI095-407
- Acronym
- IATOS
- Status last verified
- Feb 2024
- First submitted
- 20 Feb 2024
- Last updated
- 28 Feb 2024
- 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 28 Feb 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Ultra-Fast Whole-Body Bone Tomoscintigraphies Achieved With a High-Sensitivity 360° CZT Camera and a Dedicated Deep Learning Noise Reduction Algorithm
- ClinicalTrials.gov ID
- NCT06281015
- Acronym / sponsor ID
- IATOS / 2023PI095-407
- Conditions
- Bone Lesion
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 19 participants (actual)
- Lead sponsor
- Central Hospital, Nancy, FranceUniversity, hospital or other
- Study start
- 30 Aug 2023 (actual)
- Primary completion
- 10 Sep 2023 (actual)
- Study completion
- 30 Oct 2023 (actual)
- First posted
- 28 Feb 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 study aimed to determine whether the whole-body bone Single Photon Emission Computed Tomography (SPECT) recording times of around 10 minutes, routinely provided by a high-sensitivity 360 degrees cadmium and zinc telluride (CZT) camera, can be further reduced by a deep learning noise reduction (DLNR) algorithm.
Detailed description
This study aimed to determine the extent to which fast whole-body bone-SPECT recording times, routinely obtained with a high-sensitivity 360 degrees CZT-camera and rather low injected activities, can be further reduced using the DLNR algorithm.
Study design
- Observational model
- Other
- Time perspective
- Retrospective
Who may qualify
- Ages
- 18 to 95 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Nineteen cancer patients (8 women, 11 men) referred to fast whole-body bone single photon emission tomography for detection or follow-up of bone metastasis were retrospectively included in this study.
Key inclusion criteria (1 listed)
- patients referred to fast whole-body bone single photon emission tomography for detection or follow-up of bone metastasis
Key exclusion criteria (0 listed)
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 |
|---|---|---|
| Whole-body bone single photon emission tomography (SPECT) for detection or follow-up of bone metastasisCancer patients referred to fast whole-body bone for detection or follow-up of bone metastasis were retrospectively included in this study. | Diagnostic test | – |
Primary outcome
Assess a dedicated deep learning noise reduction algorithm
Time frame: one day
A deep learning noise reduction algorithm was applied on whole-body images recorded
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 Feb 2024.
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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.
The record lists no contact. Use the official record to reach the sponsor.
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 Bone Lesion, run by Central Hospital, Nancy, France 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 1 inclusion and 0 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 Feb 2024. 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?
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?
Assess a dedicated deep learning noise reduction algorithm (time frame: one day). 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 Feb 2024.