AI-Assisted Chest CT Interpretation Across the Lung Cancer Care Continuum
Development of a Chest CT-Based Artificial Intelligence Model Across the Lung Cancer Care Continuum and a Prospective Randomized Crossover Reader Study of Its Clinical Decision-Support Performance
This investigator-initiated, single-center study consists of a retrospective artificial intelligence model-development stage and a prospective physician reader-study stage. Deidentified chest CT examinations acquired during routine clinical care between January 1, 2021, and December 31, 2024, will be used to develop, validate, and lock artificial intelligence models for lung cancer-related imaging tasks.
In the prospective stage, approximately 12 to 15 physicians with experience in chest CT interpretation will complete two reading sessions in randomized order: unaided interpretation and AI-assisted interpretation. The sessions will be separated by a washout period of at least 4 weeks. The primary objective is to compare diagnostic performance between AI-assisted and unaided interpretation. Secondary objectives include reading time, diagnostic confidence, inter-reader agreement, and errors related to incorrect AI suggestions.
All readings will be performed in an offline research environment. AI outputs will not be used for patient care, and the study will not add imaging examinations, treatment, or follow-up for patients.
Studieoversikt
Status
Forhold
Intervensjon / Behandling
Studietype
Registrering (Antatt)
Fase
- Ikke aktuelt
Kontakter og plasseringer
Studiekontakt
- Navn: Lian Yang, PhD
- Telefonnummer: +86 18986273791
- E-post: yanglian@hust.edu.cn
Studiesteder
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Hubei
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Wuhan, Hubei, Kina, 430022
- Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
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Ta kontakt med:
- Lian Yang, PhD
- Telefonnummer: +86 18986273791
- E-post: yanglian@hust.edu.cn
-
-
Deltakelseskriterier
Kvalifikasjonskriterier
Alder som er kvalifisert for studier
Tar imot friske frivillige
Kjønn som er kvalifisert for studier
Beskrivelse
Inclusion Criteria:
- Physicians with education or training relevant to medical imaging
- Experience in interpreting chest CT examinations
- Ability to complete the required study training and both reading sessions
- Willingness to provide written informed consent and comply with study procedures
Exclusion Criteria:
- Failure to complete the required study training
- Inability or unwillingness to complete both reading sessions as required
- Any protocol deviation likely to compromise the validity of the reader-study data
Studieplan
Hvordan er studiet utformet?
Designdetaljer
- Primært formål: Diagnostisk
- Tildeling: Randomisert
- Intervensjonsmodell: Crossover-oppdrag
- Masking: Ingen (Open Label)
Våpen og intervensjoner
Deltakergruppe / Arm |
Intervensjon / Behandling |
|---|---|
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Eksperimentell: Sequence AB: Unaided Then AI-Assisted Interpretation
Participants first complete an unaided chest CT interpretation session. After a washout period of at least 4 weeks, they complete an AI-assisted interpretation session. |
A locked research-use-only artificial intelligence system analyzes deidentified chest CT images and provides decision-support outputs to participating physicians. The system is evaluated only in an offline reader-study environment and is not used for actual patient care. |
|
Eksperimentell: Sequence BA: AI-Assisted Then Unaided Interpretation
Participants first complete an AI-assisted chest CT interpretation session. After a washout period of at least 4 weeks, they complete an unaided interpretation session. |
A locked research-use-only artificial intelligence system analyzes deidentified chest CT images and provides decision-support outputs to participating physicians. The system is evaluated only in an offline reader-study environment and is not used for actual patient care. |
Hva måler studien?
Primære resultatmål
Resultatmål |
Tiltaksbeskrivelse |
Tidsramme |
|---|---|---|
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Difference in Diagnostic Accuracy Between AI-Assisted and Unaided Chest CT Interpretation
Tidsramme: At completion of the second reading session, after a washout period of at least 4 weeks
|
Diagnostic accuracy will be calculated as the proportion of case-level interpretations that agree with the prespecified reference standard based on pathology or clinical follow-up. The paired difference in diagnostic accuracy between AI-assisted and unaided interpretation will be estimated across participating physicians and cases using a multi-reader multi-case analysis and reported with a 95% confidence interval. Higher accuracy indicates better diagnostic performance. |
At completion of the second reading session, after a washout period of at least 4 weeks
|
Samarbeidspartnere og etterforskere
Studierekorddatoer
Studer hoveddatoer
Studiestart (Antatt)
Primær fullføring (Antatt)
Studiet fullført (Antatt)
Datoer for studieregistrering
Først innsendt
Først innsendt som oppfylte QC-kriteriene
Først lagt ut (Faktiske)
Oppdateringer av studieposter
Sist oppdatering lagt ut (Faktiske)
Siste oppdatering sendt inn som oppfylte QC-kriteriene
Sist bekreftet
Mer informasjon
Begreper knyttet til denne studien
Nøkkelord
Ytterligere relevante MeSH-vilkår
Andre studie-ID-numre
- Radio-20260816
Plan for individuelle deltakerdata (IPD)
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