NCT07741058

Brief Summary

This study will evaluate whether artificial intelligence (AI) can enhance clinicians' accuracy, efficiency, and confidence in distinguishing lung adenocarcinoma (LUAD) from lung squamous cell carcinoma (LUSC) and kidney renal papillary cell carcinoma (KIRP) from kidney renal clear cell carcinoma (KIRC) using digitized pathology slides. These subtype classifications are routinely performed by pathologists but can be challenging and time-consuming, particularly in difficult cases. During the study, participating clinicians will review lung and kidney pathology slides under three different conditions:

  • Unaided Review: Diagnosis without AI assistance.
  • AI as Double-Check: The clinician first makes an independent diagnosis, after which the AI-generated diagnosis (prediction only or prediction with explanation) is revealed for review.
  • AI as First-Look: The AI-generated diagnosis (prediction only or prediction with explanation) is presented before the clinician begins the review. Clinicians will be randomly assigned to different review sequences to minimize potential order effects. This study design will enable us to assess the impact of AI assistance on diagnostic accuracy, interpretation time, and clinician confidence.

Trial Health

55
Monitor

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
25

participants targeted

Target at below P25 for not_applicable cancer

Timeline
Completed

Started Jul 2026

Shorter than P25 for not_applicable cancer

Geographic Reach
1 country

1 active site

Status
enrolling by invitation

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

July 1, 2026

Completed
27 days until next milestone

First Submitted

Initial submission to the registry

July 28, 2026

Completed
4 days until next milestone

Primary Completion

Last participant's last visit for primary outcome

August 1, 2026

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

August 1, 2026

Completed
2 days until next milestone

First Posted

Study publicly available on registry

August 3, 2026

Completed
Last Updated

August 3, 2026

Status Verified

July 1, 2026

Enrollment Period

1 month

First QC Date

July 28, 2026

Last Update Submit

July 28, 2026

Conditions

Cancer

Keywords

AI-Augmented DiagnosisMultimodal AIExplainable AICancer DiagnosisCancer SubtypingWhole-Slide Imaging

Outcome Measures

Primary Outcomes (1)

  • Diagnostic performance of cancers

    Performance of clinicians (unaided and AI-assisted) for distinguishing LUAD- LUSC and distinguishing KIRP-KIRC, measured in accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1.

    Periprocedural (at the time of slide review)

Secondary Outcomes (4)

  • Time to diagnosis

    Periprocedural (at the time of slide review)

  • Inter-observer variability

    Periprocedural (at the time of slide review)

  • Net benefit after AI exposure

    Periprocedural (at the time of slide review)

  • Clinician confidence level

    Periprocedural (at the time of slide review)

Study Arms (4)

Unaided Review First, Then AI as Double-Check, Then AI as First-Look.

ACTIVE COMPARATOR

Readers first complete Block X (Unaided) on their assigned subset SX. They then complete Block Y1 (AI as Double-Check) on two separate subsets: SY1a (AI prediction-only as Double-Check) and SY1b (AI prediction-with-explanation as Double-Check). Within Block Y1, the order of SY1a and SY1b is randomized. They then complete Block Y2 (AI as First-Look) on two separate subsets: SY2a (AI prediction-only as First-Look) and SY2b (AI prediction-with-explanation as First-Look). Within Block Y2, the order of SY2a and SY2b is randomized. For each reader, each of the five subsets (SX, SY1a, SY1b, SY2a, and SY2b) comprises up to 80 slides: up to 40 slides from LUAD-LUSC and up to 40 slides from KIRP-KIRC.

Behavioral: Unaided Review First, Then AI as Double-Check, Then AI as First-Look.

Unaided Review First, Then AI as First-Look, Then AI as Double-Check.

ACTIVE COMPARATOR

Readers first complete Block X (Unaided) on their assigned subset SX. They then complete Block Y2 (AI as First-Look) on two separate subsets: SY2a (AI prediction-only as First-Look) and SY2b (AI prediction-with-explanation as First-Look). Within Block Y2, the order of SY2a and SY2b is randomized. They then complete Block Y1 (AI as Double-Check) on two separate subsets: SY1a (AI prediction-only as Double-Check) and SY1b (AI prediction-with-explanation as Double-Check). Within Block Y1, the order of SY1a and SY1b is randomized. For each reader, each of the five subsets (SX, SY1a, SY1b, SY2a, and SY2b) comprises up to 80 slides: up to 40 slides from LUAD-LUSC and up to 40 slides from KIRP-KIRC.

Behavioral: Unaided Review First, Then AI as First-Look, Then AI as Double-Check.

AI as Double-Check Review First, Then AI as First-Look, Then Unaided Review.

ACTIVE COMPARATOR

Readers first complete Block Y1 (AI as Double-Check) on two separate subsets: SY1a (AI prediction-only as Double-Check) and SY1b (AI prediction-with-explanation as Double-Check). Within Block Y1, the order of SY1a and SY1b is randomized. They then complete Block Y2 (AI as First-Look) on two separate subsets: SY2a (AI prediction-only as First-Look) and SY2b (AI prediction-with-explanation as First-Look). Within Block Y2, the order of SY2a and SY2b is randomized. Then readers complete Block X (Unaided) on their assigned subset SX. For each reader, each of the five subsets (SX, SY1a, SY1b, SY2a, and SY2b) comprises up to 80 slides: up to 40 slides from LUAD-LUSC and up to 40 slides from KIRP-KIRC.

Behavioral: AI as Double-Check First, Then AI as First-Look, Then Unaided Review.

AI as First-Look Review First, Then AI as Double-Check, Then Unaided Review.

ACTIVE COMPARATOR

Readers first complete Block Y2 (AI as First-Look) on two separate subsets: SY2a (AI prediction-only as First-Look) and SY2b (AI prediction-with-explanation as First-Look). Within Block Y2, the order of SY2a and SY2b is randomized. They then complete Block Y1 (AI as Double-Check) on two separate subsets: SY1a (AI prediction-only as Double-Check) and SY1b (AI prediction-with-explanation as Double-Check). Within Block Y1, the order of SY1a and SY1b is randomized. Then readers complete Block X (Unaided) on their assigned subset SX. For each reader, each of the five subsets (SX, SY1a, SY1b, SY2a, and SY2b) comprises up to 80 slides: up to 40 slides from LUAD-LUSC and up to 40 slides from KIRP-KIRC.

Behavioral: AI as First-Look First, Then AI as Double-Check, Then Unaided Review.

Interventions

Unaided Review First, Then AI as Double-Check, Then AI as First-Look.BEHAVIORAL

Readers first complete Block X (Unaided) on their assigned subset SX. They then complete Block Y1 (AI as Double-Check) on two separate subsets: SY1a (AI prediction-only as Double-Check) and SY1b (AI prediction-with-explanation as Double-Check). Within Block Y1, the order of SY1a and SY1b is randomized. They then complete Block Y2 (AI as First-Look) on two separate subsets: SY2a (AI prediction-only as First-Look) and SY2b (AI prediction-with-explanation as First-Look). Within Block Y2, the order of SY2a and SY2b is randomized. For each reader, SX, SY1a, SY1b, SY2a, and SY2b are disjoint.

Unaided Review First, Then AI as Double-Check, Then AI as First-Look.
Unaided Review First, Then AI as First-Look, Then AI as Double-Check.BEHAVIORAL

Readers first complete Block X (Unaided) on their assigned subset SX. They then complete Block Y2 (AI as First-Look) on two separate subsets: SY2a (AI prediction-only as First-Look) and SY2b (AI prediction-with-explanation as First-Look). Within Block Y2, the order of SY2a and SY2b is randomized. They then complete Block Y1 (AI as Double-Check) on two separate subsets: SY1a (AI prediction-only as Double-Check) and SY1b (AI prediction-with-explanation as Double-Check). Within Block Y1, the order of SY1a and SY1b is randomized. For each reader, SX, SY1a, SY1b, SY2a, and SY2b are disjoint.

Unaided Review First, Then AI as First-Look, Then AI as Double-Check.
AI as Double-Check First, Then AI as First-Look, Then Unaided Review.BEHAVIORAL

Readers first complete Block Y1 (AI as Double-Check) on two separate subsets: SY1a (AI prediction-only as Double-Check) and SY1b (AI prediction-with-explanation as Double-Check). Within Block Y1, the order of SY1a and SY1b is randomized. They then complete Block Y2 (AI as First-Look) on two separate subsets: SY2a (AI prediction-only as First-Look) and SY2b (AI prediction-with-explanation as First-Look). Within Block Y2, the order of SY2a and SY2b is randomized. Then readers complete Block X (Unaided) on their assigned subset SX. For each reader, SX, SY1a, SY1b, SY2a, and SY2b are disjoint.

AI as Double-Check Review First, Then AI as First-Look, Then Unaided Review.
AI as First-Look First, Then AI as Double-Check, Then Unaided Review.BEHAVIORAL

Readers first complete Block Y2 (AI as First-Look) on two separate subsets: SY2a (AI prediction-only as First-Look) and SY2b (AI prediction-with-explanation as First-Look). Within Block Y2, the order of SY2a and SY2b is randomized. They then complete Block Y1 (AI as Double-Check) on two separate subsets: SY1a (AI prediction-only as Double-Check) and SY1b (AI prediction-with-explanation as Double-Check). Within Block Y1, the order of SY1a and SY1b is randomized. Then readers complete Block X (Unaided) on their assigned subset SX. For each reader, SX, SY1a, SY1b, SY2a, and SY2b are disjoint.

AI as First-Look Review First, Then AI as Double-Check, Then Unaided Review.

Eligibility Criteria

Sexall
Healthy VolunteersNo
Age GroupsChild (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

  • Hematoxylin and eosin (H\&E)-stained pathology slides
  • Final diagnosis confirmed through molecular testing in conjunction with expert pathology evaluation

You may not qualify if:

  • Poor-quality or unreadable slides
  • Cases used in AI training
  • Board-certified or board-eligible pathologists
  • Willingness to complete both unaided and AI-assisted review sessions

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Harvard Medical School,

Boston, Massachusetts, 02115, United States

Location

MeSH Terms

Conditions

Neoplasms

Interventions

Nonoxynol

Intervention Hierarchy (Ancestors)

Polyethylene GlycolsEthylene GlycolsGlycolsAlcoholsOrganic ChemicalsPolymersMacromolecular SubstancesBiomedical and Dental MaterialsManufactured MaterialsTechnology, Industry, and Agriculture

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
QUADRUPLE
Who Masked
PARTICIPANT, CARE PROVIDER, INVESTIGATOR, OUTCOMES ASSESSOR
Purpose
DIAGNOSTIC
Intervention Model
CROSSOVER
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Associate Professor

Study Record Dates

First Submitted

July 28, 2026

First Posted

August 3, 2026

Study Start

July 1, 2026

Primary Completion

August 1, 2026

Study Completion

August 1, 2026

Last Updated

August 3, 2026

Record last verified: 2026-07

Data Sharing

IPD Sharing
Will not share

Locations

US(1)