Clinical trial NCT06831617: AI-based Low Dose CBCT Reconstruction for Clinical Application
Official title: AI-based Low Dose CBCT Reconstruction for Lung Puncture Guidance: A Multicenter Randomized Controlled Study
Study type: INTERVENTIONAL
Overall status: NOT_YET_RECRUITING
Phase: NA
Conditions: Lung Nodule
Keywords: Artificial Intelligence
Lung Nodule
Cone Beam CT
Lung Puncture
Images Reconstruction
Lead sponsor: Wuhan Union Hospital, China
Sponsor class: OTHER
First posted: 2025-02-18
Enrollment: 400
Sex: ALL
Minimum age (years): 18
Maximum age (years): 80
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: PREVENTION

Brief summary: The goal of this clinical trial is to learn if AI-based low dose CBCT reconstructed images can guide lung puncture effectively. The main questions it aims to answer are:

1. Does the AI-based low dose CBCT reconstruction model reconstruct high quality images?
2. Is it possible that low-dose CBCT reconstructed images can guide lung puncture procedures without compromising the efficiency of the procedure? Researchers will compare AI-based low dose CBCT reconstructed images to a placebo (conventional CBCT images) to see if AI-based low dose CBCT reconstructed image can guide lung puncture procedures without compromising the efficiency of the procedure.

Participants will:

1. Undergo lung puncture under AI-based low dose CBCT reconstructed images guidance or under conventional CBCT images
2. Be followed up for 1 week postoperative to obtain patient complications


Eligibility criteria: Inclusion Criteria:

* Participants who require CBCT-guided precutaneous lung puncture (PLP) and meet the clinical indications for the procedure.
* Participants whose physical condition is suitable for PLP.
* Participants are willing to sign informed consent.

Exclusion Criteria:

* Participants have metallic implants in the body, which severely affects the image quality.
* Participants are pregnant or breastfeeding.
* Participants are unwilling or unable to sign informed consent.

Primary outcomes:
measure: Number of puncture needles of participants undergoing percutaneous lung puncture procedures.
timeFrame: From enrollment to the end of the lung puncture procedure.
Secondary outcomes:
measure: Radiation Dose
timeFrame: From enrollment to the end of the lung puncture procedure.
measure: Intraoperative and postoperative complications of participants undergoing lung puncture procedures
timeFrame: From enrollment to the end of the lung puncture procedure at 1 week.
Other outcomes:
measure: Algorithmic performance (peak signal-to-noise ratio)
timeFrame: Through study completion, an average of 9 months.
measure: Algorithmic performance (structural similarity)
timeFrame: Through study completion, an average of 9 months.
Locations:
city: Wuhan
country: China
facility: Wuhan Union Hospital
state: Hubei
city: Wuhan
country: China
facility: Wuhan Union Jinyinhu Hospital
state: Hubei
city: Wuhan
country: China
facility: Wuhan Union West Hospital
state: Hubei
Study officials:
References:
citation: Zhao H, Xu Z, Chen L, Wu L, Cui Z, Ma J, Sun T, Lei Y, Wang N, Hu H, Tan Y, Lu W, Yang W, Liao K, Teng G, Liang X, Li Y, Feng C, Nie T, Han X, Xiang D, Majoie CBLM, van Zwam WH, van der Lugt A, van der Sluijs PM, van Walsum T, Feng Y, Liu G, Huang Y, Liu W, Kan X, Su R, Zhang W, Wang X, Zheng C. Large-scale pretrained frame generative model enables real-time low-dose DSA imaging: An AI system development and multi-center validation study. Med. 2025 Jan 10;6(1):100497. doi: 10.1016/j.medj.2024.07.025. Epub 2024 Aug 19.