Application of DCE-MRI Based on 4D FreeBreathing in Predicting the Efficacy of Immune and Targeted Therapy in Lung Cancer

Yunnan Cancer Hospital

Status: Enrolling

Conditions: Lung Cancer

Treatments: Diagnostic Test: Application Value of MRI Imaging in Treatment Decision-Making for Lung Cancer

Study type: Interventional

Funder types: Other

Identifiers

NCT06742021

KYLX2024-272

Details and patient eligibility

About

This study aims to address the challenge of predicting the efficacy of targeted and immunotherapy in lung cancer patients. By utilizing two DCE-MRI images-one before treatment and one after one treatment cycle-along with the patients' clinical and pathological information, we aim to achieve accurate prediction of the therapeutic efficacy of targeted and immunotherapy in lung cancer patients.

Enrollment: 195 estimated patients

Sex: All

Ages: 18 to 75 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

1. Tumor size greater than 2 cm
2. Age between 18 and 75 years

Exclusion criteria

1. Presence of MRI contraindications (e.g., metal implants, pacemaker implantation, etc.)
2. Allergy to gadolinium contrast agents
3. Lesions difficult to delineate on images due to conditions such as atelectasis or diffuse lesions

Trial design

Primary purpose: Treatment

Allocation: N/A

Interventional model: Single Group Assignment

Masking: None (Open label)

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195 participants in 1 patient group

Application Value of MRI Imaging in Treatment Decision-Making for Lung Cancer

Experimental group

Description:

A Philips 3.0T MRI scanner was used, with a dStream Torso 32-channel coil. DCE-MRI was performed using a free-breathing sequence with a flow velocity of 3.0 m/s. The image quality assessment in this study was performed by two radiologists (one with 3 years of diagnostic experience and the other with 15 years of diagnostic experience), including both subjective and objective evaluations. Then, dynamic information from the 4D FreeBreathing DCE-MRI images taken before treatment and one week after immunotherapy/targeted therapy, along with routine clinical and pathological data, were used to construct predictive models for the efficacy of immunotherapy and targeted therapy. Finally, the MRI model was compared with the CT model, and the performance of both models was evaluated.

Treatment:

Diagnostic Test: Application Value of MRI Imaging in Treatment Decision-Making for Lung Cancer