Actively Recruiting

Age: 18Years +
All Genders
NCT07559123

Imaging-based PRediction of Eligibility for ChemoImmunotherapy in reSEctable NSCLC, iPRECISE

Led by Samsung Medical Center · Updated on 2026-05-08

150

Participants Needed

1

Research Sites

147 weeks

Total Duration

On this page

AI-Summary

What this Trial Is About

This study is for adults with resectable non-small cell lung cancer who are scheduled to receive neoadjuvant chemoimmunotherapy before surgery. Neoadjuvant chemoimmunotherapy can help shrink lung cancer before surgery and may improve treatment outcomes. However, not all patients benefit from this treatment in the same way, and it can sometimes cause side effects, such as immune-related pneumonitis. At present, it is still difficult to predict before or during treatment which patients will have a strong response. The purpose of this study is to find imaging features on chest computed tomography scans that may help predict how well a patient's cancer responds to neoadjuvant chemoimmunotherapy. The study will compare computed tomography findings before treatment and before surgery with pathologic findings from surgery, including pathologic complete response and major pathologic response. The study will also evaluate whether computed tomography-based imaging features are associated with treatment-related side effects and long-term outcomes such as disease progression and survival. This is an observational study. The investigators will not assign participants to a specific cancer treatment. Participants will receive neoadjuvant chemoimmunotherapy and surgery according to standard clinical practice. Chest computed tomography scans will be obtained before treatment and before surgery as part of the study protocol. These computed tomography images will also be reconstructed using a high-resolution deep learning-based computed tomography reconstruction technique to explore whether this approach can improve the development of imaging biomarkers. The results of this study may help develop a noninvasive imaging-based model to identify patients who are more likely to benefit from neoadjuvant chemoimmunotherapy and to better guide treatment planning for resectable non-small cell lung cancer.

CONDITIONS

Official Title

Imaging-based PRediction of Eligibility for ChemoImmunotherapy in reSEctable NSCLC, iPRECISE

Who Can Participate

Age: 18Years +
All Genders

Eligibility Criteria

Eligible

You may qualify if you...

  • Age 18 years or older
  • Histologically or cytologically confirmed non-small cell lung cancer (NSCLC)
  • Resectable NSCLC of stage IIIA or lower
  • Planned to receive neoadjuvant chemoimmunotherapy before surgery according to standard clinical practice
  • Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1
  • Able and willing to provide written informed consent after receiving detailed study explanation
Not Eligible

You will not qualify if you...

  • No measurable lesion (less than 10 mm on spiral/multidetector computed tomography)
  • History of another malignancy within 5 years before enrollment (excluding adequately treated basal cell skin carcinoma or cervical carcinoma in situ)
  • History of clinically significant uncontrolled seizures, central nervous system disease, or psychiatric disorders that may interfere with study participation or consent
  • History of severe allergic reaction to iodinated CT contrast media
  • Acute renal failure or moderate to severe renal impairment (creatinine clearance less than 45 mL/min/1.73 m�b2 or serum creatinine more than 1.5 times upper limit of normal)
  • Major surgery within 4 weeks of enrollment or incomplete recovery from major surgery
  • Currently pregnant or breastfeeding; women of childbearing potential without a negative baseline pregnancy test
  • Men or women of childbearing potential unwilling to use appropriate contraception during the study

AI-Screening

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Trial Site Locations

Total: 1 location

1

Samsung Medical Center

Seoul, South Korea

Actively Recruiting

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Research Team

H

Ho Yun Lee, Prof.

CONTACT

How is the study designed?

Study Type

OBSERVATIONAL

Masking

N/A

Allocation

N/A

Model

N/A

Primary Purpose

N/A

Number of Arms

0

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