---
title: Molecular Imaging Visualization of Tumor Heterogeneity in Non-small Cell Lung Cancer
nct_id: NCT04553601
overall_status: UNKNOWN
phase: NA
sponsor: The First Affiliated Hospital of Xiamen University
study_type: INTERVENTIONAL
primary_condition: NSCLC
countries: China
canonical_url: "https://parkinsonspathways.com/agent/trials/NCT04553601.md"
clinicaltrials_gov: "https://clinicaltrials.gov/study/NCT04553601"
ct_last_update_post_date: 2020-09-17
last_seen_at: "2026-05-12T07:15:59.384Z"
source: ClinicalTrials.gov (mirrored, no enrichment)
---
# Molecular Imaging Visualization of Tumor Heterogeneity in Non-small Cell Lung Cancer

**NCT ID:** [NCT04553601](https://clinicaltrials.gov/study/NCT04553601)

## Key Facts

- **Status:** UNKNOWN
- **Phase:** NA
- **Study Type:** INTERVENTIONAL
- **Target Enrollment:** 150
- **Lead Sponsor:** The First Affiliated Hospital of Xiamen University
- **Conditions:** NSCLC, PET/CT, Biopsy, Radiomics, Genomics, Whole-exome Sequencing
- **Start Date:** 2019-10-01
- **Completion Date:** 2022-10-01
- **CT.gov Last Update:** 2020-09-17

## Brief Summary

To assess the potential usefulness of radiogenomics for tumor driving genes heterogeneity in non-small cell lung cancer.

## Detailed Description

Patients with advanced NSCLC underwent 18F-FDG PET/CT and PET/CT-guided synchronous targeted biopsy of primary and distant metastatic tumors. The LIFEx package was used to extract PET and CT radiomic features from primary and metastatic lesions. The radiomic ROI sites of primary and distant metastatic tumors were point-to-point corresponding to the PET/ CT-guided targeted biopsy sites. Whole exon sequencing of primary and distant metastatic tumor samples obtained by PET/CT-guided targeted biopsy was used to get genomic data of primary and distant metastatic tumor. Predictive radiogenomics models were established and validation.

## Eligibility

- **Minimum age:** 18 Years
- **Maximum age:** 90 Years
- **Sex:** ALL
- **Healthy Volunteers:** No

```
Criteria: Inclusion Criteria:

* (i) adult patients (aged 18 years or order);
* (ii) patients with suspected or newly diagnosed or previously treated malignant tumors (supporting evidence may include magnetic resonance imaging (MRI), CT, tumor markers and pathology report);
* (iii) patients who had scheduled both 18F-FDG PET/CT scans and PET/CT guided biopsy;
* (iv) patients who were able to provide informed consent (signed by participant, parent or legal representative) and assent according to the guidelines of the Clinical Research Ethics Committee.

Exclusion Criteria:

* (i) patients with non-malignant lesions;
* (ii) patients with pregnancy;
* (iii) the inability or unwillingness of the research participant, parent or legal representative to provide written informed consent.
```

## Arms

- **8F-FDG PET/CT and PET/CT-guide targeted biopsy** (EXPERIMENTAL) — Each subject receive a single intravenous injection of 18F-FDG PET/CT and PET/CT-guide targeted biopsy within the specified time.

## Interventions

- **18F-FDG PET/CT and PET/CT-guide targeted biopsy in another group of participants** (DIAGNOSTIC_TEST) — Each subject receive a single intravenous injection of 18F-FDG PET/CT and PET/CT-guide targeted biopsy within the specified time

## Primary Outcomes

- **Radiomic feature selection and model establishment** _(time frame: 3 years)_ — In this study, the investigators first selected the features with significant differences between genes mutant and wild type in the training set using the Mann-Whitney U test, obtaining a total of 53 features with p value \< 0.05. Then, the least absolute shrinkage and selection operator (LASSO) algorithm was used to select the optimal predictive features among the 53 selected in the training set. The LASSO algorithm adds a L1 regularization term to a least square algorithm to avoid overfitting. A prediction model was established by logistic regression, and the radiomics signature score (rad-score) for each participant was calculated based on the selected discriminating radiomic features. The model performance was tested in the validation set. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used to evaluate the model performance in the training and validation sets.

## Secondary Outcomes

- **Genes mutation detection** _(time frame: 30 days)_
- **Image acquisition** _(time frame: 30 days)_
- **Radiomic feature extraction** _(time frame: 30 days)_

## Locations (1)

- First affiliated hospital of xiamen university, Xiamen, Fujian, China — _RECRUITING_

## Recent Field Changes (last 30 days)

- `status.overallStatus` — added _(2026-05-12)_
- `status.primaryCompletionDate` — added _(2026-05-12)_
- `status.completionDate` — added _(2026-05-12)_
- `status.lastUpdatePostDate` — added _(2026-05-12)_
- `design.phases` — added _(2026-05-12)_
- `design.enrollmentCount` — added _(2026-05-12)_
- `eligibility.criteria` — added _(2026-05-12)_
- `eligibility.minAge` — added _(2026-05-12)_
- `eligibility.maxAge` — added _(2026-05-12)_
- `eligibility.sex` — added _(2026-05-12)_
- `outcomes.primary` — added _(2026-05-12)_
- `outcomes.secondary` — added _(2026-05-12)_
- `armsInterventions.arms` — added _(2026-05-12)_
- `armsInterventions.interventions` — added _(2026-05-12)_
- `sponsor.lead` — added _(2026-05-12)_
- `results.hasResults` — added _(2026-05-12)_
- `locations.first affiliated hospital of xiamen university|xiamen|fujian|china` — added _(2026-05-12)_

---

*Canonical: https://parkinsonspathways.com/agent/trials/NCT04553601.md*  
*Source data (authoritative): https://clinicaltrials.gov/study/NCT04553601*  
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