Skip to content

RaFIST: A Radiomics-Based Tool for Intratumoral Fibrosis Stratification in Non-Small Cell Lung Cancer

Development and Prognostic Validation of RaFIST: A Radiomics-Based Tool for Intratumoral Fibrosis Stratification in Non-Small Cell Lung Cancer

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT06908005
Enrollment
508
Registered
2025-04-03
Start date
2024-04-01
Completion date
2025-03-01
Last updated
2025-04-08

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Lung Cancer - Non Small Cell

Keywords

NSCLC, radiomics, PFS, fibrosis

Brief summary

Patients with suspected Lung cancer who underwent contrast-enhanced CT and pathological examinations at Center 1 between January 2011 and January 2020 and Center 2 between September 2017 and Januray 2020 were eligible for inclusion in this study.The Clinical data, preoperative clinical information, laboratory results, CT images and pathological sections were collected. The investigators also collected the disease-free survival and overall survival time. On the Deepwise multi-modal research platform, the images were semi-automatically segmented and PyRadiomics was used to extract the radiomic features. Fibrosis quantification was performed on picrosirius red (PSR)-stained tissue sections using color deconvolution and binarized collagen signal analysis in ImageJ software. The investigators developed RaFIST, a radiomics-based stratification tool, to noninvasively quantify intratumoral fibrosis in non-small cell lung cancer (NSCLC) using contrast-enhanced CT imaging. And it was further tested on the held-out external test cohort. Discrimination was assessed by using the C-index and area under the receiver operating characteristic curve (AUC).

Interventions

Radiomic features of tumor tissue

OTHERFibrosis assessment

Fibrosis quantification was performed on picrosirius red (PSR)-stained tissue sections using color deconvolution and binarized collagen signal analysis in ImageJ software (v1.5)

Sponsors

Jinling Hospital, China
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
RETROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum

Inclusion criteria

* Solid pulmonary nodule detected on CECT within 3 weeks pre-resection * No history of previous treatment such as chemotherapy, or radiotherapy

Exclusion criteria

* Unavailable pathological sections * Missing CT images or hard-to-annotate CT images * Undergone anticancer therapy before CT * Loss to follow-up * Concurrent other malignant tumors

Design outcomes

Primary

MeasureTime frameDescription
DFS (Disease-free survival)Record from the date of surgery to the date of recurrence or death from any cause, whichever comes first, and assess up to a maximum of 5 years.DFS was defined as the duration from the date of primary surgery to the first occurrence of recurrence or death from any cause.

Secondary

MeasureTime frame
OS (overall survival)Record from the date of surgery to the date of death from any cause,whichever comes first, and assess up to a maximum of 5 years.

Countries

China

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026