LTP2 Results Analysis-Schabath-Moffitt-2024

Abbreviated Name
LTP2 Results Analysis-Schabath-Moffitt-2024
Lead Investigator
Schabath, Matthew — H. Lee Moffitt Cancer Center & Research Institute, Inc.
Coordinating Investigator
Zheng, Yingye — Fred Hutchinson Cancer Center
Involved Investigators

Abstract

No abstract availalbe.

Aims

The CT images that will be curated and archived will be subjected to our in-house radiomics pipeline detailed in Figure 7.4 below and available for future use as part of the reference set. From high-quality images, the nodule/tumor is identified and semi-automatically segmented. This segmented volume is rendered from the rest of the image. From the rendered volume and its surrounding stroma, quantitative radiomic features are extracted and then databased. The databased features are merged with patient data and then analyzed. Radiomic features (Semantic and Agnostic) will be extracted from the baseline and follow-up CT images from the participants. Semantic features are those that are commonly used in the radiology lexicon to describe regions of interest. Each feature is rated as ordinal (0-5) or binary (present vs. not present) and work is ongoing to automate the extraction of these features. A

Analytic Method

No analytic method available.

Publications

  • No publications available at this time for this protocol.

Biomarkers

  • No biomarkers available at this time for this protocol.

Data Collections

  • No data collections available at this time for this protocol.
Protocol ID
557
Protocol Type
Reference Set
Fields of Research
  • UNKNOWN
Collaborative Group
Lung and Upper Aerodigestive Cancers Research Group
Cancer Types
  • Malignant neoplasm of bronchus and lung

Associated Forms