jump to content jump to footer

Early Detection of Treatment Response in Lung Cancer Using Delta-Radiomics Features

The study conducted by Heidelberg University Hospital investigates the use of diffusion-weighted MRI (DWI) to predict early treatment outcomes in patients with advanced lung adenocarcinoma. The researchers analyzed changes in radiomic features derived from ADC (Apparent Diffusion Coefficient) maps in 144 patients who were treated with either tyrosine kinase inhibitors (TKI) or platinum-based chemotherapy (PBC).

The study found that radiomic features, known as delta-radiomics features (DRFs), were able to predict treatment success and progression-free survival (PFS) as early as 14 days after the start of treatment.

These features enabled the distinction between patients with likely better and worse treatment outcomes.

The use of DWI-based radiomics shows promising potential for early decision-making in lung cancer treatment and could allow physicians to adjust therapies more quickly.

This approach offers a non-invasive, radiation-free alternative for early assessment of treatment success in lung cancer.

Read more about the study here.

Image of a patient getting an MRI scan, signifying how RACOON projects in Germany show how imaging, structured reporting, and AI jointly advance clinical research.
Overview of major RACOON projects in radiology and clinical research.
RACOON – Imaging, Data & Collaboration for Better Decisions

Modern radiology faces a central question: how can imaging and clinical data be combined in a way that leads to more precise diagnoses,…

Read more
Interview with Prof. Timm Denecke about the RACOON-MARDER project and AI-powered early detection of liver cancer using MRI
An in-depth interview with Prof. Timm Denecke about the RACOON-MARDER project
Rethinking Early Detection: How RACOON-MARDER Aims to Spot Liver Cancer Sooner

Hepatocellular carcinoma (HCC) is often diagnosed too late, limiting treatment options and survival. The RACOON-MARDER project aims to change that. By…

Read more
Image of doctor looking at a prostate in mint Lesion.
Prof. Dr. Thorsten Persigehl from University Hospital Cologne discusses the use of structured reporting and AI in prostate diagnostics with mint Lesion.
Structured Reporting and AI in Radiology: Efficiency and Quality in Prostate Diagnostics

How are structured reporting and artificial intelligence transforming radiology practice?

Prof. Dr. Thorsten Persigehl from University Hospital…

Read more
scroll-top