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N. Andratschke
Moderator of
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Combining radiation with non-chemotherapy agents (ID 19)
- Event: ELCC 2018
- Type: Multidisciplinary Interactive Session (MIS)
- Track:
- Presentations: 2
- Moderators:N. Andratschke, A. Naing
- Coordinates: 4/13/2018, 08:00 - 08:50, Room A
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Combining radiotherapy with immune-checkpoint inhibitors (ID 79)
08:00 - 08:50 | Presenting Author(s): A. Naing
- Abstract
Abstract not provided
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Combining radiotherapy with TKIs in oligo-progressive oncogene addicted NSCLC (ID 78)
08:00 - 08:50 | Presenting Author(s): N. Andratschke
- Abstract
- Presentation
Abstract not provided
Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
Author of
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+
Combining radiation with non-chemotherapy agents (ID 19)
- Event: ELCC 2018
- Type: Multidisciplinary Interactive Session (MIS)
- Track:
- Presentations: 1
- Moderators:N. Andratschke, A. Naing
- Coordinates: 4/13/2018, 08:00 - 08:50, Room A
-
+
Combining radiotherapy with TKIs in oligo-progressive oncogene addicted NSCLC (ID 78)
08:00 - 08:50 | Presenting Author(s): N. Andratschke
- Abstract
- Presentation
Abstract not provided
Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
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Poster Display session (Friday) (ID 65)
- Event: ELCC 2018
- Type: Poster Display session
- Track:
- Presentations: 1
- Moderators:
- Coordinates: 4/13/2018, 12:30 - 13:00, Hall 1
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76P - Robustness of radiomic features in [18F]-FDG PET/CT and [18F]-FDG PET/MR (ID 304)
12:30 - 13:00 | Author(s): N. Andratschke
- Abstract
Background:
Radiomics is a promising tool for identification of new prognostic biomarkers. However, image reconstruction settings may affect the absolute values of radiomic features, which reduces their value as reliable biomarkers. PET/MR is becoming more available and often replaces PET/CT. The aim of this study was to quantify to what extend [18F]-FDG PET/CT radiomics models can be transferred to [18F]-FDG PET/MR.
Methods:
Nine patients with non-small cell lung cancer underwent first an [18F]-FDG PET/MR scan followed by an [18F]-FDG PET/CT scan (SIGNA PET/MR and Discovery PET/CT 690, GE Healthcare) with a delay time of 38 min +/−5 min. Patients had one single FDG injection for both scans. The primary tumors were segmented independently on the PET scans from PET/CT and PET/MR with two semi-automated methods (gradient-based and threshold-based). Resampling was performed to the lowest resolution. In total, 1358 radiomic features were calculated, i.e. shape (18), intensity (17), texture (137), wavelets (1186). The intra-class correlation coefficient was used to compare the radiomic features in both image modalities. An ICC >0.9 was considered stable among both types of PET scans.
Results:
The median relative volume difference of the tumors segmented on PET/CT and PET/MR was 4.8% (range 0.4–39.9%) for the gradient-based and 18.0% (range 0.7–71.2%) for the threshold-based method. A larger number of radiomic features was stable using the gradient-based method compared to the threshold-based method, which concurs with the improved reproducibility of tumor volume using gradient-based method. More than 70.6% of shape and intensity features yielded an ICC >0.9 among both segmentation methods. However, only 51.5% of texture and 27.2% of wavelet features reached this criterion (for gradient-based and even less in threshold-based method). In the wavelet features analysis, more features were robust in smoothed images (low-pass filtering) in comparison to images with emphasized heterogeneity (high-pass filtering).
Conclusions:
Shape and intensity radiomic features were robust comparing the two types of [18F]-FDG PET scans (PET/CT and PET/MR). In contrast, texture and wavelet features showed reduced stability, which needs to be considered for their use in prognostic modelling.
Clinical trial identification:
Legal entity responsible for the study:
Dr. Stephanie Tanadini-Lang
Funding:
Has not received any funding
Disclosure:
M. Guckenberger: Committee Member EORTC, ESTRO Board of Directors, Head of Working Group DEGRO. All other authors have declared no conflicts of interest.
