Abstract 2737
Background
Well-differentiated liposarcomas (WDLPS) can be difficult to distinguish from lipomas. Currently, this distinction is made by testing for MDM2-amplification, which requires a biopsy. The aim of this study was to non-invasively predict the MDM2-amplification status using radiomics, i.e. a combination of quantitative imaging features and machine learning techniques, thereby differentiating between lipomas and WDLPS.
Methods
Patients with a lipoma or WDLPS, a known MDM2-amplification status and a pre-treatment T1-weighted MRI scan who were referred to or diagnosed at the Erasmus MC from 2009-2018 were included. When available, other sequences, e.g. T2-weighted (fat-saturated) MRI, were included in the radiomics analysis. Imaging features describing intensity, shape, orientation and texture were extracted from the tumor segmentations; age, gender, tumor depth and tumor localization were added as semantic features. Classification was performed using an ensemble of various machine learning approaches. Evaluation was performed through 100x random-split cross-validation.
Results
We included 116 patients: 58 patients with lipoma and 58 patients with WDLPS. The dataset originated from 41 MRI-scanners, resulting in large heterogeneity in imaging hardware and acquisition protocols. The best performing radiomics approach to differentiate between WDLPS and lipomas, based on T1-weighted imaging only, resulted in a mean [95% confidence interval] AUC of 0.75 [0.65-0.86], accuracy of 0.68 [0.59-0.77], sensitivity of 0.63 [0.48-0.78] and specificity of 0.73 [0.59-0.87]. A model based on the combination of imaging and semantic featured showed only a minor and non-significant improvement in performance.
Conclusions
There is a significant relationship between a radiomics signature, consisting of a combination of quantitative MRI features, and the MDM2-amplification status. Although further optimization and validation is needed for the transition to clinical practice, radiomics has appeared to be a promising, non-invasive approach for the classification of WDLPS and lipomas.
Clinical trial identification
Editorial acknowledgement
M.Vos and M.P.A. Starmans contributed equally to this study.
Legal entity responsible for the study
The authors.
Funding
Stichting Coolsingel, Netherlands Organisation for Scientific Research, Dutch Cancer Society.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
5054 - Inhibition of Rspo-Wnt pathway Facilitates Checkpoint Blockade Therapy by anti-RSPO3 antibody (DBPR117)
Presenter: John Hsu
Session: Poster Display session 1
Resources:
Abstract
3305 - A phase I dose-escalation and expansion trial of intratumorally administered CV8102, alone and in combination with anti-PD-1 in patients with advanced solid tumors
Presenter: Jürgen Krauss
Session: Poster Display session 1
Resources:
Abstract
5353 - Phase 1/2 Study of 9-ING-41, a small molecule selective Glycogen Synthase Kinase-3 Beta (GSK-3β) Inhibitor, as a Single Agent and Combined with Chemotherapy, in Patients with Refractory Hematological Malignancies or Solid Tumors
Presenter: Benedito Carneiro
Session: Poster Display session 1
Resources:
Abstract
3946 - Trial in progress: a Phase I, open-label study of GSK1795091 administered in combination with immunotherapies in participants with advanced solid tumors (NCT03447314).
Presenter: Aaron Hansen
Session: Poster Display session 1
Resources:
Abstract
3449 - Radiographic Phenotyping to Identify Intracranial Disseminated Recurrence in Brain metastases Treated With Radiosurgery Using Contrast-enhanced MR Imaging
Presenter: CheYu Hsu
Session: Poster Display session 1
Resources:
Abstract
4553 - Association between TP53 mutations and efficacy of Osimertinib for brain metastasis from EGFR-mutant lung cancer
Presenter: Lijuan Chen
Session: Poster Display session 1
Resources:
Abstract
4942 - Response assessment of melanoma brain metastases treated by stereotactic radiotherapy or immunotherapy or both: a comparison of RECIST 1.1, RANO and iRANO criteria
Presenter: Emilie Le Rhun
Session: Poster Display session 1
Resources:
Abstract
3529 - Management of multiple brain metastases by Staged SRS focusing on utmost risk lesions
Presenter: shaoqun Li
Session: Poster Display session 1
Resources:
Abstract
5315 - Whole brain radiotherapy plus simultaneous in-field boost versus whole brain radiotherapy plus fractionated stereotactic radiotherapy for multiple brain metastases of non-small cell lung cancer
Presenter: Lu Li
Session: Poster Display session 1
Resources:
Abstract
1116 - 3D based texture analysis serving as potential diagnostic factor in discriminating primary central nervous system lymphoma from metastatic brain tumors: A preliminary study
Presenter: Wen Guo
Session: Poster Display session 1
Resources:
Abstract