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
5011 - LCSCAF1 maintains cancer stem-like traits by stabilizing c-Myc protein and promotes metastasis and recurrence in lung cancer
Presenter: Tao Guo
Session: Poster Display session 1
Resources:
Abstract
4955 - XAF1 Enhances Temozolomide Induced Autophagic Cell Death through AMPK signaling pathway
Presenter: Mingoo Lee
Session: Poster Display session 1
Resources:
Abstract
5616 - The effect of cortisol on methylation patterns in breast cancer cell lines
Presenter: Haya Intabli
Session: Poster Display session 1
Resources:
Abstract
4649 - Global and sex-specific epigenome-wide association studies for the identification of the main methylated loci related to smoking in a Mediterranean population
Presenter: Judith Begona Ramirez Sabio
Session: Poster Display session 1
Resources:
Abstract
4984 - Whole transcriptomics analyses of mimicking Circulating Tumor Cells (CTCs) by single-cell RNA sequencing (scRNAseq)
Presenter: Jessica Garcia
Session: Poster Display session 1
Resources:
Abstract
5926 - Comparison of enzymatic- and bisulfite conversion to map the plasma cell-free methylome in cancer
Presenter: Nicole Lambert
Session: Poster Display session 1
Resources:
Abstract
5454 - Detection of low mutations in hepatocellular carcinoma by using circulating tumor DNA
Presenter: Esl Kim
Session: Poster Display session 1
Resources:
Abstract
4428 - Variants in the JAK1 and JAK2 genes in the risk and prognosis of patients with cutaneous melanoma
Presenter: Bruna Carvalho
Session: Poster Display session 1
Resources:
Abstract
4409 - P-Rex1 expression in breast cancer patients.
Presenter: Angela Lara Montero
Session: Poster Display session 1
Resources:
Abstract
4185 - Modulation of Risk of Cutaneous Melanoma Patients by Variants in STAT3 Gene and Functional Analysis
Presenter: Gabriela Gomez
Session: Poster Display session 1
Resources:
Abstract