Abstract 2751
Background
Gastrointestinal stromal tumors (GISTs) are rare mesenchymal tumors of the gastrointestinal (GI) tract. The size, the presence of a c-KIT gene mutation and the mitotic index are used to determine the prognosis and to direct systemic treatment choices. This study evaluated the use of radiomics, a technique which uses algorithms for diagnosing and predicting the c-KIT mutational status and mitotic index of GISTs from medical imaging features.
Methods
A combination of machine learning methods was used to distinguish treatment-naive GISTs from other GI tumors resembling GISTs on imaging, based on clinical and molecular characteristics, as well as imaging features extracted from the contrast-enhanced venous phase computed tomography scans. Evaluation was performed in a 100x random-split cross-validation with 20% of the data for testing.
Results
A total of 242 tumors were used for distinguishing GISTs (n = 123) from non-GISTs (n = 119) including leiomyoma (n = 25), schwannoma (n = 21), gastric carcinoma (n = 25), lymphoma (n = 23) and leiomyosarcoma (n = 25).The non-GISTs were located either gastric (23%) or non-gastric (77%) and the GISTs were located either gastric (63%) or non-gastric (37%). A c-KIT mutation was present in the majority of the GISTs (exon 9 n = 10, exon 11 n = 56, exon 13 n = 2). The dataset originated from 65 different scanners, leading to heterogeneity in the imaging protocols. Imaging feature analyses showed a mean area under the curve (mAUC) of 0.70 (95% confidence interval [CI] 0.63-0.76) for distinguishing GIST from non-GISTs. A mAUC of 0.52 (95% CI 0.32-0.72) was found for predicting all c-KIT mutations, a mAUC of 0.51 (95% CI 0.29-0.72) for predicting a c-KIT exon 9 mutation, and a mAUC of 0.61 (95% CI 0.47-0.74) for predicting a c-KIT exon 11 mutation. The mitotic index was available in 83 patients (≤5/50 high power fields (HPFs) n = 53, 43.1%, >5/50 HPFs n = 33, 26.8%), and showed a mAUC of 0.60 (95% CI 0.47-0.73).
Conclusions
This pilot study showed the potential of radiomics to distinguish GIST from other GI tumors, but no potential in predicting c-KIT mutational status and mitotic index of GISTs. Further optimization and validation of the radiomics model is required to incorporate radiomics in the diagnostic routine of GISTs.
Clinical trial identification
Editorial acknowledgement
M.J. Timbergen and M.P.A. Starmans contributed equally to this study.
Legal entity responsible for the study
The authors.
Funding
The Netherlands Organization for Scientific Research.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
1701 - Immunogenicity and optimal timing of 13-valent pneumococcal conjugate vaccination during adjuvant chemotherapy in gastric and colorectal cancer : A randomized controlled trial
Presenter: Wonyoung Choi
Session: Poster Display session 1
Resources:
Abstract
3158 - Tobacco Retail Access and Tobacco Cessation Among Head and Neck Cancer (HNC) Survivors
Presenter: Lawson Eng
Session: Poster Display session 1
Resources:
Abstract
5511 - ASSERT: A Prospective, Observational Study Measuring Sodium Improvement and Outcomes in Patients Treated for Moderate to Severe Hyponatremia Secondary to Syndrome of Inappropriate Antidiuretic Hormone secretion (SIADH) in Italy (Lung Cancer Cohort)
Presenter: Rossana Berardi
Session: Poster Display session 1
Resources:
Abstract
3821 - Efficacy and safety of controlled ovarian stimulation with or without letrozole co-administration for fertility preservation: A systematic review and meta-analysis.
Presenter: Benedetta Bonardi
Session: Poster Display session 1
Resources:
Abstract
2168 - Child development at 6 years after maternal cancer diagnosis and treatment during pregnancy
Presenter: Tineke Vandenbroucke
Session: Poster Display session 1
Resources:
Abstract
5855 - Update of the registry of young women with cancer by the International Network of Cancer, Infertility and Pregnancy
Presenter: Charlotte Maggen
Session: Poster Display session 1
Resources:
Abstract
5156 - Erectile dysfunction in patients with metastatic renal cell carcinoma
Presenter: Ilya Tsimafeyeu
Session: Poster Display session 1
Resources:
Abstract
4992 - Exercise level, interest and preferences in cancer patients.
Presenter: Alice Avancini
Session: Poster Display session 1
Resources:
Abstract
3427 - Filling the Gaps in Informed Consent for Advanced Cancer Patients considering Phase 1 Oncology Trials - an in-depth Qualitative Study of Key Stakeholders at a large United Kingdom Phase 1 unit
Presenter: Abhijit Pal
Session: Poster Display session 1
Resources:
Abstract
3537 - Breast Cancer Patients’ Quality of Life: Real World Data
Presenter: Thanos Kosmidis
Session: Poster Display session 1
Resources:
Abstract