MRI-Based Radiomics Reveals Cannabinoid-Associated Tumor Phenotypes in a Murine Breast Cancer Model
INTRODUCTION AND AIM: THC full extract, exhibit diverse and potentially subtle effects on tumor biology. Radiomics enables high-throughput extraction of quantitative imaging features that capture intratumoral heterogeneity beyond gross tumor volume. The primary aim of this study was to evaluate the utility of MRI-based radiomics as a sensitive tool for detecting cannabinoid-associated tumor phenotypic modulation in a preclinical breast cancer model. METHODS: Orthotopic breast tumors were induced in mice using the 4T1 cell line. Animals received cannabinoid formulations in combination with chemotherapy according to a predefined protocol. Tumor burden was assessed at baseline and post-treatment using ultrasonography and whole-body MRI to calculate tumor doubling time. T1- and T2-weighted MRI datasets were segmented and analyzed using radiomics to extract morphometric and signal-based features. RESULTS: THC full extract. In contrast, radiomics identified distinct, compound-specific tumor phenotypes, including structural features consistent with reduced aggressiveness, in JWH-182-treated tumors, despite similar volumetric growth patterns. CONCLUSION: MRI-based radiomics sensitively captures cannabinoid-associated tumor phenotype alterations beyond volumetric assessment, supporting its value as a pharmaco-imaging tool for characterizing treatment-related tumor biology in preclinical oncology.
Authors
- Debbie Anaby (ORCID: https://orcid.org/0000-0003-3285-6885)
- Andrei Szilagyi (ORCID: https://orcid.org/0009-0009-4734-4509)
- Cristina Mariana Urîtu (ORCID: https://orcid.org/0000-0002-7563-1267)
- Kfir M. Cohen (ORCID: https://orcid.org/0000-0001-8041-3873)
- Wael Jalloul (ORCID: https://orcid.org/0000-0001-5515-6473)
- Ioana Creangă-Murariu (ORCID: https://orcid.org/0000-0002-2631-7458)
- Raluca-Maria Gogu
- Teodora Alexa-Stratulat
- Dragos-Constantin ANITĂ
- Adriana-Elena Anita
- Mitica Ciorpac
- Radu-Andrei Baisan
- Cosmin-Vasilica Pricope
- Bogdan-Ionel Tamba
Institutions
- Sheba Medical Center (IL)
- Grigore T. Popa University of Medicine and Pharmacy (RO)
- Institutul Regional de Oncologie (RO)
- "Ion Ionescu de la Brad" Iasi University of Life Sciences (RO)
- Spitalul Clinic Judeţean de Urgenţe "Sf. Spiridon" Iaşi (RO)
Publication Details
- Journal
- Molecules
- Published
- 2026-03-31
- DOI
- https://doi.org/10.3390/molecules31071154
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00