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The purpose of this study was to investigate if radiomic analysis based on spectral micro-CT with nanoparticle contrast-enhancement can differentiate tumors based on lymphocyte burden. High mutational load transplant soft tissue sarcomas were initiated in Rag2 +/- and Rag2 -/- mice to model varying lymphocyte burden. Mice received radiation therapy (20 Gy) to the tumor-bearing hind limb and were injected with a liposomal iodinated contrast agent. Five days later, animals underwent conventional micro-CT imaging using an energy integrating detector (EID) and spectral micro-CT imaging using a photon-counting detector (PCD). Tumor volumes and iodine uptakes were measured. The radiomic features (RF) were grouped into feature-spaces corresponding to EID, PCD, and spectral decomposition images. The RFs were ranked to reduce redundancy and increase relevance based on TL burden. A stratified repeated cross validation strategy was used to assess separation using a logistic regression classifier. Tumor iodine concentration was the only significantly different conventional tumor metric between Rag2 +/- (TLs present) and Rag2 -/- (TL-deficient) tumors. The RFs further enabled differentiation between Rag2 +/- and Rag2 -/- tumors. The PCD-derived RFs provided the highest accuracy (0.68) followed by decomposition-derived RFs (0.60) and the EID-derived RFs (0.58). Such non-invasive approaches could aid in tumor stratification for cancer therapy studies.

Purpose: Tumor hypoxia contributes to aggressive phenotypes and diminished therapeutic responses to radiation therapy (RT) with hypoxic tissue being 3-fold less radiosensitive than normoxic tissue. A major challenge in implementing hypoxic radiosensitizers is the lack of a high-resolution imaging modality that directly quantifies tissue-oxygen. The electron paramagnetic resonance oxygen-imager (EPROI) was used to quantify tumor oxygenation in two murine tumor models: E0771 syngeneic transplant breast cancers and primary p53/MCA soft tissue sarcomas, with the latter autochthonous model better recapitulating the tumor microenvironment in human malignancies. We hypothesized that tumor hypoxia differs between these models. We also aimed to quantify the absolute change in tumor hypoxia induced by the mitochondrial inhibitor papaverine (PPV) and its effect on RT response. Procedures: Tumor oxygenation was characterized in E0771 and primary p53/MCA sarcomas via EPROI, with the former model also being quantified indirectly via diffuse reflectance spectroscopy (DRS). After confirming PPV's effect on hypoxic fraction (via EPROI), we compared the effect of 0 versus 2 mg/kg PPV prior to 20 Gy on tumor growth delay and survival. Results: Hypoxic sarcomas were more radioresistant than normoxic sarcomas (p=0.0057, 2-way ANOVA), and high baseline hypoxic fraction was a significant (p=0.0063, Cox Regression Model) hazard in survivability regardless of treatment. Pre-treatment with PPV before RT did not radiosensitize tumors in the sarcoma or E0771 model. In the sarcoma model, EPROI successfully identified baseline hypoxic tumors. DRS quantification of total hemoglobin, saturated hemoglobin, changes in mitochondrial potential and glucose uptake showed no significant difference in E0771 tumors pre- and post-PPV. Conclusion: EPROI provides 3D high-resolution pO2 quantification; EPR is better suited than DRS to characterize tumor hypoxia. PPV did not radiosensitize E0771 tumors nor p53/MCA sarcomas, which may be related to the complex pattern of vasculature in each tumor. Additionally, understanding model-dependent tumor hypoxia will provide a much-needed foundation for future therapeutic studies with hypoxic radiosensitizers. [ABSTRACT FROM AUTHOR]

The purpose of this study was to investigate if radiomic analysis based on spectral micro-CT with nanoparticle contrast-enhancement can differentiate tumors based on lymphocyte burden. High mutational load transplant soft tissue sarcomas were initiated in Rag2+/− and Rag2−/− mice to model varying lymphocyte burden. Mice received radiation therapy (20 Gy) to the tumor-bearing hind limb and were injected with a liposomal iodinated contrast agent. Five days later, animals underwent conventional micro-CT imaging using an energy integrating detector (EID) and spectral micro-CT imaging using a photon-counting detector (PCD). Tumor volumes and iodine uptakes were measured. The radiomic features (RF) were grouped into feature-spaces corresponding to EID, PCD, and spectral decomposition images. The RFs were ranked to reduce redundancy and increase relevance based on TL burden. A stratified repeated cross validation strategy was used to assess separation using a logistic regression classifier. Tumor iodine concentration was the only significantly different conventional tumor metric between Rag2+/− (TLs present) and Rag2−/− (TL-deficient) tumors. The RFs further enabled differentiation between Rag2+/− and Rag2−/− tumors. The PCD-derived RFs provided the highest accuracy (0.68) followed by decomposition-derived RFs (0.60) and the EID-derived RFs (0.58). Such non-invasive approaches could aid in tumor stratification for cancer therapy studies. [ABSTRACT FROM AUTHOR]