Abstract
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.
Highlights
The immune response to neoplastic disease involves infiltration by lymphocytes [1]
The results of our semantic radiomic features (RF) analysis calculated using the decomposed iodine maps are reported in the box plots of Figure 4
The results show that mean iodine concentration in the tumors is the only statistically significant (p < 0.05) distinguishing semantic RF for these two groups
Summary
The immune response to neoplastic disease involves infiltration by lymphocytes (including T cells and B cells) [1]. T cells and B cells are the major cellular components of the adaptive immune response, and they play an important role in cancer progression and response to certain therapeutics, to immunotherapy [2]. Assessment of tumor lymphocytes (TLs) is usually performed by histopathology and may provide important prognostic information in tumors [3]. Biopsy-based methods are limited due to both patient discomfort and risk with repeated invasive procedures, as well as sampling error due to tumor heterogeneity and the small volume of tissue obtained with each biopsy. Advanced quantitative imaging-based methods that enable non-invasive and repeated whole-tumor interrogation are highly desirable. We hypothesize that high-resolution and spectral CT imaging can provide rich datasets required for radiomics assessment of lymphocytic presence in tumors
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