Purposes: To develop and evaluate a boundary informed electrical properties tomography (BIEPT) technique for high-resolution imaging of tumor electrical properties (EPs) heterogeneity on a rodent tumor xenograft model. Methods: Tumor EP distributions were inferred from a reference area external to the tumor, as well as internal EP spatial variations derived from a plurality of relative transmit B1 measurements at 7T. Edge sparsity constraint was enforced to enhance numerical stability. Phantom experiments were performed to determine the imaging accuracy and sensitivity for structures of various EP values, as well as geometrical sizes down to 1.5 mm. Numerical simulation of a realistic rodent model was used to quantify the algorithm performance in the presence of noise. Eleven athymic rats with human breast cancer xenograft were imaged in vivo, and representative pathological samples were acquired for comparison. Results: Reconstructed EPs of the phantoms correspond well to the ground truth acquired from dielectric probe measurements, with the smallest structure reliably detectable being 3 mm. EPs heterogeneity inside a tumor is successfully retrieved in both simulated and experimental cases. In vivo tumor imaging results demonstrate similar local features and spatial patterns to anatomical MRI and pathological slides. The imaged conductivity of necrotic tissue is higher than that of viable tissues, which agrees with our expectation. Conclusion: BIEPT enables robust detection of tumor EPs heterogeneity with high accuracy and sensitivity to small structures. The retrieved quantitative EPs reflect tumor pathological features (e.g., necrosis). These results provide strong rationale to further expand BIEPT studies toward pathological conditions where EPs may yield valuable, non-invasive biomarkers.
Bibliographical noteFunding Information:
National Institutes of Health, Grant/Award Number: NIH EB017069, NIH EB014353, NIH MH114233, NIH EB021027, NIH , NS096761, NIH HL117664, NIH EB015894, NIH NS076408, NIH RR026783 and NIH EB008389; National Science Foundation, Grant/Award Number: NSF CBET-1450956 and NSF CBET-1264782; WM KECK Foundation
This work was supported in part by NIH EB017069, NIH EB014353, NIH MH114233, NIH EB021027, NIH NS096761, NIH HL117664, NIH EB015894, NIH NS076408, NIH RR026783, NIH EB008389, NSF CBET‐1450956, NSF CBET‐1264782, and WM KECK Foundation. The authors thank Dr. Gregor Adriany for MRI hardware assistance; Drs. Michael Garwood, Patrick Bolan and Michael Nelson for their inputs on cancer imaging; Drs. Long Yu and Ting Yang for discussions on numerical analysis; Mr. Kai Yu for inputs on phantom construction; Ms. Jiaoyue Liu for artwork assistance and Mr. Christopher Cline for manuscript editing.
- electrical properties tomography (EPT)
- electromagnetic simulation
- multi-channel B mapping
- tumor heterogeneity
- ultra-high-field MRI