Improvement of 19F MR image uniformity in a mouse model of cellular therapy using inductive coupling.

OBJECTIVE: Improve 19F magnetic resonance imaging uniformity of perfluorocarbon (PFC)-labeled cells by using a secondary inductive resonator tuned to 287 MHz to enhance the induced radio frequency (RF) magnetic field (B1) at 7.05 T. MATERIALS AND METHODS: Following Faraday's induction law, the sign of induced B1 made by the secondary resonator can be changed depending on the tuning of the resonator. A secondary resonator located on the opposite side of the phantom of the 19F surface coil can be shown to enhance or subtract the induced B1 field, depending upon its tuning. RESULTS: The numerical simulation results of rotating transmit B1 magnitude (|B 1 + |) and corresponding experimental 19F images were compared without and with the secondary resonator. With the secondary resonator tuned to 287 MHz, improvements of |B 1 + | and 19F image uniformity were demonstrated. The use of the secondary resonator improved our ability to visualize transplanted cell location non-invasively over a period of 6 weeks. CONCLUSION: The secondary resonator tuned to enhance the induced B1 results in improved image uniformity in a pre-clinical application, enabling cell tracking of PFC-labeled cells with the secondary resonator.

Radiation-free quantification of head malformations in craniosynostosis patients from 3D photography.

The evaluation of cranial malformations plays an essential role both in the early diagnosis and in the decision to perform surgical treatment for craniosynostosis. In clinical practice, both cranial shape and suture fusion are evaluated using CT images, which involve the use of harmful radiation on children. Three-dimensional (3D) photography offers non-invasive, radiation-free, and anesthetic-free evaluation of craniofacial morphology. The aim of this study is to develop an automated framework to objectively quantify cranial malformations in patients with craniosynostosis from 3D photography. We propose a new method that automatically extracts the cranial shape by identifying a set of landmarks from a 3D photograph. Specifically, it registers the 3D photograph of a patient to a reference template in which the position of the landmarks is known. Then, the method finds the closest cranial shape to that of the patient from a normative statistical shape multi-atlas built from 3D photographs of healthy cases, and uses it to quantify objectively cranial malformations. We calculated the cranial malformations on 17 craniosynostosis patients and we compared them with the malformations of the normative population used to build the multi-atlas. The average malformations of the craniosynostosis cases were 2.68 ± 0.75 mm, which is significantly higher (p<0.001) than the average malformations of 1.70 ± 0.41 mm obtained from the normative cases. Our approach can support the quantitative assessment of surgical procedures for cranial vault reconstruction without exposing pediatric patients to harmful radiation.