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OBJECTIVE: Neuroblastoma has one of the lowest survival rates of all childhood cancers, despite the use of intensive treatment regimens. Preclinical models of neuroblastoma are essential for testing new multimodality protocols, including those that involve radiotherapy (RT). The aim of this study was to develop a robust method for RT planning and tumour response monitoring based on combined MRI and cone-beam CT (CBCT) imaging and to apply it to a widely studied mouse xenograft model of neuroblastoma, SK-N-SH. METHODS: As part of a tumour growth inhibition study, SK-N-SH xenografts were generated in BALB/c nu/nu mice. Mice (n = 8) were placed in a printed MR- and CT-compatible plastic cradle, imaged using a 4.7-T MRI scanner and then transferred to a small animal radiation research platform (SARRP) irradiator with on-board CBCT. MRI/CBCT co-registration was performed to enable RT planning using the soft-tissue contrast afforded by MRI prior to delivery of RT (5 Gy). Tumour response was assessed by serial MRI and calliper measurements. RESULTS: SK-N-SH xenografts formed soft, deformable tumours that could not be differentiated from surrounding normal tissues using CBCT. MR images, which allowed clear delineation of tumours, were successfully co-registered with CBCT images, allowing conformal RT to be delivered. MRI measurements of tumour volume 4 days after RT correlated strongly with length of survival time. CONCLUSION: MRI allowed precision RT of SK-N-SH tumours and provided an accurate means of measuring tumour response. Advances in knowledge: MRI-based RT planning of murine tumours is feasible using an SARRP irradiator.

Original publication

DOI

10.1259/bjr.20160427

Type

Journal article

Journal

Br J Radiol

Publication Date

01/2017

Volume

90

Keywords

Analysis of Variance, Animals, Disease Models, Animal, Early Diagnosis, Heterografts, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Mice, Mice, Nude, Neuroblastoma, Predictive Value of Tests, Radiotherapy Dosage, Radiotherapy Planning, Computer-Assisted, Risk Assessment, Tumor Burden