Recently, the Radiobiology Research Group from the Centre for Cancer Research and Cell Biology at Queen’s University Belfast published a series of articles using SARRP to explore different translationally focused experimental approaches. The group, led by Prof Kevin Prise and Dr Karl Butterworth, have published three back to back papers within three months which reflect the interests of the research program in nanoparticle theranostics, bystander signaling and novel combination therapy.
SARRP
Xstrahl In Action: Transfer of Minibeam Radiation Therapy into a cost-effective equipment for radiobiological studies
Minibeam radiation therapy (MBRT) is an innovative synchrotron radiotherapy technique able to shift the normal tissue complication probability curves to significantly higher doses. However, its exploration was hindered due to the limited and expensive beamtime at...
MRI-guided radiotherapy of the SK-N-SH neuroblastoma xenograft model using a small animal radiation research platform
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...
Validating clinical practice using SARRP; simulating clinical radiotherapy in a model mimicking spontaneous occurring NSCLC
Over 60% of cancer patients worldwide will receive radiotherapy as a part of their overall treatment plan. Recently, stereotactic body radiation therapy (SBRT) has been recognized as a favorable treatment option for those cancer types that remain inoperable. SBRT administers very high doses of radiation in a small number of fractions, and has been shown to achieve 3-year control rates of roughly 90% in stage 1 NSCLC’s.
Immunotherapy and SARRP; a breakthrough investigation using a clinically relevant model to yield clinically relevant data
Pancreatic ductal adenocarcinoma (PDAC) is characteristically radioresistant tumor type with roughly 25% of patients requiring radiotherapy as form of treatment. With poor clinical outcomes (5-year survival of 7%) new and innovative treatments are required to improve patient outcome. Due to the lack of an effective treatment in the clinic for PDAC, translational research yielding clinically relevant results is necessary to develop new and effective treatment.
Stereotactic Body Radiation Therapy Delivery in a Genetically Engineered Mouse Model of Lung Cancer
Purpose To implement clinical stereotactic body radiation therapy (SBRT) using a small animal radiation research platform (SARRP) in a genetically engineered mouse model of lung cancer. Methods and Materials A murine model of multinodular Kras-driven spontaneous lung...
Tumor-derived CCL2 mediates resistance to radiotherapy in pancreatic ductal adenocarcinoma
Purpose: Local tumor growth is a major cause of morbidity and mortality in nearly 30% of patients with pancreatic ductal adenocarcinoma (PDAC). Radiotherapy (RT) is commonly used for local disease control in PDAC, but efficacy is limited. We studied the impact of...
Xstrahl SARRP features in new Bioluminescence Tomography paper
A new paper titled “Bioluminescence Tomography – Guided Radiation Therapy for Preclinical Research” has been published in the International Journal of Radiation Oncology. The Xstrahl SARRP system was used for the research conducted in the published paper, the study details how Bioluminescence has enabled researchers to precisely visualize their tumors in vivo.
Low-Intensity Focused Ultrasound Induces Reversal of Tumor-Induced T Cell Tolerance and Prevents Immune Escape.
In preclinical radiation research, it is challenging to localize soft tissue targets based on cone beam computed tomography (CBCT) guidance. As a more effective method to localize soft tissue targets, we developed an online bioluminescence tomography (BLT) system for small-animal radiation research platform (SARRP). We demonstrated BLT-guided radiation therapy and validated targeting accuracy based on a newly developed reconstruction algorithm.
Zhang B, Wang KK, Yu J, Eslami S, Iordachita I, Reyes J, Malek R, Tran PT, Patterson MS, Wong JW.
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