Purpose To examine the potential use of BOLD (Blood Oxygenation Level Dependent) and TOLD (Tissue Oxygenation Level Dependent) contrast MRI to assess tumor oxygenation and predict radiation response. Methods BOLD and TOLD MRI were performed on Dunning R3327-AT1 rat prostate tumors during hyperoxic gas breathing challenge at 4.7 T. Animals were divided into two groups. In Group 1 (n=9), subsequent 19F MRI based on spin lattice relaxation of hexafluorobenzene reporter molecule provided quantitative oximetry for comparison. For Group 2 rats (n=13) growth delay following a single dose of 30 Gy was compared with pre-irradiation BOLD and TOLD assessments. Results Oxygen (100%O2) and carbogen (CB; 95%O2/5%CO2) challenge elicited similar BOLD, TOLD and pO2 responses. Strong correlations were observed between BOLD or R2* response and quantitative 19F pO2 measurements. TOLD response showed a general trend with weaker correlation. Irradiation caused a significant tumor growth delay and tumors with larger changes in TOLD and R1 values upon oxygen breathing exhibited significantly increased tumor growth delay. Conclusion These results provide further insight into the relationships between oxygen sensitive (BOLD/TOLD) MRI and tumor pO2. Moreover, a larger increase in R1 response to hyperoxic gas challenge coincided with greater tumor growth delay following irradiation.
Radiation dose is central to much of radiobiological research. Precision and accuracy of dose measurements and reporting of the measurement details should be sufficient to allow the work to be interpreted and repeated and to allow valid comparisons to be made, both in the same laboratory and by other laboratories. Despite this, a careful reading of published manuscripts suggests that measurement and reporting of radiation dosimetry and setup for radiobiology research is frequently inadequate, thus undermining the reliability and reproducibility of the findings. To address these problems and propose a course of action, the National Cancer Institute (NCI), the National Institute of Allergy and Infectious Diseases (NIAID), and the National Institute of Standards and Technology (NIST) brought together representatives of the radiobiology and radiation physics communities in a workshop in September, 2011. The workshop participants arrived at a number of specific recommendations as enumerated in this paper and they expressed the desirability of creating dosimetry standard operating procedures (SOPs) for cell culture and for small and large animal experiments. It was also felt that these SOPs would be most useful if they are made widely available through mechanism(s) such as the web, where they can provide guidance to both radiobiologists and radiation physicists, be cited in publications, and be updated as the field and needs evolve. Other broad areas covered were the need for continuing education through tutorials at national conferences, and for journals to establish standards for reporting dosimetry. This workshop did not address issues of dosimetry for studies involving radiation focused at the sub-cellular level, internally-administered radionuclides, biodosimetry based on biological markers of radiation exposure, or dose reconstruction for epidemiological studies.
Accurate and automatic brain metastases target delineation is a key step for efficient and effective stereotactic radiosurgery (SRS) treatment planning. In this work, we developed a deep learning convolutional neural network (CNN) algorithm for segmenting brain metastases on contrast-enhanced T1-weighted magnetic resonance imaging (MRI) datasets. We integrated the CNN-based algorithm into an automatic brain metastases segmentation workflow and validated on both Multimodal Brain Tumor Image Segmentation challenge (BRATS) data and clinical patients' data. Validation on BRATS data yielded average DICE coefficients (DCs) of 0.75±0.07 in the tumor core and 0.81±0.04 in the enhancing tumor, which outperformed most techniques in the 2015 BRATS challenge. Segmentation results of patient cases showed an average of DCs 0.67±0.03 and achieved an area under the receiver operating characteristic curve of 0.98±0.01. The developed automatic segmentation strategy surpasses current benchmark levels and offers a promising tool for SRS treatment planning for multiple brain metastases.
A novel small animal conformal radiation therapy system has been designed and prototyped: MicroRT. The microRT system integrates multimodality imaging, radiation treatment planning, and conformal radiation therapy that utilizes a clinical 192Ir isotope high dose rate source as the radiation source (teletherapy). A multiparameter dose calculation algorithm based on Monte Carlo dose distribution simulations is used to efficiently and accurately calculate doses for treatment planning purposes. A series of precisely machined tungsten collimators mounted onto a cylindrical collimator assembly is used to provide the radiation beam portals. The current design allows a source-to-target distance range of 1-8 cm at four beam angles: 0 degrees (beam oriented down), 90 degrees, 180 degrees, and 270 degrees. The animal is anesthetized and placed in an immobilization device with built-in fiducial markers and scanned using a computed tomography, magnetic resonance, or positron emission tomography scanner prior to irradiation. Treatment plans using up to four beam orientations are created utilizing a custom treatment planning system-microRTP. A three-axis computer-controlled stage that supports and accurately positions the animals is programmed to place the animal relative to the radiation beams according to the microRTP plan. The microRT system positioning accuracy was found to be submillimeter. The radiation source is guided through one of four catheter channels and placed in line with the tungsten collimators to deliver the conformal radiation treatment. The microRT hardware specifications, the accuracy of the treatment planning and positioning systems, and some typical procedures for radiobiological experiments that can be performed with the microRT device are presented.
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