Purpose:MRI‐guided radiation therapy (RT) delivery would be beneficial for breast irradiation. The electron return effect due to the presence of a transverse magnetic field (TMF) may cause dosimetric issues on dose on skin and at the lung‐tissue interface. The purpose of this study is to investigate these issues.Methods:IMRT plans with tangential beams and VMAT plans with 200 degree arcs to cover ipsilateral breast were generated for 10 randomly selected breast cancer cases using a research planning system (Monaco, Elekta) utilizing Monte Carlo dose calculation with or without a TMF of 1.5 T. Plans were optimized to deliver uniform dose to the whole breast with an exclusion of 5 mm tissue under the skin (PTV‐EVAL). All four plans for each patient were re‐scaled to have the same PTV‐EVAL volume to receive the same prescription dose. The skin is defined as the first 5 mm of ipsilateral‐breast tissue, plus extensions in the surrounding region.Results:The presence of 1.5 T TMF resulted in (1)increased skin dose, with the mean and maximum skin dose increase of 5% and 9%, respectively; (2) similar dose homogeneity within the PTV‐EVAL; (3) the slightly improved (3%) dose homogeneity in the whole breast; (4) Averages of 9 and 16% increases in V5 and V20, respectively, for ipsilateral lung; and (5) increased the mean heart dose by 34%. VMAT plans don't improve whole breast dose uniformity as compared that to the tangential plans.Conclusion:The presence of transverse magnetic field in MRI‐guided RT delivery for whole breast irradiation can Result in slightly improved dose homogeneity in the whole breast, increased dose to the ipsilateral lung, heart, and skin. Plan optimization with additional specific dose volume constraints may eliminate/reduce these dose increases.This work is partially supported by Elekta Inc.

Purpose: : To investigate dosimetric differences between MRI- and CT-based IMRT planning for prostate cancer, the impact of a magnetic field in a MRI-Linac, and to explore the feasibility of IMRT planning based on MRI alone. Methods: IMRT plans were generated based on CT and MRI images acquired on two representative prostate-cancer patients using clinical dose volume constraints. A research planning system (Monaco, Elekta), which employs a Monte Carlo dose engine and includes a perpendicular magnetic field of 1.5T from an MRI-Linac, was used. Bulk electron density assignments based on organ-specific values from ICRU 46 were used to convert MRI (T2) to pseudo CT. With the same beam configuration as in the original CT plan, 5 additional plans were generated based on CT or MRI, with or without optimization (i.e., just recalculation) and with or without the magnetic field. The plan quality in terms of commonly used dose volume (DV) parameters for all plans was compared. The statistical uncertainty on dose was < 1%. Results: For plans with the same contour set but without re-optimization, the DV parameters were different from those for the original CT plan, mostly less than 5% with a few exceptions. These differences were reduced to mostly less than 3% when the plans were re-optimized. For plans with contours from MRI, the differences in the DV parameters varied depending on the difference in the contours as compared to CT. For the optimized plans with contours from MR, the differences for PTV were less than 3%. Conclusion: The prostate IMRT plans based on MRI-only for a MR-Linac were practically similar as compared to the CT plan under the same beam and optimization configuration if the difference on the structure delineation is excluded, indicating the feasibility of using MRI-only for prostate IMRT.

Purpose:In skin‐cancer radiotherapy, the assessment of skin lesion is challenging, particularly with important features such as the depth and width hard to determine. The aim of this study is to develop interative segmentation method to delineate tumor boundary using high‐frequency ultrasound images and to correlate the segmentation results with the histopathological tumor dimensions.Methods:We analyzed 6 patients who comprised a total of 10 skin lesions involving the face, scalp, and hand. The patient’s various skin lesions were scanned using a high‐frequency ultrasound system (Episcan, LONGPORT, INC., PA, U.S.A), with a 30‐MHz single‐element transducer. The lateral resolution was 14.6 micron and the axial resolution was 3.85 micron for the ultrasound image. Semiautomatic image segmentation was performed to extract the cancer region, using a robust statistics driven active contour algorithm. The corresponding histology images were also obtained after tumor resection and served as the reference standards in this study.Results:Eight out of the 10 lesions are successfully segmented. The ultrasound tumor delineation correlates well with the histology assessment, in all the measurements such as depth, size, and shape. The depths measured by the ultrasound have an average of 9.3% difference comparing with that in the histology images. The remaining 2 cases suffered from the situation of mismatching between pathology and ultrasound images.Conclusion:High‐frequency ultrasound is a noninvasive, accurate and easy‐accessible modality to image skin cancer. Our segmentation method, combined with high‐frequency ultrasound technology, provides a promising tool to estimate the extent of the tumor to guide the radiotherapy procedure and monitor treatment response.

Purpose: Radiobiologically adaptive radiation therapy (RT) has not been used, largely, because the patient/tumor/organ specific radiobiological parameters are difficult to obtain. We introduce a method to extract such parameters for lung cancer based on the PET/CT data acquired before and during RT. Methods: Changes in lung tumor volume measured from PET/CT data acquired before and during RT were analyzed by a two-component model, assuming that lung tumor cells comprise both radiosensitive and radioresistant components. This model consists of 4 major parameters: radiosensitivity parameter as, potential doubling time for the radiosensitive cells Tp, initial fraction of radioresistant cells h, and the disintegration half-life of radiation-damaged cells (Td). The parameter h can be determined using the pre-treatment PET with Fluoromisonidazoles. The tumor volume change measured with PET provides a strong constraint to as and Tp because it does not depend on the disintegration process. The model was used to determine the patient specific radiobiologically optimal dose and fractionation for the remaining part of RT using the model parameters determined for the patient. The method was tested using the data from 6 lung cancer patients. Results: Significant variations of the model parameters were found between patients. For example, for the patient data studied, as varies between 0.031 to 0.091 Gy-1, the potential doubling time changes from 14 to 26 days and Td varied from 3.6 and 90 days. The calculated optimal doses and/or fractionations for the remaining part of RT based on the patient specific model parameters are also patient specific, varying by 50% for the data considered. Conclusions: The change in lung tumor volume observed from PET/CT in the early part of RT provides a means to probe radiobiological properties of the tumor, allowing the delivery of individualized, radiobiologically adaptive RT in the remaining course of the treatment.