Quantitative validation of deformable image registration (DIR) algorithms is extremely difficult because of the complexity involved in constructing a deformable phantom that can duplicate various clinical scenarios. The purpose of this study is to describe a framework to test the accuracy of DIR based on computational modeling and evaluating using inverse consistency and other methods. Three clinically relevant organ deformations were created in prostate (distended rectum and rectal gas), head and neck (large neck flexion), and lung (inhale and exhale lung volumes with variable contrast enhancement) study sets. DIR was performed using both B‐spline and diffeomorphic demons algorithms in the forward and inverse direction. A compositive accumulation of forward and inverse deformation vector fields was done to quantify the inverse consistency error (ICE). The anatomical correspondence of tumor and organs at risk was quantified by comparing the original RT structures with those obtained after DIR. Further, the physical characteristics of the deformation field, namely the Jacobian and harmonic energy, were computed to quantify the preservation of image topology and regularity of spatial transformation obtained in DIR. The ICE was comparable in prostate case but the B‐spline algorithm had significantly better anatomical correspondence for rectum and prostate than diffeomorphic demons algorithm. The ICE was 6.5 mm for demons algorithm for head and neck case when compared to 0.7 mm for B‐spline. Since the induced neck flexion was large, the average Dice similarity coefficient between both algorithms was only 0.87, 0.52, 0.81, and 0.67 for tumor, cord, parotids, and mandible, respectively. The B‐spline algorithm accurately estimated deformations between images with variable contrast in our lung study, while diffeomorphic demons algorithm led to gross errors on structures affected by contrast variation. The proposed framework offers the application of known deformations on any image datasets, to evaluate the overall accuracy and limitations of a DIR algorithm used in radiation oncology. The evaluation based on anatomical correspondence, physical characteristics of deformation field, and image characteristics can facilitate DIR verification with the ultimate goal of implementing adaptive radiotherapy. The suitability of application of a particular evaluation metric in validating DIR is dependent on the clinical deformation observed.PACS numbers: 87.57 nj, 87.55‐x,87.55 Qr

The primary application of Image‐Guided Radiotherapy (IGRT) in the treatment of localized prostate cancer has been to assist precise dose delivery to the tumor. With the ability to use in‐room Computed Tomography (CT) imaging modalities, the prostate, bladder and rectum can be imaged before each treatment and the actual doses delivered to these organs can be tracked using anatomy of the day. This study evaluates the dosimetric uncertainties caused by interfraction organ variation during IGRT for 10 patients using kilovoltage cone beam CT (kvCBCT) on the Elekta Synergy system and megavoltage CT (MVCT) on the TomoTherapy Hi·Art System. The actual delivered doses to the prostate, bladder and rectum were based on dose recomputation using CT anatomy of the day. The feasibility of dose calculation accuracy in kvCBCT images from the Elekta Synergy system was investigated using the ComTom phantom. Additionally, low contrast resolution, image uniformity, and spatial resolution between the three imaging modalities of kilovoltage CT (kvCT), kvCBCT and MVCT images, were quantitatively evaluated using the Catphan 600 phantom. The Planned Adaptive software was used on the TomoTherapy Hi·Art system to construct a cumulative Dose Volume Histogram (DVH), incorporating anatomical information provided by the daily MVCT scans. The cumulative DVH was examined to identify large deviation (10% or greater) between the planned and delivered mean doses. The study proposes a framework that applies the cumulative DVH to evaluate and adapt plans that are based on actual delivered doses. Due to the large deviation in CT number (›300 HU) between the kvCBCT images and the kvCT, a direct dose recomputation on the kvCBCT images from the Elekta Synergy system was found to be inaccurate. The maximum deviation to the prostate was only 2.7% in our kvCBCT study, when compared to the daily prescribed dose. However, there was a large daily variation in rectum and bladder doses based on the anatomy of the day. The maximum variation in rectum and bladder volumes receiving the percentage of prescribed dose was 12% and 40%, respectively. We have shown that by using Planned Adaptive software on the TomoTherapy Hi·Art system, plans can be adapted based on the image feedback from daily MVCT scans to allow the actual delivered doses to closely track the original planned doses.PACS number: 87.53.Tf

The feasibility of using dual bias metal oxide semiconductor field effect transistor (MOSFET) detectors with the new hemispherical brass buildup cap for in vivo dose measurements in prostate intensity‐modulated radiotherapy (IMRT) treatments was investigated and achieved. In this work, MOSFET detectors with brass buildup caps placed on the patient's skin surface on the central axis of the individual IMRT beams are used to determine the maximum entrance dose (Dmax) from the prostate IMRT fields. A general formalism with various correction factors taken into account to predict Dmax entrance dose for the IMRT fields with MOSFETs was developed and compared against predicted dose from the treatment‐planning system (TPS). We achieved an overall accuracy of better than ±5% on all measured fields for both 6‐MV and 10‐MV beams when compared to predicted doses from the Philips Pinnacle 3 and CMS XiO TPSs, respectively. We also estimate the total uncertainty in estimation of MOSFET dose in the high‐sensitivity mode for IMRT therapy to be 4.6%.PACS numbers: 87.53Xd, 87.56Fc

The limits of applicability of DIR are strongly dependent on the magnitude of deformation. There is a threshold limit beyond which the accuracy of DIR fails in uniform low contrast anatomy. The sensitivity of the DIR performance to the number of fiducial markers present indicates that if DIR performance is solely assessed with the contrast rich features present in clinical anatomy, the results may not be reflective of the true DIR performance in uniform low contrast anatomy.