Purpose:: The aim of this study was to evaluate the appropriateness of using computed tomography (CT) to cone‐beam CT (CBCT) deformable image registration (DIR) for the application of calculating the “dose of the day” received by a head and neck patient.Methods:: NiftyReg is an open‐source registration package implemented in our institution. The affine registration uses a Block Matching‐based approach, while the deformable registration is a GPU implementation of the popular B‐spline Free Form Deformation algorithm. Two independent tests were performed to assess the suitability of our registrations methodology for “dose of the day” calculations in a deformed CT. A geometric evaluation was performed to assess the ability of the DIR method to map identical structures between the CT and CBCT datasets. Features delineated in the planning CT were warped and compared with features manually drawn on the CBCT. The authors computed the dice similarity coefficient (DSC), distance transformation, and centre of mass distance between features. A dosimetric evaluation was performed to evaluate the clinical significance of the registrations errors in the application proposed and to identify the limitations of the approximations used. Dose calculations for the same intensity‐modulated radiation therapy plan on the deformed CT and replan CT were compared. Dose distributions were compared in terms of dose differences (DD), gamma analysis, target coverage, and dose volume histograms (DVHs). Doses calculated in a rigidly aligned CT and directly in an extended CBCT were also evaluated.Results:: A mean value of 0.850 in DSC was achieved in overlap between manually delineated and warped features, with the distance between surfaces being less than 2 mm on over 90% of the pixels. Deformable registration was clearly superior to rigid registration in mapping identical structures between the two datasets. The dose recalculated in the deformed CT is a good match to the dose calculated on a replan CT. The DD is smaller than 2% of the prescribed dose on 90% of the bodyˈs voxels and it passes a 2% and 2 mm gamma‐test on over 95% of the voxels. Target coverage similarity was assessed in terms of the 95%‐isodose volumes. A mean value of 0.962 was obtained for the DSC, while the distance between surfaces is less than 2 mm in 95.4% of the pixels. The method proposed provided adequate dose estimation, closer to the gold standard than the other two approaches. Differences in DVH curves were mainly due to differences in the OARs definition (manual vs warped) and not due to differences in dose estimation (dose calculated in replan CT vs dose calculated in deformed CT).Conclusions:: Deforming a planning CT to match a daily CBCT provides the tools needed for the calculation of the “dose of the day” without the need to acquire a new CT. The initial clinical application of our method will be weekly offline calculations of the “dose of the day,” and use this information to inform adaptive radiotherapy (ART). The work here presented is a first step into a full implementation of a “dose‐driven” online ART.

An adaptive proton therapy workflow using cone beam computed tomography (CBCT) is proposed. It consists of an online evaluation of a fast range-corrected dose distribution based on a virtual CT (vCT) scan. This can be followed by more accurate offline dose recalculation on the vCT scan, which can trigger a rescan CT (rCT) for replanning. The workflow was tested retrospectively for 20 consecutive lung cancer patients. A diffeomorphic Morphon algorithm was used to generate the lung vCT by deforming the average planning CT onto the CBCT scan. An additional correction step was applied to account for anatomic modifications that cannot be modeled by deformation alone. A set of clinical indicators for replanning were generated according to the water equivalent thickness (WET) and dose statistics and compared with those obtained on the rCT scan. The fast dose approximation consisted of warping the initial planned dose onto the vCT scan according to the changes in WET. The potential under- and over-ranges were assessed as a variation in WET at the target's distal surface. The range-corrected dose from the vCT scan reproduced clinical indicators similar to those of the rCT scan. The workflow performed well under different clinical scenarios, including atelectasis, lung reinflation, and different types of tumor response. Between the vCT and rCT scans, we found a difference in the measured 95% percentile of the over-range distribution of 3.4 ± 2.7 mm. The limitations of the technique consisted of inherent uncertainties in deformable registration and the drawbacks of CBCT imaging. The correction step was adequate when gross errors occurred but could not recover subtle anatomic or density changes in tumors with complex topology. A proton therapy workflow based on CBCT provided clinical indicators similar to those using rCT for patients with lung cancer with considerable anatomic changes.

Measurements of breast tissue scattering properties have been made in an energy dispersive x-ray diffraction system over the momentum transfer range of 0.70 to 3.50 nm(-1). One hundred samples of excised tissue have been used. Results from the diffraction system have been compared with the histological analysis for each individual sample. It has been found that tissue types can be characterized on the basis of the shape of the scatter spectrum and on its relative intensity. The shapes are significantly different between tissue types in the range 1.0 to 1.8 nm(-1) and suggest that if particular values of momentum transfer are monitored, a discriminating signal could be obtained. Analysis of the maximum intensity in the signature also reveals a change of up to a factor of 2 between adipose and fat-free tissues.

Purpose: The aims of this work were to evaluate the performance of several deformable image registration (DIR) algorithms implemented in our in‐house software (NiftyReg) and the uncertainties inherent to using different algorithms for dose warping.Methods: The authors describe a DIR based adaptive radiotherapy workflow, using CT and cone‐beam CT (CBCT) imaging. The transformations that mapped the anatomy between the two time points were obtained using four different DIR approaches available in NiftyReg. These included a standard unidirectional algorithm and more sophisticated bidirectional ones that encourage or ensure inverse consistency. The forward (CT‐to‐CBCT) deformation vector fields (DVFs) were used to propagate the CT Hounsfield units and structures to the daily geometry for “dose of the day” calculations, while the backward (CBCT‐to‐CT) DVFs were used to remap the dose of the day onto the planning CT (pCT). Data from five head and neck patients were used to evaluate the performance of each implementation based on geometrical matching, physical properties of the DVFs, and similarity between warped dose distributions. Geometrical matching was verified in terms of dice similarity coefficient (DSC), distance transform, false positives, and false negatives. The physical properties of the DVFs were assessed calculating the harmonic energy, determinant of the Jacobian, and inverse consistency error of the transformations. Dose distributions were displayed on the pCT dose space and compared using dose difference (DD), distance to dose difference, and dose volume histograms.Results: All the DIR algorithms gave similar results in terms of geometrical matching, with an average DSC of 0.85 ± 0.08, but the underlying properties of the DVFs varied in terms of smoothness and inverse consistency. When comparing the doses warped by different algorithms, we found a root mean square DD of 1.9% ± 0.8% of the prescribed dose (pD) and that an average of 9% ± 4% of voxels within the treated volume failed a 2%pD DD‐test (DD_2%‐pp). Larger DD_2%‐pp was found within the high dose gradient (21% ± 6%) and regions where the CBCT quality was poorer (28% ± 9%). The differences when estimating the mean and maximum dose delivered to organs‐at‐risk were up to 2.0%pD and 2.8%pD, respectively.Conclusions: The authors evaluated several DIR algorithms for CT‐to‐CBCT registrations. In spite of all methods resulting in comparable geometrical matching, the choice of DIR implementation leads to uncertainties in dose warped, particularly in regions of high gradient and/or poor imaging quality.

A new potential quality assurance (QA) method is explored (including assessment of depth dose, dose linearity, dose rate linearity and beam profile) for clinical electron beams based on imaging Cerenkov light. The potential of using a standard commercial camera to image Cerenkov light generated from electrons in water for fast QA measurement of a clinical electron beam was explored and compared to ionization chamber measurements. The new method was found to be linear with dose and independent of dose rate (to within 3%). The uncorrected practical range measured in Cerenkov images was found to overestimate the actual value by 3 mm in the worst case. The field size measurements underestimated the dose at the edges by 5% without applying any correction factor. Still, the measured field size could be used to monitor relative changes in the beam profile. Finally, the beam-direction profile measurements were independent of the field size within 2%. A simulation was also performed of the deposited energy and of Cerenkov production in water using GEANT4. Monte Carlo simulation was used to predict the measured light distribution around the water phantom, to reproduce Cerenkov images and to find the relation between deposited energy and Cerenkov production. The camera was modelled as a pinhole camera in GEANT4, to attempt to reproduce Cerenkov images. Simulations of the deposited energy and the Cerenkov light production agreed with each other for a pencil beam of electrons, while for a realistic field size, Cerenkov production in the build-up region overestimated the dose by +8%.