Jeffrey F. Williamson

Properties of preprocessed sinogram data in x-ray computed tomography

The accurate determination of x-ray signal properties is important to several computed tomography (CT) research and development areas, notably for statistical reconstruction algorithms and dose-reduction simulation. The most commonly used model of CT signal formation, assuming monoenergetic x-ray sources with quantum counting detectors obeying simple Poisson statistics, does not reflect the actual physics of CT acquisition. This paper describes a more accurate model, taking into account the energy-integrating detection process, nonuniform flux profiles, and data-conditioning processes. Methods are developed to experimentally measure and theoretically calculate statistical distributions, as well as techniques to analyze CT signal properties. Results indicate the limitations of current models and suggest improvements for the description of CT signal properties.

Improving IMRT dose accuracy via deliverable Monte Carlo optimization for the treatment of head and neck cancer patients

The purpose of this work is to investigate the effect of dose-calculation accuracy on head and neck (H&N) intensity modulated radiation therapy (IMRT) plans by determining the systematic dose-prediction and optimization-convergence errors (DPEs and OCEs), using a superposition/convolution (SC) algorithm. Ten patients with locally advanced H&N squamous cell carcinoma who were treated with simultaneous integrated boost IMRT were selected for this study. The targets consisted of gross target volume (GTV), clinical target volume (CTV), and nodal target volumes (CTV nodes). The critical structures included spinal cord, parotid glands, and brainstem. For all patients, three IMRT plans were created: A: an SC optimized plan (SCopt), B: an SCopt plan recalculated with Monte Carlo [MC(SCopt)], and C: an MC optimized plan (MCopt). For each structure, DPEs and OCEs were estimated as DPE(SC)=D(B)-D(A) and OCE(SC)=D(C)-D(B) where A, B, and C stand for the three different optimized plans as defined above. Deliverable optimization was used for all plans, that is, a leaf-sequencing step was incorporated into the optimization loop at each iteration. The range of DPE(SC) in the GTV D98 varied from -1.9% to -4.9%, while the OCE(SC) ranged from 0.9% to 7.0%. The DPE(SC) in the contralateral parotid D50 reached 8.2%, while the OCE(SC) in the contralateral parotid D50 varied from 0.91% to 6.99%. The DPE(SC) in cord D2 reached -3.0%, while the OCE(SC) reached to -7.0%. The magnitude of the DPE(SC) and OCE(SC) differences demonstrate the importance of using the most accurate available algorithm in the deliverable IMRT optimization process, especially for the estimation of normal structure doses.

A comparison of HDR brachytherapy and IMRT techniques for dose escalation in prostate cancer: A radiobiological modeling study

A course of one to three large fractions of high dose rate (HDR) interstitial brachytherapy is an attractive alternative to intensity modulated radiation therapy (IMRT) for delivering boost doses to the prostate in combination with additional external beam irradiation for intermediate risk disease. The purpose of this work is to quantitatively compare single-fraction HDR boosts to biologically equivalent fractionated IMRT boosts, assuming idealized image guided delivery (igIMRT) and conventional delivery (cIMRT). For nine prostate patients, both seven-field IMRT and HDR boosts were planned. The linear-quadratic model was used to compute biologically equivalent dose prescriptions. The cIMRT plan was evaluated as a static plan and with simulated random and setup errors. The authors conclude that HDR delivery produces a therapeutic ratio which is significantly better than the conventional IMRT and comparable to or better than the igIMRT delivery. For the HDR, the rectal gBEUD analysis is strongly influenced by high dose DVH tails. A saturation BED, beyond which no further injury can occur, must be assumed. Modeling of organ motion uncertainties yields mean outcomes similar to static plan outcomes.

A Voxel-by-Voxel Comparison of Deformable Vector Fields Obtained by Three Deformable Image Registration Algorithms Applied to 4DCT Lung Studies

Background: Commonly used methods of assessing the accuracy of deformable image registration (DIR) rely on image segmentation or landmark selection. These methods are very labor intensive and thus limited to relatively small number of image pairs. The direct voxel-by-voxel comparison can be automated to examine fluctuations in DIR quality on a long series of image pairs. Methods: A voxel-by-voxel comparison of three DIR algorithms applied to lung patients is presented. Registrations are compared by comparing volume histograms formed both with individual DIR maps and with a voxel-by-voxel subtraction of the two maps. When two DIR maps agree one concludes that both maps are interchangeable in treatment planning applications, though one cannot conclude that either one agrees with the ground truth. If two DIR maps significantly disagree one concludes that at least one of the maps deviates from the ground truth. We use the method to compare 3 DIR algorithms applied to peak inhale-peak exhale registrations of 4DFBCT data obtained from 13 patients. Results: All three algorithms appear to be nearly equivalent when compared using DICE similarity coefficients. A comparison based on Jacobian volume histograms shows that all three algorithms measure changes in total volume of the lungs with reasonable accuracy, but show large differences in the variance of Jacobian distribution on contoured structures. Analysis of voxel-by-voxel subtraction of DIR maps shows differences between algorithms that exceed a centimeter for some registrations. Conclusion: Deformation maps produced by DIR algorithms must be treated as mathematical approximations of physical tissue deformation that are not self-consistent and may thus be useful only in applications for which they have been specifically validated. The three algorithms tested in this work perform fairly robustly for the task of contour propagation, but produce potentially unreliable results for the task of DVH accumulation or measurement of local volume change. Performance of DIR algorithms varies significantly from one image pair to the next hence validation efforts, which are exhaustive but performed on a small number of image pairs may not reflect the performance of the same algorithm in practical clinical situations. Such efforts should be supplemented by validation based on a longer series of images of clinical quality.

An alternative approach to histopathological validation of PET imaging for radiation therapy image-guidance: A proof of concept

PURPOSEnIn radiotherapy, PET images can be used to guide the delivery of selectively escalated doses to biologically relevant tumour subvolumes. Validation of PET for such applications requires demonstration of spatial coincidence between PET tracer uptake pattern and the histopathologically confirmed target. This study introduces a novel approach to histopathological validation of PET image segmentation for radiotherapy guidance.nnnMETHODS AND MATERIALSnSequential tissue sections from surgically excised whole-tumour specimens were used to acquire full 3D-sets of both histopathological images (microscopy) and PET tracer distribution images (autoradiography). After these datasets were accurately registered, a full 3D autoradiographic distribution of PET tracer was reconstructed and used to obtain synthetic PET images (sPET) by simulating the image deterioration induced by processes involved in PET image formation. To illustrate the method, sPET images were used in this study to investigate spatial coincidence between high FDG uptake areas and the distribution of viable tissue in two small animal tumour models.nnnRESULTSnThe reconstructed 3D autoradiographic distribution of the PET tracer was spatially coherent, as indicated by the high average value of the normalised pixel-by-pixel correlation of intensities between successive slices (0.84 ± 0.05 and 0.94 ± 0.02). The loss of detail in the sPET images versus the 3D autoradiography was significant as indicated by Dice coefficient values corresponding to the two tumours (0 and 0.1 at 70% threshold). The maximum overlap between the FDG segmented volumes and the extent of the viable tissue as indicated by Dice coefficient values, was 0.8 for one tumour (for the image thresholded at 22% of max intensity) and 0.88 for the other (threshold of 14% of max intensity).nnnCONCLUSIONnIt was demonstrated that the use of synthetic PET images for histopathological validation allows for bypassing a technically challenging and error-prone step of registering non-invasive PET images with histopathology.

Tumour microenvironment heterogeneity affects the perceived spatial concordance between the intratumoural patterns of cell proliferation and 18F-fluorothymidine uptake

BACKGROUND AND PURPOSEnPET imaging with (18)F-fluorothymidine ((18)F-FLT) can potentially be used to identify tumour subvolumes for selective dose escalation in radiation therapy. The purpose of this study is to analyse the co-localization of intratumoural patterns of cell proliferation with (18)F-FLT tracer uptake.nnnMATERIALS AND METHODSnMice bearing FaDu or SQ20B xenograft tumours were injected with (18)F-FLT, and bromodeoxyuridine (proliferation marker). Ex vivo images of the spatial pattern of intratumoural (18)F-FLT uptake and that of bromodeoxyuridine DNA incorporation were obtained from thin tumour tissue sections. These images were segmented by thresholding and Relative Operating Characteristic (ROC) curves and Dice similarity indices were evaluated.nnnRESULTSnThe thresholds at which maximum overlap occurred between FLT-segmented areas and areas of active cell proliferation were significantly different for the two xenograft tumour models, whereas the median Dice values were not. However, ROC analysis indicated that segmented FLT images were more specific at detecting the proliferation pattern in FaDu tumours than in SQ20B tumours.nnnCONCLUSIONnHighly dispersed patterns of cell proliferation observed in certain tumours can affect the perceived spatial concordance between the spatial pattern of (18)F-FLT uptake and that of cell proliferation even when high-resolution ex vivo autoradiography imaging is used for (18)F-FLT imaging.