Andrei Pugachev

ROLE OF BEAM ORIENTATION OPTIMIZATION IN INTENSITY- MODULATED RADIATION THERAPY

PURPOSE To investigate the role of beam orientation optimization in intensity-modulated radiation therapy (IMRT) and to examine the potential benefits of noncoplanar intensity-modulated beams. METHODS AND MATERIALS A beam orientation optimization algorithm was implemented. For this purpose, system variables were divided into two groups: beam position (gantry and table angles) and beam profile (beamlet weights). Simulated annealing was used for beam orientation optimization and the simultaneous iterative inverse treatment planning algorithm (SIITP) for beam intensity profile optimization. Three clinical cases were studied: a localized prostate cancer, a nasopharyngeal cancer, and a paraspinal tumor. Nine fields were used for all treatments. For each case, 3 types of treatment plan optimization were performed: (1) beam intensity profiles were optimized for 9 equiangular spaced coplanar beams; (2) orientations and intensity profiles were optimized for 9 coplanar beams; (3) orientations and intensity profiles were optimized for 9 noncoplanar beams. RESULTS For the localized prostate case, all 3 types of optimization described above resulted in dose distributions of a similar quality. For the nasopharynx case, optimized noncoplanar beams provided a significant gain in the gross tumor volume coverage. For the paraspinal case, orientation optimization using noncoplanar beams resulted in better kidney sparing and improved gross tumor volume coverage. CONCLUSION The sensitivity of an IMRT treatment plan with respect to the selection of beam orientations varies from site to site. For some cases, the choice of beam orientations is important even when the number of beams is as large as 9. Noncoplanar beams provide an additional degree of freedom for IMRT treatment optimization and may allow for notable improvement in the quality of some complicated plans.

Pseudo beam's-eye-view as applied to beam orientation selection in intensity-modulated radiation therapy.

PURPOSE To introduce the concept of pseudo beams-eye-view (pBEV), to establish a framework for computer-assisted beam orientation selection in intensity-modulated radiation therapy (IMRT), and to evaluate the utility of the proposed technique. METHODS AND MATERIALS To facilitate the selection of beam orientations for IMRT treatment planning, a scoring of beam direction was introduced. The score function was based on the maximum target dose deliverable by the beam without exceeding the tolerance doses of the critical structures. For the score function calculation, the beam portal at given gantry and couch angles was divided into a grid of beamlets. Each beamlet crossing the target was assigned the maximum intensity that could be used without exceeding the dose tolerances of the organs at risk (OARs) and normal tissue. Thereafter, a score was assigned to the beam according to the target dose delivered. The beams for the treatment were selected among those with the highest scores. In a sense, this technique is similar to the beams-eye-view approach used in conventional radiation therapy, except that the evaluation by a human is replaced by a score function, and beam modulation is taken into account. RESULTS The pBEV technique was tested on two clinical cases: a paraspinal treatment and a nasopharyngeal cancer with both coplanar and noncoplanar beam configurations. The plans generated under the guidance of pBEV for the paraspinal treatment offered superior target dose uniformity and reduced OAR doses. For the nasopharyngeal cancer case, it was also found that the pBEV-selected coplanar and noncoplanar beams significantly improved the target coverage without compromising the sparing of the OARs. CONCLUSIONS The pBEV technique developed in this work provides a comprehensive tool for beam orientation selection in IMRT. It is especially valuable for complicated cases, where the target is surrounded by several sensitive structures and where it is difficult to select a set of good beam orientations. The pBEV technique has considerable potential for simplifying the IMRT treatment planning process and for maximizing the technical capacity of IMRT.

Beam orientation optimization in intensity-modulated radiation treatment planning.

Beam direction optimization is an important problem in radiation therapy. In intensity modulated radiation therapy (IMRT), the difficulty for computer optimization of the beam directions arises from the fact that they are coupled with the intensity profiles of the incident beams. In order to obtain the optimal incident beam directions using iterative or stochastic methods, the beam profiles ought to be optimized after every change of beam configuration. In this paper we report an effective algorithm to optimize gantry angles for IMRT. In our calculation the gantry angles and the beam profiles (beamlet weights) were treated as two separate groups of variables. The gantry angles were sampled according to a simulated annealing algorithm. For each sampled beam configuration, beam profile calculation was done using a fast filtered backprojection (FBP) method. Simulated annealing was also used for beam profile optimization to examine the performance of the FBP for beam orientation optimization. Relative importance factors were incorporated into the objective function to control the relative importance of the target and the sensitive structures. Minimization of the objective function resulted in the best possible beam orientations and beam profiles judged by the given objective function. The algorithm was applied to several model problems and the results showed that the approach has potential for IMRT applications.

Estimation theory and model parameter selection for therapeutic treatment plan optimization

Treatment optimization is usually formulated as an inverse problem, which starts with a prescribed dose distribution and obtains an optimized solution under the guidance of an objective function. The solution is a compromise between the conflicting requirements of the target and sensitive structures. In this paper, the treatment plan optimization is formulated as an estimation problem of a discrete and possibly nonconvex system. The concept of preference function is introduced. Instead of prescribing a dose to a structure (or a set of voxels), the approach prioritizes the doses with different preference levels and reduces the problem into selecting a solution with a suitable estimator. The preference function provides a foundation for statistical analysis of the system and allows us to apply various techniques developed in statistical analysis to plan optimization. It is shown that an optimization based on a quadratic objective function is a special case of the formalism. A general two-step method for using a computer to determine the values of the model parameters is proposed. The approach provides an efficient way to include prior knowledge into the optimization process. The method is illustrated using a simplified two-pixel system as well as two clinical cases. The generality of the approach, coupled with promising demonstrations, indicates that the method has broad implications for radiotherapy treatment plan optimization.

Classification and evaluation strategies of auto-segmentation approaches for PET: Report of AAPM task group No. 211

Purpose The purpose of this educational report is to provide an overview of the present state‐of‐the‐art PET auto‐segmentation (PET‐AS) algorithms and their respective validation, with an emphasis on providing the user with help in understanding the challenges and pitfalls associated with selecting and implementing a PET‐AS algorithm for a particular application. Approach A brief description of the different types of PET‐AS algorithms is provided using a classification based on method complexity and type. The advantages and the limitations of the current PET‐AS algorithms are highlighted based on current publications and existing comparison studies. A review of the available image datasets and contour evaluation metrics in terms of their applicability for establishing a standardized evaluation of PET‐AS algorithms is provided. The performance requirements for the algorithms and their dependence on the application, the radiotracer used and the evaluation criteria are described and discussed. Finally, a procedure for algorithm acceptance and implementation, as well as the complementary role of manual and auto‐segmentation are addressed. Findings A large number of PET‐AS algorithms have been developed within the last 20 years. Many of the proposed algorithms are based on either fixed or adaptively selected thresholds. More recently, numerous papers have proposed the use of more advanced image analysis paradigms to perform semi‐automated delineation of the PET images. However, the level of algorithm validation is variable and for most published algorithms is either insufficient or inconsistent which prevents recommending a single algorithm. This is compounded by the fact that realistic image configurations with low signal‐to‐noise ratios (SNR) and heterogeneous tracer distributions have rarely been used. Large variations in the evaluation methods used in the literature point to the need for a standardized evaluation protocol. Conclusions Available comparison studies suggest that PET‐AS algorithms relying on advanced image analysis paradigms provide generally more accurate segmentation than approaches based on PET activity thresholds, particularly for realistic configurations. However, this may not be the case for simple shape lesions in situations with a narrower range of parameters, where simpler methods may also perform well. Recent algorithms which employ some type of consensus or automatic selection between several PET‐AS methods have potential to overcome the limitations of the individual methods when appropriately trained. In either case, accuracy evaluation is required for each different PET scanner and scanning and image reconstruction protocol. For the simpler, less robust approaches, adaptation to scanning conditions, tumor type, and tumor location by optimization of parameters is necessary. The results from the method evaluation stage can be used to estimate the contouring uncertainty. All PET‐AS contours should be critically verified by a physician. A standard test, i.e., a benchmark dedicated to evaluating both existing and future PET‐AS algorithms needs to be designed, to aid clinicians in evaluating and selecting PET‐AS algorithms and to establish performance limits for their acceptance for clinical use. The initial steps toward designing and building such a standard are undertaken by the task group members.

Comprehensive Approach to Coregistration of Autoradiography and Microscopy Images Acquired from a Set of Sequential Tissue Sections

Histopathologic validation of a PET tracer requires assessment of colocalization of the tracer with its intended biologic target. Using thin tissue section autoradiography, it is possible to visualize the spatial distribution of the PET tracer uptake and compare it with the distribution of the intended biologic target (as visualized with immunohistochemistry). The purpose of this study was to develop and evaluate an objective methodology for deformable coregistration of autoradiography and microscopy images acquired from a set of sequential tissue sections. Methods: Tumor-bearing animals were injected with 3′-deoxy-3′-18F-fluorothymidine (18F-FLT), 14C-FDG, and other markers of tumor microenvironment including Hoechst 33342 (blood-flow surrogate). After sacrifice, tumors were excised, frozen, and sectioned. Multiple stacks of sequential 8 μm sections were collected from each tumor. From each stack, the middle (reference) sections were used to obtain images of 18F-FLT and 14C-FDG uptake distributions using dual-tracer autoradiography. Sections adjacent to the reference were used to acquire all histopathologic data (e.g., images of cell proliferation, hematoxylin and eosin). Hoechst images were acquired from all sections. To correct for deformations and misalignments induced by tissue processing and image acquisition, the Hoechst image of each nonreference section was deformably registered to the reference Hoechst image. This transformation was then applied to all images acquired from the same tissue section. In this way, all microscopy images were registered to the reference Hoechst image. The Hoechst-to-autoradiography image registration was done using rigid point-set registration based on external markers visible in both images. Results: The mean error of Hoechst to 18F-FLT autoradiography registration (both images acquired from the same section) was 30.8 ± 20.1 μm. The error of Hoechst-based deformable registration of histopathologic images (acquired from sequential tissue sections) was 23.1 ± 17.9 μm. Total error of registration of autoradiography images to the histopathologic images acquired from adjacent sections was evaluated at 44.9 μm. This coregistration precision supersedes current rigid registration methods with reported errors of 100–200 μm. Conclusion: Deformable registration of autoradiography and histopathology images acquired from sequential sections is feasible and accurate when performed using corresponding Hoechst images.

Examination of the effect of increasing the number of radiation beams on a radiation treatment plan

Within the confines of least-squares operations, it is possible to quantify the effect of the addition of treatment fields or beamlets to a treatment plan. Using linear algebra and eigenvalue perturbation theory, the effect of the increase in number of treatments is shown to be equivalent to adding a perturbation operator. The effect of adding additional fields will be negligible if the perturbation operator is small. The correspondence of this approach to an earlier work in beam-orientation optimization is also demonstrated. Results are presented for prostate, spinal and head and neck cases, and the connection to beam-orientation optimization is examined.

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

PURPOSE In 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. METHODS AND MATERIALS Sequential 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. RESULTS The 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). CONCLUSION It 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 PURPOSE PET 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. MATERIALS AND METHODS Mice 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. RESULTS The 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. CONCLUSION Highly 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.

On autoradiographic studies comparing the distributions of 18F- and 14C-labeled compounds in tumor tissue specimens

To the Editor, We read with great interest the paper by Christian et al. [1] where the authors studied the degree of concordance between the spatial patterns of F-FDG and C-EF3 uptake in SCCVII and FSAII tumors using the dice similarity index. Although the study was meticulously performed, there are several concerns with the methodology that we believe are worth mentioning herein. The authors state they used 1 mm-thick slab of tissue to perform F-FDG and C-EF3 autoradiography. To selectively image F-FDG uptake, a layer of plastic was inserted between the tissue and the phosphor plate. This layer was sufficiently thick to block the low-energy electrons emitted by C (maximum energy 156 keV, range 0.28 mm), while allowing higher energy positrons emitted by F to penetrate. Since the maximum range of b emitted by F is 2 mm (maximum energy 634 keV), the F autoradiographic image is formed by the positrons emitted by F-FDG trapped throughout the whole 1 mm-thick slab of tissue, as was also observed in another study by Christian et al. [2]. Following complete decay of F, C-EF3 autoradiography was performed. In this case, due to the low penetrating power of C-emissions, only the electrons emanating from a very thin layer of tissue closest to the phosphor plate contribute to the image. These differences between C and F autoradiography result in a substantial reduction in the physical resolution of F-FDG autoradiograms relative to that of C-EF3 autoradiograms. As was previously demonstrated by a very insightful paper published earlier by the same group [3], such a loss of resolution results in a significant reduction of the dice similarity index, even when imaging the same underlying tracer distribution. Most importantly, the chaotic nature of tumor morphology ought to be taken into account. Tumors, unlike normal tissue, are characterized by a very irregular vasculature and highly heterogeneous microenvironment with a typical feature size of 100– 200 lm [4,5]. Therefore, throughout 1 mm of tissue thickness, the oxygenation status can easily change from normoxic to hypoxic and back. The layer of tissue located 1 mm away from the phosphor plate can potentially be characterized by the microenvironmental and oxygenation patterns completely different from those in the layer of tissue closest to the phosphor plate. Therefore, we conclude that the poor dice similarity index reported in the paper may be as much a consequence of the ambiguity of the radiotracer distribution, resulting from thick section autoradiography, as the spatial discrepancies between the F-FDG and C-EF3 microdistributions. It is for these reasons we suggest utilizing thin tissue sections (20 lm or thinner) for the correlative studies utilizing autoradiography for visualization of F-labeled tracer distribution in tumor tissue. Also, we believe that for dual tracer autoradiography it is better to avoid using additional layers of blocking material and rely on the differences in physical half lives of the isotopes instead. In this way it is possible to minimize the bias that can be induced by both the differential loss of image resolution and the chaotic nature of tumor microenvironment.