Dimitre Hristov

A grey-level image alignment algorithm for registration of portal images and digitally reconstructed radiographs.

An algorithm for automatic registration of pairs of portal images based on image correlation is presented. It uses a fast-Fourier-transform-based cross-correlation operator to find the optimal registration, accounting for both in-plane translations and rotations. Different cross-correlation operators have been tested: the Pearson linear correlation coefficient has been implemented by fast Fourier transform and its performance has been compared to that of the more conventional normalized cross-correlation. A sequential approach has been applied to speed up the registration considerably without degrading the performance of the algorithm. The algorithm has also been applied to the automatic registration of portal images to digitally reconstructed radiographs (DRRs), which have been modified to resemble megavoltage images. The results are indicative of the feasibility of this approach to the inspection of patient setup in radiation therapy.

Algorithm for X-ray Scatter, Beam-Hardening, and Beam Profile Correction in Diagnostic (Kilovoltage) and Treatment (Megavoltage) Cone Beam CT

Quantitative reconstruction of cone beam X-ray computed tomography (CT) datasets requires accurate modeling of scatter, beam-hardening, beam profile, and detector response. Typically, commercial imaging systems use fast empirical corrections that are designed to reduce visible artifacts due to incomplete modeling of the image formation process. In contrast, Monte Carlo (MC) methods are much more accurate but are relatively slow. Scatter kernel superposition (SKS) methods offer a balance between accuracy and computational practicality. We show how a single SKS algorithm can be employed to correct both kilovoltage (kV) energy (diagnostic) and megavoltage (MV) energy (treatment) X-ray images. Using MC models of kV and MV imaging systems, we map intensities recorded on an amorphous silicon flat panel detector to water-equivalent thicknesses (WETs). Scattergrams are derived from acquired projection images using scatter kernels indexed by the local WET values and are then iteratively refined using a scatter magnitude bounding scheme that allows the algorithm to accommodate the very high scatter-to-primary ratios encountered in kV imaging. The algorithm recovers radiological thicknesses to within 9% of the true value at both kV and megavolt energies. Nonuniformity in CT reconstructions of homogeneous phantoms is reduced by an average of 76% over a wide range of beam energies and phantom geometries.

Adapting radiotherapy to hypoxic tumours

In the current work, the concepts of biologically adapted radiotherapy of hypoxic tumours in a framework encompassing functional tumour imaging, tumour control predictions, inverse treatment planning and intensity modulated radiotherapy (IMRT) were presented. Dynamic contrast enhanced magnetic resonance imaging (DCEMRI) of a spontaneous sarcoma in the nasal region of a dog was employed. The tracer concentration in the tumour was assumed related to the oxygen tension and compared to Eppendorf histograph measurements. Based on the pO(2)-related images derived from the MR analysis, the tumour was divided into four compartments by a segmentation procedure. DICOM structure sets for IMRT planning could be derived thereof. In order to display the possible advantages of non-uniform tumour doses, dose redistribution among the four tumour compartments was introduced. The dose redistribution was constrained by keeping the average dose to the tumour equal to a conventional target dose. The compartmental doses yielding optimum tumour control probability (TCP) were used as input in an inverse planning system, where the planning basis was the pO(2)-related tumour images from the MR analysis. Uniform (conventional) and non-uniform IMRT plans were scored both physically and biologically. The consequences of random and systematic errors in the compartmental images were evaluated. The normalized frequency distributions of the tracer concentration and the pO(2) Eppendorf measurements were not significantly different. 28% of the tumour had, according to the MR analysis, pO(2) values of less than 5 mm Hg. The optimum TCP following a non-uniform dose prescription was about four times higher than that following a uniform dose prescription. The non-uniform IMRT dose distribution resulting from the inverse planning gave a three times higher TCP than that of the uniform distribution. The TCP and the dose-based plan quality depended on IMRT parameters defined in the inverse planning procedure (fields and step-and-shoot intensity levels). Simulated random and systematic errors in the pO(2)-related images reduced the TCP for the non-uniform dose prescription. In conclusion, improved tumour control of hypoxic tumours by dose redistribution may be expected following hypoxia imaging, tumour control predictions, inverse treatment planning and IMRT.

Dosimetric and microdosimetric study of contrast-enhanced radiotherapy with kilovolt x-rays.

Kilovolt x-rays are clearly suboptimal compared to MV photon beams for radiotherapy of deep-seated tumours because of the increased attenuation in tissue, causing a rapid dose fall-off. This picture could change drastically when tumours can be labelled with contrast medium, containing high atomic number elements. This causes a significant dose enhancement to the tumour by exploiting the high cross sections for the photo-electric effect for kV x-rays. In this work, we have investigated the dosimetric and microdosimetric characteristics of kV contrast-enhanced radiation therapy (CERT) for different photon energies, contrast-medium concentrations and types (I and Gd). Two idealized patient treatment plans (head and lung) for irradiation with CT-arc beams were calculated. It is shown that the dose enhancement in tumours can be highly significant (up to about sixfold for realistic 80-120 kVp x-ray spectra and an iodine concentration of 50 mg ml-1) but that dose homogeneity in the tumour depends on photon energy, contrast-medium concentration and type, and irradiation scheme. An attempt to optimize the irradiation scheme is discussed. The microdosimetric study of the dose mean lineal energy shows that radiation quality changes in the contrast-medium-labelled region compared to homogeneous tissue are fairly small and limited to 10%. It is concluded that kV-CERT is a promising radiotherapy technique, provided contrast medium can be delivered reliably to tumours.

Tumor volume-adapted dosing in stereotactic ablative radiotherapy of lung tumors.

PURPOSE Current stereotactic ablative radiotherapy (SABR) protocols for lung tumors prescribe a uniform dose regimen irrespective of tumor size. We report the outcomes of a lung tumor volume-adapted SABR dosing strategy. METHODS AND MATERIALS We retrospectively reviewed the outcomes in 111 patients with a total of 138 primary or metastatic lung tumors treated by SABR, including local control, regional control, distant metastasis, overall survival, and treatment toxicity. We also performed subset analysis on 83 patients with 97 tumors treated with a volume-adapted dosing strategy in which small tumors (gross tumor volume <12 mL) received single-fraction regimens with biologically effective doses (BED) <100 Gy (total dose, 18-25 Gy) (Group 1), and larger tumors (gross tumor volume ≥12 mL) received multifraction regimens with BED ≥100 Gy (total dose, 50-60 Gy in three to four fractions) (Group 2). RESULTS The median follow-up time was 13.5 months. Local control for Groups 1 and 2 was 91.4% and 92.5%, respectively (p = 0.24) at 12 months. For primary lung tumors only (excluding metastases), local control was 92.6% and 91.7%, respectively (p = 0.58). Regional control, freedom from distant metastasis, and overall survival did not differ significantly between Groups 1 and 2. Rates of radiation pneumonitis, chest wall toxicity, and esophagitis were low in both groups, but all Grade 3 toxicities developed in Group 2 (p = 0.02). CONCLUSION A volume-adapted dosing approach for SABR of lung tumors seems to provide excellent local control for both small- and large-volume tumors and may reduce toxicity.

Telerobotic system concept for real‐time soft‐tissue imaging during radiotherapy beam delivery

PURPOSE The curative potential of external beam radiation therapy is critically dependent on having the ability to accurately aim radiation beams at intended targets while avoiding surrounding healthy tissues. However, existing technologies are incapable of real-time, volumetric, soft-tissue imaging during radiation beam delivery, when accurate target tracking is most critical. The authors address this challenge in the development and evaluation of a novel, minimally interfering, telerobotic ultrasound (U.S.) imaging system that can be integrated with existing medical linear accelerators (LINACs) for therapy guidance. METHODS A customized human-safe robotic manipulator was designed and built to control the pressure and pitch of an abdominal U.S. transducer while avoiding LINAC gantry collisions. A haptic device was integrated to remotely control the robotic manipulator motion and U.S. image acquisition outside the LINAC room. The ability of the system to continuously maintain high quality prostate images was evaluated in volunteers over extended time periods. Treatment feasibility was assessed by comparing a clinically deployed prostate treatment plan to an alternative plan in which beam directions were restricted to sectors that did not interfere with the transabdominal U.S. transducer. To demonstrate imaging capability concurrent with delivery, robot performance and U.S. target tracking in a phantom were tested with a 15 MV radiation beam active. RESULTS Remote image acquisition and maintenance of image quality with the haptic interface was successfully demonstrated over 10 min periods in representative treatment setups of volunteers. Furthermore, the robots ability to maintain a constant probe force and desired pitch angle was unaffected by the LINAC beam. For a representative prostate patient, the dose-volume histogram (DVH) for a plan with restricted sectors remained virtually identical to the DVH of a clinically deployed plan. With reduced margins, as would be enabled by real-time imaging, gross tumor volume coverage was identical while notable reductions of bladder and rectal volumes exposed to large doses were possible. The quality of U.S. images obtained during beam operation was not appreciably degraded by radiofrequency interference and 2D tracking of a phantom object in U.S. images obtained with the beam on/off yielded no significant differences. CONCLUSIONS Remotely controlled robotic U.S. imaging is feasible in the radiotherapy environment and for the first time may offer real-time volumetric soft-tissue guidance concurrent with radiotherapy delivery.

An active set algorithm for treatment planning optimization.

An active set algorithm for optimization of radiation therapy dose planning by intensity modulated beams has been developed. The algorithm employs a conjugate-gradient routine for subspace minimization in order to achieve a higher rate of convergence than the widely used constrained steepest-descent method at the expense of a negligible amount of overhead calculations. The performance of the new algorithm has been compared to that of the constrained steepest-descent method for various treatment geometries and two different objectives. The active set algorithm is found to be superior to the constrained steepest descent, both in terms of its convergence properties and the residual value of the cost functions at termination. Its use can significantly accelerate the design of conformal plans with intensity modulated beams by decreasing the number of time-consuming dose calculations.

A continuous penalty function method for inverse treatment planning

Conventional inverse treatment planning attempts to calculate dose distributions that may not be feasible given the specified dose levels to various anatomical structures. A technique for inverse treatment planning has been developed that uses only target dose levels which are easily selectable to be feasible. A nonlinear constrained minimization problem is formulated to reflect the goal of sparing critical organs as much as possible while delivering a certain target dose within specified uniformity. The objective function is the squared dose delivered to critical organs. The constraints require the delivery of certain target dose within specified uniformity and non-negative pencil beam weights. A continuous penalty function method is introduced as a method for solving the large-scale constrained minimization problem. The performance of the continuous penalty function method is optimized by numerical investigation of few numerical integration schemes and a pair of weighting functions which influence the utility of the method. Clinical examples are presented that illustrate several features of the technique. The properties of the continuous penalty function method suggest that it may be a viable alternative to conventional inverse treatment planning.

Clinical evaluation of the iterative metal artifact reduction algorithm for CT simulation in radiotherapy

PURPOSE To clinically evaluate an iterative metal artifact reduction (IMAR) algorithm prototype in the radiation oncology clinic setting by testing for accuracy in CT number retrieval, relative dosimetric changes in regions affected by artifacts, and improvements in anatomical and shape conspicuity of corrected images. METHODS A phantom with known material inserts was scanned in the presence/absence of metal with different configurations of placement and sizes. The relative change in CT numbers from the reference data (CT with no metal) was analyzed. The CT studies were also used for dosimetric tests where dose distributions from both photon and proton beams were calculated. Dose differences and gamma analysis were calculated to quantify the relative changes between doses calculated on the different CT studies. Data from eight patients (all different treatment sites) were also used to quantify the differences between dose distributions before and after correction with IMAR, with no reference standard. A ranking experiment was also conducted to analyze the relative confidence of physicians delineating anatomy in the near vicinity of the metal implants. RESULTS IMAR corrected images proved to accurately retrieve CT numbers in the phantom study, independent of metal insert configuration, size of the metal, and acquisition energy. For plastic water, the mean difference between corrected images and reference images was -1.3 HU across all scenarios (N = 37) with a 90% confidence interval of [-2.4, -0.2] HU. While deviations were relatively higher in images with more metal content, IMAR was able to effectively correct the CT numbers independent of the quantity of metal. Residual errors in the CT numbers as well as some induced by the correction algorithm were found in the IMAR corrected images. However, the dose distributions calculated on IMAR corrected images were closer to the reference data in phantom studies. Relative spatial difference in the dose distributions in the regions affected by the metal artifacts was also observed in patient data. However, in absence of a reference ground truth (CT set without metal inserts), these differences should not be interpreted as improvement/deterioration of the accuracy of calculated dose. With limited data presented, it was observed that proton dosimetry was affected more than photons as expected. Physicians were significantly more confident contouring anatomy in the regions affected by artifacts. While site specific preferences were detected, all indicated that they would consistently use IMAR corrected images. CONCLUSIONS IMAR correction algorithm could be readily implemented in an existing clinical workflow upon commercial release. While residual errors still exist in IMAR corrected images, these images present with better overall conspicuity of the patient/phantom geometry and offer more accurate CT numbers for improved local dosimetry. The variety of different scenarios included herein attest to the utility of the evaluated IMAR for a wide range of radiotherapy clinical scenarios.

Inverse treatment planning by physically constrained minimization of a biological objective function.

In the current state-of-the art of clinical inverse planning, the design of clinically acceptable IMRT plans is predominantly based on the optimization of physical rather than biological objective functions. A major impetus for this trend is the unproven predictive power of radiobiological models, which is largely due to the scarcity of data sets for an accurate evaluation of the model parameters. On the other hand, these models do capture the currently known dose-volume effects in tissue dose-response, which should be accounted for in the process of optimization. In order to incorporate radiobiological information in clinical treatment planning optimization, we propose a hybrid physico-biological approach to inverse treatment planning based on the application of a continuous penalty function method to the constrained minimization of a biological objective. The objective is defined as the weighted sum of normal tissue complication probabilities evaluated with the Lyman normal-tissue complication probability model. Physical constraints specify the admissible minimum and maximum target dose. The continuous penalty function method is then used to find an approximate solution of the resulting large-scale constrained minimization problem. Plans generated by our approach are compared to ones produced by a commercial planning system incorporating physical optimization. The comparisons show clinically negligible differences, with the advantage that the hybrid technique does not require specifications of any dose-volume constraints to the normal tissues. This indicates that the proposed hybrid physico-biological method can be used for the generation of clinically acceptable plans.