Cardiac Sparing with Personalized Treatment Planning for Early-stage Left Breast Cancer.

Purpose To compare cardiac doses of different whole-breast optimization schemes including free-breathing (FB) tangential radiotherapy (TRT), deep-inspiration breath-hold (DIBH) TRT, and FB helical tomotherapy (HT). Methods Early-stage left-sided breast cancer patients who underwent breast-conserving surgery followed by adjuvant radiotherapy were included in the study. Planning images included FB and DIBH CT scans acquired in the same supine treatment position with both arms abducted. A hypofractionated regimen of 42.5 Gy in 16 fractions was used. Clinical target volume delineation was aided through the use of a radio-opaque wire. A 7-mm margin was used in generating the planning target volumes. TRT plans were generated both in FB and DIBH. For the FB tomotherapy technique, a first plan (Tomo 1) was optimized limiting the maximum contralateral breast dose to 3.1 Gy. A second tomotherapy plan (Tomo 2) focused on the reduction of the mean heart dose without controlling the contralateral breast dose. All plans were optimized to obtain an equivalent planning target volume (PTV) coverage of ≥95% of the prescribed dose while minimizing the dose to organs at risk. Results Twenty-three patients treated between October 2012 and March 2016 were included in this retrospective study. Eleven patients (48%) had at least one major cardiovascular risk factors including one patient (4%) with a history of myocardial infarction. Six patients (26%) had been exposed to cardiotoxic chemotherapy agents. The average mean dose to the heart was 3.1 Gy with FB TRT, 1.1 with DIBH TRT, 2.4 Gy for Tomo 1, and 1.5 Gy for Tomo 2. The mean dose to the left anterior descending artery was 27.0 Gy, 8.0 Gy, 13.7 Gy and 6.6 Gy for FB TRT, DIBH TRT, Tomo 1 and Tomo 2 plans respectively. Conclusion Different cardiac-sparing optimization schemes are possible when treating left breast cancer. Although DIBH offers clear mean heart dose reductions, tomotherapy can be an interesting alternative treatment modality to spare the heart and coronary vessels, notably in patients who cannot comply with DIBH.

A fast 4D cone beam CT reconstruction method based on the OSC-TV algorithm.

BACKGROUND: Four-dimensional cone beam computed tomography allows for temporally resolved imaging with useful applications in radiotherapy, but raises particular challenges in terms of image quality and computation time. OBJECTIVE: The purpose of this work is to develop a fast and accurate 4D algorithm by adapting a GPU-accelerated ordered subsets convex algorithm (OSC), combined with the total variation minimization regularization technique (TV). METHODS: Different initialization schemes were studied to adapt the OSC-TV algorithm to 4D reconstruction: each respiratory phase was initialized either with a 3D reconstruction or a blank image. Reconstruction algorithms were tested on a dynamic numerical phantom and on a clinical dataset. 4D iterations were implemented for a cluster of 8 GPUs. RESULTS: All developed methods allowed for an adequate visualization of the respiratory movement and compared favorably to the McKinnon-Bates and adaptive steepest descent projection onto convex sets algorithms, while the 4D reconstructions initialized from a prior 3D reconstruction led to better overall image quality. CONCLUSION: The most suitable adaptation of OSC-TV to 4D CBCT was found to be a combination of a prior FDK reconstruction and a 4D OSC-TV reconstruction with a reconstruction time of 4.5 minutes. This relatively short reconstruction time could facilitate a clinical use.

System matrix computation vs storage on GPU: A comparative study in cone beam CT.

PURPOSE: Iterative reconstruction algorithms in computed tomography (CT) require a fast method for computing the intersection distances between the trajectories of photons and the object, also called ray tracing or system matrix computation. This work focused on the thin-ray model is aimed at comparing different system matrix handling strategies using graphical processing units (GPUs). METHODS: In this work, the system matrix is modeled by thin rays intersecting a regular grid of box-shaped voxels, known to be an accurate representation of the forward projection operator in CT. However, an uncompressed system matrix exceeds the random access memory (RAM) capacities of typical computers by one order of magnitude or more. Considering the RAM limitations of GPU hardware, several system matrix handling methods were compared: full storage of a compressed system matrix, on-the-fly computation of its coefficients, and partial storage of the system matrix with partial on-the-fly computation. These methods were tested on geometries mimicking a cone beam CT (CBCT) acquisition of a human head. Execution times of three routines of interest were compared: forward projection, backprojection, and ordered-subsets convex (OSC) iteration. RESULTS: A fully stored system matrix yielded the shortest backprojection and OSC iteration times, with a 1.52× acceleration for OSC when compared to the on-the-fly approach. Nevertheless, the maximum problem size was bound by the available GPU RAM and geometrical symmetries. On-the-fly coefficient computation did not require symmetries and was shown to be the fastest for forward projection. It also offered reasonable execution times of about 176.4 ms per view per OSC iteration for a detector of 512 × 448 pixels and a volume of 3843 voxels, using commodity GPU hardware. Partial system matrix storage has shown a performance similar to the on-the-fly approach, while still relying on symmetries. CONCLUSION: Partial system matrix storage was shown to yield the lowest relative performance. On-the-fly ray tracing was shown to be the most flexible method, yielding reasonable execution times. A fully stored system matrix allowed for the lowest backprojection and OSC iteration times and may be of interest for certain performance-oriented applications.

Evaluation of the OSC-TV iterative reconstruction algorithm for cone-beam optical CT.

PURPOSE: The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. METHODS: This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numerical simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. RESULTS: The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. CONCLUSIONS: The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can potentially improve the rendering of spatial features and reduce cone-beam optical CT artifacts.