A unified framework for 3D radiation therapy and IMRT planning: plan optimization in the beamlet domain by constraining or regularizing the fluence map variations

Three-dimensional conformal planning with low-segment multicriteria intensity modulated radiation therapy optimization

PURPOSE

The purpose of this study was to evaluate automated multicriteria optimization (MCO), which is designed for intensity modulated radiation therapy (IMRT) but invoked with limited segmentation, to efficiently produce high-quality 3-dimensional (3D) conformal radiation therapy (3D-CRT) plans.

METHODS AND MATERIALS

Treatment for 10 patients previously planned with 3D-CRT to various disease sites (brain, breast, lung, abdomen, pelvis) was replanned with a low-segment inverse MCO technique. The MCO-3D plans used the same beam geometry of the original 3D plans but were limited to an energy of 6 MV. The MCO-3D plans were optimized with fluence-based MCO IMRT and then, after MCO navigation, segmented with a low number of segments. The 3D and MCO-3D plans were compared by evaluating mean dose for all structures, D95 (dose that 95% of the structure receives) and homogeneity indexes for targets, D1 and clinically appropriate dose-volume objectives for individual organs at risk (OARs), monitor units, and physician preference.

RESULTS

The MCO-3D plans reduced the mean doses to OARs (41 of a total of 45 OARs had a mean dose reduction; P << .01) and monitor units (7 of 10 plans had reduced monitor units; the average reduction was 17% [P = .08]) while maintaining clinical standards for coverage and homogeneity of target volumes. All MCO-3D plans were preferred by physicians over their corresponding 3D plans.

CONCLUSIONS

High-quality 3D plans can be produced by use of MCO-IMRT optimization, resulting in automated field-in-field-type plans with good monitor unit efficiency. Adoption of this technology in a clinic could improve plan quality and streamline treatment plan production by using a single system applicable to both IMRT and 3D planning.

Shared data for intensity modulated radiation therapy (IMRT) optimization research: the CORT dataset

BACKGROUND

We provide common datasets (which we call the CORT dataset: common optimization for radiation therapy) that researchers can use when developing and contrasting radiation treatment planning optimization algorithms. The datasets allow researchers to make one-to-one comparisons of algorithms in order to solve various instances of the radiation therapy treatment planning problem in intensity modulated radiation therapy (IMRT), including beam angle optimization, volumetric modulated arc therapy and direct aperture optimization.

RESULTS

We provide datasets for a prostate case, a liver case, a head and neck case, and a standard IMRT phantom. We provide the dose-influence matrix from a variety of beam/couch angle pairs for each dataset. The dose-influence matrix is the main entity needed to perform optimizations: it contains the dose to each patient voxel from each pencil beam. In addition, the original Digital Imaging and Communications in Medicine (DICOM) computed tomography (CT) scan, as well as the DICOM structure file, are provided for each case.

CONCLUSIONS

Here we present an open dataset - the first of its kind - to the radiation oncology community, which will allow researchers to compare methods for optimizing radiation dose delivery.

Single-scan patient-specific scatter correction in computed tomography using peripheral detection of scatter and compressed sensing scatter retrieval

PURPOSE

X-ray scatter results in a significant degradation of image quality in computed tomography (CT), representing a major limitation in cone-beam CT (CBCT) and large field-of-view diagnostic scanners. In this work, a novel scatter estimation and correction technique is proposed that utilizes peripheral detection of scatter during the patient scan to simultaneously acquire image and patient-specific scatter information in a single scan, and in conjunction with a proposed compressed sensing scatter recovery technique to reconstruct and correct for the patient-specific scatter in the projection space.

METHODS

The method consists of the detection of patient scatter at the edges of the field of view (FOV) followed by measurement based compressed sensing recovery of the scatter through-out the projection space. In the prototype implementation, the kV x-ray source of the Varian TrueBeam OBI system was blocked at the edges of the projection FOV, and the image detector in the corresponding blocked region was used for scatter detection. The design enables image data acquisition of the projection data on the unblocked central region of and scatter data at the blocked boundary regions. For the initial scatter estimation on the central FOV, a prior consisting of a hybrid scatter model that combines the scatter interpolation method and scatter convolution model is estimated using the acquired scatter distribution on boundary region. With the hybrid scatter estimation model, compressed sensing optimization is performed to generate the scatter map by penalizing the L1 norm of the discrete cosine transform of scatter signal. The estimated scatter is subtracted from the projection data by soft-tuning, and the scatter-corrected CBCT volume is obtained by the conventional Feldkamp-Davis-Kress algorithm. Experimental studies using image quality and anthropomorphic phantoms on a Varian TrueBeam system were carried out to evaluate the performance of the proposed scheme.

RESULTS

The scatter shading artifacts were markedly suppressed in the reconstructed images using the proposed method. On the Catphan©504 phantom, the proposed method reduced the error of CT number to 13 Hounsfield units, 10% of that without scatter correction, and increased the image contrast by a factor of 2 in high-contrast regions. On the anthropomorphic phantom, the spatial nonuniformity decreased from 10.8% to 6.8% after correction.

CONCLUSIONS

A novel scatter correction method, enabling unobstructed acquisition of the high frequency image data and concurrent detection of the patient-specific low frequency scatter data at the edges of the FOV, is proposed and validated in this work. Relative to blocker based techniques, rather than obstructing the central portion of the FOV which degrades and limits the image reconstruction, compressed sensing is used to solve for the scatter from detection of scatter at the periphery of the FOV, enabling for the highest quality reconstruction in the central region and robust patient-specific scatter correction.

Inverse planning for IMRT with nonuniform beam profiles using total-variation regularization (TVR)

PURPOSE

Radiation therapy with high dose rate and flattening filter-free (FFF) beams has the potential advantage of greatly reduced treatment time and out-of-field dose. Current inverse planning algorithms are, however, not customized for beams with nonuniform incident profiles and the resultant IMRT plans are often inefficient in delivery. The authors propose a total-variation regularization (TVR)-based formalism by taking the inherent shapes of incident beam profiles into account.

METHODS

A novel TVR-based inverse planning formalism is established for IMRT with nonuniform beam profiles. The authors introduce a TVR term into the objective function, which encourages piecewise constant fluence in the nonuniform FFF fluence domain. The proposed algorithm is applied to lung and prostate and head and neck cases and its performance is evaluated by comparing the resulting plans to those obtained using a conventional beamlet-based optimization (BBO).

RESULTS

For the prostate case, the authors' algorithm produces acceptable dose distributions with only 21 segments, while the conventional BBO requires 114 segments. For the lung case and the head and neck case, the proposed method generates similar coverage of target volume and sparing of the organs-at-risk as compared to BBO, but with a markedly reduced segment number.

CONCLUSIONS

TVR-based optimization in nonflat beam domain provides an effective way to maximally leverage the technical capacity of radiation therapy with FFF fields. The technique can generate effective IMRT plans with improved dose delivery efficiency without significant deterioration of the dose distribution.