CEST MR fingerprinting (CEST-MRF) for brain tumor quantification using EPI readout and deep learning reconstruction.

PURPOSE: To develop a clinical CEST MR fingerprinting (CEST-MRF) method for brain tumor quantification using EPI acquisition and deep learning reconstruction. METHODS: A CEST-MRF pulse sequence originally designed for animal imaging was modified to conform to hardware limits on clinical scanners while keeping scan time under 2 min. Quantitative MRF reconstruction was performed using a deep reconstruction network (DRONE) to yield the water relaxation and chemical exchange parameters. The feasibility of the six parameter DRONE reconstruction was tested in simulations using a digital brain phantom. A healthy subject was scanned with the CEST-MRF sequence, conventional MRF and CEST sequences for comparison. Reproducibility was assessed via test-retest experiments and the concordance correlation coefficient calculated for white matter and gray matter. The clinical utility of CEST-MRF was demonstrated on four patients with brain metastases in comparison to standard clinical imaging sequences. Tumors were segmented into edema, solid core, and necrotic core regions and the CEST-MRF values compared to the contra-lateral side. RESULTS: DRONE reconstruction of the digital phantom yielded a normalized RMS error of ≤7% for all parameters. The CEST-MRF parameters were in good agreement with those from conventional MRF and CEST sequences and previous studies. The mean concordance correlation coefficient for all six parameters was 0.98 ± 0.01 in white matter and 0.98 ± 0.02 in gray matter. The CEST-MRF values in nearly all tumor regions were significantly different (P = 0.05) from each other and the contra-lateral side. CONCLUSION: Combination of EPI readout and deep learning reconstruction enabled fast, accurate and reproducible CEST-MRF in brain tumors.

A multi-institutional analysis of a general pelvis continuous Hounsfield unit synthetic CT software for radiotherapy.

PURPOSE: To validate a synthetic computed tomography (sCT) software with continuous HUs and large field-of-view (FOV) coverage for magnetic resonance imaging (MRI)-only workflow of general pelvis anatomy in radiotherapy (RT). METHODS: An sCT software for general pelvis anatomy (prostate, rectum, and female pelvis) has been developed by Philips Healthcare and includes continuous HUs assignment along with large FOV coverage. General pelvis sCTs were generated using a two-stack T1-weighted mDixon fast-field echo (FFE) sequence with a superior-inferior coverage of 36 cm. Seventy-seven prostate, 43 rectum, and 27 gynecological cases were scanned by three different institutions. mDixon image quality and sCTs were evaluated for soft tissue contrast by using a confidence level scale from 1 to 5 for bladder, prostate/rectum interface, mesorectum, and fiducial maker visibility. Dosimetric comparison was performed by recalculating the RT plans on the sCT after rigid registration. For 12 randomly selected cases, the mean absolute error (MAE) between sCT and CT was calculated to evaluate HU similarity, and the Pearson correlation coefficients (PCC) between the CT- and sCT-generated digitally reconstructed radiographs (DRRs) were obtained for quantitative comparison. To examine geometric accuracy of sCT as a reference for cone beam CT (CBCT), the difference between bone-based alignment of CBCT to CT and CBCT to sCT was obtained for 19 online-acquired CBCTs from three patients. RESULTS: Two-stack mDixon scans with large FOV did not show any image inhomogeneity or fat-water swap artifact. Fiducials, Foley catheter, and even rectal spacer were visible as dark signal on the sCT. Average visibility confidence level (average ± standard deviation) on the sCT was 5.0 ± 0.0, 4.6 ± 0.5, 3.8 ± 0.4, and 4.0 ± 1.1 for bladder, prostate/rectum interface, mesorectum and fiducial markers. Dosimetric accuracy showed on average < 1% difference with the CT-based plans for target and normal structures. The MAE of bone and soft tissue between the sCT and CT are 120.9 ± 15.4 HU, 33.4 ± 4.1 HU, respectively. Average PCC of all evaluated DRR pairs was 0.975. The average offset between CT and sCT as reference was (LR, AP, SI) = (0.19 ± 0.35, 0.14 ± 0.60, 0.44 ± 0.54) mm. CONCLUSIONS: The continuous HU sCT software-generated realistic sCTs and DRRs to enable MRI-only planning for general pelvis anatomy.

Phase-sensitive deep reconstruction method for rapid multiparametric MR fingerprinting and quantitative susceptibility mapping in the brain.

INTRODUCTION: This study explores the potential of Magnetic Resonance Fingerprinting (MRF) with a novel Phase-Sensitivity Deep Reconstruction Network (PS-DRONE) for simultaneous quantification of T1, T2, Proton Density, B1+, phase and quantitative susceptibility mapping (QSM). METHODS: Data were acquired at 3 T in vitro and in vivo using an optimized EPI-based MRF sequence. Phantom experiments were conducted using a standardized phantom for T1 and T2 maps and a custom-made agar-based gadolinium phantom for B1 and QSM maps. In vivo experiments included five healthy volunteers and one patient diagnosed with brain metastasis. PSDRONE maps were compared to reference maps obtained through standard imaging sequences. RESULTS: Total scan time was 2 min for 32 slices and a resolution of [1 mm, 1 mm, 4.5 mm]. The reconstruction of T1, T2, Proton Density, B1+ and phase maps were reconstructed within 1 s. In the phantoms, PS-DRONE analysis presented accurate and strongly correlated T1 and T2 maps (r = 0.99) compared to the reference maps. B1 maps from PS-DRONE showed slightly higher values, though still correlated (r = 0.6) with the reference. QSM values showed a small bias but were strongly correlated (r = 0.99) with reference data. In the in vivo analysis, PS-DRONE-derived T1 and T2 values for gray and white matter matched reference values in healthy volunteers. PS-DRONE B1 and QSM maps showed strong correlations with reference values. CONCLUSION: The PS-DRONE network enables concurrent acquisition of T1, T2, PD, B1+, phase and QSM maps, within 2 min of acquisition time and 1 s of reconstruction time.

Quantitative longitudinal mapping of radiation-treated prostate cancer using MR fingerprinting with radial acquisition and subspace reconstruction.

MR fingerprinting (MRF) enables fast multiparametric quantitative imaging with a single acquisition and has been shown to improve diagnosis of prostate cancer. However, most prostate MRF studies were performed with spiral acquisitions that are sensitive to B0 inhomogeneities and consequent blurring. In this work, a radial MRF acquisition with a novel subspace reconstruction technique was developed to enable fast T1/T2 mapping in the prostate in under 4 min. The subspace reconstruction exploits the extensive temporal correlations in the MRF dictionary to pre-compute a low dimensional space for the solution and thus reduce the number of radial spokes to accelerate the acquisition. Iterative reconstruction with the subspace model and additional regularization of the signal representation in the subspace is performed to minimize the number of spokes and maintain matching quality and SNR. Reconstruction accuracy was assessed using the ISMRM NIST phantom. In-vivo validation was performed on two healthy subjects and two prostate cancer patients undergoing radiation therapy. The longitudinal repeatability was quantified using the concordance correlation coefficient (CCC) in one of the healthy subjects by repeated scans over 1 year. One prostate cancer patient was scanned at three time points, before initiating therapy and following brachytherapy and external beam radiation. Changes in the T1/T2 maps obtained with the proposed method were quantified. The prostate, peripheral and transitional zones, and visible dominant lesion were delineated for each study, and the statistics and distribution of the quantitative mapping values were analyzed. Significant image quality improvements compared with standard reconstruction methods were obtained with the proposed subspace reconstruction method. A notable decrease in the spread of the T1/T2 values without biasing the estimated mean values was observed with the subspace reconstruction and agreed with reported literature values. The subspace reconstruction enabled visualization of small differences in T1/T2 values in the tumor region within the peripheral zone. Longitudinal imaging of a volunteer subject yielded CCC of 0.89 for MRF T1, and 0.81 for MRF T2 in the prostate gland. Longitudinal imaging of the prostate patient confirmed the feasibility of capturing radiation treatment related changes. This work is a proof-of-concept for a high resolution and fast quantitative mapping using golden-angle radial MRF combined with a subspace reconstruction technique for longitudinal treatment response assessment in subjects undergoing radiation treatment.

Combined Compressed Sensing and SENSE to Enhance Radiation Therapy Magnetic Resonance Imaging Simulation.

PURPOSE: To assess the effect of a combination of compressed sensing and SENSitivity Encoding (SENSE) acceleration techniques on radiation therapy magnetic resonance imaging (MRI) simulation workflows. METHODS AND MATERIALS: Thirty-seven acquisitions were performed with both SENSE-only (SENSE) and combined compressed sensing and SENSE (CS) techniques in 24 patients receiving radiation therapy MRI simulation for a wide range of disease sites. The anatomic field of view prescription and image resolution were identical for both SENSE and CS acquisitions to ensure fair comparison. The acquisition time of all images was recorded to assess time savings. For each image pair, image quality, and ability to contour were assessed by 2 radiation oncologists. Aside from direct image pair comparisons, the feasibility of using CS to improve MRI simulation protocols by increasing image resolution, field of view, and reducing motion artifacts was also evaluated. RESULTS: CS resulted in an average reduction of 27% in scan time with negligible changes in image quality and the ability to contour structures for RT treatment planning compared with SENSE. Physician scoring of image quality and ability to contour shows that while SENSE still has slightly better image quality compared with CS, this observed difference in image quality did not affect the ability to contour. In addition, the higher acceleration capability of CS enabled use of superior-inferior direction phase encoding in a sagittal 3-dimensional T2-weighted scan for substantially improved visibility of the prostatic urethra, which eliminated the need for a Foley catheter in most patients. CONCLUSIONS: The combination of compressed sensing and parallel imaging resulted in marked improvements in the MRI Simulation workflow. The scan time was reduced without significantly affecting image quality in the context of ability to contour. The acceleration capabilities allowed for increased image resolution under similar scanning times as well as significantly improved urethra visualization in prostate simulations.

Treating Glioblastoma Multiforme (GBM) with super hyperfractionated radiation therapy: Implication of temporal dose fractionation optimization including cancer stem cell dynamics.

PURPOSE: A previously developed ordinary differential equation (ODE) that models the dynamic interaction and distinct radiosensitivity between cancer stem cells (CSC) and differentiated cancer cells (DCC) was used to explain the definitive treatment failure in Glioblastoma Multiforme (GBM) for conventionally and hypo-fractionated treatments. In this study, optimization of temporal dose modulation based on the ODE equation is performed to explore the feasibility of improving GBM treatment outcome. METHODS: A non-convex optimization problem with the objective of minimizing the total cancer cell number while maintaining the normal tissue biological effective dose (BEDnormal) at 100 Gy, equivalent to the conventional 2 Gy × 30 dosing scheme was formulated. With specified total number of dose fractions and treatment duration, the optimization was performed using a paired simulated annealing algorithm with fractional doses delivered to the CSC and DCC compartments and time intervals between fractions as variables. The recurrence time, defined as the time point at which the total tumor cell number regrows to 2.8×109 cells, was used to evaluate optimization outcome. Optimization was performed for conventional treatment time frames equivalent to currently and historically utilized fractionation schemes, in which limited improvement in recurrence time delay was observed. The efficacy of a super hyperfractionated approach with a prolonged treatment duration of one year was therefore tested, with both fixed regular and optimized variable time intervals between dose fractions corresponding to total number of fractions equivalent to weekly, bi-weekly, and monthly deliveries (n = 53, 27, 13). Optimization corresponding to BEDnormal of 150 Gy was also obtained to evaluate the possibility in further recurrence delay with dose escalation. RESULTS: For the super hyperfractionated schedules with dose fraction number equivalent to weekly, bi-weekly, and monthly deliveries, the recurrence time points were found to be 430.5, 423.9, and 413.3 days, respectively, significantly delayed compared with the recurrence time of 250.3 days from conventional fractionation. Results show that optimal outcome was achieved by first delivering infrequent fractions followed by dense once per day fractions in the middle and end of the treatment course, with sparse and low dose treatments in the between. The dose to the CSC compartment was held relatively constant throughout while larger dose fractions to the DCC compartment were observed in the beginning and final fractions that preceded large time intervals. Dose escalation to BEDnormal of 150 Gy was shown capable of further delaying recurrence time to 452 days. CONCLUSION: The development and utilization of a temporal dose fractionation optimization framework in the context of CSC dynamics have demonstrated that substantial delay in GBM local tumor recurrence could be achieved with a super hyperfractionated treatment approach. Preclinical and clinical studies are needed to validate the efficacy of this novel treatment delivery method.

Many-isocenter optimization for robotic radiotherapy.

Despite significant dosimetric gains, clinical implementation of the 4π non-coplanar radiotherapy on the widely available C-arm gantry system is hindered by limited clearance, and the need to perform complex coordinated gantry and couch motion. A robotic radiotherapy platform would be conducive to such treatment but a new conflict between field size and MLC modulation resolution needs to be managed for versatile applications. This study investigates the dosimetry and delivery efficiency of purposefully creating many isocenters to achieve simultaneously high MLC modulation resolution and large tumor coverage. An integrated optimization framework was proposed for simultaneous beam orientation optimization (BOO), isocenter selection, and fluence map optimization (FMO). The framework includes a least-square dose fidelity objective, a total variation term for regularizing the fluence smoothness, and a group sparsity term for beam selection. A minimal number of isocenters were identified for efficient target coverage. Colliding beams excluded, high-resolution small-field 4π intensity-modulated radiotherapy (IMRT) treatment plans with 50 cm source-to-isocenter distance (SID-50) on 10 Head and Neck (H&N) cancer patients were compared with low-resolution large-field plans with 100 cm SID (SID-100). With the same or better target coverage, the average reduction of [Dmean, Dmax] of 20-beam SID-50 plans from 20-beam SID-100 plans were [2.09 Gy, 1.19 Gy] for organs at risk (OARs) overall, [3.05 Gy, 0.04 Gy] for parotid gland, [3.62 Gy, 5.19 Gy] for larynx, and [3.27 Gy, 1.10 Gy] for mandible. R50 and integral dose were reduced by 5.3% and 9.6%, respectively. Wilcoxon signed-rank test showed significant difference (p  < 0.05) in planning target volume (PTV) homogeneity, PTV Dmax, R50, Integral dose, and OAR Dmean and Dmax. The estimated delivery time of 20-beam [SID-50, SID-100] plans were [19, 18] min and [14, 9] min, assuming 5 fractions and 30 fractions, respectively. With clinically acceptable delivery efficiency, many-isocenter optimization is dosimetrically desirable for treating large targets with high modulation resolution on the robotic platform.

Analysis of Geometric Performance and Dosimetric Impact of Using Automatic Contour Segmentation for Radiotherapy Planning.

Purpose: To analyze geometric discrepancy and dosimetric impact in using contours generated by auto-segmentation (AS) against manually segmented (MS) clinical contours. Methods: A 48-subject prostate atlas was created and another 15 patients were used for testing. Contours were generated using a commercial atlas-based segmentation tool and compared to their clinical MS counterparts. The geometric correlation was evaluated using the Dice similarity coefficient (DSC) and Hausdorff distance (HD). Dosimetric relevance was evaluated for a subset of patients by assessing the DVH differences derived by optimizing plan dose using the AS and MS contours, respectively, and evaluating with respect to each. A paired t-test was employed for statistical comparison. The discrepancy in plan quality with respect to clinical dosimetric endpoints was evaluated. The analysis was repeated for head/neck (HN) with a 31-subject atlas and 15 test cases. Results: Dice agreement between AS and MS differed significantly across structures: from (L:0.92/R: 0.91) for the femoral heads to seminal vesical of 0.38 in the prostate cohort, and from 0.98 for the brain, to 0.36 for the chiasm of the HN group. Despite the geometric disagreement, the paired t-tests showed the lack of statistical evidence for systematic differences in dosimetric plan quality yielded by the AS and MS approach for the prostate cohort. In HN cases, statistically significant differences in dosimetric endpoints were observed in structures with small volumes or elongated shapes such as cord (p = 0.01) and esophagus (p = 0.04). The largest absolute dose difference of 11 Gy was seen in the mean pharynx dose. Conclusion: Varying AS performance among structures suggests a differential approach of using AS on a subset of structures and focus MS on the rest. The discrepancy between geometric and dosimetric-end-point driven evaluation also indicates the clinical utility of AS contours in optimization and evaluating plan quality despite of suboptimal geometrical accuracy.

Practical Safety Considerations for Integration of Magnetic Resonance Imaging in Radiation Therapy.

Interest in integrating magnetic resonance imaging (MRI) in radiation therapy (RT) practice has increased dramatically in recent years owing to its unique advantages such as excellent soft tissue contrast and capability of measuring biological properties. Continuous real-time imaging for intrafractional motion tracking without ionizing radiation serves as a particularly attractive feature for applications in RT. Despite its many advantages, the integration of MRI in RT workflows is not straightforward, with many unmet needs. MR safety remains one of the key challenges and concerns in the clinical implementation of MR simulators and MR-guided radiation therapy systems in radiation oncology. Most RT staff are not accustomed to working in an environment with a strong magnetic field. There are specific requirements in RT that are different from diagnostic applications. A large variety of implants and devices used in routine RT practice do not have clear MR safety labels. RT-specific imaging pulse sequences focusing on fast acquisition, high spatial integrity, and continuous, real-time acquisition require additional MR safety testing and evaluation. This article provides an overview of MR safety tailored toward RT staff, followed by discussions on specific requirements and challenges associated with MR safety in the RT environment. Strategies and techniques for developing an MR safety program specific to RT are presented and discussed.

Single-arc VMAT optimization for dual-layer MLC.

Dual-layer multi-leaf collimator (DLMLC) has recently attracted renewed interest due to its good balance among resolution, low leakage, and high fabricability. However, existing progressive sampling based volumetric modulated arc therapy (VMAT) algorithm is ineffective for DLMLC, requiring more arcs to achieve dosimetry comparable to VMAT plans with higher resolution single-layer MLC (SLMLC). In this study, we develop a novel single-arc VMAT optimization framework to take advantage of the unique DLMLC characteristics fully. Direct aperture optimization (DAO) for single-arc DLMLC VMAT was formulated as a least square dose fidelity objective, along with an anisotropic total variation term to regulate the fluence smoothness and a single segment term for forming simple apertures. The DAO was solved through alternating optimization approach. The DLMLC deliverability constraint and the MLC leaf speed constraint were formulated as the optimization constraints and solved using a graph optimization algorithm. Feasibility of the proposed framework was tested on a brain, a lung, and a prostate cancer patient. The framework was further adapted for a simultaneous integrated boost (SIB) case. The single-arc DLMLC-10 mm (leaf width) plan was compared against single-arc SLMLC VMAT plans including SLMLC-5mm, SLMLC-10mm, and SLMLC with 10 mm leaf width and 5 mm leaf step size (SLMLC-10mm-5mm). Compared with the SLMLC-10mm plan and the SLMLC-10mm-5mm plan, with the same target coverage, the DLMLC-10 mm plan reduced R50 by 30.7% and 10.0%, the average max OAR dose by 5.79% and 3.7% of the prescription dose, and the average mean OAR dose by 4.18% and 2.1% of the prescription dose, respectively. The plan quality is comparable to that of the SLMLC-5mm plan. The novel single-arc VMAT optimization framework for DLMLC utilizes two MLC layers to improve the effective modulation resolution and afford more sophisticated modulation. Consequently, DLMLC VMAT achieves superior dosimetry to SLMLC VMAT with the same leaf width.

Integrated beam orientation and scanning-spot optimization in intensity-modulated proton therapy for brain and unilateral head and neck tumors.

PURPOSE: Intensity-Modulated Proton Therapy (IMPT) is the state-of-the-art method of delivering proton radiotherapy. Previous research has been mainly focused on optimization of scanning spots with manually selected beam angles. Due to the computational complexity, the potential benefit of simultaneously optimizing beam orientations and spot pattern could not be realized. In this study, we developed a novel integrated beam orientation optimization (BOO) and scanning-spot optimization algorithm for intensity-modulated proton therapy (IMPT). METHODS: A brain chordoma and three unilateral head-and-neck patients with a maximal target size of 112.49 cm3 were included in this study. A total number of 1162 noncoplanar candidate beams evenly distributed across 4π steradians were included in the optimization. For each candidate beam, the pencil-beam doses of all scanning spots covering the PTV and a margin were calculated. The beam angle selection and spot intensity optimization problem was formulated to include three terms: a dose fidelity term to penalize the deviation of PTV and OAR doses from ideal dose distribution; an L1-norm sparsity term to reduce the number of active spots and improve delivery efficiency; a group sparsity term to control the number of active beams between 2 and 4. For the group sparsity term, convex L2,1-norm and nonconvex L2,1/2-norm were tested. For the dose fidelity term, both quadratic function and linearized equivalent uniform dose (LEUD) cost function were implemented. The optimization problem was solved using the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA). The IMPT BOO method was tested on three head-and-neck patients and one skull base chordoma patient. The results were compared with IMPT plans created using column generation selected beams or manually selected beams. RESULTS: The L2,1-norm plan selected spatially aggregated beams, indicating potential degeneracy using this norm. L2,1/2-norm was able to select spatially separated beams and achieve smaller deviation from the ideal dose. In the L2,1/2-norm plans, the [mean dose, maximum dose] of OAR were reduced by an average of [2.38%, 4.24%] and[2.32%, 3.76%] of the prescription dose for the quadratic and LEUD cost function, respectively, compared with the IMPT plan using manual beam selection while maintaining the same PTV coverage. The L2,1/2 group sparsity plans were dosimetrically superior to the column generation plans as well. Besides beam orientation selection, spot sparsification was observed. Generally, with the quadratic cost function, 30%~60% spots in the selected beams remained active. With the LEUD cost function, the percentages of active spots were in the range of 35%~85%.The BOO-IMPT run time was approximately 20 min. CONCLUSION: This work shows the first IMPT approach integrating noncoplanar BOO and scanning-spot optimization in a single mathematical framework. This method is computationally efficient, dosimetrically superior and produces delivery-friendly IMPT plans.

Magnetic Resonance Imaging Guidance Mitigates the Effects of Intrafraction Prostate Motion During Stereotactic Body Radiotherapy for Prostate Cancer.

The accurate delivery of stereotactic body radiotherapy (SBRT) for definitive prostate cancer treatment is aided by intrafraction image guidance. The common methods for intrafraction imaging require the invasive placement of fiducial markers or electromagnetic transponders. Recently, a magnetic resonance imaging (MRI)-guided tri-cobalt-60 head radiotherapy system has become available for treatment, which can utilize real-time cine MRI to non-invasively track prostate motion. We report on a clinical vignette using this technique to deliver SBRT for the definitive treatment of intermediate-risk prostate cancer. The incorporation of an MRI-guided radiotherapy system and the implementation of real-time adaptive dose delivery accounting for intrafraction anatomic motion may improve outcomes using this technique.

A novel optimization framework for VMAT with dynamic gantry couch rotation.

Existing volumetric modulated arc therapy (VMAT) optimization using coplanar arcs is highly efficient but usually dosimetrically inferior to intensity modulated radiation therapy (IMRT) with optimized non-coplanar beams. To achieve both dosimetric quality and delivery efficiency, we proposed in this study, a novel integrated optimization method for non-coplanar VMAT (4πVMAT). 4πVMAT with direct aperture optimization (DAO) was achieved by utilizing a least square dose fidelity objective, along with an anisotropic total variation term for regularizing the fluence smoothness, a single segment term for imposing simple apertures, and a group sparsity term for selecting beam angles. Continuous gantry/couch angle trajectories were selected using the Dijkstra's algorithm, where the edge and node costs were determined based on the maximal gantry rotation speed and the estimated fluence map at the current iteration, respectively. The couch-gantry-patient collision space was calculated based on actual machine geometry and a human subject 3D surface. Beams leading to collision are excluded from the DAO and beam trajectory selection (BTS). An alternating optimization strategy was implemented to solve the integrated DAO and BTS problem. The feasibility of 4πVMAT using one full-arc or two full-arcs was tested on nine patients with brain, lung, or prostate cancer. The plan was compared against a coplanar VMAT (2πVMAT) plan using one additional arc and collimator rotation. Compared to 2πVMAT, 4πVMAT reduced the average maximum and mean organs-at-risk dose by 9.63% and 3.08% of the prescription dose with the same target coverage. R50 was reduced by 23.0%. Maximum doses to the dose limiting organs, such as the brainstem, the major vessels, and the proximal bronchus, were reduced by 8.1 Gy (64.8%), 16.3 Gy (41.5%), and 19.83 Gy (55.5%), respectively. The novel 4πVMAT approach affords efficient delivery of non-coplanar arc trajectories that lead to dosimetric improvements compared with coplanar VMAT using more arcs.

A Prospective 4π Radiation Therapy Clinical Study in Recurrent High-Grade Glioma Patients.

PURPOSE: To evaluate the feasibility, safety, dosimetric benefits, delivery efficiency, and patient comfort in the clinical implementation of 4π radiation therapy. METHODS AND MATERIALS: Eleven patients with recurrent high-grade glioma were recruited for the trial. 4π plans integrating beam orientation and fluence-map optimization were created using an in-house column-generation algorithm. The collision-free beam solution space throughout the 4π steradian was determined using a computer-aided-design model of the Varian TrueBeam system and a human subject. Twenty beams were optimized for each case and imported into Eclipse for intensity modulated radiation therapy planning. Beam orientations with neighboring couch kicks were merged for increased delivery efficiency, generating plans with an average of 16 beam orientations. Volumetric modulated arc therapy (VMAT) plans with 3-4 arcs were also generated for each case, and the plan achieving superior dosimetric quality was selected for treatment. Patient comfort was surveyed after every fraction. Multiple 2-dimensional X-ray images were obtained to measure intrafractional motion. RESULTS: Of 11 patients, 9 were treated with 4π. Mean and maximum organ at risk doses were equal or significantly lower (P < .05) with 4π than with VMAT. Particularly substantial dose reduction of 2.92 Gy in the average accumulated brainstem maximum dose enabled treatments that would otherwise not satisfy safe dose constraints with VMAT. One patient was not treated because neither plan met the dosimetric criteria. The other was treated with VMAT owing to comparable dosimetry resulting from a planning target volume located in a separate co-plane superior to organs at risk. Treatments were well tolerated, with an average patient comfort score of 8.6/10. Intrafractional motion was <1.5 mm for all delivered fractions, and the average delivery time was 34.1 minutes. CONCLUSIONS: The feasibility, safety, dosimetric benefits, delivery efficiency, and patient comfort of 4π radiation therapy have been clinically demonstrated with a prospective clinical trial. The results elucidate the potential and challenges of wider clinical implementations.

Predicting liver SBRT eligibility and plan quality for VMAT and 4π plans.

BACKGROUND: It is useful to predict planned dosimetry and determine the eligibility of a liver cancer patient for SBRT treatment using knowledge based planning (KBP). We compare the predictive accuracy using the overlap volume histogram (OVH) and statistical voxel dose learning (SVDL) KBP prediction models for coplanar VMAT to non-coplanar 4π radiotherapy plans. METHODS: In this study, 21 liver SBRT cases were selected, which were initially treated using coplanar VMAT plans. They were then re-planned using 4π IMRT plans with 20 inversely optimized non-coplanar beams. OVH was calculated by expanding the planning target volume (PTV) and then plotting the percent overlap volume v with the liver vs. r v , the expansion distance. SVDL calculated the distance to the PTV for all liver voxels and bins the voxels of the same distance. Their dose information is approximated by either taking the median or using a skew-normal or non-parametric fit, which was then applied to voxels of unknown dose for each patient in a leave-one-out test. The liver volume receiving less than 15 Gy (V<15Gy), DVHs, and 3D dose distributions were predicted and compared between the prediction models and planning methods. RESULTS: On average, V<15Gy was predicted within 5%. SVDL was more accurate than OVH and able to predict DVH and 3D dose distributions. Median SVDL yielded predictive errors similar or lower than the fitting methods and is more computationally efficient. Prediction of the 4π dose was more accurate compared to VMAT for all prediction methods, with significant (p < 0.05) results except for OVH predicting liver V<15Gy (p = 0.063). CONCLUSIONS: In addition to evaluating plan quality, KBP is useful to automatically determine the patient eligibility for liver SBRT and quantify the dosimetric gains from non-coplanar 4π plans. The two here analyzed dose prediction methods performed more accurately for the 4π plans than VMAT.

Viability of Non-Coplanar VMAT for Liver SBRT as Compared to Coplanar VMAT and Beam Orientation Optimized 4π IMRT.

PURPOSE: The 4π static non-coplanar radiotherapy delivery technique has demonstrated better normal tissue sparing and dose conformity than the clinically used volumetric modulated arc therapy (VMAT). It is unclear whether this is a fundamental limitation of VMAT delivery or the coplanar nature of its typical clinical plans. The dosimetry and the limits of normal tissue toxicity constrained dose escalation of coplanar VMAT, non-coplanar VMAT and 4π radiotherapy are quantified in this study. METHODS AND MATERIALS: Clinical stereotactic body radiation therapy plans for 20 liver patients receiving 30-60 Gy using coplanar VMAT (cVMAT) were re-planned using 3-4 partial non-coplanar arcs (nVMAT) and 4π with 20 intensity-modulated non-coplanar fields. The conformity number (CN), homogeneity index (HI), 50% dose spillage volume (R50), normal liver volume receiving >15 Gy (VL>15), dose to organs at risk (OARs), and tumor control probability (TCP) were compared for all three treatment plans. The maximum tolerable dose (MTD) yielding a normal liver normal tissue control probability (NTCP) below 1%, 5%, and 10% was calculated with the Lyman-Kutcher-Burman model for each plan, as well as the resulting survival fractions at one, two, three, and four years. RESULTS: Compared to cVMAT, the nVMAT and 4π plans reduced VL>15 by an average of 5 cm3 and 80 cm3, respectively. 4π reduced the 50% dose spillage volume by ~23% compared to both VMAT plans, and either significantly decreased or maintained OAR doses. The 4π MTDs and survival fractions were significantly higher than both cVMAT and nVMAT (p<0.05) for all normal liver NTCP limits used in this study. CONCLUSIONS: The 4π technique provides significantly better OAR sparing than both cVMAT and vMAT and enables more clinically relevant dose escalation for tumor local control. Therefore, despite the current accessibility of nVMAT, it is not a viable alternative to 4π for liver SBRT.

The development and verification of a highly accurate collision prediction model for automated noncoplanar plan delivery.

PURPOSE: Significant dosimetric benefits had been previously demonstrated in highly noncoplanar treatment plans. In this study, the authors developed and verified an individualized collision model for the purpose of delivering highly noncoplanar radiotherapy and tested the feasibility of total delivery automation with Varian TrueBeam developer mode. METHODS: A hand-held 3D scanner was used to capture the surfaces of an anthropomorphic phantom and a human subject, which were positioned with a computer-aided design model of a TrueBeam machine to create a detailed virtual geometrical collision model. The collision model included gantry, collimator, and couch motion degrees of freedom. The accuracy of the 3D scanner was validated by scanning a rigid cubical phantom with known dimensions. The collision model was then validated by generating 300 linear accelerator orientations corresponding to 300 gantry-to-couch and gantry-to-phantom distances, and comparing the corresponding distance measurements to their corresponding models. The linear accelerator orientations reflected uniformly sampled noncoplanar beam angles to the head, lung, and prostate. The distance discrepancies between measurements on the physical and virtual systems were used to estimate treatment-site-specific safety buffer distances with 0.1%, 0.01%, and 0.001% probability of collision between the gantry and couch or phantom. Plans containing 20 noncoplanar beams to the brain, lung, and prostate optimized via an in-house noncoplanar radiotherapy platform were converted into XML script for automated delivery and the entire delivery was recorded and timed to demonstrate the feasibility of automated delivery. RESULTS: The 3D scanner measured the dimension of the 14 cm cubic phantom within 0.5 mm. The maximal absolute discrepancy between machine and model measurements for gantry-to-couch and gantry-to-phantom was 0.95 and 2.97 cm, respectively. The reduced accuracy of gantry-to-phantom measurements was attributed to phantom setup errors due to the slightly deformable and flexible phantom extremities. The estimated site-specific safety buffer distance with 0.001% probability of collision for (gantry-to-couch, gantry-to-phantom) was (1.23 cm, 3.35 cm), (1.01 cm, 3.99 cm), and (2.19 cm, 5.73 cm) for treatment to the head, lung, and prostate, respectively. Automated delivery to all three treatment sites was completed in 15 min and collision free using a digital Linac. CONCLUSIONS: An individualized collision prediction model for the purpose of noncoplanar beam delivery was developed and verified. With the model, the study has demonstrated the feasibility of predicting deliverable beams for an individual patient and then guiding fully automated noncoplanar treatment delivery. This work motivates development of clinical workflows and quality assurance procedures to allow more extensive use and automation of noncoplanar beam geometries.

Incorporating cancer stem cells in radiation therapy treatment response modeling and the implication in glioblastoma multiforme treatment resistance.

PURPOSE: To perform a preliminary exploration with a simplistic mathematical cancer stem cell (CSC) interaction model to determine whether the tumor-intrinsic heterogeneity and dynamic equilibrium between CSCs and differentiated cancer cells (DCCs) can better explain radiation therapy treatment response with a dual-compartment linear-quadratic (DLQ) model. METHODS AND MATERIALS: The radiosensitivity parameters of CSCs and DCCs for cancer cell lines including glioblastoma multiforme (GBM), non-small cell lung cancer, melanoma, osteosarcoma, and prostate, cervical, and breast cancer were determined by performing robust least-square fitting using the DLQ model on published clonogenic survival data. Fitting performance was compared with the single-compartment LQ (SLQ) and universal survival curve models. The fitting results were then used in an ordinary differential equation describing the kinetics of DCCs and CSCs in response to 2- to 14.3-Gy fractionated treatments. The total dose to achieve tumor control and the fraction size that achieved the least normal biological equivalent dose were calculated. RESULTS: Smaller cell survival fitting errors were observed using DLQ, with the exception of melanoma, which had a low α/ß = 0.16 in SLQ. Ordinary differential equation simulation indicated lower normal tissue biological equivalent dose to achieve the same tumor control with a hypofractionated approach for 4 cell lines for the DLQ model, in contrast to SLQ, which favored 2 Gy per fraction for all cells except melanoma. The DLQ model indicated greater tumor radioresistance than SLQ, but the radioresistance was overcome by hypofractionation, other than the GBM cells, which responded poorly to all fractionations. CONCLUSION: The distinct radiosensitivity and dynamics between CSCs and DCCs in radiation therapy response could perhaps be one possible explanation for the heterogeneous intertumor response to hypofractionation and in some cases superior outcome from stereotactic ablative radiation therapy. The DLQ model also predicted the remarkable GBM radioresistance, a result that is highly consistent with clinical observations. The radioresistance putatively stemmed from accelerated DCC regrowth that rapidly restored compartmental equilibrium between CSCs and DCCs.

Dose domain regularization of MLC leaf patterns for highly complex IMRT plans.

PURPOSE: The advent of automated beam orientation and fluence optimization enables more complex intensity modulated radiation therapy (IMRT) planning using an increasing number of fields to exploit the expanded solution space. This has created a challenge in converting complex fluences to robust multileaf collimator (MLC) segments for delivery. A novel method to regularize the fluence map and simplify MLC segments is introduced to maximize delivery efficiency, accuracy, and plan quality. METHODS: In this work, we implemented a novel approach to regularize optimized fluences in the dose domain. The treatment planning problem was formulated in an optimization framework to minimize the segmentation-induced dose distribution degradation subject to a total variation regularization to encourage piecewise smoothness in fluence maps. The optimization problem was solved using a first-order primal-dual algorithm known as the Chambolle-Pock algorithm. Plans for 2 GBM, 2 head and neck, and 2 lung patients were created using 20 automatically selected and optimized noncoplanar beams. The fluence was first regularized using Chambolle-Pock and then stratified into equal steps, and the MLC segments were calculated using a previously described level reducing method. Isolated apertures with sizes smaller than preset thresholds of 1-3 bixels, which are square units of an IMRT fluence map from MLC discretization, were removed from the MLC segments. Performance of the dose domain regularized (DDR) fluences was compared to direct stratification and direct MLC segmentation (DMS) of the fluences using level reduction without dose domain fluence regularization. RESULTS: For all six cases, the DDR method increased the average planning target volume dose homogeneity (D95/D5) from 0.814 to 0.878 while maintaining equivalent dose to organs at risk (OARs). Regularized fluences were more robust to MLC sequencing, particularly to the stratification and small aperture removal. The maximum and mean aperture sizes using the DDR were consistently larger than those from DMS for all tested number of segments. CONCLUSIONS: The fluence map to MLC segmentation conversion problem was formulated as a secondary optimization problem in the dose domain to minimize the smoothness-regularized dose discrepancy. The large scale optimization problem was solved using a primal-dual algorithm that transformed complicated fluences into maps that were more robust to the MLC segmentation and sequencing, affording fewer and larger segments with minimal degradation to dose distribution.

Quality control procedures for dynamic treatment delivery techniques involving couch motion.

In this study, the authors introduce and demonstrate quality control procedures for evaluating the geometric and dosimetric fidelity of dynamic treatment delivery techniques involving treatment couch motion synchronous with gantry and multileaf collimator (MLC). Tests were designed to evaluate positional accuracy, velocity constancy and accuracy for dynamic couch motion under a realistic weight load. A test evaluating the geometric accuracy of the system in delivering treatments over complex dynamic trajectories was also devised. Custom XML scripts that control the Varian TrueBeam™ STx (Serial #3) axes in Developer Mode were written to implement the delivery sequences for the tests. Delivered dose patterns were captured with radiographic film or the electronic portal imaging device. The couch translational accuracy in dynamic treatment mode was 0.01 cm. Rotational accuracy was within 0.3°, with 0.04 cm displacement of the rotational axis. Dose intensity profiles capturing the velocity constancy and accuracy for translations and rotation exhibited standard deviation and maximum deviations below 3%. For complex delivery involving MLC and couch motions, the overall translational accuracy for reproducing programmed patterns was within 0.06 cm. The authors conclude that in Developer Mode, TrueBeam™ is capable of delivering dynamic treatment delivery techniques involving couch motion with good geometric and dosimetric fidelity.