Pengpeng Zhang

Volumetric Modulated Arc Therapy: Planning and Evaluation for Prostate Cancer Cases

PURPOSE To develop an optimization method using volumetric modulated arc therapy (VMAT) and evaluate VMAT plans relative to the standard intensity-modulated radiotherapy (IMRT) approach in prostate cancer. METHODS AND MATERIALS A single gantry rotation was modeled using 177 equispaced beams. Multileaf collimator apertures and dose rates were optimized with respect to gantry angle subject to dose-volume-based objectives. Our VMAT implementation used conjugate gradient descent to optimize dose rate, and stochastic sampling to find optimal multileaf collimator leaf positions. A treatment planning study of 11 prostate cancer patients with a prescription dose of 86.4 Gy was performed to compare VMAT with a standard five-field IMRT approach. Plan evaluation statistics included the percentage of planning target volume (PTV) receiving 95% of prescribed dose (V95), dose to 95% of PTV (D95), mean PTV dose, tumor control probability, and dosimetric endpoints of normal organs, whereas monitor unit (MU) and delivery time were used to assess delivery efficiency. RESULTS Patient-averaged PTV V95, D95, mean dose, and tumor control probability in VMAT plans were 96%, 82.6 Gy, 88.5 Gy, and 0.920, respectively, vs. 97%, 84.0 Gy, 88.9 Gy, and 0.929 in IMRT plans. All critical structure dose requirements were met. The VMAT plans presented better rectal wall sparing, with a reduction of 1.5% in normal tissue complication probability. An advantage of VMAT plans was that the average number of MUs (290 MU) was less than for IMRT plans (642 MU). CONCLUSION The VMAT technique can reduce beam on time by up to 55% while maintaining dosimetric quality comparable to that of the standard IMRT approach.

Optimization of collimator trajectory in volumetric modulated arc therapy: development and evaluation for paraspinal SBRT.

PURPOSE To develop a collimator trajectory optimization paradigm for volumetric modulated arc therapy (VMAT) and evaluate this technique in paraspinal stereotactic body radiation therapy (SBRT). METHOD AND MATERIALS We propose a novel VMAT paradigm, Coll-VMAT, which integrates collimator rotation with synchronized gantry rotation, multileaf collimator (MLC) motion, and dose-rate modulation. At each gantry angle a principal component analysis (PCA) is applied to calculate the primary cord orientation. The collimator angle is then aligned so that MLC travel is parallel to the PCA-derived direction. An in-house VMAT optimization follows the geometry-based collimator trajectory optimization to obtain the optimal MLC position and monitor units (MU) at each gantry angle. A treatment planning study of five paraspinal SBRT patients compared Coll-VMAT to standard VMAT (fixed collimator angle) and static field IMRT plans. Plan evaluation statistics included planning target volume (PTV) V95%, PTV-D95%, cord-D05%, and total beam-on time. RESULTS Variation of collimator angle in Coll-VMAT plans ranges from 26 degrees to 54 degrees , with a median of 40 degrees . Patient-averaged PTV V95% (94.6% Coll-VMAT vs. 92.1% VMAT and 93.3% IMRT) and D95% (22.5 Gy vs. 21.4 Gy and 22.0 Gy, respectively) are highest with Coll-VMAT, and cord D05% (9.8 Gy vs. 10.0 Gy and 11.7 Gy) is lowest. Total beam-on time with Coll-VMAT (5,164 MU) is comparable to standard VMAT (4,868 MU) and substantially lower than IMRT (13,283 MU). CONCLUSION Collimator trajectory optimization-based VMAT provides an additional degree of freedom that can improve target coverage and cord sparing of paraspinal SBRT plans compared with standard VMAT and IMRT approaches.

Acquisition of MV-scatter-free kilovoltage CBCT images during RapidArc™ or VMAT

PURPOSE To perform kilovoltage (kV) cone beam computed tomography (CBCT) imaging concomitant with the delivery of megavoltage (MV) RapidArc treatment, and demonstrate the feasibility of obtaining MV-scatter-free kV CBCT images. METHODS AND MATERIALS RapidArc/CBCT treatment and imaging plans are designed, and delivered on the Varian TrueBeam, using its Developer Mode. The plan contains 250 control points for MV-radiation delivery, each over an arc of 0.4-0.7(o). Interlaced between successive MV delivery control points are imaging control points, each over an arc of 0.7-1.1(o). During the 360(o) gantry rotation for the RapidArc delivery, CBCT projections of a phantom are acquired at 11 frames per second. The kV projections with minimal MV-scatter are selected, based on gantry angle, and the CBCT(s) image reconstructed. For comparison, a reference CBCT(r) image is acquired in the normal way. In addition, to examine the effect of MV-scatter we acquire CBCT(c) using the same treatment plan without the imaging control points, i.e. with continuous MV delivery during the 360(o) rotation. Quantitative evaluation of image qualities is performed based on the concepts of CNR (contrast-to-noise ratio) and NSTD (normalized standard deviation). RESULTS The different types of CBCT images were reconstructed, evaluated, and compared. Visual comparison indicates that the image quality of CBCT(s) is similar to that of the reference CBCT(r), and that the quality of CBCT(c) is significantly degraded by the MV-scatter. Quantitative evaluation of the image quality indicates that MV-scatter significantly decreases the CNR of CBCT (from ∼7 to ∼3.5 in one comparison). Similarly, MV-scatter significantly increases the inhomogeneity of image intensity, e.g. from ∼0.03 to ∼0.06 in one comparison. CONCLUSION We have developed a method to acquire MV-scatter-free kV CBCT images concomitant with the delivery of RapidArc treatment. Engineering development is necessary to improve the process, e.g. by synchronization of the MV and kV beams.

Choreographing Couch and Collimator in Volumetric Modulated Arc Therapy

PURPOSE To design and optimize trajectory-based, noncoplanar subarcs for volumetric modulated arc therapy (VMAT) deliverable on both Varian TrueBEAM system and traditional accelerators; and to investigate their potential advantages for treating central nervous system (CNS) tumors. METHODS AND MATERIALS To guide the computerized selection of beam trajectories consisting of simultaneous couch, gantry, and collimator motion, a score function was implemented to estimate the geometric overlap between targets and organs at risk for each couch/gantry angle combination. An initial set of beam orientations is obtained as a function of couch and gantry angle, according to a minimum search of the score function excluding zones of collision. This set is grouped into multiple continuous and extended subarcs subject to mechanical limitations using a hierarchical clustering algorithm. After determination of couch/gantry trajectories, a principal component analysis finds the collimator angle at each beam orientation that minimizes residual target-organ at risk overlaps. An in-house VMAT optimization algorithm determines the optimal multileaf collimator position and monitor units for control points within each subarc. A retrospective study of 10 CNS patients compares the proposed method of VMAT trajectory with dynamic gantry, leaves, couch, and collimator motion (Tra-VMAT); a standard noncoplanar VMAT with no couch/collimator motion within subarcs (Std-VMAT); and noncoplanar intensity-modulated radiotherapy (IMRT) plans that were clinically used. RESULTS Tra-VMAT provided improved target dose conformality and lowered maximum dose to brainstem, optic nerves, and chiasm by 7.7%, 1.1%, 2.3%, and 1.7%, respectively, compared with Std-VMAT. Tra-VMAT provided higher planning target volume minimum dose and reduced maximum dose to chiasm, optic nerves, and cochlea by 6.2%, 1.3%, 6.3%, and 8.4%, respectively, and reduced cochlea mean dose by 8.7%, compared with IMRT. Tra-VMAT averaged beam-on time was comparable to Std-VMAT but significantly (45%) less than IMRT. CONCLUSION Optimized couch, gantry, and collimator trajectories may be integrated into VMAT with improved mechanical flexibility and may provide better dosimetric properties and improved efficiency in the treatment of CNS tumors.

Optimization of Gamma Knife treatment planning via guided evolutionary simulated annealing

We present a method for generating optimized Gamma Knife (Elekta, Stockholm, Sweden) radiosurgery treatment plans. This semiautomatic method produces a highly conformal shot packing plan for the irradiation of an intracranial tumor. We simulate optimal treatment planning criteria with a probability function that is linked to every voxel in a volumetric (MR or CT) region of interest. This sigmoidal P+ parameter models the requirement of conformality (i.e., tumor ablation and normal tissue sparing). After determination of initial radiosurgery treatment parameters, a guided evolutionary simulated annealing (GESA) algorithm is used to find the optimal size, position, and weight for each shot. The three-dimensional GESA algorithm searches the shot parameter space more thoroughly than is possible during manual shot packing and provides one plan that is suitable to the treatment criteria of the attending neurosurgeon and radiation oncologist. The result is a more conformal plan, which also reduces redundancy, and saves treatment administration time.

Plug pattern optimization for gamma knife radiosurgery treatment planning

PURPOSE To develop a novel dose optimization algorithm for improving the sparing of critical structures during gamma knife radiosurgery by shaping the plug pattern of each individual shot. METHOD AND MATERIALS We first use a geometric information (medial axis) aided guided evolutionary simulated annealing (GESA) optimization algorithm to determine the number of shots and isocenter location, size, and weight of each shot. Then we create a plug quality score system that checks the dose contribution to the volume of interest by each plug in the treatment plan. A positive score implies that the corresponding source could be open to improve tumor coverage, whereas a negative score means the source could be blocked for the purpose of sparing normal and critical structures. The plug pattern is then optimized via the GESA algorithm that is integrated with this score system. Weight and position of each shot are also tuned in this procedure. RESULTS An acoustic tumor case is used to evaluate our algorithm. Compared to the treatment plan generated without plug patterns, adding an optimized plug pattern into the treatment planning process boosts tumor coverage index from 95.1% to 97.2%, reduces RTOG conformity index from 1.279 to 1.167, lowers Paddicks index from 1.34 to 1.20, and trims the critical structure receiving more than 30% maximum dose from 16 mm(3) to 6 mm(3). CONCLUSIONS Automated GESA-based plug pattern optimization of gamma knife radiosurgery frees the treatment planning team from the manual forward planning procedure and provides an optimal treatment plan.

Predictive Treatment Management: Incorporating a Predictive Tumor Response Model Into Robust Prospective Treatment Planning for Non-Small Cell Lung Cancer

PURPOSE We hypothesized that a treatment planning technique that incorporates predicted lung tumor regression into optimization, predictive treatment planning (PTP), could allow dose escalation to the residual tumor while maintaining coverage of the initial target without increasing dose to surrounding organs at risk (OARs). METHODS AND MATERIALS We created a model to estimate the geometric presence of residual tumors after radiation therapy using planning computed tomography (CT) and weekly cone beam CT scans of 5 lung cancer patients. For planning purposes, we modeled the dynamic process of tumor shrinkage by morphing the original planning target volume (PTVorig) in 3 equispaced steps to the predicted residue (PTVpred). Patients were treated with a uniform prescription dose to PTVorig. By contrast, PTP optimization started with the same prescription dose to PTVorig but linearly increased the dose at each step, until reaching the highest dose achievable to PTVpred consistent with OAR limits. This method is compared with midcourse adaptive replanning. RESULTS Initial parenchymal gross tumor volume (GTV) ranged from 3.6 to 186.5 cm(3). On average, the primary GTV and PTV decreased by 39% and 27%, respectively, at the end of treatment. The PTP approach gave PTVorig at least the prescription dose, and it increased the mean dose of the true residual tumor by an average of 6.0 Gy above the adaptive approach. CONCLUSIONS PTP, incorporating a tumor regression model from the start, represents a new approach to increase tumor dose without increasing toxicities, and reduce clinical workload compared with the adaptive approach, although model verification using per-patient midcourse imaging would be prudent.

Quantitative ultrasonic evaluation of radiation-induced late tissue toxicity: pilot study of breast cancer radiotherapy.

PURPOSE To investigate the use of advanced ultrasonic imaging to quantitatively evaluate normal-tissue toxicity in breast-cancer radiation treatment. METHODS AND MATERIALS Eighteen breast cancer patients who received radiation treatment were enrolled in an institutional review board-approved clinical study. Radiotherapy involved a radiation dose of 50.0 to 50.4 Gy delivered to the entire breast, followed by an electron boost of 10.0 to 16.0 Gy delivered to the tumor bed. Patients underwent scanning with ultrasound during follow-up, which ranged from 6 to 94 months (median, 22 months) postradiotherapy. Conventional ultrasound images and radio-frequency (RF) echo signals were acquired from treated and untreated breasts. Three ultrasound parameters, namely, skin thickness, Pearson coefficient, and spectral midband fit, were computed from RF signals to measure radiation-induced changes in dermis, hypodermis, and subcutaneous tissue, respectively. Ultrasound parameter values of the treated breast were compared with those of the untreated breast. Ultrasound findings were compared with clinical assessment using Radiation Therapy Oncology Group (RTOG) late-toxicity scores. RESULTS Significant changes were observed in ultrasonic parameter values of the treated vs. untreated breasts. Average skin thickness increased by 27.3%, from 2.05 ± 0.22 mm to 2.61 ± 0.52 mm; Pearson coefficient decreased by 31.7%, from 0.41 ± 0.07 to 0.28 ± 0.05; and midband fit increased by 94.6%, from -0.92 ± 7.35 dB to 0.87 ± 6.70 dB. Ultrasound evaluations were consistent with RTOG scores. CONCLUSIONS Quantitative ultrasound provides a noninvasive, objective means of assessing radiation-induced changes to the skin and subcutaneous tissue. This imaging tool will become increasingly valuable as we continue to improve radiation therapy technique.

Fast verification of Gamma Knife treatment plans

The Leksell stereotactic Gamma Knife™ uses radiation from 201 C60o sources that are focused to the center of a collimator helmet to deliver a high dose of radiation with minimal irradiation of proximal structures. This paper presents a method for fast verification of the irradiation time as calculated by the Leksell Gamma Knife™ treatment planning software GammaPlan®. To obtain the irradiation time for each shot in the treatment plan, one must first accurately calculate the tissue maximum ratio (TMR) for each of the individual 201 beams. The algorithm presented in this paper begins with the determination of the geometrical relationship between the Gamma Knife™ collimator helmet and the stereotactic frame. A group of reference points is measured to build a head model simulating the patient skull geometry. During radiosurgery, the isocenter of the collimator helmet is moved to the shot center. A group of spatial vectors describing the reference points at the skull surface is obtained by converting the Cartesian coordinates to Polar coordinates. For each individual beam, the three nearest reference vectors are found by ranking the relative angles. The depth that each beam penetrates the patients skull to the isocenter is obtained via linear interpolation. The TMR for each beam then is compared with the TMR for the calibration setup, which is done using a spherical 8 cm radius phantom. This algorithm is applied to verify the treatment time calculated in GammaPlan® Version 5.2. The results are shown to agree with GammaPlan® within 3%. PACS number(s): 87.52.–g, 87.66.–a

Evaluating inter-campus plan consistency using a knowledge based planning model.

BACKGROUND AND PURPOSE We investigate whether knowledge based planning (KBP) can identify systematic variations in intensity modulated radiotherapy (IMRT) plans between multiple campuses of a single institution. MATERIAL AND METHODS A KBP model was constructed from 58 prior main campus (MC) esophagus IMRT radiotherapy plans and then applied to 172 previous patient plans across MC and 4 regional sites (RS). The KBP model predicts DVH bands for each organ at risk which were compared to the previously planned DVHs for that patient. RESULTS RS1s plans were the least similar to the model with less heart and stomach sparing, and more variation in liver dose, compared to MC. RS2 produced plans most similar to those expected from the model. RS3 plans displayed more variability from the model prediction but overall, the DVHs were no worse than those of MC. RS4 did not present any statistically significant results due to the small sample size (n=11). CONCLUSIONS KBP can retrospectively highlight subtle differences in planning practices, even between campuses of the same institution. This information can be used to identify areas needing increased consistency in planning output and subsequently improve consistency and quality of care.