Dose volume histogram comparison between ADAC Pinnacle and Nomos Corvus systems for IMRT

A comparison of the dose distributions from three proton treatment planning systems in the planning of meningioma patients with single-field uniform dose pencil beam scanning

With the number of new proton centers increasing rapidly, there is a need for an assessment of the available proton treatment planning systems (TPSs). This study compares the dose distributions of complex meningioma plans produced by three proton TPSs: Eclipse, Pinnacle³, and XiO. All three systems were commissioned with the same beam data and, as best as possible, matched configuration settings. Proton treatment plans for ten patients were produced on each system with a pencil beam scanning, single‐field uniform dose approach, using a fixed horizontal beamline. All 30 plans were subjected to identical dose constraints, both for the target coverage and organ at risk (OAR) sparing, with a consistent order of priority. Beam geometry, lateral field margins, and lateral spot resolutions were made consistent across all systems. Few statistically significant differences were found between the target coverage and OAR sparing of each system, with all optimizers managing to produce plans within clinical tolerances (D2<107% of prescribed dose, D5<105%, D95>95%, D99>90%, and OAR maximum doses) despite strict constraints and overlapping structures.

PACS number: 87.55.D‐

Late toxicity after intensity-modulated radiation therapy for localized prostate cancer: an exploration of dose-volume histogram parameters to limit genitourinary and gastrointestinal toxicity

PURPOSE

To characterize the late genitourinary (GU) and gastrointestinal (GI) toxicity for prostate cancer patients treated with intensity-modulated radiation therapy (IMRT) and propose dose-volume histogram (DVH) guidelines to limit late treatment-related toxicity.

METHODS AND MATERIALS

In this study 296 consecutive men were treated with IMRT for adenocarcinoma of the prostate. Most patients received treatment to the prostate with or without proximal seminal vesicles (90%), to a median dose of 76 Gy. Concurrent androgen deprivation therapy was given to 150 men (51%) for a median of 4 months. Late toxicity was defined by Common Toxicity Criteria version 3.0 as greater than 3 months after radiation therapy completion. Four groupings of DVH parameters were defined, based on the percentage of rectal or bladder tissue receiving 70 Gy (V(70)), 65 Gy (V(65)), and 40 Gy (V(40)). These DVH groupings, as well as clinical and treatment characteristics, were correlated to maximal Grade 2+ GU and GI toxicity.

RESULTS

With a median follow-up of 41 months, the 4-year freedom from maximal Grade 2+ late toxicity was 81% and 91% for GU and GI systems, respectively, and by last follow-up, the rates of Grade 2+ GU and GI toxicity were 9% and 5%, respectively. On multivariate analysis, whole-pelvic IMRT was associated with Grade 2+ GU toxicity and age was associated with Grade 2+ GI toxicity. Freedom from Grade 2+ GI toxicity at 4 years was 100% for men with rectal V(70) ≤ 10%, V(65) ≤ 20%, and V(40) ≤ 40%; 92% for men with rectal V(70) ≤ 20%, V(65) ≤ 40%, and V(40) ≤ 80%; and 85% for men exceeding these criteria (p = 0.13). These criteria were more highly associated with GI toxicity in men aged ≥70 years (p = 0.07). No bladder dose-volume relationships were associated with the risk of GU toxicity.

CONCLUSIONS

IMRT is associated with low rates of severe GU or GI toxicity after treatment for prostate cancer. Rectal dose constraints may help limit late GI morbidity.

Dosimetric comparison between 3D conformal and intensity-modulated radiation therapy for prostate cancer

Background and Purpose: Intensity-modulated radiation therapy (IMRT) is considered by many to be the standard of care in the delivery of external-beam radiotherapy treatments to the prostate. The purpose of this study is to assess the validity of the purported benefits of IMRT.

Materials and Methods: Treatment plans were produced for 10 patients using both 3D conformal radiation therapy (3D-CRT) and IMRT, utilising the dose constraints recommended by the Radiation Therapy Oncology Group (RTOG) 0415 protocol. Three IMRT modalities used in this study were linear accelerator based IMRT, helical tomotherapy, and serial tomotherapy. The prescription to the target, 76 Gy, was the same for all plans.

Results: In general the 3D-CRT plans satisfied the RTOG criteria for planning target volume (PTV) coverage, and met or bettered the dose criteria for the organs at risk. PTV coverage was more homogeneous for the IMRT plans than the 3D-CRT plans but not significantly improved.

Conclusions: Technically, because the IMRT plans required greater effort for the optimisation, longer treatment times and higher monitor units, the use of IMRT for the fulfilment of the protocol’s dosimetric goals was not justified using these constraints.

The denoising of Monte Carlo dose distributions using convolution superposition calculations

Monte Carlo (MC) dose calculations can be accurate but are also computationally intensive. In contrast, convolution superposition (CS) offers faster and smoother results but by making approximations. We investigated MC denoising techniques, which use available convolution superposition results and new noise filtering methods to guide and accelerate MC calculations. Two main approaches were developed to combine CS information with MC denoising. In the first approach, the denoising result is iteratively updated by adding the denoised residual difference between the result and the MC image. Multi-scale methods were used (wavelets or contourlets) for denoising the residual. The iterations are initialized by the CS data. In the second approach, we used a frequency splitting technique by quadrature filtering to combine low frequency components derived from MC simulations with high frequency components derived from CS components. The rationale is to take the scattering tails as well as dose levels in the high-dose region from the MC calculations, which presumably more accurately incorporates scatter; high-frequency details are taken from CS calculations. 3D Butterworth filters were used to design the quadrature filters. The methods were demonstrated using anonymized clinical lung and head and neck cases. The MC dose distributions were calculated by the open-source dose planning method MC code with varying noise levels. Our results indicate that the frequency-splitting technique for incorporating CS-guided MC denoising is promising in terms of computational efficiency and noise reduction.