An in-silico planning study of stereotactic body radiation therapy for polymetastatic patients with more than ten extra-cranial lesions.

Background and purpose: Limited data is available about the feasibility of stereotactic body radiation therapy (SBRT) for treating more than five extra-cranial metastases, and almost no data for treating more than ten. The aim of this study was to investigate the feasibility of SBRT in this polymetatstatic setting. Materials and methods: Consecutive metastatic melanoma patients with more than ten extra-cranial metastases and a maximum lesion diameter below 11 cm were selected from a single-center prospective registry for this in-silico planning study. For each patient, SBRT plans were generated to treat all metastases with a prescribed dose of 5x7Gy, and dose-limiting organs (OARs) were analyzed. A cell-kill based inverse planning approach was used to automatically determine the maximum deliverable dose to each lesion individually, while respecting all OARs constraints. Results: A total of 23 polymetastatic patients with a medium of 17 metastases (range, 11-51) per patient were selected. SBRT plans with sufficient target coverage and respected OARs dose constraints were achieved in 16 out of 23 patients. In the remaining seven patients, the lungs V5Gy < 80 % and the liver D700 cm3 < 15Gy were most frequently the dose-limiting constraints. The cell-kill based planning approach allowed optimizing the dose administration depending on metastases total volume and location. Conclusion: This retrospective planning study shows the feasibility of definitive SBRT for 70% of polymetastatic patients with more than ten extra-cranial lesions and proposes the cell-killing planning approach as an approach to individualize treatment planning in polymetastatic patients'.

Evaluation of the hoof centre-of-pressure path in horses affected by chronic osteoarthritic pain.

INTRODUCTION: The Centre of Pressure (COP) is the single point summarising all forces transferred to the hoof during the stance phase of a stride. COP path (COPp) is the trajectory that COP follows from footstrike to lift-off. Aim of the present study was to characterize the COP and COPp in horses affected by osteoarthritis and chronic lameness. MATERIALS AND METHODS: Seventeen adult horses with a diagnosis of osteoarthritis and single limb chronic lameness were recruited. The COP was recorded using a wireless pressure measuring system (TekScan®) with sensors taped to the hooves (either fore- or hind limb, depending on lameness location). The COPp coordinates were further processed. Procrustes analysis was performed to assess the variability of single strides COPp and average COPp among strides, gaits, and limbs by calculating Procrustes distances (D-values). A linear mixed-effects model was run to analyse D-values differences for lame and sound limbs. Additionally, average COPp D-values and COPp hoofprint shape indices were compared for lame and sound limbs with the Signed Rank Test. RESULTS: At walk and trot the single-stride COPp D-values were significantly lower in lame than in sound limbs (marginal effects p<0.001). Analysis of the average COPp D-values confirmed that each hoof COPp is highly consistent with itself over subsequent trials but is different from the contralateral. COPp and hoofprint shape indices did not differ between sound and lame limbs. Footstrike and lift-off within the hoofprint showed that most horses had lateral footstrike and lift-off, independently of the lameness location. CONCLUSION: Our findings are in line with previous observations that COPp are highly repetitive and characteristic for each horse and limb. There seems to be a further decrease in COPp variability in the presence of a painful limb pathology.

Spatiotemporal fractionation schemes for stereotactic radiosurgery of multiple brain metastases.

BACKGROUND: Stereotactic radiosurgery (SRS) is an established treatment for patients with brain metastases (BMs). However, damage to the healthy brain may limit the tumor dose for patients with multiple lesions. PURPOSE: In this study, we investigate the potential of spatiotemporal fractionation schemes to reduce the biological dose received by the healthy brain in SRS of multiple BMs, and also demonstrate a novel concept of spatiotemporal fractionation for polymetastatic cancer patients that faces less hurdles for clinical implementation. METHODS: Spatiotemporal fractionation (STF) schemes aim at partial hypofractionation in the metastases along with more uniform fractionation in the healthy brain. This is achieved by delivering distinct dose distributions in different fractions, which are designed based on their cumulative biologically effective dose ( BED α / ß ${\rm{BED}}_{{{\alpha}}/{{\beta}}}$ ) such that each fraction contributes with high doses to complementary parts of the target volume, while similar dose baths are delivered to the normal tissue. For patients with multiple brain metastases, a novel constrained approach to spatiotemporal fractionation (cSTF) is proposed, which is more robust against setup and biological uncertainties. The approach aims at irradiating entire metastases with possibly different doses, but spatially similar dose distributions in every fraction, where the optimal dose contribution of every fraction to each metastasis is determined using a new planning objective to be added to the BED-based treatment plan optimization problem. The benefits of spatiotemporal fractionation schemes are evaluated for three patients, each with >25 BMs. RESULTS: For the same tumor BED10 and the same brain volume exposed to high doses in all plans, the mean brain BED2 can be reduced compared to uniformly fractionated plans by 9%-12% with the cSTF plans and by 13%-19% with the STF plans. In contrast to the STF plans, the cSTF plans avoid partial irradiation of the individual metastases and are less sensitive to misalignments of the fractional dose distributions when setup errors occur. CONCLUSION: Spatiotemporal fractionation schemes represent an approach to lower the biological dose to the healthy brain in SRS-based treatments of multiple BMs. Although cSTF cannot achieve the full BED reduction of STF, it improves on uniform fractionation and is more robust against both setup errors and biological uncertainties related to partial tumor irradiation.

A novel stochastic optimization method for handling misalignments of proton and photon doses in combined treatments.

Objective.Combined proton-photon treatments, where most fractions are delivered with photons and only a few are delivered with protons, may represent a practical approach to optimally use limited proton resources. It has been shown that, when organs at risk (OARs) are located within or near the tumor, the optimal multi-modality treatment uses protons to hypofractionate parts of the target volume and photons to achieve near-uniform fractionation in dose-limiting healthy tissues, thus exploiting the fractionation effect. These plans may be sensitive to range and setup errors, especially misalignments between proton and photon doses. Thus, we developed a novel stochastic optimization method to directly incorporate these uncertainties into the biologically effective dose (BED)-based simultaneous optimization of proton and photon plans.Approach.The method considers the expected valueEband standard deviationσbof the cumulative BEDbin every voxel of a structure. For the target, a piecewise quadratic penalty function of the formbmin-Eb-2σb+2is minimized, aiming for plans in which the expected BED minus two times the standard deviation exceeds the prescribed BEDbmin.Analogously,Eb+2σb-bmax+2is considered for OARs.Main results.Using a spinal metastasis case and a liver cancer patient, it is demonstrated that the novel stochastic optimization method yields robust combined treatment plans. Tumor coverage and a good sparing of the main OARs are maintained despite range and setup errors, and especially misalignments between proton and photon doses. This is achieved without explicitly considering all combinations of proton and photon error scenarios.Significance.Concerns about range and setup errors for safe clinical implementation of optimized proton-photon radiotherapy can be addressed through an appropriate stochastic planning method.