Impact of setup errors on the robustness of linac-based single-isocenter coplanar and non-coplanar VMAT plans for multiple brain metastases.

PURPOSE: Patient setup errors have been a primary concern impacting the dose delivery accuracy in radiation therapy. A robust treatment plan might mitigate the effects of patient setup errors. In this reported study, we aimed to evaluate the impact of translational and rotational errors on the robustness of linac-based, single-isocenter, coplanar, and non-coplanar volumetric modulated arc therapy treatment plans for multiple brain metastases. METHODS: Fifteen patients were retrospectively selected for this study with a combined total of 49 gross tumor volumes (GTVs). Single-isocenter coplanar and non-coplanar plans were generated first with a prescribed dose of 40 Gy in 5 fractions or 42 Gy in 7 fractions to cover 95% of planning target volume (PTV). Next, four setup errors (+1  and +2 mm translation, and +1° and +2° rotation) were applied individually to generate modified plans. Different plan quality evaluation metrics were compared between coplanar and non-coplanar plans. 3D gamma analysis (3%/2 mm) was performed to compare the modified plans (+2 mm and +2° only) and the original plans. Paired t-test was conducted for statistical analysis. RESULTS: After applying setup errors, variations of all plan evaluation metrics were similar (p > 0.05). The worst case for V100% to GTV was 92.07% ± 6.13% in the case of +2 mm translational error. 3D gamma pass rates were > 90% for both coplanar (+2 mm and +2°) and the +2 mm non-coplanar groups but was 87.40% ± 6.89% for the +2° non-coplanar group. CONCLUSION: Translational errors have a greater impact on PTV and GTV dose coverage for both planning methods. Rotational errors have a greater negative impact on gamma pass rates of non-coplanar plans. Plan evaluation metrics after applying setup errors showed that both coplanar and non-coplanar plans were robust and clinically acceptable.

Multi-omics approaches for biomarker discovery in predicting the response of esophageal cancer to neoadjuvant therapy: A multidimensional perspective.

Neoadjuvant chemoradiotherapy (NCRT) followed by surgery has been established as the standard treatment strategy for operable locally advanced esophageal cancer (EC). However, achieving pathologic complete response (pCR) or near pCR to NCRT is significantly associated with a considerable improvement in survival outcomes, while pCR patients may help organ preservation for patients by active surveillance to avoid planned surgery. Thus, there is an urgent need for improved biomarkers to predict EC chemoradiation response in research and clinical settings. Advances in multiple high-throughput technologies such as next-generation sequencing have facilitated the discovery of novel predictive biomarkers, specifically based on multi-omics data, including genomic/transcriptomic sequencings and proteomic/metabolomic mass spectra. The application of multi-omics data has shown the benefits in improving the understanding of underlying mechanisms of NCRT sensitivity/resistance in EC. Particularly, the prominent development of artificial intelligence (AI) has introduced a new direction in cancer research. The integration of multi-omics data has significantly advanced our knowledge of the disease and enabled the identification of valuable biomarkers for predicting treatment response from diverse dimension levels, especially with rapid advances in biotechnological and AI methodologies. Herein, we summarize the current status of research on the use of multi-omics technologies in predicting NCRT response for EC patients. Current limitations, challenges, and future perspectives of these multi-omics platforms will be addressed to assist in experimental designs and clinical use for further integrated analysis.

Dosimetric response of Gafchromic™ EBT-XD film to therapeutic protons.

EBT-XD model of Gafchromic™ films has a broader optimal dynamic dose range, up to 40 Gy, compared to its predecessor models. This characteristic has made EBT-XD films suitable for high-dose applications such as stereotactic body radiotherapy and stereotactic radiosurgery, as well as ultra-high dose rate FLASH radiotherapy. The purpose of the current study was to characterize the dependence of EBT-XD film response on linear energy transfer (LET) and dose rate of therapeutic protons from a synchrotron. A clinical spot-scanning proton beam was used to study LET dependence at three dose-averaged LET (LETd) values of 1.0 keV/µm, 3.6 keV/µm, and 7.6 keV/µm. A research proton beamline was used to study dose rate dependence at 150 Gy/second in the FLASH mode and 0.3 Gy/second in the non-FLASH mode. Film response data from LETd values of 0.9 keV/µm and 9.0 keV/µm of the proton FLASH beam were also compared. Film response data from a clinical 6 MV photon beam were used as a reference. Both gray value method and optical density (OD) method were used in film calibration. Calibration results using a specific OD calculation method and a generic OD calculation method were compared. The four-parameter NIH Rodbard function and three-parameter rational function were compared in fitting the calibration curves. Experimental results showed that the response of EBT-XD film is proton LET dependent but independent of dose rate. Goodness-of-fit analysis showed that using the NIH Rodbard function is superior for both protons and photons. Using the "specific OD + NIH Rodbard function" method for EBT-XD film calibration is recommended.

Case Report: MR-LINAC-guided adaptive radiotherapy for gastric cancer.

Background: The stomach is one of the most deformable organs. Its shape can be easily affected by breathing movements, and daily diet, and it also varies when the body position is different. The susceptibility of stomach has made it challenging to treat gastric cancer using the conventional image-guided radiotherapy, i.e., the techniques based on kilovoltage X-ray imaging. The magnetic resonance imaging guided radiotherapy (MRgRT) is usually implemented using a hybrid system MR-LINAC. It is feasible to implement adaptive radiotherapy using MR-LINAC for deformable organs such as stomach. In this case report, we present our clinical experience to treat a gastric cancer patient using MR-LINAC. Case description: The patient is a 58-year-old male who started having black stools with no apparent cause a year ago. Gastroscopy result showed pancreatic cancer, pathology: adenocarcinoma on gastric cancer biopsy, adenocarcinoma on gastric body minor curvature biopsy. The patient was diagnosed with gastric cancer (adenocarcinoma, cTxN+M1, stage IV, HER-2 positive). The patient was treated in 25 fractions with radiotherapy using MR-LINAC with online adaptive treatment plans daily. The target area in daily MR images varied considerably when compared with the target area on the CT simulation images. During the course of treatment, there have even been instances where the planned target area where the patient received radiotherapy did not cover the lesion of the day. Conclusion: Online adaptive MRgRT can be a meaningful innovation for treating malignancies in the upper abdomen. The results in the current study are promising and are indicative for further optimizing online adaptive MRgRT in patients with inoperable tumors of the upper abdomen.

Looking on the horizon; potential and unique approaches to developing radiation countermeasures for deep space travel.

Future lunar missions and beyond will require new and innovative approaches to radiation countermeasures. The Translational Research Institute for Space Health (TRISH) is focused on identifying and supporting unique approaches to reduce risks to human health and performance on future missions beyond low Earth orbit. This paper will describe three funded and complementary avenues for reducing the risk to humans from radiation exposure experienced in deep space. The first focus is on identifying new therapeutic targets to reduce the damaging effects of radiation by focusing on high throughput genetic screens in accessible, sometimes called lower, organism models. The second focus is to design innovative approaches for countermeasure development with special attention to nucleotide-based methodologies that may constitute a more agile way to design therapeutics. The final focus is to develop new and innovative ways to test radiation countermeasures in a human model system. While animal studies continue to be beneficial in the study of space radiation, they can have imperfect translation to humans. The use of three-dimensional (3D) complex in vitro models is a promising approach to aid the development of new countermeasures and personalized assessments of radiation risks. These three distinct and unique approaches complement traditional space radiation efforts and should provide future space explorers with more options to safeguard their short and long-term health.

Targeting hippocampal neurogenesis to protect astronauts' cognition and mood from decline due to space radiation effects.

Neurogenesis is an essential, lifelong process during which neural stem cells generate new neurons within the hippocampus, a center for learning, memory, and mood control. Neural stem cells are vulnerable to environmental insults spanning from chronic stress to radiation. These insults reduce their numbers and diminish neurogenesis, leading to memory decline, anxiety, and depression. Preserving neural stem cells could thus help prevent these neurogenesis-associated pathologies, an outcome particularly important for long-term space missions where environmental exposure to radiation is significantly higher than on Earth. Multiple developments, from mechanistic discoveries of radiation injury on hippocampal neurogenesis to new platforms for the development of selective, specific, effective, and safe small molecules as neurogenesis-protective agents hold great promise to minimize radiation damage on neurogenesis. In this review, we summarize the effects of space-like radiation on hippocampal neurogenesis. We then focus on current advances in drug discovery and development and discuss the nuclear receptor TLX/NR2E1 (oleic acid receptor) as an example of a neurogenic target that might rescue neurogenesis following radiation.

Adaptation and dosimetric commissioning of a synchrotron-based proton beamline for FLASH experiments.

Objective. Irradiation with ultra-high dose rates (>40 Gy s-1), also known as FLASH irradiation, has the potential to shift the paradigm of radiation therapy because of its reduced toxicity to normal tissues compared to that of conventional irradiations. The goal of this study was to (1) achieve FLASH irradiation conditions suitable for pre-clinicalin vitroandin vivobiology experiments using our synchrotron-based proton beamline and (2) commission the FLASH irradiation conditions achieved.Approach. To achieve these suitable FLASH conditions, we made a series of adaptations to our proton beamline, including modifying the spill length and size of accelerating cycles, repurposing the reference monitor for dose control, and expanding the field size with a custom double-scattering system. We performed the dosimetric commissioning with measurements using an Advanced Markus chamber and EBT-XD films as well as with Monte Carlo simulations.Main results. Through adaptations, we have successfully achieved FLASH irradiation conditions, with an average dose rate of up to 375 Gy s-1. The Advanced Markus chamber was shown to be appropriate for absolute dose calibration under our FLASH conditions with a recombination factor ranging from 1.002 to 1.006 because of the continuous nature of our synchrotron-based proton delivery within a spill. Additionally, the absolute dose measured using the Advanced Markus chamber and EBT-XD films agreed well, with average and maximum differences of 0.32% and 1.63%, respectively. We also performed a comprehensive temporal analysis for FLASH spills produced by our system, which helped us identify a unique relationship between the average dose rate and the dose in our FLASH irradiation.Significance.We have established a synchrotron-based proton FLASH irradiation platform with accurate and precise dosimetry that is suitable for pre-clinical biology experiments. The unique time structure of the FLASH irradiation produced by our synchrotron-based system may shed new light onto the mechanism behind the FLASH effect.

Optimization of FLASH proton beams using a track-repeating algorithm.

BACKGROUND: Radiation with high dose rate (FLASH) has shown to reduce toxicities to normal tissues around the target and maintain tumor control with the same amount of dose compared to conventional radiation. This phenomenon has been widely studied in electron therapy, which is often used for shallow tumor treatment. Proton therapy is considered a more suitable treatment modality for deep-seated tumors. The feasibility of FLASH proton therapy has recently been demonstrated by a series of pre- and clinical trials. One of the challenges is to efficiently generate wide enough dose distributions in both lateral and longitudinal directions to cover the entire tumor volume. The goal of this paper is to introduce a set of automatic FLASH proton beam optimization algorithms developed recently. PURPOSE: To develop a fast and efficient optimizer for the design of a passive scattering proton FLASH radiotherapy delivery at The University of Texas MD Anderson Proton Therapy Center, based on the fast dose calculator (FDC). METHODS: A track-repeating algorithm, FDC, was validated versus Geant4 simulations and applied to calculate dose distributions in various beamline setups. The design of the components was optimized to deliver homogeneous fields with well-defined diameters between 11.0 and 20.5 mm, as well as a spread-out Bragg peak (SOBP) with modulations between 8.5 and 39.0 mm. A ridge filter, a high-Z material scatterer, and a collimator with range compensator were inserted in the beam path, and their shapes and sizes were optimized to spread out the Bragg peak, widen the beam, and reduce the penumbra. The optimizer was developed and tested using two proton energies (87.0 and 159.5 MeV) in a variety of beamline arrangements. Dose rates of the optimized beams were estimated by scaling their doses to those of unmodified beams. RESULTS: The optimized 87.0-MeV beams, with a distance from the beam pipe window to the phantom surface (window-to-surface distance [WSD]) of 550 mm, produced an 8.5-mm-wide SOBP (proximal 90% to distal 90% of the maximum dose); 14.5, 12.0, and 11.0-mm lateral widths at the 50%, 80%, and 90% dose location, respectively; and a 2.5-mm penumbra from 80% to 20% in the lateral profile. The 159.5-MeV beam had an SOBP of 39.0 mm and lateral widths of 20.5, 15.0, and 12.5 mm at 50%, 80%, and 90% dose location, respectively, when the WSD was 550 mm. Wider lateral widths were obtained with increased WSD. The SOBP modulations changed when the ridge filters with different characteristics were inserted. Dose rates on the beam central axis for all optimized beams (other than the 87.0-MeV beam with 2000-mm WSD) were above that needed for the FLASH effect threshold (40 Gy/s) except at the very end of the depth dose profile scaling with a dose rate of 1400 Gy/s at the Bragg peak in the unmodified beams. The optimizer was able to instantly design the individual beamline components for each of the beamline setups, without the need of time intensive iterative simulations. CONCLUSION: An efficient system, consisting of an optimizer and an FDC have been developed and validated in a variety of beamline setups, comprising two proton energies, several WSDs, and SOBPs. The set of automatic optimization algorithms produces beam shaping element designs efficiently and with excellent quality.

Roadmap: helium ion therapy.

Helium ion beam therapy for the treatment of cancer was one of several developed and studied particle treatments in the 1950s, leading to clinical trials beginning in 1975 at the Lawrence Berkeley National Laboratory. The trial shutdown was followed by decades of research and clinical silence on the topic while proton and carbon ion therapy made debuts at research facilities and academic hospitals worldwide. The lack of progression in understanding the principle facets of helium ion beam therapy in terms of physics, biological and clinical findings persists today, mainly attributable to its highly limited availability. Despite this major setback, there is an increasing focus on evaluating and establishing clinical and research programs using helium ion beams, with both therapy and imaging initiatives to supplement the clinical palette of radiotherapy in the treatment of aggressive disease and sensitive clinical cases. Moreover, due its intermediate physical and radio-biological properties between proton and carbon ion beams, helium ions may provide a streamlined economic steppingstone towards an era of widespread use of different particle species in light and heavy ion therapy. With respect to the clinical proton beams, helium ions exhibit superior physical properties such as reduced lateral scattering and range straggling with higher relative biological effectiveness (RBE) and dose-weighted linear energy transfer (LETd) ranging from ∼4 keVµm-1to ∼40 keVµm-1. In the frame of heavy ion therapy using carbon, oxygen or neon ions, where LETdincreases beyond 100 keVµm-1, helium ions exhibit similar physical attributes such as a sharp lateral penumbra, however, with reduced radio-biological uncertainties and without potentially spoiling dose distributions due to excess fragmentation of heavier ion beams, particularly for higher penetration depths. This roadmap presents an overview of the current state-of-the-art and future directions of helium ion therapy: understanding physics and improving modeling, understanding biology and improving modeling, imaging techniques using helium ions and refining and establishing clinical approaches and aims from learned experience with protons. These topics are organized and presented into three main sections, outlining current and future tasks in establishing clinical and research programs using helium ion beams-A. Physics B. Biological and C. Clinical Perspectives.

Uncertainty in tissue equivalent proportional counter assessments of microdosimetry and RBE estimates in carbon radiotherapy.

Microdosimetry is an important tool for assessing energy deposition distributions from ionizing radiation at cellular and cellular nucleus scales. It has served as an input parameter for multiple common mathematical models, including evaluation of relative biological effectiveness (RBE) of carbon ion therapy. The most common detector used for microdosimetry is the tissue-equivalent proportional counter (TEPC). Although it is widely applied, TEPC has various inherent uncertainties. Therefore, this work quantified the magnitude of TEPC measurement uncertainties and their impact on RBE estimates for therapeutic carbon beams. Microdosimetric spectra and frequency-, dose-, and saturation-corrected dose-mean lineal energy (****) were calculated using the Monte Carlo toolkit Geant4 for five monoenergetic and three spread-out Bragg peak carbon beams in water at every millimeter along the central beam axis. We simulated the following influences on these spectra from eight sources of uncertainty: wall effects, pulse pile-up, electronics, gas pressure, W-value, gain instability, low energy cut-off, and counting statistics. Statistic uncertainty was quantified as the standard deviation of perturbed values for each source. Bias was quantified as the difference between default lineal energy values and the mean of perturbed values for each systematic source. Uncertainties were propagated to RBE using the modified microdosimetric kinetic model (MKM). Variance introduced by statistic sources iny¯Fandy¯Daveraged 3.8% and 3.4%, respectively, and 1.5% iny*across beam depths and energies. Bias averaged 6.2% and 7.3% iny¯Fandy¯D,and 4.8% iny*.These uncertainties corresponded to 1.2 ± 0.9% on average in RBEMKM. The largest contributors to variance and bias were pulse pile-up and wall effects. This study established an error budget for microdosimetric carbon measurements by quantifying uncertainty inherent to TEPC measurements. It is necessary to understand how robust the measurement of RBE model input parameters are against this uncertainty in order to verify clinical model implementation.

Monte Carlo simulation of pixelated CZT detector with Geant4: validation of clinical molecular breast imaging system.

Purpose. Molecular breast imaging (MBI) of99mTc-sestamibi with dual-headed, pixelated, cadmium-zinc-telluride (CZT) detectors is increasingly used in breast cancer care for screening/detecting lesions, monitoring response to therapy, and predicting risk of cancer. MBI as a truly quantitative tool in these applications, however, is limited due the lack of absolute99mTc-sestamibi uptake quantification. To help advance the field of quantitative MBI, we have developed a Monte Carlo simulation application of the GE Discovery NM 750b system.Methods. Our simulation consists of a two-step process using the Geant4 toolkit to model the detector and source geometry and to track photon interactions and a MATLAB script to model the charge transport within the pixelated CZT detector. Simulated detector and detector response model parameters were selected to match measured and simulated standard performance characteristics using various99mTc point-, line-, and film-sources in air. The final model parameters were verified by comparing the count profiles, energy spectra, and region of interest counts between simulated and measured images of a breast phantom with two spherical lesions in 5 cm thick medium of air or water.Results. Final performance characteristics with99mTc sources in air were: (1) energy resolution: 6.1% measured versus 5.9% simulated photopeak full-width at half-maximum (FWHM), (2) spatial resolution: mean error between measured and simulated FWHM of 0.08 mm across 4.4-14.0 mm FWHM range, and (3) sensitivity: 572 cpm/µCi measured versus 567 cpm/µCi simulated (<1% error). Good agreement was observed in the breast phantom line profiles through the spherical lesions and overall energy spectra, with <5% difference in sphere counts between simulated and measured data.Conclusion. A pixelated CZT charge transport and induction model was successfully implemented and validated to simulate imaging with the GE Discovery NM 750b system. This work will enable investigations improving MBI image quality and developing algorithms for uptake quantification.

Effect of spatial distribution of boron and oxygen concentration on DNA damage induced from boron neutron capture therapy using Monte Carlo simulations.

PURPOSE: This paper aims to investigate how the spatial distribution of boron in cells and oxygen concentration affect the DNA damage induced by charged particles in boron neutron capture therapy (BNCT) by Monte Carlo simulations, and further to evaluate the relative biological effectiveness (RBE) of DNA double-strand breaks (DSBs) induction. MATERIALS AND METHODS: The kinetic energy spectra of α, 7Li particles in BNCT arriving at the nucleus surface were obtained from GEANT4 (Geant4 10.05.p01). The DNA damage caused by BNCT was then evaluated using MCDS (MCDS 3.10A). RESULTS: When α or 7Li particles were distributed in the cytomembrane or cytoplasm, the difference in DNA damage of the same types was less than 0.5%. Taking the 137Cs photons as the reference radiation, when the oxygen concentration varied from 0% to 50%, the RBE of 0.54MeV protons and recoil protons varied from 5 to 2, whereas it decreased from 10 to 3 for α or 7Li particles. CONCLUSION: The RBE of DSB induction all charged particles in BNCT decreased with the increase of oxygen concentration. This work indicated that the RBE of different radiation particles of BNCT might be affected by many factors, which should be paid attention to in theoretical research or clinical application.

Mapping the Relative Biological Effectiveness of Proton, Helium and Carbon Ions with High-Throughput Techniques.

Large amounts of high quality biophysical data are needed to improve current biological effects models but such data are lacking and difficult to obtain. The present study aimed to more efficiently measure the spatial distribution of relative biological effectiveness (RBE) of charged particle beams using a novel high-accuracy and high-throughput experimental platform. Clonogenic survival was selected as the biological endpoint for two lung cancer cell lines, H460 and H1437, irradiated with protons, carbon, and helium ions. Ion-specific multi-step microplate holders were fabricated such that each column of a 96-well microplate is spatially situated at a different location along a particle beam path. Dose, dose-averaged linear energy transfer (LETd), and dose-mean lineal energy (yd) were calculated using an experimentally validated Geant4-based Monte Carlo system. Cells were irradiated at the Heidelberg Ion Beam Therapy Center (HIT). The experimental results showed that the clonogenic survival curves of all tested ions were yd-dependent. Both helium and carbon ions achieved maximum RBEs within specific yd ranges before biological efficacy declined, indicating an overkill effect. For protons, no overkill was observed, but RBE increased distal to the Bragg peak. Measured RBE profiles strongly depend on the physical characteristics such as yd and are ion specific.

Author Correction: Exploring the advantages of intensity-modulated proton therapy: experimental validation of biological effects using two different beam intensity-modulation patterns.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Dosimetric and Radiobiological Comparison of Five Techniques for Postmastectomy Radiotherapy with Simultaneous Integrated Boost.

PURPOSE: To compare five techniques for the postmastectomy radiotherapy (PMRT) with simultaneous integrated boost (SIB). MATERIALS AND METHODS: Twenty patients with left-sided breast cancer were retrospectively selected. Five treatment plans were created for each patient: TomoDirect (TD), unblocked helical TomoTherapy (unb-HT), blocked HT (b-HT), hybrid intensity-modulated radiotherapy (hy-IMRT), and fixed-field IMRT (ff-IMRT). A dose of 50.4 Gy in 28 fractions to PTVtotal and 60.2 Gy in 28 fractions to PTVboost were prescribed. The dosimetric parameters for targets and organs at risk (OARs), the normal tissue complication probability (NTCP), the second cancer complication probability (SCCP) for OARs, and the treatment efficiency were assessed and compared. RESULTS: TD plans and hy-IMRT plans had similar good dose coverage and homogeneity for both PTVboost and PTVtotal and superior dose sparing for the lungs and heart. The ff-IMRT plans had similar dosimetric results for the target volumes compared with the TD and hy-IMRT plans, but gave a relatively higher NTCP and SCCP for the lungs. The unb-HT plans exhibited the highest OAR mean dose, highest NTCP for the lungs (0.97 ± 1.25‰) and heart (4.58 ± 3.62%), and highest SCCP for the lungs (3.57 ± 0.05%) and contralateral breast (2.75 ± 0.29%) among all techniques. The b-HT plans significantly outperformed unb-HT plans with respect to the sparing of the lungs and heart. This technique also showed the best conformity index (0.73 ± 0.08) for PTVboost and the optimal NTCP for the lungs (0.03 ± 0.03‰) and heart (0.61 ± 0.73%). Concerning the delivery efficiency, the hy-IMRT and ff-IMRT achieved much higher delivery efficiency compared with TomoTherapy plans. CONCLUSION: Of the five techniques studied, TD and hy-IMRT are considered the preferable options for PMRT with SIB for left-sided breast cancer treatment and can be routinely applied in clinical practice.

Exploring the advantages of intensity-modulated proton therapy: experimental validation of biological effects using two different beam intensity-modulation patterns.

In current treatment plans of intensity-modulated proton therapy, high-energy beams are usually assigned larger weights than low-energy beams. Using this form of beam delivery strategy cannot effectively use the biological advantages of low-energy and high-linear energy transfer (LET) protons present within the Bragg peak. However, the planning optimizer can be adjusted to alter the intensity of each beamlet, thus maintaining an identical target dose while increasing the weights of low-energy beams to elevate the LET therein. The objective of this study was to experimentally validate the enhanced biological effects using a novel beam delivery strategy with elevated LET. We used Monte Carlo and optimization algorithms to generate two different intensity-modulation patterns, namely to form a downslope and a flat dose field in the target. We spatially mapped the biological effects using high-content automated assays by employing an upgraded biophysical system with improved accuracy and precision of collected data. In vitro results in cancer cells show that using two opposed downslope fields results in a more biologically effective dose, which may have the clinical potential to increase the therapeutic index of proton therapy.

A Monte Carlo study of pinhole collimated Cerenkov luminescence imaging integrated with radionuclide treatment.

Cerenkov luminescence imaging (CLI) is an emerging optical imaging technique, which has been widely investigated for biological imaging. In this study, we proposed to integrate the CLI technique with the radionuclide treatment as a "see-and-treat" approach, and evaluated the performance of the pinhole collimator-based CLI technique. The detection of Cerenkov luminescence during radionuclide therapy was simulated using the Monte Carlo technique for breast cancer treatment as an example. Our results show that with the pinhole collimator-based configuration, the location, size and shape of the tumors can be clearly visualized on the Cerenkov luminescence images of the breast phantom. In addition, the CLI of multiple tumors can reflect the relative density of radioactivity among tumors, indicating that the intensity of Cerenkov luminescence is independent of the size and shape of a tumor. The current study has demonstrated the high-quality performance of the pinhole collimator-based CLI in breast tumor imaging for the "see-and-treat" multi-modality treatment.

Using the Proton Energy Spectrum and Microdosimetry to Model Proton Relative Biological Effectiveness.

PURPOSE: We introduce a methodology to calculate the microdosimetric quantity dose-mean lineal energy for input into the microdosimetric kinetic model (MKM) to model the relative biological effectiveness (RBE) of proton irradiation experiments. METHODS AND MATERIALS: The data from 7 individual proton RBE experiments were included in this study. In each experiment, the RBE at several points along the Bragg curve was measured. Monte Carlo simulations to calculate the lineal energy probability density function of 172 different proton energies were carried out with use of Geant4 DNA. We calculated the fluence-weighted lineal energy probability density function (fw(y)), based on the proton energy spectra calculated through Monte Carlo at each experimental depth, calculated the dose-mean lineal energy yD¯ for input into the MKM, and then computed the RBE. The radius of the domain (rd) was varied to reach the best agreement between the MKM-predicted RBE and experimental RBE. A generic RBE model as a function of dose-averaged linear energy transfer (LETD) with 1 fitting parameter was presented and fit to the experimental RBE data as well to facilitate a comparison to the MKM. RESULTS: Both the MKM and LETD-based models modeled the RBE from experiments well. Values for rd were similar to those of other cell lines under proton irradiation that were modeled with the MKM. Analysis of the performance of each model revealed that neither model was clearly superior to the other. CONCLUSIONS: Our 3 key accomplishments include the following: (1) We developed a method that uses the proton energy spectra and lineal energy distributions of those protons to calculate dose-mean lineal energy. (2) We demonstrated that our application of the MKM provides theoretical validation of proton irradiation experiments that show that RBE is significantly greater than 1.1. (3) We showed that there is no clear evidence that the MKM is better than LETD-based RBE models.

Potential for Improvements in Robustness and Optimality of Intensity-Modulated Proton Therapy for Lung Cancer with 4-Dimensional Robust Optimization.

BACKGROUND: Major challenges in the application of intensity-modulated proton therapy (IMPT) for lung cancer patients include the uncertainties associated with breathing motion, its mitigation and its consideration in IMPT optimization. The primary objective of this research was to evaluate the potential of four-dimensional robust optimization (4DRO) methodology to make IMPT dose distributions resilient to respiratory motion as well as to setup and range uncertainties; Methods: The effect of respiratory motion, characterized by different phases of 4D computed tomography (4DCT), was incorporated into an in-house 4DRO system. Dose distributions from multiple setup and range uncertainty scenarios were calculated for each of the ten phases of CT datasets. The 4DRO algorithm optimizes dose distributions to achieve target dose coverage and normal tissue sparing for multiple setup and range uncertainty scenarios as well as for all ten respiratory phases simultaneously. IMPT dose distributions of ten lung cancer patients with different tumor sizes and motion magnitudes were optimized to illustrate our approach and its potential; Results: Compared with treatment plans generated using the conventional planning target volume (PTV)-based optimization and 3D robust optimization (3DRO), plans generated by 4DRO were found to have superior clinical target volume coverage and dose robustness in the face of setup and range uncertainties as well as for respiratory motion. In most of the cases we studied, 4DRO also resulted in more homogeneous target dose distributions. Interestingly, such improvements were found even for cases in which moving diaphragms intruded into the proton beam paths; Conclusion: The incorporation of respiratory motion, along with setup and range uncertainties, into robust optimization, has the potential to improve the resilience of target and normal tissue dose distributions in IMPT plans in the face of the uncertainties considered. Moreover, it improves the optimality of plans compared to PTV-based optimization as well as 3DRO.