Massive contractions of myotonic dystrophy type 2-associated CCTG tetranucleotide repeats occur via double-strand break repair with distinct requirements for DNA helicases.

Myotonic dystrophy type 2 (DM2) is a genetic disease caused by expanded CCTG DNA repeats in the first intron of CNBP. The number of CCTG repeats in DM2 patients ranges from 75 to 11,000, yet little is known about the molecular mechanisms responsible for repeat expansions or contractions. We developed an experimental system in Saccharomyces cerevisiae that enables the selection of large-scale contractions of (CCTG)100 within the intron of a reporter gene and subsequent genetic analysis. Contractions exceeded 80 repeat units, causing the final repetitive tract to be well below the threshold for disease. We found that Rad51 and Rad52 are involved in these massive contractions, indicating a mechanism that uses homologous recombination. Srs2 helicase was shown previously to stabilize CTG, CAG, and CGG repeats. Loss of Srs2 did not significantly affect CCTG contraction rates in unperturbed conditions. In contrast, loss of the RecQ helicase Sgs1 resulted in a 6-fold decrease in contraction rate with specific evidence that helicase activity is required for large-scale contractions. Using a genetic assay to evaluate chromosome arm loss, we determined that CCTG and reverse complementary CAGG repeats elevate the rate of chromosomal fragility compared to a short-track control. Overall, our results demonstrate that the genetic control of CCTG repeat contractions is notably distinct among disease-causing microsatellite repeat sequences.

HUNCHEST-II contributes to a shift to earlier-stage lung cancer detection: final results of a nationwide screening program.

OBJECTIVES: The introduction of low-dose CT (LDCT) altered the landscape of lung cancer (LC) screening and contributed to the reduction of mortality rates worldwide. Here we report the final results of HUNCHEST-II, the largest population-based LDCT screening program in Hungary, including the screening and diagnostic outcomes, and the characteristics of the LC cases. METHODS: A total of 4215 high-risk individuals aged between 50 and 75 years with a smoking history of at least 25 pack-years were assigned to undergo LDCT screening. Screening outcomes were determined based on the volume, growth, and volume doubling time of pulmonary nodules or masses. The clinical stage distribution of screen-detected cancers was compared with two independent practice-based databases consisting of unscreened LC patients. RESULTS: The percentage of negative and indeterminate tests at baseline were 74.2% and 21.7%, respectively, whereas the prevalence of positive LDCT results was 4.1%. Overall, 76 LC patients were diagnosed throughout the screening rounds (1.8% of total participants), out of which 62 (1.5%) patients were already identified in the first screening round. The overall positive predictive value of a positive test was 58%. Most screen-detected malignancies were stage I LCs (60.7%), and only 16.4% of all cases could be classified as stage IV disease. The percentage of early-stage malignancies was significantly higher among HUNCHEST-II screen-detected individuals than among the LC patients in the National Koranyi Institute of Pulmonology's archive or the Hungarian Cancer Registry (p < 0.001). CONCLUSIONS: HUNCHEST-II demonstrates that LDCT screening for LC facilitates early diagnosis, thus arguing in favor of introducing systematic LC screening in Hungary. CLINICAL RELEVANCE STATEMENT: HUNCHEST-II is the so-far largest population-based low-dose CT screening program in Hungary. A positive test's overall positive predictive value was 58%, and most screen-detected malignancies were early-stage lesions. These results pave the way for expansive systematic screening in the region. KEY POINTS: • Conducted in 18 medical facilities, HUNCHEST-II is the so far largest population-based low-dose CT screening program in Hungary. • The vast majority of screen-detected malignancies were early-stage lung cancers, and the overall positive predictive value of a positive test was 58%. • HUNCHEST-II facilitates early diagnosis, thus arguing in favor of introducing systematic lung cancer screening in Hungary.

Massive contractions of Myotonic Dystrophy Type 2-associated CCTG tetranucleotide repeats occur via double strand break repair with distinct requirements for helicases.

Myotonic Dystrophy Type 2 (DM2) is a genetic disease caused by expanded CCTG DNA repeats in the first intron of CNBP. The number of CCTG repeats in DM2 patients ranges from 75-11,000, yet little is known about the molecular mechanisms responsible for repeat expansions or contractions. We developed an experimental system in Saccharomyces cerevisiae that enables selection of large-scale contractions of (CCTG)100 within the intron of a reporter gene and subsequent genetic analysis. Contractions exceeded 80 repeat units, causing the final repetitive tract to be well below the threshold for disease. We found that Rad51 and Rad52 are required for these massive contractions, indicating a mechanism that involves homologous recombination. Srs2 helicase was shown previously to stabilize CTG, CAG, and CGG repeats. Loss of Srs2 did not significantly affect CCTG contraction rates in unperturbed conditions. In contrast, loss of the RecQ helicase Sgs1 resulted in a 6-fold decrease in contraction rate with specific evidence that helicase activity is required for large-scale contractions. Using a genetic assay to evaluate chromosome arm loss, we determined that CCTG and reverse complementary CAGG repeats elevate the rate of chromosomal fragility compared to a low-repeat control. Overall, our results demonstrate that the genetic control of CCTG repeat contractions is notably distinct among disease-causing microsatellite repeat sequences.

Optimum collision energies for proteomics: The impact of ion mobility separation.

Ion mobility spectrometry (IMS) is a widespread separation technique used in various research fields. It can be coupled to liquid chromatography-mass spectrometry (LC-MS/MS) methods providing an additional separation dimension. During IMS, ions are subjected to multiple collisions with buffer gas, which may cause significant ion heating. The present project addresses this phenomenon from the bottom-up proteomics point of view. We performed LC-MS/MS measurements on a cyclic ion mobility mass spectrometer with varied collision energy (CE) settings both with and without IMS. We investigated the CE dependence of identification score, using Byonic search engine, for more than 1000 tryptic peptides from HeLa digest standard. We determined the optimal CE values-giving the highest identification score-for both setups (i.e., with and without IMS). Results show that lower CE is advantageous when IMS separation is applied, by 6.3 V on average. This value belongs to the one-cycle separation configuration, and multiple cycles may supposedly have even larger impact. The effect of IMS is also reflected in the trends of optimal CE values versus m/z functions. The parameters suggested by the manufacturer were found to be almost optimal for the setup without IMS; on the other hand, they are obviously too high with IMS. Practical consideration on setting up a mass spectrometric platform hyphenated to IMS is also presented. Furthermore, the two CID (collision induced dissociation) fragmentation cells of the instrument-located before and after the IMS cell-were also compared, and we found that CE adjustment is needed when the trap cell is used for activation instead of the transfer cell. Data have been deposited in the MassIVE repository (MSV000090944).

Collision-Induced Dissociation of Citrullinated Peptide Anions.

Peptide identification by positive electrospray ionization (ES+) tandem mass spectrometry (MS/MS) is a well-established strategy in proteomics. Several research groups reported the usefulness of negative electrospray ionization (ES-) for gaining complementary structural information on peptides and their post-translational modifications (PTM) compared to ES+. Fragmentation of citrullinated peptides has not been previously explored in ES-. In this study, 9 peptides containing citrulline residues were investigated in ES- by stepwise collision energy-dependent measurements on a QTOF instrument and a Q-Orbitrap instrument. Our results of high resolution and mass accuracy show the favored citrulline-selective loss of HNCO from these peptide precursors and their fragments─similarly to that in ES+─along with y-NH3/z, c, c-NH3/b sequence ions. Loss of HNCO from citrullinated peptides in ES- and a proposed mechanism for the reaction have been described here for the first time. HNCO loss intensities from precursors were generally even higher than that in ES+. Interestingly, the most intense fragments corresponded to neutral losses from sequence ions while intact sequence ions were usually minor components of the spectra. High-intensity ions related to cleavages N-terminal to Asp and Glu residues that have been previously reported were also observed. On the other hand, a relatively high number of peaks were observed, possibly due to internal fragmentation and/or scrambling events. While (ES-) MS/MS spectra always require manual inspection and the annotation may be ambiguous, the favorable loss of HNCO and the preferable cleavage N-terminal to Asp residues can be used to differentiate between citrullinated/deamidated sequences.

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.

Target-seq: single workflow for detection of genome integration site, DNA translocation and off-target events.

Designed donor DNA delivery through viral or nonviral systems to target loci in the host genome is a critical step for gene therapy. Adeno-associated virus and lentivirus are leading vehicles for in vivo and ex vivo delivery of therapeutic genes due to their high delivery and editing efficiency. Nonviral editing tools, such as CRISPR/Cas9, are getting more attention for gene modification. However, there are safety concerns; for example, tumorigenesis due to off-target effects and DNA rearrangement. Analysis tools to detect and characterize on-target and off-target genome modification post editing in the host genome are pivotal for evaluating the success and safety of gene therapy. We developed Target-seq combined with different analysis tools to detect the genome integration site, DNA translocation and off-target events.

Compositional Analysis of Glycosaminoglycans in Different Lung Cancer Types-A Pilot Study.

Lung cancer is one of the most commonly diagnosed cancer types. Studying the molecular changes that occur in lung cancer is important to understand tumor formation and identify new therapeutic targets and early markers of the disease to decrease mortality. Glycosaminoglycan chains play important roles in various signaling events in the tumor microenvironment. Therefore, we have determined the quantity and sulfation characteristics of chondroitin sulfate and heparan sulfate in formalin-fixed paraffin-embedded human lung tissue samples belonging to different lung cancer types as well as tumor adjacent normal areas. Glycosaminoglycan disaccharide analysis was performed using HPLC-MS following on-surface lyase digestion. Significant changes were identified predominantly in the case of chondroitin sulfate; for example, the total amount was higher in tumor tissue compared to the adjacent normal tissue. We also observed differences in the degree of sulfation and relative proportions of individual chondroitin sulfate disaccharides between lung cancer types and adjacent normal tissue. Furthermore, the differences in the 6-O-/4-O-sulfation ratio of chondroitin sulfate were different between the lung cancer types. Our pilot study revealed that further investigation of the role of chondroitin sulfate chains and enzymes involved in their biosynthesis is an important aspect of lung cancer research.

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.

Sport Motivation from the Perspective of Health, Institutional Embeddedness and Academic Persistence among Higher Educational Students.

Regular physical activity from an early age is an important part of a healthy life because if we incorporate exercise early into our lifestyle, we are more likely to maintain our commitment to sport into adulthood and even throughout our lives. In our research, we used the PERSIST 2019 database, which contains data from students at higher education institutions in Hungary, Slovakia, Romania, Ukraine, and Serbia. We used factor analysis to isolate four sports motivation factors (intrinsic, introjected, extrinsic, and amotivation). Factors influencing the different types were measured using linear regression analysis, involving the variables in four models. The results show that the effects of the sociodemographic variables are significant for gender, country, and mother's job, especially in terms of intrinsic, introjected, and extrinsic motivation. The role of coping is salient for health awareness factors, with a positive effect on intrinsic motivation and a negative effect on the other types. The impacts of quality of education and support are typically negative, while the positive effect of satisfaction with infrastructure is noteworthy. The effect of persistence in sport on intrinsic and introjected motivation is positive. Frequency of training increases intrinsic motivation, while practical sport embeddedness generates extrinsic motivation. In terms of relationships, a mainly teacher-oriented network within the institution typically has a negative effect on intrinsic motivation, while peer relationships outside the institution typically increase intrinsic and extrinsic sport motivation. Academic persistence has a positive effect on intrinsic motivation and a negative effect on introjected motivation. Our research highlights the complexity of factors influencing sport motivation and the role of coping, which typically remains strong when relationship-related variables are included. In addition, we must emphasise the dominant role of relationship network patterns, which may even reduce commitment to sport.

Technical note: Optimal allocation of limited proton therapy resources using model-based patient selection.

PURPOSE: We consider the following scenario: A radiotherapy clinic has a limited number of proton therapy slots available each day to treat cancer patients of a given tumor site. The clinic's goal is to minimize the expected number of complications in the cohort of all patients of that tumor site treated at the clinic, and thereby maximize the benefit of its limited proton resources. METHODS: To address this problem, we extend the normal tissue complication probability (NTCP) model-based approach to proton therapy patient selection to the situation of limited resources at a given institution. We assume that, on each day, a newly diagnosed patient is scheduled for treatment at the clinic with some probability and with some benefit Δ N T C P $\Delta NTCP$ from protons over photons, which is drawn from a probability distribution. When a new patient is scheduled for treatment, a decision for protons or photons must be made, and a patient may wait only for a limited amount of time for a proton slot becoming available. The goal is to determine the Δ N T C P $\Delta NTCP$ thresholds for selecting a patient for proton therapy, which optimally balance the competing goals of making use of all available slots while not blocking slots with patients with low benefit. This problem can be formulated as a Markov decision process (MDP) and the optimal thresholds can be determined via a value-policy iteration method. RESULTS: The optimal Δ N T C P $\Delta NTCP$ thresholds depend on the number of available proton slots, the average number of patients under treatment, and the distribution of Δ N T C P $\Delta NTCP$ values. In addition, the optimal thresholds depend on the current utilization of the facility. For example, if one proton slot is available and a second frees up shortly, the optimal Δ N T C P $\Delta NTCP$ threshold is lower compared to a situation where all but one slot remain blocked for longer. CONCLUSIONS: MDP methodology can be used to augment current NTCP model-based patient selection methods to the situation that, on any given day, the number of proton slots is limited. The optimal Δ N T C P $\Delta NTCP$ threshold then depends on the current utilization of the proton facility. Although, the optimal policy yields only a small nominal benefit over a constant threshold, it is more robust against variations in patient load.

Stepwise Collision Energy-Resolved Tandem Mass Spectrometric Experiments for the Improved Identification of Citrullinated Peptides.

The use of tandem mass spectrometry (MS/MS) is a fundamental prerequisite of reliable protein identification and quantification in mass-spectrometry-based proteomics. In bottom-up and middle-down proteomics, proteins are identified by the characteristic fragments of their constituting peptides. Post-translational modifications (PTMs) often further complicate proteome analyses. Citrullination is an increasingly studied PTM converting arginines to citrullines (Cit, X) and is implicated in several autoimmune and neurological diseases as well as different types of cancer. Confirmation of citrullination is known to be very challenging since it results in the same molecular mass change as Asn/Gln deamidation. In this study, we explore which MS/MS characteristics can be used for the reliable identification of citrullination. We synthesized several peptides incorporating Cit residues that model enzymatic cleavages of different proteins with verified or putative citrullination. Collision-induced dissociation was used to investigate the energy dependence of Byonic and Mascot scores and confirmed sequence coverage (CSC) along with the neutral loss of HNCO characteristic to citrulline side chains. We found that although the recommended values (19-45 V) for ramped collision energy settings cover the optimal Mascot, Byonic, or %CSC scores effectively, the diagnostic HNCO loss from precursors and fragments may reach their maximum intensities at lower and higher collision energies, respectively. Therefore, we suggest broadening the ramp range to ∼5-60 V to obtain more favorable identification rates for citrullinated peptides. We also found that Byonic was more successful in correctly identifying citrullinated peptides with deamidated residues than Mascot.

Dislocation avalanches from strain-controlled loading: A discrete dislocation dynamics study.

We study strain-controlled plastic deformation of crystalline solids via two-dimensional discrete dislocation dynamics simulations. To this end, we characterize the average stress-strain curves as well as the statistical properties of strain bursts and the related stress drops as a function of the imposed strain rate and the stiffness of the specimen-machine system. The dislocation system exhibits strain-rate sensitivity such that a larger imposed strain rate results in a higher average stress at a given strain. In the limit of small strain rate and driving spring stiffness, the sizes and durations of the dislocation avalanches are power law distributed up to a cutoff scale, and exhibit temporally asymmetric average shapes. We discuss the dependence of the results on the driving parameters and compare our results to those from previous simulations where quasistatic stress-controlled loading was used.

Optimal Allocation of Proton Therapy Slots in Combined Proton-Photon Radiation Therapy.

PURPOSE: Proton therapy is a limited resource that is not available to all patients who may benefit from it. We investigated combined proton-photon treatments, in which some fractions are delivered with protons and the remaining fractions with photons, as an approach to maximize the benefit of limited proton therapy resources at a population level. METHODS AND MATERIALS: To quantify differences in normal-tissue complication probability (NTCP) between protons and photons, we considered a cohort of 45 patients with head and neck cancer for whom intensity modulated radiation therapy and intensity modulated proton therapy plans were previously created, in combination with NTCP models for xerostomia and dysphagia considered in the Netherlands for proton patient selection. Assuming limited availability of proton slots, we developed methods to optimally assign proton fractions in combined proton-photon treatments to minimize the average NTCP on a population level. The combined treatments were compared with patient selection strategies in which patients are assigned to single-modality proton or photon treatments. RESULTS: There is a benefit of combined proton-photon treatments compared with patient selection, owing to the nonlinearity of NTCP functions; that is, the initial proton fractions are the most beneficial, whereas additional proton fractions have a decreasing benefit when a flatter part of the NTCP curve is reached. This effect was small for the patient cohort and NTCP models considered, but it may be larger if dose-response relationships are better known. In addition, when proton slots are limited, patient selection methods face a trade-off between leaving slots unused and blocking slots for future patients who may have a larger benefit. Combined proton-photon treatments with flexible proton slot assignment provide a method to make optimal use of all available resources. CONCLUSIONS: Combined proton-photon treatments allow for better use of limited proton therapy resources. The benefit over patient selection schemes depends on the NTCP models and the dose differences between protons and photons.

New North American Isolates of Venturia inaequalis Can Overcome Apple Scab Resistance of Malus floribunda 821.

Apple scab, caused by Venturia inaequalis, is a destructive fungal disease of major apple cultivars worldwide, most of which are moderately to highly susceptible. Thus, development of scab resistant cultivars is one of the highest priorities of apple breeding programs. The principal source of resistance for breeding programs has been the scab resistance gene Rvi6 that originated from the Japanese crabapple Malus floribunda (Sieb.) sel. 821. Isolates of V. inaequalis able to overcome Rvi6 have been identified in Europe, but have not yet been reported on the American continents. We recently discovered scab infection on M. floribunda 821 trees in a research orchard at Geneva, NY, U.S.A., where approximately 10% of the leaves bore profusely sporulating apple scab lesions, many of which had coalesced to cover entire leaves. We observed both chlorosis, typical to Rvi6, and pinpoint pitting symptoms typical to failed infections by V. inaequalis on hosts bearing the Rvi7 gene. We assessed genetic diversity and population genetic structure of 11 V. inaequalis isolates in total, of North American and European origin, isolated from M. floribunda 821, 'Nova Easygro', 'Golden Delicious', TSR33T239, 'Schone van Boskoop', and 'Prima', using 16,321 genome-wide SNPs. Population genetic structure and PCA separated the isolates into distinct European and U.S. groups. The forgoing suggests that the new Rvi6 virulent isolates emerged within U.S. populations, rather than being transported from Europe. The complete resistance breakdown in M. floribunda 821 but not in descendant cultivars, which kept their field resistance, suggests that durable resistance to apple scab will require a more comprehensive understanding of Rvi6 mediated resistance in diverse genetic backgrounds.

Robust spatiotemporal fractionation schemes in the presence of patient setup uncertainty.

PURPOSE: Spatiotemporal fractionation schemes for photon radiotherapy have recently arisen as a promising technique for healthy tissue sparing. Because spatiotemporally fractionated treatments have a characteristic pattern of delivering high doses to different parts of the tumor in each fraction, uncertainty in patient positioning is an even more pressing concern than in conventional uniform fractionation. Until now, such concerns in patient setup uncertainty have not been addressed in the context of spatiotemporal fractionation. METHODS: A stochastic optimization model is used to incorporate patient setup uncertainty to optimize spatiotemporally fractionated plans using expected penalties for deviations from prescription values. First, a robust uniform reference plan is optimized with a stochastic optimization model. Then, a spatiotemporal plan is optimized with a constrained stochastic optimization model that minimizes a primary clinical objective and constrains the spatiotemporal plan to be at least as good as the uniform reference plan with respect to all other objectives. A discrete probability distribution is defined to characterize the random setup error occurring in each fraction. For the optimization of uniform plans, the expected penalties are computed exactly by exploiting the symmetry of the fractions, and for the spatiotemporal plans, quasi-Monte Carlo sampling is used to approximate the expectation. RESULTS: Using five clinical liver cases, it is demonstrated that spatiotemporally fractionated treatment plans maintain the same robust tumor coverage as a stochastic uniform reference plan and exhibit a reduction in the expected mean BED of the uninvolved liver. This is observed for a spectrum of probability distributions of random setup errors with shifts in the patient position of up to 5 mm from the nominal position. For probability distributions with small variance in the patient position, the spatiotemporal plans exhibit an 8-30% reduction in expected mean BED in the healthy liver tissue for shifts up to 2.5 mm and reductions of 5-25% for shifts up to 5 mm. CONCLUSIONS: In the presence of patient setup uncertainty, spatiotemporally fractionated treatment plans exhibit the same robust tumor coverage as their uniformly fractionated counterparts and still retain the benefit in sparing healthy tissues.

Optimization of spatiotemporally fractionated radiotherapy treatments with bounds on the achievable benefit.

Spatiotemporal fractionation schemes, that is, treatments delivering different dose distributions in different fractions, can potentially lower treatment side effects without compromising tumor control. This can be achieved by hypofractionating parts of the tumor while delivering approximately uniformly fractionated doses to the surrounding tissue. Plan optimization for such treatments is based on biologically effective dose (BED); however, this leads to computationally challenging nonconvex optimization problems. Optimization methods that are in current use yield only locally optimal solutions, and it has hitherto been unclear whether these plans are close to the global optimum. We present an optimization framework to compute rigorous bounds on the maximum achievable normal tissue BED reduction for spatiotemporal plans. The approach is demonstrated on liver tumors, where the primary goal is to reduce mean liver BED without compromising any other treatment objective. The BED-based treatment plan optimization problems are formulated as quadratically constrained quadratic programming (QCQP) problems. First, a conventional, uniformly fractionated reference plan is computed using convex optimization. Then, a second, nonconvex, QCQP model is solved to local optimality to compute a spatiotemporally fractionated plan that minimizes mean liver BED, subject to the constraints that the plan is no worse than the reference plan with respect to all other planning goals. Finally, we derive a convex relaxation of the second model in the form of a semidefinite programming problem, which provides a rigorous lower bound on the lowest achievable mean liver BED. The method is presented on five cases with distinct geometries. The computed spatiotemporal plans achieve 12-35% mean liver BED reduction over the optimal uniformly fractionated plans. This reduction corresponds to 79-97% of the gap between the mean liver BED of the uniform reference plans and our lower bounds on the lowest achievable mean liver BED. The results indicate that spatiotemporal treatments can achieve substantial reductions in normal tissue dose and BED, and that local optimization techniques provide high-quality plans that are close to realizing the maximum potential normal tissue dose reduction.

Spatiotemporal fractionation schemes for liver stereotactic body radiotherapy.

BACKGROUND AND PURPOSE: Dose prescription in stereotactic body radiotherapy (SBRT) for liver tumors is often limited by the mean liver dose. We explore the concept of spatiotemporal fractionation as an approach to facilitate further dose escalation in liver SBRT. MATERIALS AND METHODS: Spatiotemporal fractionation schemes aim at partial hypofractionation in the tumor along with near-uniform fractionation in normal tissues. This is achieved by delivering distinct dose distributions in different fractions, which are designed such that each fraction delivers a high single fraction dose to complementary parts of the tumor while creating a similar dose bath in the surrounding noninvolved liver. Thereby, higher biologically effective doses (BED) can be delivered to the tumor without increasing the mean BED in the liver. Planning of such treatments is performed by simultaneously optimizing multiple dose distributions based on their cumulative BED. We study this concept for five liver cancer patients with different tumor geometries. RESULTS: Spatiotemporal fractionation presents a method of increasing the ratio of prescribed tumor BED to mean BED in the noninvolved liver by approximately 10-20%, compared to conventional SBRT using identical fractions. CONCLUSIONS: Spatiotemporal fractionation may reduce the risk of liver toxicity or facilitate dose escalation in liver SBRT in circumstances where the mean dose to the non-involved liver is the prescription-limiting factor.

Technical Note: Improving the VMERGE treatment planning algorithm for rotational radiotherapy.

PURPOSE: The authors revisit the VMERGE treatment planning algorithm by Craft et al. ["Multicriteria VMAT optimization," Med. Phys. 39, 686-696 (2012)] for arc therapy planning and propose two changes to the method that are aimed at improving the achieved trade-off between treatment time and plan quality at little additional planning time cost, while retaining other desirable properties of the original algorithm. METHODS: The original VMERGE algorithm first computes an "ideal," high quality but also highly time consuming treatment plan that irradiates the patient from all possible angles in a fine angular grid with a highly modulated beam and then makes this plan deliverable within practical treatment time by an iterative fluence map merging and sequencing algorithm. We propose two changes to this method. First, we regularize the ideal plan obtained in the first step by adding an explicit constraint on treatment time. Second, we propose a different merging criterion that comprises of identifying and merging adjacent maps whose merging results in the least degradation of radiation dose. RESULTS: The effect of both suggested modifications is evaluated individually and jointly on clinical prostate and paraspinal cases. Details of the two cases are reported. CONCLUSIONS: In the authors' computational study they found that both proposed modifications, especially the regularization, yield noticeably improved treatment plans for the same treatment times than what can be obtained using the original VMERGE method. The resulting plans match the quality of 20-beam step-and-shoot IMRT plans with a delivery time of approximately 2 min.

A modular approach to intensity-modulated arc therapy optimization with noncoplanar trajectories.

Utilizing noncoplanar beam angles in volumetric modulated arc therapy (VMAT) has the potential to combine the benefits of arc therapy, such as short treatment times, with the benefits of noncoplanar intensity modulated radiotherapy (IMRT) plans, such as improved organ sparing. Recently, vendors introduced treatment machines that allow for simultaneous couch and gantry motion during beam delivery to make noncoplanar VMAT treatments possible. Our aim is to provide a reliable optimization method for noncoplanar isocentric arc therapy plan optimization. The proposed solution is modular in the sense that it can incorporate different existing beam angle selection and coplanar arc therapy optimization methods. Treatment planning is performed in three steps. First, a number of promising noncoplanar beam directions are selected using an iterative beam selection heuristic; these beams serve as anchor points of the arc therapy trajectory. In the second step, continuous gantry/couch angle trajectories are optimized using a simple combinatorial optimization model to define a beam trajectory that efficiently visits each of the anchor points. Treatment time is controlled by limiting the time the beam needs to trace the prescribed trajectory. In the third and final step, an optimal arc therapy plan is found along the prescribed beam trajectory. In principle any existing arc therapy optimization method could be incorporated into this step; for this work we use a sliding window VMAT algorithm. The approach is demonstrated using two particularly challenging cases. The first one is a lung SBRT patient whose planning goals could not be satisfied with fewer than nine noncoplanar IMRT fields when the patient was treated in the clinic. The second one is a brain tumor patient, where the target volume overlaps with the optic nerves and the chiasm and it is directly adjacent to the brainstem. Both cases illustrate that the large number of angles utilized by isocentric noncoplanar VMAT plans can help improve dose conformity, homogeneity, and organ sparing simultaneously using the same beam trajectory length and delivery time as a coplanar VMAT plan.