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Purpose Varian Halcyon linear accelerator version 2 (The Halcyon 2.0) was recently released with new upgraded features. The aim of this study was to report our clinical experience with Halcyon 2.0 for a dual‐isocenter intensity‐modulated radiation therapy (IMRT) planning and delivery for gynecological cancer patients and examine the feasibility of in vivo portal dosimetry. Methods Twelve gynecological cancer patients were treated with extended‐field IMRT technique using two isocenters on Halcyon 2.0 to treat pelvis and pelvic/or para‐aortic nodes region. The prescription dose was 45 Gy in 25 fractions (fxs) with simultaneous integrated boost (SIB) dose of 55 or 57.5 Gy in 25 fxs to involved nodes. All treatment plans, pretreatment patient‐specific QA and treatment delivery records including daily in vivo portal dosimetry were retrospectively reviewed. For in vivo daily portal dosimetry analysis, each fraction was compared to the reference baseline (1st fraction) using gamma analysis criteria of 4 %/4 mm with 90% of total pixels in the portal image planar dose. Results All 12 extended‐field IMRT plans met the planning criteria and delivered as planned (a total of 300 fractions). Conformity Index (CI) for the primary target was achieved with the range of 0.99–1.14. For organs at risks, most were well within the dose volume criteria. Treatment delivery time was from 5.0 to 6.5 min. Interfractional in vivo dose variation exceeded gamma analysis threshold for 8 fractions out of total 300 (2.7%). These eight fractions were found to have a relatively large difference in small bowel filling and SSD change at the isocenter compared to the baseline. Conclusion Halcyon 2.0 is effective to create complex extended‐field IMRT plans using two isocenters with efficient delivery. Also Halcyon in vivo dosimetry is feasible for daily treatment monitoring for organ motion, internal or external anatomy, and body weight which could further lead to adaptive radiation therapy.

Purpose To compare dosimetric and treatment delivery parameter differences between volumetric‐modulated arc radiotherapy (VMAT) and intensity‐modulated radiotherapy (IMRT) for large volume retroperitoneal sarcomas (RPS). Materials and Methods Both VMAT and IMRT planning were performed on CT datasets of 10 patients with RPS who had been previously treated with preoperative radiotherapy. Plans were optimized to deliver ≥95% dose to the PTV and were evaluated for conformity and homogeneity. Dose to the organs at risk (OARs) (kidney, liver, spinal cord, and bowel space), unspecified tissue, and dose evaluation volumes (DEVs) at 1, 2, and 5 cm from PTV were calculated and compared. Monitor units (MUs) and treatment delivery times were recorded and compared between the two techniques. The deliverability of the large volume RPS VMAT plans was verified by portal dosimetry on a Truebeam™ linac. Results VMAT and IMRT plans were equivalent for PTV coverage and homogeneity (P > 0.05); however, VMAT plans had slightly better conformity index, CI (P < 0.001). Doses to the OARs were not significantly different between VMAT and IMRT plans (P > 0.05). Mean doses to the unspecified tissue as well as at 1, 2, and 5 cm DEVs were lower with VMAT compared with IMRT, P = 0.04 and P < 0.01, respectively. MUs and average beam‐on times were both significantly lower in the VMAT vs IMRT plans, P < 0.001 and P = 0.001, respectively. All VMAT plans passed portal dosimetry delivery verification with an average gamma passing rate of 99.6 ± 0.4%. Conclusions VMAT planning for large volume RPS improved CI, and achieved comparable OAR sparing, as compared with IMRT. As treatment delivery time was lower, the use of VMAT for RPS may translate into improved treatment delivery efficiency.

Intensity‐modulated radiation therapy (IMRT) has become a standard technique in radiation therapy for treating different types of cancers. Various class solutions have been developed for simple cases (e.g., localized prostate, whole breast) to generate IMRT plans efficiently. However, for more complex cases (e.g., head and neck, pelvic nodes), it can be time‐consuming for a planner to generate optimized IMRT plans. To generate optimal plans in these more complex cases which generally have multiple target volumes and organs at risk, it is often required to have additional IMRT optimization structures such as dose limiting ring structures, adjust beam geometry, select inverse planning objectives and associated weights, and additional IMRT objectives to reduce cold and hot spots in the dose distribution. These parameters are generally manually adjusted with a repeated trial and error approach during the optimization process. To improve IMRT planning efficiency in these more complex cases, an iterative method that incorporates some of these adjustment processes automatically in a planning script is designed, implemented, and validated. In particular, regional optimization has been implemented in an iterative way to reduce various hot or cold spots during the optimization process that begins with defining and automatic segmentation of hot and cold spots, introducing new objectives and their relative weights into inverse planning, and turn this into an iterative process with termination criteria. The method has been applied to three clinical sites: prostate with pelvic nodes, head and neck, and anal canal cancers, and has shown to reduce IMRT planning time significantly for clinical applications with improved plan quality. The IMRT planning scripts have been used for more than 500 clinical cases. PACS numbers: 87.55.D, 87.55.de

The purpose was to study correlations amongst IMRT DVH evaluation points and how their relaxation impacts the overall plan. 100 head‐and‐neck cancer cases, using the Eclipse treatment planning system with the same protocol, are statistically analyzed for PTV, brainstem, and spinal cord. To measure variations amongst the plans, we use (i) interquartile range (IQR) of volume as a function of dose, (ii) interquartile range of dose as a function of volume, and (iii) dose falloff. To determine correlations for institutional and ICRU goals, conditional probabilities and medians are computed. We observe that most plans exceed the median PTV dose (average D50 = 104% prescribed dose). Furthermore, satisfying D50 reduced the probability of also satisfying D98, constituting a negative correlation of these goals. On the other hand, satisfying D50 increased the probability of satisfying D2, suggesting a positive correlation. A positive correlation is also observed between the PTV V105 and V110. Similarly, a positive correlation between the brainstem V45 and V50 is measured by an increase in the conditional median of V45, when V50 is violated. Despite the imposed institutional and international recommendations, significant variations amongst DVH points can occur. Even though DVH aims are evaluated independently, sizable correlations amongst them are possible, indicating that some goals cannot be satisfied concurrently, calling for unbiased plan criteria. PACS number(s): 87.55.dk, 87.53.Bn, 87.55.Qr, 87.55.de.

Current commercially available planning systems with Monte Carlo (MC)‐based final dose calculation in IMRT planning employ pencil‐beam (PB) algorithms in the optimization process. Consequently, dose coverage for SBRT lung plans can feature cold‐spots at the interface between lung and tumor tissue. For lung wall (LW)‐seated tumors, there can also be hot spots within nearby normal organs (example: ribs). This study evaluated two different practical approaches to limiting cold spots within the target and reducing high doses to surrounding normal organs in MC‐based IMRT planning of LW‐seated tumors. First, “iterative reoptimization”, where the MC calculation (with PB‐based optimization) is initially performed. The resultant cold spot is then contoured and used as a simultaneous boost volume. The MC‐based dose is then recomputed. The second technique uses noncoplanar beam angles with limited path through lung tissue. Both techniques were evaluated against a conventional coplanar beam approach with a single MC calculation. In all techniques the prescription dose was normalized to cover 95% of the PTV. Fifteen SBRT lung cases with LW‐seated tumors were planned. The results from iterative reoptimization showed that conformity index (CI) and/or PTV dose uniformity (UPTV) improved in 12/15 plans. Average improvement was 13%, and 24%, respectively. Nonimproved plans had PTVs near the skin, trachea, and/or very small lung involvement. The maximum dose to 1cc volume (D1cc) of surrounding OARs decreased in 14/15 plans (average 10%). Using noncoplanar beams showed an average improvement of 7% in 10/15 cases and 11% in 5/15 cases for CI and UPTV, respectively. The D1cc was reduced by an average of 6% in 10/15 cases to surrounding OARs. Choice of treatment planning technique did not statistically significantly change lung V5. The results showed that the proposed practical approaches enhance dose conformity in MC‐based IMRT planning of lung tumors treated with SBRT, improving target dose coverage and potentially reducing toxicities to surrounding normal organs. PACS numbers: 87.55.de, 87.55.kh

Commercially available intensity‐modulated radiation therapy (IMRT) inverse treatment planning systems (ITPS) typically include a smoothing function which allows the user to vary the complexity of delivered beam fluence patterns. This study evaluated the behavior of three ITPSs when varying smoothing parameters. We evaluated four cases treated with IMRT in our clinic: sinonasal carcinoma (SNC), glioblastoma multiforme (GBM), base of tongue carcinoma (BOT), and prostate carcinoma (PST). Varian Eclipse v6.5, BrainLAB BrainScan v5.31, and Nomos Corvus v6.2 ITPSs were studied for the SNC, GBM, and PST sites. Only Eclipse and Corvus were studied for BOT due to field size constraints of the BrainLAB MM3 collimator. For each ITPS, plans were first optimized using vendor‐recommended default “smoothing” values. Treatment plans were then reoptimized, exploring various smoothing values. Key metrics recorded included a delivery complexity (DC) metric and the Ian Paddick Conformality Index (IPCI). Results varied widely by vendor with regard to the impact of smoothing on complexity and conformality. Plans run on the Corvus ITPS showed the logically anticipated increase in DC as smoothing was decreased, along with associated improved organ‐at‐risk (OAR) sparing. Both Eclipse and BrainScan experienced an expected trend for increased DC as smoothing was decreased. However, this increase did not typically result in appreciably improved OAR sparing. For Eclipse and Corvus, and to a much lesser extent BrainScan, increases in smoothing decreased DC but eventually caused unacceptable losses in plan conformality. Depending on the ITPS, potential benefits from optimizing fluence smoothing levels can be significant, allowing for increases in either efficiency or conformality. Because of variability in smoothing function behavior by ITPS, it is important that users familiarize themselves with the effects of varying smoothing parameters for their respective ITPS. Based on the experience gained here, we provide recommended workflows for each ITPS to best exploit the fluence‐smoothing features of the system. PACS numbers: 87.56.bd, 87.56.N‐

The eIMRT platform is a remote distributed computing tool that provides users with Internet access to three different services: Monte Carlo optimization of treatment plans, CRT & IMRT treatment optimization, and a database of relevant radiation treatments/clinical cases. These services are accessible through a user-friendly and platform independent web page. Its flexible and scalable design focuses on providing the final users with services rather than a collection of software pieces. All input and output data (CT, contours, treatment plans and dose distributions) are handled using the DICOM format. The design, implementation, and support of the verification and optimization algorithms are hidden to the user. This allows a unified, robust handling of the software and hardware that enables these computation-intensive services. The eIMRT platform is currently hosted by the Galician Supercomputing Center (CESGA) and may be accessible upon request (there is a demo version at http://eimrt.cesga.es:8080/ eIMRT2/demo; request access in http://eimrt.cesga.es/signup.html). This paper describes all aspects of the eIMRT algorithms in depth, its user interface, and its services. Due to the flexible design of the platform, it has numerous applications including the intercenter comparison of treatment planning, the quality assurance of radiation treatments, the design and implementation of new approaches to certain types of treatments, and the sharing of information on radiation treatment techniques. In addition, the web platform and software tools developed for treatment verification and optimization have a modular design that allows the user to extend them with new algorithms. This software is not a commercial product. It is the result of the collaborative effort of different public research institutions and is planned to be distributed as an open source project. In this way, it will be available to any user; new releases will be generated with the new implemented codes or upgrades This work was financed by Xunta de Galicia of Spain through grant PGIDT05SIN00101CT and by the European Community through the BeInGrid project SI

The control loop in the Varian DMLC system (V4.8) requires ~65 msec to monitor and halt the irradiation of a segment, causing an “overshoot” effect: the segment ends on a fractional monitor unit larger than that planned. As a result, the actual MU delivered may differ from that planned. In general, for step‐and‐shoot treatments, the first segment receives more, the last receives less, and intermediate segments vary. The overshoot for each segment (ΔMU) is small, approximately 0.6 MU at 600 MU/min Our IMRT planning system (Corvus) produces plans often having more than 20% of the segments with less than 1 MU/segment. Such segments may be skipped if the ΔMU exceeds the segments’ planned MU. Furthermore, QA filming often requires reducing the total MU by a factor of 4–6, increasing the potential for dosimetric error. This study measured ΔMU over a range of MU/min and MU/segment. At >5 MU/segment, the ΔMU was stable, corresponding to a delay of 62 msec. ΔMU became larger and more variable at

The dose calculation accuracy of a commercial pencil beam IMRT planning system is evaluated by comparison with Monte Carlo calculations and measurements in an anthropomorphic phantom. The target volume is in the right lung and mediastinum and thus significant tissue inhomogeneities are present. The Monte Carlo code is an adaptation of the msnp code and the measurements were made with TLD and film. Both the Monte Carlo code and the measurements show very good agreement with the treatment planning system except in regions where the dose is high and the electron density is low. In these regions the commercial system shows doses up to 10% higher than Monte Carlo and film. The average calculated dose for the CTV is 5% higher with the commercial system as compared to Monte Carlo. PACS number(s): 87.53.‐j, 87.66.‐a