Malignancies localized to the head and neck region often are in close proximity to critical organs at risk (OARs). Providing effective treatment to these malignancies while minimizing the integral dose to surrounding OARs is advantageous. Our aim is to evaluate dosimetric data of OARs in patients with head and neck tumors treated with either volumetric modulated arc therapy (VMAT) or proton beam therapy (PBT). In a single institution study, we identified patients with head and neck tumors that were localized to the ipsilateral neck or skull base and were treated with PBT. All patients at our institution treated with PBT have a comparison VMAT plan. Averages of the mean and maximum doses for the brain avoidance, bilateral optic structures, cochlea, parotids, oral cavity, larynx and esophagus were calculated for all patients. These values were compared between treatment modalities using Wilcoxon test, with use of the Benjamini–Hochberg correction for multiple comparisons. P-values less than 0.05 were considered significant. A total of thirty-two patients were identified. The male to female ratio was 22 to 10. The median age of our patients was 69 years. Median dose delivered to the target volume was 60 cGyE (55.8-70 cGyE). Target volume coverage was similar in both PBT and VMAT plans. PBT plans showed a significant reduction to the mean and maximum doses to the contralateral parotid glands, larynx, brain avoidance, and oral cavity. PBT plans also showed a reduction in the maximum doses to the lens, optic nerves, chiasm, cochlea, esophagus, and ipsilateral parotid glands (see Table 1 for more details, *p < 0.05) PBT resulted in meaningful dose reductions to OARs while maintaining comparable target coverage when compared to VMAT plans. Further refinements in proton beam treatment may have the potential to further minimize dose to critical structures in the skull base and head and neck location.Tabled 1Abstract 2838; Table; Dose (cGyE and Gy) to OARs for Proton and VMAT PlansOrgan at RiskMean ProtonMean VMATMean DifferenceP-valueIpsilateral EyeMean dose16.9413.863.080.76Max dose37.0938.831.740.004*Contralateral EyeMean dose11.2812.150.870.52Max dose34.933.021.890.004*Ipsilateral Optic NerveMean dose28.1230.182.070.3Max dose39.7238.521.210.03*Contralateral Optic NerveMean dose28.3429.10.760.52Max dose37.8940.93.010.02*Optic ChiasmMean dose22.130.228.120.24Max dose36.2741.885.620.004*Ipsilateral CochleaMean dose24.5935.3910.80.24Max dose29.840.0810.270.01*Ipsilateral ParotidMean dose28.1630.612.450.48Max dose39.858.8219.020.03*Contralateral ParotidMean dose7.425.991.430.009*Max dose5.6514.158.50.001*Brain AvoidanceMean dose2.989.636.660.001*Max dose60.6262.031.41<0.001*LarynxMean dose19.1727.918.740.009*Max dose58.2557.840.41<0.001*EsophagusMean dose15.918.522.620.52Max dose34.9537.192.240.01*Oral CavityMean dose13.923.849.940.009*Max dose10.7459.731.17<0.001* Open table in a new tab

The European Organization for Research and Treatment of Cancer (EORTC) and the World Health Organization (WHO) classification system describes three main types of primary cutaneous B cell lymphomas: primary cutaneous follicle center lymphoma (PCFCL), primary cutaneous marginal zone lymphoma (PCMZL), and primary cutaneous diffuse large B-cell lymphoma, leg type (PCLBCL, LT). Prognosis for PCFCL and PCMZL is excellent, with 5 year survival rates between 90% and 100% for both types. PCLBCL, LT on the other hand, has a worse prognosis with 5 year survival rates of 45%-50%. Exclusion of systemic disease is important as B cell lymphoma localized to the skin has a different clinical behavior, prognosis, and treatment approach compared to those with nodal and visceral involvement. This article is protected by copyright. All rights reserved.

Background: Reduced intensity conditioning (RIC) for hematopoietic cell transplant (HCT) are better tolerated than myeloablative conditioning regimens and permit HCT in patients with advanced age. However, RIC is associated with increased risk of disease relapse. The addition of targeted marrow irradiation (TMI) to RIC may permit intensification and increased disease control without additional toxicity. We conducted a phase I dose escalation trial of TMI in combination with fludarabine and busulfan (flu/bu) RIC for high-risk hematologic malignancy patients. Methods: Eligible patients were 18 years or older, diagnosed with high-risk hematologic malignancies and candidates for an allogeneic HCT with available matched related (MRD) or unrelated donor (MUD). Eligible subjects were not candidates to receive myeloablative conditioning. TMI, 1.5 Gy was given twice daily on days T-10 through T-7. Dose escalation was done by increasing the number of fractions; dose levels included 1.5 Gy (n = 3), 3 Gy (n = 4), 4.5 Gy (n = 3) and 6 Gy (n = 2); fludarabine, 30 mg/m2/day, was given on T-6 through T-2 and busulfan was given on days T-5 and T-4 with a daily dose of 4800 microM⋅minute. Results: 9 subjects were enrolled, median age was 66 years (range 25-74), baseline diagnoses included acute myeloid leukemia (n = 3), myelodysplastic syndrome (n = 2), myeloproliferative disorder, non-Hodgkin lymphoma, multiple myeloma and T prolymphocytic leukemia (all n = 1). Median number of prior treatments was 3 (range 1-10). Median Charlson comorbidity index (CCMI) was 4 (range 1-7) and Hematopoietic Cell Transplantation-Specific Comorbidity Index (HCT-CI) was 1 (range 1-5). Stem cell source was a MUD in all cases. Neutrophil and platelet engraftment occurred at a median of 15 (range 11-17) and 24 (range 15-11) days, respectively. The maximum tolerated dose (MTD) of TMI was 4.5 Gy, with 2 subjects experiencing grade IV mucositis at the 6 Gy dose level. Grade 3 hyperbilirubinemia was observed in both subjects treated at the 6 Gy dose level, secondary to hepatic veno-occlusive disease and to severe sepsis and hypotension. Three subjects presented grade II-III acute GVDH. At a median follow up of 6 months, six patients have died; Kaplan Meier estimate of overall survival was 60%, with relapse free survival of 50%; the incidence of non-relapse mortality was 11%. Conclusions: The combination of TMI with flu/bu conditioning prior to transplant is feasible in a population of high-risk hematologic malignancy patients, with a MTD of 4.5 Gy. Mucositis and reversible hepatotoxicity are the dose limiting toxicities of this combination. Careful patient selection and monitoring may allow use of TMI plus flu/bu conditioning in patients at high risk of toxicity and relapse after transplant. Future studies are aimed at investigating whether further dose escalation of TMI is feasible in younger, fitter HCT patients.

Estimating the proper margins for the planning target volume (PTV) could be a challenging task in cases where the organ undergoes significant changes during the course of radiotherapy treatment. Developments in image-guidance and the presence of onboard imaging technologies facilitate the process of correcting setup errors. However, estimation of errors to organ motions remain an open question due to the lack of proper software tools to accompany these imaging technological advances. Therefore, we have developed a new tool for visualization and quantification of deformations from daily images. The tool allows for estimation of tumor coverage and normal tissue exposure as a function of selected margin (isotropic or anisotropic). Moreover, the software allows estimation of the optimal margin based on the probability of an organ being present at a particular location. Methods based on swarm intelligence, specifically Ant Colony Optimization (ACO) are used to provide an efficient estimate of the optimal margin extent in each direction. ACO can provide global optimal solutions in highly nonlinear problems such as margin estimation. The proposed method is demonstrated using cases from gastric lymphoma with daily TomoTherapy megavoltage CT (MVCT) contours. Preliminary results using Dice similarity index are promising and it is expected that the proposed tool will be very helpful and have significant impact for guiding future margin definition protocols.

PURPOSE To compare the difference in Hounsfield unit-relative stopping power and evaluate the dosimetric impact of spectral vs. conventional CT on proton therapy treatment plans. METHOD The Philips prototype (IQon), a detector-based, spectral CT system (spectral) was used to scan calibration and Rando phantoms. Data were reconstructed with and without energy decomposition to produce monoenergetic 70 keV, 140 keV, and the Zeff images. Relative stopping power (RSP) in the head and lung regions were evaluated as a function of HU in order to compare spectral and conventional CT. Treatment plans for the Rando phantom were also generated and used to produce DVHs of fictitious target volume and organ-at-risk contoured on the head and lung. RESULTS Agreement of the Zeff of the tissue-substitute materials determined using spectral CT agrees to within 1 to 5% of the Zeff of the known phantom composition. The discrepancy is primarily attributed to non-uniformity in the phantom. Differences between the HU-RSP curves obtained using spectral and conventional CT were small except for in the lung curve at HU>1000. The large difference in planned doses using Spectral vs. conventional CT occurred in a low-dose brain region (1.7mm between the locations of the 100 cGy lines and 3 mm for 50 cGy lines). CONCLUSION Conventionally, a single HU-RSP from CT scanner is used in proton treatment planning. Spectral CT allows site-specific HU-RSP for each patient. Spectral and conventional HU-RSP may result in different distributions as shown here. Additional study is required to evaluate the impact of Spectral CT in proton treatment planning. This study is part of a research agreement between Philips and University Hospitals/Case Medical Center.

Purpose: In this study, we investigate the effect of setup uncertainty on DVH calculations which may impact plan comparison. Methods: Treatment plans (6 MV VMAT calculated on Pinnacle TPS) were chosen for different disease sites: brain, prostate, H&N and spine in this retrospective study. A proton plan (PP) using double scattering beams was generated for each selected VMAT plan subject to the same set of dose-volume constraints as in VMAT. An uncertainty analysis was incorporated on the DVH calculations in which isocenter shifts from 1 to 5 mm in each of the ±x, ±y and ±z directions were used to simulate the setup uncertainty and residual positioning errors. A total of 40 different combinations of isocenter shifts were used in the re-calculation of DVH of the PTV and the various OARs for both the VMAT and the corresponding PT. Results: For the brain case, both VMAT and PP are comparable in PTV coverage and OAR sparing, and VMAT is a clear choice for treatment due to its ease of delivery. However, when incorporating isoshifts in DVH calculations, a significant change in dose-volume relationship emerges. For example, both VMAT and PT provide adequate coverage, even with ±3mm isoshift. However, +3mm isoshift results in increase of V40(Lcochlea, VMAT) from 7.2% in the original plan to 45% and V40(R cochlea, VMAT) from 75% to 92%. For protons, V40(Lcochlea, PT) increases from 62% in the initial plan to 75%, while V40(Rcochea, PT) increases from 7% to 26%. Conclusion: DVH alone may not be sufficient to allow an unequivocal decision in plan comparison, especially when two rival plans are very similar in both PTV coverage and OAR sparing. It is a good practice to incorporate uncertainty analysis on photon and proton plan comparison studies to test the plan robustness in plan evaluation.

Purpose:We investigate the effect of residual setup and motion errors in lung irradiation for VMAT, double scattering (DS) proton beams and spot scanning (IMPT) in a case study.Methods:The CT image and contour sets of a lung patient treated with 6 MV VMAT is re‐planned with DS as well as IMPT subject to the same constraints; V20(lung), V10(lung) and V5(lung)< 15%, 20% and 25% respectively, V20(heart)<25% and V100%(PTV)≥95%. In addition, uncertainty analysis in the form of isocenter shifts (±1–3mm) was incorporated in the DVH calculations to assess the plan robustness.Results:Only the IMPT plan satisfies all the specified constraints. The 3D‐conformal DS proton plan is able to achieve better sparing of the lung and heart dose compared to VMAT. For the lung, V20, V10 and V5 are 13%, 19% and 25% respectively for IMPT, 18%, 23% and 30% respectively for DS, and 20%, 30% and 42% respectively for VMAT. For heart: 0.6% for IMPT, 2.4% for DS and 30% for VMAT. When incorporating isocenter shifts in DVH calculations, the maximum changes in V20, V10 and V5 for lung are 14%, 21% and 28% respectively for IMPT. The corresponding max changes are19%, 24% and 32% respectively for DS, and 22%, 32% and 44% respectively for VMAT. The largest change occurs in the PTV coverage. For IMPT, V100%(PTV) varies between 88–96%, while V100%(PTV) for VMAT suffers a larger change compared to DS (Δ=5.5% vs 3.3%).Conclusion:While only IMPT satisfies the stringent dose‐volume constraints for the lung irradiation, it is not as robust as the 3D conformal DS plan. DS also has better sparing in lung and heart compared to VMAT and similar PTV coverage. By including isocenter shifts in dose‐volume calculations in treatment planning of lung, DS appears to be more robust than VMAT.

Purpose:Workflow is an important component in the operational planning of a new proton facility. By integrating the concept of failure mode and effect analysis (FMEA) and traditional QA requirements, a workflow for a proton therapy treatment course is set up. This workflow serves as the blue print for the planning of computer hardware/software requirements and network flow. A slight modification of the workflow generates a process map(PM) for FMEA and the planning of QA program in PT.Methods:A flowchart is first developed outlining the sequence of processes involved in a PT treatment course. Each process consists of a number of sub‐processes to encompass a broad scope of treatment and QA procedures. For each subprocess, the personnel involved, the equipment needed and the computer hardware/software as well as network requirements are defined by a team of clinical staff, administrators and IT personnel.Results:Eleven intermediate processes with a total of 70 sub‐processes involved in a PT treatment course are identified. The number of sub‐processes varies, ranging from 2‐12. The sub‐processes within each process are used for the operational planning. For example, in the CT‐Sim process, there are 12 sub‐processes: three involve data entry/retrieval from a record‐and‐verify system, two controlled by the CT computer, two require department/hospital network, and the other five are setup procedures. IT then decides the number of computers needed and the software and network requirement. By removing the traditional QA procedures from the workflow, a PM is generated for FMEA analysis to design a QA program for PT.Conclusion:Significant efforts are involved in the development of the workflow in a PT treatment course. Our hybrid model of combining FMEA and traditional QA program serves a duo purpose of efficient operational planning and designing of a QA program in PT.

Purpose: To investigate a new tool for quantification of deformations and optimal margin estimation from daily images using learning algorithms based on swarm intelligence. Methods: Swarm intelligence methods, specifically Ant Colony Optimization (ACO) are used to provide an efficient estimate of the optimal margin extent in each direction. ACO can provide global optimal solutions in highly nonlinear problems such as margin estimation. The proposed method is demonstrated using cases from stomach lymphoma with daily TomoTherapy megavoltage CT (MVCT) contours. Results: The process consists of two main steps that involve deriving organ motion probability and estimating the optimal margin. For motion probability, we used methods based on rigid registration. The estimation of the optimal margin was carried out using swarm intelligence based on the ACO algorithm. Preliminary results using Dice similarity index are promising. In order to achieve 95% coverage, the ACO ran for 25 nest relocations and converged in about 10 iterations with an optimal Dice metric of 0.88. It is expected that the proposed method will be helpful for guiding future margin estimation protocols. Conclusions: In this work, we have presented a new software tool and an algorithm for estimating organ motion margins from daily images. Our results indicate that the developed tool can provide improved visualization and quantification of daily deformations for estimating isotropic and anisotropic margins for radiotherapy treatment plans in cases where organ motion is an issue such as the presented example of stomach lymphoma, or in cases of lung and prostate cancers.

Purpose: To evaluate modulated electron radiotherapy (MERT) planning for delivery with the photon multicollimator (xMLC) for treatment of bilateral post-mastectomy chest wall treatment. Current techniques are complex, time consuming, and deficient in terms of target coverage and organ at risk (OAR) sparing. Conventional techniques require blocks and energy modifying bolus, while IMRT is volatile due to patient motion and provides unnecessary dose baths. Materials and Methods: An in-house Monte-Carlo-based MERT planning system has been developed for planning bilateral chest wall (MERT-biCW) treatment aided by previously developed in-house MERT optimization tools. The MERT-biCW planning was performed in three steps: 1) determine the number of portal fields needed to cover a PTV and partition the PTV into sub-PTVs for corresponding portals; 2) each sub-PTVs is then planned with MERT individually incorporating multiple energy assigned segments within each portal; 3) optimizing all portals to achieve the final plan. Several new features have been added to our MERT planning tools including; automatic selection of the best incident angle for each portal, whereby the distal surface of the tumor will be reached by selected energy and minimizing the air gap to <5 cm to maintain dose conformity. An algorithm has been developed to obtain optimal segments to facilitate target coverage and OAR sparing. Results: We typically covered the PTV with four portals for biCW. For a challenging case, we achieved acceptable PTV coverage with 80% isotope line covered by the prescription dose, and significantly reduced doses to OAR compared with conventional therapy. The V20 of left lung was reduced from 45.5 Gy to 36.9 Gy. V20 of heart was reduced from 18 to 5 Gy. Conclusions: MERT-biCW with its well-defined ranges and sharp fall-off is a promising alternative to conventional or IMRT post-mastectomy chest wall (CW) irradiation. Research is sponsored by Varian Grant.

Purpose: Estimating the proper margins for the planned target volume (PTV) could be a challenging task in cases where the organ undergoes significant changes during the course of radiotherapy treatment. This is practically the case in stomach lymphoma, where the stomach can change significantly from day to day. A common practice is to add a constant l–2cm margin isotropically around the tumor volume based on planning CT scan. This might lead to some portions of stomach being under dosed or surrounding normal structures over‐dosed. The purpose of this work is to develop a tool that utilizes information from daily images to aid localization of these deformations and guide estimations of proper margins. Method and Materials: In this work, the stomach volume for each treatment fraction was delineated manually over the course of 6 weeks of fractionated treatment using daily Tomotherapy Mega voltage CT (MVCT) images from three patients. A software tool was developed to aid tracking variations in shape during therapy and record estimates of the probability by which an organ spends at any particular place. Accordingly, plots of estimated tumor coverage and excess irradiated normal tissue volumes as a function of margin could be generated. Results: Estimated stomach volumes for these cases were 429.2±67.7, 383.0±66.6, and 294.1±27.7 cc. Plots of tumor coverage and excess irradiated volume were created for each case. It was observed that with a margin of 1.5 cm over the original stomach, the entire union volume was covered. This margin resulted in about 500–800 cc of excess volume being irradiated for the three test cases. Conclusions: This work presented a new tool for visualization and quantification of daily deformations for isotropic and anisotropic margin definition guidance.

Purpose: Electron radiotherapy is an option for shallow tumors due to sharp distal falloff. Optimization tools to perform Modulate Electron Radiotherapy (MERT) plans using photon MLCs produced promising results. This study optimizes MERT with IMRT for targets that can't be treated alone with electrons. Methods and Materials: Distances from the external contour to PTV distal border were calculated from CT scans of a post-mastectomy chest wall patient, and mapped onto a beams eye view plane. This map is converted to an energy map by binning effective depths. A MERT plan was done for the PTV portion that can be treated with MERT using the MERTgui that can interactively shape fields. Treatment head simulations using BEAMnrc and MCSIM Monte Carlo dose calculations were performed for apertures separately and resulting dose were then combined with different weights using another gui. Dose from the MERT plan was exported to Eclipse and the IMRT-PTV was generated by subtracting MERT-PTV from the original PTV. This new PTV was divided into sub-ptv regions to provide reasonable gradient between the distal and proximal subsections of the new PTV relative to the MERT-PTV. The IMRT plan was then optimized and combined with the MERT electron plan in CERR. Results: Compartmentalized MERT+IMRT plan resulted in good target organ coverage while decreasing dose to organs at risk such as heart, contralateral lung, but increased dose to the ipsilateral lung. With the MERT+IMRT plan, D20 decreased from 21Gy to 4Gy for heart, and 11Gy to 2Gy for contralateral lung, while increasing dose from 27Gy to 33Gy for ipsilateral lung. Conclusion: A four step optimization process in which optimization tools were devised to plan compartmentalized MERT and IMRT. Compartmentalized optimization of MERT and IMRT allows planning of targets that were not ideal for MERT-only planning.

Purpose: Corpus collosotomy by Gamma Knife Radiotherapy is a treatment for medically refractory epilepsy. Due to the long treatment duration (3–6 hours), the peripheral dose received by patients becomes a concern. In this study, peripheral doses for a posterior corpus collosotomy by Gamma Knife, Model C were investigated. Method and Materials: A Rando‐Phantom was used to measure the peripheral doses. Three types of dosimetry systems were used, which included ionization chambers, TLDs (TLD‐100 3×3×1mm chips), and OneDose™ MOSFET dosimeters. The dosimeters were placed on the surface of the Rando‐Phantom under 0.5 cm of build up at distances of 5.0, 17.5, 30.0, 42.5, 54.0, 70.0 and 84cm from the center of the treatment volume. Seven cylindrical ionization chambers with buildup caps were placed at the same distances, one chamber at each position. The leakage of the ionization chambers was measured before irradiation and recorded during treatment sessions. The phantom was irradiated using a clinical treatment plan for a posterior corpus collosotomy. The prescription dose was 130Gy (max dose), and the delivery dose was reduced to one third of the prescription dose for measurement purposes. The treatment time was 99.38 minutes. Results: The measured doses by TLD were 17.9, 9.9, 5.8, 2.9, 2.4, 1.5, and 1.1cGy for the seven positions respectively. The measured doses by ionization chambers were 16.9, 12.0, 5.2, 2.9, 2.8, 2.2, and 2.0cGy. The results obtained with the OneDose™ were not consistent due to the decay of the signal over the period of measurement. The doses measured by TLD and ionization chamber for the same position were averaged. The total doses to the measurement positions were 52.2, 33.0, 16.5, 8.7, 7.8, 5.7, and 4.8cGy, respectively, for the full prescription dose of 130Gy. Conclusion: The peripheral doses were significant, especially in the head and neck region.