Predicting response to immunotherapy in non-small cell lung cancer- from bench to bedside.

Background: Immune checkpoint inhibitor (ICI) therapy is first-line treatment for many advanced non-small cell lung cancer (aNSCLC) patients. Predicting response could help guide selection of intensified or alternative anti-cancer regimens. We hypothesized that radiomics and laboratory variables predictive of ICI response in a murine model would also predict response in aNSCLC patients. Methods: Fifteen mice with lung carcinoma tumors implanted in bilateral flanks received ICI. Pre-ICI laboratory and computed tomography (CT) data were evaluated for association with systemic ICI response. Baseline clinical and CT data for 117 aNSCLC patients treated with nivolumab were correlated with overall survival (OS). Models for predicting treatment response were created and subjected to internal cross-validation, with the human model further tested on 42 aNSCLC patients who received pembrolizumab. Results: Models incorporating baseline NLR and identical radiomics (surface-to-mass ratio, average Gray, and 2D kurtosis) predicted ICI response in mice and OS in humans with AUCs of 0.91 and 0.75, respectively. The human model successfully sorted pembrolizumab patients by longer vs. shorter predicted OS (median 35 months vs. 6 months, p=0.026 by log-rank). Discussion: This study advances precision oncology by non-invasively classifying aNSCLC patients according to ICI response using pre-treatment data only. Interestingly, identical radiomics features and NLR correlated with outcomes in the preclinical study and with ICI response in 2 independent patient cohorts, suggesting translatability of the findings. Future directions include using a radiogenomic approach to optimize modeling of ICI response.

Abscopal effect observed in visceral and osseous metastases after liver SBRT in combination with nivolumab and relatlimab for sinonasal mucosal melanoma-a case report.

Background: Primary sinonasal mucosal melanoma (SNMM) is a rare, aggressive histology usually diagnosed at advanced stages and associated with poor prognosis. Evidence regarding etiology, diagnosis, and treatment mainly derives from case reports, retrospective series, and national databases. In the treatment of metastatic melanoma, anti-CTLA-4 and anti-PD-1 checkpoint blockade increased 5-year overall survival from ~10% (prior to 2011) to ~50% (between 2011 and 2016). In March of 2022, the FDA approved the use of relatlimab, a novel anti-LAG3 immune checkpoint inhibitor, for the treatment of melanoma. Case presentation: A 67-year-old woman with locally advanced SNMM underwent debulking surgery, adjuvant RT, and first-line immunotherapy (ImT) with nivolumab but developed local progression. The patient started a second course of ImT with nivolumab and ipilimumab, but this was discontinued after two cycles due to an immune-related adverse event (irAE, hepatitis with elevated liver enzymes). Interval imaging identified visceral and osseous metastases including multiple lesions in the liver and in the lumbar spine. She went on to receive a third course of ImT with nivolumab and the novel agent relatlimab with concurrent stereotactic body radiation therapy (SBRT) to the largest liver tumor only, delivered in five 10-Gy fractions using MRI guidance. A PET/CT performed 3 months after SBRT demonstrated complete metabolic response (CMR) of all disease sites including non-irradiated liver lesions and spinal metastatic sites. After two cycles of the third course of ImT, the patient developed severe immune-related keratoconjunctivitis and ImT was discontinued. Conclusion: This case report describes the first complete abscopal response (AR) in an SNMM histology and the first report of AR following liver SBRT with the use of relatlimab/nivolumab combination ImT for metastatic melanoma in the setting of both visceral and osseous lesions. This report suggests that the combination of SBRT with ImT potentiates the adaptive immune response and is a viable path for immune-mediated tumor rejection. The mechanisms behind this response are hypothesis-generating and remain an area of active research with exceedingly promising potential.

Lung Inflammation Predictors in Combined Immune Checkpoint-Inhibitor and Radiation Therapy-Proof-of-Concept Animal Study.

PURPOSE: Combined radiotherapy (RT) and immune checkpoint-inhibitor (ICI) therapy can act synergistically to enhance tumor response beyond what either treatment can achieve alone. Alongside the revolutionary impact of ICIs on cancer therapy, life-threatening potential side effects, such as checkpoint-inhibitor-induced (CIP) pneumonitis, remain underreported and unpredictable. In this preclinical study, we hypothesized that routinely collected data such as imaging, blood counts, and blood cytokine levels can be utilized to build a model that predicts lung inflammation associated with combined RT/ICI therapy. MATERIALS AND METHODS: This proof-of-concept investigational work was performed on Lewis lung carcinoma in a syngeneic murine model. Nineteen mice were used, four as untreated controls and the rest subjected to RT/ICI therapy. Tumors were implanted subcutaneously in both flanks and upon reaching volumes of ~200 mm3 the animals were imaged with both CT and MRI and blood was collected. Quantitative radiomics features were extracted from imaging of both lungs. The animals then received RT to the right flank tumor only with a regimen of three 8 Gy fractions (one fraction per day over 3 days) with PD-1 inhibitor administration delivered intraperitoneally after each daily RT fraction. Tumor volume evolution was followed until tumors reached the maximum size allowed by the Institutional Animal Care and Use Committee (IACUC). The animals were sacrificed, and lung tissues harvested for immunohistochemistry evaluation. Tissue biomarkers of lung inflammation (CD45) were tallied, and binary logistic regression analyses were performed to create models predictive of lung inflammation, incorporating pretreatment CT/MRI radiomics, blood counts, and blood cytokines. RESULTS: The treated animal cohort was dichotomized by the median value of CD45 infiltration in the lungs. Four pretreatment radiomics features (3 CT features and 1 MRI feature) together with pre-treatment neutrophil-to-lymphocyte (NLR) ratio and pre-treatment granulocyte-macrophage colony-stimulating factor (GM-CSF) level correlated with dichotomized CD45 infiltration. Predictive models were created by combining radiomics with NLR and GM-CSF. Receiver operating characteristic (ROC) analyses of two-fold internal cross-validation indicated that the predictive model incorporating MR radiomics had an average area under the curve (AUC) of 0.834, while the model incorporating CT radiomics had an AUC of 0.787. CONCLUSIONS: Model building using quantitative imaging data, blood counts, and blood cytokines resulted in lung inflammation prediction models justifying the study hypothesis. The models yielded very-good-to-excellent AUCs of more than 0.78 on internal cross-validation analyses.

Toward prediction of abscopal effect in radioimmunotherapy: Pre-clinical investigation.

PURPOSE: Immunotherapy (IT) and radiotherapy (RT) can act synergistically, enhancing antitumor response beyond what either treatment can achieve separately. Anecdotal reports suggest that these results are in part due to the induction of an abscopal effect on non-irradiated lesions. Systematic data on incidence of the abscopal effect are scarce, while the existence and the identification of predictive signatures or this phenomenon are lacking. The purpose of this pre-clinical investigational work is to shed more light on the subject by identifying several imaging features and blood counts, which can be utilized to build a predictive binary logistic model. MATERIALS AND METHODS: This proof-of-principle study was performed on Lewis Lung Carcinoma in a syngeneic, subcutaneous murine model. Nineteen mice were used: four as control and the rest were subjected to combined RT plus IT regimen. Tumors were implanted on both flanks and after reaching volume of ~200 mm3 the animals were CT and MRI imaged and blood was collected. Quantitative imaging features (radiomics) were extracted for both flanks. Subsequently, the treated animals received radiation (only to the right flank) in three 8 Gy fractions followed by PD-1 inhibitor administrations. Tumor volumes were followed and animals exhibiting identical of better tumor growth delay on the non-irradiated (left) flank as compared to the irradiated flank were identified as experiencing an abscopal effect. Binary logistic regression analysis was performed to create models for CT and MRI radiomics and blood counts, which are predictive of the abscopal effect. RESULTS: Four of the treated animals experienced an abscopal effect. Three CT and two MRI radiomics features together with the pre-treatment neutrophil-to-lymphocyte (NLR) ratio correlated with the abscopal effect. Predictive models were created by combining the radiomics with NLR. ROC analyses indicated that the CT model had AUC of 0.846, while the MRI model had AUC of 0.946. CONCLUSIONS: The combination of CT and MRI radiomics with blood counts resulted in models with AUCs of 1 on the modeling dataset. Application of the models to the validation dataset exhibited AUCs above 0.84, indicating very good predictive power of the combination between quantitative imaging and blood counts.

Longitudinal fan-beam computed tomography dataset for head-and-neck squamous cell carcinoma patients.

PURPOSE: To describe in detail a dataset consisting of longitudinal fan-beam computed tomography (CT) imaging to visualize anatomical changes in head-and-neck squamous cell carcinoma (HNSCC) patients throughout radiotherapy (RT) treatment course. ACQUISITION AND VALIDATION METHODS: This dataset consists of CT images from 31 HNSCC patients who underwent volumetric modulated arc therapy (VMAT). Patients had three CT scans acquired throughout the duration of the radiation treatment course. Pretreatment planning CT scans with a median of 13 days before treatment (range: 2-27), mid-treatment CT at 22 days after start of treatment (range: 13-38), and post-treatment CT 65 days after start of treatment (range: 35-192). Patients received RT treatment to a total dose of 58-70 Gy, using daily 2.0-2.20 Gy, fractions for 30-35 fractions. The fan-beam CT images were acquired using a Siemens 16-slice CT scanner head protocol with 120 kV and current of 400 mAs. A helical scan with 1 rotation per second was used with a slice thickness of 2 mm and table increment of 1.2 mm. In addition to the imaging data, contours of anatomical structures for RT, demographic, and outcome measurements are provided. DATA FORMAT AND USAGE NOTES: The dataset with DICOM files including images, RTSTRUCT files, and RTDOSE files can be found and publicly accessed in the Cancer Imaging Archive (TCIA, http://www.cancerimagingarchive.net/) as collection Head-and-neck squamous cell carcinoma patients with CT taken during pretreatment, mid-treatment, and post-treatment (HNSCC-3DCT-RT). DISCUSSION: This is the first dataset to date in TCIA which provides a collection of multiple CT imaging studies (pretreatment, mid-treatment, and post-treatment) throughout the treatment course. The dataset can serve a wide array of research projects including (but not limited to): quantitative imaging assessment, investigation on anatomical changes with treatment progress, dosimetry of target volumes and/or normal structures due to anatomical changes occurring during treatment, investigation of RT toxicity, and concurrent chemotherapy and RT effects on head-and-neck patients.

Integral dose based inverse optimization objective function promises lower toxicity in head-and-neck.

PURPOSE: The voxels in a CT data sets contain density information. Besides its use in dose calculation density has no other application in modern radiotherapy treatment planning. This work introduces the use of density information by integral dose minimization in radiotherapy treatment planning for head-and-neck squamous cell carcinoma (HNSCC). MATERIALS AND METHODS: Eighteen HNSCC cases were studied. For each case two intensity modulated radiotherapy (IMRT) plans were created: one based on dose-volume (DV) optimization, and one based on integral dose minimization (Energy hereafter) inverse optimization. The target objective functions in both optimization schemes were specified in terms of minimum, maximum, and uniform doses, while the organs at risk (OAR) objectives were specified in terms of DV- and Energy-objectives respectively. Commonly used dosimetric measures were applied to assess the performance of Energy-based optimization. In addition, generalized equivalent uniform doses (gEUDs) were evaluated. Statistical analyses were performed to estimate the performance of this novel inverse optimization paradigm. RESULTS: Energy-based inverse optimization resulted in lower OAR doses for equivalent target doses and isodose coverage. The statistical tests showed dose reduction to the OARs with Energy-based optimization ranging from ∼2% to ∼15%. CONCLUSIONS: Integral dose minimization based inverse optimization for HNSCC promises lower doses to nearby OARs. For comparable therapeutic effect the incorporation of density information into the optimization cost function allows reduction in the normal tissue doses and possibly in the risk and the severity of treatment related toxicities.

Automated inverse optimization facilitates lower doses to normal tissue in pancreatic stereotactic body radiotherapy.

PURPOSE: Inverse planning is trial-and-error iterative process. This work introduces a fully automated inverse optimization approach, where the treatment plan is closely tailored to the unique patient anatomy. The auto-optimization is applied to pancreatic stereotactic body radiotherapy (SBRT). MATERIALS AND METHODS: The automation is based on stepwise reduction of dose-volume histograms (DVHs). Five uniformly spaced points, from 1% to 70% of the organ at risk (OAR) volumes, are used. Doses to those DVH points are iteratively decreased through multiple optimization runs. With each optimization run the doses to the OARs are decreased, while the dose homogeneity over the target is increased. The iterative process is terminated when a pre-specified dose heterogeneity over the target is reached. Twelve pancreatic cases were retrospectively studied. Doses to the target, maximum doses to duodenum, bowel, stomach, and spinal cord were evaluated. In addition, mean doses to liver and kidneys were tallied. The auto-optimized plans were compared to the actual treatment plans, which are based on national protocols. RESULTS: The prescription dose to 95% of the planning target volume (PTV) is the same for the treatment and the auto-optimized plans. The average difference for maximum doses to duodenum, bowel, stomach, and spinal cord are -4.6 Gy, -1.8 Gy, -1.6 Gy, and -2.4 Gy respectively. The negative sign indicates lower doses with the auto-optimization. The average differences in the mean doses to liver and kidneys are -0.6 Gy, and -1.1 Gy to -1.5 Gy respectively. CONCLUSIONS: Automated inverse optimization holds great potential for personalization and tailoring of radiotherapy to particular patient anatomies. It can be utilized for normal tissue sparing or for an isotoxic dose escalation.

Integral Dose-Based Inverse Optimization May Reduce Side Effects in Radiotherapy of Prostate Carcinoma.

PURPOSE: The purpose of this work is to apply a novel inverse optimization approach, based on utilization of quantitative imaging information in the optimization function, to prostate carcinoma. MATERIALS AND METHODS: This new inverse optimization algorithm relies upon quantitative information derived from computed tomography (CT) imaging studies. The Hounsfield numbers of the CT voxels are converted to physical density, which in turn is used to calculate voxel mass and the corresponding integral dose, by summation over the product of dose and mass in each dose voxel. This integral dose is used for plan optimization through its global minimization. The optimization results are compared to the optimization results derived from most commonly used dose-volume-based inverse optimization, where objective functions are formed as summation over all dose voxels of the squared differences between voxel doses and user specified doses. The data from 25 prostate plans were optimized with dose-volume histogram (DVH) and integral dose (energy) minimization objective functions. The results obtained with the energy- and DVH-based optimization schemes were studied through commonly used dosimetric indices (DIs). Statistical equivalence tests were further performed to establish population-based significance results. RESULTS: Both DVH- and energy-based plans for each case were normalized so that 95% of the planning target volume receives the prescription dose. The average differences for the rectum and bladder DIs ranged from 1.6 to 25%, where the energy-based quantities were lower. For both femoral heads, the energy-based optimization-derived doses were lower on average by 32%. The statistical tests demonstrated that the significant differences in the tallied dose indices range from 2.7% to more than 50% for rectum, bladder, and femoral heads. CONCLUSION: For majority of the clinically relevant dosimetric quantities, energy-based inverse optimization performs better than the standard of care DVH-based optimization in prostate carcinoma. The population averaged statistically significant differences range from ~3 to ~50%. Therefore, this newly proposed optimization approach, incorporating explicitly quantitative imaging information in the inverse optimization function, holds potential for further reduction of complication rates in prostate cancer.

New approach in lung cancer radiotherapy offers better normal tissue sparing.

PURPOSE: Medical images are more than pictures. They contain additional quantitative information which can be interrogated, quantified, and utilized. Besides anatomical information computed tomography (CT) imaging data provide electron density information. Radiotherapy use of this density information is limited to its application only in dose calculations. The direct product of dose, density, and volume forms a quantity called integral dose. The integral dose delivered to a volume of interest is the total energy deposited in that volume. Here it is hypothesized that minimization of the integral dose is advantageous in radiotherapy planning. The purpose of this work is to study the incorporation of quantitative imaging information in radiotherapy inverse optimization through total energy minimization (Energy hereafter). DESIGN: Twenty lung patient plans were studied. For each patient density was quantified on voxel-by-voxel basis through image gray value-to-density conversion curves. Energy-based objective function was used for inverse radiotherapy plan optimization. The obtained plans were evaluated in the light of current standard of care, based on dose-volume (DVH) optimization approach. RESULTS: The statistical significance analyses of the results indicated that the doses to normal tissue were between 14% and 45% lower, when Energy-based optimization was used instead of DVH-based optimization. CONCLUSION: Incorporation of quantitative imaging information, through CT derived density, in the optimization cost function allows reduction of dose to normal tissue for NSCLC cases. Energy-based radiotherapy plans result in lower normal tissue dose and potentially lower complication rates compared to standard of care.

Mathematical Formulation of DMH-Based Inverse Optimization.

PURPOSE: To introduce the concept of dose-mass-based inverse optimization for radiotherapy applications. MATERIALS AND METHODS: Mathematical derivation of the dose-mass-based formalism is presented. This mathematical representation is compared to the most commonly used dose-volume-based formulation used in inverse optimization. A simple example on digitally created phantom is presented. The phantom consists of three regions: a target surrounded by high- and low-density regions. The target is irradiated with two beams through those regions and inverse optimization with dose-volume and dose-mass-based objective functions is performed. The basic properties of the two optimization types are demonstrated on the phantom. RESULTS: It is demonstrated that dose-volume optimization is a special case of dose-mass optimization. In a homogenous media, dose-mass optimization turns into dose-volume optimization. The dose calculations performed on the digital phantom show that in this very simple case dose-mass optimization tends to penalize more the dose delivery through the high-density region and therefore it results in delivering more dose through the low-density region. CONCLUSION: It was demonstrated that dose-mass-based optimization is mathematically more general than dose-volume-based optimization. In the case of constant density media, dose-mass optimization transforms into dose-volume optimization.

Mathematical formulation of energy minimization - based inverse optimization.

PURPOSE: To introduce the concept of energy minimization-based inverse optimization for external beam radiotherapy. MATERIALS AND METHODS: Mathematical formulation of energy minimization-based inverse optimization is presented. This mathematical representation is compared to the most commonly used dose-volume based formulation used in inverse optimization. A simple example on digitally created phantom is demonstrated. The phantom consists of three sections: a target surrounded by high and low density regions. The target is irradiated with two beams passing through those regions. Inverse optimization with dose-volume and energy minimization-based objective functions is performed. The dosimetric properties of the two optimization results are evaluated. RESULTS: Dose-volume histograms for all the volumes of interest used for dose optimization are compared. Energy-based optimization results in higher maximum dose to the volumes that are used as dose-limiting structures. However, the average and the integral doses delivered for the volumes outside of the target are larger with dose-volume optimization. CONCLUSION: Mathematical formulation of energy minimization-based inverse optimization is derived. The optimization applied on the digital phantom shows that energy minimization-based approach tends to deliver somewhat higher maximum doses compared to standard of care, realized with dose-volume based optimization. At the same time, however, the energy minimization-based optimization reduces much more significantly the average and the integral doses.

Biological optimization in volumetric modulated arc radiotherapy for prostate carcinoma.

PURPOSE: To investigate the potential benefits achievable with biological optimization for modulated volumetric arc (VMAT) treatments of prostate carcinoma. METHODS AND MATERIALS: Fifteen prostate patient plans were studied retrospectively. For each case, planning target volume, rectum, and bladder were considered. Three optimization schemes were used: dose-volume histogram (DVH) based, generalized equivalent uniform dose (gEUD) based, and mixed DVH/gEUD based. For each scheme, a single or dual 6-MV, 356° VMAT arc was used. The plans were optimized with Pinnacle(3) (v. 9.0 beta) treatment planning system. For each patient, the optimized dose distributions were normalized to deliver the same prescription dose. The quality of the plans was evaluated by dose indices (DIs) and gEUDs for rectum and bladder. The tallied DIs were D(1%), D(15%), D(25%), and D(40%), and the tallied gEUDs were for a values of 1 and 6. Statistical tests were used to quantify the magnitude and the significance of the observed differences. Monitor units and treatment times for each optimization scheme were also assessed. RESULTS: All optimization schemes generated clinically acceptable plans. The statistical tests indicated that biological optimization yielded increased organs-at-risk sparing, ranging from ~1% to more than ~27% depending on the tallied DI, gEUD, and anatomical structure. The increased sparing was at the expense of longer treatment times and increased number of monitor units. CONCLUSIONS: Biological optimization can significantly increase the organs-at-risk sparing in VMAT optimization for prostate carcinoma. In some particular cases, however, the DVH-based optimization resulted in superior treatment plans.

The effect of gantry spacing resolution on plan quality in a single modulated arc optimization.

Volumetric-modulated arc technique (VMAT) is an efficient form of IMRT delivery. It is advantageous over conventional IMRT in terms of treatment delivery time. This study investigates the relation between the number of segments and plan quality in VMAT optimization for a single modulated arc. Five prostate, five lung, and five head-and-neck (HN) patient plans were studied retrospectively. For each case, four VMAT plans were generated. The plans differed only in the number of control points used in the optimization process. The control points were spaced 2°, 3°, 4°, and 6° apart, respectively. All of the optimization parameters were the same among the four schemes. The 2° spacing plan was used as a reference to which the other three plans were compared. The plan quality was assessed by comparison of dose indices (DIs) and generalized equivalent uniform doses (gEUDs) for targets and critical structures. All optimization schemes generated clinically acceptable plans. The differences between the majority of reference and compared DIs and gEUDs were within 3%. DIs and gEUDs which differed in excess of 3% corresponded to dose levels well below the organ tolerances. The DI and the gEUD differences increased with an increase in plan complexity from prostates to HNs. Optimization with gantry spacing resolution of 4° seems to be a very balanced alternative between plan quality and plan complexity.

Carbon fiber couch effects on skin dose for volumetric modulated arcs.

PURPOSE: The purpose of this study is to evaluate the dosimetric effect of carbon fiber couches (CFCs) on delivered skin dose as well as to explore potential venues for its minimization for volumetric modulated arc (VMAT) treatments. METHODS: A carbon fiber couch (BrainLab) was incorporated in Pinnacle treatment planning system (TPS) by autocontouring. A retrospective investigation on five lung and five prostate patient plans was performed. Targets and organs at risk (OARs), together with a 0.3 cm thick skin contour interfacing the CFC, were outlined in each plan. For each patient, two VMAT plans were generated: a single arc with 6 MV photon energy and two or three arcs with 18 MV photon energy for the posterior arc(s) and 6 MV energy for the anterior arc (mixed energy plans). Both plans for each patient case were normalized such that 95% of the PTV was covered by the same prescription dose, ranging from 7600 to 7800 cGy. For each patient, the prescription doses were escalated to the maximum allowed by the OAR constraints. CFC bolus effects on skin doses were tallied by the highest dose to 1% of skin volume. RESULTS: With the utilization of higher energy photons for the posterior arcs, the statistically significant differences in skin dose between the two plans were as high as 34% of the prescribed dose, where surface doses changed on average from 3800 to 2940 cGy for 6 MV and mixed energy plans, respectively. In addition, skin doses in excess of 68% and 80% of the prescription doses for mixed and 6 MV energy plans, respectively, were observed in individual cases. CONCLUSIONS: The presented findings indicate that mixed energy VMAT plans would result in a substantial skin sparing of more than approximately 34% compared to VMAT plans with only 6 MV arc(s). Additionally, the high skin doses in some cases (81% of the prescription dose) suggest that in hypofractionated SRS/SRT treatments, the carbon fiber couch effects on skin doses need to be evaluated when arc delivery is considered as a treatment option.

Lung dose for minimally moving thoracic lesions treated with respiration gating.

PURPOSE: To evaluate incidental doses to benign lung tissue for patients with minimally moving lung lesions treated with respiratory gating. METHODS AND MATERIALS: Seventeen lung patient plans were studied retrospectively. Tumor motion was less than 5 mm in all cases. For each patient, mid-ventilation (MidVen) and mid-inhalation (MidInh) breathing phases were reconstructed. The MidInh phase was centered on the end-of-inhale (EOI) phase within a 30% gating window. Planning target volumes, heart, and spinal cord were delineated on the MidVen phase and transferred to the MidInh phase. Lungs were contoured separately on each phase. Intensity-modulated radiotherapy plans were generated on the MidVen phases. The plans were transferred to the MidInh phase, and doses were recomputed. The evaluation metric was based on dose indices, volume indices, generalized equivalent uniform doses, and mass indices for targets and critical structures. Statistical tests were used to establish the significance of the differences between the reference (MidVen) and compared (MidInh) dose distributions. RESULTS: Statistical tests demonstrated that the indices evaluated for targets, cord, and heart differed by within 2.3%. The index differences in the lungs, however, are in excess of 6%, indicating the potentially achievable lung sparing and/or dose escalation. CONCLUSIONS: Respiratory gating is a clinical option for patients with minimally moving lung lesions treated at EOI. Gating will be more beneficial for larger tumors, since dose escalation in those cases will result in a larger increase in the tumor control probability.

Quantification of the skin sparing effect achievable with high-energy photon beams when carbon fiber tables are used.

PURPOSE: To quantify the skin doses resulting from the use of carbon fiber couches (CFCs) for patient support. MATERIALS AND METHODS: BrainLab's CFC was evaluated for five prostate patients and five lung patients. For each patient PTV, organs at risk (OARs), and a 0.3cm thick skin contour on the patient's posterior surface were outlined. Two sets of IMRT plans, each consisting of 4, 5, 7, and 9 beams, were generated per patient. The sets were identical with the exception that in the first set only 6MV energy was used, while in the second set (mixed energy) the photon energy of the beams traversing the CFC was 18MV. The plans for each patient were normalized to deliver the same dose to 95% of the PTV. The CFC skin dose was evaluated by the maximum dose received by 1% (D(1%)) of the skin volume. Paired one-tailed t-tests were used to establish the statistical significance. RESULTS: The mixed energy plans resulted in D(1%) increase from 18% to more than 23% as the number of beams in the plan was decreased from 9 to 4. CONCLUSIONS: Skin doses as high as approximately 70% of the prescription dose were found even in 9-beam mixed energy plans. Therefore mixed energy plans may be more beneficial for patients treated with higher fractional doses.