Optimization of extracranial stereotactic radiation therapy of small lung lesions using accurate dose calculation algorithms

BACKGROUND: The aim of this study was to compare and to validate different dose calculation algorithms for the use in radiation therapy of small lung lesions and to optimize the treatment planning using accurate dose calculation algorithms. METHODS: A 9-field conformal treatment plan was generated on an inhomogeneous phantom with lung mimics and a soft tissue equivalent insert, mimicking a lung tumor. The dose distribution was calculated with the Pencil Beam and Collapsed Cone algorithms implemented in Masterplan (Nucletron) and the Monte Carlo system XVMC and validated using Gafchromic EBT films. Differences in dose distribution were evaluated. The plans were then optimized by adding segments to the outer shell of the target in order to increase the dose near the interface to the lung. RESULTS: The Pencil Beam algorithm overestimated the dose by up to 15% compared to the measurements. Collapsed Cone and Monte Carlo predicted the dose more accurately with a maximum difference of -8% and -3% respectively compared to the film. Plan optimization by adding small segments to the peripheral parts of the target, creating a 2-step fluence modulation, allowed to increase target coverage and homogeneity as compared to the uncorrected 9 field plan. CONCLUSION: The use of forward 2-step fluence modulation in radiotherapy of small lung lesions allows the improvement of tumor coverage and dose homogeneity as compared to non-modulated treatment plans and may thus help to increase the local tumor control probability. While the Collapsed Cone algorithm is closer to measurements than the Pencil Beam algorithm, both algorithms are limited at tissue/lung interfaces, leaving Monte-Carlo the most accurate algorithm for dose prediction

A novel lateral disequilibrium inclusive, (LDI) pencil-beam based dose calculation algorithm: Evaluation in inhomogeneous phantoms and comparison with Monte Carlo calculations

Purpose: Pencil-beam (PB) based dose calculation for treatment planning is limited by inaccuracies in regions of tissue inhomogeneities, particularly in situations with lateral electron disequilibrium as is present at tissue/lung interfaces. To overcome these limitations, a new "lateral disequilibrium inclusive" (LDI) PB based calculation algorithm was introduced. In this study, the authors evaluated the accuracy of the new model by film and ionization chamber measurements and Monte Carlo simulations. Methods: To validate the performance of the new LDI algorithm implemented in Corvus 09 (R), eight test plans were generated on inhomogeneous thorax and pelvis phantoms. In addition, three plans were calculated with a simple effective path length (EPL) algorithm on the inhomogeneous thorax phantom. To simulate homogeneous tissues, four test plans were evaluated in homogeneous phantoms (homogeneous dose calculation). Results: The mean pixel pass rates and standard deviations of the gamma 4%/4 mm test for the film measurements were (96 +/- 3)% for the plans calculated with LDI, (70 +/- 5)% for the plans calculated with EPL, and (99 +/- 1)% for the homogeneous plans. Ionization chamber measurements and Monte Carlo simulations confirmed the high accuracy of the new algorithm (dose deviations = 96%) Conclusions: LDI represents an accurate and fast dose calculation algorithm for treatment planning. (C) 2011 American Association of Physicists in Medicine. [DOI: 10.1118/1.3557952

Arc therapy for total body irradiation - A robust novel treatment technique for standard treatment rooms

Background and purpose: We developed a simple and robust total body irradiation (TB!) method for standard treatment rooms that obviates the need for patient translation devices. Methods and materials: Two generic arcs with rectangular segments for a patient thickness of 16 and 20 cm (arc16/arc20) were generated. An analytical fit was performed to determine the weights of the arc segments depending on patient thickness and gantry angle. Stability and absolute dose for both arcs were measured using EBT3 films in a range of solid water slab phantom thicknesses. Additionally ionization chamber measurements were performed every 10 cm at a source surface distance (SSD) of similar to 200 cm. Results: The measured standard deviation for arc16 is +/- 3% with a flatness <= 9.0%. Arc20 had a standard deviation of +/- 3% with a flatness <= 7.3% for all measured thicknesses. The theoretical curves proved to be accurate for the prediction of the segment weightings for the two arcs. In vivo measurements for the first 22 clinical patients showed a dose deviation of less than 3%. Conclusions: Arc therapy is a convenient and stable method for TBI. This cost-effective approach has been introduced clinically, obviating the need for field patches and to physically move the patient. (C) 2014 Elsevier Ireland Ltd. All rights reserved

Emotional distress among survivors of Adolescent and Young Adult cancer or adult cancer

PURPOSE: We examined emotional distress in cancer survivors diagnosed as adolescents or young adults (AYAs) vs. cancer survivors diagnosed as middle/older adults and vs. the general population without a history of cancer. METHODS: Using the 2014-2017 National Health Interview Surveys, 2,500 AYA survivors (initial cancer diagnosed between aged 15-39 years) were matched with 2,500 middle/older adult survivors (initial cancer diagnosed at aged ≥40 years) as well as with 1,609 from the general population without a history of cancer. Multinomial logistic regression models estimated the risk of emotional distress (measured using the validated Kessler distress (K6) scale) in the study population (AYA vs. middle/older adult cancer survivors and vs. general population without cancer), adjusting for known covariates. RESULTS: Emotional distress was more prevalent among AYAs (average age 52.8 ± 19.1 years) than middle/older adult (average age 67.4 ± 14.0 years) cancer survivors (moderate: 25.5% vs. 19.4%; and severe: 6.4% vs. 4.4% [P\u3c.0001]); however, there was no difference in emotional distress between AYA cancer survivors (moderate: 26.8% and severe: 7.5%) vs. general population without cancer (moderate: 23.7% and severe: 6.2%). In the multivariable multinomial analyses, AYA cancer survivors had higher risk of reporting emotional distress (aRR = 1.45; 95% CI 1.13, 1.86) than middle/older adult cancer survivors. CONCLUSION: Psychosocial support may be especially needed for cancer survivors diagnosed as adolescents or young adults to mitigate adverse psychosocial outcomes