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PURPOSE/OBJECTIVE: The purpose of this study is to investigate the effect of treatment couch and immobilization devices on surface dose for megavoltage photon beams. MATERIAL/METHODS: Percentage surface dose (PSD) measurement was carried out in Elekta Synergy™ Linear accelerator using PTW Markus® Parallel plate ionization chamber of volume 0.05cm3 with water equivalent RW3 Slab phantom (PTW, Germany). The measurement depth was considered at 0.07mm. The reference PSD was measured at 0° gantry angle with 10×10cm2, 20×20cm2 and 30×30cm2 field sizes and 100cm SSD for 4MV, 6MV and 15MV photon beams. For comparison, PSD measurement was carried out at 180° gantry angle inclusion of treatment couch (TC), All in One positioning system (AIO - PS) and Vac lok Cushions (VLC). RESULTS: Beam angle at 0°, for field sizes 10×10cm2, 20×20cm2 and 30×30cm2, the PSD was observed as 30.9%, 40.5%, 48.7% for 4MV; 23.7%, 33.8%, 42.2% for 6MV; and 17.0%, 29.6%, 38.6% for 15MV respectively. Beam angle at 180° with TC, an increase in PSD by maximum of 65.0% for 4MV, 64.9% for 6MV and 55.9% for 15MV as compared to 0° angle. The PSD increased when beam angle was 180° with TC and AIO - PS were 65.0% for 4MV, 67.4% for 6MV, and 60.9% for 15MV than 0° angle. Similarly, increased PSD for beam angle at 180° with TC and VLC were 66.8% for 4MV, 66.8% for 6MV and 61.3% for 15MV as compared to 0° angle. CONCLUSION: For all three-photon energies, at 180° gantry angle, the PSD increased significantly in case of TC, VLC, and AIO - PS for all the field sizes as compared to gantry angle at 0°. It is necessary to consider TC, AIO - PS and VLC during dose calculation to ensure accuracy of patient treatment delivery.
Subject(s)
Photons , Radiotherapy Planning, Computer-Assisted , Humans , Photons/therapeutic use , Phantoms, Imaging , Particle Accelerators , Water , Radiotherapy DosageABSTRACT
Impact of three different matching methods for delivery of Volumetric Modulated Arc Therapy (VMAT) in Cone-beam computed tomography (CBCT) on patient set-up error. As per institutional imaging protocol, 300 CBCT scans of 20 VMAT head and neck cancer patients treated with 60â¯Gy/30 fractions were chosen for the present study. Approved CT images of the plan were registered as a reference with the CBCT images on board. Grey-scale matching (GM), manual matching (MM), and bone matching (BM) between on-board CBCT and reference CT images were used to assess patient translation errors. Patient positioning verification was evaluated using the Clip-box registration in all three matching methods. Using the GM approach as a reference point, two additional matchings were rendered in offline mode using BM and MM. For analysis, random error (σ), systematic error (∑), maximum error (E) mean set-up error (M), mean displacement vector (R), matching time (Mt), and multiple comparisons using Post hoc Tukey's HSD test were performed. In MM, less random and systematic errors were found than in GM and BM with an insignificant difference (pâ¯>â¯0.05) Compared to BM and GM, the maximum error, mean set-up error, and displacement vector were marginally less in MM (pâ¯>â¯0.05). In MM, an increased Mt relative to BM and GM was observed (pâ¯>â¯0.05). Furthermore, an insignificant difference in set-up error was revealed in a multiple comparison test (pâ¯>â¯0.05). Any of the three matching methods can be used during CBCT to check patient translation errors for the delivery of the VMAT head and neck patients.
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Machine learning and data analytics are being increasingly used for quantitative structure property relation (QSPR) applications in the chemical domain where the traditional Edisonian approach towards knowledge-discovery have not been fruitful. The perception of odorant stimuli is one such application as olfaction is the least understood among all the other senses. In this study, we employ machine learning based algorithms and data analytics to address the efficacy of using a data-driven approach to predict the perceptual attributes of an odorant namely the odorant characters (OC) of "sweet" and "musky". We first analyze a psychophysical dataset containing perceptual ratings of 55 subjects to reveal patterns in the ratings given by subjects. We then use the data to train several machine learning algorithms such as random forest, gradient boosting and support vector machine for prediction of the odor characters and report the structural features correlating well with the odor characters based on the optimal model. Furthermore, we analyze the impact of the data quality on the performance of the models by comparing the semantic descriptors generally associated with a given odorant to its perception by majority of the subjects. The study presents a methodology for developing models for odor perception and provides insights on the perception of odorants by untrained human subjects and the effect of the inherent bias in the perception data on the model performance. The models and methodology developed here could be used for predicting odor characters of new odorants.
Subject(s)
Odorants/analysis , Olfactory Perception/physiology , Smell/physiology , Humans , Machine Learning , Psychophysics/methods , SemanticsABSTRACT
AIM: To study the dosimetric impact of statistical uncertainty (SU) per plan on Monte Carlo (MC) calculation in Monaco™ treatment planning system (TPS) during volumetric modulated arc therapy (VMAT) for three different clinical cases. BACKGROUND: During MC calculation SU is an important factor to decide dose calculation accuracy and calculation time. It is necessary to evaluate optimal acceptance of SU for quality plan with reduced calculation time. MATERIALS AND METHODS: Three different clinical cases as the lung, larynx, and prostate treated using VMAT technique were chosen. Plans were generated with Monaco™ V5.11 TPS with 2% statistical uncertainty. By keeping all other parameters constant, plans were recalculated by varying SU, 0.5%, 1%, 2%, 3%, 4%, and 5%. For plan evaluation, conformity index (CI), homogeneity index (HI), dose coverage to PTV, organ at risk (OAR) dose, normal tissue receiving dose ≥5 Gy and ≥10 Gy, integral dose (NTID), calculation time, gamma pass rate, calculation reproducibility and energy dependency were analyzed. RESULTS: CI and HI improve as SU increases from 0.5% to 5%. No significant dose difference was observed in dose coverage to PTV, OAR doses, normal tissue receiving dose ≥5 Gy and ≥10 Gy and NTID. Increase of SU showed decrease in calculation time, gamma pass rate and increase in PTV max dose. No dose difference was seen in calculation reproducibility and dependent on energy. CONCLUSION: For VMAT plans, SU can be accepted from 1% to 3% per plan with reduced calculation time without compromising plan quality and deliverability by accepting variations in point dose within the target.
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PURPOSE: Validation of a new software version of a Monte Carlo treatment planning system through comparing plans generated by two software versions in volumetric-modulated arc therapy (VMAT) for lung cancer. MATERIALS AND METHODS: Three patients who were treated with 60 Gy/30 fractions in Elekta Synergy™ linear accelerator by VMAT technique with 2% statistical uncertainty (SU) were chosen for the study. Multiple VMAT plans were generated using two different software versions of Monaco treatment planning system TPS (V5.10.02 and V5.11). By keeping all other parameters constant, originally accepted plans were recalculated for the SUs of 0.5%, 1%, 2%, 3%, 4%, and 5%. For plan evaluation, the metrics compared were conformity Index (CI), homogeneity Index (HI), dose coverage to planning target volume (PTV), organ at risk (OAR) doses to spinal cord, pericardium, bilateral lungs-PTV, esophagus, liver, normal tissue integral dose (NTID), volumes receiving dose >5 and >10 Gy, calculation time (tCT), and gamma pass rates. RESULTS: In both versions, CI and HI improved as the SU increased from 0.5% to 5%. No significant dose difference was observed in Dmean to PTV, bilateral lungs-PTV, pericardium, esophagus, liver, normal tissue volume receiving >5, and >10 Gy and NTID. It was observed that while the tCT and gamma pass rates decreased, the maximum dose to PTV increased as the SU increased. No other significant dose differences were observed between the two MC versions compared. CONCLUSION: For lung VMAT plans, in both versions, SU could be accepted up to 3% per plan with reduced tCT without compromising plan quality and deliverability by accepting variations in point dose and an inhomogeneous dose within the target. The plan quality of Monaco™V5.10.02 was similar to Monaco™TPS-V5.11 except for tCT.
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PURPOSE: This study compared three different methods used in registering cone-beam computed tomography (CBCT) image set with planning CT image set for determining patient setup uncertainties during volumetric modulated arc therapy (VMAT) for breast cancer patients. MATERIALS AND METHODS: Seven breast cancer patients treated with 50 Gy in 25 fractions using VMAT technique were chosen for this study. A total of 105 CBCT scans were acquired by image guidance protocol for patient setup verification. Approved plans' CT images were used as the reference image sets for registration with their corresponding CBCT image sets. Setup errors in mediolateral, craniocaudal, and anteroposterior direction were determined using gray-scale matching between the reference CT images and onboard CBCT images. Patient setup verification was performed using clip-box registration (CBR) method during online imaging. Considering the CBR method as the reference, two more registrations were performed using mask registration (MR) method and dual registration (DR) (CBR + MR) method in the offline mode. For comparison, systematic error (∑), random error (σ), mean displacement vector (R), mean setup error (M), and registration time (R t) were analyzed. Post hoc Tukey's honest significant difference test was performed for multiple comparisons. RESULTS: Systematic and random errors were less in CBR as compared to MR and DR (P > 0.05). The mean displacement error and mean setup errors were less in CBR as compared to MR and DR (P > 0.05). Increased R t was observed in DR as compared to CBR and MR (P < 0.05). In addition, multiple comparisons did not show any significant difference in patient setup error (P > 0.05). CONCLUSION: For breast VMAT plan delivery, all three registration methods show insignificant variation in patient setup error. One can use any of the three registration methods for patient setup verification.
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AIM: To present a direct comparison between chemotherapy-enhanced radiotherapy (CERT) and biotherapy-enhanced radiotherapy (BERT) in locally advanced head and neck cancer. METHODS: It is a retrospective analysis of 53 patients with locally advanced head and neck cancer treated from August 2006 to December 2008. For CERT, patients received weekly cisplatin (40 mg/m2 ) and for BERT, a loading dose of 400 mg/m2 of cetuximab given one week prior to radiotherapy followed by 250 mg/m2 given weekly along with radiotherapy. Disease-free survival (DFS) and overall survival (OS) were computed with Kaplan-Meier curve with log-rank test for comparison between the two groups. Multivariate Cox proportional hazards regression analysis was performed to estimate the impact of known relevant prognostic factors on DFS and OS. RESULTS: The median DFS was significantly better with CERT than BERT group (50.82 vs 11.66 months; P = 0.031). The 3 years DFS was significantly higher in CERT group than in BERT group (60.0% vs 14.3%; P = 0.022). The median OS was significantly better with CERT than BERT group (53.61 vs 32.55 months; P = 0.044). The 3 years OS was also significantly higher in CERT group than in BERT group (74.0% vs 42.1%; P = 0.032). There were no significant differences in acute toxicities of all grade and grade ≥3 between the two groups. The compliance to treatment and assisted feeding dependency for more than 6 months duration were also not significantly different. CONCLUSION: CERT is associated with better outcome with no significantly increased acute toxicities compared to BERT.
Subject(s)
Antineoplastic Combined Chemotherapy Protocols/therapeutic use , Cetuximab/therapeutic use , Chemoradiotherapy/methods , Cisplatin/therapeutic use , Head and Neck Neoplasms/drug therapy , Head and Neck Neoplasms/radiotherapy , Aged , Asian People , Cetuximab/administration & dosage , Cetuximab/pharmacology , Cisplatin/administration & dosage , Cisplatin/pharmacology , Female , Humans , Male , Middle Aged , Retrospective StudiesABSTRACT
PURPOSE: Multimodality therapy for esophageal cancer can cause various kinds of treatment-related sequelae, especially pulmonary toxicities. This prospective study aims to investigate the clinical and dosimetric parameters predicting lung injury in patients undergoing radiation therapy for esophageal cancer. METHODS: Forty-five esophageal cancer patients were prospectively analyzed. The pulmonary toxicities (or sequelae) were evaluated by comparing chest X-ray films, pulmonary function tests and symptoms caused by pulmonary damage before and after treatment. All patients were treated with either three-dimensional radiotherapy (3DCRT) or with intensity-modulated radiotherapy (IMRT). The planning dose volume histogram was used to compute the lung volumes receiving more than 5, 10, 20 and 30 Gy (V5, V10, V20, V30) and mean lung dose. RESULTS: V20 was larger in the IMRT group than in the 3DCRT group (p = 0.002). V20 (>15%) and V30 (>20%) resulted in a statistically significant increase in the occurrence of chronic pneumonitis (p = 0.03) and acute pneumonitis (p = 0.007), respectively. CONCLUSIONS: The study signifies that a larger volume of lung receives lower doses because of multiple beam arrangement and a smaller volume of lung receives higher doses because of better dose conformity in IMRT plans. Acute pneumonitis correlates more with V30 values, whereas chronic pneumonitis was predominantly seen in patients with higher V20 values.