32 results on '"Yoganathan SA"'
Search Results
2. Generation of Synthetic CT from CBCT using Deep Learning Approaches for Head and Neck Cancer Patients
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Aouadi, Souha, primary, Yoganathan, SA, additional, Torfeh, Tarraf, additional, Paloor, Satheesh, additional, Caparrotti, Palmira, additional, Hammoud, Rabih, additional, and Al-Hammadi, Noora, additional
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- 2023
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3. Virtual pretreatment patient‐specific quality assurance of volumetric modulated arc therapy using deep learning
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Yoganathan, SA, primary, Ahmed, Sharib, additional, Paloor, Satheesh, additional, Torfeh, Tarraf, additional, Aouadi, Souha, additional, Al‐Hammadi, Noora, additional, and Hammoud, Rabih, additional
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- 2023
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4. Investigation of radiomics and deep convolutional neural networks approaches for glioma grading
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Aouadi, Souha, primary, Torfeh, Tarraf, additional, Yoganathan, SA, additional, Paloor, Satheesh, additional, Riyas, Mohamed, additional, Hammoud, Rabih, additional, and Al-Hammadi, Noora, additional
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- 2023
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5. Automatic segmentation of magnetic resonance images for high‐dose‐rate cervical cancer brachytherapy using deep learning
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Yoganathan, SA, primary, Paul, Siji Nojin, additional, Paloor, Satheesh, additional, Torfeh, Tarraf, additional, Chandramouli, Suparna Halsnad, additional, Hammoud, Rabih, additional, and Al‐Hammadi, Noora, additional
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- 2022
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6. Segmentation of organs and tumor within brain magnetic resonance images using K-nearest neighbor classification
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Zhang, Rui, primary and Yoganathan, SA, additional
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- 2022
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7. Comparison of Static Conformal Beam and Intensity Modulated Radiation Therapy for Intracranial Stereotactic Radiosurgery
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Gupta, Pramod Kumar, primary, Yoganathan, SA, additional, Das, KJ Maria, additional, and Kumar, Shaleen, additional
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- 2020
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8. Evaluating the dosimetric consequences of MLC leaf positioning errors in dynamic IMRT treatments
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Agarwal, Arpita, primary, Rastogi, Nikhil, additional, Maria Das, KJ, additional, Yoganathan, SA, additional, Udayakumar, D, additional, Naresh, R, additional, and Kumar, Shaleen, additional
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- 2019
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9. Feasibility of generating synthetic CT from T1-weighted MRI using a linear mixed-effects regression model
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Rui Zhang, Anant Pandey, Beibei Guo, and Yoganathan Sa
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medicine.diagnostic_test ,business.industry ,0206 medical engineering ,Mean absolute error ,Computed tomography ,Magnetic resonance imaging ,Regression analysis ,02 engineering and technology ,Mixed effects regression ,020601 biomedical engineering ,Article ,030218 nuclear medicine & medical imaging ,03 medical and health sciences ,0302 clinical medicine ,Hounsfield scale ,medicine ,T1 weighted ,Simple linear regression ,Nuclear medicine ,business ,General Nursing ,Mathematics - Abstract
Generation of synthetic computed tomography (sCT) for magnetic resonance imaging (MRI)-only radiotherapy is emerging as a promising direction because it can eliminate the registration error and simplify clinical workflow. The goal of this study was to generate accurate sCT from standard T1-weighted MRI for brain patients. CT and MRI data of twelve patients with brain tumors were retrospectively collected. Linear mixed-effects (LME) regression models were fitted between CT and T1-weighted MRI intensities for different segments in the brain. The whole brain sCTs were generated by combining predicted segments together. Mean absolute error (MAE) between real CTs and sCTs across all patients was 71.1 ± 5.5 Hounsfield Unit (HU). Average differences in the HU values were 1.7 ± 7.1 HU (GM), 0.9 ± 5.1 HU (WM), −24.7 ± 8.0 HU (CSF), 76.4 ± 17.8 HU (bone), 20.9 ± 20.4 HU (fat), −69.4 ± 28.3 HU (air). A simple regression technique has been devised that is capable of producing accurate HU maps from standard T1-weighted MRI, and exceptionally low MAE values indicate accurate prediction of sCTs. Improvement is needed in segmenting MRI using a more automatic approach.
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- 2019
10. Magnitude, impact, and management of respiration-induced target motion in radiotherapy treatment: A comprehensive review
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Yoganathan, SA, primary, Maria Das, KJ, additional, Agarwal, Arpita, additional, and Kumar, Shaleen, additional
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- 2017
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11. Investigating the electronic portal imaging device for small radiation field measurements
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Agarwal, Arpita, primary, Rastogi, Nikhil, additional, Maria Das, KJ, additional, Yoganathan, SA, additional, Udayakumar, D, additional, and Kumar, Shaleen, additional
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- 2017
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12. Dosimetric verification of gated delivery of electron beams using a 2D ion chamber array
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Yoganathan, SA, primary, Maria Das, KJ, additional, Raj, DGowtham, additional, and Kumar, Shaleen, additional
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- 2015
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13. SU-E-T-522: Evaluation of EDW and Sliding Window IMRT in the Presence of Organ Motion with Gating
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Das, KJ Maria, primary, Yoganathan, SA, additional, Kumar, SK Senthil, additional, Kesavan, C, additional, Vikram, R, additional, and Kumar, S, additional
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- 2011
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14. Dosimetric effect of multileaf collimator leaf width in intensity-modulated radiotherapy delivery techniques for small- and large-volume targets
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Maria Das, KJ, primary, Agarwal, Arpita, additional, Kumar, Shaleen, additional, Yoganathan, SA, additional, and Mani, KarthickRaj, additional
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- 2011
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15. SU-GG-T-161: Effect of Leaf Motion Calculator Parameters in Head and Neck IMRT
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Das, KJ Maria, primary, Mani, KR, additional, Yoganathan, SA, additional, Agarwal, A, additional, Kumar, S, additional, and Gandhi, Sanjay, additional
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- 2010
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16. Dosimetric Comparision And Clinical Feasibility Of Deep Inspiration Breath Hold (Dibh) Technique In Left Sided Breast Cancer Patients.
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Misra, Shagun, Yoganathan, SA., and Kumar, S.K.Senthil
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BREAST cancer , *CANCER patients , *CORONARY arteries , *SETUP time , *SABBATH , *BREATHING exercises , *RADIOTHERAPY - Abstract
Background: A slice of heart, especially the region of left anterior descending coronary vessel (LAD), comes into the beam trajectory when irradiating left sided breast cancers. This may have long term cardiac implications. To keep the heart away from the bi-tangential beams while the radiation beam is on - (DIBH) technique is practiced. We plan to compare this technique with the standard practice of free breathing . Material and Methods Left sided breast cancer patients after BCS or post mastectomy were enrolled as per our institutional DIBH protocol. We have analysed the dosimetric comparision of cardiac and LAD doses and efficiency of the process. Results: We have trained left sided breast cancer patients of age< 65years of age . Seven patients were trained for the procedure and out of these 3 patients underwent treatment according to DIBH technique. Among remaining 4 patients 2 were unable to hold their breath inspite of 3 training sessions, in one on planning scan heart was already out of tangential trajectory in free breathing and in one no dosimetric benefit was observed on plan. Therefore DIBH technique was abandoned in these 4 cases. Training time as an OPD exercise was 15 minutes, to capture free breathing and breath hold scan was 45 minutes. Time taken to plan by the physicist was 30 minutes. First day treatment setup and treatment time was45 minute and rest of days it was 25 minutes. Average of mean dose received by heart in free breathing versus breath hold was 5.5Gy versus 2.5Gy and mean LAD dose received was 33Gy versus 22Gy. Conclusion: Radiotherapy of the left breast in DIBH can be incorporated into daily routine. Although time taken by DIBH technique is more than usual routine patients but is associated with significant dose reduction to the heart and LAD. [ABSTRACT FROM AUTHOR]
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- 2017
17. Investigating the impact of rapidplan on ethos automated planning.
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Yoganathan SA, Basith A, Rostami A, Usman M, Paloor S, Hammoud R, and Al-Hammadi N
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Automated planning has surged in popularity within external beam radiation therapy in recent times. Leveraging insights from previous clinical knowledge could enhance auto-planning quality. In this work, we evaluated the performance of Ethos automated planning with knowledge-based guidance, specifically using Rapidplan (RP). Seventy-four patients with head-and-neck (HN) cancer and 37 patients with prostate cancer were used to construct separate RP models. Additionally, 16 patients from each group (HN and prostate) were selected to assess the performance of Ethos auto-planning results. Initially, a template-based Ethos plan (Non-RP plan) was generated, followed by integrating the corresponding RP model's DVH estimates into the optimization process to generate another plan (RP plan). We compared the target coverage, OAR doses, and total monitor units between the non-RP and RP plans. Both RP and non-RP plans achieved comparable target coverage in HN and Prostate cases, with a negligible difference of less than 0.5% (p > 0.2). RP plans consistently demonstrated lower doses of OARs in both HN and prostate cases. Specifically, the mean doses of OARs were significantly reduced by 9% (p < 0.05). RP plans required slightly higher monitor units in both HN and prostate sites (p < 0.05), however, the plan generation time was almost similar (p > 0.07). The inclusion of the RP model reduced the OAR doses, particularly reducing the mean dose to critical organs compared to non-RP plans while maintaining similar target coverage. Our findings provide valuable insights for clinics adopting Ethos planning, potentially enhancing the auto-planning to operate optimally., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)
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- 2024
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18. Small field measurements using electronic portal imaging device.
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Sait AA, Yoganathan SA, Jones GW, Patel T, Rastogi N, Pandey SP, Mani S, and Boopathy R
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- Equipment Design, Phantoms, Imaging, Calibration, Humans, Scintillation Counting instrumentation, Scintillation Counting methods, Reproducibility of Results, Radiometry instrumentation, Radiometry methods, Particle Accelerators instrumentation
- Abstract
Purpose/Objective . Small-field measurement poses challenges. Although many high-resolution detectors are commercially available, the EPID for small-field dosimetry remains underexplored. This study aimed to evaluate the performance of EPID for small-field measurements and to derive tailored correction factors for precise small-field dosimetry verification. Material/Methods . Six high-resolution radiation detectors, including W2 and W1 plastic scintillators, Edge-detector, microSilicon, microDiamond and EPID were utilized. The output factors, depth doses and profiles, were measured for various beam energies (6 MV-FF, 6 MV-FFF, 10 MV-FF, and 10 MV-FFF) and field sizes (10 × 10 cm
2 , 5 × 5 cm2 , 4 × 4 cm2 , 3 × 3 cm2 , 2 × 2 cm2 , 1 × 1 cm2 , 0.5 × 0.5 cm2 ) using a Varian Truebeam linear accelerator. During measurements, acrylic plates of appropriate depth were placed on the EPID, while a 3D water tank was used with five-point detectors. EPID measured data were compared with W2 plastic scintillator and measurements from other high-resolution detectors. The analysis included percentage deviations in output factors, differences in percentage for PDD and for the profiles, FWHM, maximum difference in the flat region, penumbra, and 1D gamma were analyzed. The output factor and depth dose ratios were fitted using exponential functions and fractional polynomial fitting in STATA 16.2, with W2 scintillator as reference, and corresponding formulae were obtained. The established correction factors were validated using two Truebeam machines. Results . When comparing EPID and W2-PSD across all field-sizes and energies, the deviation for output factors ranged from 1% to 15%. Depth doses, the percentage difference beyond dmax ranged from 1% to 19%. For profiles, maximum of 4% was observed in the 100%-80% region. The correction factor formulae were validated with two independent EPIDs and closely matched within 3%. Conclusion . EPID can effectively serve as small-field dosimetry verification tool with appropriate correction factors., (Creative Commons Attribution license.)- Published
- 2024
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19. Ultra-Hypofractionated Prostate Radiotherapy With Online Adaptive Technique: A Case Report.
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Yoganathan SA, Riyas M, Sukumaran R, Hammoud R, and Al-Hammadi N
- Abstract
Ultra-hypofractionated radiotherapy (UHF RT) is revolutionizing the treatment approach for low- and intermediate-risk prostate cancer patients. This study reports the planning process of UHF RT utilizing the cone beam computed tomography (CBCT)-based online adaptive radiotherapy (OART) treatment with the Ethos system, focusing on a comparative analysis between OART and image-guided radiotherapy (IGRT) plans. We also assessed the pre-planning capabilities of the Ethos system against the CyberKnife (CK) (Accuray, Sunnyvale, CA) system. A 66-year-old patient, diagnosed with prostatic acinar adenocarcinoma confirmed via biopsy and presenting with elevated prostate-specific antigen (PSA) levels, underwent UHF OART treatment using the Ethos system. The planning encompassed delineating the gross target volume (GTV) as the prostate, while the clinical target volume (CTV) comprised the prostate and proximal seminal vesicle. The planning target volume (PTV) was derived from the CTV with a 5 mm external margin except for a 3 mm posterior margin. A simultaneous integrated boost (SIB) technique was employed, delivering 40 Gy in five fractions (8 Gy per fraction) to the gross tumor volume (GTV) and 36.25 Gy in five fractions (7.25 Gy per fraction) to the remaining part of the planning target volume (PTV), with treatments scheduled biweekly. We compared OART and IGRT plans and conducted a comparative analysis between Ethos planning and the CK system for pre-planning assessment. When comparing Ethos planning and CK plans, Ethos demonstrated slightly better target coverage and organ-at-risk (OAR) sparing. However, CK plans showed superior containment of low-dose spillage, particularly at 50% and 25% iso-doses, due to non-coplanar beam arrangements. Our results demonstrated that OART plans yielded superior target coverage and improved OAR sparing compared to IGRT plans. Notably, the entire OART process, from planning to delivery, was accomplished within 27 minutes. The Ethos OART system's ability to adapt to daily anatomical changes, efficient workflow, and superior OAR-sparing capabilities make it a promising option for prostate cancer treatment using UHF RT., Competing Interests: Human subjects: All authors have confirmed that this study did not involve human participants or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Yoganathan et al.)
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- 2024
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20. Prediction of cervix cancer stage and grade from diffusion weighted imaging using EfficientNet.
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Aouadi S, Torfeh T, Bouhali O, Yoganathan SA, Paloor S, Chandramouli S, Hammoud R, and Al-Hammadi N
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- Humans, Female, Retrospective Studies, Middle Aged, Image Processing, Computer-Assisted methods, ROC Curve, Adult, Algorithms, Uterine Cervical Neoplasms diagnostic imaging, Uterine Cervical Neoplasms pathology, Diffusion Magnetic Resonance Imaging methods, Neural Networks, Computer, Neoplasm Staging, Neoplasm Grading
- Abstract
Purpose . This study aims to introduce an innovative noninvasive method that leverages a single image for both grading and staging prediction. The grade and the stage of cervix cancer (CC) are determined from diffusion-weighted imaging (DWI) in particular apparent diffusion coefficient (ADC) maps using deep convolutional neural networks (DCNN). Methods . datasets composed of 85 patients having annotated tumor stage (I, II, III, and IV), out of this, 66 were with grade (II and III) and the remaining patients with no reported grade were retrospectively collected. The study was IRB approved. For each patient, sagittal and axial slices containing the gross tumor volume (GTV) were extracted from ADC maps. These were computed using the mono exponential model from diffusion weighted images (b-values = 0, 100, 1000) that were acquired prior to radiotherapy treatment. Balanced training sets were created using the Synthetic Minority Oversampling Technique (SMOTE) and fed to the DCNN. EfficientNetB0 and EfficientNetB3 were transferred from the ImageNet application to binary and four-class classification tasks. Five-fold stratified cross validation was performed for the assessment of the networks. Multiple evaluation metrics were computed including the area under the receiver operating characteristic curve (AUC). Comparisons with Resnet50, Xception, and radiomic analysis were performed. Results . for grade prediction, EfficientNetB3 gave the best performance with AUC = 0.924. For stage prediction, EfficientNetB0 was the best with AUC = 0.931. The difference between both models was, however, small and not statistically significant EfficientNetB0-B3 outperformed ResNet50 (AUC = 0.71) and Xception (AUC = 0.89) in stage prediction, and demonstrated comparable results in grade classification, where AUCs of 0.89 and 0.90 were achieved by ResNet50 and Xception, respectively. DCNN outperformed radiomic analysis that gave AUC = 0.67 (grade) and AUC = 0.66 (stage). Conclusion. the prediction of CC grade and stage from ADC maps is feasible by adapting EfficientNet approaches to the medical context., (© 2024 IOP Publishing Ltd.)
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- 2024
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21. Generating synthetic images from cone beam computed tomography using self-attention residual UNet for head and neck radiotherapy.
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Yoganathan SA, Aouadi S, Ahmed S, Paloor S, Torfeh T, Al-Hammadi N, and Hammoud R
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Background and Purpose: Accurate CT numbers in Cone Beam CT (CBCT) are crucial for precise dose calculations in adaptive radiotherapy (ART). This study aimed to generate synthetic CT (sCT) from CBCT using deep learning (DL) models in head and neck (HN) radiotherapy., Materials and Methods: A novel DL model, the 'self-attention-residual-UNet' (ResUNet), was developed for accurate sCT generation. ResUNet incorporates a self-attention mechanism in its long skip connections to enhance information transfer between the encoder and decoder. Data from 93 HN patients, each with planning CT (pCT) and first-day CBCT images were used. Model performance was evaluated using two DL approaches (non-adversarial and adversarial training) and two model types (2D axial only vs. 2.5D axial, sagittal, and coronal). ResUNet was compared with the traditional UNet through image quality assessment (Mean Absolute Error (MAE), Peak-Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM)) and dose calculation accuracy evaluation (DVH deviation and gamma evaluation (1 %/1mm))., Results: Image similarity evaluation results for the 2.5D-ResUNet and 2.5D-UNet models were: MAE: 46±7 HU vs. 51±9 HU, PSNR: 66.6±2.0 dB vs. 65.8±1.8 dB, and SSIM: 0.81±0.04 vs. 0.79±0.05. There were no significant differences in dose calculation accuracy between DL models. Both models demonstrated DVH deviation below 0.5 % and a gamma-pass-rate (1 %/1mm) exceeding 97 %., Conclusions: ResUNet enhanced CT number accuracy and image quality of sCT and outperformed UNet in sCT generation from CBCT. This method holds promise for generating precise sCT for HN ART., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors. Published by Elsevier B.V. on behalf of European Society of Radiotherapy & Oncology.)
- Published
- 2023
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22. Predicting respiratory motion using a novel patient specific dual deep recurrent neural networks.
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Yoganathan SA, Paloor S, Torfeh T, Aouadi S, Hammoud R, and Al-Hammadi N
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- Forecasting, Humans, Motion, Respiratory Rate, Algorithms, Neural Networks, Computer
- Abstract
Real-time tracking of a target volume is a promising solution for reducing the planning margins and both dosimetric and geometric uncertainties in the treatment of thoracic and upper-abdomen cancers. Respiratory motion prediction is an integral part of real-time tracking to compensate for the latency of tracking systems. The purpose of this work was to develop a novel method for accurate respiratory motion prediction using dual deep recurrent neural networks (RNNs). The respiratory motion data of 111 patients were used to train and evaluate the method. For each patient, two models (Network1 and Network2) were trained on 80% of the respiratory wave, and the remaining 20% was used for evaluation. The first network (Network 1) is a 'coarse resolution' prediction of future points and second network (Network 2) provides a 'fine resolution' prediction to interpolate between the future predictions. The performance of the method was tested using two types of RNN algorithms : Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). The accuracy of each model was evaluated using the root mean square error (RMSE) and mean absolute error (MAE). Overall, the RNN model with GRU- function had better accuracy than the RNN model with LSTM-function (RMSE (mm): 0.4 ± 0.2 versus 0.6 ± 0.3; MAE (mm): 0.4 ± 0.2 versus 0.6 ± 0.2). The GRU was able to predict the respiratory motion accurately (<1 mm) up to the latency period of 440 ms, and LSTM's accuracy was acceptable only up to 240 ms. The proposed method using GRU function can be used for respiratory-motion prediction up to a latency period of 440 ms., (© 2022 IOP Publishing Ltd.)
- Published
- 2022
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23. Segmentation of Organs and Tumor within Brain Magnetic Resonance Images Using K-Nearest Neighbor Classification.
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Yoganathan SA and Zhang R
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Purpose: To fully exploit the benefits of magnetic resonance imaging (MRI) for radiotherapy, it is desirable to develop segmentation methods to delineate patients' MRI images fast and accurately. The purpose of this work is to develop a semi-automatic method to segment organs and tumor within the brain on standard T1- and T2-weighted MRI images., Methods and Materials: Twelve brain cancer patients were retrospectively included in this study, and a simple rigid registration was used to align all the images to the same spatial coordinates. Regions of interest were created for organs and tumor segmentations. The K-nearest neighbor (KNN) classification algorithm was used to characterize the knowledge of previous segmentations using 15 image features (T1 and T2 image intensity, 4 Gabor filtered images, 6 image gradients, and 3 Cartesian coordinates), and the trained models were used to predict organ and tumor contours. Dice similarity coefficient (DSC), normalized surface dice, sensitivity, specificity, and Hausdorff distance were used to evaluate the performance of segmentations., Results: Our semi-automatic segmentations matched with the ground truths closely. The mean DSC value was between 0.49 (optical chiasm) and 0.89 (right eye) for organ segmentations and was 0.87 for tumor segmentation. Overall performance of our method is comparable or superior to the previous work, and the accuracy of our semi-automatic segmentation is generally better for large volume objects., Conclusion: The proposed KNN method can accurately segment organs and tumor using standard brain MRI images, provides fast and accurate image processing and planning tools, and paves the way for clinical implementation of MRI-guided radiotherapy and adaptive radiotherapy., Competing Interests: There are no conflicts of interest., (Copyright: © 2022 Journal of Medical Physics.)
- Published
- 2022
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24. An atlas-based method to predict three-dimensional dose distributions for cancer patients who receive radiotherapy.
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Yoganathan SA and Zhang R
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- Algorithms, Female, Humans, Male, Radiotherapy Dosage, Tomography, X-Ray Computed methods, Breast Neoplasms radiotherapy, Prostatic Neoplasms radiotherapy, Radiotherapy Planning, Computer-Assisted methods
- Abstract
Due to the complexity of advanced radiotherapy techniques, treatment planning process is usually time consuming and plan quality can vary considerably among planners and institutions. It is also impractical to generate all possible treatment plans based on available radiotherapy techniques and select the best option for a specific patient. Automatic dose prediction will be very helpful in these situations, while there were a few studies of three-dimensional (3D) dose prediction for patients who received radiotherapy. The purpose of this work was to develop a novel atlas-based method to predict 3D dose prediction and to evaluate its performance. Previously treated nineteen left-sided post-mastectomy breast cancer patients and sixteen prostate cancer patients were included in this study. One patient was arbitrarily chosen as the reference for each type of cancer and all the remaining patients' computed tomography (CT) images and contours were aligned to it using deformable image registration (DIR). Deformable vector field (DVF) for each patient i (DVF
i-ref ) was used to deform the original 3D dose matrix of that patient. CT scan of a test patient was also registered with the same reference patient using DIR and both direct DVF (DVFtest-ref ) and inverse DVF ([Formula: see text]) were derived. Similarity of atlas patients to the test patient was determined based on the similarity of DVFtest-ref to atlas DVFs (DVFi-ref ) and appropriate weighting factors were calculated. Patients' doses in the atlas were deformed again using [Formula: see text] to transform them from the reference patient's coordinates to the test patient's coordinates and the final 3D dose distribution for the test patient was predicted by summing the weighted individual 3D dose distributions. Performance of our method was evaluated and the results revealed that the proposed method was able to predict the 3D dose distributions accurately. The mean dose difference between clinical and predicted 3D dose distributions were 0.9 ± 1.1 Gy and 1.9 ± 1.2 Gy for breast and prostate plans. The proposed dose prediction method can be used to improve planning quality and facilitate plan comparisons.- Published
- 2019
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25. Evaluation of Lung Density and Its Dosimetric Impact on Lung Cancer Radiotherapy: A Simulation Study.
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Raj Verma T, Kumar Painuly N, Prasad Mishra S, Yoganathan SA, Singh N, Bhatt MLB, and Jamal N
- Abstract
Background: The dosimetric parameters required in lung cancer radiation therapy are taken from a homogeneous water phantom; however, during treatment, the expected results are being affected because of its inhomogeneity. Therefore, it becomes necessary to quantify these deviations., Objective: The present study has been undertaken to find out inter- and intra- lung density variations and its dosimetric impact on lung cancer radiotherapy using Monte Carlo code FLUKA and PBC algorithms., Material and Methods: Density of 100 lungs was recorded from their CT images along with age. Then, after PDD calculated by FLUKA MC Code and PBC algorithm for virtual phantom having density 0.2 gm/cm3 and 0.4 gm/cm3 (density range obtained from CT images of 100 lungs) using Co-60 10 x10 cm2 beams were compared., Results: Average left and right lung densities were 0.275±0.387 and 0.270±0.383 respectively. The deviation in PBC calculated PDD were (+)216%, (+91%), (+)45%, (+)26.88%, (+)14%, (-)1%, (+)2%, (-)0.4%, (-)1%, (+)1%, (+)4%, (+)4.5% for 0.4 gm/cm3 and (+)311%, (+)177%, (+)118%, (+)90.95%, (+)72.23%, (+)55.83% ,(+)38.85%, (+)28.80%, (+)21.79%, (+)15.95%, (+)1.67%, (-) 2.13%, (+)1.27%, (+)0.35%, (-)1.79%, (-)2.75% for 0.2 gm/cm3 density mediums at depths of 1mm, 2mm, 3mm, 4mm, 5mm, 6 mm, 7 mm, 8mm, 9mm,10mm, 15mm, 30mm, 40mm, 50mm, 80mm and 100 mm, respectively., Conclusion: Large variations in inter- and intra- lung density were recorded. PBC overestimated the dose at air/lung interface as well as inside lung. The results of Monte Carlo simulation can be used to assess the performance of other treatment planning systems used in lung cancer radiotherapy.
- Published
- 2019
26. Investigating different computed tomography techniques for internal target volume definition.
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Yoganathan SA, Maria Das KJ, Subramanian VS, Raj DG, Agarwal A, and Kumar S
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- Humans, Lung Neoplasms diagnosis, Lung Neoplasms physiopathology, Motion, Phantoms, Imaging, Radiotherapy Planning, Computer-Assisted methods, Respiration, Cone-Beam Computed Tomography methods, Four-Dimensional Computed Tomography methods, Lung Neoplasms diagnostic imaging
- Abstract
Purpose: The aim of this work was to evaluate the various computed tomography (CT) techniques such as fast CT, slow CT, breath-hold (BH) CT, full-fan cone beam CT (FF-CBCT), half-fan CBCT (HF-CBCT), and average CT for delineation of internal target volume (ITV). In addition, these ITVs were compared against four-dimensional CT (4DCT) ITVs., Materials and Methods: Three-dimensional target motion was simulated using dynamic thorax phantom with target insert of diameter 3 cm for ten respiration data. CT images were acquired using a commercially available multislice CT scanner, and the CBCT images were acquired using On-Board-Imager. Average CT was generated by averaging 10 phases of 4DCT. ITVs were delineated for each CT by contouring the volume of the target ball; 4DCT ITVs were generated by merging all 10 phases target volumes. Incase of BH-CT, ITV was derived by boolean of CT phases 0%, 50%, and fast CT target volumes., Results: ITVs determined by all CT and CBCT scans were significantly smaller (P < 0.05) than the 4DCT ITV, whereas there was no significant difference between average CT and 4DCT ITVs (P = 0.17). Fast CT had the maximum deviation (-46.1% ± 20.9%) followed by slow CT (-34.3% ± 11.0%) and FF-CBCT scans (-26.3% ± 8.7%). However, HF-CBCT scans (-12.9% ± 4.4%) and BH-CT scans (-11.1% ± 8.5%) resulted in almost similar deviation. On the contrary, average CT had the least deviation (-4.7% ± 9.8%)., Conclusions: When comparing with 4DCT, all the CT techniques underestimated ITV. In the absence of 4DCT, the HF-CBCT target volumes with appropriate margin may be a reasonable approach for defining the ITV.
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- 2017
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27. Evaluating the four-dimensional cone beam computed tomography with varying gantry rotation speed.
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Yoganathan SA, Maria Das KJ, Mohamed Ali S, Agarwal A, Mishra SP, and Kumar S
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- Humans, Phantoms, Imaging, Respiration, Rotation, Thorax, Cone-Beam Computed Tomography methods, Four-Dimensional Computed Tomography methods
- Abstract
Objective: The purpose of this work was to evaluate the four-dimensional cone beam CT (4DCBCT) imaging with different gantry rotation speed., Methods: All the 4DCBCT image acquisitions were carried out in Elekta XVI Symmetry™ system (Elekta AB, Stockholm, Sweden). A dynamic thorax phantom with tumour mimicking inserts of diameter 1, 2 and 3 cm was programmed to simulate the respiratory motion (4 s) of the target. 4DCBCT images were acquired with different gantry rotation speeds (36°, 50°, 75°, 100°, 150° and 200° min(-1)). Owing to the technical limitation of 4DCBCT system, average cone beam CT (CBCT) images derived from the 10 phases of 4DCBCT were used for the internal target volume (ITV) contouring. ITVs obtained from average CBCT were compared with the four-dimensional CT (4DCT). In addition, the image quality of 4DCBCT was also evaluated for various gantry rotation speeds using Catphan(®) 600 (The Phantom Laboratory Inc., Salem, NY)., Results: Compared to 4DCT, the average CBCT underestimated the ITV. The ITV deviation increased with increasing gantry speed (-10.8% vs -17.8% for 36° and 200° min(-1) in 3-cm target) and decreasing target size (-17.8% vs -26.8% for target diameter 3 and 1 cm in 200° min(-1)). Similarly, the image quality indicators such as spatial resolution, contrast-to-noise ratio and uniformity also degraded with increasing gantry rotation speed., Conclusion: The impact of gantry rotation speed has to be considered when using 4DCBCT for ITV definition. The phantom study demonstrated that 4DCBCT with slow gantry rotation showed better image quality and less ITV deviation., Advances in Knowledge: Usually, the gantry rotation period of Elekta 4DCBCT system is kept constant at 4 min (50° min(-1)) for acquisition, and any attempt of decreasing/increasing the acquisition duration requires careful investigation. In this study, the 4DCBCT images with different gantry rotation speed were evaluated.
- Published
- 2016
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28. Evaluating the image quality of cone beam CT acquired during rotational delivery.
- Author
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Yoganathan SA, Maria Das KJ, Maria Midunvaleja K, Gowtham Raj D, Agarwal A, Velmurugan J, and Kumar S
- Subjects
- Algorithms, Humans, Cone-Beam Computed Tomography methods, Phantoms, Imaging, Radiographic Image Interpretation, Computer-Assisted methods
- Abstract
Objective: The aim of this work was to evaluate the quality of kilovoltage (kV) cone beam CT (CBCT) images acquired during arc delivery., Methods: Arc plans were delivered on a Catphan(®) 600 phantom (The Phantom Laboratory Inc., Salem, NY), and kV CBCT images were acquired during the treatment. The megavoltage (MV) scatter effect on kV CBCT image quality was evaluated using parameters such as Hounsfield unit (HU) accuracy, spatial resolution, contrast-to-noise ratio (CNR) and spatial non-uniformity (SNU). These CBCT images were compared with reference scans acquired with the same acquisition parameters without MV "beam on". This evaluation was carried out for different photon beams (6 and 15 MV), arc types (half vs full arc), static field sizes (10 × 10 and 25 × 25 cm(2)) and source-to-imager distances (SID) (150 and 170 cm)., Results and Conclusion: HU accuracy, CNR and SNU were considerably affected by MV scatter, and this effect was increased with increasing field size and decreasing photon energy, whereas the spatial resolution was almost unchanged. The MV scatter effect was observed to be more for full-rotation arc delivery than for half-arc delivery. In addition, increasing the SID resulted in decreased MV scatter effect and improved the image quality., Advances in Knowledge: Nowadays, volumetric modulated arc therapy (VMAT) is increasingly used in clinics, and this arc therapy enables us to acquire CBCT imaging simultaneously. But, the main issue of concurrent imaging is the "MV scatter" effect on CBCT imaging. This study aims to experimentally quantify the effect of MV scatter on CBCT image quality.
- Published
- 2015
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29. Performance evaluation of respiratory motion-synchronized dynamic IMRT delivery.
- Author
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Yoganathan SA, Maria Das KJ, Agarwal A, and Kumar S
- Subjects
- Humans, Phantoms, Imaging, Radiotherapy Dosage, Movement, Neoplasms radiotherapy, Radiotherapy Planning, Computer-Assisted, Radiotherapy, Intensity-Modulated, Respiration
- Abstract
The purpose of this study was to evaluate the capabilities of DMLC to deliver the respiratory motion-synchronized dynamic IMRT (MS-IMRT) treatments under various dose rates. In order to create MS-IMRT plans, the DMLC leaf motions in dynamic IMRT plans of eight lung patients were synchronized with the respiratory motion of breathing period 4 sec and amplitude 2 cm (peak to peak) using an in-house developed leaf position modification program. The MS-IMRT plans were generated for the dose rates of 100 MU/min, 400 MU/min, and 600 MU/min. All the MS-IMRT plans were delivered in a medical linear accelerator, and the fluences were measured using a 2D ion chamber array, placed over a moving platform. The accuracy of MS-IMRT deliveries was evaluated with respect to static deliveries (no compensation for target motion) using gamma test. In addition, the fluences of gated delivery of 30% duty cycle and non- MS-IMRT deliveries were also measured and compared with static deliveries. The MS-IMRT was better in terms of dosimetric accuracy, compared to gated and non-MS-IMRT deliveries. The dosimetric accuracy was observed to be significantly better for 100 MU/min MS-IMRT. However, the use of high-dose rate in a MS-IMRT delivery introduced dose-rate modulation/beam hold-offs that affected the synchronization between the DMLC leaf motion and target motion. This resulted in more dose deviations in MS-IMRT deliveries at the dose rate of 600 MU/min.
- Published
- 2013
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30. Investigating the effect of dose rate and maximum allowable MLC leaf velocity in dynamic IMRT.
- Author
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Yoganathan SA, Mani KR, Maria Das KJ, Agarwal A, Kesavan C, and Kumar S
- Subjects
- Humans, Retrospective Studies, Head and Neck Neoplasms radiotherapy, Radiotherapy Dosage, Radiotherapy Planning, Computer-Assisted methods, Radiotherapy, Intensity-Modulated methods
- Abstract
The purpose of this study is to analyze the effect of various dose rates (DR) and maximum allowable MLC leaf velocities (MLV) in dynamic Intensity Modulated Radiotherapy (IMRT) planning and delivery of head and neck patients. Five head and neck patients were retrospectively included in this study. The initial dynamic IMRT 'reference plans' were created for all these patients, using a DR of 400 MU/min and MLV of 2.5 cm/s. Additional plans were generated by varying the DR and MLV values. The DR value was varied from 100 to 600 MU/min, in increments of 100 MU/min, for a MLV of 2.5 cm/s. Also the MLV was varied from 0.5 to 3 cm/s, in increments of 0.5 cm, for a DR of 400 MU/min. In order to maintain the prescribed dose to the PTV, the DR was allowed to vary ('beam hold or DR modulation' during delivery) when the MLV was changed and the MLV was allowed to vary when the DR was changed. The mean doses to the PTV as well as parotids, maximum dose of spinal cord and total MU were recorded for analysis. The effect of DR and MLV on treatment delivery was analyzed using the portal dosimetry for all the above plans. The predicted portal dose fluences of the TPS were compared with the measured EPID fluences using gamma evaluation criteria of 2% dose difference and 2 mm distance to agreement. A small proportional increase in OAR doses with DR was observed. Increases to MLV value resulted in decreases of the OAR doses and this effect was considerable for values below 1.5 cm/s. DR and MLV both resulted in no appreciable dose variation to the target. The total MU to deliver the plan increases with increasing DR and decreasing MLV. When comparing portal images derived from the treatment plans with portal images obtained by delivering the treatments, it was observed that the treatments was most reliably delivered when the DRs were set to lower values and when the MLVs were set to higher values.
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- 2012
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31. Correlation of phase values with CT Hounsfield and R2* values in calcified neurocysticercosis.
- Author
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Roy B, Verma S, Awasthi R, Rathore RK, Venkatesan R, Yoganathan SA, Das JK, Prasad KN, and Gupta RK
- Subjects
- Adult, Brain Injuries diagnosis, Brain Injuries diagnostic imaging, Calcinosis diagnosis, Humans, Male, Models, Statistical, Neurocysticercosis diagnosis, Radiographic Image Interpretation, Computer-Assisted, Calcinosis diagnostic imaging, Magnetic Resonance Imaging methods, Neurocysticercosis diagnostic imaging, Tomography, X-Ray Computed methods
- Abstract
Purpose: To correlate phase and R2* derived from susceptibility-weighted magnetic resonance imaging (MRI) with computed tomography-Hounsfield (CT-HU) values in calcified neurocysticercosis and to evaluate phase imaging in the assessment of calcified neurocysticercosis., Materials and Methods: Thirty-five patients with 52 calcified lesions underwent both CT and MRI. Phase and R2* were calculated from multi-echo 3D-T2-star-weighted-angiography data. MRI and CT data were coregistered using mutual information. Spearman's correlation was performed between quantitative phase and CT-HU and R2* values. The Mann-Whitney U-test was used to see differences between CT-HU and R2* values from corresponding positive and negative phase regions., Results: The median values of CT-HU and R2* from regions with positive and negative phase were found to be 142.10 (range: 41.89-491.75) and 68.5/sec (range: 20-110/sec) and 137.30 (range: 30.83-458.88) and 69/sec (range: 0-110/sec), respectively. There was a significant correlation of positive phase values with corresponding CT-HU and R2* values. In addition, there was a significant correlation of R2* and CT-HU with negative phase values., Conclusion: We conclude that there is a significant correlation between negative and positive phase with CT-HU and R2* values, suggesting that the CT hyperdense lesion may have both calcium and other minerals, which can be differentiated using phase imaging. Conventional MRI should include phase imaging to detect calcified neurocysticercosis., (Copyright © 2011 Wiley Periodicals, Inc.)
- Published
- 2011
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32. Dosimetric effect of multileaf collimator leaf width in intensity-modulated radiotherapy delivery techniques for small- and large-volume targets.
- Author
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Yoganathan SA, Mani KR, Das KJ, Agarwal A, and Kumar S
- Abstract
The purpose of this study was to evaluate the dosimetric effect of the leaf width of a multileaf collimator (MLC) in intensity-modulated radiotherapy (IMRT) delivery techniques for small- and large-volume targets. We retrospectively selected previously treated 5 intracranial and 5 head-neck patients for this study to represent small- (range, 18.37-72.75 cc; mean, 42.99 cc) and large-volume (range, 312.31-472.84 cc; mean, 361.14 cc) targets. A 6-MV photon beam data was configured for Brianlab m3 (3 mm), Varian Millennium 120 (5 mm) and Millennium 80 (10 mm) MLCs in the Eclipse treatment-planning system. Sliding window and step-shoot IMRT plans were generated for intracranial patients using all the above-mentioned MLCs; but due to the field size limitation of Brainlab MLC, we used only 5-mm and 10-mm MLCs in the head-and-neck patients. Target conformity, dose to the critical organs and dose to normal tissues were recorded and evaluated. Although the 3-mm MLC resulted in better target conformity (mean difference of 7.7% over 5-mm MLC and 12.7% over 10-mm MLC) over other MLCs for small-volume targets, it increased the total monitor units of the plans. No appreciable differences in terms of target conformity, organ at risk and normal-tissue sparing were observed between the 5-mm and 10-mm MLCs for large-volume targets. The effect of MLC leaf width was not quantifiably different in sliding window and step and shoot techniques. In addition, we observed that there was no additional benefit to the sliding-window (SW) technique when compared to the step-shoot (SS) technique as a result of reduction of MLC leaf width.
- Published
- 2011
- Full Text
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