Research Interests: Mathematics, Health Sciences, Biomedical Engineering, Medical Imaging, Computed Tomography, and 15 moreCancer, Medical Physics, Elasticity, Anatomy, Computer Simulation, Hemodynamics, Diseases, Density dependence, Lung, Clinical Sciences, Interpolation, Dosimetry, Lungs, Distribution Function, and lung neoplasms
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Research Interests: Mathematics, Health Sciences, Biomedical Engineering, Finite Element Methods, Biomechanics, and 15 moreCancer, Locomotion, Finite element method, Elasticity, Finite Element Analysis, Anatomy, Humans, Computer Simulation, Liver, Hemodynamics, Computed radiography, Dosimetry, Computerised Tomography, Centroid, and Liver neoplasms
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We have previously reported that computer-controlled table repositioning can increase the reproducibility of patient setup in 2D using a megavoltage imager and bony anatomy as reference of position. This investigation was extended to... more
We have previously reported that computer-controlled table repositioning can increase the reproducibility of patient setup in 2D using a megavoltage imager and bony anatomy as reference of position. This investigation was extended to daily 3D localization of soft tissue structures (“target of the day” treatment). Research to date has involved liver (under ventilatory immobilization) and prostate patients. Both protocols involve
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ABSTRACT Purpose: For NSCLC radiotherapy, toxicity outcomes such as radiation pneumonitis ≥G2 (RP2) may depend on patients’ physical, clinical, biological and genomic characteristics, and on biomarkers measured during the course of... more
ABSTRACT Purpose: For NSCLC radiotherapy, toxicity outcomes such as radiation pneumonitis ≥G2 (RP2) may depend on patients’ physical, clinical, biological and genomic characteristics, and on biomarkers measured during the course of radiotherapy. This can include 100s of predictors. To reduce complexity, a two-step, signature-based data fusion mechanism was developed to estimate a relationship between patient specific characteristics and the probability of RP2 in terms of a modifying effect on mean lung dose (MLD).
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Research Interests: Health Sciences, Biomedical Engineering, Computed Tomography, Monte Carlo, Nuclear medicine, and 15 moreMedical Physics, Medicine, Monte Carlo Methods, Humans, Movement, Computed radiography, Convolution, Lung, Dosimetry, Lungs, Computerised Tomography, Data Sets, Center of Mass, Monte Carlo Method, and lung neoplasms
Research Interests: Magnetic Resonance Imaging, Brachytherapy, Medicine, Image Registration, Humans, and 11 moreMale, Prostate, Mutual Information, Clinical Sciences, Implant, Visual Quality Inspection Systems, X ray Computed Tomography, Region of Interest, Visual Inspection, Prostate carcinoma, and Prostatic neoplasms
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ABSTRACT Purpose: The use of mean lung dose (MLD) limits allows individualization of lung patient tumor doses at safe levels. However, MLD does not account for local lung function differences between patients, leading to toxicity... more
ABSTRACT Purpose: The use of mean lung dose (MLD) limits allows individualization of lung patient tumor doses at safe levels. However, MLD does not account for local lung function differences between patients, leading to toxicity variability at the same MLD. We investigated dose rearrangement to minimize dose to functional lung, as measured by perfusion SPECT, while maintaining target coverage and conventional MLD limits.
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Modern radiotherapy stands to benefit from the ability to efficiently adapt plans during treatment in response to setup and geometric variations such as those caused by internal organ deformation or tumor shrinkage. A promising strategy... more
Modern radiotherapy stands to benefit from the ability to efficiently adapt plans during treatment in response to setup and geometric variations such as those caused by internal organ deformation or tumor shrinkage. A promising strategy is to develop a framework, which given an initial state defined by patient-attributes, can predict future states based on pre-learned patterns from a well-defined patient population. Here, we investigate the feasibility of predicting patient anatomical changes, defined as a joint state of volume and daily setup changes, across a fractionated treatment schedule using two approaches. The first is based on a new joint framework employing quantum mechanics in combination with deep recurrent neural networks, denoted QRNN. The second approach is developed based on a classical framework, which models patient changes as a Markov process, denoted MRNN. We evaluated the performance characteristics of these two approaches on a dataset of 125 head and neck cancer patients, which was supplemented by synthetic data generated using a generative adversarial network. Model performance was evaluated using area under the receiver operating characteristic curve (AUC) scores. The MRNN framework had slightly better performance than the QRNN framework, with MRNN(QRNN) validation AUC scores of 0.742 ± 0.021 (0.675 ± 0.036), 0.709 ± 0.026 (0.656 ± 0.02l), 0.724 ± 0.036 (0.652 ± 044), and 0.698 ± 0.016 (0.605 ± 0.035) for system state vector sizes of 4, 6, 8, and 10, respectively. Of these, only the results from the two higher order states had statistically significant differences (p < 0.05). A similar trend was also observed when the models were applied to an external testing dataset of 20 patients, yielding MRNN(QRNN) AUC scores of 0.707 (0.623), 0.687 (0.608), 0.723 (0.669), and 0.697 (0.609) for states vectors sizes of 4, 6, 8, and 10, respectively. These results suggest that both stochastic models have potential value in predicting patient changes during the course of adaptive radiotherapy.
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Research Interests: Mathematics, Computer Science, Health Sciences, Biomedical Engineering, Computed Tomography, and 15 moreCancer, Radiation Therapy, Medical Physics, Multiple Instance Learning, Medicine, Optimization, Anatomy, Optimisation, Radiation Dose, Gaussian distribution, Rigid Body, Dosimetry, Intensity Modulated Radiation Therapy, Inverse, and phantoms
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Abstract A quadrupole doublet lens refocuses particles of rigidities up to 400 MeV/c per unit charge scattered within an angular range of− 15 to+ 140 from a 30 cm chamber onto a detection surface 3.0 m removed from the target. This... more
Abstract A quadrupole doublet lens refocuses particles of rigidities up to 400 MeV/c per unit charge scattered within an angular range of− 15 to+ 140 from a 30 cm chamber onto a detection surface 3.0 m removed from the target. This system, herein to be called the ...
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ABSTRACT Purpose: Preemptive Goal Programming (PGP) facilitates the use of soft‐constraints in a hierarchical manner for solving complex inverse planning problems. It is a highly effective multicriteria strategy for IMRT planning.... more
ABSTRACT Purpose: Preemptive Goal Programming (PGP) facilitates the use of soft‐constraints in a hierarchical manner for solving complex inverse planning problems. It is a highly effective multicriteria strategy for IMRT planning. However, in order to ensure good numerical performance, a robust constrained optimization algorithm with a practical strategy for handling degeneracy is required. This study identifies cases when PGP introduces challenging problems that do not hold a conventional constraint qualification. Numerical performance for such problems is evaluated using nonlinear planning metrics (DVH, EUD, and NTCP). Method and Materials: PGP, as implemented in our in‐house planning system, solves a series of nonlinear least‐squares problems by a sequential quadratic programming (SQP) algorithm provided with precise Jacobians by an automatic differentiation algorithm. In the presence of constraint degeneracy, an elastic mode (feasibility bound relaxation) is used to ensure a positive step taken at all iterations. Dosimetric as well as numerical performance is evaluated for dose (or EUD) escalation cases with critical organ dose constraints. Reformulation of constraints is also studied as a potential way of reducing degeneracy in these problems. Results: Optimization levels involving strongly active constraints showed degeneracy near optimality, thus requiring use of the elastic mode for convergence. This mode exhibited robust convergence (typically &lt;∼100 iterations) for all IMRT cases studied. Highly nonlinear models (NTCP or EUD with high +/−powers) were handled well by SQP. A strategy of constraint reformulation showed a monotonic decrease in merit function value and its dosimetric performances were comparable to those without reformulation. Conclusion: The optimization task of escalating target dose is limited by binding dose constraints of OARs, which can also create degeneracy in PGP. This study shows SQP with an elastic mode exhibits a stable convergence using the dose‐volume, EUD and NTCP metrics. Numerical performances can be further stabilized by reformulating degenerate constraints.
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Research Interests: Breast Cancer, Radiation Therapy, Nuclear medicine, Medicine, Lung Cancer, and 15 moreProspective studies, Humans, Female, Confidence intervals, Perfusion, Lung, Mastectomy, Clinical Sciences, Aged, Middle Aged, Adult, Intensity Modulated Radiotherapy, Antineoplastic Agents, Postoperative Period, and Lymph nodes
Research Interests: RADIATION DAMAGE, Medicine, Uncertainty, Population, Humans, and 14 moreLiver, Radiation Therapy Treatment Planning, Feasibility Studies, Normal tissue complication probability, Motion, Clinical Sciences, Three Dimensional, Uncertainties, Uncertainty Modeling, National Cancer Institute, Treatment planning, Liver Tumor, Probability Distribution Function, and Liver neoplasms
This paper presents the results of a feasibility study specifically addressing the technical and operational difficulties in making quantitative use of Magnetic Resonance Imaging (MRI) in radiation therapy treatment planning (RTTP).... more
This paper presents the results of a feasibility study specifically addressing the technical and operational difficulties in making quantitative use of Magnetic Resonance Imaging (MRI) in radiation therapy treatment planning (RTTP). Selected radiotherapy patients have been studied with both CT and MRI as part of the treatment planning process. Both sets of images, along with mechanically-obtained external contour and simulator film data, are entered into the treatment planning system. All of the capabilities of the fully three dimensional planning system U-MPlan are available to both the CT and MRI images, in which any image can be used as the backdrop for interactive beam positioning, beam portal simulation, and dose distribution displays for external beam and brachytherapy applications in both 2- and 3-dimensionally-oriented displays. The study has shown that to use MRI data for RTTP, one must (a) use careful patient positioning and marking, (b) transfer information from CT to MRI and vice versa, (c) determine the geometrical consistency between the CT and MR data sets, (d) investigate the unwarping of distorted MR images, and (e) have the ability to use non-axial images for determination of beam treatment technique, dose calculations, and plan evaluation.
Research Interests: Magnetic Resonance Imaging, Brachytherapy, Radiation Therapy, Medical Physics, Radiotherapy, and 10 moreMedicine, Humans, Radiation Therapy Treatment Planning, Clinical Sciences, Neoplasms, Treatment planning, X ray Computed Tomography, Brain Neoplasms, Magnetic resonance image, and Medical Dosimetry
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Research Interests: Breast Cancer, Radiation Therapy, Nuclear medicine, Radiotherapy, Medicine, and 15 moreX Rays, Humans, Electromagnetic Radiation, Beta decay, Female, Lung, Clinical Sciences, Radiation Dose, Cross Section, Mammary gland, Computerized tomography, Treatment planning, Ionizing Radiation, Breast Neoplasms, and Low density
A new computerized radiation treatment planning system has been developed to aid in three-dimensional treatment planning. Using interactive colour graphics in conjunction with a DPD 11/45 computer, the system can take multiple transverse... more
A new computerized radiation treatment planning system has been developed to aid in three-dimensional treatment planning. Using interactive colour graphics in conjunction with a DPD 11/45 computer, the system can take multiple transverse contours and construct a perspective display of the treatment region showing organ surfaces as well as cross-sectional contours. With interactively selected orientations, the display allows easy perception of the relative positioning of the treatment volume and neighbouring anatomy. For external beam treatment planning, interactive computer simulation is used to select diaphragm sizes which best conform to the target area while avoiding sensitive structures. Dose calculations for the selected beams are carried out on multiple transverse planes. The calculational planes and surfaces are displayed in perspective with radiation dosage displayed in an interactively manipulated colour display. Altogether the system provides an easy assessment of the volume to be irradiated, interactive selection of optimal arrangements of treatment fields and a means for visualizing and evaluating the resulting dose distributions.