Anuj J Kapadia
Associate Professor in Radiology
Associate Professor of Physics (Secondary)
1) Experimental Implementation of NSECT
Neutron spectroscopy techniques are showing significant promise in determining element concentrations in the human body. We have developed a tomographic imaging system capable of generating tomographic images of the element concentration within a body through a single non-invasive in-vivo scan. This system has been implemented using a Van-de-Graaf accelerator fast neutron source and high-purity germanium gamma detectors at the Triangle Universities Nuclear Laboratory. This setup has been used to obtain NSECT scans for several samples such as bovine liver, mouse specimens and human breast tissue. In order to extract maximum information about a target sample with the lowest possible levels of dose, it is essential to maximize the sensitivity of the scanning system. In other words, the signal to noise ratio for the experimental setup must be maximized. This project aims at increasing the sensitivity of the NSECT system by understanding the various sources of noise and implementing techniques to reduce their effect. Noise in the system may originate from several factors such as the radiative background in the scanning room, and neutron scatter off of components of the system other than the target. Some of these effects can be reduced by using Time-of-Flight background reduction, while others can be reduced by acquiring a separate sample-out scan. Post processing background reduction techniques are also being developed for removing detector efficiency dependent noise. At this point we have acquired element information from whole mouse specimens and iron-overloaded liver models made of bovine liver tissue artificially injected with iron. Tomographic images have been generated from a solid iron and copper phantom. Our final goal is to implement a low-dose non-invasive scanning system for diagnosis of iron overload and breast cancer.
2) Monte-Carlo simulations in GEANT4
For each tomographic scan of a sample using NSECT, there are several acquisition parameters that can be varied. These parameters can broadly be classified into three categories: (i) Neutron Beam parameters: neutron flux, energy and beam width, (ii) Detector parameters: detector type, size, efficiency and location; (iii) Scanning Geometry: spatial and angular sampling rates. Due to the enormous number of combinations possible using these parameters, it is not feasible to investigate the effects of each parameter on the reconstructed image using a real neutron beam in the limited beam time available. A feasible alternative to this is to use Monte-Carlo simulations to reproduce the entire experiment in a virtual world. The effect of each individual parameter can then be studied using only computer processing time and resources. We use the high energy physics Monte-Carlo software package GEANT4, developed by CERN, which incorporates numerous tools required for building particle sources and detectors, and tracking particle interactions within them. The simulations built so far include the neutron source, HPGE and BGO gamma detectors, and several target materials such as iron, liver and breast tissue.
Odinaka, Ikenna, et al. “Joint System and Algorithm Design for Computationally Efficient Fan Beam Coded Aperture X-Ray Coherent Scatter Imaging.” Ieee Trans. Computational Imaging, vol. 3, 2017, pp. 506–21.
Kapadia, A., et al. “TH-AB-209-10: Breast Cancer Identification Through X-Ray Coherent Scatter Spectral Imaging.” Med Phys, vol. 43, no. 6, June 2016, p. 3865. Pubmed, doi:10.1118/1.4958101. Full Text
Lakshmanan, Manu N., et al. “Design and implementation of coded aperture coherent scatter spectral imaging of cancerous and healthy breast tissue samples.” J Med Imaging (Bellingham), vol. 3, no. 1, Jan. 2016, p. 013505. Pubmed, doi:10.1117/1.JMI.3.1.013505. Full Text
Lakshmanan, Manu N., et al. “Volumetric x-ray coherent scatter imaging of cancer in resected breast tissue: a Monte Carlo study using virtual anthropomorphic phantoms.” Phys Med Biol, vol. 60, no. 16, Aug. 2015, pp. 6355–70. Pubmed, doi:10.1088/0031-9155/60/16/6355. Full Text
Harrawood, B. P., et al. “Geant4 distributed computing for compact clusters.” Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, vol. 764, Nov. 2014, pp. 11–17. Scopus, doi:10.1016/j.nima.2014.07.014. Full Text
Lakshmanan, M. N., et al. “Simulations of nuclear resonance fluorescence in Geant4.” Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, vol. 763, Nov. 2014, pp. 89–96. Scopus, doi:10.1016/j.nima.2014.06.030. Full Text
Lakshmanan, M. N., et al. “An X-ray scatter system for material identification in cluttered objects: A Monte Carlo simulation study.” Nuclear Instruments and Methods in Physics Research, Section B: Beam Interactions With Materials and Atoms, vol. 335, Sept. 2014, pp. 31–38. Scopus, doi:10.1016/j.nimb.2014.05.021. Full Text
Belley, Matthew D., et al. “Assessment of individual organ doses in a realistic human phantom from neutron and gamma stimulated spectroscopy of the breast and liver.” Med Phys, vol. 41, no. 6, June 2014, p. 063902. Pubmed, doi:10.1118/1.4873684. Full Text
Lakshmanan, Manu N., et al. “Simulations of breast cancer imaging using gamma-ray stimulated emission computed tomography.” Ieee Trans Med Imaging, vol. 33, no. 2, Feb. 2014, pp. 546–55. Pubmed, doi:10.1109/TMI.2013.2290287. Full Text
Lakshmanan, M. N., et al. “X-ray coherent scatter imaging for surgical margin detection: A Monte Carlo study.” Progress in Biomedical Optics and Imaging Proceedings of Spie, vol. 9033, Jan. 2014. Scopus, doi:10.1117/12.2043856. Full Text
Sharma, S., et al. “A Real-Time Monte-Carlo Simulation Technique for Dose and Scatter Estimation in Virtual Clinical Trials for CT Imaging.” Medical Physics, vol. 45, no. 6, WILEY, 2018, pp. E689–E689.
Abadi, E., et al. “Incorporating Respiratory Motion to High-Resolution Textured Computational Phantoms to Simulate Realistic Free-Breathing CT Images.” Medical Physics, vol. 45, no. 6, WILEY, 2018, pp. E638–E638.
Fu, W., et al. “From patient-informed to patient-specific organ dose estimation in clinical computed tomography.” Progress in Biomedical Optics and Imaging Proceedings of Spie, vol. 10573, 2018. Scopus, doi:10.1117/12.2294954. Full Text
Abadi, E., et al. “Virtual clinical trial in action: Textured XCAT phantoms and scanner-specific CT simulator to characterize noise across CT reconstruction algorithms.” Progress in Biomedical Optics and Imaging Proceedings of Spie, vol. 10573, 2018. Scopus, doi:10.1117/12.2294599. Full Text
Sharma, S., et al. “A rapid GPU-based Monte Carlo simulation tool for individualized dose estimations in CT.” Progress in Biomedical Optics and Imaging Proceedings of Spie, vol. 10573, 2018. Scopus, doi:10.1117/12.2294965. Full Text
Abadi, E., et al. “Development of a fast, voxel-based, and scanner-specific CT simulator for image-quality-based virtual clinical trials.” Progress in Biomedical Optics and Imaging Proceedings of Spie, vol. 10573, 2018. Scopus, doi:10.1117/12.2293123. Full Text
Hoye, J., et al. “Organ Dose Estimation for CT Localizer Images.” Medical Physics, vol. 6, no. 44, American Association of Physicists in Medicine, 2017, pp. 3301–3301.
Hoye, J., et al. “A Smartphone Application for Organ Dose Estimation in CT, Tomosynthesis, and Radiography.” Medical Physics, vol. 44, no. 6, WILEY, 2017, pp. 3022–3022.
Hoye, J., et al. “Organ Dose Estimation for CT Localizer Images.” Medical Physics, vol. 44, no. 6, WILEY, 2017, pp. 3301–3301.
Spencer, J., et al. “BEST IN PHYSICS (IMAGING): X-Ray Diffraction Spectral Imaging for Breast Cancer Assessment.” Medical Physics, vol. 44, no. 6, WILEY, 2017, pp. 3292–3292.