Browsing by Subject "NSECT"

Proposed is an investigation into the effect of lower-energy source on the tumor representation of an image acquired by a neutron-based spectroscopic imaging modality, Neutron Stimulated Emission Computed Tomography (NSECT).

The NSECT experiments were performed at a shielded neutron source of the Triangle Universities Nuclear Laboratory (TUNL), which was proficient at creating neutron beams of energy up to 20MeV. However, this neutron generator is not feasible for clinical use due to its large size. Smaller compact sources such as deuterium-deuterium (DD) neutron generators are attractive alternatives that can produce neutrons of sufficient energy to stimulate isotopes of interest in the human body. However, DD generator is not competent at producing neutrons of high energy. Thus, the focus of this work is to evaluate the effect of lower-energy neutrons, such as 2.5MeV and 3.2MeV, on the NSECT images.

The experiments were modeled and simulated in this work using a Monte Carlo toolkit, Geant4. In Geant4 space, an anthropomorphic phantom of cancerous tissue was scanned by a simulated neutron source. During scanning, the phantom was translated to cover the whole field of view (FOV) and rotated over 180 degrees for the purpose of tomographic imaging. Neutrons and gammas emitted were captured by a virtual detector, which could identify the energy and position of each particle. Information of position and energy of gammas detected resulted in a sinogram for an array of energies, created by selecting the energy characteristic to a specific element. Using the sinograms, two-dimensional maps of the spatial concentration of the element could be reconstructed through a reconstruction algorithm and the elemental concentration revealed the internal geometry of the phantom.

Images were generated when the phantom was scanned by 5MeV, 3.2MeV and 2.5MeV neutron sources. Comparison of tumor parameters in these images indicates that a neutron source of lower energy could degrade the tumor representation in a NSECT image on the aspects of concentration, brightness and underestimation of the tumor size. Then further investigations with 50,000, 100,000, 150,000 and 200,000 neutron events were performed respectively in the 3.2MeV-source case and 2.5MeV-source case in order to test whether the number of neutrons is correlated to the quality of the reconstructed images. Improvement of tumor representation, for example, a clearer tumor region and more accurate tumor size information, shows that increase in the number of incident neutrons has a positive effect on the reconstructed image. This work demonstrates the effect that low energy neutrons have on the image and verifies the feasibility of using low-energy neutrons as the source in NSECT breast imaging.

Proposed is a method for investigating optimal acquisition parameters in NSECT, neutron stimulated emission computed tomography, for good image quality and low dose for diagnosing liver and breast cancers. These parameters include the number of angles, number of translations per angle, beam width, and beam width spacing. These parameters will affect dose, which will increase with increasing total neutron flux. Therefore, a balance must be achieved for the parameters mentioned above, to yield a desired dose limit and tolerable spatial resolution necessary for liver and breast cancer diagnosis.

Using Monte Carlo simulation toolkit GEANT4, the effects of beam spread due to neutron elastic scatter was explored. Then, a geometrical water torso phantom with slanted edge solid iron phantom was run for different acquisition parameters, and an MTF was taken to determine resolution for each set. For dose considerations, two anthropomorphic voxelized phantoms, one with liver cancer lesions, and one with breast cancer lesions, were scanned with the same parameter sets, and organ doses and DVHs, dose volume histograms, was computed for each set. In addition, images of the phantom in the lesion plane were reconstructed for those parameter sets showing best resolution and lowest dose.

It is found that beam spread due to elastic scatter off of Hydrogen atoms is negligible for all beam widths. For optimal resolution in the primary breast phantom, it was found that acquisition parameters of a 5 mm beam, with no gaps, with any of the five angles provided the superior resolution. For the optimal resolution in the liver, it was found that down sampling angles and introducing gaps between projections greatly affected image accuracy and resolution. Also, the 5 mm beam width provided better geometrical accuracy, but the 1 cm bream width provided slightly better resolution.

Organ doses are computed for the primary organ and organs at risk for each parameter set at 500 K neutrons per projection. For a scan of the full volume of the liver, liver organ doses ranged from 25.83 to 0.19 mSv. For the same scan, the organ doses for the heart ranged from 0.18 to 0.05 mSv. For a scan with the same pool of acquisition parameters of the full volume of the breast, breast organ doses ranged from 49.87 to 0.38 mSv. Furthermore, the DVHs for both scans showed a very steep drop-off at low dose bins for secondary organs at risk and a reasonable drop-off for the primary organ.

In choosing the optimal acquisition parameters using both resolution and dose, a metric equal to resolution times dose is used, in which low values are optimal. An upper threshold for the metric was chosen based on dose values in currently used medical imaging modalities. A pool of optimal parameter sets was then identified using the metric. To further identify the optimum, a metric estimating geometrical accuracy of the reconstructed square was used. For the breast scan, the optimal parameter set was a 1 cm beam width, with 0 mm a gap, with 12 angles. For the liver scan, the optimal parameter set was a 1 cm beam width, with a 0 mm gap, with 36 angles.

Finally, reconstructed images of the anthropomorphic scans using the super sampled geometry in the liver scan showed one lesion, using images of iron and phosphorous. With more degraded image quality, reconstructed images of the breasts using the super sampled geometry showed only the three cm lesion accurately. The images reconstructed from the optimal set identified for liver scans also showed the larger lesion, except with some noise from the presence of iron and phosphorous in other organs. The images reconstructed from the optimal set identified for the breast scans had a similar result to that of the super-sampled case, albeit with lower contrast. The least sampled case for both scans were found to be diagnostically useless. From these anthropomorphic images, this work demonstrates that in-vivo imaging of breast and liver cancers may be potentially possible with NSECT at a low dose.