Breast cancer detection using neutron stimulated emission computed tomography: prominent elements and dose requirements

Determining Serum Zinc and Magnesium Levels in Hemodialysis Patients Could be Helpful for Clinicians

Trace element determination is requested rarely for critically ill patients in Iran, due to the underestimation of the trace element determination by Iranian physicians. The aim was to compare the levels of Zn and Mg in a group of hemodialysis patients and normal individuals. This study shows that trace element determination is helpful for management of hemodialysis patients. Fifty-three hemodialysis patients and 51 control individuals were randomly analyzed for Zn and Mg serum levels. Comparison of before or after dialysis and with normal individuals was done and receiver operating characteristics (ROC) curves were plotted to evaluate the analytical sensitivity and specificity of Zn and Mg determination. Confidence interval for all statistical methods was 95 %. Zinc serum levels were decreased after hemodialysis insignificantly (P = 0.201) but Mg levels were decreased significantly (P = 0.000). Both Zn and Mg levels, before and after hemodialysis were meaningfully lower than normal controls (P < 0.05). ROC analysis showed that the area under the curve was high for Zn levels both before and after hemodialysis but it was high for Mg only before hemodialysis. Current study shows that serum Zn and Mg measurements can have clinical importance. Both before and after hemodialysis, serum Zn = 297.5 µg/L and Mg = 2.295 µg/L are proposed as cut-off values with about 90 % specificity, for monitoring of these two element in hemodialysis patients. It is suggested that clinicians consider the measurement of these trace elements for hemodialysis patients routinely or periodically as clinical chemistry tests.

Simulations of breast cancer imaging using gamma-ray stimulated emission computed tomography

Here, we present an innovative imaging technology for breast cancer using gamma-ray stimulated spectroscopy based on the nuclear resonance fluorescence (NRF) technique. In NRF, a nucleus of a given isotope selectively absorbs gamma rays with energy exactly equal to one of its quantized energy states, emitting an outgoing gamma ray with energy nearly identical to that of the incident gamma ray. Due to its application of NRF, gamma-ray stimulated spectroscopy is sensitive to trace element concentration changes, which are suspected to occur at early stages of breast cancer, and therefore can be potentially used to noninvasively detect and diagnose cancer in its early stages. Using Monte-Carlo simulations, we have designed and demonstrated an imaging system that uses gamma-ray stimulated spectroscopy for visualizing breast cancer. We show that gamma-ray stimulated spectroscopy is able to visualize breast cancer lesions based primarily on the differences in the concentrations of trace elements between diseased and healthy tissue, rather than differences in density that are crucial for X-ray mammography. The technique shows potential for early breast cancer detection; however, improvements are needed in gamma-ray laser technology for the technique to become a clinically feasible method of detecting and diagnosing cancer at early stages.

Quantitative assessment of lesion detection accuracy, resolution, and reconstruction algorithms in neutron stimulated emission computed tomography

We present a quantitative analysis of the image quality obtained using filtered back-projection (FBP) with Ram-Lak filtering and maximum likelihood-expectation maximization (ML-EM)-with no post-reconstruction filtering in either case-in neutron stimulated emission computed tomography (NSECT) imaging using Monte Carlo simulations in the context of clinically relevant models of liver iron overload. The ratios of pixel intensities for several regions of interest and lesion shape detection using an active-contours segmentation algorithm are assessed for accuracy across different scanning configurations and reconstruction algorithms. The modulation transfer functions (MTFs) are also computed for the cases under study and are applied to determine a minimum detectable lesion spacing as a form of sensitivity analysis. The accuracy of NSECT imaging in measuring relative tissue concentration is presented for simulated clinical liver cases. When using the 15th iteration, ML-EM provides at least 25% better resolution than FBP and proves to be highly robust under low-signal high-noise conditions prevalent in NSECT. However, FBP gives more accurate lesion pixel intensity ratios and size estimates in some cases; due to advantages provided by both reconstruction algorithms, it is worth exploring the development of an algorithm that is a hybrid of the two. We also show that NSECT imaging can be used to accurately detect 3-cm lesions in backgrounds that are a significant fraction (one-quarter) of the concentration of the lesion, down to a 4-cm spacing between lesions.

Dual-energy contrast-enhanced breast tomosynthesis: optimization of beam quality for dose and image quality

Dual-energy contrast-enhanced breast tomosynthesis is a promising technique to obtain three-dimensional functional information from the breast with high resolution and speed. To optimize this new method, this study searched for the beam quality that maximized image quality in terms of mass detection performance. A digital tomosynthesis system was modeled using a fast ray-tracing algorithm, which created simulated projection images by tracking photons through a voxelized anatomical breast phantom containing iodinated lesions. The single-energy images were combined into dual-energy images through a weighted log subtraction process. The weighting factor was optimized to minimize anatomical noise, while the dose distribution was chosen to minimize quantum noise. The dual-energy images were analyzed for the signal difference to noise ratio (SdNR) of iodinated masses. The fast ray-tracing explored 523 776 dual-energy combinations to identify which yields optimum mass SdNR. The ray-tracing results were verified using a Monte Carlo model for a breast tomosynthesis system with a selenium-based flat-panel detector. The projection images from our voxelized breast phantom were obtained at a constant total glandular dose. The projections were combined using weighted log subtraction and reconstructed using commercial reconstruction software. The lesion SdNR was measured in the central reconstructed slice. The SdNR performance varied markedly across the kVp and filtration space. Ray-tracing results indicated that the mass SdNR was maximized with a high-energy tungsten beam at 49 kVp with 92.5 µm of copper filtration and a low-energy tungsten beam at 49 kVp with 95 µm of tin filtration. This result was consistent with Monte Carlo findings. This mammographic technique led to a mass SdNR of 0.92 ± 0.03 in the projections and 3.68 ± 0.19 in the reconstructed slices. These values were markedly higher than those for non-optimized techniques. Our findings indicate that dual-energy breast tomosynthesis can be performed optimally at 49 kVp with alternative copper and tin filters, with reconstruction following weighted subtraction. The optimum technique provides best visibility of iodine against structured breast background in dual-energy contrast-enhanced breast tomosynthesis.

Prompt gamma-ray emission from biological tissues during proton irradiation: a preliminary study

In this paper, we present the results of a preliminary study of secondary 'prompt' gamma-ray emission produced by proton-nuclear interactions within tissue during proton radiotherapy. Monte Carlo simulations were performed for mono-energetic proton beams, ranging from 2.5 MeV to 250 MeV, irradiating elemental and tissue targets. Calculations of the emission spectra from different biological tissues and their elemental components were made. Also, prompt gamma rays emitted during delivery of a clinical proton spread-out Bragg peak (SOBP) in a homogeneous water phantom and a water phantom containing heterogeneous tissue inserts were calculated to study the correlation between prompt gamma-ray production and proton dose delivery. The results show that the prompt gamma-ray spectra differ significantly for each type of tissue studied. The relative intensity of the characteristic gamma rays emitted from a given tissue was shown to be proportional to the concentration of each element in that tissue. A strong correlation was found between the delivered SOBP dose distribution and the characteristic prompt gamma-ray production. Based on these results, we discuss the potential use of prompt gamma-ray emission as a method to verify the accuracy and efficacy of doses delivered with proton radiotherapy.

Experimental detection of iron overload in liver through neutron stimulated emission spectroscopy

Iron overload disorders have been the focus of several quantification studies involving non-invasive imaging modalities. Neutron spectroscopic techniques have demonstrated great potential in detecting iron concentrations within biological tissue. We are developing a neutron spectroscopic technique called neutron stimulated emission computed tomography (NSECT), which has the potential to diagnose iron overload in the liver at clinically acceptable patient dose levels through a non-invasive scan. The technique uses inelastic scatter interactions between atomic nuclei in the sample and incoming fast neutrons to non-invasively determine the concentration of elements in the sample. This paper discusses a non-tomographic application of NSECT investigating the feasibility of detecting elevated iron concentrations in the liver. A model of iron overload in the human body was created using bovine liver tissue housed inside a human torso phantom and was scanned with a 5 MeV pulsed beam using single-position spectroscopy. Spectra were reconstructed and analyzed with algorithms designed specifically for NSECT. Results from spectroscopic quantification indicate that NSECT can currently detect liver iron concentrations of 6 mg g(-1) or higher and has the potential to detect lower concentrations by optimizing the acquisition geometry to scan a larger volume of tissue. The experiment described in this paper has two important outcomes: (i) it demonstrates that NSECT has the potential to detect clinically relevant concentrations of iron in the human body through a non-invasive scan and (ii) it provides a comparative standard to guide the design of iron overload phantoms for future NSECT liver iron quantification studies.