Dosimetric Evaluation of Metal Artefact Reduction using Metal Artefact Reduction (MAR) Algorithm and Dual-energy Computed Tomography (CT) Method

Purpose: Computed Tomography (CT) is one of the standard diagnostic imaging modalities for the evaluation of a patient’s medical condition. In comparison to other imaging modalities such as Magnetic Resonance Imaging (MRI), CT is a fast acquisition imaging device with higher spatial resolution and higher contrast-to-noise ratio (CNR) for bony structures. CT images are presented through a gray scale of independent values in Hounsfield units (HU). High HU-valued materials represent higher density. High density materials, such as metal, tend to erroneously increase the HU values around it due to reconstruction software limitations. This problem of increased HU values due to metal presence is referred to as metal artefacts. Hip prostheses, dental fillings, aneurysm clips, and spinal clips are a few examples of metal objects that are of clinical relevance. These implants create artefacts such as beam hardening and photon starvation that distort CT images and degrade image quality. This is of great significance because the distortions may cause improper evaluation of images and inaccurate dose calculation in the treatment planning system. Different algorithms are being developed to reduce these artefacts for better image quality for both diagnostic and therapeutic purposes. However, very limited information is available about the effect of artefact correction on dose calculation accuracy. This research study evaluates the dosimetric effect of metal artefact reduction algorithms on severe artefacts on CT images. This study uses Gemstone Spectral Imaging (GSI)-based MAR algorithm, projection-based Metal Artefact Reduction (MAR) algorithm, and the Dual-Energy method.

Materials and Methods: The Gemstone Spectral Imaging (GSI)-based and SMART Metal Artefact Reduction (MAR) algorithms are metal artefact reduction protocols embedded in two different CT scanner models by General Electric (GE), and the Dual-Energy Imaging Method was developed at Duke University. All three approaches were applied in this research for dosimetric evaluation on CT images with severe metal artefacts. The first part of the research used a water phantom with four iodine syringes. Two sets of plans, multi-arc plans and single-arc plans, using the Volumetric Modulated Arc therapy (VMAT) technique were designed to avoid or minimize influences from high-density objects. The second part of the research used projection-based MAR Algorithm and the Dual-Energy Method. Calculated Doses (Mean, Minimum, and Maximum Doses) to the planning treatment volume (PTV) were compared and homogeneity index (HI) calculated.

Results: (1) Without the GSI-based MAR application, a percent error between mean dose and the absolute dose ranging from 3.4-5.7% per fraction was observed. In contrast, the error was decreased to a range of 0.09-2.3% per fraction with the GSI-based MAR algorithm. There was a percent difference ranging from 1.7-4.2% per fraction between with and without using the GSI-based MAR algorithm. (2) A range of 0.1-3.2% difference was observed for the maximum dose values, 1.5-10.4% for minimum dose difference, and 1.4-1.7% difference on the mean doses. Homogeneity indexes (HI) ranging from 0.068-0.065 for dual-energy method and 0.063-0.141 with projection-based MAR algorithm were also calculated.

Conclusion: (1) Percent error without using the GSI-based MAR algorithm may deviate as high as 5.7%. This error invalidates the goal of Radiation Therapy to provide a more precise treatment. Thus, GSI-based MAR algorithm was desirable due to its better dose calculation accuracy. (2) Based on direct numerical observation, there was no apparent deviation between the mean doses of different techniques but deviation was evident on the maximum and minimum doses. The HI for the dual-energy method almost achieved the desirable null values. In conclusion, the Dual-Energy method gave better dose calculation accuracy to the planning treatment volume (PTV) for images with metal artefacts than with or without GE MAR Algorithm.

Development of Plasmonic Nanoplatforms for Diagnostics, Therapy, and Sensing

Recent advances in nanotechnology have led to the application of nanoparticles in a wide variety of fields. In the field of nanomedicine, there is great emphasis on combining diagnostic and therapeutic modalities into a single nanoparticle construct (theranostics). In particular, anisotropic nanoparticles have shown great potential for surface-enhanced Raman scattering (SERS) detection due to their unique optical properties. Gold nanostars are a type of anisotropic nanoparticle with one of the highest SERS enhancement factors in a non-aggregated state. By utilizing the distinct characteristics of gold nanostars, new plasmonic materials for diagnostics, therapy, and sensing can be synthesized. The work described herein is divided into two main themes. The first half presents a novel, theranostic nanoplatform that can be used for both SERS detection and photodynamic therapy (PDT). The second half involves the rational design of silver-coated gold nanostars for increasing SERS signal intensity and improving reproducibility and quantification in SERS measurements.

The theranostic nanoplatforms consist of Raman-labeled gold nanostars coated with a silica shell. Photosensitizer molecules for PDT can be loaded into the silica matrix, while retaining the SERS signal of the gold nanostar core. SERS detection and PDT are performed at different wavelengths, so there is no interference between the diagnostic and therapeutic modalities. Singlet oxygen generation (a measure of PDT effectiveness) was demonstrated from the drug-loaded nanocomposites. In vitro testing with breast cancer cells showed that the nanoplatform could be successfully used for PDT. When further conjugating the nanoplatform with a cell-penetrating peptide (CPP), efficacy of both SERS detection and PDT is enhanced.

The rational design of plasmonic nanoparticles for SERS sensing involved the synthesis of silver-coated gold nanostars. Investigation of the silver coating process revealed that preservation of the gold nanostar tips was necessary to achieve the increased SERS intensity. At the optimal amount of silver coating, the SERS intensity is increased by over an order of magnitude. It was determined that a majority of the increased SERS signal can be attributed to reducing the inner filter effect, as the silver coating process moves the extinction of the particles far away from the laser excitation line. To improve reproducibility and quantitative SERS detection, an internal standard was incorporated into the particles. By embedding a small-molecule dye between the gold and silver surfaces, SERS signal was obtained both from the internal dye and external analyte on the particle surface. By normalizing the external analyte signal to the internal reference signal, reproducibility and quantitative analysis are improved in a variety of experimental conditions.