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Gemstone Spectral Imaging
Gemstone Spectral Imaging (GSI) is GE’s proven DECT solution, which enables the generator to switch the beam energy between the low setting (80 kVp) and the high setting (140 kVp) within microseconds. Use this to achieve the 0.25 ms cycle time, achieve simultaneous temporal and spatial registration, and get better energy separation with full 50 cm spectral Field of View. GSI has been routinely used in diagnostic oncology.
GSI’s unique, fast KV switching design with projection-based material decomposition can achieve excellent quantification accuracy and material differentiation and reduce artifact.
Based on the evidence, GSI potential benefits in target delineation, normal tissue characterization, and the dose calculation accuracy by leveraging different GSI images, included:
- Monochromatic images
- Material decomposition images
- Virtual unenhanced image (VUE)
- GSI Metal artifact reduction (MAR)
- Effective-Z
- Artifact reduction
Monochromatic images
Left: 70 keV; Right: 40 keV. Monochromatic images at lower energy levels can achieve higher CNR and benefit lesion depiction and target delineation. Monochromatic images at higher energy levels have the benefits of beam hardening reduction. Monochromatic images potential benefits for radiation oncology: enhanced lesion depiction, precise target delineation, beam hardening reduction, and potential for precise target delineation and dose calculation.Material density
Iodine color maps. The material density images (MD) provide qualitative and quantitative information regarding tissue composition and contrast media distribution, increase tissue contrast and amplify subtle differences in attenuation between normal and abnormal tissues. The material density benefits for radiation oncology: enhanced lesion detection, characterization and delineation, and potential for post-treatment tumor vitality monitoring.
GSI MAR
Left: 40 keV; Right: 40 keV with GSI MAR. GSI Metal Artifact Reduction (GSI MAR) is a dual energy metal artifact reduction algorithm designed to reveal anatomic details obscured by metal artifacts. GSI MAR benefits for radiation oncology: reduced artifacts for more productive target delineation and dose calculation.VUE
Iodine color maps. Virtual Unenhanced images (VUE) – The HU values in the VUE images were similar to the HU values in the non-contrast images which can assess anatomy potential masked by contrast and provide reliable information for characterizing diverse lesions. VUE benefits for radiation oncology6: VUE potentially may be used for lesion characterization, avoiding the error of registration when contrast enhancement requires: accurate target delineation and dose calculations.
Effective-Z map
Effective-Z (effective atomic number) generated by GSI is accurate2 and closely related to diverse tissue electron density. Eff-Z map may help to illustrate tissue distribution. The accuracy of proton stopping-power ratio (SPR) prediction is dependent on the ability to correctly characterize patient tissues. Conventional CT HU-SPR conversion has limitations in dealing with human tissue diversity.1 Effective-Z map benefits for radiation oncology: Eff-Z may be used for prediction in proton therapy, with the potential1,3,4 to reduce uncertainties in particle range prediction5 and improve accuracy of dose planning.
Image Gallery
Female, patients with cancer in anal canal
Patients with prostate cancer metastasis to left shoulder
Smart MAR for single energy
GSI MAR for dual energy
Phantom image with motion artifact (A)
Rev CT ES 4D CT clinical image (A)
Phantom image with motion artifact (B)
Rev CT ES 4D CT clinical image (B)
AdvantageSim™ MD and AW Server
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2. Goodsitt, M., Christodoulou, E., Larson, S. (2011). Accuracies of the synthesized monochromatic CT numbers and effective atomic numbers obtained with a rapid kVp switching dual energy CT scanner Medical Physics 38(4), 2222-2232.
3. Kaginelli, S. B., Rajeshwari, T., Sharanabasappa, Kerur, B. R., & Kumar, A. S. (2009). Effective atomic numbers and electron density of dosimetric material. Journal of medical physics, 34(3), 176–179.
4. Yang M, Virshup G , Clayton J, Zhu XR, Mohan R, Dong L. Theoreti-cal variance analysis of single- and dual-energy computed tomography methods for calculating proton stopping power ratios of biological tissues. Phys Med Biol. 2010;55:1343–1362.
5. Compared to generic Hounsfield look-up table (HLUT) method.