The isotopes of lithium separate somewhat during a variety of geological processes, including mineral formation (chemical precipitation and ion exchange). A small percentage of lithium-6 is also known to be produced by nuclear reactions in certain stars. Lithium-7 and lithium-6 are two of the primordial nuclides that were produced in the Big Bang, with lithium-7 to be 10 −9 of all primordial nuclides, and lithium-6 around 10 −13. The shortest-lived known isotope of lithium is lithium-4, which decays by proton emission with a half-life of about 91(9) yoctoseconds ( 9.1(9) ×10 −23 s), although the half-life of lithium-3 is yet to be determined, and is likely to be much shorter, like helium-2 (diproton) which undergoes proton emission within 10 −9 s. All of the remaining isotopes of lithium have half-lives that are shorter than 10 nanoseconds. Lithium-9 has a half-life of 178.2(4) ms, and lithium-11 has a half-life of 8.75(6) ms. The longest-lived radioisotope of lithium is lithium-8, which has a half-life of just 838.7(3) milliseconds. Both of the natural isotopes have an unexpectedly low nuclear binding energy per nucleon ( 5 332.3312(3) MeV for lithium-6 and 5 606.4401(6) MeV for lithium-7) when compared with the adjacent lighter and heavier elements, helium ( 7 073.9156(4) MeV for helium-4) and beryllium ( 6 462.6693(85) MeV for beryllium-9). © 2021 American Association of Physicists in Medicine.Naturally occurring lithium ( 3Li) is composed of two stable isotopes, lithium-6 and lithium-7, with the latter being far more abundant on Earth. Additionally, when there are no perfusion defects present in the derived PBV maps, no pulmonary emboli were diagnosed by an experienced thoracic radiologist.Įffective atomic number-based quantitative PBV maps provide the needed sensitive and specific biomarker to quantify pulmonary perfusion defects.ĭual energy CT effective atomic number map functional lung imaging material decomposition multienergy CT pulmonary embolism pulmonary perfusion imaging quantitative imaging. Perfusion maps were generated for four human subjects to demonstrate the differences between conventional iodine material image-based PBV (PBV iodine ) derived from two-material decompositions and the proposed PB V Z eff method.Īmong patients with pulmonary emboli, the proposed PB V Z eff maps clearly show the perfusion defects while the PBV iodine maps do not. Namely, quantitative PB V Z eff is determined by Z eff images instead of the iodine basis images.
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The quantitative relationship between the perfusion blood volume (PBV) in pulmonary parenchyma and the effective atomic number (Z eff ) spatial distribution was studied to show that the desired quantitative PBV maps are determined by the spatial maps of Z eff as PB V Z eff ( x ) = a Z eff β ( x ) + b, where a, b, and β are three constants. (i) To demonstrate the limitations of iodine material images in pulmonary perfusion defect quantification and (ii) to develop and validate a new quantitative biomarker using effective atomic numbers derived from DECT images. However, iodine material images do not provide the needed absolute quantification of the pulmonary blood pool, as materials with effective atomic numbers (Z eff ) different from those of basis materials may also contribute to iodine material images, thus confounding the quantification of perfusion defects. Iodine material images (aka iodine basis images) generated from dual energy computed tomography (DECT) have been used to assess potential perfusion defects in the pulmonary parenchyma.