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An anthropomorphic phantom underwent CT imaging with ULDCT (10mAs) and standard-dose CT (SDCT) (120mAs), respectively. ULDCT was reconstructed with AIIR and hybrid iterative reconstruction (HIR) (expressed as ULDCT-AIIR\n                      <jats:sub>phantom<\/jats:sub>\n                      and ULDCT-HIR\n                      <jats:sub>phantom<\/jats:sub>\n                      ), respectively, and SDCT was reconstructed with HIR (SDCT-HIR\n                      <jats:sub>phantom<\/jats:sub>\n                      ) as control. In the clinical part, 52 patients with malignant tumors underwent the total-body PET\/CT scan. ULDCT with AIIR (ULDCT-AIIR) and HIR (ULDCT-HIR), respectively, was reconstructed for PET attenuation correction, followed by the SDCT reconstructed with HIR (SDCT-HIR) for anatomical location. PET\/CT images\u2019 quality was qualitatively assessed by two readers. The CT\n                      <jats:sub>mean<\/jats:sub>\n                      , as well as the CT standard deviation (CT\n                      <jats:sub>sd<\/jats:sub>\n                      ), SUV\n                      <jats:sub>max<\/jats:sub>\n                      , SUV\n                      <jats:sub>mean<\/jats:sub>\n                      , and the SUV standard deviation (SUV\n                      <jats:sub>sd<\/jats:sub>\n                      ), was recorded. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated and compared.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The image quality of ULDCT-HIR\n                      <jats:sub>phantom<\/jats:sub>\n                      was inferior to the SDCT-HIR\n                      <jats:sub>phantom<\/jats:sub>\n                      , but no significant difference was found between the ULDCT-AIIR\n                      <jats:sub>phantom<\/jats:sub>\n                      and SDCT-HIR\n                      <jats:sub>phantom<\/jats:sub>\n                      . The subjective score of ULDCT-AIIR in the neck, chest and lower limb was equivalent to that of SDCT-HIR. Besides the brain and lower limb, the change rates of CT\n                      <jats:sub>mean<\/jats:sub>\n                      in thyroid, neck muscle, lung, mediastinum, back muscle, liver, lumbar muscle, first lumbar spine and sigmoid colon were \u22122.15, \u22121.52, 0.66, 2.97, 0.23, 8.91, 0.06, \u22124.29 and 8.78%, respectively, while all CT\n                      <jats:sub>sd<\/jats:sub>\n                      of ULDCT-AIIR was lower than that of SDCT-HIR. Except for the brain, the CNR of ULDCT-AIIR was the same as the SDCT-HIR, but the SNR was higher. The change rates of SUV\n                      <jats:sub>max<\/jats:sub>\n                      , SUV\n                      <jats:sub>mean<\/jats:sub>\n                      and SUV\n                      <jats:sub>sd<\/jats:sub>\n                      were within\n                      <jats:inline-formula>\n                        <jats:alternatives>\n                          <jats:tex-math>$$\\pm$$<\/jats:tex-math>\n                          <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                            <mml:mo>\u00b1<\/mml:mo>\n                          <\/mml:math>\n                        <\/jats:alternatives>\n                      <\/jats:inline-formula>\n                      3% in all ROIs. For the lesions, the SUV\n                      <jats:sub>max<\/jats:sub>\n                      , SUV\n                      <jats:sub>sd<\/jats:sub>\n                      and TBR showed no significant difference between PET-AIIR and PET-HIR.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The SDCT-HIR could not be replaced by the ULDCT-AIIR at date, but the AIIR algorithm decreased the image noise and increased the SNR, which can be implemented under special circumstances in PET\/CT examination.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s40658-022-00521-8","type":"journal-article","created":{"date-parts":[[2023,1,2]],"date-time":"2023-01-02T09:03:50Z","timestamp":1672650230000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Ultra-low-dose CT reconstructed with the artificial intelligence iterative reconstruction algorithm (AIIR) in 18F-FDG total-body PET\/CT examination: a preliminary study"],"prefix":"10.1186","volume":"10","author":[{"given":"Yan","family":"Hu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhe","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haojun","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingyi","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinlan","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7457-876X","authenticated-orcid":false,"given":"Hongcheng","family":"Shi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,1,2]]},"reference":[{"issue":"10114","key":"521_CR1","doi-asserted-by":"publisher","first-page":"2790","DOI":"10.1016\/S0140-6736(17)32134-7","volume":"390","author":"P Borchmann","year":"2017","unstructured":"Borchmann P, Goergen H, Kobe C, Lohri A, Greil R, Eichenauer DA, et al. 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This retrospective study was approved by the Institutional Review Board of Zhongshan Hospital, Fudan University, and written informed consent was signed for the use of the data from all the subjects.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"All authors discussed and approved the final manuscript for submission.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"1"}}