{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,4]],"date-time":"2026-11-04T02:17:31Z","timestamp":1793758651347,"version":"4.6.1"},"reference-count":22,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2017,10,13]],"date-time":"2017-10-13T00:00:00Z","timestamp":1507852800000},"content-version":"vor","delay-in-days":12,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100000070","name":"National Institute of Biomedical Imaging and Bioengineering","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000070","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2017,10]]},"abstract":"<jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>Using common datasets, to estimate and compare the diagnostic performance of image\u2010based denoising techniques or iterative reconstruction algorithms for the task of detecting hepatic metastases.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Datasets from contrast\u2010enhanced\n                      <jats:styled-content style=\"fixed-case\">CT<\/jats:styled-content>\n                      scans of the liver were provided to participants in an\n                      <jats:styled-content style=\"fixed-case\">NIH<\/jats:styled-content>\n                      \u2010,\n                      <jats:styled-content style=\"fixed-case\">AAPM<\/jats:styled-content>\n                      \u2010 and Mayo Clinic\u2010sponsored Low Dose\n                      <jats:styled-content style=\"fixed-case\">CT<\/jats:styled-content>\n                      Grand Challenge. Training data included full\u2010dose and quarter\u2010dose scans of the\n                      <jats:styled-content style=\"fixed-case\">ACR CT<\/jats:styled-content>\n                      accreditation phantom and 10 patient examinations; both images and projections were provided in the training data. Projection data were supplied in a vendor\u2010neutral standardized format (\n                      <jats:styled-content style=\"fixed-case\">DICOM<\/jats:styled-content>\n                      \u2010\n                      <jats:styled-content style=\"fixed-case\">CT<\/jats:styled-content>\n                      \u2010\n                      <jats:styled-content style=\"fixed-case\">PD<\/jats:styled-content>\n                      ). Twenty quarter\u2010dose patient datasets were provided to each participant for testing the performance of their technique. Images were provided to sites intending to perform denoising in the image domain. Fully preprocessed projection data and statistical noise maps were provided to sites intending to perform iterative reconstruction. Upon return of the denoised or iteratively reconstructed quarter\u2010dose images, randomized, blinded evaluation of the cases was performed using a Latin Square study design by 11 senior radiology residents or fellows, who marked the locations of identified hepatic metastases. Markings were scored against reference locations of clinically or pathologically demonstrated metastases to determine a per\u2010lesion normalized score and a per\u2010case normalized score (a faculty abdominal radiologist established the reference location using clinical and pathological information). Scores increased for correct detections; scores decreased for missed or incorrect detections. The winner for the competition was the entry that produced the highest total score (mean of the per\u2010lesion and per\u2010case normalized score). Reader confidence was used to compute a Jackknife alternative free\u2010response receiver operating characteristic (\n                      <jats:styled-content style=\"fixed-case\">JAFROC<\/jats:styled-content>\n                      ) figure of merit, which was used for breaking ties.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      103 participants from 90 sites and 26 countries registered to participate. Training data were shared with 77 sites that completed the data sharing agreements. Subsequently, 41 sites downloaded the 20 test cases, which included only the 25% dose data (\n                      <jats:styled-content style=\"fixed-case\">CTDI<\/jats:styled-content>\n                      vol\u00a0=\u00a03.0\u00a0\u00b1\u00a01.8\u00a0\n                      <jats:styled-content style=\"fixed-case\">mG<\/jats:styled-content>\n                      y,\n                      <jats:styled-content style=\"fixed-case\">SSDE<\/jats:styled-content>\n                      \u00a0=\u00a03.5\u00a0\u00b1\u00a01.3\u00a0\n                      <jats:styled-content style=\"fixed-case\">mG<\/jats:styled-content>\n                      y). 22 sites submitted results for evaluation. One site provided binary images and one site provided images with severe artifacts; cases from these sites were excluded from review and the participants removed from the challenge. The mean (range) per\u2010lesion and per\u2010case normalized scores were \u221224.2% (\u221275.8%, 3%) and 47% (10%, 70%), respectively. Compared to reader results for commercially reconstructed quarter\u2010dose images with no noise reduction, 11 of the 20 sites showed a numeric improvement in the mean\n                      <jats:styled-content style=\"fixed-case\">JAFROC<\/jats:styled-content>\n                      figure of merit. Notably two sites performed comparably to the reader results for full\u2010dose commercial images. The study was not designed for these comparisons, so wide confidence intervals surrounded these figures of merit and the results should be used only to motivate future testing.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      Infrastructure and methodology were developed to rapidly estimate observer performance for liver metastasis detection in low\u2010dose\n                      <jats:styled-content style=\"fixed-case\">CT<\/jats:styled-content>\n                      examinations of the liver after either image\u2010based denoising or iterative reconstruction. The results demonstrated large differences in detection and classification performance between noise reduction methods, although the majority of methods provided some improvement in performance relative to the commercial quarter\u2010dose images with no noise reduction applied.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.12345","type":"journal-article","created":{"date-parts":[[2017,10,13]],"date-time":"2017-10-13T02:10:19Z","timestamp":1507860619000},"source":"Crossref","is-referenced-by-count":317,"title":["Low\u2010dose\n                    <scp>CT<\/scp>\n                    for the detection and classification of metastatic liver lesions: Results of the 2016 Low Dose\n                    <scp>CT<\/scp>\n                    Grand Challenge"],"prefix":"10.1002","volume":"44","author":[{"given":"Cynthia H.","family":"McCollough","sequence":"first","affiliation":[{"name":"Department of Radiology Mayo Clinic Rochester MN 55920 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adam C.","family":"Bartley","sequence":"additional","affiliation":[{"name":"Department of Health Sciences Research Mayo Clinic Rochester MN 55920 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rickey E.","family":"Carter","sequence":"additional","affiliation":[{"name":"Department of Health Sciences Research Mayo Clinic Rochester MN 55920 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Baiyu","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Radiology Mayo Clinic Rochester MN 55920 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tammy A.","family":"Drees","sequence":"additional","affiliation":[{"name":"Department of Radiology Mayo Clinic Rochester MN 55920 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Phillip","family":"Edwards","sequence":"additional","affiliation":[{"name":"Department of Physiology and Biomedical Engineering Mayo Clinic Rochester MN 55920 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"suffix":"III","given":"David R.","family":"Holmes","sequence":"additional","affiliation":[{"name":"Department of Physiology and Biomedical Engineering Mayo Clinic Rochester MN 55920 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alice E.","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Radiology Mayo Clinic Rochester MN 55920 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Farhana","family":"Khan","sequence":"additional","affiliation":[{"name":"Information Services American Association of Physicists in Medicine Alexandria VA 22314 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuai","family":"Leng","sequence":"additional","affiliation":[{"name":"Department of Radiology Mayo Clinic Rochester MN 55920 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kyle L.","family":"McMillan","sequence":"additional","affiliation":[{"name":"Department of Radiology Mayo Clinic Rochester MN 55920 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gregory J.","family":"Michalak","sequence":"additional","affiliation":[{"name":"Department of Radiology Mayo Clinic Rochester MN 55920 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kristina M.","family":"Nunez","sequence":"additional","affiliation":[{"name":"Department of Radiology Mayo Clinic Rochester MN 55920 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lifeng","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Radiology Mayo Clinic Rochester MN 55920 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joel G.","family":"Fletcher","sequence":"additional","affiliation":[{"name":"Department of Radiology Mayo Clinic Rochester MN 55920 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2017,10,13]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.12112201"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.11102452"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.10101157"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.mayocp.2015.07.011"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2532082010"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1148\/rg.262055138"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.2217\/iim.09.5"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.12112265"},{"key":"e_1_2_8_10_1","first-page":"97831B","article-title":"An open library of CT patient projection data","volume":"9783","author":"Chen B","year":"2016","journal-title":"Proc SPIE"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1097\/RCT.0b013e318258e891"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.4935406"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2015141991"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.1769632"},{"key":"e_1_2_8_15_1","first-page":"220","volume-title":"Use of Water Equivalent Diameter for Calculating Patient Size and Size\u2010Specific Dose Estimates (SSDE) in CT (Task Group 220)","author":"American Association of Physicists in Medicine","year":"2014"},{"key":"e_1_2_8_16_1","first-page":"204","volume-title":"Size\u2010Specific Dose Estimates (SSDE) in Pediatric and Adult Body CT Examinations (Task Group 204)","author":"American Association of Physicists in Medicine","year":"2011"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.1769352"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1097\/00004424-199209000-00015"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.2532"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(86)90837-8"},{"key":"e_1_2_8_21_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.14131928"},{"key":"e_1_2_8_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-013-2964-1"},{"key":"e_1_2_8_23_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.13122349"}],"container-title":["Medical Physics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fmp.12345","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/mp.12345","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,24]],"date-time":"2023-09-24T11:58:31Z","timestamp":1695556711000},"score":1,"resource":{"primary":{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/10.1002\/mp.12345"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,10]]},"references-count":22,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2017,10]]}},"alternative-id":["10.1002\/mp.12345"],"URL":"https:\/\/doi.org\/10.1002\/mp.12345","archive":["Portico"],"relation":{},"ISSN":["0094-2405","2473-4209"],"issn-type":[{"value":"0094-2405","type":"print"},{"value":"2473-4209","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,10]]}}}