{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T12:06:50Z","timestamp":1783512410779,"version":"3.55.0"},"reference-count":26,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["SAGE Open Medicine"],"published-print":{"date-parts":[[2025,7]]},"abstract":"<jats:sec>\n                    <jats:title>Objectives:<\/jats:title>\n                    <jats:p>Radiation exposure has been a cause of concern in computed tomography imaging. Reducing radiation dose increases the image noise which can be compensated by using reconstruction techniques. Recently artificial intelligence-based reconstruction technique has been introduced. Therefore, the purpose of the study was to prospectively compare the image quality between Idose4 and Precise Image in normal BMI individuals.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>Sixty-six consecutive patients with a normal body habitus undergoing contrast-enhanced abdomen and pelvis scan were included in the study. All scans were performed using 100\u2009kVp and tube current modulation. The acquired images were reconstructed to iDose4 and precise imaging. Quantitatively images were analyzed by placing regions of interest in different organs to estimate the image noise, signal-to-noise ratio, and contrast-to-noise ratio. Qualitative analysis was done by two radiologists on a five-point Likert scale.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>Image noise was significantly reduced using Precise Image across the plain (9.11\u2009\u00b1\u20091.43 vs 8.18\u2009\u00b1\u20091.2), arterial (14.34\u2009\u00b1\u20092.1 vs 10.21\u2009\u00b1\u20091.5), and portovenous phase (14.78\u2009\u00b1\u20092.30 vs 11.97\u2009\u00b1\u20092.07) with maximum noise reduction in the arterial and portovenous phases. Signal-to-noise ratio and contrast-to-noise ratio was significantly improved in all the organs across the plain, arterial, and portovenous phases. Qualitative analysis showed no significant difference between Idose4 and Precise Image with regards to visualization of large vessels in the arterial and portovenous phases. However, precise image was graded better than Idose4 with respect to visualization\/conspicuity, image noise, and artifacts.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>Precise Image can be useful in reducing the image noise and improving the signal-to-noise ratio and contrast-to-noise ratio in low-dose computed tomography protocol among normal BMI individuals.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/20503121251336046","type":"journal-article","created":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T09:49:36Z","timestamp":1755856176000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["A comparison of the image quality between deep learning reconstruction algorithm and iDose4 using low dose abdominopelvic computed tomography for individuals with normal BMI"],"prefix":"10.1177","volume":"13","author":[{"given":"Thejas","family":"Marike Shivakumar","sequence":"first","affiliation":[{"name":"Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3725-6774","authenticated-orcid":false,"given":"Nitika C.","family":"Panakkal","sequence":"additional","affiliation":[{"name":"Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shailesh","family":"Nayak","sequence":"additional","affiliation":[{"name":"Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rajagopal","family":"Kadavigere","sequence":"additional","affiliation":[{"name":"Radio-Diagnosis and Imaging, Department of Radio Diagnosis and Medical Imaging, Kasturba Medical College, Manipal Academy of Higher Education, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tanushree R.","family":"Kamath","sequence":"additional","affiliation":[{"name":"Radio-Diagnosis and Imaging, Department of Radio Diagnosis and Medical Imaging, Kasturba Medical College, Manipal Academy of Higher Education, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suresh","family":"Sukumar","sequence":"additional","affiliation":[{"name":"Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,8,22]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmir.2020.09.001"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.14.12590"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-018-5810-7"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-012-2764-z"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.crad.2021.01.010"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.1097\/RCT.0b013e31821fee94"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics13061182"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.1177\/20584601211008391"},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11604-021-01089-6"},{"issue":"3","key":"e_1_3_3_11_2","article-title":"Low kilovoltage protocol based on body mass index: feasibility and influence on radiation dose and image quality","volume":"54","author":"Panakkal NC","year":"2023","unstructured":"Panakkal NC, Rajagopal K, Suresh S, et al Low kilovoltage protocol based on body mass index: feasibility and influence on radiation dose and image quality. 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