{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T11:18:50Z","timestamp":1788347930805,"version":"build-2803163510"},"reference-count":28,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T00:00:00Z","timestamp":1788307200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002476","name":"Eulji University","doi-asserted-by":"publisher","award":["2023-EMBRI UI0002"],"award-info":[{"award-number":["2023-EMBRI UI0002"]}],"id":[{"id":"10.13039\/501100002476","id-type":"DOI","asserted-by":"publisher"}]},{"award":["2023-EMBRI UI0002"],"award-info":[{"award-number":["2023-EMBRI UI0002"]}],"id":[{"id":"https:\/\/ror.org\/005bty106","id-type":"ROR","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea (NRF) grant funded by the Korea government","doi-asserted-by":"publisher","award":["NRF-2022R1G1A1004775"],"award-info":[{"award-number":["NRF-2022R1G1A1004775"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"award":["NRF-2022R1G1A1004775"],"award-info":[{"award-number":["NRF-2022R1G1A1004775"]}],"id":[{"id":"https:\/\/ror.org\/013aysd81","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background\/Objectives: N-3-[18F]fluoropropyl-2\u03b2-carbomethoxy-3\u03b2-4-iodophenyl nortropane ([18F]FP-CIT) positron emission tomography\/computed tomography (PET\/CT) is an effective imaging tool for diagnosing parkinsonism. This study evaluated the feasibility of deep learning (DL)-driven image restoration of short-duration [18F]FP-CIT images. Methods: List-mode data from 202 patients who underwent [18F]FP-CIT PET\/CT were reconstructed into 30-s (30sec), 1-min (1min), and reference 10-min (10min) acquisition durations. Patients were divided into training, validation, and test sets in a 6:2:2 ratio. The U-Net model was implemented to generate the DL images from 30sec and 1min data. The visual image quality was assessed using a three-point scale, visual interpretation of striatal dopamine transporter binding patterns, regional standardized uptake value ratios (SUVRs), and quantitative quality metrics including the peak signal-to-noise ratio, root mean squared error, and universal quality index among five series of images: 30sec, 1min, DL-30sec, DL-1min, and 10min. Results: While 30sec and 1min low-count scans showed poor image quality, the DL-driven algorithm showed significant improvement; DL-1min scans achieved excellent ratings in 95% of cases. Concordance with the reference images was 85.0% for visual image quality and 92.5% for visual interpretation in the DL-30sec images, and 97.5% and 92.5%, respectively, in the DL-1min images. Discordant interpretations occurred mainly in patients with atypical parkinsonism. Regional SUVR values and quantitative metrics for the DL-1min images showed good agreement and smaller biases with respect to the reference images, compared with those of DL-30sec images. Conclusions: The DL-driven method generated clinically acceptable [18F]FP-CIT images while reducing acquisition time, with better image quality in the DL-1min than in the DL-30sec images. Concordance in visual interpretation was reduced in the small subgroup of patients with atypical parkinsonism.<\/jats:p>","DOI":"10.3390\/diagnostics16172825","type":"journal-article","created":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T10:57:23Z","timestamp":1788346643000},"page":"2825","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Feasibility Study of Deep Learning-Driven Image Restoration for Fast, Low-Count [18F]FP-CIT Digital PET\/CT"],"prefix":"10.3390","volume":"16","author":[{"given":"Sora","family":"Baek","sequence":"first","affiliation":[{"name":"Department of Nuclear Medicine, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, 150, Seongan-ro, Gangdong-gu, Seoul 05355, Republic of 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Young","family":"Joo","sequence":"additional","affiliation":[{"name":"Department of Neurology, Uijeongbu Eulji Medical Center, Eulji University School of Medicine, 712, Dongil-ro, Uijeongbu-si 11759, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"investigation","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"Hyung-ji","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Neurology, Uijeongbu Eulji Medical Center, Eulji University School of Medicine, 712, Dongil-ro, Uijeongbu-si 11759, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"investigation","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"Ohyun","family":"Kwon","sequence":"additional","affiliation":[{"name":"Department of Neurology, Uijeongbu Eulji Medical Center, Eulji University School of Medicine, 712, Dongil-ro, Uijeongbu-si 11759, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"investigation","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"Minkyu","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, Uijeongbu Eulji Medical Center, Eulji University School of Medicine, 712, Dongil-ro, Uijeongbu-si 11759, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"investigation","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"Min-Gwan","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Radiological Science, College of Health Science, Eulji University, 553, Sanseong-daero, Sujeong-gu, Seongnam-si 13135, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"software","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4103-5704","authenticated-orcid":false,"given":"Chanrok","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Radiological Science, College of Health Science, Eulji University, 553, Sanseong-daero, Sujeong-gu, Seongnam-si 13135, Republic of 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