{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T10:10:44Z","timestamp":1788775844909,"version":"build-2803163510"},"reference-count":36,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T00:00:00Z","timestamp":1788652800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"ClariPi","award":["CLARIPI\\SRA UMMC 22-U-065"],"award-info":[{"award-number":["CLARIPI\\SRA UMMC 22-U-065"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Objective: To evaluate the feasibility of simulated ultra-low-dose CT (ULD-CT) enhanced with deep learning denoising (DLD) for detecting pelvic and hip fractures. Method: This Institutional Review Board-approved retrospective study was performed at a multisite, single academic institution between October 2020 and May 2021, including 30 full-dose CT (CTfull) exams of acute pelvic and hip trauma (10 normal, 10 \u201ceasy,\u201d 10 \u201chard\u201d cases by fracture conspicuity). Simulated low-dose CT images at 10% (CT10sim) and 5% (CT5sim) radiation dose were generated using a noise model-based algorithm and reconstructed from full-dose CT datasets. A commercial deep learning denoising algorithm enhanced these images, resulting in denoised low-dose CTs (CT10dld and CT5dld) for evaluation. The 90 resulting CT cases were reviewed independently for diagnostic accuracy, confidence, sufficiency, and imaging quality. Result: Diagnostic accuracy was similar across CT modalities overall (CTfull 80.8% [72.9, 86.9]; CT10dld 78.3% [70.1, 84.8]; CT5dld 77.5% [69.2, 84.1]) and within the easy and normal strata; in hard cases, accuracy was numerically lower for CT10dld (45.0%) and CT5dld (42.5%) than for CTfull (57.5%). Diagnostic sufficiency was similarly high across modalities (CTfull 91.7%, CT10dld 87.5%, CT5dld 88.3%). CT full was rated highest in perceived image quality across all strata (mean 4.21 \u00b1 0.83 overall vs. 3.47 \u00b1 0.97 for CT10dld and 3.23 \u00b1 0.98 for CT5dld) and in diagnostic confidence (mean 4.61 \u00b1 0.63 vs. 4.45 \u00b1 0.71 and 4.41 \u00b1 0.72, respectively), though neither translated into a corresponding drop in diagnostic accuracy overall. Inter-reader agreement was highest between MSK radiologists, reaching substantial agreement on CT10dld (\u03ba = 0.760) and CT5dld (\u03ba = 0.672). Conclusions: DLD-enhanced ULD-CT showed diagnostic accuracy and sufficiency similar to full-dose CT for pelvic and hip fracture detection, at a fraction of the radiation dose, though full-dose CT was rated higher in perceived image quality and diagnostic confidence and outperformed denoised low-dose CT numerically in hard cases. Full-dose CT remains the preferred modality for complex and high-energy trauma, while denoised low-dose CT modalities represent a promising option for straightforward presentations where radiation minimization is a priority.<\/jats:p>","DOI":"10.3390\/diagnostics16172862","type":"journal-article","created":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T09:23:37Z","timestamp":1788773017000},"page":"2862","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Feasibility of AI-Denoised Ultra-Low-Dose CT for Detection of Acute Pelvic and Hip Fractures: A Pilot Multi-Reader Study"],"prefix":"10.3390","volume":"16","author":[{"given":"Daniel","family":"Nguyen","sequence":"first","affiliation":[{"name":"Department of Medicine, University of Massachusetts Chan Medical School, Worcester, 01655 MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3290-3143","authenticated-orcid":false,"given":"Tina","family":"Shiang","sequence":"additional","affiliation":[{"name":"Department of Radiology, University of Massachusetts Chan Medical School, Worcester, 01655 MA, USA"},{"name":"Department of Radiology, Massachusetts General Hospital, Boston, 02114 MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"}]},{"given":"Connie","family":"Ge","sequence":"additional","affiliation":[{"name":"Department of Medicine, University of Massachusetts Chan Medical School, Worcester, 01655 MA, USA"},{"name":"Department of Radiology, Vanderbilt University, Nashville, 37235 TN, USA"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"}]},{"given":"George","family":"Watts","sequence":"additional","affiliation":[{"name":"Department of Radiology, University of Massachusetts Chan Medical School, Worcester, 01655 MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"investigation","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"Christopher","family":"Sereni","sequence":"additional","affiliation":[{"name":"Department of Radiology, University of Massachusetts Chan Medical School, Worcester, 01655 MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"investigation","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"David","family":"Radcliffe","sequence":"additional","affiliation":[{"name":"Department of Radiology, University of Massachusetts Chan Medical School, Worcester, 01655 MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"investigation","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1231-8935","authenticated-orcid":false,"given":"Hemang","family":"Kotecha","sequence":"additional","affiliation":[{"name":"Department of Radiology, University of Massachusetts Chan Medical School, Worcester, 01655 MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"investigation","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"Gabriela Santos","family":"Nunez","sequence":"additional","affiliation":[{"name":"Department of Radiology, University of Massachusetts Chan Medical School, Worcester, 01655 MA, USA"},{"name":"VRad, Minneapolis, 55435 MN, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Young H.","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Radiology, University of Massachusetts Chan Medical School, Worcester, 01655 MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2119","DOI":"10.1016\/j.injury.2017.07.027","article-title":"What Injuries Should We Expect in the Emergency Room?","volume":"48","author":"Voth","year":"2017","journal-title":"Injury"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1177\/08982643221132450","article-title":"Hip Fracture-Related Emergency Department Visits, Hospitalizations and Deaths by Mechanism of Injury among Adults Aged 65 and Older, United States 2019","volume":"35","author":"Moreland","year":"2023","journal-title":"J. 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