Evidence map›Paper›PMID 30155628›Full record

ArticleSkeletal radiology2019

Radiation dose reduction for musculoskeletal computed tomography of the pelvis with preserved image quality.

Elaina Zabak, Hythem Omar, Ethan Boothe, Lulu Tenorio, Jeffrey Guild, Suhny Abbara, Avneesh Chhabra

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Article in Skeletal radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Elaina ZabakUT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390-9178, USA.
Hythem OmarUT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390-9178, USA.
Ethan BootheUT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390-9178, USA. Ethan.Boothe@UTSouthwestern.edu.
Lulu TenorioUT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390-9178, USA.
Jeffrey GuildUT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390-9178, USA.
Suhny AbbaraUT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390-9178, USA.
Avneesh ChhabraUT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390-9178, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo analyze the impact of pelvic computed tomography (CT) technique optimization on estimated dose and subjective and objective image quality. MATERIALS AND

methodsAn institutional review board (IRB)-approved retrospective records review was performed with waived informed consent. Five CT scanners (various manufacturers/models) were standardized to match the lowest dose profile on campus via subjective assessment of clinical images by experienced musculoskeletal radiologists. The lowest dose profile had previously been established through image assessment by experienced musculoskeletal radiologists after a department-wide radiation dose reduction initiative. A consecutive series of 60 pre- and 59 post-optimization bony pelvis CTs were analyzed by two residents, who obtained signal-to-noise ratio for femoral cortex and marrow, gluteus medius muscle, and subcutaneous and visceral fat in a standardized fashion. Two blinded attending radiologists ranked image quality from poor to excellent.

resultsPre- and post-optimization subjects exhibited no difference in gender, age, or BMI (p > 0.2). Mean CT dose index (CTDIvol) and dose-length product (DLP) decreased by approximately 45%, from 39± 14 to 18± 12 mGy (p < 0.0001) and 1,227± 469 to 546± 384 mGy-cm (p < 0.0001). Lower body mass index (BMI) was associated with a larger dose reduction and higher BMI with higher DLP regardless of pre- or post-optimization examination. Inter-observer agreement was 0.64-0.92 for SNR measurements. Cortex SNR increased significantly for both observers (p < 0.02). Although qualitative image quality significantly decreased for one observer (p < 0.01), adequate mean quality (3.3 out of 5) was maintained for both observers.

conclusionSubjective and objective image quality for pelvic CT examination remains adequate, despite a substantially reduced radiation dose.

Indexed as

FemaleHumansMalePelvisRadiation DosageRadiation ProtectionRadiographic Image Interpretation, Computer-AssistedRetrospective StudiesSignal-To-Noise RatioTomography Scanners, X-Ray ComputedTomography, X-Ray ComputedComputed tomographyCTMusculoskeletalPelvisRadiation dose reduction

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.