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Smartphone imaging repository: a novel method for creating a CT image bank.
Dula, Adrienne N; Milling, Truman J; Johnston, S Claiborne; Aydelotte, Jayson; Peil, Gary W; Robinson, Alec; Asif, Kaiz; Pan, Stephen; Parekh, Sohan; Warach, Steven.
Afiliação
  • Dula AN; Dell Medical School, 1601 Trinity Street, Austin, TX, 78712, USA.
  • Milling TJ; Seton Dell Medical School Stroke Institute, 1601 Trinity, 10th floor, Austin, TX, 78712, USA. tjmilling@yahoo.com.
  • Johnston SC; Dell Medical School, 1601 Trinity Street, Austin, TX, 78712, USA.
  • Aydelotte J; RNDS, 1201 W. Sixth St., Suite D, Austin, TX, 78705, USA.
  • Peil GW; RNDS, 1201 W. Sixth St., Suite D, Austin, TX, 78705, USA.
  • Robinson A; RNDS, 1201 W. Sixth St., Suite D, Austin, TX, 78705, USA.
  • Asif K; Amita Health, 301 N. Madison St., Ste. 300, Joliet, IL, 60435, USA.
  • Pan S; Dell Medical School, 1601 Trinity Street, Austin, TX, 78712, USA.
  • Parekh S; Dell Medical School, 1601 Trinity Street, Austin, TX, 78712, USA.
  • Warach S; Seton Dell Medical School Stroke Institute, 1601 Trinity, 10th floor, Austin, TX, 78712, USA.
Trials ; 24(1): 46, 2023 Jan 20.
Article em En | MEDLINE | ID: mdl-36670459
BACKGROUND: Imaging repositories are commonly attached to ongoing clinical trials, but capturing, transmitting, and storing images can be complicated and labor-intensive. Typical methods include outdated technologies such as compact discs. Electronic file transfer is becoming more common, but even this requires hours of staff time on dedicated computers in the radiology department. METHODS: We describe and test an image capture method using smartphone camera video-derived images of brain computed tomography (CT) scans of traumatic intracranial hemorrhage. The deidentified videos are emailed or uploaded from the emergency department for central adjudication. We selected eight scans, mild moderate, and severe subdural and multicompartmental hematomas and mild and moderate intraparenchymal hematomas. Ten users acquired data using seven different smartphones. We measured the time in seconds it took to capture and send the files. The primary outcomes were hematoma volume measured by ABC/2, Marshall scale, midline shift measurement, image quality by a contrast-to-noise ratio (CNR), and time to capture. A radiologist and an imaging scientist applied the ABC/2 method and calculated the Marshall scale and midline shift on the data acquired on different smartphones and the PACS in a randomized order. We calculate the intraclass correlation coefficient (ICC). We measured image quality by calculating the contrast-to-noise ratio (CNR). We report summary statistics on time to capture in the smartphone group without a comparator. RESULTS: ICC for lesion volume, midline shift, and Marshall score were 0.973 (95% CI 0.931, 0.994), 0.998 (95% CI: 0.996, 0.999), and 0.973 (0.931, 0.994), respectively. Lesion conspicuity was not different among the image types via assessment of CNR using the Friedman test, [Formula: see text] of 24.8, P = < .001, with a small Kendall's W effect size (0.591). Mean (standard deviation) time to capture and email the video was 60.1 (24.3) s. CONCLUSIONS: Typical smartphones may produce video image quality high enough for use in a clinical trial imaging repository. Video capture and transfer takes only seconds, and hematoma volumes, Marshall scales, and image quality measured on the videos did not differ significantly from those calculated on the PACS.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Smartphone / Hematoma Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Smartphone / Hematoma Idioma: En Ano de publicação: 2023 Tipo de documento: Article