dc.contributor.author |
Szilveszter, Bálint |
|
dc.contributor.author |
Kolossváry, Márton József |
|
dc.contributor.author |
Karády, Júlia |
|
dc.contributor.author |
Jermendy, Ádám Levente |
|
dc.contributor.author |
Károlyi, Mihály |
|
dc.contributor.author |
Panajotu, Alexisz |
|
dc.contributor.author |
Bagyura, Zsolt |
|
dc.contributor.author |
Vecsey-Nagy M |
|
dc.contributor.author |
Cury RC |
|
dc.contributor.author |
Leipsic JA |
|
dc.contributor.author |
Merkely, Béla Péter |
|
dc.contributor.author |
Maurovich-Horvat, Pál |
|
dc.date.accessioned |
2018-08-10T08:53:54Z |
|
dc.date.available |
2018-08-10T08:53:54Z |
|
dc.date.issued |
2017 |
|
dc.identifier |
85029630923 |
|
dc.identifier.citation |
pagination=449-454;
journalVolume=11;
journalIssueNumber=6;
journalTitle=JOURNAL OF CARDIOVASCULAR COMPUTED TOMOGRAPHY; |
|
dc.identifier.uri |
http://repo.lib.semmelweis.hu//handle/123456789/5779 |
|
dc.identifier.uri |
doi:10.1016/j.jcct.2017.09.008 |
|
dc.description.abstract |
BACKGROUND: Structured reporting in cardiac imaging is strongly encouraged to improve quality through consistency. The Coronary Artery Disease - Reporting and Data System (CAD-RADS) was recently introduced to facilitate interdisciplinary communication of coronary CT angiography (CTA) results. We aimed to assess the agreement between manual and automated CAD-RADS classification using a structured reporting platform. METHODS: Five readers prospectively interpreted 500 coronary CT angiographies using a structured reporting platform that automatically calculates the CAD-RADS score based on stenosis and plaque parameters manually entered by the reader. In addition, all readers manually assessed CAD-RADS blinded to the automatically derived results, which was used as the reference standard. We evaluated factors influencing reader performance including CAD-RADS training, clinical load, time of the day and level of expertise. RESULTS: Total agreement between manual and automated classification was 80.2%. Agreement in stenosis categories was 86.7%, whereas the agreement in modifiers was 95.8% for "N", 96.8% for "S", 95.6% for "V" and 99.4% for "G". Agreement for V improved after CAD-RADS training (p = 0.047). Time of the day and clinical load did not influence reader performance (p > 0.05 both). Less experienced readers had a higher total agreement as compared to more experienced readers (87.0% vs 78.0%, respectively; p = 0.011). CONCLUSIONS: Even though automated CAD-RADS classification uses data filled in by the readers, it outperforms manual classification by preventing human errors. Structured reporting platforms with automated calculation of the CAD-RADS score might improve data quality and support standardization of clinical decision making. |
|
dc.relation.ispartof |
urn:issn:1934-5925 |
|
dc.title |
Structured reporting platform improves CAD-RADS assessment. |
|
dc.type |
Journal Article |
|
dc.date.updated |
2018-07-13T07:20:42Z |
|
dc.language.rfc3066 |
en |
|
dc.identifier.mtmt |
3270858 |
|
dc.identifier.wos |
WOS:000416978600006 |
|
dc.identifier.pubmed |
28941999 |
|
dc.contributor.department |
SE/AOK/K/VAROSMAJOR_SZÍVÉRGYÓGY/KARDI KZP_KARDIO-T/MTA-SE Lendület Kardiovaszkuláris Képalkotó Kutatócsoport [2017.10.31] |
|
dc.contributor.institution |
Semmelweis Egyetem |
|
dc.mtmt.swordnote |
Merkely B and Maurovich-Horvat P contributed equally to this work. |
|