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Diagnostic accuracy of an artificial neural network compared with statistical quantitation of myocardial perfusion images: a Japanese multicenter study.

Abstract：

PURPOSE:Artificial neural networks (ANN) might help to diagnose coronary artery disease. This study aimed to determine whether the diagnostic accuracy of an ANN-based diagnostic system and conventional quantitation are comparable. METHODS:The ANN was trained to classify potentially abnormal areas as true or false based on the nuclear cardiology expert interpretation of 1001 gated stress/rest 99mTc-MIBI images at 12 hospitals. The diagnostic accuracy of the ANN was compared with 364 expert interpretations that served as the gold standard of abnormality for the validation study. Conventional summed stress/rest/difference scores (SSS/SRS/SDS) were calculated and compared with receiver operating characteristics (ROC) analysis. RESULTS:The ANN generated a better area under the ROC curves (AUC) than SSS (0.92 vs. 0.82, p < 0.0001), indicating better identification of stress defects. The ANN also generated a better AUC than SDS (0.90 vs. 0.75, p < 0.0001) for stress-induced ischemia. The AUC for patients with old myocardial infarction based on rest defects was 0.97 (0.91 for SRS, p = 0.0061), and that for patients with and without a history of revascularization based on stress defects was 0.94 and 0.90 (p = 0.0055 and p < 0.0001 vs. SSS, respectively). The SSS/SRS/SDS steeply increased when ANN values (probability of abnormality) were >0.80. CONCLUSION:The ANN was diagnostically accurate in various clinical settings, including that of patients with previous myocardial infarction and coronary revascularization. The ANN could help to diagnose coronary artery disease.

journal_name

Eur J Nucl Med Mol Imaging

journal_title

European journal of nuclear medicine and molecular imaging

authors

Nakajima K,Kudo T,Nakata T,Kiso K,Kasai T,Taniguchi Y,Matsuo S,Momose M,Nakagawa M,Sarai M,Hida S,Tanaka H,Yokoyama K,Okuda K,Edenbrandt L

doi

10.1007/s00259-017-3834-x

subject

Has Abstract

pub_date

2017-12-01 00:00:00

pages

2280-2289

issue

eissn

1619-7070

issn

1619-7089

pii

10.1007/s00259-017-3834-x

journal_volume

pub_type

杂志文章,多中心研究

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Diagnostic accuracy of an artificial neural network compared with statistical quantitation of myocardial perfusion images: a Japanese multicenter study.