1. |
- Pellegrino, T, et al.
(författare)
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Moderated Poster Session 3 : Monday 4 May 2015, 10
- 2015
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Ingår i: European Heart Journal Cardiovascular Imaging. - : Oxford University Press (OUP). - 2047-2404 .- 2047-2412. ; 16 Suppl 1
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Tidskriftsartikel (refereegranskat)
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2. |
- Nakajima, K., et al.
(författare)
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Artificial neural network retrained to detect myocardial ischemia using a Japanese multicenter database
- 2018
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Ingår i: Annals of Nuclear Medicine. - : Springer Science and Business Media LLC. - 0914-7187 .- 1864-6433. ; 32:5, s. 303-310
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Tidskriftsartikel (refereegranskat)abstract
- An artificial neural network (ANN) has been applied to detect myocardial perfusion defects and ischemia. The present study compares the diagnostic accuracy of a more recent ANN version (1.1) with the initial version 1.0. We examined 106 patients (age, 77 +/- 10 years) with coronary angiographic findings, comprising multi-vessel disease ( 50% stenosis) (52%) or old myocardial infarction (27%), or who had undergone coronary revascularization (30%). The ANN versions 1.0 and 1.1 were trained in Sweden (n = 1051) and Japan (n = 1001), respectively, using Tc-99m-methoxyisobutylisonitrile myocardial perfusion images. The ANN probabilities (from 0.0 to 1.0) of stress defects and ischemia were calculated in candidate regions of abnormalities. The diagnostic accuracy was compared using receiver-operating characteristics (ROC) analysis and the calculated area under the ROC curve (AUC) using expert interpretation as the gold standard. Although the AUC for stress defects was 0.95 and 0.93 (p = 0.27) for versions 1.1 and 1.0, respectively, that for detecting ischemia was significantly improved in version 1.1 (p = 0.0055): AUC 0.96 for version 1.1 (sensitivity 87%, specificity 96%) vs. 0.89 for version 1.0 (sensitivity 78%, specificity 97%). The improvement in the AUC shown by version 1.1 was also significant for patients with neither coronary revascularization nor old myocardial infarction (p = 0.0093): AUC = 0.98 for version 1.1 (sensitivity 88%, specificity 100%) and 0.88 for version 1.0 (sensitivity 76%, specificity 100%). Intermediate ANN probability between 0.1 and 0.7 was more often calculated by version 1.1 compared with version 1.0, which contributed to the improved diagnostic accuracy. The diagnostic accuracy of the new version was also improved in patients with either single-vessel disease or no stenosis (n = 47; AUC, 0.81 vs. 0.66 vs. p = 0.0060) when coronary stenosis was used as a gold standard. The diagnostic ability of the ANN version 1.1 was improved by retraining using the Japanese database, particularly for identifying ischemia.
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3. |
- Nakajima, K., et al.
(författare)
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Diagnostic Performance of Artificial Neural Network for Detecting Ischemia in Myocardial Perfusion Imaging
- 2015
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Ingår i: Circulation Journal. - 1346-9843. ; 79:7, s. 1549-1556
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Tidskriftsartikel (refereegranskat)abstract
- Background: The purpose of this study was to apply an artificial neural network (ANN) in patients with coronary artery disease (CAD) and to characterize its diagnostic ability compared with conventional visual and quantitative methods in myocardial perfusion imaging (MPI). Methods and Results: A total of 106 patients with CAD were studied with MPI, including multiple vessel disease (49%), history of myocardial infarction (27%) and coronary intervention (30%). The ANN detected abnormal areas with a probability of stress defect and ischemia. The consensus diagnosis based on expert interpretation and coronary stenosis was used as the gold standard. The left ventricular ANN value was higher in the stress-defect group than in the no-defect group (0.92 +/- 0.11 vs. 0.25 +/- 0.32, P<0.0001) and higher in the ischemia group than in the noischemia group (0.70 +/- 0.40 vs. 0.004 +/- 0.032, P<0.0001). Receiver-operating characteristics curve analysis showed comparable diagnostic accuracy between ANN and the scoring methods (0.971 vs. 0.980 for stress defect, and 0.882 vs. 0.937 for ischemia, both P=NS). The relationship between the ANN and defect scores was non-linear, with the ANN rapidly increased in ranges of summed stress score of 2-7 and summed defect score of 2-4. Conclusions: Although the diagnostic ability of ANN was similar to that of conventional scoring methods, the ANN could provide a different viewpoint for judging abnormality, and thus is a promising method for evaluating abnormality in MPI.
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4. |
- Nakajima, K., et al.
(författare)
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Improved quantification of small hearts for gated myocardial perfusion imaging
- 2013
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Ingår i: European Journal of Nuclear Medicine and Molecular Imaging. - : Springer Science and Business Media LLC. - 1619-7070 .- 1619-7089. ; 40:8, s. 1163-1170
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Tidskriftsartikel (refereegranskat)abstract
- In patients with a small heart, defined as an end-systolic volume (ESV) of a parts per thousand currency sign20 mL calculated using the Quantitative Gated SPECT (QGS) program, underestimation of ESV and overestimation of ejection fraction (EF) using gated myocardial perfusion imaging are considered errors caused by inappropriate delineation of the left ventricle (LV). The aim of this study was to develop a new method for delineation of the LV and to evaluate it in studies using a digital phantom, normal subjects and patients. The active shape-based method for LV delineation, EXINI heart (ExH), was adjusted to more accurately process small hearts. In small hearts, due to the partial volume effect and the short distance to the opposite ventricular wall, the endocardial and the epicardial surfaces are shifted in the epicardial direction depending on the midventricular volume. The adjusted method was evaluated using digital XCAT phantoms with Monte Carlo simulation (8 virtual patients), a Japanese multicentre normal database (69 patients) and consecutive Japanese patients (116 patients). The LV volumes, EF and diastolic parameters derived from ExH and QGS were compared. The digital phantom studies showed a mean ESV of 87 % +/- 9 % of the true volume calculated using ExH and 22 % +/- 18 % calculated using QGS. In the normal database, QGS gave higher EFs in women than in men (71.4 +/- 6.0 % vs. 67.2 +/- 6.0 %, p = 0.0058), but ExH gave comparable EFs (70.7 +/- 4.9 % and 71.4 +/- 5 % in men and women, respectively, p = ns). QGS gave higher EFs in subjects with a small heart than in those with a normal-sized heart (74.5 +/- 5.1 % vs. 66.1 +/- 4.9 %), but ExH gave comparable values (70.0 +/- 5.9 % vs. 71.6 +/- 4.2 %, respectively, p = ns). In consecutive patients, the average EFs with QGS in patients with ESV > 20 mL, 11-20 mL and a parts per thousand currency sign10 mL were 57.9 %, 71.9 % and 83.2 %, but with ExH the differences among these groups were smaller (65.2 %, 67.8 % and 71.5 %, respectively). The volume-dependent edge correction algorithm was able to effectively reduce the effects on ESV and EF of a small heart. The uniform normal values might be applicable to both men and women and to both small and normal-sized hearts.
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5. |
- Yoneyama, H., et al.
(författare)
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Reducing the small-heart effect in pediatric gated myocardial perfusion single-photon emission computed tomography
- 2017
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Ingår i: Journal of Nuclear Cardiology. - : Springer Science and Business Media LLC. - 1071-3581 .- 1532-6551. ; 24:4, s. 1378-1388
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Tidskriftsartikel (refereegranskat)abstract
- Background. We compared two reconstruction algorisms and two cardiac functional evaluation software programs in terms of their accuracy for estimating ejection fraction (EF) of small hearts (SH). Methods. The study group consisted of 66 pediatric patients. Data were reconstructed using a filtered back projection (FBP) method without the resolution correction (RC) and an iterative method based on an ordered subset expectation maximization (OSEM) algorithm with the RC. EF was evaluated using two software programs of quantitative gated single-photon emission computed tomography (SPECT) (QGS) and cardioREPO. We compared the EF of gated myocardial perfusion SPECT to echocardiographic measurement (Echo). Results. Forty-eight of 66 patients had an end-systolic volume < 20 mL which was used as the criterion for being included in the SH group, and the SH effect led to an overestimation of EF. While significant differences were observed between Echo (66.9 +/- 5.0%) and QGS-FBP without RC (76.9 +/- 8.4%, P < .0001), QGS-OSEM with RC (76.6 +/- 8.6%, P < .0001), and cardioREPO-FBP without RC (72.1 +/- 10.0%, P = .0011), no significant difference was observed between Echo and cardioREPO-OSEM with RC (67.4 +/- 6.1%) in SH group. Conclusions. In pediatric gated myocardial perfusion SPECT, the SH effect can be significantly reduced when an OSEM algorithm is used with RC in combination with the specific cardioREPO algorithm.
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