From: A review of current trends in three-dimensional analysis of left ventricular myocardial strain
Author Year (Ref.#) | n | Patients | Vendor | Feasibility | Remarks | |||||
LV remodeling | ||||||||||
Abate 2012 [64] | 153 | Acute STEMI | GE | 96% (patients) | 1) Regional 3D LS of 11.1% had a > 90% sensitivity and specificity for predicting improvement of LV regional function. 2) 3D GLS had an incremental value over clinical and standard echocardiography parameters for predicting improvement of LVEF (> 5%). | |||||
Li 2012 [65] | 61 | Recent NSTEMI | Toshiba | 80% (patients) | 1) Regional AS > 23% at baseline had a 75% sensitivity and a 76% specificity for predicting improvement of LV regional function. 2) 3D GAS ≤32% after PCI predicted LV adverse remodeling with 86% sensitivity and 68% specificity. | |||||
Sugano 2017 [49] | 71 | Acute STEMI | Toshiba | 96% (patients) | 1) 3D GCS < 23% had an 84% sensitivity and a 74% specificity for predicting LV adverse remodeling. 2) 3D GAS < 31% had an 84% sensitivity and a 58% specificity for predicting LV adverse remodeling. | |||||
Xu 2017 [27] | 110 | Acute STEMI | GE | 91% (patients) | 1) 2D GLS, 3D GLS, 3D GAS, and 3D GRS were independent predictors of LV adverse remodeling. 2) 3D GLS < 12.6% had a 92% sensitivity and a 60% specificity for predicting LV adverse remodeling. 3) 3D GAS < 24.2% had a 92% sensitivity and a 46% specificity for predicting LV adverse remodeling. 4) AUC of 3D GLS (0.82) was significantly higher than that of 2D GLS (0.72), 3D GAS (0.68) and 3D GRS (0.68) for predicting LV adverse remodeling. | |||||
Transmurality of MI | ||||||||||
Hayat 2012 [30] | 25 | OMI | Toshiba | 76% (patients) 96% (segments) | 1) 2D LS and CS and all 3D regional strains were significantly different among segments derived from control subjects, those with non-transmural MI, and those with transmural MI. | |||||
Thorstensen 2013 [33] | 58 | RMI | GE | 62% (patients) 71% (segments) | 1) All 3D regional strains were significantly different among segments with no MI, those with non-transmural MI, and those with transmural MI. 2) All 3D regional strains predicted transmural MI (AUC: 0.73–0.87). 3) 2D GLS had a higher AUC (0.88) for the prediction of transmural MI than 3DGLS (0.73, p < 0.05). | |||||
Zhu 2014 [66] | 26 | AMI | Toshiba | Not described | 1. Regional 3D LS and 3D CS discriminated among segments with no MI, those with non-transmural MI, and those with transmural MI. | |||||
Aly 2016 [67] | 82 | LV dysfunction | Toshiba | 88% (segments) | 1. Regional 3D CS and 3D AS discriminated among segments with no MI, those with non-transmural MI, and those with transmural MI. 2. Regional 3D LS discriminated between segments with non-transmural MI and those with transmural MI. 3. Included 11 patients with non-ischemic LV dysfunction. | |||||
Sugano 2017 [49] | 71 | Acute STEMI | Toshiba | 95% (segments) | 1. Regional 2D CS, 3D CS, and 3D AS discriminated among segments with no MI, those with non-transmural MI, and those with transmural MI. 2. Regional 2D LS failed to differentiate between non-transmural MI and transmural MI. 3D LS failed to differentiate between no MI and non-transmural MI. | |||||
Infarct size | ||||||||||
Author Year (Ref.#) | n | Patients | Vendor | Correlation of infarction size | remarks | |||||
2D GLS | 3D GLS | 3D GCS | 3D GRS | 3DS | 3D AS | |||||
Hayat 2012 [30] | 25 | OMI | Toshiba | NA | r = 0.45 | r = 0.47 | r = 0.07 | r = 0.10 | r = 0.49 | |
Thorstensen 2013 [33] | 58 | RMI | GE | r = 0.67 | r = 0.42 | r = 0.47 | r = 0.48 | r = 0.52 | r = 0.50 | 2DGLS was more closely correlated with infarct size than 3DGLS. |
Zhu 2014 [66] | 26 | AMI | Toshiba | NA | r = 0.86 | r = 0.81 | r = 0.71 | NA | NA | |
Aly 2016 [67] | 71 | ICM | Toshiba | NA | r = 0.29 | r = 0.32 | r = 0.08 | r = 0.29 | r = 0.39 |