Background: Cardiac CT with late iodine enhancement (LIE-CT) may characterize the scarred myocardium, but the role of readers’ experience and scar pattern on LIE-CT diagnostic performance is unknown. Aim was to assess the diagnostic performance of LIE-CT according to readers’ experience, scar pattern and contrast-to-noise ratio (CNR) using late gadolinium enhancement MRI (LGE-MRI) as reference. Methods: LIE-CT and LGE-MRI images of 40 consecutive patients were analyzed. Two readers with different experience (8 and 2 years) independently analyzed LIE-CT images defining the presence/absence of scar and scar CNR, segmental involvement, transmural pattern and scar etiology. The same parameters were extracted from LGE-MRI by two expert readers in consensus, blinded to the LIE-CT results. Results: Scars were identified at LGE-MRI in 29/40 patients and 141/680 segments. Scar burden at LIE-CT versus LGE-MRI correlated better for the most experienced reader than for the least experienced one (ρ = 0.954 and ρ = 0.797, p < 0.001). The most experienced reader missed scars in 2 patients and in 21/141 segments; the least experienced in 5 patients and 53/141 segments. The most experienced reader showed higher accuracy and sensitivity compared to the least experienced in per-patient (accuracy: 95% vs. 88%; sensitivity: 93% vs. 83%) and per-segment analysis (accuracy: 96% vs. 92%; sensitivity: 85% vs. 62%). Specificity was excellent (100% per-patient, 99% per-segment,) regardless of readers’ experience. Missed scars had non-ischemic pattern, low scar burden (< 6%) and lower CNR compared to ischemic scars (2.33 vs. 3.54, p = 0.005). Conclusion: LIE-CT represents an alternative to LGE-MRI, although the impact of readers’ experience on sensitivity for small non-ischemic scars should be considered.

Late iodine enhancement cardiac computed tomography for detection of myocardial scars: impact of experience in the clinical practice

Palmisano A.;Vignale D.;Del Maschio A.;De Cobelli F.;Esposito A.
2020-01-01

Abstract

Background: Cardiac CT with late iodine enhancement (LIE-CT) may characterize the scarred myocardium, but the role of readers’ experience and scar pattern on LIE-CT diagnostic performance is unknown. Aim was to assess the diagnostic performance of LIE-CT according to readers’ experience, scar pattern and contrast-to-noise ratio (CNR) using late gadolinium enhancement MRI (LGE-MRI) as reference. Methods: LIE-CT and LGE-MRI images of 40 consecutive patients were analyzed. Two readers with different experience (8 and 2 years) independently analyzed LIE-CT images defining the presence/absence of scar and scar CNR, segmental involvement, transmural pattern and scar etiology. The same parameters were extracted from LGE-MRI by two expert readers in consensus, blinded to the LIE-CT results. Results: Scars were identified at LGE-MRI in 29/40 patients and 141/680 segments. Scar burden at LIE-CT versus LGE-MRI correlated better for the most experienced reader than for the least experienced one (ρ = 0.954 and ρ = 0.797, p < 0.001). The most experienced reader missed scars in 2 patients and in 21/141 segments; the least experienced in 5 patients and 53/141 segments. The most experienced reader showed higher accuracy and sensitivity compared to the least experienced in per-patient (accuracy: 95% vs. 88%; sensitivity: 93% vs. 83%) and per-segment analysis (accuracy: 96% vs. 92%; sensitivity: 85% vs. 62%). Specificity was excellent (100% per-patient, 99% per-segment,) regardless of readers’ experience. Missed scars had non-ischemic pattern, low scar burden (< 6%) and lower CNR compared to ischemic scars (2.33 vs. 3.54, p = 0.005). Conclusion: LIE-CT represents an alternative to LGE-MRI, although the impact of readers’ experience on sensitivity for small non-ischemic scars should be considered.
2020
Computed tomography; Late iodine enhancement; Myocardium; Scar; Cardiac-Gated Imaging Techniques; Cicatrix; Contrast Media; Female; Humans; Iohexol; Magnetic Resonance Imaging; Male; Middle Aged; Myocardium; Organometallic Compounds; Sensitivity and Specificity; Tomography, X-Ray Computed
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11768/97972
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