Extracellular volume fraction imaging can quantitatively characterize myocardial infarction, atypical diffuse fibrosis, and subtle myocardial abnormalities not clinically apparent on LGE images. Taken within the context of prior literature, these subtle ECV abnormalities are consistent with diffuse fibrosis related to age and changes remote from infarction.

Background— Using a resolution 1000-fold higher than prior studies, we studied (1) the degree to which late gadolinium-enhancement (LGE) cardiac magnetic resonance tracks fibrosis from chronic myocardial infarction and (2) the relationship between intermediate signal intensity and partial volume averaging at distinct “smooth” infarct borders versus disorganized mixtures of fibrosis and viable cardiomyocytes. Methods and Results— Sprague-Dawley rats underwent myocardial infarction by coronary ligation. Two months later, rats were euthanized 10 minutes after administration of 0.3 mmol/kg intravenous gadolinium. LGE images ex vivo at 7 T with a 3D gradient echo sequence with 50×50×50 μm voxels were compared with histological sections (Masson trichrome). Planimetered histological and LGE regions of fibrosis correlated well ( y =1.01 x −0.01; R 2 =0.96; P <0.001). In addition, LGE images routinely detected clefts of viable cardiomyocytes 2 to 4 cells thick that separated bands of fibrous tissue. Although LGE clearly detected disorganized mixtures of fibrosis and viable cardiomyocytes characterized by intermediate signal intensity voxels, the percentage of apparent intermediate signal intensity myocardium increased significantly ( P <0.01) when image resolution was degraded to resemble clinical resolution consistent with significant partial volume averaging. Conclusions— These data provide important validation of LGE at nearly the cellular level for detection of fibrosis after myocardial infarction. Although LGE can detect heterogeneous patches of fibrosis and viable cardiomyocytes as patches of intermediate signal intensity, the percentage of intermediate signal intensity voxels is resolution dependent. Thus, at clinical resolutions, distinguishing the peri-infarct border zone from partial volume averaging with LGE is challenging.

Purpose: To develop a computer algorithm to measure myocardial infarct size in gadolinium-enhanced magnetic resonance (MR) imaging and to validate this method using a canine histopathological reference. Materials and Methods:Delayed enhancement MR was performed in 11 dogs with myocardial infarction (MI) determined by triphenyltetrazolium chloride (TTC). Infarct size on in vivo and ex vivo images was measured by a computer algorithm based on automated feature analysis and combined thresholding (FACT). For comparison, infarct size by human manual contouring and simple intensity thresholding (based on two standard deviation [2SD] and full width at half maximum [FWHM]) were studied.Results: Both in vivo and ex vivo MR infarct size measured by the FACT algorithm correlated well with TTC (R ϭ 0.95-0.97) and showed no significant bias on Bland Altman analysis (P ϭ not significant). Despite similar correlations (R ϭ 0.91-0.97), human manual contouring overestimated in vivo MR infarct size by 5.4% of the left ventricular (LV) area (equivalent to 55.1% of the MI area) vs. TTC (P Ͻ 0.001). Infarct size measured by simple intensity thresholdings was less accurate than the proposed algorithm (P Ͻ 0.001 and P ϭ 0.007). Conclusion:The FACT algorithm accurately measured MI size on delayed enhancement MR imaging in vivo and ex vivo. The FACT algorithm was also more accurate than human manual contouring and simple intensity thresholding approaches.