A new automatic algorithm for quantification of myocardial infarction imaged by late gadolinium enhancement cardiovascular magnetic resonance: experimental validation and comparison to expert delineations in multi-center, multi-vendor patient data

Abstract

BackgroundLate gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) using magnitude inversion recovery (IR) or phase sensitive inversion recovery (PSIR) has become clinical standard for assessment of myocardial infarction (MI). However, there is no clinical standard for quantification of MI even though multiple methods have been proposed. Simple thresholds have yielded varying results and advanced algorithms have only been validated in single center studies. Therefore, the aim of this study was to develop an automatic algorithm for MI quantification in IR and PSIR LGE images and to validate the new algorithm experimentally and compare it to expert delineations in multi-center, multi-vendor patient data.MethodsThe new automatic algorithm, EWA (Expectation Maximization, weighted intensity, a priori information), was implemented using an intensity threshold by Expectation Maximization (EM) and a weighted summation to account for partial volume effects.The EWA algorithm was validated in-vivo against triphenyltetrazolium-chloride (TTC) staining (n = 7 pigs with paired IR and PSIR images) and against ex-vivo high resolution T1-weighted images (n = 23 IR and n = 13 PSIR images). The EWA algorithm was also compared to expert delineation in 124 patients from multi-center, multi-vendor clinical trials 2–6 days following first time ST-elevation myocardial infarction (STEMI) treated with percutaneous coronary intervention (PCI) (n = 124 IR and n = 49 PSIR images).ResultsInfarct size by the EWA algorithm in vivo in pigs showed a bias to ex-vivo TTC of −1 ± 4%LVM (R = 0.84) in IR and −2 ± 3%LVM (R = 0.92) in PSIR images and a bias to ex-vivo T1-weighted images of 0 ± 4%LVM (R = 0.94) in IR and 0 ± 5%LVM (R = 0.79) in PSIR images. In multi-center patient studies, infarct size by the EWA algorithm showed a bias to expert delineation of −2 ± 6 %LVM (R = 0.81) in IR images (n = 124) and 0 ± 5%LVM (R = 0.89) in PSIR images (n = 49).ConclusionsThe EWA algorithm was validated experimentally and in patient data with a low bias in both IR and PSIR LGE images. Thus, the use of EM and a weighted intensity as in the EWA algorithm, may serve as a clinical standard for the quantification of myocardial infarction in LGE CMR images.Clinical trial registrationCHILL-MI: NCT01379261. MITOCARE: NCT01374321.

Longitudinal left ventricular function is globally depressed within a week of STEMI

“…The reproducibility of manual interactions in the patient population of CHILL-MI and MITOCARE have been shown to be very high (bias 1 AE 1%, r = 0Á99) and the bias of infarct quantification versus the reference standard of ex. vivo TTC is very low (À1 AE 1%, r = 0Á98) (Engblom et al, 2016).…”

“…The SV generated by the AVPD was calculated as LV AVPD (cm) multiplied by the mean of the largest LV short-axis epicardial area (cm 2 ) within the AVPD range as previously described (Carlsson et al, 2007). Infarct size was quantified in LGE images after manual delineation of the endocardial and epicardial borders using a validated automatic algorithm with manual corrections as previously described (Engblom et al, 2016) (Erlinge et al, 2014;Atar et al, 2015). Phase-sensitive inversion recovery LGE was used for infarct quantification in 28% of the patients.…”

Cardiovascular Magnetic Resonance to Predict Appropriate Implantable Cardioverter Defibrillator Therapy in Ischemic and Nonischemic Cardiomyopathy Patients Using Late Gadolinium Enhancement Border Zone

“…The EWA and WBZ algorithms have also been validated in vivo and ex vivo for infarct size and does not require user input to determine SI thresholds in remote myocardium [24,25]. …”

“…a newly developed semi-automatic quantitative weighted border zone algorithm based on E xpectation Maximization for intensity classification resulting in a volume with hyperenhancement (total LGE), w eighted summation of infarct size to account for partial volume effects inside the hyperenhanced volume according to pixel intensity and a priori information utilized for pre and post processing (EWA) [25]. …”

“…In 2008 our group presented a semi-automatic algorithm based on a pixel weighting approach for infarct/fibrosis quantification that accounts for partial volume effects and has the potential to quantify LGE border zone [24]. Recently, we developed and validated a new semi-automatic algorithm for infarct/fibrosis and LGE border zone analysis that also incorporates intensity thresholding by Expectation Maximization [25]. The semi-automatic methods require less user input and are more automated than current approaches for determining LGE border zone.…”