An integrated characterization of serological, pathological, and functional events in doxorubicin-induced cardiotoxicity.

Many efficacious cancer treatments cause significant cardiac morbidity, yet biomarkers or functional indices of early damage, which would allow monitoring and intervention, are lacking. In this study, we have utilized a rat model of progressive doxorubicin (DOX)-induced cardiomyopathy, applying multiple approaches, including cardiac magnetic resonance imaging (MRI), to provide the most comprehensive characterization to date of the timecourse of serological, pathological, and functional events underlying this toxicity. Hannover Wistar rats were dosed with 1.25 mg/kg DOX weekly for 8 weeks followed by a 4 week off-dosing "recovery" period. Electron microscopy of the myocardium revealed subcellular degeneration and marked mitochondrial changes after a single dose. Histopathological analysis revealed progressive cardiomyocyte degeneration, hypertrophy/cytomegaly, and extensive vacuolation after two doses. Extensive replacement fibrosis (quantified by Sirius red staining) developed during the off-dosing period. Functional indices assessed by cardiac MRI (including left ventricular ejection fraction (LVEF), cardiac output, and E/A ratio) declined progressively, reaching statistical significance after two doses and culminating in "clinical" LV dysfunction by 12 weeks. Significant increases in peak myocardial contrast enhancement and serological cardiac troponin I (cTnI) emerged after eight doses, importantly preceding the LVEF decline to <50%. Troponin I levels positively correlated with delayed and peak gadolinium contrast enhancement, histopathological grading, and diastolic dysfunction. In summary, subcellular cardiomyocyte degeneration was the earliest marker, followed by progressive functional decline and histopathological manifestations. Myocardial contrast enhancement and elevations in cTnI occurred later. However, all indices predated "clinical" LV dysfunction and thus warrant further evaluation as predictive biomarkers.