Pathology-validated prevalence and clinical characteristics of coronary medial arterial calcification.

AIMS: Medial arterial calcification (MAC) is well characterized in peripheral arteries, but its pathology-validated prevalence in the coronary circulation remains uncertain. Because intravascular imaging cannot routinely delineate the elastic laminae in advanced atherosclerotic lesions, deep intimal calcification (DIC) accumulating adjacent to the internal elastic lamina (IEL) may fundamentally mimic MAC. This study aimed to determine the strict pathology-validated prevalence of true coronary MAC and morphologically characterize DIC as a potential imaging mimic using a large-scale autopsy registry.

METHODS AND

RESULTS

We evaluated 4508 histologic sections from 327 coronary arteries in 112 autopsy cases. To ensure accurate layer-specific differentiation, the IEL and external elastic lamina were precisely identified using Movat Pentachrome and EVG stains. The cohort was high-risk, featuring 85% cardiac deaths. Pathology-confirmed MAC was remarkably rare, present in only 1.0% of sections and 3.6% of patients. Strikingly, coronary MAC presented in two distinct morphological phenotypes. Three patients exhibited nodular MAC strictly co-existing with intimal nodules in severely stenotic segments, representing secondary mechanical protrusion from the intima. Conversely, only one patient exhibited isolated medial sheet calcification with minimal intimal narrowing, representing true primary medial disease. Notably, the IEL-overriding pattern occasionally seen in peripheral MAC was entirely absent. Meanwhile, DIC was significantly more prevalent, identified in 35.7% of patients.

CONCLUSION

True primary coronary MAC is exceptionally rare. Because dense acoustic shadowing clinically conceals secondary medial nodular protrusions in vivo, imaging-reported coronary 'MAC' almost exclusively represents DIC. Recognizing three distinct phenotypes-DIC, secondary nodular protrusion, and the rare true Mönckeberg-type MAC-is essential to accurately interpret clinical imaging findings.