Echocardiography and vascular ultrasound are essential for comprehensive cardiovascular assessment, yet manual evaluation and writing reports are labor-intensive, time-consuming, and require expertise from both cardiology and vascular surgery departments. Current automated report generation systems mainly focus on X-ray or CT, often neglecting echocardiographic modalities and critical quantitative parameters like aortic diameter and main pulmonary artery diameter, limiting their clinical utility. Moreover, the interdependence between cardiac and peripheral vascular health necessitates cross-departmental insights, which existing methods fail to incorporate. To address these limitations, we first propose the vision-language framework named the Echo-Cardiac-Vascular (ECV) framework, for joint cardiac and vascular ultrasound report generation and parameter measurements. ECV introduces a Mixture-of-Experts vision encoder tailored for distinct ultrasound subtypes, a structured parameter measurement module for accurate quantification, and a cross-modal attention mechanism that generates interpretable, multimodal diagnostic reports. Our framework, trained on 11,276 paired records that achieves high accuracy and fast generation speed, significantly improving diagnostic efficiency, consistency, and cross-disciplinary clinical applicability. Our model and codes will be publicly available.