Dear Editor, I read the article titled “Development of an Innovation Pipeline With Fusion, Digital Planning, and three-Dimensional Printing to Improve Mitral Valve Interventional Care” by Man et al., published in your journal Echocardiography [(Man, 2025)](#ref-0002). This Manuscript presents a novel and technically innovative pipeline that integrates TEE and CT imaging to produce personalized, flexible 3D-printed mitral valve (MV) models for interventional planning. The integration of multimodal imaging with tactile simulation aligns well with current trends in structural heart intervention and surgical education. However, several methodological and design limitations may reduce the generalizability and clinical readiness of the proposed system. The study has a very small sample size, and the retrospective analysis of just three patients, chosen for different MR pathologies, limits statistical validity and generalizability. While small cohorts are acceptable in feasibility studies, the authors‘ conclusions regarding “technology readiness” are premature without broader validation. [(Pate, 2020)](#ref-0003). While the 3D models are promising, the authors do not evaluate any procedural or clinical endpoints, such as surgical decision-making, procedural time, or complications. Without outcome data, the utility of the pipeline in “interventional care” remains in doubt. [(Diment, 2017)](#ref-0001). The study suggests the use of five different software platforms, which would require a large team. In a busy clinical setting, this may hinder workflow efficiency. Therefore, the study should have focused on time, cost, and computational resources in a real-world context. Despite their critiques, the authors did well in presenting their insights and findings regarding innovative modalities for the treatment of MR. This study introduces a meaningful technical advancement but is not yet ready for clinical application. Hence, a major revision is warranted, and future research, ideally in the form of RCTs and cohort studies, should include an increased sample size, correlation with surgical outcomes, and insight into the real-world cost and workforce requirements for the integration of these procedures in the treatment of MR