Image-derived cardiomegaly biomarker values for 96K chest X-rays in MIMIC-CXR/MIMIC-CXR-JPG

Cardiomegaly is a condition characterized by an abnormal enlargement of the heart, its identification is of paramount importance as it associate with a wide range of cardiac conditions. It is primary identified via the cardiothoracic ratio (CTR), however this metric can be inaccurate as it is affect by external factors such as breathing and body position. Multimodal approaches could mitigate these limitations by integrating non-imaging data, however reliable and explainable integration of imaging and non-imaging data remains a significant challenge. While this database does not directly use multimodal data, it hopes to tackle this challenge by extracting cardiomegaly biomarkers (CTR and cardiopulmonary area ratio) from chest X-rays. Thus encapsulating the relevant imaging information into individual datapoints, allowing easy integration of ‘imaging’ data with non-imaging data for more reliable diagnostic tools. The values were extracted from over 93,000 posterior-anterior MIMIC-CXR scans using detection and segmentation neural networks, tuned for cardiac and pulmonary identification.

心肥大是一种以心脏异常增大为特征的条件，其识别至关重要，因为它与多种心脏疾病相关联。该疾病主要通过心胸比（CTR）进行初步识别，然而，这一指标可能存在不准确之处，因为它受到诸如呼吸和身体姿势等外部因素的影响。多模态方法可以通过整合非成像数据来减轻这些限制，然而，可靠且可解释地整合成像和非成像数据仍然是一项重大挑战。尽管该数据库并未直接使用多模态数据，但希望通过从胸片提取心肥大生物标志物（心胸比和心肺面积比）来应对这一挑战。从而将相关成像信息封装成单个数据点，便于将‘成像’数据与非成像数据进行整合，以构建更加可靠的诊断工具。这些值是从超过93,000例MIMIC-CXR后前位扫描中提取的，使用针对心脏和肺识别进行调优的检测和分割神经网络。