Cardiac MRI of characteristic motion findings in right bundle branch block.

While there have been many descriptions of characteristic motion findings in left bundle branch block (LBBB), there are few published descriptions of such findings in right bundle branch block (RBBB). The purpose of this study was to assess the frequency of particular regional motion findings in cardiac magnetic resonance imaging (CMR) studies of patients with RBBB, compared with normal subjects. We focused on three distinctive motion patterns that can be seen in RBBB during early systole: delayed apex-ward motion of the RV base, "reverse septal flash", and "basal bulge". The presence and relative magnitude of these findings were independently scored by four experienced observers, in 3-chamber and 4-chamber CMR cines, for both normal subjects and patients with RBBB. These motion patterns were found to be strongly associated with the presence of RBBB. While only moderately sensitive, they were quite specific for RBBB, when present. In particular, with ROC analysis, a combined feature set of the findings in the 4-chamber view had an area under the curve of 0.81.This previously undescribed set of RBBB-associated early-systolic regional motion features (delayed apex-ward motion of the RV base, "reverse septal flash", and "basal bulge") is strongly suggestive of RBBB when present, particularly in the 4-chamber view. Although here evaluated with CMR, it is also likely to be associated with RBBB when seen with other cardiac imaging modalities.

Current imaging of PE and emerging techniques: is there a role for artificial intelligence?

Acute pulmonary embolism (PE) is a critical, potentially life-threatening finding on contrast-enhanced cross-sectional chest imaging. Timely and accurate diagnosis of thrombus acuity and extent directly influences patient management, and outcomes. Technical and interpretive pitfalls may present challenges to the radiologist, and by extension, pose nuance in the development and integration of artificial intelligence support tools. This review delineates imaging considerations for diagnosis of acute PE, and rationale, hurdles and applications of artificial intelligence for the PE task.