Prediction of the development of new coronary atherosclerotic plaques with radiomics.

Background: Radiomics is expected to identify imaging features beyond the human eye. We investigated whether radiomics can identify coronary segments that will develop new atherosclerotic plaques on coronary computed tomography angiography (CCTA).

Methods: From a prospective multinational registry of patients with serial CCTA studies at ≥ 2-year intervals, segments without identifiable coronary plaque at baseline were selected and radiomic features were extracted.

Identifying Coronary Artery Calcification Using Chest X-ray Radiographs and Machine Learning: The Role of the Radiomics Score.

Purpose: To evaluate the ability of radiomics score (RS)-based machine learning to identify moderate to severe coronary artery calcium (CAC) on chest x-ray radiographs (CXR).

Materials And Methods: We included 559 patients who underwent a CAC scan with CXR obtained within 6 months and divided them into training (n = 391) and validation (n = 168) cohorts. We extracted radiomic features from annotated cardiac contours in the CXR images and developed an RS through feature selection with the least absolute shrinkage and selection operator regression in the training cohort.

Gefitinib-induced paronychia: response to autologous platelet-rich plasma.

Background: Paronychia has been reported in as many as 10% of patients treated with gefitinib. Although conservative management and treatment with topical or systemic antibiotics are beneficial, no effective method exists for intractable cases. Platelet-rich plasma (PRP)consists of a high concentration of platelets that promote wound healing through chemotaxis, cell proliferation,angiogenesis, and tissue remodeling.