Assessing Quantitative Parenchymal Features at Baseline Dynamic Contrast-enhanced MRI and Cancer Occurrence in Women with Extremely Dense Breasts.

Background Automated identification of quantitative breast parenchymal enhancement features on dynamic contrast-enhanced (DCE) MRI scans could provide added value in assessment of breast cancer risk in women with extremely dense breasts. Purpose To automatically identify quantitative properties of the breast parenchyma on baseline DCE MRI scans and assess their association with breast cancer occurrence in women with extremely dense breasts. Materials and Methods This study represents a secondary analysis of the Dense Tissue and Early Breast Neoplasm Screening trial.

Validation of Combined Deep Learning Triaging and Computer-Aided Diagnosis in 2901 Breast MRI Examinations From the Second Screening Round of the Dense Tissue and Early Breast Neoplasm Screening Trial.

Objectives: Computer-aided triaging (CAT) and computer-aided diagnosis (CAD) of screening breast magnetic resonance imaging have shown potential to reduce the workload of radiologists in the context of dismissing normal breast scans and dismissing benign disease in women with extremely dense breasts. The aim of this study was to validate the potential of integrating CAT and CAD to reduce workload and workup on benign lesions in the second screening round of the DENSE trial, without missing cancer.

Methods: We included 2901 breast magnetic resonance imaging scans, obtained from 8 hospitals in the Netherlands.

Relationship between 3D Morphologic Change and 2D and 3D Growth of Unruptured Intracranial Aneurysms.

Background And Purpose: Untreated unruptured intracranial aneurysms are usually followed radiologically to detect aneurysm growth, which is associated with increased rupture risk. The ideal aneurysm size cutoff for defining growth remains unclear and also whether change in morphology should be part of the definition. We investigated the relationship between change in aneurysm size and 3D quantified morphologic changes during follow-up.

Deep Learning for Automated Triaging of 4581 Breast MRI Examinations from the DENSE Trial.

Background Supplemental screening with MRI has proved beneficial in women with extremely dense breasts. Most MRI examinations show normal anatomic and physiologic variation that may not require radiologic review. Thus, ways to triage these normal MRI examinations to reduce radiologist workload are needed.

Reliability and Agreement of 2D and 3D Measurements on MRAs for Growth Assessment of Unruptured Intracranial Aneurysms.

Background And Purpose: Reliable and reproducible measurement of unruptured intracranial aneurysm growth is important for unruptured intracranial aneurysm rupture risk assessment. This study aimed to compare the reliability and reproducibility of 2D and 3D growth measurements of unruptured intracranial aneurysms.

Materials And Methods: 2D height, width, and neck and 3D volume measurements of unruptured intracranial aneurysms on baseline and follow-up TOF-MRAs were performed by two observers.

Toward Computer-Assisted Triaging of Magnetic Resonance Imaging-Guided Biopsy in Preoperative Breast Cancer Patients.

Objectives: Incidental MR-detected breast lesions (ie, additional lesions to the index cancer) pose challenges in the preoperative workup of patients with early breast cancer. We pursue computer-assisted triaging of magnetic resonance imaging (MRI)-guided breast biopsy of additional lesions at high specificity.

Materials And Methods: We investigated 316 consecutive female patients (aged 26 to 76 years; mean, 54 years) with early breast cancer who received preoperative multiparametric breast MRI between 2013 and 2016.

Computer-Aided Diagnosis in Multiparametric Magnetic Resonance Imaging Screening of Women With Extremely Dense Breasts to Reduce False-Positive Diagnoses.

Objectives: To reduce the number of false-positive diagnoses in the screening of women with extremely dense breasts using magnetic resonance imaging (MRI), we aimed to predict which BI-RADS 3 and BI-RADS 4 lesions are benign. For this purpose, we use computer-aided diagnosis (CAD) based on multiparametric assessment.

Materials And Methods: Consecutive data were used from the first screening round of the DENSE (Dense Tissue and Early Breast Neoplasm Screening) trial.

Deep Learning for Automatic Calcium Scoring in CT: Validation Using Multiple Cardiac CT and Chest CT Protocols.

Background Although several deep learning (DL) calcium scoring methods have achieved excellent performance for specific CT protocols, their performance in a range of CT examination types is unknown. Purpose To evaluate the performance of a DL method for automatic calcium scoring across a wide range of CT examination types and to investigate whether the method can adapt to different types of CT examinations when representative images are added to the existing training data set. Materials and Methods The study included 7240 participants who underwent various types of nonenhanced CT examinations that included the heart: coronary artery calcium (CAC) scoring CT, diagnostic CT of the chest, PET attenuation correction CT, radiation therapy treatment planning CT, CAC screening CT, and low-dose CT of the chest.

Evaluation of Variable Density and Data-Driven K-Space Undersampling for Compressed Sensing Magnetic Resonance Imaging.

Objectives: The aim of this study was to investigate the influence of variable density and data-driven k-space undersampling patterns on reconstruction quality for compressed sensing (CS) magnetic resonance imaging to provide recommendations on how to avoid suboptimal CS reconstructions.

Materials And Methods: First, we investigated the influence of randomness and sampling density on the reconstruction quality when using random variable density and variable density Poisson disk undersampling. Compressed sensing reconstructions on 1 knee and 2 brain data sets were compared with fully sampled data sets and reconstruction errors were measured.

Association between Parenchymal Enhancement of the Contralateral Breast in Dynamic Contrast-enhanced MR Imaging and Outcome of Patients with Unilateral Invasive Breast Cancer.

Purpose: To retrospectively investigate whether parenchymal enhancement in dynamic contrast material-enhanced magnetic resonance (MR) imaging of the contralateral breast in patients with unilateral invasive breast cancer is associated with therapy outcome.

Materials And Methods: After obtaining approval of the institutional review board and patients' written informed consent, 531 women with unilateral invasive breast cancer underwent dynamic contrast-enhanced MR imaging between 2000 and 2008. The contralateral parenchyma was segmented automatically, in which the mean of the top 10% late enhancement was calculated.