A comprehensive imaging review of early placental formation, normal placental imaging features, and various placental pathologic conditions is provided, with discussion of newer imaging techniques for evaluation of the placenta. The placenta plays a crucial role throughout pregnancy, and its importance may be overlooked during routine antenatal imaging evaluation. Detailed systematic assessment of the placenta at ultrasonography (US), the standard imaging examination during pregnancy, is important. Familiarity with the normal and abnormal imaging appearance of the placenta along with the multimodality and methodical approach for evaluation of its related abnormalities is necessary, so that radiologists can alert clinicians regarding appropriate prompt management decisions. This will potentially decrease fetal and maternal morbidity and mortality. This article reviews early placental formation and the expected imaging appearance of the placenta during pregnancy, as well as variations in its morphology. It also discusses various placental diseases and their potential clinical consequences. Placental pathologic conditions include abnormalities of placental size, cord insertion, placental and cord location, and placental adherence. O...

Combined hepatocellular-cholangiocarcinoma is a rare but unique primary hepatic tumor with characteristic histology and tumor biology. Recent development in genetics and molecular biology support the fact that combined hepatocellular-cholangiocarcinoma is closely linked with cholangiocarcinoma, rather than hepatocellular carcinoma. Combined hepatocellular cholangiocarcinoma tends to present with an more aggressive behavior and a poorer prognosis than either hepatocellular carcinoma or cholangiocarcinoma. An accurate preoperative diagnosis and aggressive treatment planning can play crucial roles in appropriate patient management.

Virtual unenhanced images from a dual-energy CT multimaterial decomposition algorithm yield renal mass attenuation comparable to true unenhanced images for both enhancing renal masses and nonenhanc... Background Virtual unenhanced (VUE) images obtained by using a dual-energy CT (DECT) multimaterial decomposition algorithm hold promise for diagnostic use in the abdomen in lieu of true unenhanced ...

Context: Thyroid nodule ultrasound-based risk stratification schemas rely on the presence of high-risk sonographic features. However, some malignant thyroid nodules have benign appearance on thyroid ultrasound. New methods for thyroid nodule risk assessment are needed. Objective: We investigated polygenic risk score (PRS) accounting for inherited thyroid cancer risk combined with ultrasound-based analysis for improved thyroid nodule risk assessment. Methods: The convolutional neural network classifier was trained on thyroid ultrasound still images and cine clips from 621 thyroid nodules. Phenome-wide association study (PheWAS) and PRS PheWAS were used to optimize PRS for distinguishing benign and malignant nodules. PRS was evaluated in 73 346 participants in the Colorado Center for Personalized Medicine Biobank. Results: When the deep learning model output was combined with thyroid cancer PRS and genetic ancestry estimates, the area under the receiver operating characteristic curve (AUROC) of the benign vs malignant thyroid nodule classifier increased from 0.83 to 0.89 (DeLong, P value = .007). The combined deep learning and genetic classifier achieved a clinically relevant sensitivity of 0.95, 95% CI [0.88-0.99], specificity of 0.63 [0.55-0.70], and positive and negative predictive values of 0.47 [0.41-0.58] and 0.97 [0.92-0.99], respectively. AUROC improvement was consistent in European ancestry-stratified analysis (0.83 and 0.87 for deep learning and deep learning combined with PRS classifiers, respectively). Elevated PRS was associated with a greater risk of thyroid cancer structural disease recurrence (ordinal logistic regression, P value = .002). Conclusion: Augmenting ultrasound-based risk assessment with PRS improves diagnostic accuracy.