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• Mono + DECT combines increased contrast with reduced image noise, unlike linearly blended images. • Mono + DECT imaging allows for superior CNR and subjective image quality. • Head and neck tumour contrast-to-noise ratio peaks at 40 keV. • 55 keV images are preferred over all other series by observers.

• Mono+ combines increased attenuation with reduced image noise compared to standard DE-CTA. • Mono+ shows superior contrast-to-noise ratios at low keV compared to linearly-blended images. • Contrast-to-noise ratio in monoenergetic DE-CTA peaks at 40 keV. • Mono+ reconstructions significantly improve quantitative image quality at low keV levels.

Objectives To analyze the performance of radiological assessment categories and quantitative computational analysis of apparent diffusion coefficient (ADC) maps using variant machine learning algorithms to differentiate clinically significant versus insignificant prostate cancer (PCa). Methods Retrospectively, 73 patients were included in the study. The patients (mean age, 66.3 ± 7.6 years) were examined with multiparametric MRI (mpMRI) prior to radical prostatectomy (n = 33) or targeted biopsy (n = 40). The index lesion was annotated in MRI ADC and the equivalent histologic slides according to the highest Gleason Grade Group (GrG). Volumes of interest (VOIs) were determined for each lesion and normal-appearing peripheral zone. VOIs were processed by radiomic analysis. For the classification of lesions according to their clinical significance (GrG ≥ 3), principal component (PC) analysis, univariate analysis (UA) with consecutive support vector machines, neural networks, and random forest analysis were performed. Results PC analysis discriminated between benign and malignant prostate tissue. PC evaluation yielded no stratification of PCa lesions according to their clinical significance, but UA revealed differences in clinical assessment categories and radiomic features. We trained three classification models with fifteen feature subsets. We identified a subset of shape features which improved the diagnostic accuracy of the clinical assessment categories (maximum increase in diagnostic accuracy ΔAUC = + 0.05, p < 0.001) while also identifying combinations of features and models which reduced overall accuracy. Conclusions The impact of radiomic features to differentiate PCa lesions according to their clinical significance remains controversial. It depends on feature selection and the employed machine learning algorithms. It can result in improvement or reduction of diagnostic performance. Key Points • Quantitative imaging features differ between normal and malignant tissue of the peripheral zone in prostate cancer. • Radiomic feature analysis of clinical routine multiparametric MRI has the potential to improve the stratification of clinically significant versus insignificant prostate cancer lesions in the peripheral zone. • Certain combinations of standard multiparametric MRI reporting and assessment categories with feature subsets and machine learning algorithms reduced the diagnostic performance over standard clinical assessment categories alone.

Heterotaxy and situs abnormalities describe an abnormal arrangement of visceral organs in the thoracoabdominal cavity across the normal left–right axis of the body. It is associated with a high occurrence of congenital heart and abdominal defects, including anomalous pulmonary venous connections, systemic venous abnormalities, asplenia, and intestinal malrotation. Without proper diagnosis and surgical intervention, the prognosis of patients with heterotaxy syndrome and associated congenital defects is extremely poor. Complex intracardiac and extracardiac lesions are common in heterotaxy and can be difficult to assess by echocardiography. CT angiography (CTA) is a useful tool in this setting to accurately assess intracardiac and extracardiac abnormalities in this population for medical or surgical management. The intention of this pictorial essay is to review the most common cardiovascular defects involved with heterotaxy syndrome in addition to emphasizing the utility of CTA in the identification and classification of anomalies seen in these patients. This review briefly defines most common terminology used in situs abnormalities as well as presents CT images and 3-dimensional reconstructions of common anomalies associated with situs abnormalities. In summary, this review should prepare radiologists and pediatric cardiologists to describe heterotaxy and situs abnormalities in addition to recognizing the utility of CTA in these patients.