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Abstract Background Radiomics is a quantitative approach that allows the extraction of mineable data from medical images. Despite the growing clinical interest, radiomics studies are affected by variability stemming from analysis choices. We aimed to investigate the agreement between two open-source radiomics software for both contrast-enhanced computed tomography (CT) and contrast-enhanced magnetic resonance imaging (MRI) of lung cancers and to preliminarily evaluate the existence of radiomic features stable for both techniques. Methods Contrast-enhanced CT and MRI images of 35 patients affected with non-small cell lung cancer (NSCLC) were manually segmented and preprocessed using three different methods. Sixty-six Image Biomarker Standardisation Initiative-compliant features common to the considered platforms, PyRadiomics and LIFEx, were extracted. The correlation among features with the same mathematical definition was analyzed by comparing PyRadiomics and LIFEx (at fixed imaging technique), and MRI with CT results (for the same software). Results When assessing the agreement between LIFEx and PyRadiomics across the considered resampling, the maximum statistically significant correlations were observed to be 94% for CT features and 95% for MRI ones. When examining the correlation between features extracted from contrast-enhanced CT and MRI using the same software, higher significant correspondences were identified in 11% of features for both software. Conclusions Considering NSCLC, (i) for both imaging techniques, LIFEx and PyRadiomics agreed on average for 90% of features, with MRI being more affected by resampling and (ii) CT and MRI contained mostly non-redundant information, but there are shape features and, more importantly, texture features that can be singled out by both techniques. Relevance statement Identifying and selecting features that are stable cross-modalities may be one of the strategies to pave the way for radiomics clinical translation. Key points • More than 90% of LIFEx and PyRadiomics features contain the same information. • Ten percent of features (shape, texture) are stable among contrast-enhanced CT and MRI. • Software compliance and cross-modalities stability features are impacted by the resampling method. Graphical Abstract

Abstract Background Benign nerve sheath tumors presenting as solitary retroperitoneal masses (RBNSTs) pose a complex diagnostic challenge for multidisciplinary teams regarding differential diagnosis, staging, and treatment planning. This article reviews the role played by different imaging techniques in assessing RBNSTs and elucidates their typical pathological features with a particular emphasis on the correlation between imaging and histological findings. Furthermore, some examples of retroperitoneal tumors that merit consideration in the process of differential diagnosis based on cross-sectional investigations (CSIs) are reported. The correlation between tissue architecture and appearance on imaging can help increase the accuracy of differential diagnosis with other retroperitoneal neoplasms at CSIs. Critical relevance statement This educational review critically examines the correlation between imaging and histological features in solitary retroperitoneal benign nerve sheath tumors, offering valuable insights for improving the accuracy of differential diagnosis in clinical radiology. Key Points RBNSTs are challenging to diagnose because they lack specific radiological features. Differential diagnosis of RBNSTs from other retroperitoneal neoplasms on imaging is complex. Surgical removal of RBNSTs is recommended for an accurate diagnosis. Graphical Abstract

Artificial Intelligence (AI) and Machine Learning (ML) approaches that could learn from large data sources have been identified as useful tools to support clinicians in their decisional process; AI and ML implementations have had a rapid acceleration during the recent COVID-19 pandemic. However, many ML classifiers are “black box” to the final user, since their underlying reasoning process is often obscure. Additionally, the performance of such models suffers from poor generalization ability in the presence of dataset shifts. Here, we present a comparison between an explainable-by-design (“white box”) model (Bayesian Network (BN)) versus a black box model (Random Forest), both studied with the aim of supporting clinicians of Policlinico San Matteo University Hospital in Pavia (Italy) during the triage of COVID-19 patients. Our aim is to evaluate whether the BN predictive performances are comparable with those of a widely used but less explainable ML model such as Random Forest and to test the generalization ability of the ML models across different waves of the pandemic.

(1) Background: Quantitative CT analysis (QCT) has demonstrated promising results in the prognosis prediction of patients affected by COVID-19. We implemented QCT not only at diagnosis but also at short-term follow-up, pairing it with a clinical examination in search of a correlation between residual respiratory symptoms and abnormal QCT results. (2) Methods: In this prospective monocentric trial performed during the “first wave” of the Italian pandemic, i.e., from March to May 2020, we aimed to test the relationship between %deltaCL (variation of %CL-compromised lung volume) and variations of symptoms-dyspnea, cough and chest pain-at follow-up clinical assessment after hospitalization. (3) Results: 282 patients (95 females, 34%) with a median age of 60 years (IQR, 51–69) were included. We reported a correlation between changing lung abnormalities measured by QCT, and residual symptoms at short-term follow up after COVID-19 pneumonia. Independently from age, a low percentage of surviving patients (1–4%) may present residual respiratory symptoms at approximately two months after discharge. QCT was able to quantify the extent of residual lung damage underlying such symptoms, as the reduction of both %PAL (poorly aerated lung) and %CL volumes was correlated to their disappearance. (4) Conclusions QCT may be used as an objective metric for the measurement of COVID-19 sequelae.

Testicular arteries usually arise from the abdominal aorta. During an elective embolization of superior rectal arteries for hemorrhoidal disease performed in a 52-year-old male patient, a previously unreported vascular variant was identified. On selective angiography, the inferior mesenteric artery split into left colic artery and left testicular artery, without any evidence of vascular supply to the hemorrhoidal cushions. Superior rectal arteries were embolized after catheterization of the median sacral artery. A thorough knowledge of vascular variations is essential for interventional radiologists in order to recognize them and avoid potential complications.

Pulmonary hypertension (PH) is a pathophysiological disorder, defined by a mean pulmonary arterial pressure (mPAP) > 20 mmHg at rest, as assessed by right heart catheterization (RHC). PH is not a specific disease, as it may be observed in multiple clinical conditions and may complicate a variety of thoracic diseases. Conditions associated with the risk of developing PH are categorized into five different groups, according to similar clinical presentations, pathological findings, hemodynamic characteristics, and treatment strategy. Most chronic lung diseases that may be complicated by PH belong to group 3 (interstitial lung diseases, chronic obstructive pulmonary disease, combined pulmonary fibrosis, and emphysema) and are associated with the lowest overall survival among all groups. However, some of the chronic pulmonary diseases may develop PH with unclear/multifactorial mechanisms and are included in group 5 PH (sarcoidosis, pulmonary Langerhans’ cell histiocytosis, and neurofibromatosis type 1). This paper focuses on PH associated with chronic lung diseases, in which radiological imaging—particularly computed tomography (CT)—plays a crucial role in diagnosis and classification. Radiologists should become familiar with the hemodynamical, physiological, and radiological aspects of PH and chronic lung diseases in patients at risk of developing PH, whose prognosis and treatment depend on the underlying disease.

Sarcopenia has been associated with lower overall survival in patients with cirrhosis and hepatocellular carcinoma (HCC) undergoing surgical resection, TACE, TARE, or transplantation. This monocentric study evaluated the prognostic significance of sarcopenia in patients affected by HCC who received bland transarterial embolization (TAE) therapy, by analyzing its impact on survival and treatment-related complications. All consecutive patients who underwent the 1st TAE between March 1st 2011 and July 1st 2019 in our Institution were retrospectively studied. To evaluate sarcopenia, the skeletal muscle index (SMI) was calculated by normalizing the cross-sectional muscle area at the level of L3 on an abdominal CT scan prior to embolization (cm2) by patient height (m2). SMI cut-off values for sarcopenia were considered ≤ 39 cm2/m2 for women and ≤55 cm2/m2 for men. Data about age, gender, body mass index (BMI), underlying liver disease, liver function, MELD score, Child-Pugh score, multifocal disease, performance status, previous interventions, length of stay (LOS), complications after the procedure, readmission rate within 30 days, survival time from TAE and total number and type of TAE received following the first procedure were collected. From 2011 to 2019, 142 consecutive patients underwent 305 TAEs. Observation time ranged from 1.4 to 100.5 months (median 20.1 SD = 22). Sarcopenia at baseline was present in 121 (85%) patients. Overall 87 (61.2%) patients died during follow-up with survival rates at 1-, 2-, 3-, 4-, and 5-year of 71%, 41%, 22%, 16% and 11% respectively. After multivariate analysis sarcopenia (HR = 2.22, p = 0.046), previous ablation/resection (HR = 0.51, p = 0.005) and multifocal disease (HR = 1.84, p = 0.02) were associated with reduced survival. Sarcopenia did not influence the safety of TAE in terms of LOS (2 days vs 1.5 days, p = 0.2), early complications rate (8% vs 5%, p = 0.5) and readmission rate within 30 days (7% vs 5%, p = 0.74). Sarcopenia, estimated by the L3SMI method, is an emerging prognostic factor in patients with HCC undergoing bland TAE therapy as it is associated with increased mortality, without impairing the safety of the locoregional treatment. Measures to ameliorate the SMI, such as nutritional support and physical exercise, should be evaluated in clinical trials for HCC patients receiving liver embolization to determine their impact on overall survival.

[This corrects the article DOI: 10.1371/journal.pone.0232371.].