Recurrent Metastatic Pulmonary Synovial Sarcoma during Pregnancy: A Case Report and Literature Review.

Primary pulmonary synovial sarcoma is a rare type of soft tissue tumor. Exceptionally it can occur during pregnancy, representing a challenge in management and treatment given its notable aggressiveness and the not infrequent incidence of maternal death. We report our case of metastatic recurrence of pulmonary synovial sarcoma during pregnancy, with the aim to emphasize the decision-making, diagnostic, and therapeutic multidisciplinary processes and the evolution of the pathology. Besides, we focused on the analysis of the limited literature data available on the topic.

Pre-TAVI imaging: an Italian survey by the CT PRotocol optimization (CT-PRO) group.

PURPOSE: The purpose of this survey was to evaluate the current state-of-art of pre-TAVI imaging in a large radiological professional community. METHODS: Between December 2022 and January 2023 all members of the Italian Society of Medical and Interventional Radiology (SIRM) were invited by the CT PRotocol Optimization group (CT-PRO group) to complete an online 24-item questionnaire about pre-TAVI imaging. RESULTS: 557 SIRM members participated in the survey. The greatest part of respondents were consultant radiologists employed in public hospitals and 84% claimed to routinely perform pre-TAVI imaging at their institutions. The most widespread acquisition protocol consisted of an ECG-gated CT angiography (CTA) scan of the aortic root and heart followed by a non-ECG-synchronized CTA of the thorax, abdomen, and pelvis. Contrast agent administration was generally tailored on the patient's body weight with a preference for using high concentration contrast media. The reports were commonly written by radiologists with expertise in cardiovascular imaging, and included all the measurements suggested by current guidelines for adequate pre-procedural planning. About 60% of the subjects affirmed that the Heart Team is present at their institutions, however only 7% of the respondents regularly attended the multidisciplinary meetings. CONCLUSIONS: This survey defines the current pre-TAVI imaging practice in a large radiological professional community. Interestingly, despite the majority of radiologists follow the current guidelines regarding acquisition and reporting of pre-TAVI imaging studies, there is still a noteworthy absence from multidisciplinary meetings and from the Heart Team.

Real-World Balance Assessment While Standing for Fall Prediction in Older Adults.

OBJECTIVE: Postural control naturally declines with age, leading to an increased risk of falling. Within clinical settings, the deployment of balance assessments has become commonplace, facilitating the identification of postural instability and targeted interventions to forestall falls among older adults. Some studies have ventured beyond the controlled laboratory, leaving, however, a gap in our understanding of balance in real-world scenarios. METHODS: Previously reported algorithms were used to build a finite-state machine (FSM) with four states: walking, turning, sitting, and standing. The FSM was validated against video annotations (gold standard) in an independent dataset with data collected on 20 older adults. Later, the FSM was applied to data from 168 community-dwelling older people in the InCHIANTI cohort who were evaluated both in the laboratory and then remotely in real-world conditions for a week. A 70/30 data split with recursive feature selection and resampling techniques was used to train and test four machine-learning models. RESULTS: In identifying fallers, duration, distance, and mean frequency computed during standing in real-world settings revealed significant relationships with fall risk. Also, the best-performing model (Lasso Regression) built on real-world balance features had a higher area under the curve (AUC, 0.76) than one built on lab-based assessments (0.57). CONCLUSION: Real-world balance features differ considerably from laboratory balance assessments (Romberg test) and have a higher predictive capacity for identifying patients at high risk of falling. SIGNIFICANCE: These findings highlight the need to move beyond traditional laboratory-based balance measures and develop more sensitive and accurate methods for predicting falls.

Fall risk stratification of community-living older people. Commentary on the world guidelines for fall prevention and management.

The Task Force on Global Guidelines for Falls in Older Adults has put forward a fall risk stratification tool for community-dwelling older adults. This tool takes the form of a flowchart and is based on expert opinion and evidence. It divides the population into three risk categories and recommends specific preventive interventions or treatments for each category. In this commentary, we share our insights on the design, validation, usability and potential impact of this fall risk stratification tool with the aim of guiding future research.

Machine learning-based prediction of hospital prolonged length of stay admission at emergency department: a Gradient Boosting algorithm analysis.

Objective: This study aims to develop and compare different models to predict the Length of Stay (LoS) and the Prolonged Length of Stay (PLoS) of inpatients admitted through the emergency department (ED) in general patient settings. This aim is not only to promote any specific model but rather to suggest a decision-supporting tool (i.e., a prediction framework). Methods: We analyzed a dataset of patients admitted through the ED to the "Sant"Orsola Malpighi University Hospital of Bologna, Italy, between January 1 and October 26, 2022. PLoS was defined as any hospitalization with LoS longer than 6 days. We deployed six classification algorithms for predicting PLoS: Random Forest (RF), Support Vector Machines (SVM), Gradient Boosting (GB), AdaBoost, K-Nearest Neighbors (KNN), and logistic regression (LoR). We evaluated the performance of these models with the Brier score, the area under the ROC curve (AUC), accuracy, sensitivity (recall), specificity, precision, and F1-score. We further developed eight regression models for LoS prediction: Linear Regression (LR), including the penalized linear models Least Absolute Shrinkage and Selection Operator (LASSO), Ridge and Elastic-net regression, Support vector regression, RF regression, KNN, and eXtreme Gradient Boosting (XGBoost) regression. The model performances were measured by their mean square error, mean absolute error, and mean relative error. The dataset was randomly split into a training set (70%) and a validation set (30%). Results: A total of 12,858 eligible patients were included in our study, of whom 60.88% had a PloS. The GB classifier best predicted PloS (accuracy 75%, AUC 75.4%, Brier score 0.181), followed by LoR classifier (accuracy 75%, AUC 75.2%, Brier score 0.182). These models also showed to be adequately calibrated. Ridge and XGBoost regressions best predicted LoS, with the smallest total prediction error. The overall prediction error is between 6 and 7 days, meaning there is a 6-7 day mean difference between actual and predicted LoS. Conclusion: Our results demonstrate the potential of machine learning-based methods to predict LoS and provide valuable insights into the risks behind prolonged hospitalizations. In addition to physicians' clinical expertise, the results of these models can be utilized as input to make informed decisions, such as predicting hospitalizations and enhancing the overall performance of a public healthcare system.

Practical Guide to Interpreting Cardiac Magnetic Resonance in Patients with Cardiac Masses.

It is common for a cardiac mass to be discovered accidentally during an echocardiographic examination. Following the relief of a cardiac mass, being able to evaluate and characterize it using non-invasive imaging methods is critical. Echocardiography, computed tomography (CT), cardiac magnetic resonance imaging (CMR), and positron emission tomography (PET) are the main imaging modalities used to evaluate cardiac masses. Although multimodal imaging often allows for a better assessment, CMR is the best technique for the non-invasive characterization of tissues, as the different MR sequences help in the diagnosis of cardiac masses. This article provides detailed descriptions of each CMR sequence employed in the evaluation of cardiac masses, underlining the potential information it can provide. The description in the individual sequences provides useful guidance to the radiologist in performing the examination.

Tips and Tricks in Thoracic Radiology for Beginners: A Findings-Based Approach.

This review has the purpose of illustrating schematically and comprehensively the key concepts for the beginner who approaches chest radiology for the first time. The approach to thoracic imaging may be challenging for the beginner due to the wide spectrum of diseases, their overlap, and the complexity of radiological findings. The first step consists of the proper assessment of the basic imaging findings. This review is divided into three main districts (mediastinum, pleura, focal and diffuse diseases of the lung parenchyma): the main findings will be discussed in a clinical scenario. Radiological tips and tricks, and relative clinical background, will be provided to orient the beginner toward the differential diagnoses of the main thoracic diseases.

Update on the Applications of Radiomics in Diagnosis, Staging, and Recurrence of Intrahepatic Cholangiocarcinoma.

BACKGROUND: This paper offers an assessment of radiomics tools in the evaluation of intrahepatic cholangiocarcinoma. METHODS: The PubMed database was searched for papers published in the English language no earlier than October 2022. RESULTS: We found 236 studies, and 37 satisfied our research criteria. Several studies addressed multidisciplinary topics, especially diagnosis, prognosis, response to therapy, and prediction of staging (TNM) or pathomorphological patterns. In this review, we have covered diagnostic tools developed through machine learning, deep learning, and neural network for the recurrence and prediction of biological characteristics. The majority of the studies were retrospective. CONCLUSIONS: It is possible to conclude that many performing models have been developed to make differential diagnosis easier for radiologists to predict recurrence and genomic patterns. However, all the studies were retrospective, lacking further external validation in prospective and multicentric cohorts. Furthermore, the radiomics models and the expression of results should be standardized and automatized to be applicable in clinical practice.

Conservative Management and Ultrasound Follow-Up of Parasitic Myoma: Our Experience and Literature Review.

A uterine fibroid is a benign smooth muscle neoplasm of the uterus. Parasitic fibroids (PMs) are a type of myoma that do not have any direct attachment to the uterus. PMs can arise from the implantation of tissue fragments generated during the morcellation process in previous laparoscopic myomectomies or hysterectomies. Transvaginal ultrasound (TV-US) may be helpful in the diagnosis of these benign tumors. Almost all the case reports in the literature suggest surgical management of parasitic fibroids. Conversely, we report an ultrasound-guided histological diagnosis and a non-surgical treatment of a parasitic myoma that arose twenty years after a total laparotomic hysterectomy and bilateral adnexectomy in a patient with multiple comorbidities, in order to offer a follow-up alternative to the management of this rare pathology. Our experience reveals that a non-surgical conservative approach can be considered as an alternative therapeutic option for the management of rare cases such as PMs in highly selected patients.

Imaging of Bone Anatomical Variants Around the Foot and Ankle.

Different anatomical variants can be found in the ankle and foot, generally as occasional findings, although they can be the cause of diagnostic pitfalls and difficulties, especially in radiographic interpretation in trauma. These variants include accessory bones, supernumerary sesamoid bones, and accessory muscles. In most cases, they represent developmental anomalies found in incidental radiographic findings. This review discusses the main bony anatomical variants, including accessory and sesamoid ossicles, most commonly found in the foot and ankle that can be a cause of diagnostic challenges.

Recent Advances in Ultrasound Breast Imaging: From Industry to Clinical Practice.

Breast ultrasound (US) has undergone dramatic technological improvement through recent decades, moving from a low spatial resolution, grayscale-limited technique to a highly performing, multiparametric modality. In this review, we first focus on the spectrum of technical tools that have become commercially available, including new microvasculature imaging modalities, high-frequency transducers, extended field-of-view scanning, elastography, contrast-enhanced US, MicroPure, 3D US, automated US, S-Detect, nomograms, images fusion, and virtual navigation. In the subsequent section, we discuss the broadened current application of US in breast clinical scenarios, distinguishing among primary US, complementary US, and second-look US. Finally, we mention the still ongoing limitations and the challenging aspects of breast US.

Gender Medicine in Clinical Radiology Practice.

Gender Medicine is rapidly emerging as a branch of medicine that studies how many diseases common to men and women differ in terms of prevention, clinical manifestations, diagnostic-therapeutic approach, prognosis, and psychological and social impact. Nowadays, the presentation and identification of many pathological conditions pose unique diagnostic challenges. However, women have always been paradoxically underestimated in epidemiological studies, drug trials, as well as clinical trials, so many clinical conditions affecting the female population are often underestimated and/or delayed and may result in inadequate clinical management. Knowing and valuing these differences in healthcare, thus taking into account individual variability, will make it possible to ensure that each individual receives the best care through the personalization of therapies, the guarantee of diagnostic-therapeutic pathways declined according to gender, as well as through the promotion of gender-specific prevention initiatives. This article aims to assess potential gender differences in clinical-radiological practice extracted from the literature and their impact on health and healthcare. Indeed, in this context, radiomics and radiogenomics are rapidly emerging as new frontiers of imaging in precision medicine. The development of clinical practice support tools supported by artificial intelligence allows through quantitative analysis to characterize tissues noninvasively with the ultimate goal of extracting directly from images indications of disease aggressiveness, prognosis, and therapeutic response. The integration of quantitative data with gene expression and patient clinical data, with the help of structured reporting as well, will in the near future give rise to decision support models for clinical practice that will hopefully improve diagnostic accuracy and prognostic power as well as ensure a more advanced level of precision medicine.

MR Imaging of the Lower Limb: Pitfalls, Tricks, and Tips.

The purpose of this article is to discuss most common diagnostic pitfalls of the lower limb with specific attention to the knee, ankle, and foot joints. The knowledge of normal anatomic variants, correlation with age, symptoms, and medical history together with these potential MR imaging pitfalls is fundamental for an accurate interpretation of the imaging findings of the lower limb.

Post-Surgical Imaging Assessment in Rectal Cancer: Normal Findings and Complications.

Rectal cancer (RC) is one of the deadliest malignancies worldwide. Surgery is the most common treatment for RC, performed in 63.2% of patients. The type of surgical approach chosen aims to achieve maximum residual function with the lowest risk of recurrence. The selection is made by a multidisciplinary team that assesses the characteristics of the patient and the tumor. Total mesorectal excision (TME), including both low anterior resection (LAR) and abdominoperineal resection (APR), is still the standard of care for RC. Radical surgery is burdened by a 31% rate of major complications (Clavien-Dindo grade 3-4), such as anastomotic leaks and a risk of a permanent stoma. In recent years, less-invasive techniques, such as local excision, have been tested. These additional procedures could mitigate the morbidity of rectal resection, while providing acceptable oncologic results. The "watch and wait" approach is not a globally accepted model of care but encouraging results on selected groups of patients make it a promising strategy. In this plethora of treatments, the radiologist is called upon to distinguish a physiological from a pathological postoperative finding. The aim of this narrative review is to identify the main post-surgical complications and the most effective imaging techniques.

Exploring Radiologists' Burnout in the COVID-19 Era: A Narrative Review.

Since its beginning in March 2020, the COVID-19 pandemic has claimed an exceptionally high number of victims and brought significant disruption to the personal and professional lives of millions of people worldwide. Among medical specialists, radiologists have found themselves at the forefront of the crisis due to the pivotal role of imaging in the diagnostic and interventional management of COVID-19 pneumonia and its complications. Because of the disruptive changes related to the COVID-19 outbreak, a proportion of radiologists have faced burnout to several degrees, resulting in detrimental effects on their working activities and overall wellbeing. This paper aims to provide an overview of the literature exploring the issue of radiologists' burnout in the COVID-19 era.

Risk Assessment and Cholangiocarcinoma: Diagnostic Management and Artificial Intelligence.

Intrahepatic cholangiocarcinoma (iCCA) is the second most common primary liver tumor, with a median survival of only 13 months. Surgical resection remains the only curative therapy; however, at first detection, only one-third of patients are at an early enough stage for this approach to be effective, thus rendering early diagnosis as an efficient approach to improving survival. Therefore, the identification of higher-risk patients, whose risk is correlated with genetic and pre-cancerous conditions, and the employment of non-invasive-screening modalities would be appropriate. For several at-risk patients, such as those suffering from primary sclerosing cholangitis or fibropolycystic liver disease, the use of periodic (6-12 months) imaging of the liver by ultrasound (US), magnetic Resonance Imaging (MRI)/cholangiopancreatography (MRCP), or computed tomography (CT) in association with serum CA19-9 measurement has been proposed. For liver cirrhosis patients, it has been proposed that at-risk iCCA patients are monitored in a similar fashion to at-risk HCC patients. The possibility of using Artificial Intelligence models to evaluate higher-risk patients could favor the diagnosis of these entities, although more data are needed to support the practical utility of these applications in the field of screening. For these reasons, it would be appropriate to develop screening programs in the research protocols setting. In fact, the success of these programs reauires patient compliance and multidisciplinary cooperation.

Imaging of metabolic and overload disorders in tissues and organs.

Metabolic and overload disorders are a heterogeneous group of relatively uncommon but important diseases. While imaging plays a key role in the early detection and accurate diagnosis in specific organs with a pivotal role in several metabolic pathways, most of these diseases affect different tissues as part of a systemic syndromes. Moreover, since the symptoms are often vague and phenotypes similar, imaging alterations can present as incidental findings, which must be recognized and interpreted in the light of further biochemical and histological investigations. Among imaging modalities, MRI allows, thanks to its multiparametric properties, to obtain numerous information on tissue composition, but many metabolic and accumulation alterations require a multimodal evaluation, possibly using advanced imaging techniques and sequences, not only for the detection but also for accurate characterization and quantification. The purpose of this review is to describe the different alterations resulting from metabolic and overload pathologies in organs and tissues throughout the body, with particular reference to imaging findings.

Imaging Features of Main Hepatic Resections: The Radiologist Challenging.

Liver resection is still the most effective treatment of primary liver malignancies, including hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), and of metastatic disease, such as colorectal liver metastases. The type of liver resection (anatomic versus non anatomic resection) depends on different features, mainly on the type of malignancy (primary liver neoplasm versus metastatic lesion), size of tumor, its relation with blood and biliary vessels, and the volume of future liver remnant (FLT). Imaging plays a critical role in postoperative assessment, offering the possibility to recognize normal postoperative findings and potential complications. Ultrasonography (US) is the first-line diagnostic tool to use in post-surgical phase. However, computed tomography (CT), due to its comprehensive assessment, allows for a more accurate evaluation and more normal findings than the possible postoperative complications. Magnetic resonance imaging (MRI) with cholangiopancreatography (MRCP) and/or hepatospecific contrast agents remains the best tool for bile duct injuries diagnosis and for ischemic cholangitis evaluation. Consequently, radiologists should be familiar with the surgical approaches for a better comprehension of normal postoperative findings and of postoperative complications.

Diffusion kurtosis imaging and standard diffusion imaging in the magnetic resonance imaging assessment of prostate cancer.

Background and Objective: In recent years, magnetic resonance imaging (MRI) has shown excellent results in the study of the prostate gland. MRI has indeed shown to be advantageous in the prostate cancer (PCa) detection, as in guiding targeting biopsy, improving its diagnostic yield. Although current acquisition protocols provide for multiparametric acquisition, recent evidence has shown that biparametric protocols can be non-inferior in PCa detection. Diffusion-weighted imaging (DWI) sequence, in particular, plays a key role, particularly in the peripheral zone which accounts for the larger part of the prostate. High b-values are generally recommended, although with the possibility of obtaining non-Gaussian diffusion effects, which requires a more sophisticated model for the analysis, namely through the diffusion kurtosis imaging (DKI). Purpose of this narrative review was to analyze the current applications and clinical evidence regarding the use of DKI with a main focus on PCa detection, also in comparison with DWI. Methods: This narrative review synthesized the findings of literature retrieved from main researches, narrative and systematic reviews, and meta-analyses obtained from PubMed. Key Content and Findings: DKI analyses the non-Gaussian water diffusivity and describe the effect of signal intensity decay related to high b-value through two main metrics (Dapp and Kapp). Differently from DWI-apparent diffusion coefficient (DWI-ADC) which reflects only water restriction outside of cells, DKI metrics are supposed to represent also the direct interaction of water molecules with cell membranes and intracellular compounds. This review describes current evidence on ADC and DKI metrics in clinical imaging, and finally collect the results derived from the main articles focused on DWI and DKI models in detecting PCa. Conclusions: DKI advantages, compared to conventional ADC analysis, still remain controversial. Wider application and greater technical knowledge of DKI, however, may help in proving its intrinsic validity in the field of oncology and therefore in the study of clinically significant PCa. Finally, a deep understanding of DKI is important for radiologists to better understand what Kapp and Dapp mean in the context of different cancer and how these metrics may vary specifically in PCa imaging.

Spatiotemporal heterogeneity of SARS-CoV-2 diffusion at the city level using geographically weighted Poisson regression model: The case of Bologna, Italy.

This paper aimed to analyse the spatio-temporal patterns of the diffusion of SARS-CoV-2, the virus causing coronavirus 2019 (COVID-19, in the city of Bologna, the capital and largest city of the Emilia-Romagna Region in northern Italy. The study took place from February 1st, 2020 to November 20th, 2021 and accounted for space, sociodemographic characteristics and health conditions of the resident population. A second goal was to derive a model for the level of risk of being infected by SARS-CoV-2 and to identify and measure the place-specific factors associated with the disease and its determinants. Spatial heterogeneity was tested by comparing global Poisson regression (GPR) and local geographically weighted Poisson regression (GWPR) models. The key findings were that different city areas were impacted differently during the first three epidemic waves. The area-to-area influence was estimated to exert its effect over an area with 4.7 km radius. Spatio-temporal heterogeneity patterns were found to be independent of the sociodemographic and the clinical characteristics of the resident population. Significant single-individual risk factors for detected SARS-CoV-2 infection cases were old age, hypertension, diabetes and co-morbidities. More specifically, in the global model, the average SARS-CoV-2 infection rate decreased 0.93-fold in the 21-65 years age group compared to the >65 years age group, whereas hypertension, diabetes, and any other co-morbidities (present vs absent), increased 1.28-, 1.39- and 1.15-fold, respectively. The local GWPR model had a better fit better than GPR. Due to the global geographical distribution of the pandemic, local estimates are essential for mitigating or strengthening security measures.