Mitral Annular Disease at Cardiac MRI: What to Know and Look For.

Accurate evaluation of the mitral valve (MV) apparatus is essential for understanding the mechanisms of MV disease across various clinical scenarios. The mitral annulus (MA) is a complex and crucial structure that supports MV function; however, conventional imaging techniques have limitations in fully capturing the entirety of the MA. Moreover, recognizing annular changes might aid in identifying patients who may benefit from advanced cardiac imaging and interventions. Multimodality cardiovascular imaging plays a major role in the diagnosis, prognosis, and management of MV disease. Transthoracic echocardiography is the first-line modality for evaluation of the MA, but it has limitations. Cardiac MRI (CMR) has emerged as a robust imaging modality for assessing annular changes, with distinct advantages over other imaging techniques, including accurate flow and volumetric quantification and assessment of variations in the measurements and shape of the MA during the cardiac cycle. Mitral annular disjunction (MAD) is defined as atrial displacement of the hinge point of the MV annulus away from the ventricular myocardium, a condition that is now more frequently diagnosed and studied owing to recent technical advances in cardiac imaging. However, several unresolved issues regarding MAD, such as the functional significance of pathologic disjunction and how this disjunction advances in the clinical course, require further investigation. The authors review the role of CMR in the assessment of MA disease, with a focus on MAD and its functional implications in MV prolapse and mitral regurgitation. ©RSNA, 2024 Supplemental material is available for this article. See the invited commentary by Stojanovska and Fujikura in this issue.

Hospital admission and mortality rates for non-COVID-19 respiratory diseases in Brazil's public health system during the covid-19 pandemic: a nationwide observational study.

OBJECTIVE: To assess the influence of the COVID-19 pandemic on hospital admissions (HA), intra-hospital deaths (HD), and intra-hospital lethality rates (HL) related to respiratory diseases (RD) other than COVID-19 in Brazil. METHODS: This observational time-series study was conducted through comparative analyses of the HA, HD, and HL related to non-COVID-19 RD registered between March and December 2020 by the Brazilian Unified Public Health System on the DataSUS Tabnet platform, using as reference the values recorded in the same period of 2019 and those projected by linear regression methods for 2020, considering the period from 2015 to 2019. The adopted statistical significance level was 5% (p < 0.05). RESULTS: Compared to 2019, in 2020, there was a 42% decrease in HA and a 7.4% decrease in total HD related to non-COVID-19 RD, followed by a 60% increase in HL associated with this group of diseases. The HA and HL registered in 2020 differed significantly from the projected trend for that year by linear regression (p < 0.05). Of note, a significant reduction in hospitalizations due to asthma (-46%), chronic obstructive pulmonary disease (-45%), bronchiectasis (-54%), pneumonia (-46%), and acute bronchitis (-73%) was observed. CONCLUSIONS: During the first 8 months of the pandemic, there was a decline in HA and an increase in HL related to non-COVID-19 RD in Brazil, which can hypothetically reflect logistical challenges and delays in the management of this group of diseases.

Current status and future perspectives of radiomics in hepatocellular carcinoma.

Given the frequent co-existence of an aggressive tumor and underlying chronic liver disease, the management of hepatocellular carcinoma (HCC) patients requires experienced multidisciplinary team discussion. Moreover, imaging plays a key role in the diagnosis, staging, restaging, and surveillance of HCC. Currently, imaging assessment of HCC entails the assessment of qualitative characteristics which are prone to inter-reader variability. Radiomics is an emerging field that extracts high-dimensional mineable quantitative features that cannot be assessed visually with the naked eye from medical imaging. The main potential applications of radiomic models in HCC are to predict histology, response to treatment, genetic signature, recurrence, and survival. Despite the encouraging results to date, there are challenges and limitations that need to be overcome before radiomics implementation in clinical practice. The purpose of this article is to review the main concepts and challenges pertaining to radiomics, and to review recent studies and potential applications of radiomics in HCC.

Hospital admission and mortality rates for non-COVID-19 respiratory diseases in Brazil's public health system during the covid-19 pandemic: a nationwide observational study / Internações hospitalares e taxas de mortalidade por doenças respiratórias não COVID-19 no sistema público de saúde do Brasil durante a pandemia de COVID-19: um estudo observacional nacional

ABSTRACT Objective: To assess the influence of the COVID-19 pandemic on hospital admissions (HA), intra-hospital deaths (HD), and intra-hospital lethality rates (HL) related to respiratory diseases (RD) other than COVID-19 in Brazil. Methods: This observational time-series study was conducted through comparative analyses of the HA, HD, and HL related to non-COVID-19 RD registered between March and December 2020 by the Brazilian Unified Public Health System on the DataSUS Tabnet platform, using as reference the values recorded in the same period of 2019 and those projected by linear regression methods for 2020, considering the period from 2015 to 2019. The adopted statistical significance level was 5% (p < 0.05). Results: Compared to 2019, in 2020, there was a 42% decrease in HA and a 7.4% decrease in total HD related to non-COVID-19 RD, followed by a 60% increase in HL associated with this group of diseases. The HA and HL registered in 2020 differed significantly from the projected trend for that year by linear regression (p < 0.05). Of note, a significant reduction in hospitalizations due to asthma (-46%), chronic obstructive pulmonary disease (-45%), bronchiectasis (-54%), pneumonia (-46%), and acute bronchitis (-73%) was observed. Conclusions: During the first 8 months of the pandemic, there was a decline in HA and an increase in HL related to non-COVID-19 RD in Brazil, which can hypothetically reflect logistical challenges and delays in the management of this group of diseases.

RESUMO Objetivo: Avaliar a influência da pandemia de COVID-19 nas taxas de internações hospitalares (IH), óbitos intra-hospitalares (OH) e letalidade intra-hospitalar (LH) relacionadas a outras doenças respiratórias (DR) que não a COVID-19 no Brasil. Métodos: Este estudo observacional de série temporal foi realizado por meio da análise comparativa das IH, OH e LH relacionadas a DR não COVID-19 registradas entre março e dezembro de 2020 pelo Sistema Único de Saúde na plataforma DataSUS Tabnet, tendo como referência o valores registrados no mesmo período de 2019 e aqueles projetados pelos métodos de regressão linear para 2020, considerando o período de 2015 a 2019. O nível de significância estatística adotado foi de 5% (p < 0,05). Resultados: Comparado a 2019, em 2020, houve uma redução de 42% nas IH e de 7,4% nos OH totais relacionados a DR não COVID-19, seguido de um aumento de 60% nas taxas de LH associadas a esse grupo de doenças. As IH e as taxas de LH registradas em 2020 diferiram significantemente da tendência projetada para aquele ano por regressão linear (p < 0,05). Vale ressaltar que foi observada uma redução significativa das internações por asma (-46%), doença pulmonar obstrutiva crônica (-45%), bronquiectasia (-54%), pneumonia (-46%) e bronquite aguda (-73%). Conclusão: Durante os primeiros 8 meses da pandemia, houve um declínio nas IH e um aumento das taxas de LH relacionadas a DR não COVID-19 no Brasil, o que pode, hipoteticamente, refletir desafios logísticos e atrasos no manejo desse grupo de doenças.

Hepatobiliary phases in magnetic resonance imaging using liver-specific contrast for focal lesions in clinical practice.

BACKGROUND: Challenging lesions, difficult to diagnose through non-invasive methods, constitute an important emotional burden for each patient regarding a still uncertain diagnosis (malignant x benign). In addition, from a therapeutic and prognostic point of view, delay in a definitive diagnosis can lead to worse outcomes. One of the main innovative trends currently is the use of molecular and functional methods to diagnosis. Numerous liver-specific contrast agents have been developed and studied in recent years to improve the performance of liver magnetic resonance imaging (MRI). More recently, one of the contrast agents introduced in clinical practice is gadoxetic acid (gadoxetate disodium). AIM: To demonstrate the value of the hepatobiliary phases using gadoxetic acid in MRI for the characterization of focal liver lesions (FLL) in clinical practice. METHODS: Overall, 302 Lesions were studied in 136 patients who underwent MRI exams using gadoxetic acid for the assessment of FLL. Two radiologists independently reviewed the MRI exams using four stages, and categorized them on a 6-point scale, from 0 (lesion not detected) to 5 (definitely malignant). The stages were: stage 1- images without contrast, stage 2- addition of dynamic phases after contrast (analogous to usual extracellular contrasts), stage 3- addition of hepatobiliary phase after 10 min (HBP 10'), stage 4- hepatobiliary phase after 20 min (HBP 20') in addition to stage 2. RESULTS: The interobserver agreement was high (weighted Kappa coefficient: 0.81- 1) at all stages in the characterization of benign and malignant FLL. The diagnostic weighted accuracy (Az) was 0.80 in stage 1 and was increased to 0.90 in stage 2. Addition of the hepatobiliary phase increased Az to 0.98 in stage 3, which was also 0.98 in stage 4. CONCLUSION: The hepatobiliary sequences improve diagnostic accuracy. With growing potential in the era of precision medicine, the improvement and dissemination of the method among medical specialties can bring benefits in the management of patients with FLL that are difficult to diagnose.

Multimodal integration of radiology, pathology and genomics for prediction of response to PD-(L)1 blockade in patients with non-small cell lung cancer.

Immunotherapy is used to treat almost all patients with advanced non-small cell lung cancer (NSCLC); however, identifying robust predictive biomarkers remains challenging. Here we show the predictive capacity of integrating medical imaging, histopathologic and genomic features to predict immunotherapy response using a cohort of 247 patients with advanced NSCLC with multimodal baseline data obtained during diagnostic clinical workup, including computed tomography scan images, digitized programmed death ligand-1 immunohistochemistry slides and known outcomes to immunotherapy. Using domain expert annotations, we developed a computational workflow to extract patient-level features and used a machine-learning approach to integrate multimodal features into a risk prediction model. Our multimodal model (area under the curve (AUC) = 0.80, 95% confidence interval (CI) 0.74-0.86) outperformed unimodal measures, including tumor mutational burden (AUC = 0.61, 95% CI 0.52-0.70) and programmed death ligand-1 immunohistochemistry score (AUC = 0.73, 95% CI 0.65-0.81). Our study therefore provides a quantitative rationale for using multimodal features to improve prediction of immunotherapy response in patients with NSCLC using expert-guided machine learning.

Rectal MRI radiomics for predicting pathological complete response: Where we are.

Radiomics using rectal MRI radiomics has emerged as a promising approach in predicting pathological complete response. In this study, we present a typical pipeline of a radiomics analysis and review recent studies, exploring applications, development of radiomics methodologies and model construction in pCR prediction. Finally, we will offer our opinion about the future and discuss the next steps of rectal MRI radiomics for predicting pCR.

Lung Lesion Burden found on Chest CT as a Prognostic Marker in Hospitalized Patients with High Clinical Suspicion of COVID-19 Pneumonia: a Brazilian experience.

OBJECTIVE: To investigate the relationship between lung lesion burden (LLB) found on chest computed tomography (CT) and 30-day mortality in hospitalized patients with high clinical suspicion of coronavirus disease 2019 (COVID-19), accounting for tomographic dynamic changes. METHODS: Patients hospitalized with high clinical suspicion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in a dedicated and reference hospital for COVID-19, having undergone at least one RT-PCR test, regardless of the result, and with one CT compatible with COVID-19, were retrospectively studied. Clinical and laboratory data upon admission were assessed, and LLB found on CT was semi-quantitatively evaluated through visual analysis. The primary outcome was 30-day mortality after admission. Secondary outcomes, including the intensive care unit (ICU) admission, mechanical ventilation used, and length of stay (LOS), were assessed. RESULTS: A total of 457 patients with a mean age of 57±15 years were included. Among these, 58% presented with positive RT-PCR result for COVID-19. The median time from symptom onset to RT-PCR was 8 days [interquartile range 6-11 days]. An initial LLB of ≥50% using CT was found in 201 patients (44%), which was associated with an increased crude at 30-day mortality (31% vs. 15% in patients with LLB of <50%, p<0.001). An LLB of ≥50% was also associated with an increase in the ICU admission, the need for mechanical ventilation, and a prolonged LOS after adjusting for baseline covariates and accounting for the CT findings as a time-varying covariate; hence, patients with an LLB of ≥50% remained at a higher risk at 30-day mortality (adjusted hazard ratio 2.17, 95% confidence interval 1.47-3.18, p<0.001). CONCLUSION: Even after accounting for dynamic CT changes in patients with both clinical and imaging findings consistent with COVID-19, an LLB of ≥50% might be associated with a higher risk of mortality.

A machine learning framework for the evaluation of myocardial rotation in patients with noncompaction cardiomyopathy.

AIMS: Noncompaction cardiomyopathy (NCC) is considered a genetic cardiomyopathy with unknown pathophysiological mechanisms. We propose to evaluate echocardiographic predictors for rigid body rotation (RBR) in NCC using a machine learning (ML) based model. METHODS AND RESULTS: Forty-nine outpatients with NCC diagnosis by echocardiography and magnetic resonance imaging (21 men, 42.8±14.8 years) were included. A comprehensive echocardiogram was performed. The layer-specific strain was analyzed from the apical two-, three, four-chamber views, short axis, and focused right ventricle views using 2D echocardiography (2DE) software. RBR was present in 44.9% of patients, and this group presented increased LV mass indexed (118±43.4 vs. 94.1±27.1g/m2, P = 0.034), LV end-diastolic and end-systolic volumes (P< 0.001), E/e' (12.2±8.68 vs. 7.69±3.13, P = 0.034), and decreased LV ejection fraction (40.7±8.71 vs. 58.9±8.76%, P < 0.001) when compared to patients without RBR. Also, patients with RBR presented a significant decrease of global longitudinal, radial, and circumferential strain. When ML model based on a random forest algorithm and a neural network model was applied, it found that twist, NC/C, torsion, LV ejection fraction, and diastolic dysfunction are the strongest predictors to RBR with accuracy, sensitivity, specificity, area under the curve of 0.93, 0.99, 0.80, and 0.88, respectively. CONCLUSION: In this study, a random forest algorithm was capable of selecting the best echocardiographic predictors to RBR pattern in NCC patients, which was consistent with worse systolic, diastolic, and myocardium deformation indices. Prospective studies are warranted to evaluate the role of this tool for NCC risk stratification.

Abdominal gastrointestinal imaging findings on computed tomography in patients with COVID-19 and correlation with clinical outcomes.

PURPOSE: Pulmonary imaging finding of Coronavirus disease 2019 (COVID-19) has been widely described, but until now few studies have been published about abdominal radiological presentation. The aim of this study was to provide an overview of abdominal imaging findings in patients with COVID-19 in a multicenter study and correlate them with worse clinical outcomes. MATERIALS AND METHODS: This retrospective study included adult COVID-positive patients with abdominal CT performed from 4/1/2020 to 5/1/2020 from two institutions. Demographic, laboratory and clinical data were recorded, including clinical outcomes. RESULTS: Of 81 COVID-positive patients, the average age was 61 years, 42 (52%) women and 45 (55%) had positive abdominopelvic findings. The most common abdominal imaging features were intestinal imaging findings (20/81, 24%), including colorectal (4/81, 5%) and small bowel thickening (10/81, 12%), intestinal distension (15/81, 18%), pneumatosis (1/81, 1%) and intestinal perforation (1/81, 1%). On multivariate analysis, intestinal imaging findings were associated with higher risk of worse outcome (death or invasive mechanical ventilation) (RR = 2.6, p = 0.04) and higher risk of invasive mechanical ventilation alone (RR = 6.2, p = 0.05). CONCLUSION: Intestinal abnormalities were common findings in COVID-19 patients who underwent abdominal CT and were significantly correlated to worse outcomes in the clinical follow-up.

Lung lesion burden found on chest ct as a prognostic marker in hospitalized patients with high clinical suspicion of COVID-19 pneumonia: a brazilian experience

OBJECTIVE: To investigate the relationship between lung lesion burden (LLB) found on chest computed tomography (CT) and 30-day mortality in hospitalized patients with high clinical suspicion of coronavirus disease 2019 (COVID-19), accounting for tomographic dynamic changes. METHODS: Patients hospitalized with high clinical suspicion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in a dedicated and reference hospital for COVID-19, having undergone at least one RT-PCR test, regardless of the result, and with one CT compatible with COVID-19, were retrospectively studied. Clinical and laboratory data upon admission were assessed, and LLB found on CT was semi-quantitatively evaluated through visual analysis. The primary outcome was 30-day mortality after admission. Secondary outcomes, including the intensive care unit (ICU) admission, mechanical ventilation used, and length of stay (LOS), were assessed. RESULTS: A total of 457 patients with a mean age of 57±15 years were included. Among these, 58% presented with positive RT-PCR result for COVID-19. The median time from symptom onset to RT-PCR was 8 days [interquartile range 6-11 days]. An initial LLB of ≥50% using CT was found in 201 patients (44%), which was associated with an increased crude at 30-day mortality (31% vs. 15% in patients with LLB of <50%, p<0.001). An LLB of ≥50% was also associated with an increase in the ICU admission, the need for mechanical ventilation, and a prolonged LOS after adjusting for baseline covariates and accounting for the CT findings as a time-varying covariate; hence, patients with an LLB of ≥50% remained at a higher risk at 30-day mortality (adjusted hazard ratio 2.17, 95% confidence interval 1.47-3.18, p<0.001). CONCLUSION: Even after accounting for dynamic CT changes in patients with both clinical and imaging findings consistent with COVID-19, an LLB of ≥50% might be associated with a higher risk of mortality.

Lung radiofrequency ablation: post-procedure imaging patterns and late follow-up.

PURPOSE: To describe expected imaging features on chest computed tomography (CT) after percutaneous radiofrequency ablation (RFA) of lung tumors, and their frequency over time after the procedure. METHODS: In this double-center retrospective study, we reviewed CT scans from patients who underwent RFA for primary or secondary lung tumors. Patients with partial ablation or tumor recurrence during the imaging follow-up were not included. The imaging features were assessed in pre-defined time points: immediate post-procedure, ≤4 weeks, 5-24 weeks, 25-52 weeks and ≥52 weeks. Late follow-up (3 and 5 years after procedure) was assessed clinically in 48 patients. RESULTS: The study population consisted of 69 patients and 144 pulmonary tumors. Six out of 69 (9%) patients had primary lung nodules (stage I) and 63/69 (91 %) had metastatic pulmonary nodules. In a patient-level analysis, immediately after lung RFA, the most common CT features were ground glass opacities (66/69, 96 %), consolidation (56/69, 81 %), and hyperdensity within the nodule (47/69, 68 %). Less than 4 weeks, ground glass opacities (including reversed halo sign) was demonstrated in 20/22 (91 %) patients, while consolidation and pleural thickening were detected in 17/22 patients (77 %). Cavitation, pneumatocele, pneumothorax and pleural effusions were less common features. From 5 weeks onwards, the most common imaging features were parenchymal bands. CONCLUSIONS: Our study demonstrated the expected CT features after lung RFA, a safe and effective minimally invasive treatment for selected patients with primary and secondary lung tumors. Diagnostic and interventional radiologists should be familiar with the expected imaging features immediately after RFA and their change over time in order to avoid misinterpretation and inadequate treatments.

State-of-the-art in radiomics of hepatocellular carcinoma: a review of basic principles, applications, and limitations.

Radiomics is a new field in medical imaging with the potential of changing medical practice. Radiomics is characterized by the extraction of several quantitative imaging features which are not visible to the naked eye from conventional imaging modalities, and its correlation with specific relevant clinical endpoints, such as pathology, therapeutic response, and survival. Several studies have evaluated the use of radiomics in patients with hepatocellular carcinoma (HCC) with encouraging results, particularly in the pretreatment prediction of tumor biological characteristics, risk of recurrence, and survival. In spite of this, there are limitations and challenges to be overcome before the implementation of radiomics into clinical routine. In this article, we will review the concepts of radiomics and their current potential applications in patients with HCC. It is important that the multidisciplinary team involved in the treatment of patients with HCC be aware of the basic principles, benefits, and limitations of radiomics in order to achieve a balanced interpretation of the results toward a personalized medicine.