Prediction of Response to Anti-Angiogenic Treatment for Advanced Colorectal Cancer Patients: From Biological Factors to Functional Imaging.

Colorectal cancer (CRC) is a leading tumor worldwide. In CRC, the angiogenic pathway plays a crucial role in cancer development and the process of metastasis. Thus, anti-angiogenic drugs represent a milestone for metastatic CRC (mCRC) treatment and lead to significant improvement of clinical outcomes. Nevertheless, not all patients respond to treatment and some develop resistance. Therefore, the identification of predictive factors able to predict response to angiogenesis pathway blockade is required in order to identify the best candidates to receive these agents. Unfortunately, no predictive biomarkers have been prospectively validated to date. Over the years, research has focused on biologic factors such as genetic polymorphisms, circulating biomarkers, circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and microRNA. Moreover, research efforts have evaluated the potential correlation of molecular biomarkers with imaging techniques used for tumor assessment as well as the application of imaging tools in clinical practice. In addition to functional imaging, radiomics, a relatively newer technique, shows real promise in the setting of correlating molecular medicine to radiological phenotypes.

Intraprocedural continuous saline infusion lines significantly reduce the incidence of acute kidney injury during endovascular procedures for stroke and myocardial infarction: evidence from a systematic review and meta-regression.

BACKGROUND: Contrast media used in mechanical therapies for stroke and myocardial infarction represent a significant cause of acute kidney injury (AKI) in acute medical scenarios. Although the continuous saline infusion line (CSIL) is a standard procedure to prevent thrombus formation within the catheter during neurovascular interventions of mechanical thrombectomy (MT), it is not utilized in percutaneous coronary interventions (PCI). METHODS: A systematic review of the incidence of AKI after MT for stroke treatment was performed. These data were compared with those reported in the literature regarding the incidence of AKI after PCI for acute myocardial infarction. A random-effect model meta-regression was performed to explore the effects of CSIL on AKI incidence, using clinical details as covariates. RESULTS: A total of 18 and 33 studies on MT and PCI were included, respectively, with 69,464 patients (30,138 [43.4%] for MT and 39,326 [56.6%] for PCI). The mean age was 63.6 years±5.8 with male 66.6%±12.8. Chronic kidney disease ranged 2.0-50.3%. Diabetes prevalence spanned 11.1% to 53.0%. Smoking status had a prevalence of 7.5-72.0%. Incidence of AKI proved highly variable (I2=98%, Cochrane's Q 2985), and appeared significantly lower in the MT subgroup than in the PCI subgroups (respectively 8.3% [95% confidence interval: 4.7-11.9%] vs. 14.7 [12.6-16.8%], P<0.05). Meta-regression showed that CSIL was significantly associated with a decreased incidence of AKI (OR=0.93 [1.001-1.16]; P=0.03). CONCLUSIONS: Implementation of CSIL during endovascular procedures in acute settings was associated with a significant decrease in the risk of AKI, and its safety should be routinely considered in such interventions.

Structural Brain MR Imaging Alterations in Patients with Systemic Lupus Erythematous with and without Neuropsychiatric Events.

BACKGROUND AND PURPOSE: Systemic lupus erythematosus is a complex autoimmune disease known for its diverse clinical manifestations, including neuropsychiatric systemic lupus erythematosus, which impacts a patient's quality of life. Our aim was to explore the relationships among brain MR imaging morphometric findings, neuropsychiatric events, and laboratory values in patients with systemic lupus erythematosus, shedding light on potential volumetric biomarkers and diagnostic indicators for neuropsychiatric systemic lupus erythematosus. MATERIALS AND METHODS: Twenty-seven patients with systemic lupus erythematosus (14 with neuropsychiatric systemic lupus erythematosus, 13 with systemic lupus erythematosus), 24 women and 3 men (average age, 43 years, ranging from 21 to 62 years) were included in this cross-sectional study, along with 10 neuropsychiatric patients as controls. An MR imaging morphometric analysis, with the VolBrain online platform, to quantitatively assess brain structural features and their differences between patients with neuropsychiatric systemic lupus erythematosus and systemic lupus erythematosus, was performed. Correlations and differences between MR imaging morphometric findings and laboratory values, including disease activity scores, such as the Systemic Lupus Erythematosus Disease Activity Index and the Systemic Lupus International Collaborating Clinics Damage Index, were explored. An ordinary least squares regression analysis further explored the Systemic Lupus Erythematosus Disease Activity Index and Systemic Lupus International Collaborating Clinics Damage Index relationship with MR imaging features. RESULTS: For neuropsychiatric systemic lupus erythematosus and non-neuropsychiatric systemic lupus erythematosus, the brain regions with the largest difference in volumetric measurements were the insular central operculum volume (P value = .003) and the occipital cortex thickness (P = .003), which were lower in neuropsychiatric systemic lupus erythematosus. The partial correlation analysis showed that the most correlated morphometric features with neuropsychiatric systemic lupus erythematosus were subcallosal area thickness asymmetry (P < .001) and temporal pole thickness asymmetry (P = .011). The ordinary least squares regression analysis yielded an R 2 of 0.725 for the Systemic Lupus Erythematosus Disease Activity Index score, with calcarine cortex volume as a significant predictor, and an R 2 of 0.715 for the Systemic Lupus International Collaborating Clinics Damage Index score, with medial postcentral gyrus volume as a significant predictor. CONCLUSIONS: The MR imaging volumetric analysis, along with the correlation study and the ordinary least squares regression analysis, revealed significant differences in brain regions and their characteristics between patients with neuropsychiatric systemic lupus erythematosus and those with systemic lupus erythematosus, as well as between patients with different Systemic Lupus Erythematosus Disease Activity Index and Systemic Lupus International Collaborating Clinics Damage Index scores.

Utility of Dual-Energy Computed Tomography in Clinical Conundra.

Advancing medical technology revolutionizes our ability to diagnose various disease processes. Conventional Single-Energy Computed Tomography (SECT) has multiple inherent limitations for providing definite diagnoses in certain clinical contexts. Dual-Energy Computed Tomography (DECT) has been in use since 2006 and has constantly evolved providing various applications to assist radiologists in reaching certain diagnoses SECT is rather unable to identify. DECT may also complement the role of SECT by supporting radiologists to confidently make diagnoses in certain clinically challenging scenarios. In this review article, we briefly describe the principles of X-ray attenuation. We detail principles for DECT and describe multiple systems associated with this technology. We describe various DECT techniques and algorithms including virtual monoenergetic imaging (VMI), virtual non-contrast (VNC) imaging, Iodine quantification techniques including Iodine overlay map (IOM), and two- and three-material decomposition algorithms that can be utilized to demonstrate a multitude of pathologies. Lastly, we provide our readers commentary on examples pertaining to the practical implementation of DECT's diverse techniques in the Gastrointestinal, Genitourinary, Biliary, Musculoskeletal, and Neuroradiology systems.

The fascinating theory of fetal programming of adult diseases: A review of the fundamentals of the Barker hypothesis.

The theory of fetal programming of adult diseases was first proposed by David J.P. Barker in the eighties of the previous century, to explain the higher susceptibility of some people toward the development of ischemic heart disease. According to his hypothesis, poor maternal living conditions during gestation represent an important risk factor for the onset of atherosclerotic heart disease later in life. The analysis of the early phases of fetal development is a fundamental tool for the risk stratification of children and adults, allowing the identification of susceptible or resistant subjects to multiple diseases later in life. Here, we provide a narrative summary of the most relevant evidence supporting the Barker hypothesis in multiple fields of medicine, including neuropsychiatric disorders, such as Parkinson disease and Alzheimer disease, kidney failure, atherosclerosis, coronary heart disease, stroke, diabetes, cancer onset and progression, metabolic syndrome, and infectious diseases including COVID-19. Given the consensus on the role of body weight at birth as a practical indicator of the fetal nutritional status during gestation, every subject with a low birth weight should be considered an "at risk" subject for the development of multiple diseases later in life. The hypothesis of the "physiological regenerative medicine," able to improve fetal organs' development in the perinatal period is discussed, in the light of recent experimental data indicating Thymosin Beta-4 as a powerful growth promoter when administered to pregnant mothers before birth.

The Role of Artificial Intelligence in Cardiac Imaging.

Artificial intelligence (AI) is having a significant impact in medical imaging, advancing almost every aspect of the field, from image acquisition and postprocessing to automated image analysis with outreach toward supporting decision making. Noninvasive cardiac imaging is one of the main and most exciting fields for AI development. The aim of this review is to describe the main applications of AI in cardiac imaging, including CT and MR imaging, and provide an overview of recent advancements and available clinical applications that can improve clinical workflow, disease detection, and prognostication in cardiac disease.

Left atrial strain in patients with ß-thalassemia major: a cross-sectional CMR study.

OBJECTIVES: The aim of this cross-sectional study was to investigate the association of left atrial (LA) strain parameters with demographics, clinical data, cardiovascular magnetic resonance (CMR) findings, and cardiac complications (heart failure and arrhythmias) in a cohort of patients with ß-thalassemia major (ß-TM). MATERIALS AND METHODS: We considered 264 ß-TM patients (133 females, 36.79 ± 11.95 years) consecutively enrolled in the Extension-Myocardial Iron Overload in Thalassemia (E-MIOT) project. Moreover, we included 35 sex- and age-matched healthy controls (14 females, mean age 37.36 ± 17.52 years). Reservoir, conduit, and booster LA functions were analysed by CMR feature tracking using dedicated software. RESULTS: Compared to the healthy control group, ß-TM patients demonstrated lower LA reservoir strain and booster strains, as well as LA reservoir and booster strain rates. However, no differences were found in LA conduit deformation parameters. In ß-TM patients, ageing, sex, and left ventricle (LV) volume indexes were independent determinants of LA strain parameters. The number of segments with late gadolinium enhancement (LGE) significantly correlated with all LA strain parameters, with the exception of the LA conduit rate. Patients with cardiac complications exhibited significantly impaired strain parameters compared to patients without cardiac complications. CONCLUSION: In patients with ß-TM, LA strain parameters were impaired compared to control subjects, and they exhibited a significant correlation with the number of LV segments with LGE. Furthermore, patients with cardiac complications had impaired left atrial strain parameters. Clinical relevance statement In patients with ß-thalassemia major, left atrial strain parameters were impaired compared to control subjects and emerged as a sensitive marker of cardiac complications, stronger than cardiac iron levels. KEY POINTS: • Compared to healthy subjects, ß-thalassemia major patients demonstrated significantly lower left atrial reservoir strain and booster strains, as well as left atrial reservoir and booster strain rates. • In ß-thalassemia major, ageing, sex, and left ventricular volume indexes were independent determinants of left atrial strain parameters, while left atrial strain parameters were not correlated with myocardial iron overload. • An independent association between reduced left atrial strain parameters and a history of cardiac complications was found in ß-thalassemia major patients.

Atrial and ventricular strain using cardiovascular magnetic resonance in the prediction of outcomes of pericarditis patients: a pilot study.

OBJECTIVE: Our study aimed to explore with cardiovascular magnetic resonance (CMR) the impact of left atrial (LA) and left ventricular (LV) myocardial strain in patients with acute pericarditis and to investigate their possible prognostic significance in adverse outcomes. METHOD: This retrospective study performed CMR scans in 36 consecutive patients with acute pericarditis (24 males, age 52 [23-52]). The primary endpoint was the combination of recurrent pericarditis, constrictive pericarditis, and surgery for pericardial diseases defined as pericardial events. Atrial and ventricular strain function were performed on conventional cine SSFP sequences. RESULTS: After a median follow-up time of 16 months (interquartile range [13-24]), 12 patients with acute pericarditis reached the primary endpoint. In multivariable Cox regression analysis, LA reservoir and LA conduit strain parameters were all independent determinants of adverse pericardial diseases. Conversely, LV myocardial strain parameters did not remain an independent predictor of outcome. With receiving operating characteristics curve analysis, LA conduit and reservoir strain showed excellent predictive performance (area under the curve of 0.914 and 0.895, respectively) for outcome prediction at 12 months. CONCLUSION: LA reservoir and conduit mechanisms on CMR are independently associated with a higher risk of adverse pericardial events. Including atrial strain parameters in the management of acute pericarditis may improve risk stratification. CLINICAL RELEVANCE STATEMENT: Atrial strain could be a suitable non-invasive and non-contrast cardiovascular magnetic resonance parameter for predicting adverse pericardial complications in patients with acute pericarditis. KEY POINTS: • Myocardial strain is a well-validated CMR parameter for risk stratification in cardiovascular diseases. • LA reservoir and conduit functions are significantly associated with adverse pericardial events. • Atrial strain may serve as an additional non-contrast CMR parameter for stratifying patients with acute pericarditis.

Why selective screening for asymptomatic carotid stenosis is currently appropriate: a special report.

INTRODUCTION: Two of the main reasons recent guidelines do not recommend routine population-wide screening programs for asymptomatic carotid artery stenosis (AsxCS) is that screening could lead to an increase of carotid revascularization procedures and that such mass screening programs may not be cost-effective. Nevertheless, selective screening for AsxCS could have several benefits. This article presents the rationale for such a program. AREAS COVERED: The benefits of selective screening for AsxCS include early recognition of AsxCS allowing timely initiation of preventive measures to reduce future myocardial infarction (MI), stroke, cardiac death and cardiovascular (CV) event rates. EXPERT OPINION: Mass screening programs for AsxCS are neither clinically effective nor cost-effective. Nevertheless, targeted screening of populations at high risk for AsxCS provides an opportunity to identify these individuals earlier rather than later and to initiate a number of lifestyle measures, risk factor modifications, and intensive medical therapy in order to prevent future strokes and CV events. For patients at 'higher risk of stroke' on best medical treatment, a prophylactic carotid intervention may be considered.

GeneAI 3.0: powerful, novel, generalized hybrid and ensemble deep learning frameworks for miRNA species classification of stationary patterns from nucleotides.

Due to the intricate relationship between the small non-coding ribonucleic acid (miRNA) sequences, the classification of miRNA species, namely Human, Gorilla, Rat, and Mouse is challenging. Previous methods are not robust and accurate. In this study, we present AtheroPoint's GeneAI 3.0, a powerful, novel, and generalized method for extracting features from the fixed patterns of purines and pyrimidines in each miRNA sequence in ensemble paradigms in machine learning (EML) and convolutional neural network (CNN)-based deep learning (EDL) frameworks. GeneAI 3.0 utilized five conventional (Entropy, Dissimilarity, Energy, Homogeneity, and Contrast), and three contemporary (Shannon entropy, Hurst exponent, Fractal dimension) features, to generate a composite feature set from given miRNA sequences which were then passed into our ML and DL classification framework. A set of 11 new classifiers was designed consisting of 5 EML and 6 EDL for binary/multiclass classification. It was benchmarked against 9 solo ML (SML), 6 solo DL (SDL), 12 hybrid DL (HDL) models, resulting in a total of 11 + 27 = 38 models were designed. Four hypotheses were formulated and validated using explainable AI (XAI) as well as reliability/statistical tests. The order of the mean performance using accuracy (ACC)/area-under-the-curve (AUC) of the 24 DL classifiers was: EDL > HDL > SDL. The mean performance of EDL models with CNN layers was superior to that without CNN layers by 0.73%/0.92%. Mean performance of EML models was superior to SML models with improvements of ACC/AUC by 6.24%/6.46%. EDL models performed significantly better than EML models, with a mean increase in ACC/AUC of 7.09%/6.96%. The GeneAI 3.0 tool produced expected XAI feature plots, and the statistical tests showed significant p-values. Ensemble models with composite features are highly effective and generalized models for effectively classifying miRNA sequences.

Cine-cardiac magnetic resonance to distinguish between ischemic and non-ischemic cardiomyopathies: a machine learning approach.

OBJECTIVE: This work aimed to derive a machine learning (ML) model for the differentiation between ischemic cardiomyopathy (ICM) and non-ischemic cardiomyopathy (NICM) on non-contrast cardiovascular magnetic resonance (CMR). METHODS: This retrospective study evaluated CMR scans of 107 consecutive patients (49 ICM, 58 NICM), including atrial and ventricular strain parameters. We used these data to compare an explainable tree-based gradient boosting additive model with four traditional ML models for the differentiation of ICM and NICM. The models were trained and internally validated with repeated cross-validation according to discrimination and calibration. Furthermore, we examined important variables for distinguishing between ICM and NICM. RESULTS: A total of 107 patients and 38 variables were available for the analysis. Of those, 49 were ICM (34 males, mean age 60 ± 9 years) and 58 patients were NICM (38 males, mean age 56 ± 19 years). After 10 repetitions of the tenfold cross-validation, the proposed model achieved the highest area under curve (0.82, 95% CI [0.47-1.00]) and lowest Brier score (0.19, 95% CI [0.13-0.27]), showing competitive diagnostic accuracy and calibration. At the Youden's index, sensitivity was 0.72 (95% CI [0.68-0.76]), the highest of all. Analysis of predictions revealed that both atrial and ventricular strain CMR parameters were important for the identification of ICM patients. CONCLUSION: The current study demonstrated that using a ML model, multi chamber myocardial strain, and function on non-contrast CMR parameters enables the discrimination between ICM and NICM with competitive diagnostic accuracy. CLINICAL RELEVANCE STATEMENT: A machine learning model based on non-contrast cardiovascular magnetic resonance parameters may discriminate between ischemic and non-ischemic cardiomyopathy enabling wider access to cardiovascular magnetic resonance examinations with lower costs and faster imaging acquisition. KEY POINTS: • The exponential growth in cardiovascular magnetic resonance examinations may require faster and more cost-effective protocols. • Artificial intelligence models can be utilized to distinguish between ischemic and non-ischemic etiologies. • Machine learning using non-contrast CMR parameters can effectively distinguish between ischemic and non-ischemic cardiomyopathies.

Music Therapy as a Complementary Treatment in Patients with Dementia Associated to Alzheimer's Disease: A Systematic Review.

Background: Alzheimer's disease (AD) is a complex condition that affects various aspects of a patient's life. Music therapy may be considered a beneficial supplementary tool to traditional therapies, that not fully address the range of AD manifestations. Objective: The purpose of this systematic review is to investigate whether music therapy can have a positive impact on AD patients and on which symptoms. Methods: The main research databases employed have been PubMed and Cochrane, using the keywords "dementia", "music therapy", "Alzheimer", "fMRI", "music", and "EEG". Results: After removing duplicates and irrelevant studies, 23 were screened using set criteria, resulting in the final inclusion of 15 studies. The total number of participants included in these studies has been of 1,196 patients. For the fMRI analysis the search resulted in 28 studies on PubMed, two of which were included in the research; the total number of participants was of 124 individuals. The studies conducted with EEG were found using PubMed. The initial search resulted in 15 studies, but after a more accurate evaluation only 2 have been included in the analysis. Conclusions: Even though the data currently available is not sufficient to draw conclusions supported by robust statistical power, the impact of music therapy on AD neuropsychiatric symptoms deserves great interest. Further research should be ushered, possibly multicentric studies, led with neuroimaging and other recent techniques, which can eventually open views on the music role in improving the cognitive status in AD.

Coronary Artery Calcium Score Predicts Major Adverse Cardiovascular Events in Stable Chest Pain.

Background Coronary artery calcium (CAC) has prognostic value for major adverse cardiovascular events (MACE) in asymptomatic individuals, whereas its role in symptomatic patients is less clear. Purpose To assess the prognostic value of CAC scoring for MACE in participants with stable chest pain initially referred for invasive coronary angiography (ICA). Materials and Methods This prespecified subgroup analysis from the Diagnostic Imaging Strategies for Patients With Stable Chest Pain and Intermediate Risk of Coronary Artery Disease (DISCHARGE) trial, conducted between October 2015 and April 2019 across 26 centers in 16 countries, focused on adult patients with stable chest pain referred for ICA. Participants were randomly assigned to undergo either ICA or coronary CT. CAC scores from noncontrast CT scans were categorized into low, intermediate, and high groups based on scores of 0, 1-399, and 400 or higher, respectively. The end point of the study was the occurrence of MACE (myocardial infarction, stroke, and cardiovascular death) over a median 3.5-year follow-up, analyzed using Cox proportional hazard regression tests. Results The study involved 1749 participants (mean age, 60 years ± 10 [SD]; 992 female). The prevalence of obstructive coronary artery disease (CAD) at CT angiography rose from 4.1% (95% CI: 2.8, 5.8) in the CAC score 0 group to 76.1% (95% CI: 70.3, 81.2) in the CAC score 400 or higher group. Revascularization rates increased from 1.7% to 46.2% across the same groups (P < .001). The CAC score 0 group had a lower MACE risk (0.5%; HR, 0.08 [95% CI: 0.02, 0.30]; P < .001), as did the 1-399 CAC score group (1.9%; HR, 0.27 [95% CI: 0.13, 0.59]; P = .001), compared with the 400 or higher CAC score group (6.8%). No significant difference in MACE between sexes was observed (P = .68). Conclusion In participants with stable chest pain initially referred for ICA, a CAC score of 0 showed very low risk of MACE, and higher CAC scores showed increasing risk of obstructive CAD, revascularization, and MACE at follow-up. Clinical trial registration no. NCT02400229 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Hanneman and Gulsin in this issue.

aiGeneR 1.0: An Artificial Intelligence Technique for the Revelation of Informative and Antibiotic Resistant Genes in Escherichia coli.

BACKGROUND: There are several antibiotic resistance genes (ARG) for the Escherichia coli (E. coli) bacteria that cause urinary tract infections (UTI), and it is therefore important to identify these ARG. Artificial Intelligence (AI) has been used previously in the field of gene expression data, but never adopted for the detection and classification of bacterial ARG. We hypothesize, if the data is correctly conferred, right features are selected, and Deep Learning (DL) classification models are optimized, then (i) non-linear DL models would perform better than Machine Learning (ML) models, (ii) leads to higher accuracy, (iii) can identify the hub genes, and, (iv) can identify gene pathways accurately. We have therefore designed aiGeneR, the first of its kind system that uses DL-based models to identify ARG in E. coli in gene expression data. METHODOLOGY: The aiGeneR consists of a tandem connection of quality control embedded with feature extraction and AI-based classification of ARG. We adopted a cross-validation approach to evaluate the performance of aiGeneR using accuracy, precision, recall, and F1-score. Further, we analyzed the effect of sample size ensuring generalization of models and compare against the power analysis. The aiGeneR was validated scientifically and biologically for hub genes and pathways. We benchmarked aiGeneR against two linear and two other non-linear AI models. RESULTS: The aiGeneR identifies tetM (an ARG) and showed an accuracy of 93% with area under the curve (AUC) of 0.99 (p < 0.05). The mean accuracy of non-linear models was 22% higher compared to linear models. We scientifically and biologically validated the aiGeneR. CONCLUSIONS: aiGeneR successfully detected the E. coli genes validating our four hypotheses.

Atrial and Ventricular Strain Imaging Using CMR in the Prediction of Ventricular Arrhythmia in Patients with Myocarditis.

(1) Objective: Myocarditis can be associated with ventricular arrhythmia (VA), individual non-invasive risk stratification through cardiovascular magnetic resonance (CMR) is of great clinical significance. Our study aimed to explore whether left atrial (LA) and left ventricle (LV) myocardial strain serve as independent predictors of VA in patients with myocarditis. (2) Methods: This retrospective study evaluated CMR scans in 141 consecutive patients diagnosed with myocarditis based on the updated Lake Louise criteria (29 females, mean age 41 ± 20). The primary endpoint was VA; this encompassed ventricular fibrillation, sustained ventricular tachycardia, nonsustained ventricular tachycardia, and frequent premature ventricular complexes. LA and LV strain function were performed on conventional cine SSFP sequences. (3) Results: After a median follow-up time of 23 months (interquartile range (18-30)), 17 patients with acute myocarditis reached the primary endpoint. In the multivariable Cox regression analysis, LA reservoir (hazard ratio [HR] and 95% confidence interval [CI]: 0.93 [0.87-0.99], p = 0.02), LA booster (0.87 95% CI [0.76-0.99], p = 0.04), LV global longitudinal (1.26 95% CI [1.02-1.55], p = 0.03), circumferential (1.37 95% CI [1.08-1.73], p = 0.008), and radial strain (0.89 95% CI [0.80-0.98], p = 0.01) were all independent determinants of VA. Patients with LV global circumferential strain > -13.3% exhibited worse event-free survival compared to those with values ≤ -13.3% (p < 0.0001). (4) Conclusions: LA and LV strain mechanism on CMR are independently associated with VA events in patients with myocarditis, independent to LV ejection fraction, and late gadolinium enhancement location. Incorporating myocardial strain parameters into the management of myocarditis may improve risk stratification.

Effect of Body Mass Index on Effectiveness of CT versus Invasive Coronary Angiography in Stable Chest Pain: The DISCHARGE Trial.

Background Recent trials support the role of cardiac CT in the evaluation of symptomatic patients suspected of having coronary artery disease (CAD); however, body mass index (BMI) has been reported to negatively impact CT image quality. Purpose To compare initial use of CT versus invasive coronary angiography (ICA) on clinical outcomes in patients with stable chest pain stratified by BMI category. Materials and Methods This prospective study represents a prespecified BMI subgroup analysis of the multicenter Diagnostic Imaging Strategies for Patients with Stable Chest Pain and Intermediate Risk of Coronary Artery Disease (DISCHARGE) trial conducted between October 2015 and April 2019. Adult patients with stable chest pain and a CAD pretest probability of 10%-60% were randomly assigned to undergo initial CT or ICA. The primary end point was major adverse cardiovascular events (MACE), including cardiovascular death, nonfatal myocardial infarction, or stroke. The secondary end point was an expanded MACE composite, including transient ischemic attack, and major procedure-related complications. Competing risk analyses were performed using the Fine and Gray subdistribution Cox proportional hazard model to assess the impact of the relationship between BMI and initial management with CT or ICA on the study outcomes, whereas noncardiovascular death and unknown causes of death were considered competing risk events. Results Among the 3457 participants included, 831 (24.0%), 1358 (39.3%), and 1268 (36.7%) had a BMI of less than 25, between 25 and 30, and greater than 30 kg/m2, respectively. No interaction was found between CT or ICA and BMI for MACE (P = .29), the expanded MACE composite (P = .38), or major procedure-related complications (P = .49). Across all BMI subgroups, expanded MACE composite events (CT, 10 of 409 [2.4%] to 23 of 697 [3.3%]; ICA, 26 of 661 [3.9%] to 21 of 422 [5.1%]) and major procedure-related complications during initial management (CT, one of 638 [0.2%] to five of 697 [0.7%]; ICA, nine of 630 [1.4%] to 12 of 422 [2.9%]) were less frequent in the CT versus ICA group. Participants with a BMI exceeding 30 kg/m² exhibited a higher nondiagnostic CT rate (7.1%, P = .044) compared to participants with lower BMI. Conclusion There was no evidence of a difference in outcomes between CT and ICA across the three BMI subgroups. Clinical trial registration no. NCT02400229 © RSNA, 2024 Supplemental material is available for this article.

Age and Computed Tomography and Invasive Coronary Angiography in Stable Chest Pain: A Prespecified Secondary Analysis of the DISCHARGE Randomized Clinical Trial.

Importance: The effectiveness and safety of computed tomography (CT) and invasive coronary angiography (ICA) in different age groups is unknown. Objective: To determine the association of age with outcomes of CT and ICA in patients with stable chest pain. Design, Setting, and Participants: The assessor-blinded Diagnostic Imaging Strategies for Patients With Stable Chest Pain and Intermediate Risk of Coronary Artery Disease (DISCHARGE) randomized clinical trial was conducted between October 2015 and April 2019 in 26 European centers. Patients referred for ICA with stable chest pain and an intermediate probability of obstructive coronary artery disease were analyzed in an intention-to-treat analysis. Data were analyzed from July 2022 to January 2023. Interventions: Patients were randomly assigned to a CT-first strategy or a direct-to-ICA strategy. Main Outcomes and Measures: MACE (ie, cardiovascular death, nonfatal myocardial infarction, or stroke) and major procedure-related complications. The primary prespecified outcome of this secondary analysis of age was major adverse cardiovascular events (MACE) at a median follow-up of 3.5 years. Results: Among 3561 patients (mean [SD] age, 60.1 [10.1] years; 2002 female [56.2%]), 2360 (66.3%) were younger than 65 years, 982 (27.6%) were between ages 65 to 75 years, and 219 (6.1%) were older than 75 years. The primary outcome was MACE at a median (IQR) follow-up of 3.5 (2.9-4.2) years for 3523 patients (99%). Modeling age as a continuous variable, age, and randomization group were not associated with MACE (hazard ratio, 1.02; 95% CI, 0.98-1.07; P for interaction = .31). Age and randomization group were associated with major procedure-related complications (odds ratio, 1.15; 95% CI, 1.05-1.27; P for interaction = .005), which were lower in younger patients. Conclusions and Relevance: Age did not modify the effect of randomization group on the primary outcome of MACE but did modify the effect on major procedure-related complications. Results suggest that CT was associated with a lower risk of major procedure-related complications in younger patients. Trial Registration: ClinicalTrials.gov Identifier: NCT02400229.