Enhanced aortic stiffness in adolescents with chronic disease is associated with decreased left ventricular global longitudinal strain.

Background: The recent Cardiovascular Disease in Adolescents with Chronic Disease (CDACD) study showed enhanced aortic stiffness and wall thickness in adolescents with various chronic disorders. Enhanced aortic stiffness can increase left ventricular (LV) afterload and trigger a cascade of adverse arterioventricular interaction. Here, we investigate the relation between aortic changes and LV function in the CDACD study participants. Methods: This cross-sectional study included 114 adolescents 12-18 years old with cystic fibrosis (CF, n = 24), corrected coarctation of the aorta (CoA, n = 25), juvenile idiopathic arthritis (JIA, n = 20), obesity (n = 20), and healthy controls (n = 25). Aortic pulse wave velocity (PWV), which reflects aortic stiffness, and aortic wall thickness (AWT) were assessed with cardiovascular magnetic resonance imaging (CMR). Echocardiography was employed to study conventional markers of LV function, as well as LV global longitudinal strain (LVGLS), which is an established (pre)clinical marker of LV dysfunction. Results: First, aortic PWV and AWT were increased in all chronic disease groups, compared to controls. Second, in adolescents with CoA, JIA, and obesity, echocardiography showed a decreased LVGLS, while LV dimensions and conventional LV function markers were similar to controls. Third, multivariable linear regression identified aortic PWV as the most important determinant of their decreased LVGLS (standardized ß -0.522, p < 0.001). Conclusions: The decreased LVGLS in several adolescent chronic disease groups was associated with enhanced aortic PWV, which might reflect adverse arterioventricular interaction. Whether the decreased LVGLS in the chronic disease groups could negatively impact their long-term cardiovascular outcomes requires further study.

From algorithms to action: improving patient care requires causality.

In cancer research there is much interest in building and validating outcome prediction models to support treatment decisions. However, because most outcome prediction models are developed and validated without regard to the causal aspects of treatment decision making, many published outcome prediction models may cause harm when used for decision making, despite being found accurate in validation studies. Guidelines on prediction model validation and the checklist for risk model endorsement by the American Joint Committee on Cancer do not protect against prediction models that are accurate during development and validation but harmful when used for decision making. We explain why this is the case and how to build and validate models that are useful for decision making.

A prediction model for response to immune checkpoint inhibition in advanced melanoma.

Predicting who will benefit from treatment with immune checkpoint inhibition (ICI) in patients with advanced melanoma is challenging. We developed a multivariable prediction model for response to ICI, using routinely available clinical data including primary melanoma characteristics. We used a population-based cohort of 3525 patients with advanced cutaneous melanoma treated with anti-PD-1-based therapy. Our prediction model for predicting response within 6 months after ICI initiation was internally validated with bootstrap resampling. Performance evaluation included calibration, discrimination and internal-external cross-validation. Included patients received anti-PD-1 monotherapy (n = 2366) or ipilimumab plus nivolumab (n = 1159) in any treatment line. The model included serum lactate dehydrogenase, World Health Organization performance score, type and line of ICI, disease stage and time to first distant recurrence-all at start of ICI-, and location and type of primary melanoma, the presence of satellites and/or in-transit metastases at primary diagnosis and sex. The over-optimism adjusted area under the receiver operating characteristic was 0.66 (95% CI: 0.64-0.66). The range of predicted response probabilities was 7%-81%. Based on these probabilities, patients were categorized into quartiles. Compared to the lowest response quartile, patients in the highest quartile had a significantly longer median progression-free survival (20.0 vs 2.8 months; P < .001) and median overall survival (62.0 vs 8.0 months; P < .001). Our prediction model, based on routinely available clinical variables and primary melanoma characteristics, predicts response to ICI in patients with advanced melanoma and discriminates well between treated patients with a very good and very poor prognosis.

Effects of exercise during chemotherapy for breast cancer on long-term cardiovascular toxicity.

OBJECTIVE: Animal data suggest that exercise during chemotherapy is cardioprotective, but clinical evidence to support this is limited. This study evaluated the effect of exercise during chemotherapy for breast cancer on long-term cardiovascular toxicity. METHODS: This is a follow-up study of two previously performed randomised trials in patients with breast cancer allocated to exercise during chemotherapy or non-exercise controls. Cardiac imaging parameters, including T1 mapping (native T1, extracellular volume fraction (ECV)), left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS), cardiorespiratory fitness, and physical activity levels, were acquired 8.5 years post-treatment. RESULTS: In total, 185 breast cancer survivors were included (mean age 58.9±7.8 years), of whom 99% and 18% were treated with anthracyclines and trastuzumab, respectively. ECV and Native T1 were 25.3%±2.5% and 1026±51 ms in the control group, and 24.6%±2.8% and 1007±44 ms in the exercise group, respectively. LVEF was borderline normal in both groups, with an LVEF<50% prevalence of 22.5% (n=40/178) in all participants. Compared with control, native T1 was statistically significantly lower in the exercise group (ß=-20.16, 95% CI -35.35 to -4.97). We found no effect of exercise on ECV (ß=-0.69, 95% CI -1.62 to 0.25), LVEF (ß=-1.36, 95% CI -3.45 to 0.73) or GLS (ß=0.31, 95% CI -0.76 to 1.37). Higher self-reported physical activity levels during chemotherapy were significantly associated with better native T1 and ECV. CONCLUSIONS: In long-term breast cancer survivors, exercise and being more physically active during chemotherapy were associated with better structural but not functional cardiac parameters. The high prevalence of cardiac dysfunction calls for additional research on cardioprotective measures, including alternative exercise regimens. TRIAL REGISTRATION NUMBER: NTR7247.

Combined evaluation of blood flow and tissue perfusion in diabetic feet by intra-arterial dynamic 4DCT imaging.

Critical limb ischemia is associated with high mortality and major amputations. Intra-arterial digital subtraction angiography (IADSA) has been the reference standard but has some shortcomings including the two-dimensional projection and the lack of tissue perfusion information. The aim of this exploratory study is to examine four-dimensional computed tomography (4DCT) angiography and perfusion imaging using low-volume intra-arterial contrast injections for an improved anatomic and hemodynamic assessment in patients with foot ulcers. Three patients underwent a low-volume (2 mL) intra-arterial contrast-enhanced 4DCT examination combined with a diagnostic IADSA. An automated assessment of blood flow and tissue perfusion from the 4DCT data was performed. Vascular structures and corresponding blood flows were successfully assessed and correlated well with the IADSA results. Perfusion values of the affected tissue were significantly higher compared to the unaffected tissue. The proposed 4DCT protocol combined with the minimal usage of contrast agent (2 mL) provides superior images compared to IADSA as three phases (arterial, perfusion, and venous) are captured. The obtained parameters could allow for an improved diagnosis of critical limb ischemia as both the proximal vasculature and the extent of the perfusion deficit in the microvasculature can be assessed.Relevance statementIntra-arterial 4DCT allows for assessing three phases (arterial, perfusion and venous) using minimal contrast (2 mL). This method could lead to an improved diagnosis of critical limb ischemia as both proximal vasculature and the extent of the perfusion deficit are assessed.Trial registrationISRCTN, ISRCTN95737449. Registered 14 March 2023-retrospectively registered, https://www.isrctn.com/ISRCTN95737449 Key points• Three phases (arterial, perfusion, and venous) are obtained from 2 mL intra-arterial 4DCT.• The obtained hemodynamic parameters correlated well with the IADSA findings.• 4DCT surpassed IADSA in terms of assessment of venous blood flow and inflammatory hyperperfusion.• The assessment of tissue perfusion could lead to optimizing the revascularization strategy.

Robustness of pulmonary nodule radiomic features on computed tomography as a function of varying radiation dose levels-a multi-dose in vivo patient study.

OBJECTIVE: Analysis of textural features of pulmonary nodules in chest CT, also known as radiomics, has several potential clinical applications, such as diagnosis, prognostication, and treatment response monitoring. For clinical use, it is essential that these features provide robust measurements. Studies with phantoms and simulated lower dose levels have demonstrated that radiomic features can vary with different radiation dose levels. This study presents an in vivo stability analysis of radiomic features for pulmonary nodules against varying radiation dose levels. METHODS: Nineteen patients with a total of thirty-five pulmonary nodules underwent four chest CT scans at different radiation dose levels (60, 33, 24, and 15 mAs) in a single session. The nodules were manually delineated. To assess the robustness of features, we calculated the intra-class correlation coefficient (ICC). To visualize the effect of milliampere-second variation on groups of features, a linear model was fitted to each feature. We calculated bias and calculated the R2 value as a measure of goodness of fit. RESULTS: A small minority of 15/100 (15%) radiomic features were considered stable (ICC > 0.9). Bias increased and R2 decreased at lower dose, but shape features seemed to be more robust to milliampere-second variations than other feature classes. CONCLUSION: A large majority of pulmonary nodule radiomic features were not inherently robust to radiation dose level variations. For a subset of features, it was possible to correct this variability by a simple linear model. However, the correction became increasingly less accurate at lower radiation dose levels. CLINICAL RELEVANCE STATEMENT: Radiomic features provide a quantitative description of a tumor based on medical imaging such as computed tomography (CT). These features are potentially useful in several clinical tasks such as diagnosis, prognosis prediction, treatment effect monitoring, and treatment effect estimation. KEY POINTS: • The vast majority of commonly used radiomic features are strongly influenced by variations in radiation dose level. • A small minority of radiomic features, notably the shape feature class, are robust against dose-level variations according to ICC calculations. • A large subset of radiomic features can be corrected by a linear model taking into account only the radiation dose level.

CT radiomics compared to a clinical model for predicting checkpoint inhibitor treatment outcomes in patients with advanced melanoma.

INTRODUCTION: Predicting checkpoint inhibitors treatment outcomes in melanoma is a relevant task, due to the unpredictable and potentially fatal toxicity and high costs for society. However, accurate biomarkers for treatment outcomes are lacking. Radiomics are a technique to quantitatively capture tumour characteristics on readily available computed tomography (CT) imaging. The purpose of this study was to investigate the added value of radiomics for predicting clinical benefit from checkpoint inhibitors in melanoma in a large, multicenter cohort. METHODS: Patients who received first-line anti-PD1±anti-CTLA4 treatment for advanced cutaneous melanoma were retrospectively identified from nine participating hospitals. For every patient, up to five representative lesions were segmented on baseline CT, and radiomics features were extracted. A machine learning pipeline was trained on the radiomics features to predict clinical benefit, defined as stable disease for more than 6 months or response per RECIST 1.1 criteria. This approach was evaluated using a leave-one-centre-out cross validation and compared to a model based on previously discovered clinical predictors. Lastly, a combination model was built on the radiomics and clinical model. RESULTS: A total of 620 patients were included, of which 59.2% experienced clinical benefit. The radiomics model achieved an area under the receiver operator characteristic curve (AUROC) of 0.607 [95% CI, 0.562-0.652], lower than that of the clinical model (AUROC=0.646 [95% CI, 0.600-0.692]). The combination model yielded no improvement over the clinical model in terms of discrimination (AUROC=0.636 [95% CI, 0.592-0.680]) or calibration. The output of the radiomics model was significantly correlated with three out of five input variables of the clinical model (p < 0.001). DISCUSSION: The radiomics model achieved a moderate predictive value of clinical benefit, which was statistically significant. However, a radiomics approach was unable to add value to a simpler clinical model, most likely due to the overlap in predictive information learned by both models. Future research should focus on the application of deep learning, spectral CT-derived radiomics, and a multimodal approach for accurately predicting benefit to checkpoint inhibitor treatment in advanced melanoma.

Time interval from primary melanoma to first distant recurrence in relation to patient outcomes in advanced melanoma.

Since the introduction of BRAF(/MEK) inhibition and immune checkpoint inhibition (ICI), the prognosis of advanced melanoma has greatly improved. Melanoma is known for its remarkably long time to first distant recurrence (TFDR), which can be decades in some patients and is partly attributed to immune-surveillance. We investigated the relationship between TFDR and patient outcomes after systemic treatment for advanced melanoma. We selected patients undergoing first-line systemic therapy for advanced melanoma from the nationwide Dutch Melanoma Treatment Registry. The association between TFDR and progression-free survival (PFS) and overall survival (OS) was assessed by Cox proportional hazard regression models. The TFDR was modeled categorically, linearly, and flexibly using restricted cubic splines. Patients received anti-PD-1-based treatment (n = 1844) or BRAF(/MEK) inhibition (n = 1618). For ICI-treated patients with a TFDR <2 years, median OS was 25.0 months, compared to 37.3 months for a TFDR >5 years (P = .014). Patients treated with BRAF(/MEK) inhibition with a longer TFDR also had a significantly longer median OS (8.6 months for TFDR <2 years compared to 11.1 months for >5 years, P = .004). The hazard of dying rapidly decreased with increasing TFDR until approximately 5 years (HR 0.87), after which the hazard of dying further decreased with increasing TFDR, but less strongly (HR 0.82 for a TFDR of 10 years and HR 0.79 for a TFDR of 15 years). Results were similar when stratifying for type of treatment. Advanced melanoma patients with longer TFDR have a prolonged PFS and OS, irrespective of being treated with first-line ICI or targeted therapy.

Incidental findings on routine preoperative noncontrast chest computed tomography and chest radiography prior to cardiac surgery in the multicenter randomized controlled CRICKET study.

OBJECTIVE: To describe the prevalence and consequences of incidental findings when implementing routine noncontrast CT prior to cardiac surgery. METHODS: In the multicenter randomized controlled CRICKET study, 862 adult patients scheduled for cardiac surgery were randomized 1:1 to undergo standard of care (SoC), which included a chest-radiograph, or an additional preoperative noncontrast chest CT-scan (SoC+CT). In this subanalysis, all incidental findings detected on the chest radiograph and CT-scan were analyzed. The influence of smoking status on incidental findings was also evaluated, adjusting for sex, age, and group allocation. RESULTS: Incidental findings were observed in 11.4% (n = 49) of patients in the SoC+CT group and in 3.7% (n = 16) of patients in the SoC-group (p < 0.001). The largest difference was observed in findings requiring follow-up (SoC+CT 7.7% (n = 33) vs SoC 2.3% (n = 10), p < 0.001). Clinically relevant findings changing the surgical approach or requiring specific treatment were observed in 10 patients (1.2%, SoC+CT: 1.6% SoC: 0.7%), including lung cancer in 0.5% of patients (n = 4) and aortic dilatation requiring replacement in 0.2% of patients (n = 2). Incidental findings were more frequent in patients who stopped smoking (OR 1.91, 1.03-3.63) or who actively smoked (OR 3.91, 1.85-8.23). CONCLUSIONS: Routine CT-screening increases the rate of incidental findings, mainly by identifying more pulmonary findings requiring follow-up. Incidental findings are more prevalent in patients with a history of smoking, and preoperative CT might increase the yield of identifying lung cancer in these patients. Incidental findings, but not specifically the use of routine CT, are associated with delay of surgery. KEY POINTS: • Clinically relevant incidental findings are identified more often after a routine preoperative CT-scan, when compared to a standard of care workup, with some findings changing patient management. • Patients with a history of smoking have a higher rate of incidental findings and a lung cancer rate comparable to that of lung cancer screening trials. • We observed no clear delay in the time to surgery when adding routine CT screening.

Imaging to predict checkpoint inhibitor outcomes in cancer. A systematic review.

BACKGROUND: Checkpoint inhibition has radically improved the perspective for patients with metastatic cancer, but predicting who will not respond with high certainty remains difficult. Imaging-derived biomarkers may be able to provide additional insights into the heterogeneity in tumour response between patients. In this systematic review, we aimed to summarise and qualitatively assess the current evidence on imaging biomarkers that predict response and survival in patients treated with checkpoint inhibitors in all cancer types. METHODS: PubMed and Embase were searched from database inception to 29th November 2021. Articles eligible for inclusion described baseline imaging predictive factors, radiomics and/or imaging machine learning models for predicting response and survival in patients with any kind of malignancy treated with checkpoint inhibitors. Risk of bias was assessed using the QUIPS and PROBAST tools and data was extracted. RESULTS: In total, 119 studies including 15,580 patients were selected. Of these studies, 73 investigated simple imaging factors. 45 studies investigated radiomic features or deep learning models. Predictors of worse survival were (i) higher tumour burden, (ii) presence of liver metastases, (iii) less subcutaneous adipose tissue, (iv) less dense muscle and (v) presence of symptomatic brain metastases. Hazard rate ratios did not exceed 2.00 for any predictor in the larger and higher quality studies. The added value of baseline fluorodeoxyglucose positron emission tomography parameters in predicting response to treatment was limited. Pilot studies of radioactive drug tracer imaging showed promising results. Reports on radiomics were almost unanimously positive, but numerous methodological concerns exist. CONCLUSIONS: There is well-supported evidence for several imaging biomarkers that can be used in clinical decision making. Further research, however, is needed into biomarkers that can more accurately identify which patients who will not benefit from checkpoint inhibition. Radiomics and radioactive drug labelling appear to be promising approaches for this purpose.

The Association between Muscle Quantity and Overall Survival Depends on Muscle Radiodensity: A Cohort Study in Non-Small-Cell Lung Cancer Patients.

The prognostic value of CT-derived muscle quantity for overall survival (OS) in patients with non-small-cell lung cancer (NSCLC) is uncertain due to conflicting evidence. We hypothesize that increased muscle quantity is associated with better OS in patients with normal muscle radiodensity but not in patients with fatty degeneration of muscle tissue and low muscle radiodensity. We performed an observational cohort study in NSCLC patients treated with radiotherapy. A deep learning algorithm was used to measure muscle quantity as psoas muscle index (PMI) and psoas muscle radiodensity (PMD) on computed tomography. The potential interaction between PMI and PMD for OS was investigated using Cox proportional-hazards regression. Baseline adjustment variables were age, sex, histology, performance score and body mass index. We investigated non-linear effects of continuous variables and imputed missing values using multiple imputation. We included 2840 patients and observed 1975 deaths in 5903 patient years. The average age was 68.9 years (standard deviation 10.4, range 32 to 96) and 1692 patients (59.6%) were male. PMI was more positively associated with OS for higher values of PMD (hazard ratio for interaction 0.915; 95% confidence interval 0.861-0.972; p-value 0.004). We found evidence that high muscle quantity is associated with better OS when muscle radiodensity is higher, in a large cohort of NSCLC patients treated with radiotherapy. Future studies on the association between muscle status and OS should accommodate this interaction in their analysis for more accurate and more generalizable results.

Preclinical Aortic Atherosclerosis in Adolescents With Chronic Disease.

Background Adolescents with chronic disease are often exposed to inflammatory, metabolic, and hemodynamic risk factors for early atherosclerosis. Since postmortem studies have shown that atherogenesis starts in the aorta, the CDACD (Cardiovascular Disease in Adolescents with Chronic Disease) study investigated preclinical aortic atherosclerosis in these adolescents. Methods and Results The cross-sectional CDACD study enrolled 114 adolescents 12 to 18 years old with chronic disorders including juvenile idiopathic arthritis, cystic fibrosis, obesity, corrected coarctation of the aorta, and healthy controls with a corrected atrial septal defect. Cardiovascular magnetic resonance was used to assess aortic pulse wave velocity and aortic wall thickness, as established aortic measures of preclinical atherosclerosis. Cardiovascular magnetic resonance showed a higher aortic pulse wave velocity, which reflects aortic stiffness, and higher aortic wall thickness in all adolescent chronic disease groups, compared with controls (P<0.05). Age (ß=0.253), heart rate (ß=0.236), systolic blood pressure (ß=-0.264), and diastolic blood pressure (ß=0.365) were identified as significant predictors for aortic pulse wave velocity, using multivariable linear regression analysis. Aortic wall thickness was predicted by body mass index (ß=0.248) and fasting glucose (ß=0.242), next to aortic lumen area (ß=0.340). Carotid intima-media thickness was assessed using ultrasonography, and was only higher in adolescents with coarctation of the aorta, compared with controls (P<0.001). Conclusions Adolescents with chronic disease showed enhanced aortic stiffness and wall thickness compared with controls. The enhanced aortic pulse wave velocity and aortic wall thickness in adolescents with chronic disease could indicate accelerated atherogenesis. Our findings underscore the importance of the aorta for assessment of early atherosclerosis, and the need for tailored cardiovascular follow-up of children with chronic disease.

Safety and feasibility study of non-invasive robot-assisted high-intensity focused ultrasound therapy for the treatment of atherosclerotic plaques in the femoral artery: protocol for a pilot study.

INTRODUCTION: Peripheral arterial disease (PAD) is an atherosclerotic disease leading to stenosis and/or occlusion of the arterial circulation of the lower extremities. The currently available revascularisation methods have an acceptable initial success rate, but the long-term patency is limited, while surgical revascularisation is associated with a relatively high perioperative risk. This urges the need for development of less invasive and more effective treatment modalities. This protocol article describes a study investigating a new non-invasive technique that uses robot assisted high-intensity focused ultrasound (HIFU) to treat atherosclerosis in the femoral artery. METHODS AND ANALYSIS: A pilot study is currently performed in 15 symptomatic patients with PAD with a significant stenosis in the common femoral and/or proximal superficial femoral artery. All patients will be treated with the dual-mode ultrasound array system to deliver imaging-guided HIFU to the atherosclerotic plaque. Safety and feasibility are the primary objectives assessed by the technical feasibility of this therapy and the 30-day major complication rate as primary endpoints. Secondary endpoints are angiographic and clinical success and quality of life. ETHICS AND DISSEMINATION: Ethical approval for this study was obtained in 2019 from the Medical Ethics Committee of the University Medical Center Utrecht, the Netherlands. Data will be presented at national and international conferences and published in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: NL7564.

Individual treatment effect estimation in the presence of unobserved confounding using proxies: a cohort study in stage III non-small cell lung cancer.

Randomized Controlled Trials (RCT) are the gold standard for estimating treatment effects but some important situations in cancer care require treatment effect estimates from observational data. We developed "Proxy based individual treatment effect modeling in cancer" (PROTECT) to estimate treatment effects from observational data when there are unobserved confounders, but proxy measurements of these confounders exist. We identified an unobserved confounder in observational cancer research: overall fitness. Proxy measurements of overall fitness exist like performance score, but the fitness as observed by the treating physician is unavailable for research. PROTECT reconstructs the distribution of the unobserved confounder based on these proxy measurements to estimate the treatment effect. PROTECT was applied to an observational cohort of 504 stage III non-small cell lung cancer (NSCLC) patients, treated with concurrent chemoradiation or sequential chemoradiation. Whereas conventional confounding adjustment methods seemed to overestimate the treatment effect, PROTECT provided credible treatment effect estimates.

4D flow cardiovascular magnetic resonance derived energetics in the Fontan circulation correlate with exercise capacity and CMR-derived liver fibrosis/congestion.

AIM: This study explores the relationship between in vivo 4D flow cardiovascular magnetic resonance (CMR) derived blood flow energetics in the total cavopulmonary connection (TCPC), exercise capacity and CMR-derived liver fibrosis/congestion. BACKGROUND: The Fontan circulation, in which both caval veins are directly connected with the pulmonary arteries (i.e. the TCPC) is the palliative approach for single ventricle patients. Blood flow efficiency in the TCPC has been associated with exercise capacity and liver fibrosis using computational fluid dynamic modelling. 4D flow CMR allows for assessment of in vivo blood flow energetics, including kinetic energy (KE) and viscous energy loss rate (EL). METHODS: Fontan patients were prospectively evaluated between 2018 and 2021 using a comprehensive cardiovascular and liver CMR protocol, including 4D flow imaging of the TCPC. Peak oxygen consumption (VO2) was determined using cardiopulmonary exercise testing (CPET). Iron-corrected whole liver T1 (cT1) mapping was performed as a marker of liver fibrosis/congestion. KE and EL in the TCPC were computed from 4D flow CMR and normalized for inflow. Furthermore, blood flow energetics were compared between standardized segments of the TCPC. RESULTS: Sixty-two Fontan patients were included (53% male, 17.3 ± 5.1 years). Maximal effort CPET was obtained in 50 patients (peak VO2 27.1 ± 6.2 ml/kg/min, 56 ± 12% of predicted). Both KE and EL in the entire TCPC (n = 28) were significantly correlated with cT1 (r = 0.50, p = 0.006 and r = 0.39, p = 0.04, respectively), peak VO2 (r = - 0.61, p = 0.003 and r = - 0.54, p = 0.009, respectively) and % predicted peak VO2 (r = - 0.44, p = 0.04 and r = - 0.46, p = 0.03, respectively). Segmental analysis indicated that the most adverse flow energetics were found in the Fontan tunnel and left pulmonary artery. CONCLUSIONS: Adverse 4D flow CMR derived KE and EL in the TCPC correlate with decreased exercise capacity and increased levels of liver fibrosis/congestion. 4D flow CMR is promising as a non-invasive screening tool for identification of patients with adverse TCPC flow efficiency.

Clinically Significant Incidental Findings on CT Imaging During TAVI Work-up: A Systematic Review and Meta-Analysis.

BACKGROUND: The transcatheter aortic valve implantation (TAVI) population is mostly elderly and frail. Clinically significant incidental findings (SIFs) are commonly encountered in the work-up of TAVI patients. This is a systematic review of current literature on the occurrence of SIFs on computed tomography (CT) imaging preceding TAVI and their association with mortality, delayed planning, and procedure cancellation. METHODS: A systematic search on Medline, Embase, and Cochrane resulted in 19 retrospective studies (published from 2010-2020) reporting SIFs in the work-up for TAVI. A total of 6358 individuals from 19 studies were analyzed, with mean age of 80 years and sex equally divided. A random-effects meta-analysis was performed, with weighting based on study size. RESULTS: Pooled prevalence of patients with SIF was 22.2% (95% confidence interval [CI], 17.8-26.6) and most findings (48.3%) were found in the lungs. Pooled prevalence of new malignancies was 3.4% (95% CI, 2.5-4.4). Higher mortality in patients with SIF was only found in studies with a follow-up period >4 years (hazard ratio, 1.5-1.7). TAVI was more frequently cancelled in patients with SIF vs those with no SIF (ranges, 10.1%-47.1% vs 5.2%-37.0%, respectively). SIF did not delay time to TAVI (ranges, 6-91 days in SIF patients vs 4-81 days in non-SIF patients). CONCLUSION: SIFs are common in patients screened for TAVI. SIF is associated with a higher risk of TAVI cancellation and with increased mortality risk over the long term, which should be taken into consideration in decision making. These findings may help inform patients and aid patient selection.

AI-Based Quantification of Planned Radiation Therapy Dose to Cardiac Structures and Coronary Arteries in Patients With Breast Cancer.

PURPOSE: The purpose of this work is to develop and evaluate an automatic deep learning method for segmentation of cardiac chambers and large arteries, and localization of the 3 main coronary arteries in radiation therapy planning on computed tomography (CT). In addition, a second purpose is to determine the planned radiation therapy dose to cardiac structures for breast cancer therapy. METHODS AND MATERIALS: Eighteen contrast-enhanced cardiac scans acquired with a dual-layer-detector CT scanner were included for method development. Manual reference annotations of cardiac chambers, large arteries, and coronary artery locations were made in the contrast scans and transferred to virtual noncontrast images, mimicking noncontrast-enhanced CT. In addition, 31 noncontrast-enhanced radiation therapy treatment planning CTs with corresponding dose-distribution maps of breast cancer cases were included for evaluation. For reference, cardiac chambers and large vessels were manually annotated in two 2-dimensional (2D) slices per scan (26 scans, totaling 52 slices) and in 3-dimensional (3D) scan volumes in 5 scans. Coronary artery locations were annotated on 3D imaging. The method uses an ensemble of convolutional neural networks with 2 output branches that perform 2 distinct tasks: (1) segmentation of the cardiac chambers and large arteries and (2) localization of coronary arteries. Training was performed using reference annotations and virtual noncontrast cardiac scans. Automatic segmentation of the cardiac chambers and large vessels and the coronary artery locations was evaluated in radiation therapy planning CT with Dice score (DSC) and average symmetrical surface distance (ASSD). The correlation between dosimetric parameters derived from the automatic and reference segmentations was evaluated with R2. RESULTS: For cardiac chambers and large arteries, median DSC was 0.76 to 0.88, and the median ASSD was 0.17 to 0.27 cm in 2D slice evaluation. 3D evaluation found a DSC of 0.87 to 0.93 and an ASSD of 0.07 to 0.10 cm. Median DSC of the coronary artery locations ranged from 0.80 to 0.91. R2 values of dosimetric parameters were 0.77 to 1.00 for the cardiac chambers and large vessels, and 0.76 to 0.95 for the coronary arteries. CONCLUSIONS: The developed and evaluated method can automatically obtain accurate estimates of planned radiation dose and dosimetric parameters for the cardiac chambers, large arteries, and coronary arteries.

Effect of routine preoperative screening for aortic calcifications using noncontrast computed tomography on stroke rate in cardiac surgery: the randomized controlled CRICKET study.

OBJECTIVES: To evaluate if routine screening for aortic calcification using unenhanced CT lowers the risk of stroke and alters the surgical approach in patients undergoing general cardiac surgery compared with standard of care (SoC). METHODS: In this prospective, multicenter, randomized controlled trial, adult patients scheduled for cardiac surgery from September 2014 to October 2019 were randomized 1:1 into two groups: SoC alone, including chest radiography, vs. SoC plus preoperative noncontrast CT. The primary endpoint was in-hospital perioperative stroke. Secondary endpoints were preoperative change of the surgical approach, in-hospital mortality, and postoperative delirium. The trial was halted halfway for expected futility, as the conditional power analysis showed a chance < 1% of finding the hypothesized effect. RESULTS: A total of 862 patients were evaluated (SoC-group: 433 patients (66 ± 11 years; 74.1% male) vs. SoC + CT-group: 429 patients (66 ± 10 years; 69.9% male)). The perioperative stroke rate (SoC + CT: 2.1%, 9/429 vs. SoC: 1.2%, 5/433, p = 0.27) and rate of changed surgical approach (SoC + CT: 4.0% (17/429) vs. SoC: 2.8% (12/433, p = 0.35) did not differ between groups. In-hospital mortality and postoperative delirium were comparable between groups. In the SoC + CT group, aortic calcification was observed on CT in the ascending aorta in 28% (108/380) and in the aortic arch in 70% (265/379). CONCLUSIONS: Preoperative noncontrast CT in cardiac surgery candidates did not influence the surgical approach nor the incidence of perioperative stroke compared with standard of care. Aortic calcification is a frequent finding on the CT scan in these patients but results in major surgical alterations to prevent stroke in only few patients. KEY POINTS: • Aortic calcification is a frequent finding on noncontrast computed tomography prior to cardiac surgery. • Routine use of noncontrast computed tomography does not often lead to a change of the surgical approach, when compared to standard of care. • No effect was observed on perioperative stroke after cardiac surgery when using routine noncontrast computed tomography screening on top of standard of care.

Identification of Risk of Cardiovascular Disease by Automatic Quantification of Coronary Artery Calcifications on Radiotherapy Planning CT Scans in Patients With Breast Cancer.

IMPORTANCE: Cardiovascular disease (CVD) is common in patients treated for breast cancer, especially in patients treated with systemic treatment and radiotherapy and in those with preexisting CVD risk factors. Coronary artery calcium (CAC), a strong independent CVD risk factor, can be automatically quantified on radiotherapy planning computed tomography (CT) scans and may help identify patients at increased CVD risk. OBJECTIVE: To evaluate the association of CAC with CVD and coronary artery disease (CAD) in patients with breast cancer. DESIGN, SETTING, AND PARTICIPANTS: In this multicenter cohort study of 15 915 patients with breast cancer receiving radiotherapy between 2005 and 2016 who were followed until December 31, 2018, age, calendar year, and treatment-adjusted Cox proportional hazard models were used to evaluate the association of CAC with CVD and CAD. EXPOSURES: Overall CAC scores were automatically extracted from planning CT scans using a deep learning algorithm. Patients were classified into Agatston risk categories (0, 1-10, 11-100, 101-399, >400 units). MAIN OUTCOMES AND MEASURES: Occurrence of fatal and nonfatal CVD and CAD were obtained from national registries. RESULTS: Of the 15 915 participants included in this study, the mean (SD) age at CT scan was 59.0 (11.2; range, 22-95) years, and 15 879 (99.8%) were women. Seventy percent (n = 11 179) had no CAC. Coronary artery calcium scores of 1 to 10, 11 to 100, 101 to 400, and greater than 400 were present in 10.0% (n = 1584), 11.5% (n = 1825), 5.2% (n = 830), and 3.1% (n = 497) respectively. After a median follow-up of 51.2 months, CVD risks increased from 5.2% in patients with no CAC to 28.2% in patients with CAC scores higher than 400. After adjustment, CVD risk increased with higher CAC score (hazard ratio [HR]CAC = 1-10 = 1.1; 95% CI, 0.9-1.4; HRCAC = 11-100 = 1.8; 95% CI, 1.5-2.1; HRCAC = 101-400 = 2.1; 95% CI, 1.7-2.6; and HRCAC>400 = 3.4; 95% CI, 2.8-4.2). Coronary artery calcium was particularly strongly associated with CAD (HRCAC>400 = 7.8; 95% CI, 5.5-11.2). The association between CAC and CVD was strongest in patients treated with anthracyclines (HRCAC>400 = 5.8; 95% CI, 3.0-11.4) and patients who received a radiation boost (HRCAC>400 = 6.1; 95% CI, 3.8-9.7). CONCLUSIONS AND RELEVANCE: This cohort study found that coronary artery calcium on breast cancer radiotherapy planning CT scan results was associated with CVD, especially CAD. Automated CAC scoring on radiotherapy planning CT scans may be used as a fast and low-cost tool to identify patients with breast cancer at increased risk of CVD, allowing implementing CVD risk-mitigating strategies with the aim to reduce the risk of CVD burden after breast cancer. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03206333.

Update in imaging of cancer therapy-related cardiac toxicity in adults.

Over the past decades, prognosis of patients with cancer has strongly improved and the number of cancer survivors is rapidly growing. Despite this success, cancer treatment is associated with development of serious cardiovascular diseases including left ventricular (LV) systolic dysfunction, heart failure, valvular disease, myocardial infarction, arrhythmias or pericardial diseases. Serial non-invasive cardiac imaging is an important tool to detect early signs of cardiotoxicity, to allow for timely intervention and provide optimal circumstances for long-term prognosis. Currently, echocardiographic imaging is the method of choice for the evaluation of myocardial function during and after cancer therapy. However, 2D echocardiography may fail to detect subtle changes in myocardial function, potentially resulting in a significant delay of therapeutic intervention to impede advanced cardiac disease states with more overt systolic dysfunction. Strain imaging is a promising method for early detection of myocardial dysfunction and may predict future changes in LV ejection fraction. The use of three-dimensional echocardiography may overcome the limitations of 2D echocardiography with more precise and reproducible measurements of LV performance. Cardiac MRI is the gold standard for volumetric assessment and can also be used to perform myocardial tissue characterisation. Visualisation of oedema and fibrosis may provide insights into the degree and disease course of cardiotoxicity and underlying pathophysiological mechanisms. There is growing body of literature regarding the promising role of these advanced imaging modalities in early detection of cardiotoxicity. With this overview paper, new insights and recent results in literature regarding echocardiographic and cardiac magnetic resonance imaging of cancer therapy-related cardiac dysfunction in post-cancer therapy adults will be highlighted.