18 research outputs found

    Low-Iodine Diet of 4 Days Is Sufficient Preparation for I-131 Therapy in Differentiated Thyroid Cancer Patients

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    CONTEXT: No consensus exists about the optimal duration of the low-iodine diet (LID) in the preparation of (131)I therapy in differentiated thyroid cancer (DTC) patients. OBJECTIVE: This work aimed to investigate if a LID of 4 days is enough to achieve adequate iodine depletion in preparation for (131)I therapy. In addition, the nutritional status of the LID was evaluated. METHODS: In this prospective study, 65 DTC patients treated at 2 university medical centers were included between 2018 and 2021. The patients collected 24-hour urine on days 4 and 7 of the LID and kept a food diary before and during the LID. The primary outcome was the difference between the 24-hour urinary iodine excretion (UIE) on both days. RESULTS: The median 24-hour UIE on days 4 and 7 of the LID were not significantly different (36.1 mcg [interquartile range, 25.4-51.2 mcg] and 36.5 mcg [interquartile range, 23.9-47.7 mcg], respectively, P = .43). On day 4 of the LID, 72.1% of the DTC patients were adequately prepared (24-hour UIE < 50 mcg), and 82.0% of the DTC patients on day 7 (P = .18). Compared to the self-reported regular diet, DTC patients showed a significantly (P < .01) lower percentage of nutrient intake (calories, protein, calcium, iodine, and water) during the LID. CONCLUSION: The 24-hour UIE on day 4 of the LID did not differ from day 7, and therefore shortening the LID from 7 to 4 days seems justified to prepare DTC patients for (131)I therapy in areas with sufficient iodine intake and may be beneficial to maintain a sufficient nutritional intake during DTC treatment

    Extracellular Vesicles in Diagnosing Chronic Coronary Syndromes the Bumpy Road to Clinical Implementation

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    Coronary artery disease (CAD), comprising both acute coronary syndromes (ACS) and chronic coronary syndromes (CCS), remains one of the most important killers throughout the entire world. ACS is often quickly diagnosed by either deviation on an electrocardiogram or elevated levels of troponin, but CCS appears to be more complicated. The most used noninvasive strategies to diagnose CCS are coronary computed tomography and perfusion imaging. Although both show reasonable accuracy (80&ndash;90%), these modalities are becoming more and more subject of debate due to costs, radiation and increasing inappropriate use in low-risk patients. A reliable, blood-based biomarker is not available for CCS but would be of great clinical importance. Extracellular vesicles (EVs) are lipid-bilayer membrane vesicles containing bioactive contents e.g., proteins, lipids and nucleic acids. EVs are often referred to as the &ldquo;liquid biopsy&rdquo; since their contents reflect changes in the condition of the cell they originate from. Although EVs are studied extensively for their role as biomarkers in the cardiovascular field during the last decade, they are still not incorporated into clinical practice in this field. This review provides an overview on EV biomarkers in CCS and discusses the clinical and technological aspects important for successful clinical application of EVs

    Extracellular Vesicles for risk stratification in coronary artery disease: Trash or Treasure

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    Coronary artery disease is caused by atherosclerosis and a typical disease of the elderly. Often the clinical situation is stable for a very long period but it can be disrupted by an acute myocardial infarction (obstructive coronary artery disease), especially if a patients in not on optimal (medical) treatment. All patient suspected of coronary artery disease undergo risk stratification to determine their current and future risk. Currently this stratification process is time consuming and expensive leading to a high burden on our healthcare system. Considering our aging population the need for diagnostic and prognostic risk stratification will increase even more. Extracellular vesicles (EV) are bilayer lipid membrane vesicles that contain bioactive material (RNA, DNA and proteins). With only a small amount of human blood we are able to isolate these vesicles and study their content. It is thought that EV content displays the condition of the mother cell of which they originate from and thereby enable a close look on cellular level. We investigated the protein content of extracellular vesicles as biomarker source to improve the risk stratification of patients suspected of coronary artery disease. Additionally to our projects regarding the EVs we studied another method to improve risk stratification. Coronary artery calcification (CAC) scores are known as one of the best prognostic factors for adequate risk stratification. For this a dedicated ECG triggered CT is made. The downside of coronary CT is that it is not possible to reliable determine perfusion defects, which is also an import factor in determining a patients current risk of having obstructive coronary artery disease. We know from studies that a combined approach results in an improved risk stratification, however this currently involves additional scanning and subsequently radiation exposure. In the second part of this thesis we studied a deep learning method to automatically determine the CAC score on CT images acquired for perfusion imaging

    Extracellular vesicles in diagnosing chronic coronary syndromes—the bumpy road to clinical implementation

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    Coronary artery disease (CAD), comprising both acute coronary syndromes (ACS) and chronic coronary syndromes (CCS), remains one of the most important killers throughout the entire world. ACS is often quickly diagnosed by either deviation on an electrocardiogram or elevated levels of troponin, but CCS appears to be more complicated. The most used noninvasive strategies to diagnose CCS are coronary computed tomography and perfusion imaging. Although both show reasonable accuracy (80–90%), these modalities are becoming more and more subject of debate due to costs, radiation and increasing inappropriate use in low‐risk patients. A reliable, blood‐based biomarker is not available for CCS but would be of great clinical importance. Extracellular vesicles (EVs) are lipid‐bilayer membrane vesicles containing bioactive contents e.g., proteins, lipids and nucleic acids. EVs are often referred to as the “liquid biopsy” since their contents reflect changes in the condition of the cell they originate from. Although EVs are studied extensively for their role as biomarkers in the cardiovascular field during the last decade, they are still not incorporated into clinical practice in this field. This review provides an overview on EV biomarkers in CCS and discusses the clinical and technological aspects important for successful clinical application of EVs

    Ceramides and phospholipids in plasma extracellular vesicles are associated with high risk of major cardiovascular events after carotid endarterectomy

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    Ceramides and phosphatidylcholines (PCs) are bioactive lipids and lipid bilayer membrane components. Distinct ceramides/PCs (ratios) predict cardiovascular outcome in patients with coronary artery disease. Extracellular vesicles (EVs) are proposed biomarkers for cardiovascular disease and contain ceramides/PCs. Ceramides/PCs have not been studied in patients undergoing carotid endarterectomy (CEA) nor in EVs. We therefore investigated whether levels of ceramides/PCs in plasma and EVs are associated with postoperative risk of major adverse cardiovascular events (MACE) following CEA. In 873 patients undergoing CEA of the Athero-Express biobank, we quantitatively measured seven ceramides/PCs in preoperative blood samples: Cer(d18:1/16:0), Cer(d18:1/18:0), Cer(d18:1/24:0), Cer(d18:1/24:1), PC(14:0/22:6), PC(16:0/16:0) and PC(16:0/22:5) in plasma and two plasma EV-subfractions (LDL and TEX). We analyzed the association of ceramides, PCs and their predefined ratios with the three-year postoperative risk of MACE (including stroke, myocardial infarction and cardiovascular death). A total of 138 patients (16%) developed MACE during the three-year follow-up. In the LDL-EV subfraction, higher levels of Cer(d18:1/24:1) and Cer(d18:1/16:0)/PC(16:0/22:5) ratio were significantly associated with an increased risk of MACE (adjusted HR per SD [95% CI] 1.24 [1.01–1.53] and 1.26 [1.04–1.52], respectively). In the TEX-EV subfraction, three ratios Cer(d18:1/16:0)/Cer(d18:1/24:0), Cer(d18:1/18:0)/Cer(d18:1/24:0) and Cer(d18:1/24:1)/Cer(d18:1/24:0) were positively associated with MACE (adjusted HR per SD 1.34 [1.06–1.70], 1.24 [1.01–1.51] and 1.31 [1.08–1.58], respectively). In conclusion, distinct ceramides and PCs in plasma EVs determined in preoperative blood were independently associated with an increased 3-year risk of MACE after CEA. These lipids are therefore potential markers to identify high-risk CEA patients qualifying for secondary preventive add-on therapy

    Ceramides and phospholipids in plasma extracellular vesicles are associated with high risk of major cardiovascular events after carotid endarterectomy

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    Ceramides and phosphatidylcholines (PCs) are bioactive lipids and lipid bilayer membrane components. Distinct ceramides/PCs (ratios) predict cardiovascular outcome in patients with coronary artery disease. Extracellular vesicles (EVs) are proposed biomarkers for cardiovascular disease and contain ceramides/PCs. Ceramides/PCs have not been studied in patients undergoing carotid endarterectomy (CEA) nor in EVs. We therefore investigated whether levels of ceramides/PCs in plasma and EVs are associated with postoperative risk of major adverse cardiovascular events (MACE) following CEA. In 873 patients undergoing CEA of the Athero-Express biobank, we quantitatively measured seven ceramides/PCs in preoperative blood samples: Cer(d18:1/16:0), Cer(d18:1/18:0), Cer(d18:1/24:0), Cer(d18:1/24:1), PC(14:0/22:6), PC(16:0/16:0) and PC(16:0/22:5) in plasma and two plasma EV-subfractions (LDL and TEX). We analyzed the association of ceramides, PCs and their predefined ratios with the three-year postoperative risk of MACE (including stroke, myocardial infarction and cardiovascular death). A total of 138 patients (16%) developed MACE during the three-year follow-up. In the LDL-EV subfraction, higher levels of Cer(d18:1/24:1) and Cer(d18:1/16:0)/PC(16:0/22:5) ratio were significantly associated with an increased risk of MACE (adjusted HR per SD [95% CI] 1.24 [1.01–1.53] and 1.26 [1.04–1.52], respectively). In the TEX-EV subfraction, three ratios Cer(d18:1/16:0)/Cer(d18:1/24:0), Cer(d18:1/18:0)/Cer(d18:1/24:0) and Cer(d18:1/24:1)/Cer(d18:1/24:0) were positively associated with MACE (adjusted HR per SD 1.34 [1.06–1.70], 1.24 [1.01–1.51] and 1.31 [1.08–1.58], respectively). In conclusion, distinct ceramides and PCs in plasma EVs determined in preoperative blood were independently associated with an increased 3-year risk of MACE after CEA. These lipids are therefore potential markers to identify high-risk CEA patients qualifying for secondary preventive add-on therapy.publishedVersionPeer reviewe

    High lipoprotein(a) is associated with major adverse limb events after femoral artery endarterectomy

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    Backgrounds and aims: Elevated lipoprotein(a) (Lp[a]) has been identified as a causal risk factor for cardiovascular disease including peripheral arterial disease (PAD). Although Lp(a) is associated with the diagnosis of PAD, it remains elusive whether there is an association of Lp(a) with cardiovascular and limb events in patients with severe PAD. Methods: Preoperative plasma Lp(a) levels were measured in 384 consecutive patients that underwent iliofemoral endarterectomy and were included in the Athero-Express biobank. Our primary objective was to assess the association of Lp(a) levels with Major Adverse Limb Events (MALE). Our secondary objective was to relate Lp(a) levels to Major Adverse Cardiovascular Events (MACE) and femoral plaque composition that was acquired from baseline surgery. Results: During a median follow-up time of 5.6 years, a total of 225 MALE were recorded in 132 patients. Multivariable analysis, including history of peripheral intervention, age, diabetes mellitus, end stage renal disease and PAD disease stages, showed that Lp(a) was independently associated with first (HR of 1.36 (95% CI 1.02–1.82) p = .036) and recurrent MALE (HR 1.36 (95% CI 1.10–1.67) p = .004). A total of 99 MACE were recorded but Lp(a) levels were not associated with MACE.sLp(a) levels were significantly associated with a higher presence of smooth muscle cells in the femoral plaque, although this was not associated with MALE or MACE. Conclusions: Plasma Lp(a) is independently associated with first and consecutive MALE after iliofemoral endarterectomy. Hence, in patients who undergo iliofemoral endarterectomy, Lp(a) could be considered as a biomarker to enhance risk stratification for future MALE

    Automated calcium scores collected during myocardial perfusion imaging improve identification of obstructive coronary artery disease

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    Background: Myocardial perfusion imaging (MPI) is an accurate noninvasive test for patients with suspected obstructive coronary artery disease (CAD) and coronary artery calcium (CAC) score is known to be a powerful predictor of cardiovascular events. Collection of CAC scores simultaneously with MPI is unexplored. Aim: We aimed to investigate whether automatically derived CAC scores during myocardial perfusion imaging would further improve the diagnostic accuracy of MPI to detect obstructive CAD. Methods: We analyzed 150 consecutive patients without a history of coronary revascularization with suspected obstructive CAD who were referred for 82Rb PET/CT and available coronary angiographic data. Myocardial perfusion was evaluated both semi quantitatively as well as quantitatively according to the European guidelines. CAC scores were automatically derived from the low-dose attenuation correction CT scans using previously developed software based on deep learning. Obstructive CAD was defined as stenosis >70% (or >50% in the left main coronary artery) and/or fractional flow reserve (FFR) ≤0.80. Results: In total 58% of patients had obstructive CAD of which seventy-four percent were male. Addition of CAC scores to MPI and clinical predictors significantly improved the diagnostic accuracy of MPI to detect obstructive CAD. The area under the curve (AUC) increased from 0.87 to 0.91 (p: 0.025). Sensitivity and specificity analysis showed an incremental decrease in false negative tests with our MPI + CAC approach (n = 14 to n = 4), as a consequence an increase in false positive tests was seen (n = 11 to n = 28). Conclusion: CAC scores collected simultaneously with MPI improve the detection of obstructive coronary artery disease in patients without a history of coronary revascularization

    The prognostic value of automated coronary calcium derived by a deep learning approach on non-ECG gated CT images from 82Rb-PET/CT myocardial perfusion imaging

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    Background: Assessment of both coronary artery calcium(CAC) scores and myocardial perfusion imaging(MPI) in patients suspected of coronary artery disease(CAD) provides incremental prognostic information. We used an automated method to determine CAC scores on low-dose attenuation correction CT(LDACT) images gathered during MPI in one single assessment. The prognostic value of this automated CAC score is unknown, we therefore investigated the association of this automated CAC scores and major adverse cardiovascular events(MACE) in a large chest-pain cohort. Method: We analyzed 747 symptomatic patients referred for 82RubidiumPET/CT, without a history of coronary revascularization. Ischemia was defined as a summed difference score≥2. We used a validated deep learning(DL) method to determine CAC scores. For survival analysis CAC scores were dichotomized as low(90 days after scanning) or nonfatal myocardial infarction. Cox proportional hazard analysis were performed to identify predictors of MACE. Results: During 4 years follow-up, 115 MACEs were observed. High CAC scores showed higher cumulative event rates, irrespective of ischemia (nonischemic: 25.8% vs 11.9% and ischemic: 57.6% vs 23.4%, P-values <0.001). Multivariable cox regression revealed both high CAC scores (HR 2.19 95%CI 1.43–3.35) and ischemia (HR 2.56 95%CI 1.71–3.35) as independent predictors of MACE. Addition of automated CAC scores showed a net reclassification improvement of 0.13(0.022–0.245). Conclusion: Automatically derived CAC scores determined during a single imaging session are independently associated with MACE. This validated DL method could improve risk stratification and subsequently lead to more personalized treatment in patients suspected of CAD

    Automated calcium scores collected during myocardial perfusion imaging improve identification of obstructive coronary artery disease

    No full text
    Background: Myocardial perfusion imaging (MPI) is an accurate noninvasive test for patients with suspected obstructive coronary artery disease (CAD) and coronary artery calcium (CAC) score is known to be a powerful predictor of cardiovascular events. Collection of CAC scores simultaneously with MPI is unexplored. Aim: We aimed to investigate whether automatically derived CAC scores during myocardial perfusion imaging would further improve the diagnostic accuracy of MPI to detect obstructive CAD. Methods: We analyzed 150 consecutive patients without a history of coronary revascularization with suspected obstructive CAD who were referred for 82Rb PET/CT and available coronary angiographic data. Myocardial perfusion was evaluated both semi quantitatively as well as quantitatively according to the European guidelines. CAC scores were automatically derived from the low-dose attenuation correction CT scans using previously developed software based on deep learning. Obstructive CAD was defined as stenosis >70% (or >50% in the left main coronary artery) and/or fractional flow reserve (FFR) ≤0.80. Results: In total 58% of patients had obstructive CAD of which seventy-four percent were male. Addition of CAC scores to MPI and clinical predictors significantly improved the diagnostic accuracy of MPI to detect obstructive CAD. The area under the curve (AUC) increased from 0.87 to 0.91 (p: 0.025). Sensitivity and specificity analysis showed an incremental decrease in false negative tests with our MPI + CAC approach (n = 14 to n = 4), as a consequence an increase in false positive tests was seen (n = 11 to n = 28). Conclusion: CAC scores collected simultaneously with MPI improve the detection of obstructive coronary artery disease in patients without a history of coronary revascularization
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