Global longitudinal strain by CMR improves prognostic stratification in acute myocarditis presenting with normal LVEF.

BACKGROUND: Prognostic stratification of acute myocarditis (AM) presenting with normal left ventricular ejection fraction (LVEF) relies mostly on late gadolinium enhancement (LGE) characterization. Left ventricular peak global longitudinal strain (LV-GLS) measured by feature tracking analysis might improve prognostication of AM presenting with normal LVEF. METHODS: Data of patients undergoing cardiac magnetic resonance (CMR) for clinically suspected AM in seven European Centres (2013-2020) were retrospectively analysed. Patients with AM confirmed by CMR and LVEF ≥50% were included. LGE was visually characterized: localized versus. non-localized, subepicardial versus midwall. LV-GLS was measured by dedicated software. The primary outcome was the first occurrence of an adverse cardiovascular event (ACE) including cardiac death, life-threatening arrhythmias, development of heart failure or of LVEF <50%. RESULTS: Of 389 screened patients, 256 (66%) fulfilled inclusion criteria: median age 36 years, 71% males, median LVEF 60%, median LV-GLS -17.3%. CMR was performed at 4 days from hospitalization. At 27 months, 24 (9%) patients experienced ≥1 ACE (71% developed LVEF <50%). Compared to the others, they had lower median LV-GLS values (-13.9% vs. -17.5%, p = .001). At Kaplan-Meier analysis, impaired LV-GLS (both considered as > -20% or quartiles), non-localized and midwall LGE were associated with ACEs. Patients with LV-GLS ≤-20% did not experience ACEs. LV-GLS remained associated with ACEs after adjustment for non-localized and midwall LGE. CONCLUSION: In AM presenting with LVEF ≥50%, LV-GLS provides independent prognostic value over LGE characterization, improving risk stratification and representing a rationale for further studies of therapy in this cohort.

Precision measurement of cardiac structure and function in cardiovascular magnetic resonance using machine learning.

BACKGROUND: Measurement of cardiac structure and function from images (e.g. volumes, mass and derived parameters such as left ventricular (LV) ejection fraction [LVEF]) guides care for millions. This is best assessed using cardiovascular magnetic resonance (CMR), but image analysis is currently performed by individual clinicians, which introduces error. We sought to develop a machine learning algorithm for volumetric analysis of CMR images with demonstrably better precision than human analysis. METHODS: A fully automated machine learning algorithm was trained on 1923 scans (10 scanner models, 13 institutions, 9 clinical conditions, 60,000 contours) and used to segment the LV blood volume and myocardium. Performance was quantified by measuring precision on an independent multi-site validation dataset with multiple pathologies with n = 109 patients, scanned twice. This dataset was augmented with a further 1277 patients scanned as part of routine clinical care to allow qualitative assessment of generalization ability by identifying mis-segmentations. Machine learning algorithm ('machine') performance was compared to three clinicians ('human') and a commercial tool (cvi42, Circle Cardiovascular Imaging). FINDINGS: Machine analysis was quicker (20 s per patient) than human (13 min). Overall machine mis-segmentation rate was 1 in 479 images for the combined dataset, occurring mostly in rare pathologies not encountered in training. Without correcting these mis-segmentations, machine analysis had superior precision to three clinicians (e.g. scan-rescan coefficients of variation of human vs machine: LVEF 6.0% vs 4.2%, LV mass 4.8% vs. 3.6%; both P < 0.05), translating to a 46% reduction in required trial sample size using an LVEF endpoint. CONCLUSION: We present a fully automated algorithm for measuring LV structure and global systolic function that betters human performance for speed and precision.

Identification of a Multiplex Biomarker Panel for Hypertrophic Cardiomyopathy Using Quantitative Proteomics and Machine Learning.

Hypertrophic cardiomyopathy (HCM) is defined by pathological left ventricular hypertrophy (LVH). It is the commonest inherited cardiac condition and a significant number of high risk cases still go undetected until a sudden cardiac death (SCD) event. Plasma biomarkers do not currently feature in the assessment of HCM disease progression, which is tracked by serial imaging, or in SCD risk stratification, which is based on imaging parameters and patient/family history. There is a need for new HCM plasma biomarkers to refine disease monitoring and improve patient risk stratification. To identify new plasma biomarkers for patients with HCM, we performed exploratory myocardial and plasma proteomics screens and subsequently developed a multiplexed targeted liquid chromatography-tandem/mass spectrometry-based assay to validate the 26 peptide biomarkers that were identified. The association of discovered biomarkers with clinical phenotypes was prospectively tested in plasma from 110 HCM patients with LVH (LVH+ HCM), 97 controls, and 16 HCM sarcomere gene mutation carriers before the development of LVH (subclinical HCM). Six peptides (aldolase fructose-bisphosphate A, complement C3, glutathione S-transferase omega 1, Ras suppressor protein 1, talin 1, and thrombospondin 1) were increased significantly in the plasma of LVH+ HCM compared with controls and correlated with imaging markers of phenotype severity: LV wall thickness, mass, and percentage myocardial scar on cardiovascular magnetic resonance imaging. Using supervised machine learning (ML), this six-biomarker panel differentiated between LVH+ HCM and controls, with an area under the curve of ≥ 0.87. Five of these peptides were also significantly increased in subclinical HCM compared with controls. In LVH+ HCM, the six-marker panel correlated with the presence of nonsustained ventricular tachycardia and the estimated five-year risk of sudden cardiac death. Using quantitative proteomic approaches, we have discovered six potentially useful circulating plasma biomarkers related to myocardial substrate changes in HCM, which correlate with the estimated sudden cardiac death risk.

Prevalence of Subclinical Coronary Artery Disease in Masters Endurance Athletes With a Low Atherosclerotic Risk Profile.

BACKGROUND: Studies in middle-age and older (masters) athletes with atherosclerotic risk factors for coronary artery disease report higher coronary artery calcium (CAC) scores compared with sedentary individuals. Few studies have assessed the prevalence of coronary artery disease in masters athletes with a low atherosclerotic risk profile. METHODS: We assessed 152 masters athletes 54.4±8.5 years of age (70% male) and 92 controls of similar age, sex, and low Framingham 10-year coronary artery disease risk scores with an echocardiogram, exercise stress test, computerized tomographic coronary angiogram, and cardiovascular magnetic resonance imaging with late gadolinium enhancement and a 24-hour Holter. Athletes had participated in endurance exercise for an average of 31±12.6 years. The majority (77%) were runners, with a median of 13 marathon runs per athlete. RESULTS: Most athletes (60%) and controls (63%) had a normal CAC score. Male athletes had a higher prevalence of atherosclerotic plaques of any luminal irregularity (44.3% versus 22.2%; P=0.009) compared with sedentary males, and only male athletes showed a CAC ≥300 Agatston units (11.3%) and a luminal stenosis ≥50% (7.5%). Male athletes demonstrated predominantly calcific plaques (72.7%), whereas sedentary males showed predominantly mixed morphology plaques (61.5%). The number of years of training was the only independent variable associated with increased risk of CAC >70th percentile for age or luminal stenosis ≥50% in male athletes (odds ratio, 1.08; 95% confidence interval, 1.01-1.15; P=0.016); 15 (14%) male athletes but none of the controls revealed late gadolinium enhancement on cardiovascular magnetic resonance imaging. Of these athletes, 7 had a pattern consistent with previous myocardial infarction, including 3(42%) with a luminal stenosis ≥50% in the corresponding artery. CONCLUSIONS: Most lifelong masters endurance athletes with a low atherosclerotic risk profile have normal CAC scores. Male athletes are more likely to have a CAC score >300 Agatston units or coronary plaques compared with sedentary males with a similar risk profile. The significance of these observations is uncertain, but the predominantly calcific morphology of the plaques in athletes indicates potentially different pathophysiological mechanisms for plaque formation in athletic versus sedentary men. Coronary plaques are more abundant in athletes, whereas their stable nature could mitigate the risk of plaque rupture and acute myocardial infarction.

Diagnostic performance of T1 and T2 mapping to detect intramyocardial hemorrhage in reperfused ST-segment elevation myocardial infarction (STEMI) patients.

PURPOSE: To investigate the performance of T1 and T2 mapping to detect intramyocardial hemorrhage (IMH) in ST-segment elevation myocardial infarction (STEMI) patients treated by primary percutaneous coronary intervention (PPCI). MATERIALS AND METHODS: Fifty STEMI patients were prospectively recruited between August 2013 and July 2014 following informed consent. Forty-eight patients completed a 1.5T cardiac magnetic resonance imaging (MRI) with native T1 , T2 , and T2* maps at 4 ± 2 days. Receiver operating characteristic (ROC) analyses were performed to assess the performance of T1 and T2 to detect IMH. RESULTS: The mean age was 59 ± 13 years old and 88% (24/48) were male. In all, 39 patients had interpretable T2* maps and 26/39 (67%) of the patients had IMH ( T2* <20 msec on T2* maps). Both T1 and T2 values of the hypointense core within the area-at-risk (AAR) performed equally well to detect IMH (T1 maps AUC 0.86 [95% confidence interval [CI] 0.72-0.99] versus T2 maps AUC 0.86 [95% CI 0.74-0.99]; P = 0.94). Using the binary assessment of presence or absence of a hypointense core on the maps, the diagnostic performance of T1 and T2 remained equally good (T1 AUC 0.87 [95% CI 0.73-1.00] versus T2 AUC 0.85 [95% CI 0.71-0.99]; P = 0.90) with good sensitivity and specificity (T1 : 88% and 85% and T2 : 85% and 85%, respectively). CONCLUSION: The presence of a hypointense core on the T1 and T2 maps can detect IMH equally well and with good sensitivity and specificity in reperfused STEMI patients and could be used as an alternative when T2* images are not acquired or are not interpretable. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:877-886.

Blood correction reduces variability and gender differences in native myocardial T1 values at 1.5 T cardiovascular magnetic resonance - a derivation/validation approach.

BACKGROUND: Myocardial native T1 measurements are likely influenced by intramyocardial blood. Since blood T1 is both variable and longer compared to myocardial T1, this will degrade the precision of myocardial T1 measurements. Precision could be improved by correction, but the amount of correction and the optimal blood T1 variables to correct with are unknown. We hypothesized that an appropriate correction would reduce the standard deviation (SD) of native myocardial T1. METHODS: Consecutive patients (n = 400) referred for CMR with known or suspected heart disease were split into a derivation cohort for model construction (n = 200, age 51 ± 18 years, 50% male) and a validation cohort for assessing model performance (n = 200, age 48 ± 17 years, 50% male). Exclusion criteria included focal septal abnormalities. A Modified Look-Locker inversion recovery sequence (MOLLI, 1.5 T Siemens Aera) was used to acquire T1 and T1* maps. T1 and T1* maps were used to measure native myocardial T1, and blood T1 and T1*. A multivariate linear regression correction model was implemented using blood measurement of R1 (1/T1), R1* (1/T1*) or hematocrit. The correction model from the derivation cohort was applied to the validation cohort, and assessed for reduction in variability with the F-test. RESULTS: Blood [LV + RV] mean R1, mean R1* and hematocrit correlated with myocardial T1 (Pearson's r, range 0.37 to 0.45, p < 0.05 for all) in both the derivation and validation cohorts respectively, suggesting that myocardial T1 measurements are influenced by intramyocardial blood. Mean myocardial native T1 did not differ between the derivation and validation cohorts (1030 ± 42.6 ms and 1023 ± 45.2 ms respectively, p = 0.07). In the derivation cohort, correction using blood mean R1 and mean R1* yielded a decrease in myocardial T1 SD (45.2 ms to 36.6 ms, p = 0.03). When the model from the derivation cohort was applied to the validation cohort, the SD reduction was maintained (39.3 ms, p = 0.049). This 13% reduction in measurement variability leads to a 23% reduction in sample size to detect a 50 ms difference in native myocardial T1. CONCLUSIONS: Correcting native myocardial T1 for R1 and R1* of blood improves the precision of myocardial T1 measurement by ~13%, and could consequently improve disease detection and reduce sample size needs for clinical research.

Defining left ventricular remodeling following acute ST-segment elevation myocardial infarction using cardiovascular magnetic resonance.

BACKGROUND: The assessment of post-myocardial infarction (MI) left ventricular (LV) remodeling by cardiovascular magnetic resonance (CMR) currently uses criteria defined by echocardiography. Our aim was to provide CMR criteria for assessing LV remodeling following acute MI. METHODS: Firstly, 40 reperfused ST-segment elevation myocardial infarction (STEMI) patients with paired acute (4 ± 2 days) and follow-up (5 ± 2 months) CMR scans were analyzed by 2 independent reviewers and the minimal detectable changes (MDCs) for percentage change in LV end-diastolic volume (%ΔLVEDV), LV end-systolic volume (%ΔLVESV), and LV ejection fraction (%ΔLVEF) between the acute and follow-up scans were determined. Secondly, in 146 reperfused STEMI patients, receiver operator characteristic curve analyses for predicting LVEF <50% at follow-up (as a surrogate for clinical poor clinical outcome) were undertaken to obtain cut-off values for %ΔLVEDV and %ΔLVESV. RESULTS: The MDCs for %ΔLVEDV, %ΔLVESV, and %ΔLVEF were similar at 12%, 12%, 13%, respectively. The cut-off values for predicting LVEF < 50% at follow-up were 11% for %ΔLVEDV on receiver operating characteristic curve analysis (area under the curve (AUC) 0.75, 95% CI 0.6 to 0.83, sensitivity 72% specificity 70%), and 5% for %ΔLVESV (AUC 0.83, 95% CI 0.77 to 0.90, sensitivity and specificity 78%). Using cut-off MDC values (higher than the clinically important cut-off values) of 12% for both %ΔLVEDV and %ΔLVESV, 4 main patterns of LV remodeling were identified in our cohort: reverse LV remodeling (LVEF predominantly improved); no LV remodeling (LVEF predominantly unchanged); adverse LV remodeling with compensation (LVEF predominantly improved); and adverse LV remodeling (LVEF unchanged or worsened). CONCLUSIONS: The MDCs for %ΔLVEDV and %ΔLVESV between the acute and follow-up CMR scans of 12% each may be used to define adverse or reverse LV remodeling post-STEMI. The MDC for %ΔLVEF of 13%, relative to baseline, provides the minimal effect size required for investigating treatments aimed at improving LVEF following acute STEMI.

A case report in cardiovascular magnetic resonance: the contrast agent matters in amyloid.

BACKGROUND: Cardiac amyloidosis is a progressive but underdiagnosed and underappreciated cause of heart failure. In the last few years, cardiovascular magnetic resonance (CMR) has become the gold standard for non invasive diagnosis of cardiac amyloidosis with the characteristic subendocardial late gadolinium enhancement. CASE PRESENTATION: We describe a case of a patient who, in the process of aligning protocols for a trial between different centers, had a paired study with two different contrast agents, Dotarem® and MultiHance®. MultiHance® surprisingly failed to demonstrate the characteristic imaging pattern, showing only non specific late gadolinium enhancement at the inferior right ventricular insertion point and different myocardial extracellular volume fraction compared to the one obtained with Dotarem®. MultiHance® is used by many centres, because its partial blood protein binding is a strength for MR angiography, but late gadolinium enhancement, particularly non-ischemic, appears to be compromised. CONCLUSIONS: This case report suggests that contrast agents should be selected with caution, especially with new therapies lining up for amyloid and CMR being used as exploratory end point in clinical trials.

Prognostic Value of Late Gadolinium Enhancement Cardiovascular Magnetic Resonance in Cardiac Amyloidosis.

BACKGROUND: The prognosis and treatment of the 2 main types of cardiac amyloidosis, immunoglobulin light chain (AL) and transthyretin (ATTR) amyloidosis, are substantially influenced by cardiac involvement. Cardiovascular magnetic resonance with late gadolinium enhancement (LGE) is a reference standard for the diagnosis of cardiac amyloidosis, but its potential for stratifying risk is unknown. METHODS AND RESULTS: Two hundred fifty prospectively recruited subjects, 122 patients with ATTR amyloid, 9 asymptomatic mutation carriers, and 119 patients with AL amyloidosis, underwent LGE cardiovascular magnetic resonance. Subjects were followed up for a mean of 24±13 months. LGE was performed with phase-sensitive inversion recovery (PSIR) and without (magnitude only). These were compared with extracellular volume measured with T1 mapping. PSIR was superior to magnitude-only inversion recovery LGE because PSIR always nulled the tissue (blood or myocardium) with the longest T1 (least gadolinium). LGE was classified into 3 patterns: none, subendocardial, and transmural, which were associated with increasing amyloid burden as defined by extracellular volume (P<0.0001), with transitions from none to subendocardial LGE at an extracellular volume of 0.40 to 0.43 (AL) and 0.39 to 0.40 (ATTR) and to transmural at 0.48 to 0.55 (AL) and 0.47 to 0.59 (ATTR). Sixty-seven patients (27%) died. Transmural LGE predicted death (hazard ratio, 5.4; 95% confidence interval, 2.1-13.7; P<0.0001) and remained independent after adjustment for N-terminal pro-brain natriuretic peptide, ejection fraction, stroke volume index, E/E', and left ventricular mass index (hazard ratio, 4.1; 95% confidence interval, 1.3-13.1; P<0.05). CONCLUSIONS: There is a continuum of cardiac involvement in systemic AL and ATTR amyloidosis. Transmural LGE is determined reliably by PSIR and represents advanced cardiac amyloidosis. The PSIR technique provides incremental information on outcome even after adjustment for known prognostic factors.

T1 mapping and T2 mapping at 3T for quantifying the area-at-risk in reperfused STEMI patients.

BACKGROUND: Whether T1-mapping cardiovascular magnetic resonance (CMR) can accurately quantify the area-at-risk (AAR) as delineated by T2 mapping and assess myocardial salvage at 3T in reperfused ST-segment elevation myocardial infarction (STEMI) patients is not known and was investigated in this study. METHODS: 18 STEMI patients underwent CMR at 3T (Siemens Bio-graph mMR) at a median of 5 (4-6) days post primary percutaneous coronary intervention using native T1 (MOLLI) and T2 mapping (WIP #699; Siemens Healthcare, UK). Matching short-axis T1 and T2 maps covering the entire left ventricle (LV) were assessed by two independent observers using manual, Otsu and 2 standard deviation thresholds. Inter- and intra-observer variability, correlation and agreement between the T1 and T2 mapping techniques on a per-slice and per patient basis were assessed. RESULTS: A total of 125 matching T1 and T2 mapping short-axis slices were available for analysis from 18 patients. The acquisition times were identical for the T1 maps and T2 maps. 18 slices were excluded due to suboptimal image quality. Both mapping sequences were equally prone to susceptibility artifacts in the lateral wall and were equally likely to be affected by microvascular obstruction requiring manual correction. The Otsu thresholding technique performed best in terms of inter- and intra-observer variability for both T1 and T2 mapping CMR. The mean myocardial infarct size was 18.8 ± 9.4 % of the LV. There was no difference in either the mean AAR (32.3 ± 11.5 % of the LV versus 31.6 ± 11.2 % of the LV, P = 0.25) or myocardial salvage index (0.40 ± 0.26 versus 0.39 ± 0.27, P = 0.20) between the T1 and T2 mapping techniques. On a per-slice analysis, there was an excellent correlation between T1 mapping and T2 mapping in the quantification of the AAR with an R(2) of 0.95 (P < 0.001), with no bias (mean ± 2SD: bias 0.0 ± 9.6 %). On a per-patient analysis, the correlation and agreement remained excellent with no bias (R(2) 0.95, P < 0.0001, bias 0.7 ± 5.1 %). CONCLUSIONS: T1 mapping CMR at 3T performed as well as T2 mapping in quantifying the AAR and assessing myocardial salvage in reperfused STEMI patients, thereby providing an alternative CMR measure of the the AAR.

Free-breathing T2* mapping using respiratory motion corrected averaging.

BACKGROUND: Pixel-wise T2* maps based on breath-held segmented image acquisition are prone to ghost artifacts in instances of poor breath-holding or cardiac arrhythmia. Single shot imaging is inherently immune to ghost type artifacts. We propose a free-breathing method based on respiratory motion corrected single shot imaging with averaging to improve the signal to noise ratio. METHODS: Images were acquired using a multi-echo gradient recalled echo sequence and T2* maps were calculated at each pixel by exponential fitting. For 40 subjects (2 cohorts), two acquisition protocols were compared: (1) a breath-held, segmented acquisition, and (2) a free-breathing, single-shot multiple repetition respiratory motion corrected average. T2* measurements in the interventricular septum and liver were compared for the 2-methods in all studies with diagnostic image quality. RESULTS: In cohort 1 (N = 28) with age 51.4 ± 17.6 (m ± SD) including 1 subject with severe myocardial iron overload, there were 8 non-diagnostic breath-held studies due to poor image quality resulting from ghost artifacts caused by respiratory motion or arrhythmias. In cohort 2 (N = 12) with age 30.9 ± 7.5 (m ± SD), including 7 subjects with severe myocardial iron overload and 4 subjects with mild iron overload, a single subject was unable to breath-hold. Free-breathing motion corrected T2* maps were of diagnostic quality in all 40 subjects. T2* measurements were in excellent agreement (In cohort #1, T2*FB = 0.95 x T2*BH + 0.41, r2 = 0.93, N = 39 measurements, and in cohort #2, T2*FB = 0.98 x T2*BH + 0.05, r2 > 0.99, N = 22 measurements). CONCLUSIONS: A free-breathing approach to T2* mapping is demonstrated to produce consistently good quality maps in the presence of respiratory motion and arrhythmias.

Myocardial T1 mapping.

Cardiovascular magnetic resonance is a well-established tool for the quantification of focal fibrosis. With the introduction of T1 mapping, diffuse myocardial processes can be detected and quantified. In particular, infiltration and storage disorders with large disease-related changes, and diffuse fibrosis where measurement is harder but the potential impact larger. This has added a new dimension to the understanding and assessment of various myocardial diseases. T1 mapping promises to detect early disease, quantify disease severity and provide prognostic insights into certain conditions. It also has the potential to be a robust surrogate marker in drug development trials to monitor therapeutic response and be a prognostic marker in certain diseases. T1 mapping is an evolving field and numerous factors currently preclude its standardization. In this review, we describe the current status of T1 mapping and its potential promises and pitfalls.

Baseline white blood cell count is an independent predictor of long-term cardiovascular mortality in patients with non-ST-segment elevation acute coronary syndrome, but it does not improve the risk classification of the GRACE score.

OBJECTIVES: To investigate the prognostic significance of baseline white blood cell count (WBCc) in non-ST-segment elevation acute coronary syndrome (NSTE-ACS) and its additive predictive value beyond the Global Registry of Acute Coronary Events (GRACE) score. METHODS: We included 1,315 consecutive NSTE-ACS patients. Patients were divided in quartiles according to the WBCc (cells per 1 mm(3)) i.e. Q1 <6,850, Q2 = 6,850-8,539, Q3 = 8,540-10,857 and Q4 ≥10,858. The study end point was 3-year cardiovascular death (CVD). RESULTS: The median age of the study population was 76 years. Overall, 335 patients (25.5%) died with 211 of these (16%) suffering from CVD. Patients in Q4 showed a higher cumulative probability of CVD compared to patients in Q1-Q3. On multivariable analysis, patients in Q4 were at higher risk of CVD [hazard ratio (HR) = 1.47, 95% confidence interval (CI) 1.09-1.98, p = 0.011]. WBCc as a continuous variable was also independently associated with the study end point (HR = 1.043; 95% CI 1.02-1.07; p = 0.001). However, the incorporation of WBCc into the GRACE score did not improve either prediction of risk (C-index = 0.796 for GRACE score with or without WBCc) or classification of risk [relative integrated discrimination improvement = 0.0154, 95% CI) -0.029 to 0.0618; continuous net reclassification improvement = -0.0676, 95% CI -0.2149-0.0738). CONCLUSIONS: WBCc was an independent predictor of 3-year CVD in patients with NSTE-ACS. However, it did not add prognostic information beyond the GRACE score.

Pericardial Fluid Analysis in Diagnosis and Prognosis of Patients Who Underwent Pericardiocentesis.

In this study, we aimed to examine the diagnostic yield of pericardial fluid biochemistry and cytology and their prognostic significance in patients with percutaneously drained pericardial effusions, with and without malignancy. This is a single-center, retrospective study of patients who underwent pericardiocentesis between 2010 and 2020. Data were extracted from electronic patient records, including procedural information, underlying diagnosis, and laboratory results. Patients were grouped into those with and without underlying malignancy. A Cox proportional hazards model was used to analyze the association of variables with mortality. The study included 179 patients; 50% had an underlying malignancy. There were no significant differences in pericardial fluid protein and lactate dehydrogenase between the 2 groups. Diagnostic yield from pericardial fluid analysis was greater in the malignant group (32% vs 11%, p = 0.002); 72% of newly diagnosed malignancies had positive fluid cytology. The 1-year survival was 86% and 33% in nonmalignant and malignant groups, respectively (p <0.001). Of 17 patients who died within the nonmalignant group, idiopathic effusions were the largest group (n = 6). In malignancy, lower pericardial fluid protein and higher serum C-reactive protein were associated with increased risk of mortality. In conclusion, pericardial fluid biochemistry has limited value in determining the etiology of pericardial effusions; fluid cytology is the most important diagnostic test. Mortality in malignant pericardial effusions may be associated with lower pericardial fluid protein levels and a higher serum C-reactive protein. Nonmalignant pericardial effusions do not have a benign prognosis and close follow-up is required.

Improved Diagnostic Criteria for Apical Hypertrophic Cardiomyopathy.

BACKGROUND: There is no acceptable maximum wall thickness (MWT) threshold for diagnosing apical hypertrophic cardiomyopathy (ApHCM), with guidelines referring to ≥15 mm MWT for all hypertrophic cardiomyopathy subtypes. A normal myocardium naturally tapers apically; a fixed diagnostic threshold fails to account for this. Using cardiac magnetic resonance, "relative" ApHCM has been described with typical electrocardiographic features, loss of apical tapering, and cavity obliteration but also with MWT <15 mm. OBJECTIVES: The authors aimed to define normal apical wall thickness thresholds in healthy subjects and use these to accurately identify ApHCM. METHODS: The following healthy subjects were recruited: healthy UK Biobank imaging substudy subjects (n = 4,112) and an independent healthy volunteer group (n = 489). A clinically defined disease population of 104 ApHCM subjects was enrolled, with 72 overt (MWT ≥15 mm) and 32 relative (MWT <15 mm but typical electrocardiographic/imaging findings) ApHCM subjects. Cardiac magnetic resonance-derived MWT was measured in 16 segments using a published clinically validated machine learning algorithm. Segmental normal reference ranges were created and indexed (for age, sex, and body surface area), and diagnostic performance was assessed. RESULTS: In healthy cohorts, there was no clinically significant age-related difference for apical wall thickness. There were sex-related differences, but these were not clinically significant after indexing to body surface area. Therefore, segmental reference ranges for apical hypertrophy required indexing to body surface area only (not age or sex). The upper limit of normal (the largest of the 4 apical segments measured) corresponded to a maximum apical MWT in healthy subjects of 5.2 to 5.6 mm/m2 with an accuracy of 0.94 (the unindexed equivalent being 11 mm). This threshold was categorized as abnormal in 99% (71/72) of overt ApHCM patients, 78% (25/32) of relative ApHCM patients, 3% (122/4,112) of UK Biobank subjects, and 3% (13/489) of healthy volunteers. CONCLUSIONS: Per-segment indexed apical wall thickness thresholds are highly accurate for detecting apical hypertrophy, providing confidence to the reader to diagnose ApHCM in those not reaching current internationally recognized criteria.