Multiparametric Cardiac Magnetic Resonance Assessment in Sickle Beta Thalassemia.

Cardiac involvement in sickle beta thalassemia (Sß-thal) patients has been poorly investigated. We aimed to evaluate cardiac function and myocardial iron overload by cardiovascular magnetic resonance (CMR) in patients with Sß-thal. One-hundred and eleven Sß-thal patients consecutively enrolled in the Myocardial Iron Overload in Thalassemia (MIOT) network were studied and compared with 46 sickle cell anemia (SCA) patients and with 111 gender- and age- matched healthy volunteers. Cine images were acquired to quantify biventricular function. Myocardial iron overload (MIO) was assessed by the T2* technique, while macroscopic myocardial fibrosis was evaluated by the late gadolinium enhancement (LGE) technique. In Sß-thal and SCA patients, the morphological and functional CMR parameters were not significantly different, except for the left atrial area and left ventricular (LV) stroke volume, indexed by body surface area (p = 0.023 and p = 0.048, respectively), which were significantly higher in SCA patients. No significant differences between the two groups were found in terms of myocardial iron overload and macroscopic myocardial fibrosis. When compared to healthy subjects, Sß-thal patients showed significantly higher bi-atrial and biventricular parameters, except for LV ejection fraction, which was significantly lower. The CMR analysis confirmed that Sß-thal and SCA patients are phenotypically similar. Since Sß-thal patients showed markedly different morphological and functional indices from healthy subjects, it would be useful to identify Sß-thal/SCA-specific bi-atrial and biventricular reference values.

Impact of the COVID-19 Pandemic on Iron Overload Assessment by MRI in Patients with Hemoglobinopathies: The E-MIOT Network Experience.

BACKGROUND: The E-MIOT (Extension-Myocardial Iron Overload in Thalassemia) project is an Italian Network assuring high-quality quantification of tissue iron overload by magnetic resonance imaging (MRI). We evaluated the impact of the COVID-19 pandemic on E-MIOT services. METHODS: The activity of the E-MIOT Network MRI centers in the year 2020 was compared with that of 2019. A survey evaluated whether the availability of MRI slots for patients with hemoglobinopathies was reduced and why. RESULTS: The total number of MRI scans was 656 in 2019 and 350 in 2020, with an overall decline of 46.4% (first MRI: 71.7%, follow-up MRI: 36.9%), a marked decline (86.9%) in the period March-June 2020, and a reduction in the gap between the two years in the period July-September. A new drop (41.4%) was recorded in the period October-December for two centers, due to the general reduction in the total amount of MRIs/day for sanitization procedures. In some centers, patients refused MRI scans for fear of getting COVID. Drops in the MRI services >80% were found for patients coming from a region without an active MRI site. CONCLUSIONS: The COVID-19 pandemic had a strong negative impact on MRI multi-organ iron quantification, with a worsening in the management of patients with hemoglobinopathies.

Quantitative T2* MRI for bone marrow iron overload: normal reference values and assessment in thalassemia major patients.

PURPOSE: We evaluated the feasibility and reproducibility of bone marrow T2* values and established the lower limit of normal in a cohort of healthy subjects. We investigated the clinical correlates of bone marrow T2* values in patients with thalassemia major (TM). MATERIAL AND METHODS: Thirty healthy subjects and 274 consecutive TM patients (38.96 ± 8.49 years, 151 females) underwent MRI at 1.5T. An axial slice in the upper abdomen was acquired by a T2* gradient-echo multiecho sequence and the T2* value was calculated in a circular region of interest defined in the visible body of the first or second lumbar vertebra. In patients, also liver and heart T2* values were assessed. RESULTS: In healthy subjects bone marrow T2* values were independent of age and gender. The lower limit of normal for bone marrow T2* was 13 ms. In both healthy subjects and 30 randomly selected patients, the coefficient of variation for inter-operator-reproducibility was < 10%. TM patients exhibited significantly lower bone marrow T2* values than healthy subjects (7.47 ± 5.18 ms vs. 17.08 ± 1.89 ms; p < 0.0001). A pathological bone marrow T2* was detected in 82.8% of TM patients. In TM, the female sex was associated with reduced bone marrow T2* values. Bone marrow T2* values were inversely correlated with mean serum ferritin levels (R = -0.431; P < 0.0001) and hepatic iron load (R = - 0.215; P < 0.0001). A serum ferritin level > 536 ng/ml predicted the presence of a pathological bone marrow T2*. A positive correlation was found between bone marrow and heart T2* values (R = 0.143; P = 0.018). A normal bone marrow T2* showed a negative predictive value of 100% for cardiac iron. CONCLUSION: Bone marrow T2* measurements can be easily obtained using the same sequences acquired for liver iron quantification and may bring new insights into the pathophysiology of iron deposition; hence, they should be incorporated into clinical practice.

Simultaneous Functional and Morphological Assessment of Left Atrial Appendage by 3D Virtual Models.

Purpose: The left atrial appendage (LAA) is responsible for thrombus formation in patients with atrial fibrillation. The evaluation of both LAA function and morphology is crucial for the patient characterization and the preprocedural planning of LAA closure intervention. Despite the availability of 3D imaging modalities, the current standard image analysis is based on manual delineation of the LAA contours on 2D views. Methods: In this study, a comprehensive approach based on a full 3D analysis of the tomographic dataset by surface extraction and processing (3D-S) is presented. The proposed method allows extracting functional and morphologic information in the entire cardiac cycle by minimalizing manual user interaction. The proposed methodology has been validated on ten computer tomography datasets. Results: The proposed 3D-S method was feasible in all cases. Reproducibility was improved with respect to the reference 2D manual procedure (2D-S) (coefficient of variation 2.9 vs. 4.1% for diastolic ostium area; 3.8 vs. 6.1% for systolic ostium area; 2.4 vs. 5.3% for diastolic LAA volume; 2.7 vs. 5.9% for systolic LAA volume; and 7.7 vs. 17.1% for LAA ejection fraction). No significant differences were found between 2D-S and 3D-S measurements. Conclusions: In this study, we introduced a fully 3D approach for LAA characterization, allowing the simultaneous assessment of LAA function and geometry. The proposed approach could be used to improve the patient selection and the best sizing of the device for LAA closure and to allow a patient-specific 3D printing.

Estimation of pancreatic R2* for iron overload assessment in the presence of fat: a comparison of different approaches.

OBJECTIVES: To propose a method for estimating pancreatic relaxation rate, R2*, from conventional multi-echo MRI, based on the nonlinear fitting of the acquired magnitude signal decay to MR signal models that take into account both the signal oscillations induced by fat and the different R2* values of pancreatic parenchyma and fat. MATERIALS AND METHODS: Single-peak fat (SPF) and multi-peak fat (MPF) models were introduced. Single-R2* and dual-R2* assumptions were considered as well. Analyses were conducted on simulated data and 20 thalassemia major patients. RESULTS: Simulations revealed the ability of the MPF model to correctly estimate the R2* value in a large range of fat fractions and R2* values. From the comparison between the results obtained with a single R2* value for water and fat and the dual-R2* approach, the latter is more accurate in both water R2* and fat fraction estimation. In patient's data analysis, a strong concordance was found between SPF and MPF estimated data with measurements done with manual signal correction and from fat-saturated images. The MPF method showed better reproducibility. CONCLUSION: The MPF dual-R2* approach improves reproducibility and reduces image analysis time in the assessment of pancreatic R2* value in patients with iron overload.

Non-compact myocardium assessment by cardiac magnetic resonance: dependence on image analysis method.

To compare image analysis methods for the assessment of left ventricle non-compaction from cardiac magnetic resonance (CMR) imaging. CMR images were analyzed in 20 patients and 10 normal subjects. A reference model of the MR signal was introduced and validated based on image data. Non-compact (NC) myocardium size and distribution were assessed by tracing a single, continuous contour delimiting trabeculated region (Jacquier) or by one-by-one selection of trabeculae (Grothoff). The global non-compact/compact (NC/C) ratio, the NC mass, and the segmental NC/C ratio were assessed. Results were compared with the reference model. A significant difference between Grothoff and Jacquier approaches in the estimation of NC/C ratio (32.08 ± 6.63 vs. 19.81 ± 5.72, p < 0.0001) and NC mass (26.59 ± 8.36 vs. 14.15 ± 5.73 g/m2, p < 0.0001) was found. The Grothoff approach better matches the expected signal distribution. Inter-observer reproducibility of both Grothoff and Jacquier methods was adequate (9.71 and 8.22%, respectively) with no significant difference between observers. Jacquier and Grothoff approaches are not interchangeable so that specific diagnostic thresholds should be used for different image analysis methods. Grothoff method seems to better capture the true extension of trabeculated tissue.

A modular informatics platform for effective support of collaborative and multicenter studies in cardiology.

Collaborative and multicenter studies permit a large number of patients to be enrolled within a reasonable time and providing the opportunity to collect different data. Informatics platforms play an important role in management, storage, and exchange of data between the participants involved in the study. In this article, we describe a modular informatics platform designed and developed to support collaborative and multicenter studies in cardiology. In each developed module, data management is implemented following local defined protocols. The modular characteristic of the developed platform allows independent transfer of different kinds of data, such as biological samples, imaging raw data, and patients' digital information. Moreover, it offers safe central storage of the data collected during the study. The developed platform was successfully tested during a European collaborative and multicenter study, focused on evaluating multimodal non-invasive imaging to diagnose and characterize ischemic heart disease.

Quantitative T2* magnetic resonance imaging for renal iron overload assessment: normal values by age and sex.

PURPOSE: Few studies of renal iron content have been performed with multiecho gradient-echo (ME-GRE) T2* magnetic resonance imaging (MRI). We assessed the feasibility and reproducibility of ME-GRE T2* MRI for measuring regional and global renal T2* values, and established the lower limits of normal in healthy subjects, also correlating the measured values with age and sex. METHODS: Twenty consecutive healthy subjects (13 men and 7 women, mean age 29.1 ± 7.2 years, range 19-42 years) underwent MRI examinations using a 1.5 T magnet and an ME-GRE T2* sequence. For each kidney, T2* was measured in anterior, posterolateral, and posteromedial renal parenchymal regions. The mean T2* value was calculated as the average of the two kidneys T2* values. RESULTS: For the mean kidney T2* value, the coefficients of variation for intra- and inter-operator reproducibility were 1.76% and 6.23%, respectively. The lower limit of normal for the mean kidney T2* value was 31 ms (median 51.39 ± 10.09). There was no significant difference between left and right kidney T2* values (p = 0.578). No significant correlation was found between T2* values and subjects' age or sex. CONCLUSIONS: Renal ME-GRE T2* appears to be a feasible and reproducible technique. The renal T2* values showed no dependence on sex or age.

How the signal-to-noise ratio influences hyperpolarized 13C dynamic MRS data fitting and parameter estimation.

MRS of hyperpolarized (13) C-labeled compounds represents a promising technique for in vivo metabolic studies. However, robust quantification and metabolic modeling are still important areas of investigation. In particular, time and spatial resolution constraints may lead to the analysis of MRS signals with low signal-to-noise ratio (SNR). The relationship between SNR and the precision of quantitative analysis for the evaluation of the in vivo kinetic behavior of metabolites is unknown. In this article, this topic is addressed by Monte Carlo simulations, covering the problem of MRS signal model parameter estimation, with strong emphasis on the peak amplitude and kinetic model parameters. The results of Monte Carlo simulation were confirmed by in vivo experiments on medium-sized animals injected with hyperpolarized [1-(13) C]pyruvate. The results of this study may be useful for the establishment of experimental planning and for the optimization of kinetic model estimation as a function of the SNR value.

Regional and global pancreatic T*2 MRI for iron overload assessment in a large cohort of healthy subjects: normal values and correlation with age and gender.

Multiecho gradient-echo T*2 magnetic resonance imaging is a well-established technique for iron overload assessment but there are few reports concerning the pancreas. The aim of this work was to assess the feasibility and reproducibility of the magnetic resonance imaging for measuring pancreatic regional and global T*2 values, to establish the lower limit of normal in a large cohort of healthy subjects and to correlate the measured values with age and gender. One hundred and twenty healthy subjects (61 males, 51±17 years) underwent magnetic resonance imaging (1.5T) using a multiecho gradient-echo T*2 sequence. T*2 measurements were performed in pancreatic head, body, and tail. The global value was calculated as the mean. Measurement of pancreatic T*2 values was feasible in all subjects. For the T*2 global value the coefficient of variation for intraoperator and interoperator reproducibility were 7.7% and 13%, respectively. The global T*2 values ranged from 24 to 52 ms with the lower limit of normal of 26 ms. There were no significant differences among the regional pancreatic T*2 values. No significant correlation was found between T*2 and patient age or gender. In conclusion, pancreatic T*2 measurements appear to be feasible, reproducible, nontime-consuming and reliable. Gender- and age-related differences concerning pancreatic T*2 were not found.

Registration of myocardial PET and SPECT for viability assessment using mutual information.

PURPOSE: The combination of sequentially acquired cardiac PET and SPECT data integrating metabolic and perfusion information allows the assessment of myocardial viability, a relevant clinical parameter for the management of patients who have suffered myocardial infarction and are now candidates for complex and cost intensive therapies such as bypass surgery. However, registration of cardiac functional datasets acquired on different imaging systems is limited by the difficulty to define anatomical landmarks and by the relatively poor inherent spatial resolution. In this article, the authors sought to evaluate whether it is possible to automatically register FDG-PET and sestamibi-SPECT cardiac data. METHODS: Automatic rigid registration was implemented with the ITK framework using Mattes mutual information as the similarity measure and a quaternion to represent the rotational component. The goodness of the alignment was evaluated by computing the mean target registration error (mTRE) at the myocardial wall. The registration parameters were optimized for robustness and speed using the data from 11 cardiac patients undergoing both PET and SPECT examinations (training datasets). The optimized algorithm was applied on the PET and SPECT data from 11 further patients (evaluation datasets). Quantitative (mTRE calculation) and visual (scoring method) comparisons were performed between automatic and manual registrations. Moreover, the automatic registration was also compared to the registration implicitly defined in the standard clinical analysis. RESULTS: The registration parameters were successfully optimized and resulted in a mean mTRE of 1.13 mm and 1.2 s average runtime on standard computer hardware for the training datasets. Automatic registration in the 11 validation datasets resulted in an average mTRE of 2.3 mm, with 7.5 mm mTRE in the worst case and an average runtime of 1.6 s. Automatic registration outperformed manual registrations both for the mTRE and for the visual assessment. Automatic registration also resulted in higher accuracy and better visual assessment as compared to the registration implicitly performed in the standard clinical analysis. CONCLUSIONS: The results demonstrate the possibility to successfully perform mutual information based registration of PET and SPECT cardiac data, allowing an improved workflow for the sequentially acquired cardiac datasets, in general, and specifically for the assessment of myocardial viability.

Improved T2* assessment in liver iron overload by magnetic resonance imaging.

In the clinical MRI practice, it is common to assess liver iron overload by T2* multi-echo gradient-echo images. However, there is no full consensus about the best image analysis approach for the T2* measurements. The currently used methods involve manual drawing of a region of interest (ROI) within MR images of the liver. Evaluation of a representative liver T2* value is done by fitting an appropriate model to the signal decay within the ROIs vs. the echo time. The resulting T2* value may depend on both ROI placement and choice of the signal decay model. The aim of this study was to understand how the choice of the analysis methodology may affect the accuracy of T2* measurements. A software model of the iron overloaded liver was inferred from MR images acquired from 40 thalassemia major patients. Different image analysis methods were compared exploiting the developed software model. Moreover, a method for global semiautomatic T2* measurement involving the whole liver was developed. The global method included automatic segmentation of parenchyma by an adaptive fuzzy-clustering algorithm able to compensate for signal inhomogeneities. Global liver T2* value was evaluated using a pixel-wise technique and an optimized signal decay model. The global approach was compared with the ROI-based approach used in the clinical practice. For the ROI-based approach, the intra-observer and inter-observer coefficients of variation (CoVs) were 3.7% and 5.6%, respectively. For the global analysis, the CoVs for intra-observers and inter-observers reproducibility were 0.85% and 2.87%, respectively. The variability shown by the ROI-based approach was acceptable for use in the clinical practice; however, the developed global method increased the accuracy in T2* assessment and significantly reduced the operator dependence and sampling errors. This global approach could be useful in the clinical arena for patients with borderline liver iron overload and/or requiring follow-up studies.

Automatic correction of intensity inhomogeneities improves unsupervised assessment of abdominal fat by MRI.

PURPOSE: To demonstrate that unsupervised assessment of abdominal adipose tissue distribution by magnetic resonance imaging (MRI) can be improved by integrating automatic correction of signal inhomogeneities. MATERIALS AND METHODS: Twenty subjects (body mass index [BMI] 23.7-44.0 kg/m(2)) underwent abdominal (32 slices) MR imaging with a 1.9T Elscint Prestige scanner. Many images were affected by relevant intensity distortions. Unsupervised segmentation of subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) was performed by a previously validated algorithm exploiting standard fuzzy clustering segmentation. Images were also processed by an improved version of the software, including automatic correction of intensity inhomogeneities. To assess the effectiveness of the two methods SAT and VAT volumes were compared with manual analysis performed by a trained operator. RESULTS: Coefficient of variation between manual and unsupervised analysis was significantly improved by inhomogeneities correction in SAT evaluation. Systematic underestimation of SAT was also corrected. A less important performance improvement was found in VAT measurement. CONCLUSION: The results of this study suggest that the compensation of signal inhomogeneities greatly improves the effectiveness of the unsupervised assessment of abdominal fat. Correction of intensity distortions is important in SAT evaluation and less significant in VAT measurement.

A robust method for assessment of iron overload in liver by magnetic resonance imaging.

Assessment of iron overload in liver by T2* magnetic resonance imaging (MRI) is a widely used clinical procedure. In the common clinical practice, measurement is performed locally by manually drawing a small region of interest in liver. This procedure may be affected by a noticeable intra- and inter-observer variability. In this study, a new approach is proposed that performs a global semiautomatic measurement of T2* involving the whole liver extension. Parenchyma is automatically segmented by an adaptive fuzzy-clustering algorithm. The liver T2* global value is evaluated using a pixel-wise approach by introducing an appropriate signal decay model. The proposed method was tested on a synthetic software model and on MR images acquired from 30 thalassemia major patients. The methods was demonstrated to increase the measure precision in T2* assessment and to significantly reduce the intra- and inter-observer variability.

An accurate and robust method for unsupervised assessment of abdominal fat by MRI.

PURPOSE: To describe and evaluate an automatic and unsupervised method for assessing the quantity and distribution of abdominal adipose tissue by MRI. MATERIAL AND METHODS: A total of 20 patients underwent whole-abdomen MRI. A total of 32 transverse T1-weighted images were acquired from each subject. The data collected were transferred to a dedicated workstation and analyzed by both our unsupervised method and a manual procedure. The proposed methodology allows the automatic processing of MRI axial images, segmenting the adipose tissue by fuzzy clustering approach. The use of an active contour algorithm on image masks provided by the fuzzy clustering algorithm allows the separation of subcutaneous fat from visceral fat. Finally, an automated procedure based on automatic image histogram analysis identifies the visceral fat. RESULTS: The accuracy, reproducibility, and speed of our automatic method were compared with the state-of-the-art manual approach. The unsupervised analysis correlated well with the manual analysis, and was significantly faster than manual tracing. Moreover, the unsupervised method was not affected by intraobserver and interobserver variability. CONCLUSION: The results obtained demonstrate that the proposed method can provide the volume of subcutaneous adipose tissue, visceral adipose tissue, global adipose tissue, and the ratio between subcutaneous and visceral fat in an unsupervised and effective manner.