AcquisitionFocus: Joint Optimization of Acquisition Orientation and Cardiac Volume Reconstruction Using Deep Learning.

In cardiac cine imaging, acquiring high-quality data is challenging and time-consuming due to the artifacts generated by the heart's continuous movement. Volumetric, fully isotropic data acquisition with high temporal resolution is, to date, intractable due to MR physics constraints. To assess whole-heart movement under minimal acquisition time, we propose a deep learning model that reconstructs the volumetric shape of multiple cardiac chambers from a limited number of input slices while simultaneously optimizing the slice acquisition orientation for this task. We mimic the current clinical protocols for cardiac imaging and compare the shape reconstruction quality of standard clinical views and optimized views. In our experiments, we show that the jointly trained model achieves accurate high-resolution multi-chamber shape reconstruction with errors of <13 mm HD95 and Dice scores of >80%, indicating its effectiveness in both simulated cardiac cine MRI and clinical cardiac MRI with a wide range of pathological shape variations.

Light-Sheet Imaging to Reveal Cardiac Structure in Rodent Hearts.

Light-sheet microscopy (LSM) plays a pivotal role in comprehending the intricate three-dimensional (3D) structure of the heart, providing crucial insights into fundamental cardiac physiology and pathologic responses. We hereby delve into the development and implementation of the LSM technique to elucidate the micro-architecture of the heart in mouse models. The methodology integrates a customized LSM system with tissue clearing techniques, mitigating light scattering within cardiac tissues for volumetric imaging. The combination of conventional LSM with image stitching and multiview deconvolution approaches allows for the capture of the entire heart. To address the inherent trade-off between axial resolution and field of view (FOV), we further introduce an axially swept light-sheet microscopy (ASLM) method to minimize out-of-focus light and uniformly illuminate the heart across the propagation direction. In the meanwhile, tissue clearing methods such as iDISCO enhance light penetration, facilitating the visualization of deep structures and ensuring a comprehensive examination of the myocardium throughout the entire heart. The combination of the proposed LSM and tissue clearing methods presents a promising platform for researchers in resolving cardiac structures in rodent hearts, holding great potential for the understanding of cardiac morphogenesis and remodeling.

Intracortical brain-heart interplay: An EEG model source study of sympathovagal changes.

The interplay between cerebral and cardiovascular activity, known as the functional brain-heart interplay (BHI), and its temporal dynamics, have been linked to a plethora of physiological and pathological processes. Various computational models of the brain-heart axis have been proposed to estimate BHI non-invasively by taking advantage of the time resolution offered by electroencephalograph (EEG) signals. However, investigations into the specific intracortical sources responsible for this interplay have been limited, which significantly hampers existing BHI studies. This study proposes an analytical modeling framework for estimating the BHI at the source-brain level. This analysis relies on the low-resolution electromagnetic tomography sources localization from scalp electrophysiological recordings. BHI is then quantified as the functional correlation between the intracortical sources and cardiovascular dynamics. Using this approach, we aimed to evaluate the reliability of BHI estimates derived from source-localized EEG signals as compared with prior findings from neuroimaging methods. The proposed approach is validated using an experimental dataset gathered from 32 healthy individuals who underwent standard sympathovagal elicitation using a cold pressor test. Additional resting state data from 34 healthy individuals has been analysed to assess robustness and reproducibility of the methodology. Experimental results not only confirmed previous findings on activation of brain structures affecting cardiac dynamics (e.g., insula, amygdala, hippocampus, and anterior and mid-cingulate cortices) but also provided insights into the anatomical bases of brain-heart axis. In particular, we show that the bidirectional activity of electrophysiological pathways of functional brain-heart communication increases during cold pressure with respect to resting state, mainly targeting neural oscillations in the δ $$ \delta $$ , ß $$ \beta $$ , and γ $$ \gamma $$ bands. The proposed approach offers new perspectives for the investigation of functional BHI that could also shed light on various pathophysiological conditions.

Manifold-based denoising for Ferumoxytol-enhanced 3D cardiac cine MRI.

The two-dimensional (2D) cine cardiovascular magnetic resonance (CMR) technique is the reference standard for assessing cardiac function. However, one challenge with 2D cine is that the acquisition time for the whole cine stack is long and requires multiple breath holds, which may not be feasible for pediatric or ill patients. Though single breath-hold multi-slice cine may address the issue, it can only acquire low-resolution images, and hence, affect the accuracy of cardiac function assessment. To address these challenges, a Ferumoxytol-enhanced, free breathing, isotropic high-resolution 3D cine technique was developed. The method produces high-contrast cine images with short acquisition times by using compressed sensing together with a manifold-based method for image denoising. This study included fifteen patients (9.1 $ \pm $ 5.6 yrs.) who were referred for clinical cardiovascular magnetic resonance imaging (MRI) with Ferumoxytol contrast and were prescribed the 3D cine sequence. The data was acquired on a 1.5T scanner. Statistical analysis shows that the manifold-based denoised 3D cine can accurately measure ventricular function with no significant differences when compared to the conventional 2D breath-hold (BH) cine. The multiplanar reconstructed images of the proposed 3D cine method are visually comparable to the golden standard 2D BH cine method in terms of clarity, contrast, and anatomical precision. The proposed method eliminated the need for breath holds, reduced scan times, enabled multiplanar reconstruction within an isotropic data set, and has the potential to be used as an effective tool to access cardiovascular conditions.

3D whole heart k-space-based super-resolution cardiac T1 mapping using rotated stacks.

Objective. To provide three-dimensional (3D) whole-heart high-resolution isotropic cardiac T1 maps using a k-space-based through-plane super-resolution reconstruction (SRR) with rotated multi-slice stacks.Approach. Due to limited SNR and cardiac motion, often only 2D T1 maps with low through-plane resolution (4-8 mm) can be obtained. Previous approaches used SRR to calculate 3D high-resolution isotropic cardiac T1 maps. However, they were limited to the ventricles. The proposed approach acquires rotated stacks in long-axis orientation with high in-plane resolution but low through-plane resolution. This results in radially overlapping stacks from which high-resolution T1 maps of the whole heart are reconstructed using a k-space-based SRR framework considering the complete acquisition model. Cardiac and residual respiratory motion between different breath holds is estimated and incorporated into the reconstruction. The proposed approach was evaluated in simulations and phantom experiments and successfully applied to ten healthy subjects.Main results. 3D T1 maps of the whole heart were obtained in the same acquisition time as previous methods covering only the ventricles. T1 measurements were possible even for small structures, such as the atrial wall. The proposed approach provided accurate (P> 0.4;R2> 0.99) and precise T1 values (SD of 64.32 ± 22.77 ms in the proposed approach, 44.73 ± 31.9 ms in the reference). The edge sharpness of the T1 maps was increased by 6.20% and 4.73% in simulation and phantom experiments, respectively. Contrast-to-noise ratios between the septum and blood pool increased by 14.50% inin vivomeasurements with a k-space compared to an image-space-based SRR.Significance. The proposed approach provided whole-heart high-resolution 1.3 mm isotropic T1 maps in an overall acquisition time of approximately three minutes. Small structures, such as the atrial and right ventricular walls, could be visualized in the T1 maps.

STADNet: Spatial-Temporal Attention-Guided Dual-Path Network for cardiac cine MRI super-resolution.

Cardiac cine magnetic resonance imaging (MRI) is a commonly used clinical tool for evaluating cardiac function and morphology. However, its diagnostic accuracy may be compromised by the low spatial resolution. Current methods for cine MRI super-resolution reconstruction still have limitations. They typically rely on 3D convolutional neural networks or recurrent neural networks, which may not effectively capture long-range or non-local features due to their limited receptive fields. Optical flow estimators are also commonly used to align neighboring frames, which may cause information loss and inaccurate motion estimation. Additionally, pre-warping strategies may involve interpolation, leading to potential loss of texture details and complicated anatomical structures. To overcome these challenges, we propose a novel Spatial-Temporal Attention-Guided Dual-Path Network (STADNet) for cardiac cine MRI super-resolution. We utilize transformers to model long-range dependencies in cardiac cine MR images and design a cross-frame attention module in the location-aware spatial path, which enhances the spatial details of the current frame by using complementary information from neighboring frames. We also introduce a recurrent flow-enhanced attention module in the motion-aware temporal path that exploits the correlation between cine MRI frames and extracts the motion information of the heart. Experimental results demonstrate that STADNet outperforms SOTA approaches and has significant potential for clinical practice.

Self-supervised learning for medical image data with anatomy-oriented imaging planes.

Self-supervised learning has emerged as a powerful tool for pretraining deep networks on unlabeled data, prior to transfer learning of target tasks with limited annotation. The relevance between the pretraining pretext and target tasks is crucial to the success of transfer learning. Various pretext tasks have been proposed to utilize properties of medical image data (e.g., three dimensionality), which are more relevant to medical image analysis than generic ones for natural images. However, previous work rarely paid attention to data with anatomy-oriented imaging planes, e.g., standard cardiac magnetic resonance imaging views. As these imaging planes are defined according to the anatomy of the imaged organ, pretext tasks effectively exploiting this information can pretrain the networks to gain knowledge on the organ of interest. In this work, we propose two complementary pretext tasks for this group of medical image data based on the spatial relationship of the imaging planes. The first is to learn the relative orientation between the imaging planes and implemented as regressing their intersecting lines. The second exploits parallel imaging planes to regress their relative slice locations within a stack. Both pretext tasks are conceptually straightforward and easy to implement, and can be combined in multitask learning for better representation learning. Thorough experiments on two anatomical structures (heart and knee) and representative target tasks (semantic segmentation and classification) demonstrate that the proposed pretext tasks are effective in pretraining deep networks for remarkably boosted performance on the target tasks, and superior to other recent approaches.

Automatic multi-view pose estimation in focused cardiac ultrasound.

Focused cardiac ultrasound (FoCUS) is a valuable point-of-care method for evaluating cardiovascular structures and function, but its scope is limited by equipment and operator's experience, resulting in primarily qualitative 2D exams. This study presents a novel framework to automatically estimate the 3D spatial relationship between standard FoCUS views. The proposed framework uses a multi-view U-Net-like fully convolutional neural network to regress line-based heatmaps representing the most likely areas of intersection between input images. The lines that best fit the regressed heatmaps are then extracted, and a system of nonlinear equations based on the intersection between view triplets is created and solved to determine the relative 3D pose between all input images. The feasibility and accuracy of the proposed pipeline were validated using a novel realistic in silico FoCUS dataset, demonstrating promising results. Interestingly, as shown in preliminary experiments, the estimation of the 2D images' relative poses enables the application of 3D image analysis methods and paves the way for 3D quantitative assessments in FoCUS examinations.

Advanced maternal age alters cardiac functional and structural adaptations to pregnancy in rats.

A significant number of pregnancies occur at advanced maternal age (>35 yr), which is a risk factor for pregnancy complications. Healthy pregnancies require massive hemodynamic adaptations, including an increased blood volume and cardiac output. There is growing evidence that these cardiovascular adaptations are impaired with age, however, little is known about maternal cardiac function with advanced age. We hypothesized that cardiac adaptations to pregnancy are impaired with advanced maternal age. Younger (4 mo; ∼early reproductive maturity in humans) and aged (9 mo; ∼35 yr in humans) pregnant Sprague-Dawley rats were assessed and compared with age-matched nonpregnant controls. Two-dimensional echocardiographic images were obtained (ultrasound biomicroscopy; under anesthesia) on gestational day 19 (term = 22 days) and compared with age-matched nonpregnant rats (n = 7-9/group). Left ventricular structure and function were assessed using short-axis images and transmitral Doppler signals. During systole, left ventricular anterior wall thickness increased with age in the nonpregnant rats, but there was no age-related difference between the pregnant groups. There were no significant pregnancy-associated differences in left ventricular wall thickness. Calculated left ventricular mass increased with age in nonpregnant rats and increased with pregnancy only in young rats. Compared with young pregnant rats, the aortic ejection time of aged pregnant rats was greater and Tei index was lower. Overall, the greater aortic ejection time and lower Tei index with age in pregnant rats suggest mildly altered cardiac adaptations to pregnancy with advanced maternal age, which may contribute to adverse outcomes in advanced maternal age pregnancies.NEW & NOTEWORTHY We demonstrated that even before the age of reproductive senescence, rats show signs of age-related alterations in cardiac structure that suggests increased cardiac work. Our data also demonstrate, using an in vivo echocardiographic approach, that advanced maternal age in a rat model is associated with altered cardiac function and structure relative to younger pregnant controls.

Multi-residual 2D network integrating spatial correlation for whole heart segmentation.

Whole heart segmentation (WHS) has significant clinical value for cardiac anatomy, modeling, and analysis of cardiac function. This study aims to address the WHS accuracy on cardiac CT images, as well as the fast inference speed and low graphics processing unit (GPU) memory consumption required by practical clinical applications. Thus, we propose a multi-residual two-dimensional (2D) network integrating spatial correlation for WHS. The network performs slice-by-slice segmentation on three-dimensional cardiac CT images in a 2D encoder-decoder manner. In the network, a convolutional long short-term memory skip connection module is designed to perform spatial correlation feature extraction on the feature maps at different resolutions extracted by the sub-modules of the pre-trained ResNet-based encoder. Moreover, a decoder based on the multi-residual module is designed to analyze the extracted features from the perspectives of multi-scale and channel attention, thereby accurately delineating the various substructures of the heart. The proposed method is verified on a dataset of the multi-modality WHS challenge, an in-house WHS dataset, and a dataset of the abdominal organ segmentation challenge. The dice, Jaccard, average symmetric surface distance, Hausdorff distance, inference time, and maximum GPU memory of the WHS are 0.914, 0.843, 1.066 mm, 15.778 mm, 9.535 s, and 1905 MB, respectively. The proposed network has high accuracy, fast inference speed, minimal GPU memory consumption, strong robustness, and good generalization. It can be deployed to clinical practical applications for WHS and can be effectively extended and applied to other multi-organ segmentation fields. The source code is publicly available at https://github.com/nancy1984yan/MultiResNet-SC.

Post-hoc standardisation of parametric T1 maps in cardiovascular magnetic resonance imaging: a proof-of-concept.

BACKGROUND: In cardiovascular magnetic resonance imaging parametric T1 mapping lacks universally valid reference values. This limits its extensive use in the clinical routine. The aim of this work was the introduction of our self-developed Magnetic Resonance Imaging Software for Standardization (MARISSA) as a post-hoc standardisation approach. METHODS: Our standardisation approach minimises the bias of confounding parameters (CPs) on the base of regression models. 214 healthy subjects with 814 parametric T1 maps were used for training those models on the CPs: age, gender, scanner and sequence. The training dataset included both sex, eleven different scanners and eight different sequences. The regression model type and four other adjustable standardisation parameters were optimised among 240 tested settings to achieve the lowest coefficient of variation, as measure for the inter-subject variability, in the mean T1 value across the healthy test datasets (HTE, N = 40, 156 T1 maps). The HTE were then compared to 135 patients with left ventricular hypertrophy including hypertrophic cardiomyopathy (HCM, N = 112, 121 T1 maps) and amyloidosis (AMY, N = 24, 24 T1 maps) after applying the best performing standardisation pipeline (BPSP) to evaluate the diagnostic accuracy. FINDINGS: The BPSP reduced the COV of the HTE from 12.47% to 5.81%. Sensitivity and specificity reached 95.83% / 91.67% between HTE and AMY, 71.90% / 72.44% between HTE and HCM, and 87.50% / 98.35% between HCM and AMY. INTERPRETATION: Regarding the BPSP, MARISSA enabled the comparability of T1 maps independently of CPs while keeping the discrimination of healthy and patient groups as found in literature. FUNDING: This study was supported by the BMBF / DZHK.

Influence of a 7-day Transalpine Trail Run on cardiac biomarkers and myocardial function.

Intense physical exercise is known to increase cardiac biomarkers; however, it is unclear, whether this phenomenon is physiological, or if it indicates myocardial tissue injury. The aim of our study was to investigate the effects of seven consecutive days of excessive endurance exercise on continuous assessment of cardiac biomarkers, function, and tissue injury. During a 7-day trail-running competition (Transalpine Run, distance 267.4 km, altitude ascent/descent 15556/14450 m), daily blood samples were obtained for cardiac biomarkers (hs-TnT, NT-proBNP, and suppression of tumorigenicity-2 protein (ST2)) at baseline, after each stage and 24-48 h post-race. In addition, echocardiography was performed every second day, cardiac magnetic resonance imaging (CMR) before (n = 7) and after (n = 16) the race. Twelve (eight males) out of 17 healthy athletes finished all seven stages (average total finish time: 43 ± 8 h). Only NT-proBNP increased significantly (3.6-fold, p = 0.009) during the first stage and continued to increase during the race. Hs-TnT revealed an incremental trend during the first day (2.7-fold increase, p = 0.098) and remained within the pathological range throughout the race. ST2 levels did not change during the race. All cardiac biomarkers completely returned to physiological levels post-race. NT-proBNP kinetics correlated significantly with mild transient reductions in right ventricular function (assessed by TAPSE, tricuspid annular plane systolic function; r = -0.716; p = 0.014). No significant echocardiographic changes in LV dimensions, LV function, or relevant alterations in CMR were observed post-race. In summary, this study shows that prolonged, repetitive, high-volume exercise induced a transient, significant increase in NT-proBNP associated with right ventricular dysfunction without corresponding left ventricular functional or structural impairment.

Differences in cardiac adaptation to exercise in male and female athletes assessed by noninvasive techniques: a state-of-the-art review.

Athlete's heart is generally regarded as a physiological adaptation to regular training, with specific morphological and functional alterations in the cardiovascular system. Development of the noninvasive imaging techniques over the past several years enabled better assessment of cardiac remodeling in athletes, which may eventually mimic certain pathological conditions with the potential for sudden cardiac death, or disease progression. The current literature provides a compelling overview of the available methods that target the interrelation of prolonged exercise with cardiac structure and function. However, this data stems from scientific studies that included mostly male athletes. Despite the growing participation of females in competitive sport meetings, little is known about the long-term cardiac effects of repetitive training in this population. There are several factors-biochemical, physiological and psychological, that determine sex-dependent cardiac response. Herein, the aim of this review was to compare cardiac adaptation to endurance exercise in male and female athletes with the use of electrocardiographic, echocardiographic, and biochemical examination, to determine the sex-specific phenotypes, and to improve the healthcare providers' awareness of cardiac remodeling in athletes. Finally, we discuss the possible exercise-induced alternations that should arouse suspicion of pathology and be further evaluated.

Cardiac DTI using short-axis PROPELLER: A feasibility study.

PURPOSE: We aimed to develop a free-breathing (FB) cardiac DTI (cDTI) method based on short-axis PROPELLER (SAP) and M2 motion compensated spin-echo EPI (SAP-M2-EPI) to mitigate geometric distortion and eliminate aliasing in acquired diffusion-weighted (DW) images, particularly in patients with a higher body mass index (BMI). THEORY AND METHODS: The study involved 10 healthy volunteers whose BMI values fell into specific categories: BMI <25 (4 volunteers), 25< BMI <28 (5 volunteers), and BMI >30 (1 volunteer). We compared DTI parameters, including fractional anisotropy (FA), mean diffusivity (MD), and helix angle transmurality (HAT), between SAP-M2-EPI and M2-ssEPI. To evaluate the performance of SAP-M2-EPI in reducing geometric distortions in the left ventricle (LV) compared to CINE and M2-ssEPI, we utilized the DICE similarity coefficient (DSC) and assessed misregistration area. RESULTS: In all volunteers, SAP-M2-EPI yielded high-quality LV DWIs without aliasing, demonstrating significantly reduced geometric distortion (with an average DSC of 0.92 and average misregistration area of 90 mm2) and diminished signal loss due to bulk motion when compared to M2-ssEPI. DTI parameter maps exhibited consistent patterns across slices without motion related artifacts. CONCLUSION: SAP-M2-EPI facilitates free-breathing cDTI of the entire LV, effectively eliminating aliasing and minimizing geometric distortion compared to M2-ssEPI. Furthermore, it preserves accurate quantification of myocardial microstructure.

Clinical characteristics of patients with Parkinson's disease with reduced 123I-metaiodobenzylguanidine uptake in the major salivary glands and heart.

BACKGROUND: Parkinson's disease (PD) shows cardiac sympathetic denervation (SD) in 123I-metaiodobezylguanidine (MIBG) scintigraphy. Recently, SD in the major salivary glands (MSG-SD) was introduced as a possible radiological feature of PD. OBJECTIVE: To identify the clinical characteristics of patients with PD with reduced MSG and cardiac MIBG uptake (dual-SD) compared with those with reduced MSG or cardiac MIBG uptake only (single-SD). METHODS: We recruited 90 patients with PD and 30 controls and evaluated their non-motor (e.g., hyposmia, autonomic dysfunction) and motor (e.g., Movement Disorder Society-Unified Parkinson's Disease Rating Scale) features. We also assessed MIBG uptake in the MSG and heart using a quantitative semi-automatic method, and compared MIBG uptakes between PD and controls. We set cut-off values for optimal sensitivity and specificity, and compared the clinical characteristics of patients with PD between dual- and single-SD groups. RESULTS: MSG and cardiac MIBG uptakes were significantly reduced in PD. Sixty-one patients had dual-SD, 25 had single-SD, and four had non-SD. In patients with PD with normal cardiac SD, 76.5% (13/17) of whom showed abnormalities only in MSG-SD. When clinical characteristics were compared between the dual-SD and single-/non-SD groups, patients in the dual-SD group were older and had more severe hyposmia and autonomic dysfunction, except motor features. Multiple logistic regression analysis identified age as an important confounder. CONCLUSIONS: Patients with PD with dual-SD have more severe non-motor features than other patients. Autonomic dysfunction might progress independently from dopaminergic degeneration. Furthermore, our findings indicate that aging is a crucial factor in PD progression.

Nonlocal based FISTA network for noninvasive cardiac transmembrane potential imaging.

Objective. The primary aim of our study is to advance our understanding and diagnosis of cardiac diseases. We focus on the reconstruction of myocardial transmembrane potential (TMP) from body surface potential mapping.Approach. We introduce a novel methodology for the reconstruction of the dynamic distribution of TMP. This is achieved through the integration of convolutional neural networks with conventional optimization algorithms. Specifically, we utilize the subject-specific transfer matrix to describe the dynamic changes in TMP distribution and ECG observations at the body surface. To estimate the TMP distribution, we employ LNFISTA-Net, a learnable non-local regularized iterative shrinkage-thresholding network. The coupled estimation processes are iteratively repeated until convergence.Main results. Our experiments demonstrate the capabilities and benefits of this strategy. The results highlight the effectiveness of our approach in accurately estimating the TMP distribution, thereby providing a reliable method for the diagnosis of cardiac diseases.Significance. Our approach demonstrates promising results, highlighting its potential utility for a range of applications in the medical field. By providing a more accurate and dynamic reconstruction of TMP, our methodology could significantly improve the diagnosis and treatment of cardiac diseases, thereby contributing to advancements in healthcare.

Left ventricle segment-specific motion assessment for cardiac-gated radiosurgery.

Purpose.Cardiac radiosurgery is a non-invasive treatment modality for ventricular tachycardia, where a linear accelerator is used to irradiate the arrhythmogenic region within the heart. In this work, cardiac magnetic resonance (CMR) cine images were used to quantify left ventricle (LV) segment-specific motion during the cardiac cycle and to assess potential advantages of cardiac-gated radiosurgery.Methods.CMR breath-hold cine images and LV contour points were analyzed for 50 controls and 50 heart failure patients with reduced ejection fraction (HFrEF, EF < 40%). Contour points were divided into anatomic segments according to the 17-segment model, and each segment was treated as a hypothetical treatment target. The optimum treatment window (one fifth of the cardiac cycle) was determined where segment centroid motion was minimal, then the maximum centroid displacement and treatment area were determined for the full cardiac cycle and for the treatment window. Mean centroid displacement and treatment area reductions with cardiac gating were determined for each of the 17 segments.Results.Full motion segment centroid displacements ranged between 6-14 mm (controls) and 4-11 mm (HFrEF). Full motion treatment areas ranged between 129-715 mm2(controls) and 149-766 mm2(HFrEF). With gating, centroid displacements were reduced to 1 mm (controls and HFrEF), while treatment areas were reduced to 62-349 mm2(controls) and 83-393 mm2(HFrEF). Relative treatment area reduction ranged between 38%-53% (controls) and 26%-48% (HFrEF).Conclusion.This data demonstrates that cardiac cycle motion is an important component of overall target motion and varies depending on the anatomic cardiac segment. Accounting for cardiac cycle motion, through cardiac gating, has the potential to significantly reduce treatment volumes for cardiac radiosurgery.

Functional and 123I-MIBG scintigraphy assessment of cardiac adrenergic dysfunction in diabetes.

OBJECTIVES: To assess the agreement between clinical cardiovascular adrenergic function and cardiac adrenergic innervation in type 2 diabetes patients (T2D). METHODS: Thirty-three patients with T2D were investigated bimodally through (1) a standardized clinical cardiovascular adrenergic assessment, evaluating adequacy of blood pressure responses to the Valsalva maneuver and (2) 123I-meta-iodobenzylguanidine (MIBG) scintigraphy assessing myocardial adrenergic innervation measured as early and delayed heart heart/mediastinum (H/M) ratio, and washout rate (WR). RESULTS: T2D patients had significantly lower early and delayed H/M-ratios, and lower WR, compared to laboratory specific reference values. Thirteen patients had an abnormal adrenergic composite autonomic severity score (CASS > 0). Patients with abnormal CASS scores had significantly higher early H/M ratios (1.76 [1.66-1.88] vs. 1.57 [1.49-1.63], p < 0.001), higher delayed H/M ratios (1.64 [1.51:1.73] vs. 1.51 [1.40:1.61] (p = 0.02)), and lower WR (-0.13(0.10) vs -0.05(0.07), p = 0.01). Lower Total Recovery and shorter Pressure Recovery Time responses from the Valsalva maneuver was significantly correlated to lower H/M early (r = 0.55, p = 0.001 and r = 0.5, p = 0.003, respectively) and lower WR for Total Recovery (r = -0.44, p = 0.01). CONCLUSION: The present study found impairment of sympathetic innervation in T2D patients based on parameters derived from MIBG cardiac scintigraphy (low early H/M, delayed H/M, and WR). These results confirm prior studies. We found a mechanistically inverted relationship with favourable adrenergic cardiovascular responses being significantly associated unfavourable MIBG indices for H/M early and delayed. This paradoxical relationship needs to be further explored but could indicate adrenergic hypersensitivity in cardiac sympathetic denervated T2D patients.