Quantification Of Perfusion Research Articles

Quantitative pulmonary perfusion in acute pulmonary embolism and chronic thromboembolic pulmonary hypertension.

Current methods for quantifying perfusion from computed tomography pulmonary angiography (CTPA) often rely on semi-quantitative scoring systems and requires an experienced evaluator. Few studies report on absolute quantitative variables derived from the images, and the methods are varied with mixed results. Dual-energy CTPA (DE-CTPA) enables automatic quantification of lung and lobar perfusion with minimal user interaction by utilizing machine learning based software. We aimed to evaluate differences in DE-CTPA derived quantitative perfusion variables between patients with acute pulmonary embolism (PE) and chronic thromboembolic pulmonary hypertension (CTEPH). This retrospective, single-center, observational study included 162 adult patients diagnosed with PE (n = 81) or CTEPH (n = 81) and scanned using dual-energy CT between 2020 and 2023. Mann-Whitney U tests and permutational analysis of variance (PERMANOVA) were used for comparative analyses. We found whole lung perfusion blood volume to be lower (p < 0.001) in PE patients (median 3399 mL [2554, 4284]) than in CTEPH patients (median 4094 mL [3397, 4818]). The same was observed at single lung and lobar level. PERMANOVA encompassing all perfusion variables showed a difference between the two groups (F-statistic = 13.3, p = 0.002). Utilizing logistic regression, right and left lower lobe perfusion blood volume showed some ability to differentiate between PE and CTEPH with area under the receiver operation characteristics curve values of 0.71 (95% CI: 0.56; 0.84) and 0.72 (95% CI: 0.56; 0.86). Pulmonary perfusion is lower in patients with PE than patients with CTEPH, highlighted by differences in DECT-derived perfusion blood volume. Quantitative perfusion variables might be useful to differentiate between the two diseases.

Hybrid quantification of absolute perfusion requires accurate measurement of myocardial mass.

Hybrid quantification of absolute perfusion requires accurate measurement of myocardial mass.

3D quantitative myocardial perfusion imaging with hyperpolarized HP001(bis-1,1-(hydroxymethyl)-[1-13C]cyclopropane-d8): Application of gradient echo and balanced SSFP sequences.

This study aims to show the viability of conducting three-dimensional (3D) myocardial perfusion quantification covering the entire heart using both GRE and bSSFP sequences with hyperpolarized HP001. A GRE sequence and a bSSFP sequence, both with a stack-of-spirals readout, were designed and applied to three pigs. The images were reconstructed using C coil sensitivity maps measured in a phantom experiment. Perfusion was quantified using a constrained decomposition method, and the estimated rest/stress perfusion values from C GRE/bSSFP and Dynamic contrast-enhanced MRI (DCE-MRI) were individually analyzed through histograms and the mean perfusion values were compared with reference values obtained from PET( O-water). The Myocardial Perfusion Reserve Index (MPRI) was estimated for C GRE/bSSFP and DCE-MRI and compared with the reference values. Perfusion values, estimated by both DCE and C MRI, were found to be lower than reference values. However, DCE-MRI's estimated perfusion values were closer to the reference values than those obtained from C MRI. In the case of MPRI estimation, the C estimated MPRI values (GRE/bSSFP: 2.3/2.0) more closely align with the literature value (around 3) than the DCE estimated MPRI value (1.6). This study demonstrated the feasibility of 3D whole-heart myocardial perfusion quantification using hyperpolarized HP001 with both GRE and bSSFP sequences. The C perfusion measurements underestimated perfusion values compared to the O PET literature value, while the C estimated MPRI value aligned better with the literature. This preliminary result indicates C imaging may more accurately estimate MPRI values compared to DCE-MRI.

Parathyroid gland identification and angiography classification using simple machine learning methods.

Near-infrared indocyanine green angiography allows experienced surgeons to reliably evaluate parathyroid gland vitality during thyroid and parathyroid operations in order to predict postoperative function. To facilitate equal performance between surgeons, we developed an automatic computational quantification method using computer vision that portrays expert interpretation of visualized parathyroid gland near-infrared indocyanine green angiographic fluorescence signals. Near-infrared indocyanine green-parathyroid gland angiography video recordings (Fluobeam® LX, Fluoptics, Grenoble-part of Getinge-Göteborg) from patients undergoing endocrine cervical surgery in a high-volume unit were used for model development. Computation (MATLAB, Mathworks, Ireland) included segmentation-identification of the parathyroid gland (by autofluorescence), image stabilization (by linear translation) and adjusted time-fluorescence intensity profile generation. Relative upslope and maximum intensity ratios then trained a simple logistic regression model based on expert interpretation and outcome (including hypoparathyroidism), with subsequent unseen testing for validation. The model was trained on 37 patient videos (45 glands, 29 judged well perfused by parathyroid gland angiography experts), achieving feature data separation with 100% accuracy, and tested on 22 unseen videos (27 glands, 15 judged well perfused), including four in real time. Segmentation-guided parathyroid gland detection correctly identified all parathyroid glands during unseen testing along with three additional non-parathyroid gland regions (90% positive predictive value). Subsequent time-fluorescence intensity profile extraction with vitality prediction was shown feasible in all cases within 5 min, with a 96.3% model accuracy (sensitivity and specificity were 93.3 and 100% respectively) when compared with expert judgement. Automatic parathyroid gland perfusion quantification using simple machine learning computational methods discriminates parathyroid gland perfusion in concordance with expert surgeon interpretation, providing a means for near-infrared indocyanine green-parathyroid gland signal evaluation.

Neuroimaging analysis reveals distinct cerebral perfusion responses to fasting-postprandial metabolic switching in Alzheimer's disease patients.

Extended fasting-postprandial switch intermitting time has been shown to affect Alzheimer's disease (AD). Few studies have investigated the cerebral perfusion response to fasting-postprandial metabolic switching (FMS) in AD patients. We aimed to evaluate the cerebral perfusion response to FMS in AD patients. In total, 30 AD patients, 32 mild cognitive impairment (MCI) patients, and 30 healthy control individuals (HCs) were included in the quantification of cerebral perfusion via cerebral blood flow (CBF). The cerebral perfusion response to FMS was defined as the difference (ΔCBF) between fasting and postprandial CBF. Patients with AD had a regional negative ΔCBF in the anterior temporal lobe, part of the occipital lobe and the parietal lobe under FMS stimulation, whereas HCs had no significant ΔCBF. The AD patients had lower ΔCBF values in the right anterior temporal lobe than the MCI patients and HCs. ΔCBF in the anterior temporal lobe was negatively correlated with cognitive severity and cognitive reserve factors in AD patients. AD patients exhibited a poor ability to maintain cerebral perfusion homeostasis under FMS stimulation. The anterior temporal lobe is a distinct area that responds to FMS in AD patients and negatively correlates with cognitive function.

Post-Surgical Non-Invasive Wound Healing Monitoring in Oropharyngeal Mucosa.

Postoperative bleeding is the most significant complication of tonsillectomy. Regular monitoring of post-surgical wound healing in the pharynx is required. For this purpose, we propose endoscope-based non-invasive perfusion mapping and quantification. The combination of imaging photoplethysmography and image processing provides automated wound area selection and microcirculation characterization. In this feasibility study, we demonstrate the first results of the proposed approach to wound monitoring in clinical trial on eight patients after tonsillectomy. Combination of probe-based optical system and image processing algorithms can provide the valuable and consistent data on perfusion distribution. The quantitative microcirculation data obtained 1, 4, and 7 days after surgery are in good agreement with existing monitoring protocols.

Real-time fMRI neurofeedback of the anterior insula using arterial spin labelling.

Arterial spin labelling (ASL) is the only non-invasive technique that allows absolute quantification of perfusion and is increasingly used in brain activation studies. Contrary to the blood oxygen level-dependent (BOLD) effect ASL measures the cerebral blood flow (CBF) directly. However, the ASL signal has a lower signal-to-noise ratio (SNR), than the BOLD signal, which constrains its utilization in neurofeedback studies. If successful, ASL neurofeedback can be used to aid in the rehabilitation of health conditions with impaired blood flow, for example, stroke. We provide the first ASL-based neurofeedback study incorporating a double-blind, sham-controlled design. A pseudo-continuous ASL (pCASL) approach with background suppression and 3D GRASE readout was combined with a real-time post-processing pipeline. The real-time pipeline allows to monitor the ASL signal and provides real-time feedback on the neural activity to the subject. In total 41 healthy adults (19-56 years) divided into three groups underwent a neurofeedback-based emotion imagery training of the left anterior insula. Two groups differing only in the explicitness level of instruction received real training and a third group received sham feedback. Only those participants receiving real feedback with explicit instruction showed significantly higher absolute CBF values in the trained region during neurofeedback than participants receiving sham feedback. However, responder analyses of percent signal change values show no differences in activation between the three groups. Persisting limitations, such as the lower SNR, confounding effects of arterial transit time and partial volume effects still impact negatively the implementation of ASL neurofeedback.

Turn-table micro-CT scanner for dynamic perfusion imaging in mice: design, implementation, and evaluation

Objective.This study introduces a novel desktop micro-CT scanner designed for dynamic perfusion imaging in mice, aimed at enhancing preclinical imaging capabilities with high resolution and low radiation doses.Approach.The micro-CT system features a custom-built rotating table capable of both circular and helical scans, enabled by a small-bore slip ring for continuous rotation. Images were reconstructed with a temporal resolution of 3.125 s and an isotropic voxel size of 65µm, with potential for higher resolution scanning. The system's static performance was validated using standard quality assurance phantoms. Dynamic performance was assessed with a custom 3D-bioprinted tissue-mimetic phantom simulating single-compartment vascular flow. Flow measurements ranged from 1.51to 9 ml min-1, with perfusion metrics such as time-to-peak, mean transit time, and blood flow index calculated.In vivoexperiments involved mice with different genetic risk factors for Alzheimer's and cardiovascular diseases to showcase the system's capabilities for perfusion imaging.Main Results.The static performance validation confirmed that the system meets standard quality metrics, such as spatial resolution and uniformity. The dynamic evaluation with the 3D-bioprinted phantom demonstrated linearity in hemodynamic flow measurements and effective quantification of perfusion metrics.In vivoexperiments highlighted the system's potential to capture detailed perfusion maps of the brain, lungs, and kidneys. The observed differences in perfusion characteristics between genotypic mice illustrated the system's capability to detect physiological variations, though the small sample size precludes definitive conclusions.Significance.The turn-table micro-CT system represents a significant advancement in preclinical imaging, providing high-resolution, low-dose dynamic imaging for a range of biological and medical research applications. Future work will focus on improving temporal resolution, expanding spectral capabilities, and integrating deep learning techniques for enhanced image reconstruction and analysis.

Quantitative non-contrast perfusion MRI in the body using arterial spin labeling.

Arterial spin labeling (ASL) is a non-invasive magnetic resonance imaging (MRI) method that enables the assessment and the quantification of perfusion without the need for an exogenous contrast agent. ASL was originally developed in the early 1990s to measure cerebral blood flow. The utility of ASL has since then broadened to encompass various organ systems, offering insights into physiological and pathological states. In this review article, we present a synopsis of ASL for quantitative non-contrast perfusion MRI, as a contribution to the special issue titled "Quantitative MRI-how to make it work in the body?" The article begins with an introduction to ASL principles, followed by different labeling strategies, such as pulsed, continuous, pseudo-continuous, and velocity-selective approaches, and their role in perfusion quantification. We proceed to address the technical challenges associated with ASL in the body and outline some of the innovative approaches devised to surmount these issues. Subsequently, we summarize potential clinical applications, challenges, and state-of-the-art ASL methods to quantify perfusion in some of the highly perfused organs in the thorax (lungs), abdomen (kidneys, liver, pancreas), and pelvis (placenta) of the human body. The article concludes by discussing future directions for successful translation of quantitative ASL in body imaging.

Dye-less quantification of tissue perfusion by laser speckle contrast imaging is equivalent to quantified indocyanine green in a porcine model.

Subjective surgeon interpretation of near-infrared perfusion video is limited by low inter-observer agreement and poor correlation to clinical outcomes. In contrast, quantification of indocyanine green fluorescence video (Q-ICG) correlates with histologic level of perfusion as well as clinical outcomes. Measuring dye volume over time, however, has limitations, such as it is not on-demand, has poor spatial resolution, and is not easily repeatable. Laser speckle contrast imaging quantification (Q-LSCI) is a real-time, dye-free alternative, but further validation is needed. We hypothesize that Q-LSCI will distinguish ischemic tissue and correlate over a range of perfusion levels equivalent to Q-ICG. Nine sections of intestine in three swine were devascularized. Pairs of indocyanine green fluorescence imaging and laser speckle contrast imaging video were quantified within perfused, watershed, and ischemic regions. Q-ICG used normalized peak inflow slope. Q-LSCI methods were laser speckle perfusion units (LSPU), the base unit of laser speckle imaging, relative perfusion units (RPU), a previously described methodology which utilizes an internal control, and zero-lag normalized cross-correlation (X-Corr), to investigate if the signal deviations convey accurate perfusion information. We determine the ability to distinguish ischemic regions and correlation to Q-ICG over a perfusion gradient. All modalities distinguished ischemic from perfused regions of interest; Q-ICG values of 0.028 and 0.155 (p < 0.001); RPU values of 0.15 and 0.68 (p < 0.001); and X-corr values of 0.73 and 0.24 (p < 0.001). Over a range of perfusion levels, RPU had the best correlation with Q-ICG (r = 0.79, p < 0.001) compared with LSPU (r = 0.74, p < 0.001) and X-Corr (r = 0.46, p < 0.001). These results demonstrate that Q-LSCI discriminates ischemic from perfused tissue and represents similar perfusion information over a broad range of perfusion levels comparable to clinically validated Q-ICG. This suggests that Q-LSCI might offer clinically predictive real-time dye-free quantification of tissue perfusion. Further work should include validation in histologic studies and human clinical trials.

Hyperpolarized Water for Coronary Artery Angiography and Whole-Heart Myocardial Perfusion Quantification.

Purpose: Water freely diffuses across cell membranes, making it suitable for measuring absolute tissue perfusion. In this study, we introduce an imaging method for conducting coronary artery angiography and quantifying myocardial perfusion across the entire heart using hyperpolarized water. Methods:1H was hyperpolarized using dissolution dynamic nuclear polarization (dDNP) with UV-generated radicals. Submillimeter resolution coronary artery images were acquired as 2D projections using a spoiled GRE (SPGRE) sequence gated on diastole. Dynamic perfusion images were obtained with a multi-slice SPGRE with diastole gating, covering the entire heart. Perfusion values were analyzed through histograms, and the most frequent estimated perfusion value (the mode of the distribution), was compared with the average values for 15O water PET from the literature. Results: A liquid state polarization of 10% at the time of the injection and a 30 s T1 in D2O TRIS buffer were measured. Both coronary artery and dynamic perfusion images exhibited good quality. The main and small coronary artery branches were well resolved. The most frequent estimated perfusion value is around 0.6 mL/g/min, which is lower than the average values obtained from the literature for 15O-water PET (around 1.1 and 1.5 mL/g/min). Conclusions: The study successfully demonstrated the feasibility of achieving high-resolution, motion-free coronary artery angiography and 3D whole-heart quantitative myocardial perfusion using hyperpolarized water.

Quantitative transport mapping of multi-delay arterial spin labeling MRI detects early blood perfusion alterations in Alzheimer’s disease

BackgroundQuantitative transport mapping (QTM) of blood velocity, based on the transport equation has been demonstrated higher accuracy and sensitivity of perfusion quantification than the traditional Kety’s method-based cerebral blood flow (CBF). This study aimed to investigate the associations between QTM velocity and cognitive function in Alzheimer’s disease (AD) using multiple post-labeling delay arterial spin labeling (ASL) MRI.MethodsA total of 128 subjects (21 normal controls (NC), 80 patients with mild cognitive impairment (MCI), and 27 AD) were recruited prospectively. All participants underwent MRI examination and neuropsychological evaluation. QTM velocity and traditional CBF maps were computed from multiple delay ASL. Regional quantitative perfusion measurements were performed and compared to study group differences. We tested the hypothesis that cognition declines with reduced cerebral blood perfusion with consideration of age and gender effects.ResultsIn cortical gray matter (GM) and the hippocampus, QTM velocity and CBF showed decreased values in the AD group compared to NC and MCI groups; QTM velocity, but not CBF, showed a significant difference between MCI and NC groups. QTM velocity and CBF showed values decreasing with age; QTM velocity, but not CBF, showed a significant gender difference between male and female. QTM velocity and CBF in the hippocampus were positively correlated with cognition, including global cognition, memory, executive function, and language function.ConclusionThis study demonstrated an increased sensitivity of QTM velocity as compared with the traditional Kety’s method-based CBF. Specifically, we observed only in QTM velocity, reduced perfusion velocity in GM and the hippocampus in MCI compared with NC. Both QTM velocity and CBF demonstrated a reduction in AD vs. controls. Decreased QTM velocity and CBF in the hippocampus were correlated with poor cognitive measures. These findings suggest QTM velocity as potential biomarker for early AD blood perfusion alterations and it could provide an avenue for early intervention of AD.

Evaluating cerebrovascular reactivity measured by velocity selective inversion arterial spin labeling with different post-labeling delays: The effect of fast flow.

Velocity selective arterial spin labeling (VSASL) quantification assumes that the labeled bolus continuously moves into the imaging voxel during the post-labeling delay (PLD). Faster blood flow could lead to a bolus duration shorter than the applied PLD of VSASL and cause underestimation of cerebral blood flow (CBF). This study aims to evaluate the performance of velocity-selective inversion (VSI) prepared arterial spin labeling (ASL) with different PLDs and pseudo-continuous ASL (PCASL) for quantification of hypercapnia-induced cerebrovascular reactivity (CVR), using phase-contrast (PC) MRI as a global reference. We compared CVR obtained by VSI-ASL with PLD of 1520 ms (VSASL-1520), 1000 ms (VSASL-1000), and 500 ms (VSASL-500), PCASL with PLD of 1800 ms (PCASL-1800), and PC MRI on eight healthy volunteers at two sessions. Compared with PC MRI, VSASL-1520 produced significantly lower global CVR values, while PCASL-1800, VSASL-1000, and VSASL-500 yielded more consistent results. The reduced CVR in VSASL-1520 was more pronounced in carotid territories including frontal and temporal lobes than in vertebral territories such as the occipital lobe. This is largely caused by the underestimated perfusion during hypercapnia due to the reduced bolus duration being less than the PLD. Although VSASL offers certain advantages over spatially selective ASL due to its reduced susceptibility to delayed ATT, this technique is prone to biases when the ATT is excessively short. Therefore, a short PLD should be employed for reliable perfusion and CVR quantification in populations or conditions with fast flow.

Contrast agent-free functional magnetic resonance imaging with matrix pencil decomposition to quantify abnormalities in lung perfusion and ventilation in patients with cystic fibrosis.

Previous studies showed that contrast-enhanced (CE) morpho-functional magnetic resonance imaging (MRI) detects abnormalities in lung morphology and perfusion in patients with cystic fibrosis (CF). Novel matrix pencil decomposition MRI (MP-MRI) enables quantification of lung perfusion and ventilation without intravenous contrast agent administration. To compare MP-MRI with established morpho-functional MRI and spirometry in patients with CF. Thirty-nine clinically stable patients with CF (mean age 21.6 ± 10.7 years, range 8-45 years) prospectively underwent morpho-functional MRI including CE perfusion MRI, MP-MRI and spirometry. Two blinded chest radiologists assessed morpho-functional MRI and MP-MRI employing the validated chest MRI score. In addition, MP-MRI data were processed by automated software calculating perfusion defect percentage (QDP) and ventilation defect percentage (VDP). MP perfusion score and QDP correlated strongly with the CE perfusion score (both r = 0.81; p < 0.01). MP ventilation score and VDP showed strong inverse correlations with percent predicted FEV1 (r = -0.75 and r = -0.83; p < 0.01). The comparison of visual and automated parameters showed that both MP perfusion score and QDP, and MP ventilation score and VDP were strongly correlated (r = 0.74 and r = 0.78; both p < 0.01). Further, the MP perfusion score and MP ventilation score, as well as QDP and VDP were strongly correlated (r = 0.88 and r = 0.86; both p < 0.01). MP-MRI detects abnormalities in lung perfusion and ventilation in patients with CF without intravenous or inhaled contrast agent application, and correlates strongly with the well-established CE perfusion MRI score and spirometry. Automated analysis of MP-MRI may serve as quantitative noninvasive outcome measure for diagnostic monitoring and clinical trials.

Identifiability of spatiotemporal tissue perfusion models

Objective. Standard models for perfusion quantification in DCE-MRI produce a bias by treating voxels as isolated systems. Spatiotemporal models can remove this bias, but it is unknown whether they are fundamentally identifiable. The aim of this study is to investigate this question in silico using one-dimensional toy systems with a one-compartment blood flow model and a two-compartment perfusion model. Approach. For each of the two models, identifiability is explored theoretically and in-silico for three systems. Concentrations over space and time are simulated by forward propagation. Different levels of noise and temporal undersampling are added to investigate sensitivity to measurement error. Model parameters are fitted using a standard gradient descent algorithm, applied iteratively with a stepwise increasing time window. Model fitting is repeated with different initial values to probe uniqueness of the solution. Reconstruction accuracy is quantified for each parameter by comparison to the ground truth. Main results. Theoretical analysis shows that flows and volume fractions are only identifiable up to a constant, and that this degeneracy can be removed by proper choice of parameters. Simulations show that in all cases, the tissue concentrations can be reconstructed accurately. The one-compartment model shows accurate reconstruction of blood velocities and arterial input functions, independent of the initial values and robust to measurement error. The two-compartmental perfusion model was not fully identifiable, showing good reconstruction of arterial velocities and input functions, but multiple valid solutions for the perfusion parameters and venous velocities, and a strong sensitivity to measurement error in these parameters. Significance. These results support the use of one-compartment spatiotemporal flow models, but two-compartment perfusion models were not sufficiently identifiable. Future studies should investigate whether this degeneracy is resolved in more realistic 2D and 3D systems, by adding physically justified constraints, or by optimizing experimental parameters such as injection duration or temporal resolution.

The prognostic relevance of a gene expression signature in MRI-defined highly vascularized glioblastoma

BackgroundThe vascular heterogeneity of glioblastomas (GB) remains an important area of research, since tumor progression and patient prognosis are closely tied to this feature. With this study, we aim to identify gene expression profiles associated with MRI-defined tumor vascularity and to investigate its relationship with patient prognosis. MethodsThe study employed MRI parameters calculated with DSC Perfusion Quantification of ONCOhabitats glioma analysis software and RNA-seq data from the TCGA-GBM project dataset. In our study, we had a total of 147 RNA-seq samples, which 15 of them also had MRI parameter information. We analyzed the gene expression profiles associated with MRI-defined tumor vascularity using differential gene expression analysis and performed Log-rank tests to assess the correlation between the identified genes and patient prognosis. ResultsThe findings of our research reveal a set of 21 overexpressed genes associated with the high vascularity pattern. Notably, several of these overexpressed genes have been previously implicated in worse prognosis based on existing literature. Our log-rank test further validates that the collective upregulation of these genes is indeed correlated with an unfavorable prognosis. This set of genes includes a variety of molecules, such as cytokines, receptors, ligands, and other molecules with diverse functions. ConclusionsOur findings suggest that the set of 21 overexpressed genes in the High Vascularity group could potentially serve as prognostic markers for GB patients. These results highlight the importance of further investigating the relationship between the molecules such as cytokines or receptors underlying the vascularity in GB and its observation through MRI and developing targeted therapies for this aggressive disease.

Arterial Input Function (AIF) Correction Using AIF Plus Tissue Inputs with a Bi-LSTM Network.

Background: The arterial input function (AIF) is vital for myocardial blood flow quantification in cardiac MRI to indicate the input time-concentration curve of a contrast agent. Inaccurate AIFs can significantly affect perfusion quantification. Purpose: When only saturated and biased AIFs are measured, this work investigates multiple ways of leveraging tissue curve information, including using AIF + tissue curves as inputs and optimizing the loss function for deep neural network training. Methods: Simulated data were generated using a 12-parameter AIF mathematical model for the AIF. Tissue curves were created from true AIFs combined with compartment-model parameters from a random distribution. Using Bloch simulations, a dictionary was constructed for a saturation-recovery 3D radial stack-of-stars sequence, accounting for deviations such as flip angle, T2* effects, and residual longitudinal magnetization after the saturation. A preliminary simulation study established the optimal tissue curve number using a bidirectional long short-term memory (Bi-LSTM) network with just AIF loss. Further optimization of the loss function involves comparing just AIF loss, AIF with compartment-model-based parameter loss, and AIF with compartment-model tissue loss. The optimized network was examined with both simulation and hybrid data, which included in vivo 3D stack-of-star datasets for testing. The AIF peak value accuracy and ktrans results were assessed. Results: Increasing the number of tissue curves can be beneficial when added tissue curves can provide extra information. Using just the AIF loss outperforms the other two proposed losses, including adding either a compartment-model-based tissue loss or a compartment-model parameter loss to the AIF loss. With the simulated data, the Bi-LSTM network reduced the AIF peak error from -23.6 ± 24.4% of the AIF using the dictionary method to 0.2 ± 7.2% (AIF input only) and 0.3 ± 2.5% (AIF + ten tissue curve inputs) of the network AIF. The corresponding ktrans error was reduced from -13.5 ± 8.8% to -0.6 ± 6.6% and 0.3 ± 2.1%. With the hybrid data (simulated data for training; in vivo data for testing), the AIF peak error was 15.0 ± 5.3% and the corresponding ktrans error was 20.7 ± 11.6% for the AIF using the dictionary method. The hybrid data revealed that using the AIF + tissue inputs reduced errors, with peak error (1.3 ± 11.1%) and ktrans error (-2.4 ± 6.7%). Conclusions: Integrating tissue curves with AIF curves into network inputs improves the precision of AI-driven AIF corrections. This result was seen both with simulated data and with applying the network trained only on simulated data to a limited in vivo test dataset.

A 3D dual-echo spiral sequence for simultaneous dynamic susceptibility contrast and dynamic contrast-enhanced MRI with single bolus injection.

Perfusion MRI reveals important tumor physiological and pathophysiologic information, making it a critical component in managing brain tumor patients. This study aimed to develop a dual-echo 3D spiral technique with a single-bolus scheme to simultaneously acquire both dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) data and overcome the limitations of current EPI-based techniques. A 3D spiral-based technique with dual-echo acquisition was implemented and optimized on a 3T MRI scanner with a spiral staircase trajectory and through-plane SENSE acceleration for improved speed and image quality, in-plane variable-density undersampling combined with a sliding-window acquisition and reconstruction approach for increased speed, and an advanced iterative deblurring algorithm. Four volunteers were scanned and compared with the standard of care (SOC) single-echo EPI and a dual-echo EPI technique. Two patients were scanned with the spiral technique during a preload bolus and compared with the SOC single-echo EPI collected during the second bolus injection. Volunteer data demonstrated that the spiral technique achieved high image quality, reduced geometric artifacts, and high temporal SNR compared with both single-echo and dual-echo EPI. Patient perfusion data showed that the spiral acquisition achieved accurate DSC quantification comparable to SOC single-echo dual-dose EPI, with the additional DCE information. A 3D dual-echo spiral technique was developed to simultaneously acquire both DSC and DCE data in a single-bolus injection with reduced contrast use. Preliminary volunteer and patient data demonstrated increased temporal SNR, reduced geometric artifacts, and accurate perfusion quantification, suggesting a competitive alternative to SOC-EPI techniques for brain perfusion MRI.

AI-Defined Cardiac Anatomy Improves Risk Stratification of Hybrid Perfusion Imaging

BackgroundComputed tomography attenuation correction (CTAC) improves perfusion quantification of hybrid myocardial perfusion imaging by correcting for attenuation artifacts. Artificial intelligence (AI) can automatically measure coronary artery calcium (CAC) from CTAC to improve risk prediction but could potentially derive additional anatomic features. ObjectivesThe authors evaluated AI-based derivation of cardiac anatomy from CTAC and assessed its added prognostic utility. MethodsThe authors considered consecutive patients without known coronary artery disease who underwent single-photon emission computed tomography/computed tomography (CT) myocardial perfusion imaging at 3 separate centers. Previously validated AI models were used to segment CAC and cardiac structures (left atrium, left ventricle, right atrium, right ventricular volume, and left ventricular [LV] mass) from CTAC. They evaluated associations with major adverse cardiovascular events (MACEs), which included death, myocardial infarction, unstable angina, or revascularization. ResultsIn total, 7,613 patients were included with a median age of 64 years. During a median follow-up of 2.4 years (IQR: 1.3-3.4 years), MACEs occurred in 1,045 (13.7%) patients. Fully automated AI processing took an average of 6.2 ± 0.2 seconds for CAC and 15.8 ± 3.2 seconds for cardiac volumes and LV mass. Patients in the highest quartile of LV mass and left atrium, LV, right atrium, and right ventricular volume were at significantly increased risk of MACEs compared to patients in the lowest quartile, with HR ranging from 1.46 to 3.31. The addition of all CT-based volumes and CT-based LV mass improved the continuous net reclassification index by 23.1%. ConclusionsAI can automatically derive LV mass and cardiac chamber volumes from CT attenuation imaging, significantly improving cardiovascular risk assessment for hybrid perfusion imaging.

Clinical Utility of Laser Speckle Contrast Imaging and Real-Time Quantification of Bowel Perfusion in Minimally Invasive Left-Sided Colorectal Resections.

Left-sided colorectal surgery demonstrates high anastomotic leak rates, with tissue ischemia thought to influence outcomes. Indocyanine green is commonly used for perfusion assessment, but evidence remains mixed for whether it reduces colorectal anastomotic leaks. Laser speckle contrast imaging provides dye-free perfusion assessment in real-time through perfusion heat maps and quantification. This study investigates the efficacy of advanced visualization (indocyanine green versus laser speckle contrast imaging), perfusion assessment, and utility of laser speckle perfusion quantification in determining ischemic margins. Prospective intervention group using advanced visualization with case-matched, retrospective control group. Single academic medical center. Forty adult patients undergoing elective, minimally invasive, left-sided colorectal surgery. Intraoperative perfusion assessment using white light imaging and advanced visualization at 3 time points: T1-proximal colon after devascularization, before transection, T2-proximal/distal colon before anastomosis, and T3-completed anastomosis. Intraoperative indication of ischemic line of demarcation before resection under each visualization method, surgical decision change using advanced visualization, post hoc laser speckle perfusion quantification of colorectal tissue, and 30-day postoperative outcomes. Advanced visualization changed surgical decision-making in 17.5% of cases. For cases in which surgeons changed a decision, the average discordance between the line of demarcation in white light imaging and advanced visualization was 3.7 cm, compared to 0.41 cm ( p = 0.01) for cases without decision changes. There was no statistical difference between the line of ischemic demarcation using laser speckle versus indocyanine green ( p = 0.16). Laser speckle quantified lower perfusion values for tissues beyond the line of ischemic demarcation while suggesting an additional 1 cm of perfused tissue beyond this line. One (2.5%) anastomotic leak occurred in the intervention group. This study was not powered to detect differences in anastomotic leak rates. Advanced visualization using laser speckle and indocyanine green provides valuable perfusion information that impacts surgical decision-making in minimally invasive left-sided colorectal surgeries. See Video Abstract . ANTECEDENTES:La cirugía colorrectal del lado izquierdo demuestra altas tasas de fuga anastomótica, y se cree que la isquemia tisular influye en los resultados. El verde de indocianina se utiliza habitualmente para evaluar la perfusión, pero la evidencia sobre si reduce las fugas anastomóticas colorrectales sigue siendo contradictoria. Las imágenes de contraste moteado con láser proporcionan una evaluación de la perfusión sin colorantes en tiempo real a través de mapas de calor de perfusión y cuantificación.OBJETIVO:Este estudio investiga la eficacia de la evaluación de la perfusión mediante visualización avanzada (verde de indocianina versus imágenes de contraste moteado con láser) y la utilidad de la cuantificación de la perfusión con moteado láser para determinar los márgenes isquémicos.DISEÑO:Grupo de intervención prospectivo que utiliza visualización avanzada con un grupo de control retrospectivo de casos emparejados.LUGARES:Centro médico académico único.PACIENTES:Cuarenta pacientes adultos sometidos a cirugía colorrectal electiva, mínimamente invasiva, del lado izquierdo.INTERVENCIONES:Evaluación de la perfusión intraoperatoria mediante imágenes con luz blanca y visualización avanzada en tres puntos temporales: T1-colon proximal después de la devascularización, antes de la transección; T2-colon proximal/distal antes de la anastomosis; y T3-anastomosis completa.PRINCIPALES MEDIDAS DE VALORACIÓN:Indicación intraoperatoria de la línea de demarcación isquémica antes de la resección bajo cada método de visualización, cambio de decisión quirúrgica mediante visualización avanzada, cuantificación post-hoc de la perfusión con láser moteado del tejido colorrectal y resultados posoperatorios a los 30 días.RESULTADOS:La visualización avanzada cambió la toma de decisiones quirúrgicas en el 17,5% de los casos. Para los casos en los que los cirujanos cambiaron una decisión, la discordancia promedio entre la línea de demarcación en las imágenes con luz blanca y la visualización avanzada fue de 3,7 cm, en comparación con 0,41 cm (p = 0,01) para los casos sin cambios de decisión. No hubo diferencias estadísticas entre la línea de demarcación isquémica utilizando láser moteado versus verde de indocianina (p = 0,16). El moteado con láser cuantificó valores de perfusión más bajos para los tejidos más allá de la línea de demarcación isquémica y al mismo tiempo sugirió 1 cm adicional de tejido perfundido más allá de esta línea. Se produjo una fuga anastomótica (2,5%) en el grupo de intervención.LIMITACIONES:Este estudio no tuvo el poder estadístico suficiente para detectar diferencias en las tasas de fuga anastomótica.CONCLUSIONES:La visualización avanzada utilizando moteado láser y verde de indocianina proporciona información valiosa sobre la perfusión que impacta la toma de decisiones quirúrgicas en cirugías colorrectales mínimamente invasivas del lado izquierdo. (Traducción-Dr. Ingrid Melo).