3D Time-of-flight Research Articles

An Energy-Efficient Dynamic Feedback Image Signal Processor for Three-Dimensional Time-of-Flight Sensors.

With the recent prominence of artificial intelligence (AI) technology, various research outcomes and applications in the field of image recognition and processing utilizing AI have been continuously emerging. In particular, the domain of object recognition using 3D time-of-flight (ToF) sensors has been actively researched, often in conjunction with augmented reality (AR) and virtual reality (VR). However, for more precise analysis, high-quality images are required, necessitating significantly larger parameters and computations. These requirements can pose challenges, especially in developing AR and VR technologies for low-power portable devices. Therefore, we propose a dynamic feedback configuration image signal processor (ISP) for 3D ToF sensors. The ISP achieves both accuracy and energy efficiency through dynamic feedback. The proposed ISP employs dynamic area extraction to perform computations and post-processing only for pixels within the valid area used by the application in each frame. Additionally, it uses dynamic resolution to determine and apply the appropriate resolution for each frame. This approach enhances energy efficiency by avoiding the processing of all sensor data while maintaining or surpassing accuracy levels. Furthermore, These functionalities are designed for hardware-efficient implementation, improving processing speed and minimizing power consumption. The results show a maximum performance of 178 fps and a high energy efficiency of up to 123.15 fps/W. When connected to the hand pose estimation (HPE) accelerator, it demonstrates an average mean squared error (MSE) of 10.03 mm, surpassing the baseline ISP value of 20.25 mm. Therefore, the proposed ISP can be effectively utilized in low-power, small form-factor devices.

Histological Validation of 3D Variable Flip Angle TSE Multi-Contrast Magnetic Resonance Vessel Wall Imaging in Characterizing Carotid Vulnerable Atherosclerotic Plaques

BackgroundAccurate assessment of the vulnerability of carotid atherosclerotic plaques is crucial for stroke prevention. The three-dimensional (3D) magnetic resonance (MR) vessel wall imaging (VWI) has been increasingly employed to evaluate carotid plaques due to its extensive coverage and isotropic high spatial resolution. However, the accuracy of such technique lacks validation by histology. ObjectiveThis study aims to validate the accuracy of 3D multi-contrast MR VWI used variable-flip-angle (VFA) and turbo spin echo (TSE) readout in identifying vulnerable carotid plaques, using histological analysis as a reference. MethodsTwenty-one male patients (mean age: 64.4 ± 7.2 years) scheduled for carotid endarterectomy (CEA) were recruited for this study. All patients underwent carotid multi-contrast MR VWI, including 3D T1- and T2-weighted variable flip angle-based turbo spin echo (VFA-TSE) sequences, as well as 3D time of flight (TOF) MR angiography (MRA), using a 3.0T MR system. Histological processing was performed for carotid plaque specimens. The presence or absence, along with the area measurements, of lipid-rich necrotic core (LRNC), intraplaque hemorrhage (IPH), and calcifications (CA) were independently evaluated on both MR images and histological sections. Cohen’s kappa (κ) analysis was utilized to determine the agreement between 3D multi-contrast MR VWI and histology in identifying carotid plaque compositions before and after excluding compositions bellow certain size threshold. Spearman’s correlation analysis was also conducted to assess the agreement in quantifying plaque compositions. ResultsA total of 81 slices of MR images were successfully matched with histological sections. Moderate to almost perfect agreements were observed between 3D MR VWI and histology in the identification of LRNC (κ: 0.85 and 0.89), IPH (κ: 0.65 and 0.69), and CA (κ: 0.46 and 0.62) before and after excluding compositions smaller than 0.79 mm2. Strong to very strong correlations were found in the quantification of plaque compositions including LRNC (r=0.88), IPH (r=0.80), and CA (r=0.74) between MR imaging and histology. ConclusionThe 3D VFA-TSE multi-contrast MR VWI is capable of accurately characterizing vulnerable carotid atherosclerotic plaques.

Reducing blood flow pulsation artifacts in 3D time-of-flight angiography by locally scrambling the order of the acquisition at 3 T and 7 T.

Non-contrast-enhanced time of flight (TOF) is a standard method for magnetic resonance angiography used to depict vessel morphology. TOF is commonly performed with a 3D steady-state acquisition, employing a short repetition time to support high resolution imaging. At 7 T, TOF exhibits substantial increase in SNR and contrast, improving its clinical value. However, one of the remaining challenges, exacerbated at 7 T, is the presence of artifacts due to pulsatile blood flow, especially near major blood vessels. In this study we examine a method to significantly reduce these artifacts. We recently introduced a new "local-scrambling" approach that semi-randomizes the acquisition order of the phase encodes, to achieve a controllable cutoff frequency above which the artifacts are drastically reduced. With this approach, artifacts resulting from fast local fluctuations such as cardiac pulsation are significantly reduced. In this study, we explore the ability of this local-scrambling approach to reduce pulsatile blood flow artifacts in a 3D TOF acquisition. Cartesian line-by-line and center-out ordering, with and without local-scrambling, were compared in simulations and in human brain imaging at 3 and 7 T scanners. In the simulations the artifact intensity showed a 10-fold reduction using local-scrambling compared to line-by-line and 4-fold compared to center-out ordering. In vivo results show that artifacts are much more pronounced at 7 T compared to 3 T, and in both cases they are effectively reduced by local-scrambling. Local-scrambling improves image quality for both line-by-line and center-out ordering. This approach can easily be implemented in the scanner without any changes to the reconstruction.

3D ToF LiDAR for Mobile Robotics in Harsh Environments: A Review

Over the past decade, the use of 3D Time-of-Flight (ToF) LiDARs in mobile robotics has grown rapidly. Based on our accumulation of relevant research, this paper systematically reviews and analyzes the use of 3D ToF LiDARs for mobile robotics under harsh conditions such as adverse weather, GPS-denied, and highly dynamic environments for both research and industrial applications. The former include LiDAR data processing in adverse weather, object detection, and autonomous navigation. The latter encompasses autonomous driving, service robotics, and public health crises applications. We hope that our efforts can effectively provide readers with a reference based on our hands-on experiences and promote the deployment of existing mature technologies in real-world systems.

Synthesizing 4D Magnetic Resonance Angiography From 3D Time-of-Flight Using Deep Learning: A Feasibility Study.

Objective and background This study aimed to develop a deep convolutional neural network (DCNN) model capable of generating synthetic 4D magnetic resonance angiography (MRA) from 3D time-of-flight (TOF) images, allowing estimation of temporal changes in arterial flow. TOF MRA provides static information about arterial structures through maximum intensity projection (MIP) processing, but it does not capture the dynamic information of contrast agent circulation, which is lost during MIP processing. Considering the principles of TOF, it is hypothesized that dynamic information about arterial blood flow is latent within TOF signals. Although arterial spin labeling (ASL) can extract dynamic arterial information, ASL MRA has drawbacks, such as longer imaging times and lower spatial resolution than TOF MRA. This study's primary aim is to extend the utility of TOF MRA by training a machine-learning model on paired TOF and ASL data to extract latent dynamic information from TOF signals. Methods A DCNN combining a modified U-Net and a long-short-term memory (LSTM) network was trained on a dataset of 13 subjects (11 menand two women, aged 42-77 years) using paired 3D TOF MRA and 4D ASL MRA images. Subjects had no history of cerebral vessel occlusion or significant stenosis. The dataset was acquired using a 3T MRI system with a 32-channel head coil. Preprocessing involved resampling and intensity normalization of TOF and ASL images, followed by data augmentation and arterial mask generation. The model learned to extract flow information from TOF images and generate 8-phase 4D MRA images. The precision of flow estimation was evaluated using the coefficient of determination (R²) and Bland-Altman analysis. A board-certified neuroradiologist validated the quality of the images and the absence of significant stenosis in the major cerebral arteries. Results The generated 4D MRA images closely resembled the ground-truth ASL MRA data, with R² values of 0.92, 0.85, and 0.84 for the internal carotid artery (ICA), proximal middle cerebral artery (MCA), and distal MCA, respectively. Bland-Altman analysis revealed a systematic error of -0.06, with 95% agreement limits ranging from -0.18 to 0.12. Additionally, the model successfully identified flow abnormalities in a subject with left MCA stenosis, displaying a delayed peak and subsequent flattening distal to the stenosis, indicative of reduced blood flow. Visualization of the predicted arterial flow overlaid on the original TOF MRA images highlighted the spatial progression and dynamics of the flow. Conclusions The DCNN model effectively generated synthetic 4D MRA images from TOF images, demonstrating its potential to estimate temporal changes in arterial flow accurately. This non-invasive technique offers a promising alternative to conventional methods for visualizing and evaluating healthy and pathological flow dynamics. It has significant potential to improve the diagnosis and treatment of cerebrovascular diseases by providing detailed temporal flow information without the need for contrast agents or invasive procedures. The practical implementation of this model could enable the extraction of dynamic cerebral blood flow information from routine brain MRI examinations, contributing to the early diagnosis and management of cerebrovascular disorders.

Deep learning-based platform performs high detection sensitivity of intracranial aneurysms in 3D brain TOF-MRA: An external clinical validation study

PurposeTo evaluate the diagnostic efficacy of a developed artificial intelligence (AI) platform incorporating deep learning algorithms for the automated detection of intracranial aneurysms in time-of-flight (TOF) magnetic resonance angiography (MRA). MethodThis retrospective study encompassed 3D TOF MRA images acquired between January 2023 and June 2023, aiming to validate the presence of intracranial aneurysms via our developed AI platform. The manual segmentation results by experienced neuroradiologists served as the “gold standard”. Following annotation of MRA images by neuroradiologists using InferScholar software, the AI platform conducted automatic segmentation of intracranial aneurysms. Various metrics including accuracy (ACC), balanced ACC, area under the curve (AUC), sensitivity (SE), specificity (SP), F1 score, Brier Score, and Net Benefit were utilized to evaluate the generalization of AI platform. Comparison of intracranial aneurysm identification performance was conducted between the AI platform and six radiologists with experience ranging from 3 to 12 years in interpreting MR images. Additionally, a comparative analysis was carried out between radiologists’ detection performance based on independent visual diagnosis and AI-assisted diagnosis. Subgroup analyses were also performed based on the size and location of the aneurysms to explore factors impacting aneurysm detectability. Results510 patients were enrolled including 215 patients (42.16 %) with intracranial aneurysms and 295 patients (57.84 %) without aneurysms. Compared with six radiologists, the AI platform showed competitive discrimination power (AUC, 0.96), acceptable calibration (Brier Score loss, 0.08), and clinical utility (Net Benefit, 86.96 %). The AI platform demonstrated superior performance in detecting aneurysms with an overall SE, SP, ACC, balanced ACC, and F1 score of 91.63 %, 92.20 %, 91.96 %, 91.92 %, and 90.57 % respectively, outperforming the detectability of the two resident radiologists. For subgroup analysis based on aneurysm size and location, we observed that the SE of the AI platform for identifying tiny (diameter＜3mm), small (3 mm ≤ diameter＜5mm), medium (5 mm ≤ diameter＜7mm) and large aneurysms (diameter ≥ 7 mm) was 87.80 %, 93.14 %, 95.45 %, and 100 %, respectively. Furthermore, the SE for detecting aneurysms in the anterior circulation was higher than that in the posterior circulation. Utilizing the AI assistance, six radiologists (i.e., two residents, two attendings and two professors) achieved statistically significant improvements in mean SE (residents: 71.40 % vs. 88.37 %; attendings: 82.79 % vs. 93.26 %; professors: 90.07 % vs. 97.44 %; P < 0.05) and ACC (residents: 85.29 % vs. 94.12 %; attendings: 91.76 % vs. 97.06 %; professors: 95.29 % vs. 98.82 %; P < 0.05) while no statistically significant change was observed in SP. Overall, radiologists’ mean SE increased by 11.40 %, mean SP increased by 1.86 %, and mean ACC increased by 5.88 %, mean balanced ACC promoted by 6.63 %, mean F1 score grew by 7.89 %, and Net Benefit rose by 12.52 %, with a concurrent decrease in mean Brier score declined by 0.06. ConclusionsThe deep learning algorithms implemented in the AI platform effectively detected intracranial aneurysms on TOF-MRA and notably enhanced the diagnostic capabilities of radiologists. This indicates that the AI-based auxiliary diagnosis model can provide dependable and precise prediction to improve the diagnostic capacity of radiologists.

Model-Based 3D Gaze Estimation Using a TOF Camera.

Among the numerous gaze-estimation methods currently available, appearance-based methods predominantly use RGB images as input and employ convolutional neural networks (CNNs) to detect facial images to regressively obtain gaze angles or gaze points. Model-based methods require high-resolution images to obtain a clear eyeball geometric model. These methods face significant challenges in outdoor environments and practical application scenarios. This paper proposes a model-based gaze-estimation algorithm using a low-resolution 3D TOF camera. This study uses infrared images instead of RGB images as input to overcome the impact of varying illumination intensity in the environment on gaze estimation. We utilized a trained YOLOv8 neural network model to detect eye landmarks in captured facial images. Combined with the depth map from a time-of-flight (TOF) camera, we calculated the 3D coordinates of the canthus points of a single eye of the subject. Based on this, we fitted a 3D geometric model of the eyeball to determine the subject's gaze angle. Experimental validation showed that our method achieved a root mean square error of 6.03° and 4.83° in the horizontal and vertical directions, respectively, for the detection of the subject's gaze angle. We also tested the proposed method in a real car driving environment, achieving stable driver gaze detection at various locations inside the car, such as the dashboard, driver mirror, and the in-vehicle screen.

Simultaneous time-of-flight MR angiography and quantitative susceptibility mapping with key time-of-flight features.

A technique for combined time-of-flight (TOF) MR angiography (MRA) and quantitative susceptibility mapping (QSM) was developed with key features of standard three-dimensional (3D) TOF acquisitions, including multiple overlapping thin slab acquisition (MOTSA), ramped RF excitation, and venous saturation. The developed triple-echo 3D TOF-QSM sequence enabled TOF-MRA, susceptibility-weighted imaging (SWI), QSM, and R2* mapping. The effects of ramped RF, resolution, flip angle, venous saturation, and MOTSA were studied on QSM. Six volunteers were scanned at 3 T with the developed sequence, conventional TOF-MRA, and conventional SWI. Quantitative comparison of susceptibility values on QSM and normalized arterial and venous vessel-to-background contrasts on TOF and SWI were performed. The ramped RF excitation created an inherent phase variation in the raw phase. A generic correction factor was computed to remove the phase variation to obtain QSM without artifacts from the TOF-QSM sequence. No statistically significant difference was observed between the developed and standard QSM sequence for susceptibility values. However, maintaining standard TOF features led to compromises in signal-to-noise ratio for QSM and SWI, arising from the use of MOTSA rather than one large 3D slab, higher TOF spatial resolution, increased TOF background suppression due to larger flip angles, and reduced venous signal from venous saturation. In terms of vessel contrast, veins showed higher normalized contrast on SWI derived from TOF-QSM than the standard SWI sequence. While fast flowing arteries had reduced contrast compared with standard TOF-MRA, no statistical difference was observed for slow flowing arteries. Arterial contrast differences largely arise from the longer TR used in TOF-QSM over standard TOF-MRA to accommodate additional later echoes for SWI. In conclusion, although the sequence has a longer TR and slightly lower arterial contrast, provided an adequate correction is made for ramped RF excitation effects on phase, QSM may be performed from a multiecho sequence that includes all key TOF features, thus enabling simultaneous TOF-MRA, SWI, QSM, and R2* map computation.

Determining Body Condition of Dairy Cows for Early Diagnosis of Physiological Diseases

The paper points out the problem with automated diagnostics of body condition in dairy cattle, including ketosis. The conducted research is aimed at determining the possibility for non-contact automated diagnostics of the cattle physiological state on a daily basis. (Research purpose) To develop an algorithm for complex operational diagnostics of the physiological state of dairy cows by their live weight and body condition. (Materials and methods) Field data were collected in 2021-2022 on the FSUE Grigoryevskoye (Yaroslavl Region), Istra Cheese Factory and Lenin Dairy State Farm (Moscow Region). A commercial 3D ToF (Time-of-Flight) camera O3D303 was used. The 3D camera is capable of calculating and displaying the Point Cloud space as a multidimensional array. The program received 144 images, 136 images passed the filtering stage, 6 images did not detect the areas of interest, because of the high level of image noise, and the sacrum was not detected. 62 cows were subject to research. (Results and discussion) The sample and the dependence are proved to be representative as the Pearson correlation coefficient equals R=0.849, which shows a strong linear relationship between the body condition score and live weight. It was determined that in 24 percent of cases the body condition score is less than the least normal one. An algorithm was developed to help veterinarians to detect the animals that need additional examination. (Conclusions) It was found that the developed algorithm helps to quickly detect ketosis in dairy cows and automatically diagnose physiological diseases at an early stage, without additional labor and monetary costs.

Fetal-placental MR angiography at 1.5 T and 3 T

ObjectivesThe objective of this work was to investigate the application of 2D Time-of-Flight (TOF) magnetic resonance angiography (MRA) to observe the placental vasculature at both 1.5 T and 3 T. MethodsFifteen appropriate for gestational age (AGA) (GA: 29.7 ± 3.4 weeks; GA range: 23 and 6/7 weeks to 36 and 2/7 weeks) and eleven patients with an abnormal singleton pregnancy (GA: 31.4 ± 4.4 weeks; GA range: 24 weeks to 35 and 2/7 weeks) were recruited in the study. Three AGA patients were scanned twice at different gestational ages. Patients were scanned either at 3 T or 1.5 T using both T2-HASTE and 2D TOF to image the entire placental vasculature. ResultsThe umbilical, chorionic vessels, stem vessels, arcuate arteries, radial arteries, and spiral arteries were shown in most of the subjects. Hyrtl's anastomosis was found in two subjects in the 1.5 T data. The uterine arteries were observed in more than half of the subjects. For those patients scanned twice, the same spiral arteries were identified in both scans. Conclusions2D TOF is a technique that can be applied in studying the fetal-placental vasculature at both 1.5 T and 3 T.

Accuracy of a time-of-flight (ToF) imaging system for monitoring deep-inspiration breath-hold radiotherapy (DIBH-RT) for left breast cancer patients.

Deep inspiration breath-hold radiotherapy (DIBH-RT) reduces cardiac dose by over 50%. However, poor breath-hold reproducibility could result in target miss which compromises the treatment success. This study aimed to benchmark the accuracy of a Time-of-Flight (ToF) imaging system for monitoring breath-hold during DIBH-RT. The accuracy of an Argos P330 3D ToF camera (Bluetechnix, Austria) was evaluated for patient setup verification and intra-fraction monitoring among 13 DIBH-RT left breast cancer patients. The ToF imaging was performed simultaneously with in-room cone beam computed tomography (CBCT) and electronic portal imaging device (EPID) imaging systems during patient setup and treatment delivery, respectively. Patient surface depths (PSD) during setup were extracted from the ToF and the CBCT images during free breathing and DIBH using MATLAB (MathWorks, Natick, MA) and the chest surface displacement were compared. The mean difference ± standard deviation, correlation coefficient, and limit of agreement between the CBCT and ToF were 2.88 ± 5.89mm, 0.92, and -7.36, 1.60mm, respectively. The breath-hold stability and reproducibility were estimated using the central lung depth extracted from the EPID images during treatment and compared with the PSD from the ToF. The average correlation between ToF and EPID was -0.84. The average intra-field reproducibility for all the fields was within 2.70mm. The average intra-fraction reproducibility and stability were 3.74mm, and 0.80mm, respectively. The study demonstrated the feasibility of using ToF camera for monitoring breath-hold during DIBH-RT and shows good breath-hold reproducibility and stability during the treatment delivery.

Whole-Neck Non-Contrast-Enhanced MR Angiography Using Velocity Selective Magnetization Preparation.

This study aimed to optimize velocity-selective magnetic resonance angiography (VS-MRA) protocols for whole-neck angiography and demonstrate its feasibility in healthy subjects with comparisons to clinical 3D time-of-flight (TOF) angiography. To help optimize VS-MRA protocols, 2D phase-contrast (PC) flow imaging and 3D B0 and B1 field mappings were performed on five healthy volunteers. Based on these measurements, a slab-selective (SS) inversion preparation was applied prior to a VS saturation preparation to further suppress venous blood, while the VS preparation pulse was designed with compensation for field offsets. VS-MRA and 3D TOF were performed on six healthy subjects, and relative contrast ratios (CRs) between artery and muscle signals were calculated for twenty arterial regions for comparisons. The pre-compensated VS pulse improved the visualization of the subclavian arteries and suppression of background tissues, which involved large B0 and B1 field errors. The combination of SS and VS preparations effectively suppressed venous blood. While the relative CR values were 0.78 ± 0.08 and 0.72 ± 0.10 for VS-MRA and 3D TOF, respectively, over the twenty segments, VS-MRA outperformed 3D TOF in visualizing arterial segments of a small size or with a horizontal orientation, such as subclavian, facial, and occipital arteries. The proposed neck VS-MRA with the field-error-compensated VS preparation combined with the SS preparation is feasible and superior to 3D TOF in visualizing small and/or horizontally oriented arterial segments.

A Combination of 3D TOF MRA and FIESTA Predicts Surgery-Needed Primary Trigeminal Neuralgia and Specific Offending Vessels.

To investigate the predictive accuracy of three-dimension (3D) time-of-flight (TOF) MR angiography (MRA) and 3D Fast Imaging Employing Steady-state Acquisition (FIESTA) techniques in assessing neurovascular compression (NVC) with specific vessels in patients with primary trigeminal neuralgia (TN). Patients with single-site primary TN undergoing microvascular decompression (MVD) were retrospectively recruited. All patients had available preoperative magnetic resonance imaging (MRI) scans. A quantitative NVC scoring system was applied to assess the severity of NVC on MRI. The radiological findings were correlated with the intraoperative result to determine the diagnostic accuracy of MRI techniques. Besides, the radiological indicator of MVD was determined. Seventy-three TN patients were recruited. Thirty-three patient had bilateral NVC but with unilateral neuralgia. The average NVC score of the asymptomatic side was significantly lower than that of the symptomatic side (1.6 vs. 6.7; p < 0.001). A cut-off value of NVC >4 was determined as a radiological indicator of MVD with sensitivity and specificity of 82.2% and 98.6%, respectively Area Under Curve (AUC = 0.97; p < 0.001). Approximately 90% of symptomatic patients had the distance to REZ ≤3 mm. 68.5% of patients had a single conflicting vessel, and superior cerebellar artery (SCA) was the predominate vessel (46.6%). The sensitivity and specificity of MRI to detect NVC were 95.8% and 100%, respectively. Regarding each vessel, the cohen's kappa statistic (K) was 0.632 overall. 3D TOF MRA and FIESTA show an overall good ability to predict specific offending vessels. NVC score >4 is identified to predict TN, suggestive of subsequent surgical treatment.

Time-of-Flight Intracranial MRA at 3 T versus 5 T versus 7 T: Visualization of Distal Small Cerebral Arteries.

Background Three-dimensional (3D) time-of-flight (TOF) MR angiography (MRA) at 7 T has been reported to have high image quality for visualizing small perforating vessels. However, B1 inhomogeneity and more physiologic considerations limit its applications. Angiography at 5 T may provide another choice for intracranial vascular imaging. Purpose To evaluate the image quality and cerebrovascular visualization of 5-T 3D TOF MRA for visualizing intracranial small branch arteries. Materials and Methods Participants (healthy volunteers or participants with a history of ischemic stroke undergoing intracranial CT angiography or MRA for identifying steno-occlusive disease) were prospectively included from September 2021 to November 2021. Each participant underwent 3-T, 5-T, and 7-T 3D TOF MRA with use of customized MR protocols within 48 hours. Radiologist scoring from 0 (invisible) to 3 (excellent) and quantitative assessment were obtained to evaluate the image quality. The Friedman test was used for comparison of characteristics derived from 3 T, 5 T, and 7 T. Results A total of 12 participants (mean age ± SD, 38 years ± 9; nine men) were included. Visualizations of the distal arteries and small vessels at 5-T TOF MRA were significantly higher than those at 3 T (median score: 3.0 vs 2.0, all P < .001 for distal segments and lenticulostriate artery; median score: 2.0 vs 0, P < .001 for pontine artery). The total length of small vessel branches detected at 5 T was larger than that at 3 T (5.1 m ± 0.7 vs 1.9 m ± 0.4; P < .001). However, there was no evidence of a significant difference compared with 7 T in either the depiction of distal segments and small vessel branches (average median score, 2.5; all P > .05) or the quantitative measurements (total length, 5.6 m ± 0.5; P = .41). Conclusion Three-dimensional time-of-flight MR angiography at 5 T presented the capability to provide superior visualization of distal large arteries and small vessel branches (in terms of subjective and quantitative assessment) to 3 T and had image quality similar to 7 T. © RSNA, 2022 Online supplemental material is available for this article. An earlier incorrect version appeared online. This article was corrected on September 14, 2022.

Non-invasive angiographic analysis of dural carotid cavernous fistula using time-of-flight MR angiography and silent MR angiography: a comparative study.

A non-invasive, reliable imaging modality that characterizes cavernous sinus dural arteriovenous fistula (CSDAVF) is beneficial for diagnosis and to assess resolution on follow-up. To assess the utility of 3D time-of-flight (TOF) and silent magnetic resonance angiography (MRA) for evaluation of CSDAVF from an endovascular perspective. This prospective study included 37 patients with CSDAVF, who were subjected to digital subtraction angiography (DSA) and 3-T MR imaging with 3D TOF and silent MRA. The main arterial feeders, fistula site, and venous drainage pattern were evaluated, and the results were compared with DSA findings. The diagnostic confidence scores were also recorded using a 4-point Likert scale. Silent MRA correlated better for shunt site localization and angiographic classification (86% vs. 75% and 83% vs. 75%, respectively) compared to TOF MRA. The proportion of arterial feeders detected was marginally significant for silent MRA over TOF MRA sequences (92.8% vs. 89.5%; P=0.048), though for veins both were comparable. Sensitivity of silent MRA was higher for identification of cortical venous reflux (CVR) (90.9% vs. 81.8%) and deep venous drainage (82.4% vs. 64.7%), while specificity was >90% for both modalities. The overall diagnostic confidence score fared better for silent MRA for venous assessment (P < 0.001) as well as fistula point identification (P < 0.001), while no significant difference was evident with TOF MRA for arterial feeders (P=0.06). Various angiographic components of CSDAVF could be identified and delineated by 3D TOF and silent MRA, though silent MRA was superior for overall diagnostic assessment.

Unespected dectection of unruptured brain arteriovenous malformation with 18F-DOPA PET/MR.

Unruptured brain arteriovenous malformations (AVM) have a heterogeneous clinical presentation, mainly related to the presence of intracerebral hemorrhage. We report the diagnosis of AVM in a patient with Parkinson's disease (PD), who undergone positron emission tomography/magnetic resonance imaging (PET/MRI) molecular brain imaging with fluorine-18-dihydroxyphenylalanine (18F-DOPA). This case suggests that AVM may be occasionally recognized in molecular imaging studies using positron-emitting amino acids. Magnetic resonance imaging with susceptibility-weighted imaging (SWI) sequences and 3D time of flight (TOF) reconstruction may contribute to manage patients with AVM.

DOP13 The Arborisation index: An MRI-based measure of mesenteric hyperaemia in Crohn’s Disease

Abstract Background Robust and sensitive therapeutic targets are key in effective management of Inflammatory Bowel Disease1. Mesenteric hyperaemia is a recognized sign of active disease and in cross-sectional image is described as the comb sign. Although it is subjectively described, no automated quantitative MRI-based measures have been developed. We aim to develop an automated methodology using contrast-less time of flight (TOF) Magnetic resonance angiography (MRA). Methods A MATLAB algorithm was developed to track the vessels on a 3D maximum intensity projection of a TOF MRA data set and calculate an arborization Index which is the number of branching points in the intrabdominal vessels (figure 1). 2D TOF scans were acquired in the transverse plane between the top of the hip joint and L4 vertebra using a 3T Ingenia Wide bore scanner (Philips, The Netherlands). The primary outcome was a comparison of the arborization index between Crohn’s disease (CD) and healthy volunteers (HV) groups. A planned sub-analysis was undertaken across CD and HV matched for BMI to investigate the effect of visceral fat on the arborization index. Repeated measures were undertaken to evaluate the variability of the quantification method. No contrast agents were used for the TOF MRA scans. Biological variations within each group and test-retest repeatability were assessed using the coefficient of variation (CV). Statistical analysis with unpaired, two-tailed t-tests were conducted and differences were considered significant when the p-value ≤0.05. All absolute values are presented as mean ±standard deviation (SD). Results In this prospective pilot study, 7 CD patients (C-Reactive Protein=5.2±6.1 mg/L, Faecal Calprotectin 611±981μg/g, BMI=23±3 kg/m2) and 15 HVs (BMI=29±7 kg/m2) were recruited. Patients showed a significantly higher arborization index when compared to HVs (mean arborization in HV=94±21 and CD=139±26; p-value=0.002). The difference in arborization index persisted in a sub-analysis of 7 HVs (BMI=24±2 kg/m2) and 7 CD patients (mean arborization in matched HVs=101±22 vs mean index in CD=139±26; p=0.01) (Figure 2). The CV was 23% for HVs and 18% for CD indicating biological variation. Test-retest variability calculated from multiple TOF scans of the same subjects gave a mean CV of 6±5% for both groups combined. Conclusion Our preliminary data suggest that the arborization index may be a useful measure of hypervascularity and hence intestinal inflammation in Inflammatory Bowel Disease. Further validation to standard disease activity measures is needed across larger cohorts to better investigate the utility of this potential biomarker as a non-invasive measure of disease activity and its reversibility to IBD therapies. Reference 1.Turner,D.,et al.Gastro.2021;160(5):1570–1583.

Spiral 3D time-of-flight MR angiography for rapid non-contrast carotid artery imaging: Clinical feasibility and protocol optimization.

To assess the clinical feasibility of spiral 3D Time-Of-Flight (TOF) MR Angiography (MRA) sequence variants for rapid non-contrast carotid artery imaging. Nine different 3D TOF MRA sequences were acquired in nine healthy volunteers on a standard clinical 1.5T scanner. Three cartesian sequences (fully sampled (10:15min), accelerated with SENSE (05:08min), accelerated with Compressed SENSE (03:32min)) and six different spiral sequences were acquired (spiral acquisition windows ranging from 10 to 5ms (01:32min-03:05min)). Three readers graded the images qualitatively in terms of overall image quality, vessel sharpness, inhomogeneous intraluminal signal, background noise, visualization of large and small vessels and overall impression of the number of visible vessels. Cross-sectional areas of the vessel lumen were measured and vessel sharpness was quantified. The SENSE and Compressed SENSE accelerated cartesian sequences and the Spiral 6ms and 5ms sequences were deemed comparable to the fully sampled cartesian sequence in most qualitative categories (p>0.05) based on exact binomial tests. The Spiral 6ms and 5ms sequences achieved a scan time reduction of 75.3% and 69.9% respectively compared to the fully sampled cartesian sequence. The spiral sequences (generally) exhibited improved subjective vessel sharpness (p<0.01-p=0.13) but increased background noise (p=0.03-p=0.25). Cross-sectional area measurements were similar between all sequences (Krippendorff's alpha: 0.955-0.982). Quantitative vessel sharpness was increased for all spiral sequences compared to all cartesian sequences (p=0.004). Spiral 3D TOF MRA sequences with a spiral acquisition window of 5ms or 6ms may be used for accurate, rapid, clinical non-contrast carotid artery imaging.

Time-magnified photon counting with 550-fs resolution

Time-correlated single-photon counting (TCSPC) is an enabling technology for applications such as low-light fluorescence lifetime microscopy and photon counting time-of-flight (ToF) 3D imaging. However, state-of-the-art TCSPC single-photon timing resolution (SPTR) is limited to 3–100 ps by single-photon detectors. Here, we experimentally demonstrate a time-magnified TCSPC (TM-TCSPC) that achieves an ultrashort SPTR of 550 fs with an off-the-shelf single-photon detector. The TM-TCSPC can resolve ultrashort pulses with a 130-fs pulse width difference at a 22-fs accuracy. When applied to photon counting ToF 3D imaging, the TM-TCSPC greatly suppresses the range walk error that limits all photon counting ToF 3D imaging systems by 99.2% and thus provides high depth accuracy and precision of 26 µm and 3 µm, respectively.

Quantitative time-of-flight MR angiography for simultaneous luminal and hemodynamic evaluation of the intracranial arteries.

To report a quantitative time-of-flight (qTOF) MRA technique for simultaneous luminal and hemodynamic evaluation of the intracranial arteries. Implemented using a thin overlapping slab 3D stack-of-stars based 3-echo FLASH readout, qTOF was tested in a flow phantom and for imaging the intracranial arteries of 10 human subjects at 3 Tesla. Display of the intracranial arteries with qTOF was compared to resolution-matched and scan time-matched standard Cartesian 3D time-of-flight (TOF) MRA, whereas quantification of mean blood flow velocity with qTOF, done using a computer vision-based inter-echo image analysis procedure, was compared to 3D phase contrast MRA. Arterial-to-background contrast-to-noise ratio was measured, and intraclass correlation coefficient was used to evaluate agreement of flow velocities. For resolution-matched protocols of similar scan time, qTOF portrayed the intracranial arteries with good morphological correlation with standard Cartesian TOF, and both techniques provided superior contrast-to-noise ratio and arterial delineation compared to phase contrast (20.6 ± 3.0 and 37.8 ± 8.7 vs. 11.5 ± 2.2, P < .001, both comparisons). With respect to phase contrast, qTOF showed excellent agreement for measuring mean flow velocity in the flow phantom (intraclass correlation coefficient = 0.981, P < .001) and good agreement in the intracranial arteries (intraclass correlation coefficient = 0.700, P < .001). Stack-of-stars data sampling used with qTOF eliminated oblique in-plane flow misregistration artifacts that were seen with standard Cartesian TOF. qTOF is a new 3D MRA technique for simultaneous luminal and hemodynamic evaluation of the intracranial arteries that provides significantly greater contrast-to-noise ratio efficiency than phase contrast and eliminates misregistration artifacts from oblique in-plane blood flow that occur with standard 3D TOF.