Frame Rate Reduction Research Articles

Comparison of angiography-derived index of microcirculatory resistance measurements between low and high frame-rate acquisitions: the prospective ADMIRAL-study

Abstract Background Angiography-derived index of microcirculatory resistance (angio-IMR) is a novel, wire-free, angiography-based method (QFR-IMR®) to assess coronary microvascular dysfunction. If a frame-rate of 15 frames per second (fps) is recommended, there is an interest in decreasing this frame-rate to reduce X-ray exposure. However, the impact of frame-rate reduction on angio-IMR quantification has not been investigated. Purpose To compare angio-IMR at 7.5 fps (angio-IMRlow) to angio-IMR at 15 fps (angio-IMRhigh) in a multicentric study. Methods From October 2023 to February 2024, we conducted a multicentre prospective study including consecutive patients referred for an invasive coronary angiogram with a final diagnosis of ischemia with no obstructive coronaries arteries (INOCA) (positive stress test with normal coronary angiogram) or acute coronary syndrome (ACS). Main exclusion criteria were creatinine clearance<45ml/kg/1.73m2, factors that might substantially impact the coronary angiograms quality (e.g: aortic stenosis, supraventricular tachycardia), and TIMI flow <3. In ACS patients, angio-IMR was measured after revascularisation. The same two acquisitions with different angles (≥25°) were recorded at a rate of 7.5 fps and a rate of 15 fps to measure angio-IMR in the selected vessel (culprit coronary vessel in ACS patients or left anterior descending artery in patients with INOCA). Angio-IMR was measured with dedicated software (QFR-IMR® RE, Medis Medical Imaging). Correlation between angio-IMRlow and angio-IMRhigh was assessed by linear regression and Bland-Altman test. The diagnostic accuracy of angio-IMRlow to predict microcirculatory dysfunction (defined as angio-IMRhigh≥ 25 for INOCA and ≥ 40 for ACS) was also assessed. Statistical significance was awarded by p≤0.05. Results Of 87 consecutive eligible patients, 75 were included in the study, comprising 57 with ACS and 18 with INOCA (mean age 61±12 years, 72% male). Angio-IMRlow (median=35; [IQR:28-48]) was slightly but significantly higher (p=0.04) than angio-IMRhigh (median=34; [IQR:25-45]). Angio-IMRlow and angio-IMRhigh were significantly correlated (r=0.90; p<0.0001) (Figure 1). Using Bland-Altman analysis, mean difference between the two measurements was 2.2 (95% CI 0.1-4.4) with a significant higher value with angio-IMRlow (p=0.04). Moreover, as value of Angio-IMRhigh increases, the difference between angio-IMRlow and angio-IMRhigh becomes more significant (Figure 2). Using angio-IMRhigh to diagnose microcirculatory dysfunction as reference, angio-IMRlow achieved positive and negative predictive values of 83% and 85% respectively with 6 false positives, and 6 false negatives. Conclusion Correlation between angio-IMRhigh and angio-IMRlow is acceptable. Lowering frame acquisition rate reduces radiation exposure without relevantly impact on the diagnostic accuracy of angio-IMR, which can contribute to a widespread use of angio-IMR.Correlation between angioIMRlow and highBland-Altman plot

Time Efficient Ultrasound Localization Microscopy Based on A Novel Radial Basis Function 2D Interpolation.

Ultrasound localization microscopy (ULM) allows for the generation of super-resolved (SR) images of the vasculature by precisely localizing intravenously injected microbubbles. Although SR images may be useful for diagnosing and treating patients, their use in the clinical context is limited by the need for prolonged acquisition times and high frame rates. The primary goal of our study is to relax the requirement of high frame rates to obtain SR images. To this end, we propose a new time-efficient ULM (TEULM) pipeline built on a cutting-edge interpolation method. More specifically, we suggest employing Radial Basis Functions (RBFs) as interpolators to estimate the missing values in the 2-dimensional (2D) spatio-temporal structures. To evaluate this strategy, we first mimic the data acquisition at a reduced frame rate by applying a down-sampling (DS = 2, 4, 8, and 10) factor to high frame rate ULM data. Then, we up-sample the data to the original frame rate using the suggested interpolation to reconstruct the missing frames. Finally, using both the original high frame rate data and the interpolated one, we reconstruct SR images using the ULM framework steps. We evaluate the proposed TEULM using four in vivo datasets, a Rat brain (dataset A), a Rat kidney (dataset B), a Rat tumor (dataset C) and a Rat brain bolus (dataset D), interpolating at the in-phase and quadrature (IQ) level. Results demonstrate the effectiveness of TEULM in recovering vascular structures, even at a DS rate of 10 (corresponding to a frame rate of sub-100Hz). In conclusion, the proposed technique is successful in reconstructing accurate SR images while requiring frame rates of one order of magnitude lower than standard ULM.

36‐3: Research on Partitioned Color Calibration Principle and Frame Rate Reduction Technology Based on Liquid Crystal Displays

36‐3: Research on Partitioned Color Calibration Principle and Frame Rate Reduction Technology Based on Liquid Crystal Displays

Complete Complementary Coded Excitation Scheme for SNR Improvement of 2D Sparse Array Ultrasound Imaging.

Driving the numerous elements of 2D matrix arrays for 3D ultrasound imaging is very challenging in terms of cable size, wiring and data rate. The sparse array approach tackles this problem by optimally distributing a reduced number of elements over a 2D aperture while preserving a decent image quality and beam steering capabilities. Unfortunately, reducing the number of elements significantly reduces the active probe footprint reducing as a consequence the sensitivity and at the end the signal-to-noise ratio. Here we propose a new coded excitation scheme based on complete complementary codes to increase the signal-to-noise ratio in 3D ultrasound imaging with sparse arrays. These codes are known for their ideal auto-correlation and cross-correlation properties and have been widely used in Code-Division Multiple Access systems (CDMA). An algorithm for generating such codes is presented as well as the adopted imaging sequence. The proposed method has been compared in simulations to other coded excitation schemes and showed significant increase in the signal-to-noise ratio of sparse arrays with no correlation artifacts and no frame rate reduction. The gain in signal-to-noise ratio compared to the case where no coded excitation is used was around [Formula: see text] and the contrast was also improved by [Formula: see text] while the resolution was unchanged.

Model-based deep learning for ultrasound localization microscopy

Ultrasound localization microscopy (ULM) effectively visualizes vasculature through localization of microbubbles using ultrasound. However, challenges arise from the domain gap between clean data from controlled lab environments and real-world scenarios. Factors, such as high bubble densities, reduced frame rates, and poor image quality (e.g., due to aberration), impede clinical adoption. Traditional methods face limitations in handling the challenging nature of ULM, which have spurred the integration of data-driven techniques. We specifically focus on model-based deep learning, emphasizing statistical inference techniques for increased robustness on out-of-distribution data. The localization task is expressed as an inverse problem y = Hx + n, where y, x, and n represent the observed ultrasound signal, underlying microbubble localizations, and noise. Inaccuracies in the measurement matrix H arise from oversimplified ultrasound acquisition models (i.e., aberration distorting the point-spread function), necessitating the application of spatial priors to regularize the forward model. The ISTA algorithm can enforce sparsity on x and help solve the ill-posed inverse problem. A deep learning extension, namely learned ISTA, can additionally mitigate errors in the forward model. Beyond spatial priors, imposing temporal priors on individual microbubbles enhances accuracy. KalmanNet, integrating Kalman filtering with deep learning, exemplifies this approach by effectively learning the temporal dynamics of microbubbles.

A parametrization study of TEULM’s image reconstruction performance

Time efficient ultrasound localization microscopy (TEULM) allows imaging the microvascular structures with reduced frame rates compared to standard ULM. The quality of reconstructed images relies on different parameters. In this study, we aim at understanding the links between TEULM performance and three key parameters: SVD k-value (representing the number of components considered as noise), the maximum linking distance (indicating the assumed maximum distance that a microbubble can cover between two successive frames), and the minimum length of a track. We generated TEULM density and dynamics maps, singularly varying these three parameters. Next, we evaluated the quality of TEULM images by means of a root mean squared error (RMSE), dice score, and Fourier ring correlation (FRC) analysis. A publicly available preclinical in-vivo dataset was used for this study. Results demonstrate that minimum track length and k-value have the greatest impact on both density and dynamic maps RMSE, whereas the minimum linking distance is the key factor influencing the dice score. Additionally, the relationship between these parameters and metrics is non-linear. Furthermore, the resolution measured by the FRC is negatively affected by increasing the SVD k-value and by increasing the maximum linking distance but positively affected by increasing the minimum track length.

Synthetic interpolated DSA for radiation exposure reduction via gamma variate contrast flow modeling: a retrospective cohort study

BackgroundDigital subtraction angiography (DSA) yields high cumulative radiation dosages (RD) delivered to patients. We present a temporal interpolation of low frame rate angiograms as a method to reduce cumulative RDs.MethodsPatients undergoing interventional evaluation and treatment of cerebrovascular vasospasm following subarachnoid hemorrhage were retrospectively identified. DSAs containing pre- and post-intervention runs capturing the full arterial, capillary, and venous phases with at least 16 frames each were selected. Frame rate reduction (FRR) of the original DSAs was performed to 50%, 66%, and 75% of the original frame rate. Missing frames were regenerated by sampling a gamma variate model (GVM) fit to the contrast response curves to the reduced data. A formal reader study was performed to assess the diagnostic accuracy of the “synthetic” studies (sDSA) compared to the original DSA.ResultsThirty-eight studies met inclusion criteria (average RD 1,361.9 mGy). Seven were excluded for differing views, magnifications, or motion. GVMs fit to 50%, 66%, and 75% FRR studies demonstrated average voxel errors of 2.0 ± 2.5% (mean ± standard deviation), 6.5 ± 1.5%, and 27 ± 2%, respectively for anteroposterior projections, 2.0 ± 2.2%, 15.0 ± 3.1%, and 14.8 ± 13.0% for lateral projections, respectively. Reconstructions took 0.51 s/study. Reader studies demonstrated an average rating of 12.8 (95% CI 12.3−13.3) for 75% FRR, 12.7 (12.2−13.2) for 66% FRR and 12.0 (11.5−12.5) for 50% FRR using Subjective Image Grading Scale. Kendall’s coefficient of concordance resulted in W = 0.506.ConclusionFRR by 75% combined with GVM reconstruction does not compromise diagnostic quality for the assessment of cerebral vasculature.Relevance statementUsing this novel algorithm, it is possible to reduce the frame rate of DSA by as much as 75%, with a proportional reduction in radiation exposure, without degrading imaging quality.Key points• DSA delivers some of the highest doses of radiation to patients.• Frame rate reduction (FRR) was combined with bolus tracking to interpolate intermediate frames.• This technique provided a 75% FRR with preservation of diagnostic utility as graded by a formal reader study for cerebral angiography performed for the evaluation of cerebral vasospasm.• This approach can be applied to other types of angiography studies.Graphical

Reducing frame rate and pulse rate for routine diagnostic cerebral angiography: ALARA principles in practice.

Diagnostic cerebral angiograms (DCAs) are widely used in neurosurgery due to their high sensitivity and specificity to diagnose and characterize pathology using ionizing radiation. Eliminating unnecessary radiation is critical to reduce risk to patients, providers, and health care staff. We investigated if reducing pulse and frame rates during routine DCAs would decrease radiation burden without compromising image quality. We performed a retrospective review of prospectively acquired data after implementing a quality improvement protocol in which pulse rate and frame rate were reduced from 15 p/s to 7.5 p/s and 7.5 f/s to 4.0 f/s respectively. Radiation doses and exposures were calculated. Two endovascular neurosurgeons reviewed randomly selected angiograms of both doses and blindly assessed their quality. A total of 40 consecutive angiograms were retrospectively analyzed, 20 prior to the protocol change and 20 after. After the intervention, radiation dose, radiation per run, total exposure, and exposure per run were all significantly decreased even after adjustment for BMI (all p<0.05). On multivariable analysis, we identified a 46% decrease in total radiation dose and 39% decrease in exposure without compromising image quality or procedure time. We demonstrated that for routine DCAs, pulse rate of 7.5 with a frame rate of 4.0 is sufficient to obtain diagnostic information without compromising image quality or elongating procedure time. In the interest of patient, provider, and health care staff safety, we strongly encourage all interventionalists to be cognizant of radiation usage to avoid unnecessary radiation exposure and consequential health risks.

Ultrafast Cardiac Imaging Using Deep Learning for Speckle-Tracking Echocardiography.

High-quality ultrafast ultrasound imaging is based on coherent compounding from multiple transmissions of plane waves (PW) or diverging waves (DW). However, compounding results in reduced frame rate, as well as destructive interferences from high-velocity tissue motion if motion compensation (MoCo) is not considered. While many studies have recently shown the interest of deep learning for the reconstruction of high-quality static images from PW or DW, its ability to achieve such performance while maintaining the capability of tracking cardiac motion has yet to be assessed. In this article, we addressed such issue by deploying a complex-weighted convolutional neural network (CNN) for image reconstruction and a state-of-the-art speckle-tracking method. The evaluation of this approach was first performed by designing an adapted simulation framework, which provides specific reference data, i.e., high-quality, motion artifact-free cardiac images. The obtained results showed that, while using only three DWs as input, the CNN-based approach yielded an image quality and a motion accuracy equivalent to those obtained by compounding 31 DWs free of motion artifacts. The performance was then further evaluated on nonsimulated, experimental in vitro data, using a spinning disk phantom. This experiment demonstrated that our approach yielded high-quality image reconstruction and motion estimation, under a large range of velocities and outperforms a state-of-the-art MoCo-based approach at high velocities. Our method was finally assessed on in vivo datasets and showed consistent improvement in image quality and motion estimation compared to standard compounding. This demonstrates the feasibility and effectiveness of deep learning reconstruction for ultrafast speckle-tracking echocardiography.

STDC-Net: A spatial-temporal deformable convolution network for conference video frame interpolation

AbstractVideo conference communication can be seriously affected by dropped frames or reduced frame rates due to network or hardware restrictions. Video frame interpolation techniques can interpolate the dropped frames and generate smoother videos. However, existing methods can not generate plausible results in video conferences due to the large motions of the eyes, mouth and head. To address this issue, we propose a Spatial-Temporal Deformable Convolution Network (STDC-Net) for conference video frame interpolation. The STDC-Net first extracts shallow spatial-temporal features by an embedding layer. Secondly, it extracts multi-scale deep spatial-temporal features through Spatial-Temporal Representation Learning (STRL) module, which contains several Spatial-Temporal Feature Extracting (STFE) blocks and downsample layers. To extract the temporal features, each STFE block splits feature maps along the temporal pathway and processes them with Multi-Layer Perceptron (MLP). Similarly, the STFE block splits the temporal features along horizontal and vertical pathways and processes them by another two MLPs to get spatial features. By splitting the feature maps into segments of varying lengths in different scales, the STDC-Net can extract both local details and global spatial features, allowing it to effectively handle large motions. Finally, Frame Synthesis (FS) module predicts weights, offsets and masks using the spatial-temporal features, which are used in deformable convolution to generate the intermediate frames. Experimental results demonstrate the STDC-Net outperforms state-of-the-art methods in both quantitative and qualitative evaluations. Compared to the baseline, the proposed method achieved a PSNR improvement of 0.13 dB and 0.17 dB on the Voxceleb2 and HDTF datasets, respectively.

Frame-rate reduction to reduce radiation dose for cardiac device implantation is safe.

Radiation exposure to patient and surgeon during cardiac implantable electrical device (CIED) procedures remains a substantial health hazard to date. Advanced technical options for radiation dose reduction often pose considerable financial hurdles. We propose a near-zero cost, low-effort modification to a clinical x-ray system significantly reducing radiation dose during CIED implantation. We aim to evaluate a reduced frame rate protocol in CIED implantation for complication rates and reduction in radiation exposure. Starting May 2019, the frame rate during CIED implantations at our hospital was halved from 7.5 frames/s to 3.8 frames/s, and no further technical changes were made. During the following year, 264 patients were operated using this protocol and retrospectively compared with 231 cases implanted in the year before the protocol change, totaling 495 cases. Of these, 17%, 63%, and 19% were single-chamber, dual-chamber, or resynchronization devices, respectively. Incidence of complication prior to hospital discharge was considered the primary endpoint of the analysis. Radiation dose and procedural parameters were secondary endpoints. There was no increase in complications with the reduced frame rate protocol. Regression analysis further supported that the reduced frame rate radiation protocol was not associated with complication rates. Radiation exposure measured as dose area product was significantly reduced by ∼62% (median 369 [interquartile range 154-1207] cGy·cm2 via the reduced frame rate protocol vs median 970 [interquartile range 400-1906] cGy·cm2 with the standard frame rate; P < 0.01). A reduction of frame rate during CIED implantation is safe in terms of complication incidence and effective in terms of reducing radiation exposure.

Subsurface impact damage imaging for composite structures using 3D digital image correlation

An integrated system is proposed to visualize subsurface barely visible impact damage (BVID) in composite structures using three-dimensional (3D) digital image correlation (3D DIC). This system uses a pair of digital cameras to record video frames in the field-of-view (FOV) of the structure’s surface, capturing the wavefield generated via chirp excitation in the near-ultrasonic frequency range. Significant pitfalls of previous efforts of damage imaging using two-dimensional DIC have been largely mitigated. First, 3D DIC enables capturing out-of-plane displacements, which are much larger in amplitude versus in-plane displacements that a single camera would be limited to sensing, thus increasing the signal-to-noise ratio. This enhancement in turn increases the sensitivity of the stereo-camera system. Second, a total wave energy (TWE) damage imaging condition is proposed to visualize the local damage region. The monogenic signal obtained via Reisz transform (RT) is employed to compute the instantaneous amplitude, with which the local wave energy can be calculated spatially over time. Since a high displacement amplitude and thus high wave energy will occur in the damage region due to the local resonance, the proposed TWE imaging condition can relax the Nyquist sampling requirement, unlike guided-wave-based structural health monitoring techniques which require fully reconstructing the wavefield and wave modes through sampling that satisfies the Nyquist criterion. As such, a much lower camera frame rate is adequate for the proposed system. Consequently, the maximum spatial resolution of the camera for a given FOV can be achieved at the expense of a reduced frame rate. With the maximized pixel resolution and reduced frame rate for employing the TWE imaging condition, composite structures can be inspected or monitored with a larger FOV. As a result, there is no longer any need to apply signal enhancement techniques, such as sample interleaving, image stitching, or averaging, to increase the effective performance of the camera. Rather than needing thousands of repeated videos for minimizing the incoherent noise, only a single stereo-video with a few seconds of sampling duration is necessary for damage imaging. The use of a powerful piezo-shaker also increases the wave signal amplitude and further enhances sensitivity without permanent adhesion. To demonstrate this stereo-camera concept with the TWE imaging condition, the system was used to image damage in two carbon fiber reinforced polymer composite honeycomb panels, which had been subjected to low-velocity impacts (2 J). For each panel, two excitation configurations were used to verify the robustness of the system. Initial damage maps produced for a 100 × 100-mm FOV using a three-second stereo-video show accurate damage imaging ability that is independent of excitation location and comparable to benchmark damage images computed from laser Doppler vibrometer data and those gathered from ultrasonic and X-ray computerized tomography scans. This efficient and reliable integrated system demonstrated high potential for in-time damage inspection on composite aircraft and other critical structures.

A Single-Shot Harmonic Imaging Approach Utilizing Deep Learning for Medical Ultrasound.

Tissue Harmonic Imaging (THI) is an invaluable tool in clinical ultrasound owing to its enhanced contrast resolution and reduced reverberation clutter in comparison to fundamental mode imaging. However, harmonic content separation based on high pass filtering suffers from potential contrast degradation or lower axial resolution due to spectral leakage. Whereas nonlinear multi-pulse harmonic imaging schemes, such as amplitude modulation and pulse inversion, suffer from a reduced framerate and comparatively higher motion artifacts due to the necessity of at least two pulse echo acquisitions. To address this problem, we propose a deep-learning-based single-shot harmonic imaging technique capable of generating comparable image quality to pulse amplitude modulation methods, yet at a higher framerate and with fewer motion artifacts. Specifically, an asymmetric convolutional encoder-decoder structure is designed to estimate the combination of the echoes resulting from the half-amplitude transmissions using the echo produced from the full amplitude transmission as input. The echoes were acquired with the checkerboard amplitude modulation technique for training. The model was evaluated across various targets and samples to illustrate generalizability as well as the possibility and impact of transfer learning. Furthermore, for possible interpretability of the network, we investigate if the latent space of the encoder holds information on the nonlinearity parameter of the medium. We demonstrate the ability of the proposed approach to generate harmonic images with a single firing that are comparable to those from a multi-pulse acquisition.

Low-dose fluoroscopy technique drastically decreases patient radiation exposure during percutaneous nephrolithotomy.

Fluoroscopy is essential in percutaneous nephrolithotomy (PCNL) but exposes patients and operating room staff to radiation. We investigated whether a low-dose (LD) protocol could reduce radiation exposure during fluoroscopy-guided access without compromising clinical outcomes. Patients undergoing PCNL with fluoroscopy-guided access at a tertiary care stone center between January 2019 and July 2021 were identified. Prior to September 3, 2020, the Philips Veradius C-arm's default settings were used: standard per-frame dose, 15 pulses per second (PPS) frame rate. After this date, a low-dose protocol was used: reduced per-frame dose, reduced frame rate of 8 PPS for needle puncture and 4 PPS for all other steps. Clinical and radiographical data were retrospectively collected. The primary outcome was cumulative radiation dose. Secondary outcomes were stone-free status (SFS; defined as no fragments ≥ 2mm) and complications. Multivariate regression analysis was performed. 100 patients were identified; 31 were in the LD group. The LD cohort was exposed to a significantly lower mean cumulative radiation dose of 11.68mGy compared to 48.88mGy (p < 0.0001). There were no differences in operative time, fluoroscopy time, stone burden, SFS, or complications. In a multivariable regression model adjusting for several variables, LD protocol was associated with lower radiation dose while skin-to-calyx-distance (STCD) was positively associated with cumulative radiation dose. Low-dose fluoroscopy and decreased frame rate during PCNL decreased radiation exposure fourfold without affecting SFS or complication rates.

Spatiotemporal image quality of virtual reality head mounted displays

Virtual reality (VR) head mounted displays (HMDs) require both high spatial resolution and fast temporal response. However, methods to quantify the VR image quality in the spatiotemporal domain when motion exists are not yet standardized. In this study, we characterize the spatiotemporal capabilities of three VR devices: the HTC VIVE, VIVE Pro, and VIVE Pro 2 during smooth pursuit. A spatiotemporal model for VR HMDs is presented using measured spatial and temporal characteristics. Among the three evaluated headsets, the VIVE Pro 2 improves the display temporal performance using a fast 120 Hz refresh rate and pulsed emission with a small duty cycle of 5%. In combination with a high pixel resolution beyond 2 k times 2 k per eye, the VIVE Pro 2 achieves an improved spatiotemporal performance compared to the VIVE and VIVE Pro in the high spatial frequency range above 8 cycles per degree during smooth pursuit. The result demonstrates that reducing the display emission duty cycle to less than 20% is beneficial to mitigate motion blur in VR HMDs. Frame rate reduction (e.g., to below 60 Hz) of the input signal compared to the display refresh rate of 120 Hz yields replicated shadow images that can affect the image quality under motion. This work supports the regulatory science research efforts in development of testing methods to characterize the spatiotemporal performance of VR devices for medical use.

CNN-Based Image Reconstruction Method for Ultrafast Ultrasound Imaging.

Ultrafast ultrasound (US) revolutionized biomedical imaging with its capability of acquiring full-view frames at over 1 kHz, unlocking breakthrough modalities such as shear-wave elastography and functional US neuroimaging. Yet, it suffers from strong diffraction artifacts, mainly caused by grating lobes, sidelobes, or edge waves. Multiple acquisitions are typically required to obtain a sufficient image quality, at the cost of a reduced frame rate. To answer the increasing demand for high-quality imaging from single unfocused acquisitions, we propose a two-step convolutional neural network (CNN)-based image reconstruction method, compatible with real-time imaging. A low-quality estimate is obtained by means of a backprojection-based operation, akin to conventional delay-and-sum beamforming, from which a high-quality image is restored using a residual CNN with multiscale and multichannel filtering properties, trained specifically to remove the diffraction artifacts inherent to ultrafast US imaging. To account for both the high dynamic range and the oscillating properties of radio frequency US images, we introduce the mean signed logarithmic absolute error (MSLAE) as a training loss function. Experiments were conducted with a linear transducer array, in single plane-wave (PW) imaging. Trainings were performed on a simulated dataset, crafted to contain a wide diversity of structures and echogenicities. Extensive numerical evaluations demonstrate that the proposed approach can reconstruct images from single PWs with a quality similar to that of gold-standard synthetic aperture imaging, on a dynamic range in excess of 60 dB. In vitro and in vivo experiments show that trainings carried out on simulated data perform well in experimental settings.

RADIATION EXPOSURE IN ACCESSORY PATHWAY ABLATION PROCEDURES IN CARDIAC ELECTROPHYSIOLOGY: A RETROSPECTIVE ANALYSIS

Background. Radiofrequency catheter ablation (CA) has been the treatment of choice in patients with accessory pathway (AP)-mediated tachycardias. Most of these procedures are done under fluoroscopic guidance, leading to significant radiation exposure to the patient and the laboratory personnel. In this analysis, we have looked at the amount of radiation exposure in AP CA procedures performed without the support of a three-dimensional electroanatomic mapping system. We have analyzed changes in exposure indices over the study period and the impact of change in fluoroscopy frame rate (FFR). Objectives. The objectives of this study are to quantify radiation exposure in accessory pathway ablation procedures; to analyze the radiation exposure trend over time; and to evaluate the effect of fluoroscopy frame rate reduction on the radiation exposure indices in these procedures. Methods. All the AP ablation procedures performed at our institute from January 2016 to December 2019 were retrospectively analyzed. The collected data were age, sex, location of APs based on successful site of ablation on fluoroscopy, procedure time, fluoroscopy time, and dose-area product (DAP). Effective dose (ED) was estimated from DAP. The data of procedures performed before January 2018 (“pre” group) were compared with those of the procedures performed after that date (“post” group). Pre-group procedures were performed at an FFR of 7.5 frames per second (fps), and post-group procedures – at an FFR of 3.75 fps. Results. The total number of procedures included in the analysis was 635. The mean age of the patients was 39±14 years, and 401 of them (63%) were males. The most common location of the APs was left lateral (38%). Procedure time and radiation indices showed a significant decrease over the study period (p &lt; 0.001). Post group procedures had significantly shorter procedure time and lower radiation exposure than pre group procedures. Conclusions. A decrease in the FFR was associated with a significant reduction in radiation exposure in AP ablation procedures

Effect of fluoroscopy frame rate on radiation exposure and in-hospital outcomes in cardiovascular implantable electronic device implantation procedures

ObjectiveTo assess the radiation exposure in cardiovascular implantable electronic device(CIED) implantation procedures, the effect of fluoroscopy frame rate on various radiation exposure indices, and in-hospital outcomes. MethodsData of CIED implantation procedures from September 2015 to December 2019 of all the CIED implantation procedures performed at our institute were retrospectively analyzed. The procedural data were divided into two groups: a) pre-group: procedures that were performed under fluoroscopy frame rate of 7.5 frames per second(fps); b) post-group: procedures that were performed under fluoroscopy frame rate of 3.75 fps. We compared procedure time, fluoroscopy time, Kerma air product, effective dose, and in-hospital outcomes between the two groups. ResultsA total of 2,225 procedures were included in the analysis with mean age of (62 ​± ​15) years. The procedures consisted of the implantation of single-chamber (n ​= ​1,436), double chamber (n ​= ​656), and biventricular devices (n ​= ​133). Procedure time and radiation indices showed a significant reduction over the study period (P ​< ​0.001). Reduction in the fluoroscopy frame rate was associated with a significant reduction in radiation exposure indices(P ​< ​0.001). In-hospital outcomes did not differ between the two groups. ConclusionsReduction in the fluoroscopy frame rate from 7.5 to 3.75 fps significantly decreased the radiation exposure in CIED implantation procedures. A framerate lower than 3.75 fps should be the default setting during such procedures.

Scrolling-Aware Rendering to Reduce Frame Rates on Smartphones

One of the major sources of power drain in smartphones is a frame rendering and display process called graphics pipeline, in which power consumption depends largely on frame rendering operations per second (fps), known as the frame rate, and the quantity of UI content to be rendered. We discovered a major problem causing power consumption upon a scrolling operation: The Android graphics pipeline renders all or a large portion of the content displayed most recently at a frame rate of nearly 60 fps. This paper proposes a scrolling-aware rendering (SCAR) scheme to reduce the frame rate caused by a scrolling. When rendering a frame for UI content to be displayed, SCAR pre-renders UI content that is likely to be displayed soon in any subsequent scrolling operation. This frame is extended to place the pre-rendered UI content contiguously with the UI content to be displayed. Upon a subsequent scrolling, SCAR repositions the extended frame on screen by a scrolling distance instead of rendering a new frame. Our experiments on a smartphone show that SCAR reduced frame rates to below one fps in scrolling, thus saving power by up to 30%.

CNN-Based Ultrasound Image Reconstruction for Ultrafast Displacement Tracking.

Thanks to its capability of acquiring full-view frames at multiple kilohertz, ultrafast ultrasound imaging unlocked the analysis of rapidly changing physical phenomena in the human body, with pioneering applications such as ultrasensitive flow imaging in the cardiovascular system or shear-wave elastography. The accuracy achievable with these motion estimation techniques is strongly contingent upon two contradictory requirements: a high quality of consecutive frames and a high frame rate. Indeed, the image quality can usually be improved by increasing the number of steered ultrafast acquisitions, but at the expense of a reduced frame rate and possible motion artifacts. To achieve accurate motion estimation at uncompromised frame rates and immune to motion artifacts, the proposed approach relies on single ultrafast acquisitions to reconstruct high-quality frames and on only two consecutive frames to obtain 2-D displacement estimates. To this end, we deployed a convolutional neural network-based image reconstruction method combined with a speckle tracking algorithm based on cross-correlation. Numerical and in vivo experiments, conducted in the context of plane-wave imaging, demonstrate that the proposed approach is capable of estimating displacements in regions where the presence of side lobe and grating lobe artifacts prevents any displacement estimation with a state-of-the-art technique that relies on conventional delay-and-sum beamforming. The proposed approach may therefore unlock the full potential of ultrafast ultrasound, in applications such as ultrasensitive cardiovascular motion and flow analysis or shear-wave elastography.