Deep learning-based automatic pipeline for 3D needle localization on intra-procedural 3D MRI.

PURPOSE: Accurate and rapid needle localization on 3D magnetic resonance imaging (MRI) is critical for MRI-guided percutaneous interventions. The current workflow requires manual needle localization on 3D MRI, which is time-consuming and cumbersome. Automatic methods using 2D deep learning networks for needle segmentation require manual image plane localization, while 3D networks are challenged by the need for sufficient training datasets. This work aimed to develop an automatic deep learning-based pipeline for accurate and rapid 3D needle localization on in vivo intra-procedural 3D MRI using a limited training dataset. METHODS: The proposed automatic pipeline adopted Shifted Window (Swin) Transformers and employed a coarse-to-fine segmentation strategy: (1) initial 3D needle feature segmentation with 3D Swin UNEt TRansfomer (UNETR); (2) generation of a 2D reformatted image containing the needle feature; (3) fine 2D needle feature segmentation with 2D Swin Transformer and calculation of 3D needle tip position and axis orientation. Pre-training and data augmentation were performed to improve network training. The pipeline was evaluated via cross-validation with 49 in vivo intra-procedural 3D MR images from preclinical pig experiments. The needle tip and axis localization errors were compared with human intra-reader variation using the Wilcoxon signed rank test, with p < 0.05 considered significant. RESULTS: The average end-to-end computational time for the pipeline was 6 s per 3D volume. The median Dice scores of the 3D Swin UNETR and 2D Swin Transformer in the pipeline were 0.80 and 0.93, respectively. The median 3D needle tip and axis localization errors were 1.48 mm (1.09 pixels) and 0.98°, respectively. Needle tip localization errors were significantly smaller than human intra-reader variation (median 1.70 mm; p < 0.01). CONCLUSION: The proposed automatic pipeline achieved rapid pixel-level 3D needle localization on intra-procedural 3D MRI without requiring a large 3D training dataset and has the potential to assist MRI-guided percutaneous interventions.

Automated abdominal adipose tissue segmentation and volume quantification on longitudinal MRI using 3D convolutional neural networks with multi-contrast inputs.

OBJECTIVE: Increased subcutaneous and visceral adipose tissue (SAT/VAT) volume is associated with risk for cardiometabolic diseases. This work aimed to develop and evaluate automated abdominal SAT/VAT segmentation on longitudinal MRI in adults with overweight/obesity using attention-based competitive dense (ACD) 3D U-Net and 3D nnU-Net with full field-of-view volumetric multi-contrast inputs. MATERIALS AND METHODS: 920 adults with overweight/obesity were scanned twice at multiple 3 T MRI scanners and institutions. The first scan was divided into training/validation/testing sets (n = 646/92/182). The second scan from the subjects in the testing set was used to evaluate the generalizability for longitudinal analysis. Segmentation performance was assessed by measuring Dice scores (DICE-SAT, DICE-VAT), false negatives (FN), and false positives (FP). Volume agreement was assessed using the intraclass correlation coefficient (ICC). RESULTS: ACD 3D U-Net achieved rapid (< 4.8 s/subject) segmentation with high DICE-SAT (median ≥ 0.994) and DICE-VAT (median ≥ 0.976), small FN (median ≤ 0.7%), and FP (median ≤ 1.1%). 3D nnU-Net yielded rapid (< 2.5 s/subject) segmentation with similar DICE-SAT (median ≥ 0.992), DICE-VAT (median ≥ 0.979), FN (median ≤ 1.1%) and FP (median ≤ 1.2%). Both models yielded excellent agreement in SAT/VAT volume versus reference measurements (ICC > 0.997) in longitudinal analysis. DISCUSSION: ACD 3D U-Net and 3D nnU-Net can be automated tools to quantify abdominal SAT/VAT volume rapidly, accurately, and longitudinally in adults with overweight/obesity.

Concurrent Asian monsoon strengthening and early modern human dispersal to East Asia during the last interglacial.

The relationship between initial Homo sapiens dispersal from Africa to East Asia and the orbitally paced evolution of the Asian summer monsoon (ASM)-currently the largest monsoon system-remains underexplored due to lack of coordinated synthesis of both Asian paleoanthropological and paleoclimatic data. Here, we investigate orbital-scale ASM dynamics during the last 280 thousand years (kyr) and their likely influences on early H. sapiens dispersal to East Asia, through a unique integration of i) new centennial-resolution ASM records from the Chinese Loess Plateau, ii) model-based East Asian hydroclimatic reconstructions, iii) paleoanthropological data compilations, and iv) global H. sapiens habitat suitability simulations. Our combined proxy- and model-based reconstructions suggest that ASM precipitation responded to a combination of Northern Hemisphere ice volume, greenhouse gas, and regional summer insolation forcing, with cooccurring primary orbital cycles of ~100-kyr, 41-kyr, and ~20-kyr. Between ~125 and 70 kyr ago, summer monsoon rains and temperatures increased in vast areas across Asia. This episode coincides with the earliest H. sapiens fossil occurrence at multiple localities in East Asia. Following the transcontinental increase in simulated habitat suitability, we suggest that ASM strengthening together with Southeast African climate deterioration may have promoted the initial H. sapiens dispersal from their African homeland to remote East Asia during the last interglacial.

Weakening of the South Asian summer monsoon linked to interhemispheric ice-sheet growth since 12 Ma.

The evolution and driving mechanism of the South Asian summer monsoon (SASM) are still poorly understood. We here present a 12-Myr long SASM record by analyzing the strontium and neodymium isotopic composition of detrital components at IODP Exp. 359 Site U1467 from the northern Indian Ocean. The provenance investigation demonstrates that more dust enriched in εNd from northeastern Africa and the Arabian Peninsula was transported to the study site by monsoonal and Shamal winds during the summer monsoon season. A two-step weakening of the SASM wind since ~12 Ma is proposed based on the εNd record. This observational phenomenon is supported by climate modeling results, demonstrating that the SASM evolution was mainly controlled by variations in the gradient between the Mascarene High and the Indian Low, associated with meridional shifts of the Hadley Cell and the Intertropical Convergence Zone, which were caused by interhemispheric ice-sheet growth since the Middle Miocene.

The Synergistic Effect of Polyphosphates Acid and Different Compounds of Waste Cooking Oil on Conventional and Rheological Properties of Modified Bitumen.

In order to conserve non-renewable natural resources, waste cooking oil (WCO) in bitumen can help lower CO2 emissions and advance the environmental economy. In this study, three different components of WCO were isolated and then, together with polyphosphoric acid (PPA), used separately as bitumen modifiers to determine the suitability of various substances in WCO with PPA. Conventional tests, including penetration, softening point temperature, and ductility, and the dynamic shear rheology (DSR) test, including temperature sweep and frequency sweep, were used to evaluate the influence of WCO/PPA on the traditional performance and rheological properties at high and low temperatures. The results indicate that WCO reduced the ductility and penetration value, when the use of PPA increased the softening point temperature and high-temperature performance. Compared to reference bitumen, the rutting factor and viscous activation energy (Ea) of bitumen modified with 4% WCO and 2% PPA has the most significant increase by 18.6% and 31.5, respectively. All components of WCO have a significant impact on improving the low-temperature performance of PPA-modified bitumen. The performance of the composite-modified bitumen at low temperatures is negatively affected by some waxy compounds in WCO, such as methyl palmitate, which tends to undergo a solid-liquid phase change as the temperature decreases. In conclusion, the inclusion of WCO/PPA in bitumen offers a fresh approach to developing sustainable pavement materials.

Laboratory Study and Field Validation of the Performance of Salt-Storage Asphalt Mixtures.

The traditional method of removing ice and snow on roads carries the risk of damaging roads and the environment. In this circumstance, the technology of salt-storage asphalt pavement has gradually attracted attention. However, snow-melting salts may also have an impact on asphalt mixture performance. To explore the effect of snow-melting salts on the mechanical and surface properties of salt-storage asphalt mixtures (SSAM), SSAMs were prepared with styrene-butadiene-styrene (SBS)-modified asphalt and high-elastic asphalt (HEA) as binders and snow-melting salts as fillers. The influence of the type of asphalt binder and the content of snow-melting salt on the performance of the SSAM was preliminarily investigated through laboratory tests. The results show that the high-temperature, low-temperature, and moisture resistance performance of the SBS group SSAM decreased by 9.8-15.1%, 1.6-12.3%, and 6.3-19.4%, respectively, compared with SBS00. The higher the amount of snow-melting salt, the greater the performance drop. The three mechanical properties of the HEA group containing high-elastic agent TPS are 11.3-19.7%, 4.2-12.3%, and 4.8-13.3% higher than that of the SBS group. Even when the content of snow-melting salt is 50% or 75%, the mechanical properties of the HEA group are better than that of SBS00 without snow-melting salt. Snow-melting salt has clear advantages in improving the anti-skid performance but decreases the anti-spalling performance. The surface properties of the HEA group were also better than that of the SBS group. Considering the mechanical properties and surface properties, the comprehensive performance of the HEA group is better than that of the SBS group, and HEA50 has the best comprehensive performance. In addition, the construction performance of the SSAM has also been verified, and the production of SSAM according to the hot mix asphalt can meet the specification requirements.

Rheological Properties of Styrene-Butadiene-Styrene Asphalt Mastic Containing High Elastic Polymer and Snow Melting Salt.

Sprinkled snow melting salt (SMS) exerts a snow melting effect and also has a negative impact on the asphalt pavement and the environment. Salt storage pavement technology can alleviate these two problems. However, non-alkaline SMSs may have the risk of affecting asphalt mastic properties and further affecting the mechanical properties of asphalt pavements. Therefore, the general properties and rheological properties of two styrene-butadiene-styrene-modified asphalts with and without high elastic polymer were studied after adding SMS. The asphalt mastic without a high elastic agent is defined as the SBS group, and the other group is the HEA group. Our results show that the HEA group shows a lower penetration and a higher softening point, ductility, and viscosity than the SBS group. The more the SMS, the more the reduction effect of the general performance. The elastic recovery of asphalt mastic decreases with the content of SMS. SMS has no obvious effect on the ratio of the viscous and elastic composition of asphalt mastic. The creep of asphalt mastic increases with the content of SMS. The high elastic polymer can significantly reduce the creep, and even the strain of HEA100 is smaller than that of SBS00. SMS increases the creep stiffness and reduces the creep rate at low temperature. Although SMS increases the potential of asphalt pavement to melt ice and snow, it also reduces the high-temperature rutting resistance and low-temperature crack resistance of asphalt mastic. Salt storage pavement materials can be used in combination with high elastic polymers to reduce the negative effects brought by SMSs.

Anthropogenic sulfate aerosol pollution in South and East Asia induces increased summer precipitation over arid Central Asia.

Precipitation has increased across the arid Central Asia region over recent decades. However, the underlying mechanisms of this trend are poorly understood. Here, we analyze multi-model simulations from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP) to investigate potential drivers of the observed precipitation trend. We find that anthropogenic sulfate aerosols over remote polluted regions in South and East Asia lead to increased summer precipitation, especially convective and extreme precipitation, in arid Central Asia. Elevated concentrations of sulfate aerosols over remote polluted Asia cause an equatorward shift of the Asian Westerly Jet Stream through a fast response to cooling of the local atmosphere at mid-latitudes. This shift favours moisture supply from low-latitudes and moisture flux convergence over arid Central Asia, which is confirmed by a moisture budget analysis. High levels of absorbing black carbon lead to opposing changes in the Asian Westerly Jet Stream and reduced local precipitation, which can mask the impact of sulfate aerosols. This teleconnection between arid Central Asia precipitation and anthropogenic aerosols in remote Asian polluted regions highlights long-range impacts of anthropogenic aerosols on atmospheric circulations and the hydrological cycle.

Accelerated k-space shift calibration for free-breathing stack-of-radial MRI quantification of liver fat and R2∗.

PURPOSE: To develop an accelerated k-space shift calibration method for free-breathing 3D stack-of-radial MRI quantification of liver proton-density fat fraction (PDFF) and R2∗ . METHODS: Accelerated k-space shift calibration was developed to partially skip acquisition of k-space shift data in the through-plane direction then interpolate in processing, as well as to reduce the in-plane averages. A multi-echo stack-of-radial sequence with the baseline calibration was evaluated on a phantom versus vendor-provided reference-standard PDFF and R2∗ values at 1.5T, and in 13 healthy subjects and 5 clinical subjects at 3T with respect to reference-standard breath-hold Cartesian acquisitions. PDFF and R2∗ maps were calculated with different calibration acceleration factors offline and compared to reference-standard values using Bland-Altman analysis. Bias and uncertainty were evaluated using normal distribution and Bayesian probability of difference (P < .05 considered significant). RESULTS: Bland-Altman plots of phantom and in vivo data showed that substantial acceleration was highly feasible in both through-plane and in-plane directions. Compared to the baseline calibration without acceleration, Bayesian analysis revealed no significant differences on biases and uncertainties of PDFF and R2∗ measurements with all acceleration methods in this study, except the method with through-plane acceleration equaling slices and averages equaling 20 for PDFF and R2∗ (both P < .001) for the phantom. A six-fold reduction in equivalent calibration acquisition time (time saving ≥25 s and ≥80.7%) was achieved using recommended acceleration factors for the in vivo protocols in this study. CONCLUSION: This proposed method may allow accelerated calibration for free-breathing stack-of-radial MRI PDFF and R2∗ mapping.

Increased tropical vegetation respiration is dually induced by El Niño and upper atmospheric warm anomalies.

Tropical vegetation respiration (TVR) is affected by extreme climate change. As it is very difficult to directly observe TVR, our understanding of the land-ocean-atmosphere carbon cycle, and particularly the regulatory effect of El Niño-Southern Oscillation (ENSO) on TVR and the land-atmosphere carbon balance, is very limited. Therefore, usingModerate Resolution Imaging Spectroradiometer (MODIS) products and meteorological data, we investigated the response of TVR to changes in ENSO during 2000-2015. The influence of El Niño on TVR was approximately 10.8% higher than that of La Niña. During El Niño years, a significant and anomalous increase in thermal measures related to TVR and ENSO and a significant and anomalous decrease in related hydrological measures favor the formation of warmer and drier climate conditions. Furthermore, the zonal distributions of air temperature and vertical velocity at 200-1000 hPa during El Niño years show that a stronger atmospheric inversion over tropical regions causes an increase in the surface temperature. Moreover, anomalous atmospheric subsidence inhibits the upward transport of water vapor, leading to a decrease in the cloud formation probability and reduced precipitation. In summary, increased surface temperatures caused by increased solar radiation and enhanced atmospheric inversion and decreased precipitation cause warmer and drier climate conditions, which forces TVR to increase. As TVR constitutes the key node of the land-atmosphere­carbon cycle process, we focus on TVR and its close linkage with ENSO events and further establish a knowledge framework for understanding the land-atmosphere-ocean carbon cycle. This study deepens our understanding of not only the mechanism of the land-atmosphere carbon balance but also the ocean-induced terrestrial ecosystem processes spurred by ENSO-involved climate change. PLAIN LANGUAGE SUMMARY: Vegetation respiration regulates the carbon balance of the land and atmosphere. As it is very difficult to directly observe vegetation respiration, our understanding of the land-ocean-atmosphere carbon cycle involved and the roles of vegetation respiration and El Niño-Southern Oscillation (ENSO) in regulating the land-atmosphere carbon balance is very limited. Therefore, using MODIS products and meteorological data, we investigated the response of tropical vegetation respiration to changes in ENSO during 2000-2015. We found that during El Niño years, warmer and drier climate conditions over tropical regions increased vegetation respiration. Exacerbating the warmer and drier climate conditions, upper atmospheric warm anomalies further caused a remarkable increase in tropical vegetation respiration. Based on the land-atmosphere­carbon cycle process, we establish a knowledge framework for understanding the land-atmosphere-ocean carbon cycle. This knowledge deepens our understanding of not only the mechanism of the land-atmosphere carbon balance but also the ocean-induced terrestrial ecosystem processes spurred by ENSO-involved climate change.

Eccentricity-paced monsoon variability on the northeastern Tibetan Plateau in the Late Oligocene high CO2 world.

Constraining monsoon variability and dynamics in the warm unipolar icehouse world of the Late Oligocene can provide important clues to future climate responses to global warming. Here, we present a ~4-thousand year (ka) resolution rubidium-to-strontium ratio and magnetic susceptibility records between 28.1 and 24.1 million years ago from a distal alluvial sedimentary sequence in the Lanzhou Basin (China) on the northeastern Tibetan Plateau margin. These Asian monsoon precipitation records exhibit prominent short (~110-ka) and long (405-ka) eccentricity cycles throughout the Late Oligocene, with a weak expression of obliquity (41-ka) and precession (19-ka and 23-ka) cycles. We conclude that a combination of eccentricity-modulated low-latitude summer insolation and glacial-interglacial Antarctic Ice Sheet fluctuations drove the eccentricity-paced precipitation variability on the northeastern Tibetan Plateau in the Late Oligocene high CO2 world by governing regional temperatures, water vapor loading in the western Pacific and Indian Oceans, and the Asian monsoon intensity and displacement.

3D Neural Networks for Visceral and Subcutaneous Adipose Tissue Segmentation using Volumetric Multi-Contrast MRI.

Individuals with obesity have larger amounts of visceral (VAT) and subcutaneous adipose tissue (SAT) in their body, increasing the risk for cardiometabolic diseases. The reference standard to quantify SAT and VAT uses manual annotations of magnetic resonance images (MRI), which requires expert knowledge and is time-consuming. Although there have been studies investigating deep learning-based methods for automated SAT and VAT segmentation, the performance for VAT remains suboptimal (Dice scores of 0.43 to 0.89). Previous work had key limitations of not fully considering the multi-contrast information from MRI and the 3D anatomical context, which are critical for addressing the complex spatially varying structure of VAT. An additional challenge is the imbalance between the number and distribution of pixels representing SAT/VAT. This work proposes a network based on 3D U-Net that utilizes the full field-of-view volumetric T1-weighted, water, and fat images from dual-echo Dixon MRI as the multi-channel input to automatically segment SAT and VAT in adults with overweight/obesity. In addition, this work extends the 3D U-Net to a new Attention-based Competitive Dense 3D U-Net (ACD 3D U-Net) trained with a class frequency-balancing Dice loss (FBDL). In an initial testing dataset, the proposed 3D U-Net and ACD 3D U-Net with FBDL achieved 3D Dice scores of (mean ± standard deviation) 0.99 ±0.01 and 0.99±0.01 for SAT, and 0.95±0.04 and 0.96 ±0.04 for VAT, respectively, compared to manual annotations. The proposed 3D networks had rapid inference time (<60 ms/slice) and can enable automated segmentation of SAT and VAT.Clinical relevance- This work developed 3D neural networks to automatically, accurately, and rapidly segment visceral and subcutaneous adipose tissue on MRI, which can help to characterize the risk for cardiometabolic diseases such as diabetes, elevated glucose levels, and hypertension.

Global warming-induced Asian hydrological climate transition across the Miocene-Pliocene boundary.

Across the Miocene-Pliocene boundary (MPB; 5.3 million years ago, Ma), late Miocene cooling gave way to the early-to-middle Pliocene Warm Period. This transition, across which atmospheric CO2 concentrations increased to levels similar to present, holds potential for deciphering regional climate responses in Asia-currently home to more than half of the world's population- to global climate change. Here we find that CO2-induced MPB warming both increased summer monsoon moisture transport over East Asia, and enhanced aridification over large parts of Central Asia by increasing evaporation, based on integration of our ~1-2-thousand-year (kyr) resolution summer monsoon records from the Chinese Loess Plateau aeolian red clay with existing terrestrial records, land-sea correlations, and climate model simulations. Our results offer palaeoclimate-based support for 'wet-gets-wetter and dry-gets-drier' projections of future regional hydroclimate responses to sustained anthropogenic forcing. Moreover, our high-resolution monsoon records reveal a dynamic response to eccentricity modulation of solar insolation, with predominant 405-kyr and ~100-kyr periodicities between 8.1 and 3.4 Ma.

Responsive Nanoparticles to Enable a Focused Ultrasound-Stimulated Magnetic Resonance Imaging Spotlight.

Magnetic resonance imaging (MRI)-guided high-intensity focused ultrasound (HIFU) has been applied as a therapeutic tool in the clinic, and enhanced MRI contrast for depiction of target tissues will improve the precision and applicability of HIFU therapy. This work presents a "spotlight MRI" contrast enhancement technique, which combines four essential components: periodic HIFU stimulation, strong modulation of T1 caused by HIFU, rapid MRI signal collection, and spotlight MRI spectral signal processing. The T1 modulation is enabled by a HIFU-responsive nanomaterial based on mesoporous silica nanoparticles with Pluronic polymers (Poloxamers) and MRI contrast agents attached. With periodic HIFU stimulation in a precisely defined region containing the nanomaterial, strong periodic MRI T1-weighted signal changes are generated. Rapid MRI signal collection of the periodic signal changes is realized by a rapid dynamic 3D MRI technique, and spotlight MRI spectral signal processing creates modulation enhancement maps (MEM) that suppress background signal and spotlight the spatial location with nanomaterials experiencing HIFU stimulation. In particular, a framework is presented to analyze the trade-offs between different parameter choices for the signal processing method. The optimal parameter choices under a specific experimental setting achieved MRI contrast enhancement of more than 2 orders of magnitude at the HIFU focal point, compared to controls.

Free-Breathing Volumetric Liver R2* and Proton Density Fat Fraction Quantification in Pediatric Patients Using Stack-of-Radial MRI With Self-Gating Motion Compensation.

BACKGROUND: Stack-of-radial multiecho gradient-echo MRI is promising for free-breathing liver R2* quantification and may benefit children. PURPOSE: To validate stack-of-radial MRI with self-gating motion compensation in phantoms, and to evaluate it in children. STUDY TYPE: Prospective. PHANTOMS: Four vials with different R2* driven by a motion stage. SUBJECTS: Sixteen pediatric patients with suspected nonalcoholic fatty liver disease or steatohepatitis (five females, 13 ± 4 years, body mass index 29.2 ± 8.6 kg/m2 ). FIELD STRENGTH/SEQUENCES: Stack-of-radial, and 2D and 3D Cartesian multiecho gradient-echo sequences at 3T. ASSESSMENT: Ungated and gated stack-of-radial proton density fat fraction (PDFF) and R2* maps were reconstructed without and with self-gating motion compensation. Stack-of-radial R2* measurements of phantoms without and with motion were validated against reference 2D Cartesian results of phantoms without motion. In subjects, free-breathing stack-of-radial and reference breath-hold 3D Cartesian were acquired. Subject inclusion for statistical analysis and region of interest placement were determined independently by two observers. STATISTICAL TESTS: Phantom results were fitted with a weighted linear model. Demographic differences between excluded and included subjects were tested by multivariate analysis of variance. PDFF and R2* measurements were compared using Bland-Altman analysis. Interobserver agreement was assessed by the intraclass correlation coefficient (ICC). RESULTS: Ungated stack-of-radial R2* inside moving phantom vials showed a significant positive bias of 64.3 s-1 (P < 0.00001), unlike gated results (P > 0.31). Subject inclusion decisions for statistical analysis from two observers were consistent. No significant differences were found between four excluded and 12 included subjects (P = 0.14). Compared to breath-hold Cartesian, ungated and gated free-breathing stack-of-radial exhibited mean R2* differences of 18.5 s-1 and 3.6 s-1 . Mean PDFF differences were 1.1% and 1.0% for ungated and gated measurements, respectively. Interobserver agreement was excellent (ICC for PDFF = 0.99, ICC for R2* = 0.90; P < 0.0003). DATA CONCLUSION: Stack-of-radial MRI with self-gating motion compensation seems to allow free-breathing liver R2* and PDFF quantification in children. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2.

Characterization of Uterine Motion in Early Gestation Using MRI-Based Motion Tracking.

Magnetic resonance imaging (MRI) is a promising non-invasive imaging technique that can be safely used to study placental development and function. However, studies of the human placenta performed by MRI are limited by uterine motion and motion in the uterus during MRI remains one of the major limiting factors. Here, we aimed to investigate the characterization of uterine activity during MRI in the second trimester of pregnancy using MRI-based motion tracking. In total, 46 pregnant women were scanned twice (first scan between 14 and 18 weeks and second scan between 19 and 24 weeks), and 20 pregnant subjects underwent a single MRI between 14 and 18 weeks GA, resulting in 112 MRI scans. An MRI-based algorithm was used to track uterine motion in the superior-inferior and left-right directions. Uterine contraction and maternal motion cases were separated by the experts, and unpaired Wilcoxon tests were performed within the groups of gestational age (GA), fetal sex, and placental location in terms of the overall intensity measures of the uterine activity. In total, 22.3% of cases had uterine contraction during MRI, which increased from 18.6% at 14-18 weeks to 26.4% at 19-24 weeks GA. The dominant direction of the uterine contraction and maternal motion was the superior to the inferior direction during early gestation.

Automatic needle tracking using Mask R-CNN for MRI-guided percutaneous interventions.

PURPOSE: Accurate needle tracking provides essential information for MRI-guided percutaneous interventions. Passive needle tracking using MR images is challenged by variations of the needle-induced signal void feature in different situations. This work aimed to develop an automatic needle tracking algorithm for MRI-guided interventions based on the Mask Region Proposal-Based Convolutional Neural Network (R-CNN). METHODS: Mask R-CNN was adapted and trained to segment the needle feature using 250 intra-procedural images from 85 MRI-guided prostate biopsy cases and 180 real-time images from MRI-guided needle insertion in ex vivo tissue. The segmentation masks were passed into the needle feature localization algorithm to extract the needle feature tip location and axis orientation. The proposed algorithm was tested using 208 intra-procedural images from 40 MRI-guided prostate biopsy cases, and 3 real-time MRI datasets in ex vivo tissue. The algorithm results were compared with human-annotated references. RESULTS: In prostate datasets, the proposed algorithm achieved needle feature tip localization error with median Euclidean distance (dxy) of 0.71 mm and median difference in axis orientation angle (dθ) of 1.28°, respectively. In 3 real-time MRI datasets, the proposed algorithm achieved consistent dynamic needle feature tracking performance with processing time of 75 ms/image: (a) median dxy = 0.90 mm, median dθ = 1.53°; (b) median dxy = 1.31 mm, median dθ = 1.9°; (c) median dxy = 1.09 mm, median dθ = 0.91°. CONCLUSIONS: The proposed algorithm using Mask R-CNN can accurately track the needle feature tip and axis on MR images from in vivo intra-procedural prostate biopsy cases and ex vivo real-time MRI experiments with a range of different conditions. The algorithm achieved pixel-level tracking accuracy in real time and has potential to assist MRI-guided percutaneous interventions.

Real-time 3T MRI-guided cardiovascular catheterization in a porcine model using a glass-fiber epoxy-based guidewire.

PURPOSE: Real-time magnetic resonance imaging (MRI) is a promising alternative to X-ray fluoroscopy for guiding cardiovascular catheterization procedures. Major challenges, however, include the lack of guidewires that are compatible with the MRI environment, not susceptible to radiofrequency-induced heating, and reliably visualized. Preclinical evaluation of new guidewire designs has been conducted at 1.5T. Here we further evaluate the safety (device heating), device visualization, and procedural feasibility of 3T MRI-guided cardiovascular catheterization using a novel MRI-visible glass-fiber epoxy-based guidewire in phantoms and porcine models. METHODS: To evaluate device safety, guidewire tip heating (GTH) was measured in phantom experiments with different combinations of catheters and guidewires. In vivo cardiovascular catheterization procedures were performed in both healthy (N = 5) and infarcted (N = 5) porcine models under real-time 3T MRI guidance using a glass-fiber epoxy-based guidewire. The times for each procedural step were recorded separately. Guidewire visualization was assessed by measuring the dimensions of the guidewire-induced signal void and contrast-to-noise ratio (CNR) between the guidewire tip signal void and the blood signal in real-time gradient-echo MRI (specific absorption rate [SAR] = 0.04 W/kg). RESULTS: In the phantom experiments, GTH did not exceed 0.35°C when using the real-time gradient-echo sequence (SAR = 0.04 W/kg), demonstrating the safety of the glass-fiber epoxy-based guidewire at 3T. The catheter was successfully placed in the left ventricle (LV) under real-time MRI for all five healthy subjects and three out of five infarcted subjects. Signal void dimensions and CNR values showed consistent visualization of the glass-fiber epoxy-based guidewire in real-time MRI. The average time (minutes:seconds) for the catheterization procedure in all subjects was 4:32, although the procedure time varied depending on the subject's specific anatomy (standard deviation = 4:41). CONCLUSIONS: Real-time 3T MRI-guided cardiovascular catheterization using a new MRI-visible glass-fiber epoxy-based guidewire is feasible in terms of visualization and guidewire navigation, and safe in terms of radiofrequency-induced guidewire tip heating.

Respiratory Motion Prediction Using Fusion-Based Multi-Rate Kalman Filtering and Real-Time Golden-Angle Radial MRI.

OBJECTIVE: Magnetic resonance imaging (MRI) can provide guidance for interventions in organs affected by respiration (e.g., liver). This study aims to: 1) investigate image-based and surrogate-based motion tracking methods using real-time golden-angle radial MRI; and 2) propose and evaluate a new fusion-based respiratory motion prediction framework with multi-rate Kalman filtering. METHODS: Images with different temporal footprints were reconstructed from the same golden-angle radial MRI data stream to simultaneously enable image-based and surrogate-based tracking at 10 Hz. A custom software pipeline was constructed to perform online tracking and calibrate tracking error and latency using a programmable motion phantom. A fusion-based motion prediction method was developed to combine the lower tracking error of image-based tracking with the lower latency of surrogate-based tracking. The fusion-based method was evaluated in retrospective studies using in vivo real-time free-breathing liver MRI. RESULTS: Phantom experiments confirmed that the median online tracking error of image-based tracking was lower than surrogate-based methods, however, with higher median system latency (350 ms vs. 150 ms). In retrospective in vivo studies, 75 respiratory waveforms of target features from eight subjects were analyzed. The median root-mean-squared prediction error (RMSE) for the fusion-based method (0.97 mm) was reduced (Wilcoxon signed rank test p < 0.05) compared to surrogate-based (1.18 mm) and image-based (1.3 mm) methods. CONCLUSION: The proposed fusion-based respiratory motion prediction framework using golden-angle radial MRI can achieve low-latency feedback with improved accuracy. SIGNIFICANCE: Respiratory motion prediction using the fusion-based method can overcome system latency to provide accurate feedback information for MRI-guided interventions.

MRI-guided targeted needle placement during motion using hydrostatic actuators.

BACKGROUND: Magnetic resonance imaging (MRI) has unique advantages for guiding interventions, but the narrow space is a major challenge. This study evaluates the feasibility of a remote-controlled hydrostatic actuator system for MRI-guided targeted needle placement. METHODS: The effects of the hydrostatic actuator system on MR image quality were evaluated. Using a reference step-and-shoot method (SS) and the proposed actuator-assisted method (AA), two operators performed MRI-guided needle placement in targets (n = 12) in a motion phantom. RESULTS: The hydrostatic actuator system exhibited negligible impact on MR image quality. In dynamic targets, AA was significantly more accurate and precise than SS, with mean ± SD needle-to-target error of 1.8 ± 1.0 mm (operator 1) and 1.3 ± 0.5 mm (operator 2). AA reduced the insertion time by 50% to 80% and total procedure time by 25%, compared to SS. CONCLUSIONS: The proposed hydrostatic actuator system may improve accuracy and reduce procedure time for MRI-guided targeted needle placement during motion.