A model-based cost-utility analysis of an automated notification system for deteriorating patients on general wards

BACKGROUND

Delayed response to clinical deterioration of hospital inpatients is common. Deployment of an electronic automated advisory vital signs monitoring and notification system to signal clinical deterioration is associated with significant improvements in clinical outcomes but there is no evidence on the cost-effectiveness compared with routine monitoring, in the National Health Service (NHS) in the United Kingdom (UK).

METHODS

A decision analytic model was developed to estimate the cost-effectiveness of an electronic automated advisory notification system versus standard care, in adults admitted to a district general hospital. Analyses considered: (1) the cost-effectiveness of the technology based on secondary analysis of patient level data of 3787 inpatients in a before-and-after study; and (2) the cost-utility (cost per quality-adjusted life-year (QALY)) over a lifetime horizon, extrapolated using published data. Analysis was conducted from the perspective of the NHS. Uncertainty in the model was assessed using a range of sensitivity analyses.

RESULTS

The study population had a mean age of 68 years, 48% male, with a median inpatient stay of 6 days. Expected life expectancy at discharge was assumed to be 17.74 years. (1) Cost-effectiveness analysis: The automated notification system was more effective (-0.027 reduction in mean events per patient) and provided a cost saving of -£12.17 (-182.07 to 154.80) per patient admission. (2) Cost-utility analysis: Over a lifetime horizon the automated notification system was dominant, demonstrating a positive incremental QALY gain (0.0287 QALYs, equivalent to ~10 days of perfect health) and a cost saving of £55.35. At a threshold of £20,000 per QALY, the probability of automated monitoring being cost-effective in the NHS was 81%. Increased use of cableless sensors may reduce cost-savings, however, the intervention remains cost-effective at 100% usage (ICER: £3,107/QALY). Stratified cost-effectiveness analysis by age, National Early Warning Score (NEWS) on admission, and primary diagnosis indicated the automated notification system was cost-effective for most strategies and that use representative of the patient population studied was the most cost-saving strategy.

CONCLUSION

Automated notification system for adult patients admitted to general wards appears to be a cost-effective use in the NHS; adopting this technology could be good use of scarce resources with significance for patient safety.

Accelerated liver water T1 mapping using single-shot continuous inversion-recovery spiral imaging

PURPOSE

Liver T1 mapping techniques typically require long breath holds or long scan time in free-breathing, need correction for B 1 + inhomogeneities and process composite (water and fat) signals. The purpose of this work is to accelerate the multi-slice acquisition of liver water selective T1 (wT1) mapping in a single breath hold, improving the k-space sampling efficiency.

METHODS

The proposed continuous inversion-recovery (IR) Look-Locker methodology combines a single-shot gradient echo spiral readout, Dixon processing and a dictionary-based analysis for liver wT1 mapping at 3 T. The sequence parameters were adapted to obtain short scan times. The influence of fat, B 1 + inhomogeneities and TE on the estimation of T1 was first assessed using simulations. The proposed method was then validated in a phantom and in 10 volunteers, comparing it with MRS and the modified Look-Locker inversion-recovery (MOLLI) method. Finally, the clinical feasibility was investigated by comparing wT1 maps with clinical scans in nine patients.

RESULTS

The phantom results are in good agreement with MRS. The proposed method encodes the IR-curve for the liver wT1 estimation, is minimally sensitive to B 1 + inhomogeneities and acquires one slice in 1.2 s. The volunteer results confirmed the multi-slice capability of the proposed method, acquiring nine slices in a breath hold of 11 s. The present work shows robustness to B 1 + inhomogeneities (wT 1 , No B 1 + = 1.07 wT 1 , B 1 + - 45.63 , R 2 = 0.99 ) , good repeatability (wT 1 , 2 ° = 1 . 0 wT 1 , 1 ° - 2.14 , R 2 = 0.96 ) and is in better agreement with MRS (wT 1 = 0.92 wT 1 MRS + 103.28 , R 2 = 0.38 ) than is MOLLI (wT 1 MOLLI = 0.76 wT 1 MRS + 254.43 , R 2 = 0.44 ) . The wT1 maps in patients captured diverse lesions, thus showing their clinical feasibility.

CONCLUSION

A single-shot spiral acquisition can be combined with a continuous IR Look-Locker method to perform rapid repeatable multi-slice liver water T1 mapping at a rate of 1.2 s per slice without a B 1 + map. The proposed method is suitable for nine-slice liver clinical applications acquired in a single breath hold of 11 s.

Motion-induced phase-corrected homodyne reconstruction for partial Fourier single-shot diffusion-weighted echo planar imaging of the liver

Partial Fourier encoding is popular in single-shot (ss) diffusion-weighted (DW) echo planar imaging (EPI) because it enables a shorter echo time (TE) and, hence, improves the signal-to-noise-ratio. Motion during diffusion encoding causes k-space shifting and dispersion, which compromises the quality of the homodyne reconstruction. This work provides a comprehensive understanding of the artifacts in homodyne reconstruction of partial Fourier ss-DW-EPI data in the presence of motion-induced phase and proposes the motion-induced phase-corrected homodyne (mpc-hdyne) reconstruction method to ameliorate these artifacts. Simulations with different types of motion-induced phase were performed to provide an understanding of the potential artifacts that occur in the homodyne reconstruction of partial Fourier ss-DW-EPI data. To correct for the artifacts, the mpc-hdyne reconstruction is proposed. The algorithm recenters k-space, updates the partial Fourier factor according to detected global k-space shifts, and removes low-resolution nonlinear phase before the conventional homodyne reconstruction. The mpc-hdyne reconstruction is tested on both simulation and in vivo data. Motion-induced phase can cause signal overestimation, worm artifacts, and signal loss in partial Fourier ss-DW-EPI data with the conventional homodyne reconstruction. Simulation and in vivo data showed that the proposed mpc-hdyne reconstruction ameliorated artifacts, yielding higher quality DW images compared with conventional homodyne reconstruction. Based on the understanding of the artifacts in homodyne reconstruction of partial Fourier ss-DW-EPI data, the mpc-hdyne reconstruction was proposed and showed superior performance compared with the conventional homodyne reconstruction on both simulation and in vivo data.

Accelerating spiral deblurring with square kernels and low-pass preconditioning

PURPOSE

Robust implementation of spiral imaging requires efficient deblurring. A deblurring method was previously proposed to separate and deblur water and fat simultaneously, based on image-space kernel operations. The goal of this work is to improve the performance of the previous deblurring method using kernels with better properties.

METHODS

Four types of kernels were formed using different models for the region outside the collected k-space as well as low-pass preconditioning (LP). The performances of the kernels were tested and compared with both phantom and volunteer data. Data were also synthesized to evaluate the SNR.

RESULTS

The proposed "square" kernels are much more compact than the previously used circular kernels. Square kernels have better properties in terms of normalized RMS error, structural similarity index measure, and SNR. The square kernels created by LP demonstrated the best performance of artifact mitigation on phantom data.

CONCLUSIONS

The sizes of the blurring kernels and thus the computational cost can be reduced by the proposed square kernels instead of the previous circular ones. Using LP may further enhance the performance.

Volumetric T2 -weighted spin echo imaging with improved SNR using localized quadratic encoding and a spiral readout trajectory

PURPOSE

To demonstrate T2 -weighted (single-echo) spin-echo (SE) imaging with near-optimal acquisition efficiency by applying SNR-efficient RF slice encoding and spiral readout.

METHODS

A quadratic-phase (frequency swept) excitation RF pulse replaced the conventional excitation in T2 -weighted SE sequence to excite a thick slab that is internally spatially encoded by a variable phase along the slice direction. Highly overlapping slabs centered at every desired slice location were acquired in multiple passes, such that the entire imaging volume was excited by contiguous slabs in any given pass. Following 90° excitation, each slab was refocused with a conventional 180° RF to produce a SE signal, followed by a spiral in-out readout. A noise-insensitive reconstruction removed the quadratic phase in the spatial frequency domain, yielding desired slice resolution and improved SNR.

RESULTS

Increasing the RF frequency sweep (hence, excitation width) allowed more frequent encoding of each slice over the multiple passes, improving final image SNR, until crosstalk ensued at excessive slab widths compared to their center-to-center spacing. With an optimized slab width, the proposed technique used all passes to acquire every prescribed slice, with substantially improved SNR over conventional SE or 2D-turbo-spin-echo (TSE) scans. Quantitative SNR measurements indicated similar SNR as 3D-TSE, but radiologist scoring favored 3D-TSE, mainly because of spiral-related artifacts and possibly because of regularized reconstructions in 3D-TSE.

CONCLUSION

Using SNR-efficient slice excitation scheme and spiral readout helped eliminate SNR and temporal inefficiencies in conventional T2 -weighted imaging, yielding SNR independent of TR or number of passes.

OpenCap: Human movement dynamics from smartphone videos

Measures of human movement dynamics can predict outcomes like injury risk or musculoskeletal disease progression. However, these measures are rarely quantified in large-scale research studies or clinical practice due to the prohibitive cost, time, and expertise required. Here we present and validate OpenCap, an open-source platform for computing both the kinematics (i.e., motion) and dynamics (i.e., forces) of human movement using videos captured from two or more smartphones. OpenCap leverages pose estimation algorithms to identify body landmarks from videos; deep learning and biomechanical models to estimate three-dimensional kinematics; and physics-based simulations to estimate muscle activations and musculoskeletal dynamics. OpenCap's web application enables users to collect synchronous videos and visualize movement data that is automatically processed in the cloud, thereby eliminating the need for specialized hardware, software, and expertise. We show that OpenCap accurately predicts dynamic measures, like muscle activations, joint loads, and joint moments, which can be used to screen for disease risk, evaluate intervention efficacy, assess between-group movement differences, and inform rehabilitation decisions. Additionally, we demonstrate OpenCap's practical utility through a 100-subject field study, where a clinician using OpenCap estimated musculoskeletal dynamics 25 times faster than a laboratory-based approach at less than 1% of the cost. By democratizing access to human movement analysis, OpenCap can accelerate the incorporation of biomechanical metrics into large-scale research studies, clinical trials, and clinical practice.

Acoustic noise reduction for spiral MRI by gradient derating

PURPOSE

To show that the acoustic noise of spiral MRI can be reduced by derating the gradients with minimal penalty to image quality and scan time, and to illustrate an algorithm for optimal choice of derating parameters.

THEORY AND METHODS

Acoustic noise level was measured and compared for various values of maximum gradient amplitude and slew rate for T₁ -weighted spin-echo spiral scans while maintaining image contrast, FOV and resolution, and readout time. A full gradient trajectory and a derated gradient (undersampled) trajectory were chosen for a volunteer scan followed by parallel imaging-aided reconstruction to illustrate comparable image SNR. Two auto-derating methods, which prioritize slew rate and gradient amplitude, respectively, were derived using analytical results from the WHIRLED PEAS variant of spiral waveforms and compared in their acoustic noise level under test use cases.

RESULTS

Derating the gradients made the scan quieter by 16.6 dB(A) on average than a full gradient trajectory and required an undersampling factor R = 2 in order to maintain scan time, with no appreciable penalty in image SNR. Prioritizing reduced slew rate resulted in maximal loudness reduction.

CONCLUSION

Scanner gradients can often be derated to reduce the acoustic noise for spiral MRI with minimal penalty in scan time and image quality with the help of parallel imaging. An automatic slew-priority derating method that maximizes loudness reduction is given.

Accelerated Breast Diffusion-weighted Imaging Using Multiband Sensitivity Encoding with the CAIPIRINHA Method: Clinical Experience at 3 T

Purpose To examine the clinical value of multiband (MB) sensitivity encoding (SENSE)-accelerated diffusion-weighted imaging (DWI) for breast imaging by performing quantitative and qualitative comparisons with conventional diffusion-weighted echo-planar imaging, or conventional DWI (cDWI). Materials and Methods In this prospective study (ClinicalTrials.gov identifier NCT03607552), women with breast cancer were recruited from July 2018 to July 2019 to undergo additional MB SENSE DWI during clinical 3-T breast MRI examinations. The cDWI and MB SENSE DWI acquisitions were assessed both quantitatively and qualitatively. Regions of interest were defined for tumorous and normal tissue, and the tumor apparent diffusion coefficient (ADC), contrast-to-noise ratio (CNR), and signal index (SI) were calculated for both DWI methods. Three readers independently reviewed the two acquisitions side by side and provided relative image quality scores. Tumor ADC, CNR, and SI measures were compared between cDWI and MB SENSE DWI acquisitions by using a paired t test, and reader preferences were evaluated by using the sign test. Results The study included 38 women (median age, 48 years; range, 28-83 years). Overall agreement was good between cDWI and MB SENSE DWI tumor ADC measures (intraclass correlation coefficient, 0.87 [95% CI: 0.75, 0.94]), and no differences were evident in the ADC (median, 0.93 × 10^-3 mm²/sec vs 0.87 ×10^-3 mm²/sec; P = .50), CNR (2.2 vs 2.3; P = .17), or SI (9.2 vs 9.2; P = .23) measurements. The image quality of cDWI and MB SENSE DWI acquisitions were considered equal for 51% of images (58 of 114), whereas MB SENSE DWI was preferred more often than cDWI (37% [42 of 114] vs 12% [14 of 114]; P < .001). The preference for MB SENSE DWI was most often attributed to better fat suppression. Conclusion MB SENSE can be used to accelerate breast DWI acquisition times without compromising the image quality or the fidelity of quantitative ADC measurements. Keywords: MR-Diffusion-weighted Imaging, Breast, Comparative Studies, Technology Assessment Clinical trial registration no. NCT03607552 © RSNA, 2022.

Fast 3D MR elastography of the whole brain using spiral staircase: Data acquisition, image reconstruction, and joint deblurring

PURPOSE

To address the need for a method to acquire 3D data for MR elastography (MRE) of the whole brain with substantially improved spatial resolution, high SNR, and reduced acquisition time compared with conventional methods.

METHODS

We combined a novel 3D spiral staircase data-acquisition method with a spoiled gradient-echo pulse sequence and MRE motion-encoding gradients (MEGs). The spiral-out acquisition permitted use of longer-duration motion-encoding gradients (ie, over two full oscillatory cycles) to enhance displacement SNR, while still maintaining a reasonably short TE for good phase-SNR. Through-plane parallel imaging with low noise penalties was implemented to accelerate acquisition along the slice direction. Shared anatomical information was exploited in the deblurring procedure to further boost SNR for stiffness inversion.

RESULTS

In vivo and phantom experiments demonstrated the feasibility of the proposed method in producing brain MRE results comparable to the spin-echo-based approaches, both qualitatively and quantitatively. High-resolution (2-mm isotropic) brain MRE data were acquired in 5 minutes using our method with good SNR. Joint deblurring with shared anatomical information produced SNR-enhanced images, leading to upward stiffness estimation.

CONCLUSION

A novel 3D gradient-echo-based approach has been designed and implemented, and shown to have promising potential for fast and high-resolution in vivo MRE of the whole brain.

Yttrium-90 quantitative phantom study using digital photon counting PET

BACKGROUND

PET imaging of 90Y-microsphere distribution following radioembolisation is challenging due to the count-starved statistics from the low branching ratio of e+/e- pair production during 90Y decay. PET systems using silicon photo-multipliers have shown better 90Y image quality compared to conventional photo-multiplier tubes. The main goal of the present study was to evaluate reconstruction parameters for different phantom configurations and varying listmode acquisition lengths to improve quantitative accuracy in 90Y dosimetry, using digital photon counting PET/CT.

METHODS

Quantitative PET and dosimetry accuracy were evaluated using two uniform cylindrical phantoms specific for PET calibration validation. A third body phantom with a 9:1 hot sphere-to-background ratio was scanned at different activity concentrations of 90Y. Reconstructions were performed using OSEM algorithm with varying parameters. Time-of-flight and point-spread function modellings were included in all reconstructions. Absorbed dose calculations were carried out using voxel S-values convolution and were compared to reference Monte Carlo simulations. Dose-volume histograms and root-mean-square deviations were used to evaluate reconstruction parameter sets. Using listmode data, phantom and patient datasets were rebinned into various lengths of time to assess the influence of count statistics on the calculation of absorbed dose. Comparisons between the local energy deposition method and the absorbed dose calculations were performed.

RESULTS

Using a 2-mm full width at half maximum post-reconstruction Gaussian filter, the dosimetric accuracy was found to be similar to that found with no filter applied but also reduced noise. Larger filter sizes should not be used. An acquisition length of more than 10 min/bed reduces image noise but has no significant impact in the quantification of phantom or patient data for the digital photon counting PET. 3 iterations with 10 subsets were found suitable for large spheres whereas 1 iteration with 30 subsets could improve dosimetry for smaller spheres.

CONCLUSION

The best choice of the combination of iterations and subsets depends on the size of the spheres. However, one should be careful on this choice, depending on the imaging conditions and setup. This study can be useful in this choice for future studies for more accurate 90Y post-dosimetry using a digital photon counting PET/CT.

Predictive Modeling for Voxel-Based Quantification of Imaging-Based Subtypes of Pancreatic Ductal Adenocarcinoma (PDAC): A Multi-Institutional Study

Previously, we characterized qualitative imaging-based subtypes of pancreatic ductal adenocarcinoma (PDAC) on computed tomography (CT) scans. Conspicuous (high delta) PDAC tumors are more likely to have aggressive biology and poorer clinical outcomes compared to inconspicuous (low delta) tumors. Here, we developed a quantitative classification of this imaging-based subtype (quantitative delta; q-delta). Retrospectively, baseline pancreatic protocol CT scans of three cohorts (cohort#1 = 101, cohort#2 = 90 and cohort#3 = 16 [external validation]) of patients with PDAC were qualitatively classified into high and low delta. We used a voxel-based method to volumetrically quantify tumor enhancement while referencing normal-pancreatic-parenchyma and used machine learning-based analysis to build a predictive model. In addition, we quantified the stromal content using hematoxylin- and eosin-stained treatment-naïve PDAC sections. Analyses revealed that PDAC quantitative enhancement values are predictive of the qualitative delta scoring and were used to build a classification model (q-delta). Compared to high q-delta, low q-delta tumors were associated with improved outcomes, and the q-delta class was an independent prognostic factor for survival. In addition, low q-delta tumors had higher stromal content and lower cellularity compared to high q-delta tumors. Our results suggest that q-delta classification provides a clinically and biologically relevant tool that may be integrated into ongoing and future clinical trials.

Adaptive Maximal Blood Flow Velocity Estimation From Transcranial Doppler Echos

OBJECTIVE

Novel applications of transcranial Doppler (TCD) ultrasonography, such as the assessment of cerebral vessel narrowing/occlusion or the non-invasive estimation of intracranial pressure (ICP), require high-quality maximal flow velocity waveforms. However, due to the low signal-to-noise ratio of TCD spectrograms, measuring the maximal flow velocity is challenging. In this work, we propose a calibration-free algorithm for estimating maximal flow velocities from TCD spectrograms and present a pertaining beat-by-beat signal quality index.

METHODS

Our algorithm performs multiple binary segmentations of the TCD spectrogram and then extracts the pertaining envelopes (maximal flow velocity waveforms) via an edge-following step that incorporates physiological constraints. The candidate maximal flow velocity waveform with the highest signal quality index is finally selected.

RESULTS

We evaluated the algorithm on 32 TCD recordings from the middle cerebral and internal carotid arteries in 6 healthy and 12 neurocritical care patients. Compared to manual spectrogram tracings, we obtained a relative error of -1.5%, when considering the whole waveform, and a relative error of -3.3% for the peak systolic velocity.

CONCLUSION

The feedback loop between the signal quality assessment and the binary segmentation yields a robust algorithm for maximal flow velocity estimation. Clinical Impact: The algorithm has already been used in our ICP estimation pipeline. By making the code and the data publicly available, we hope that the algorithm will be a useful building block for the development of novel TCD applications that require high-quality flow velocity waveforms.

Analysis of spatiotemporal fidelity in quantitative 3D first-pass perfusion cardiovascular magnetic resonance

BACKGROUND

Whole-heart first-pass perfusion cardiovascular magnetic resonance (CMR) relies on highly accelerated image acquisition. The influence of undersampling on myocardial blood flow (MBF) quantification has not been systematically investigated yet. In the present work, the effect of spatiotemporal scan acceleration on image reconstruction accuracy and MBF error was studied using a numerical phantom and validated in-vivo.

METHODS

Up to 10-fold scan acceleration using k-t PCA and k-t SPARSE-SENSE was simulated using the MRXCAT CMR numerical phantom framework. Image reconstruction results were compared to ground truth data in the k-f domain by means of modulation transfer function (MTF) analysis. In the x-t domain, errors pertaining to specific features of signal intensity-time curves and MBF values derived using Fermi model deconvolution were analysed. In-vivo first-pass CMR data were acquired in ten healthy volunteers using a dual-sequence approach assessing the arterial input function (AIF) and myocardial enhancement. 10x accelerated 3D k-t PCA and k-t SPARSE-SENSE were compared and related to non-accelerated 2D reference images.

RESULTS

MTF analysis revealed good recovery of data upon k-t PCA reconstruction at 10x undersampling with some attenuation of higher temporal frequencies. For 10x k-t SPARSE-SENSE the MTF was found to decrease to zero at high spatial frequencies for all temporal frequencies indicating a loss in spatial resolution. Signal intensity-time curve errors were most prominent in AIFs from 10x k-t PCA, thereby emphasizing the need for separate AIF acquisition using a dual-sequence approach. These findings were confirmed by MBF estimation based on AIFs from fully sampled and undersampled simulations. Average in-vivo MBF estimates were in good agreement between both accelerated and the fully sampled methods. Intra-volunteer MBF variation for fully sampled 2D scans was lower compared to 10x k-t PCA and k-t SPARSE-SENSE data.

CONCLUSION

Quantification of highly undersampled 3D first-pass perfusion CMR yields accurate MBF estimates provided the AIF is obtained using fully sampled or moderately undersampled scans as part of a dual-sequence approach. However, relative to fully sampled 2D perfusion imaging, intra-volunteer variation is increased using 3D approaches prompting for further developments.

Magnetic Particle Imaging for High Temporal Resolution Assessment of Aneurysm Hemodynamics

Purpose

The purpose of this work was to demonstrate the capability of magnetic particle imaging (MPI) to assess the hemodynamics in a realistic 3D aneurysm model obtained by additive manufacturing. MPI was compared with magnetic resonance imaging (MRI) and dynamic digital subtraction angiography (DSA).

Materials and Methods

The aneurysm model was of saccular morphology (7 mm dome height, 5 mm cross-section, 3–4 mm neck, 3.5 mm parent artery diameter) and connected to a peristaltic pump delivering a physiological flow (250 mL/min) and pulsation rate (70/min). High-resolution (4 h long) 4D phase contrast flow quantification (4D pc-fq) MRI was used to directly assess the hemodynamics of the model. Dynamic MPI, MRI, and DSA were performed with contrast agent injections (3 mL volume in 3 s) through a proximally placed catheter.

Results and Discussion

4D pc-fq measurements showed distinct pulsatile flow velocities (20–80 cm/s) as well as lower flow velocities and a vortex inside the aneurysm. All three dynamic methods (MPI, MRI, and DSA) also showed a clear pulsation pattern as well as delayed contrast agent dynamics within the aneurysm, which is most likely caused by the vortex within the aneurysm. Due to the high temporal resolution of MPI and DSA, it was possible to track the contrast agent bolus through the model and to estimate the average flow velocity (about 60 cm/s), which is in accordance with the 4D pc-fq measurements.

Conclusions

The ionizing radiation free, 4D high resolution MPI method is a very promising tool for imaging and characterization of hemodynamics in human. It carries the possibility of overcoming certain disadvantages of other modalities like considerably lower temporal resolution of dynamic MRI and limited 2D characteristics of DSA. Furthermore, additive manufacturing is the key for translating powerful pre-clinical techniques into the clinic.