Optimal Acquisition Protocols Research Articles

Automatic assignment of optimal data acquisition protocols for MRI examinations in Japanese

Automatic assignment of optimal data acquisition protocols for MRI examinations in Japanese

Imaging and anesthesia protocol optimization in sedated clinical resting state fMRI.

The quality of resting-state functional MRI (rs-fMRI) under anesthesia is variable and there are no guidelines on optimal image acquisition or anesthesia protocol. We aim to identify the factors that may lead to compromised clinical rs-fMRI under anesthesia. In this cross-sectional study, we analyzed clinical rs-fMRI data acquired under anesthesia from 2009-2023 at Massachusetts General Hospital. Independent component analysis driven resting state networks (RSN) of each patient were evaluated qualitatively and quantitatively and grouped as robust or weak. Overall networks were evaluated using the qualitative method, and motor and language networks were evaluated using the quantitative method. RSN robustness was analyzed in 4 outcome categories: overall, combined Motor-Language, individual motor, and language networks. Predictor variables included rs-fMRI acquisition parameters, anesthesia medications, underlying brain structural abnormalities, age, and sex. Logistic regression was used to examine the effect of the study variables on RSN robustness. Sixty-nine patients were identified. With qualitative assessment, 40 had robust and 29 had weak overall RSN. Quantitatively, 45 patients had robust, while 24 had weak Motor-Language networks. Among all the predictor variables, only sevoflurane significantly contributed to the outcomes, with sevoflurane administration reducing the odds of having robust RSN in overall (Odds Radio (OR)= 0.2, 95% Confidence Interval (CI) = [0.05;0.79], p = .02), Motor-Language (OR = 0.18, 95% CI = [0.04;0.80], p = .02) and individual motor (OR= 0.1, 95% CI = [0.02;0.64], p= .02) categories. Individual language network robustness was not associated with the tested predictor variables. Sevoflurane anesthesia may compromise the visibility of fMRI resting state networks, particularly impacting motor networks. This finding suggests that the type of anesthesia is a critical factor in rs-fMRI quality. We did not observe the association of the MR acquisition technique or underlying structural abnormality with the RSN robustness. BOLD = Blood Oxygen Level-Dependent; ICA = Independent Component Analysis; Rs-fMRI = Resting-State Functional Magnetic Resonance Imaging; RSN = Resting-State Networks; SNR = Signal-to-Noise Ratio.

Scaling up contrast-enhanced micro-CT imaging: Optimizing contrast and acquisition for large ex-vivo human samples

Microfocus Computed Tomography (Micro-CT) is a novel method for non-destructive 3D imaging of samples, reaching microscale resolutions. While initially prominent in material sciences for small samples, micro-CT now gains significance in biological and medical studies. Here we present our utilization of micro-CT for imaging large ex-vivo human samples for anatomical and forensic research in three recent experiments and discuss the fundamentals of micro-CT imaging.For pelvic anatomical research, whole human pelvises were imaged to explore nerve anatomy around the prostate using various concentrations of buffered lugol (B-lugol). Advanced acquisition protocols were essential due to X-ray attenuation properties of the sample, which required higher energy for sufficient photon transmission.For fetal research, B-lugol stained fetuses of 20–24 gestational weeks underwent full body imaging. However, this led to challenging acquisition parameters and images of insufficient quality. Subsequent destaining yielded less dense, yet contrast-maintaining samples allowing higher quality images. Refined acquisition protocols with reduced energy improved image quality.For forensic research, explanted hyoid-larynx complexes were imaged. Micro-CT imaging showed potential in visualizing micro-fractures. The addition of B-lugol allowed for excellent soft tissue contrast and promising possibilities for forensic evaluation.In conclusion, micro-CT imaging accommodates a diversity of large ex-vivo human samples for anatomical and forensic purposes, though challenges arise with optimal soft tissue staining and acquisition protocols. We describe partial destaining as a new possibility to alleviate scanning issues to improve scan quality and highlight topics for future research. Micro-CT imaging is a promising new avenue for medical research and forensic evaluation.

Can patient-specific acquisition protocol improve performance on defect detection task in myocardial perfusion SPECT?

Myocardial perfusion imaging using single-photon emission computed tomography (SPECT), or myocardial perfusion SPECT (MPS) is a widely used clinical imaging modality for the diagnosis of coronary artery disease. Current clinical protocols for acquiring and reconstructing MPS images are similar for most patients. However, for patients with outlier anatomical characteristics, such as large breasts, images acquired using conventional protocols are often sub-optimal in quality, leading to degraded diagnostic accuracy. Solutions to improve image quality for these patients outside of increased dose or total acquisition time remain challenging. Thus, there is an important need for new methodologies that can help improve the quality of the acquired images for such patients, in terms of the ability to detect myocardial perfusion defects. One approach to improving this performance is adapting the image acquisition protocol specific to each patient. Studies have shown that in MPS, different projection angles usually contain varying amounts of information for the detection task. However, current clinical protocols spend the same time at each projection angle. In this work, we evaluated whether an acquisition protocol that is optimized for each patient could improve performance on the task of defect detection on reconstructed images for patients with outlier anatomical characteristics. For this study, we first designed and implemented a personalized patient-specific protocol-optimization strategy, which we term precision SPECT (PRESPECT). This strategy integrates the theory of ideal observers with the constraints of tomographic reconstruction to optimize the acquisition time for each projection view, such that performance on the task of detecting myocardial perfusion defects is maximized. We performed a clinically realistic simulation study on patients with outlier anatomies on the task of detecting perfusion defects on various realizations of low-dose scans by an anthropomorphic channelized Hotelling observer. Our results show that using PRESPECT led to improved performance on the defect detection task for the considered patients. These results provide evidence that personalization of MPS acquisition protocol has the potential to improve defect detection performance on reconstructed images by anthropomorphic observers for patients with outlier anatomical characteristics. Thus, our findings motivate further research to design optimal patient-specific acquisition and reconstruction protocols for MPS, as well as developing similar approaches for other medical imaging modalities.

CACTUS: a computational framework for generating realistic white matter microstructure substrates.

Monte-Carlo diffusion simulations are a powerful tool for validating tissue microstructure models by generating synthetic diffusion-weighted magnetic resonance images (DW-MRI) in controlled environments. This is fundamental for understanding the link between micrometre-scale tissue properties and DW-MRI signals measured at the millimetre-scale, optimizing acquisition protocols to target microstructure properties of interest, and exploring the robustness and accuracy of estimation methods. However, accurate simulations require substrates that reflect the main microstructural features of the studied tissue. To address this challenge, we introduce a novel computational workflow, CACTUS (Computational Axonal Configurator for Tailored and Ultradense Substrates), for generating synthetic white matter substrates. Our approach allows constructing substrates with higher packing density than existing methods, up to 95% intra-axonal volume fraction, and larger voxel sizes of up to 500μm3 with rich fibre complexity. CACTUS generates bundles with angular dispersion, bundle crossings, and variations along the fibres of their inner and outer radii and g-ratio. We achieve this by introducing a novel global cost function and a fibre radial growth approach that allows substrates to match predefined targeted characteristics and mirror those reported in histological studies. CACTUS improves the development of complex synthetic substrates, paving the way for future applications in microstructure imaging.

Optimized SPECT Imaging of 224Ra α-Particle Therapy by 212Pb Photon Emissions.

In preparation for an α-particle therapy trial using 1-7 MBq of 224Ra, the feasibility of tomographic SPECT/CT imaging was of interest. The nuclide decays in 6 steps to stable 208Pb, with 212Pb as the principle photon-emitting nuclide. 212Bi and 208Tl emit high-energy photons up to 2,615 keV. A phantom study was conducted to determine the optimal acquisition and reconstruction protocol. Methods: The spheres of a body phantom were filled with a 224Ra-RaCl2 solution, and the background compartment was filled with water. Images were acquired on a SPECT/CT system. In addition, 30-min scans were acquired for 80- and 240-keV emissions, using triple-energy windows, with both medium-energy and high-energy collimators. Images were acquired at 90-95 and 29-30 kBq/mL, plus an explorative 3-min acquisition at 20 kBq/mL (using only the optimal protocol). Reconstructions were performed with attenuation correction only, attenuation plus scatter correction, 3 levels of postfiltering, and 24 levels of iterative updates. Acquisitions and reconstructions were compared using the maximum value and signal-to-scatter peak ratio for each sphere. Monte Carlo simulations were performed to examine the contributions of key emissions. Results: Secondary photons of the 2,615-keV 208Tl emission produced in the collimators make up most of the acquired energy spectrum, as revealed by Monte Carlo simulations, with only a small fraction (3%-6%) of photons in each window providing useful information for imaging. Still, decent image quality is possible at 30 kBq/mL, and nuclide concentrations are imageable down to approximately 2-5 kBq/mL. The overall best results were obtained with the 240-keV window, medium-energy collimator, attenuation and scatter correction, 30 iterations and 2 subsets, and a 12-mm gaussian postprocessing filter. However, all combinations of the applied collimators and energy windows were capable of producing adequate results, even though some failed to reconstruct the 2 smallest spheres. Conclusion: SPECT/CT imaging of 224Ra in equilibrium with daughters is possible, with sufficient image quality to provide clinical utility for the current trial of intraperitoneally administrated activity. A systematic scheme for optimization was designed to select acquisition and reconstruction settings.

Modification of [18F]-FDG PET/CT imaging protocols in obese oncology patients: A nationwide survey

IntroductionThe use of medical imaging for diagnosis, staging and follow-up in Oncology context is incredibly important, being the use of [18F]-FDG PET/CT particularly advantageous in specific contexts like the case of obese patients. However, imaging the latter can be challenging sometimes, since their own body size may affect overall image quality and adds technical difficulties for the operator(s) performing the examination. MethodsThis research project was developed with the aim of analysing the current personal practices of Portuguese Nuclear Medicine Technologists (NMTs) in the adaptation of 18F-FDG PET/CT oncological protocols for obese patients and comparing the results with parameters referenced in literature. A non-experimental research study was conducted using a survey delivered online to NMTs through social media platforms (Facebook® and LinkedIn®) and by sending the link directly to contacts within the research team professional and personal networks. ResultsAnswers from a total of 26 participants were obtained, with 88.5% of participants admitting modifying technical protocols in examinations for obese patients. Changes in PET protocols included an increase in the administered activity (60.9%), an increase in scan time per individual bed position (69.6%) and the use of Time-of-Flight (TOF) technology whenever available. Protocol changes in CT included increasing the mA (82.6%), raising the KVp (47.8%), the application of iterative reconstruction (69.6%) and the use of automatic exposure control (AEC) (52.2%). The remaining parameters (pitch, algorithm, slice thickness, display FOV, gantry rotation time and energy acceptance window) were claimed not to be modified by around 90% of professionals. ConclusionPortuguese NMTs tend to change the [18F]-FDG PET/CT protocols for obese patients. However, while some of the parameters appear to be contradictory or redundant, others require further optimisation, especially in the CT component. Implications for practiceEfforts should be made to optimize acquisition protocols used in [18F]-FDG PET/CT scans for obese patients.

Optimal theranostic SPECT imaging protocol for 223radium dichloride therapy

223Radium dichloride image-based individual dosimetry requires an optimal acquisition and reconstruction protocol and proper image correction methods for theranostic applications. To assess this problem, radium-223 dichloride SPECT images were acquired from a Jaszczak simulator with a dual-headed gamma camera, LEHR collimator, 128 × 128 matrix, and total time of 32 minutes. A cylindrical PMMA phantom was used to calibrate the measurements performed with Jaszczak. The image quality parameters (noise coefficient, contrast, contrast-to-noise ratio and recovery coefficient) and septal penetration correction were calculated by MATLAB®. The best results for the investigated image quality parameters were obtained with an 89 keV energy window (24% wide) produced together with OSEM/MLEM reconstruction (8 subsets and 4 iterations) applying a Butterworth filter (order 10 and cutoff frequency of 0.48 cycles·cm−1). The successfully performed recovery coefficient parameter evaluation allows uptake correction for future patient dosimetry applications.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques.

ObjectiveSummarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments.MethodsExperts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics).ResultsHigh-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies.ConclusionConsiderable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.

Towards reliable spinal cord fMRI: Assessment of common imaging protocols

Functional magnetic resonance imaging (fMRI) has revolutionized the investigation of brain function. Similar approaches can be translated to probe spinal mechanisms. However, imaging the spinal cord remains challenging, notably due to its size and location. Technological advances are gradually tackling these issues, though there is yet no consensus on optimal acquisition protocols. In this study, we assessed the performance of three sequences during a simple motor task and at rest, in 15 healthy humans. Building upon recent literature, we selected three imaging protocols: a sequence integrating outer volume suppression (OVS) and two sequences implementing inner field-of-view imaging (ZOOMit) with different spatial and temporal resolutions. Images acquired using the OVS sequence appeared more prone to breathing-induced signal fluctuations, though they exhibited a higher temporal signal-to-noise ratio than ZOOMit sequences. Conversely, the spatial signal-to-noise ratio was higher for the two ZOOMit schemes. In spite of these differences in signal properties, all sequences yielded comparable performance in detecting group-level task-related activity, observed in the expected spinal levels. Nevertheless, our results suggest a superior sensitivity and robustness of patterns imaged using the OVS acquisition scheme. To analyze the data acquired at rest, we deployed a dynamic functional connectivity framework, SpiCiCAP, and we evaluated the ability of the three acquisition schemes to disentangle intrinsic spinal signals. We demonstrated that meaningful subdivisions of the spinal cord's functional architecture could be uncovered for all three sequences, with similar spatio-temporal properties across acquisition parameters. Cleaner and more stable components were, however, obtained using ZOOMit sequences. This study emphasizes the potential of fMRI as a robust tool to image spinal activity in vivo and it highlights specificities and similarities of three acquisition methods. This represents a key step towards the establishment of standardized spinal cord fMRI protocols.

The effect of different statistical approaches on image quality data obtained from radiological examinations

IntroductionSelection of optimal image acquisition protocols in medical imaging remains a grey area, the superimposed use of the Likert scale in radiological image quality evaluations creates an additional challenge for the statistical analysis of image quality data.Using a simulation study, we have trialled a novel approach to analysing radiological image quality Likert scale data. MethodsA simulation study was undertaken where simulated datasets were generated based on the distribution of Likert scale values according to varying image acquisition protocols from a real dataset. Simulated Likert scale values were pooled in four different ways; the mean, median, mode and the summation of patient Likert scale values of which the total was assigned a categorical Likert scale value. Estimates of bias, MAPE and RMSPE were then calculated for all four pooling approaches to determine which method most accurately represented an expert's opinion. ResultsWhen compared to an expert's opinion, the method of summation and categorisation of Likert scale values was most accurate 49 times out of the 114 (43.0%) tests. The mean 28 times out of 114 (24.6%), the median 23 times out of 114 (20.2%) and the mode 17 times out of 114 (14.9%). ConclusionWe conclude that our method of summation and categorisation of Likert scale values is most often the best representation of the simulated data compared to the expert's opinion. Implications for practiceThere is scope to reproduce this simulation study with multiple observers to reflect clinical reality more accurately with the dynamic nature of multiple observers. This also prompts future investigation into other anatomical areas, to see if the same methods produce similar results.

Neural networks for parameter estimation in microstructural MRI: Application to a diffusion-relaxation model of white matter

Specific features of white matter microstructure can be investigated by using biophysical models to interpret relaxation-diffusion MRI brain data. Although more intricate models have the potential to reveal more details of the tissue, they also incur time-consuming parameter estimation that may converge to inaccurate solutions due to a prevalence of local minima in a degenerate fitting landscape. Machine-learning fitting algorithms have been proposed to accelerate the parameter estimation and increase the robustness of the attained estimates. So far, learning-based fitting approaches have been restricted to microstructural models with a reduced number of independent model parameters where dense sets of training data are easy to generate. Moreover, the degree to which machine learning can alleviate the degeneracy problem is poorly understood. For conventional least-squares solvers, it has been shown that degeneracy can be avoided by acquisition with optimized relaxation-diffusion-correlation protocols that include tensor-valued diffusion encoding. Whether machine-learning techniques can offset these acquisition requirements remains to be tested. In this work, we employ artificial neural networks to vastly accelerate the parameter estimation for a recently introduced relaxation-diffusion model of white matter microstructure. We also develop strategies for assessing the accuracy and sensitivity of function fitting networks and use those strategies to explore the impact of the acquisition protocol. The developed learning-based fitting pipelines were tested on relaxation-diffusion data acquired with optimal and sub-optimal acquisition protocols. Networks trained with an optimized protocol were observed to provide accurate parameter estimates within short computational times. Comparing neural networks and least-squares solvers, we found the performance of the former to be less affected by sub-optimal protocols; however, model fitting networks were still susceptible to degeneracy issues and their use could not fully replace a careful design of the acquisition protocol.

Quantifying pulmonary perfusion from noncontrast computed tomography.

PurposeComputed tomography (CT)‐derived ventilation methods compute respiratory induced volume changes as a surrogate for pulmonary ventilation. Currently, there are no known methods to derive perfusion information from noncontrast CT. We introduce a novel CT‐Perfusion (CT‐P) method for computing the magnitude mass changes apparent on dynamic noncontrast CT as a surrogate for pulmonary perfusion.Methods CT‐Perfusion is based on a mass conservation model which describes the unknown mass change as a linear combination of spatially corresponding inhale and exhale HU estimated voxel densities. CT‐P requires a deformable image registration (DIR) between the inhale/exhale lung CT pair, a preprocessing lung volume segmentation, and an estimate for the Jacobian of the DIR transformation. Given this information, the CT‐P image, which provides the magnitude mass change for each voxel within the lung volume, is formulated as the solution to a constrained linear least squares problem defined by a series of subregional mean magnitude mass change measurements. Similar to previous robust CT‐ventilation methods, the amount of uncertainty in a subregional sample mean measurement is related to measurement resolution and can be characterized with respect to a tolerance parameter τ. Spatial Spearman correlation between single photon emission CT perfusion (SPECT‐P) and the proposed CT‐P method was assessed in two patient cohorts via a parameter sweep of τ. The first cohort was comprised of 15 patients diagnosed with pulmonary embolism (PE) who had SPECT‐P and 4DCT imaging acquired within 24 h of PE diagnosis. The second cohort was comprised of 15 nonsmall cell lung cancer patients who had SPECT‐P and 4DCT images acquired prior to radiotherapy. For each test case, CT‐P images were computed for 30 different uncertainty parameter values, uniformly sampled from the range [0.01, 0.125], and the Spearman correlation between the SPECT‐P and the resulting CT‐P images were computed.ResultsThe median correlations between CT‐P and SPECT‐P taken over all 30 test cases ranged between 0.49 and 0.57 across the parameter sweep. For the optimal tolerance τ = 0.0385, the CT‐P and SPECT‐P correlations across all 30 test cases ranged between 0.02 and 0.82. A one‐sample sign test was applied separately to the PE and lung cancer cohorts. A low Spearmen correlation of 15% was set as the null median value and two‐sided alternative was tested. The PE patients showed a median correlation of 0.57 (IQR = 0.305). One‐sample sign test was statistically significant with 96.5 % confidence interval: 0.20–0.63, P < 0.00001. Lung cancer patients had a median correlation of 0.57(IQR = 0.230). Again, a one‐sample sign test for median was statistically significant with 96.5 percent confidence interval: 0.45–0.71, P < 0.00001.Conclusion CT‐Perfusion is the first mechanistic model designed to quantify magnitude blood mass changes on noncontrast dynamic CT as a surrogate for pulmonary perfusion. While the reported correlations with SPECT‐P are promising, further investigation is required to determine the optimal CT acquisition protocol and numerical method implementation for CT‐P imaging.

Dynamic Contrast Enhancement (DCE) MRI-Derived Renal Perfusion and Filtration: Basic Concepts.

Dynamic contrast-enhanced (DCE) MRI monitors the transit of contrast agents, typically gadolinium chelates, through the intrarenal regions, the renal cortex, the medulla, and the collecting system. In this way, DCE-MRI reveals the renal uptake and excretion of the contrast agent. An optimal DCE-MRI acquisition protocol involves finding a good compromise between whole-kidney coverage (i.e., 3D imaging), spatial and temporal resolution, and contrast resolution. By analyzing the enhancement of the renal tissues as a function of time, one can determine indirect measures of clinically important single-kidney parameters as the renal blood flow, glomerular filtration rate, and intrarenal blood volumes. Gadolinium-containing contrast agents may be nephrotoxic in patients suffering from severe renal dysfunction, but otherwise DCE-MRI is clearly useful for diagnosis of renal functions and for assessing treatment response and posttransplant rejection.Here we introduce the concept of renal DCE-MRI, describe the existing methods, and provide an overview of preclinical DCE-MRI applications to illustrate the utility of this technique to measure renal perfusion and glomerular filtration rate in animal models.This publication is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction is complemented by two separate publications describing the experimental procedure and data analysis.

In-vivo diffusion MRI protocol optimization for the chimpanzee brain and examination of aging effects on the primate optic nerve at 3T

BackgroundDiffusion MRI (dMRI) data acquisition protocols are well-established on modern high-field clinical scanners for human studies. However, these protocols are not suitable for the chimpanzee (or other large-brained mammals) because of its substantial difference in head geometry and brain volume compared with humans. Therefore, an optimal dMRI data acquisition protocol dedicated to chimpanzee neuroimaging is needed. MethodsA multi-shot (4 segments) double spin-echo echo-planar imaging (MS-EPI) sequence and a single-shot double spin-echo EPI (SS-EPI) sequence were optimized separately for in vivo dMRI data acquisition of chimpanzees using a clinical 3T scanner. Correction for severe susceptibility-induced image distortion and signal drop-off of the chimpanzee brain was performed and evaluated using FSL software. DTI indices in different brain regions and probabilistic tractography were compared. A separate DTI data set from n=34 chimpanzees (13 to 56 years old) was collected using the optimal protocol. Age-related changes in diffusivity indices of optic nerve fibers were evaluated. ResultsThe SS-EPI sequence acquired dMRI data of the chimpanzee brain with approximately doubled the SNR as the MS-EPI sequence given the same scan time. The quality of white matter fiber tracking from the SS-EPI data was much higher than that from MS-EPI data. However, quantitative analysis of DTI indices showed no difference in most ROIs between the SS-EPI and MS-EPI sequences. The progressive evolution of diffusivity indices of optic nerves indicated mild changes in fiber bundles of chimpanzees aged 40 years and above. ConclusionThe single-shot EPI-based acquisition protocol provided better image quality of dMRI for chimpanzee brains and is recommended for in vivo dMRI study or clinical diagnosis of chimpanzees (or other large animals) using a clinical scanner. Also, the tendency of FA decrease or diffusivity increase in the optic nerve of aged chimpanzees was seen but did not show significant age-related changes, suggesting aging may have less impact on optic nerve fiber integrity of chimpanzees, in contrast to previous results for both macaque monkeys and humans.

On the optimization of bone SPECT/CT in terms of image quality and radiation dose.

IntroductionThe purpose of this study was to present the optimization process of CT parameters to reduce patient exposure during bone SPECT/CT without affecting the quality of SPECT images with attenuation correction (AC).Material and methodsA fillable phantom reflecting realistic bone scintigraphy conditions was developed and acquired on an AnyScan SC. SPECT/CT scans were carried out with different x‐ray tube current values (10, 20, 30, 40, 50, 60, 70, 90, 110, 130, 150, and 200 mA) at three different high‐voltage values (80, 100, and 120 kV). The contrast (C) and coefficients of variation (CV) in the SPECT images as well as the signal‐to‐noise ratio (SNR) and noise (SDCT) in the CT images with CTDIvol were measured. An optimal acquisition protocol that obtained SPECT/CT images with no artifacts on both CT and SPECT images, acceptable C, SNR, CV, and SDCT values, and the largest reduction in patient exposure compared to the reference acquisition procedure was sought.ResultsThe optimal set of parameters for bone SPECT/CT was determined based on a phantom study. It has been implemented in clinical practice. Two groups of patients were examined according to the baseline and optimized protocols, respectively. The new SPECT/CT protocol substantially reduced patients’ radiation exposure compared to the old protocol while maintaining the required diagnostic quality of SPECT and CT images.ConclusionsIn the study, we present a methodology that finds a compromise between diagnostic information and patient exposure during bone SPECT/CT procedures.

Fully Balanced SSFP Without an Endorectal Coil for Postimplant QA of MRI-Assisted Radiosurgery (MARS) of Prostate Cancer: A Prospective Study

To investigate fully balanced steady-state free precession (bSSFP) with optimized acquisition protocols for magnetic resonance imaging (MRI)-based postimplant quality assessment of low-dose-rate (LDR) prostate brachytherapy without an endorectal coil (ERC). Seventeen patients at a major academic cancer center who underwent MRI-assisted radiosurgery (MARS) LDR prostate cancer brachytherapy were imaged with moderate, high, or very high spatial resolution fully bSSFP MRIs without using an ERC. Between 1 and 3 signal averages (NEX) were acquired with acceleration factors (R) between 1 and 2, with the goal of keeping scan times between 4 and 6 minutes. Acquisitions with R >1 were reconstructed with parallel imaging and compressed sensing (PICS) algorithms. Radioactive seeds were identified by 3 medical dosimetrists. Additionally, some of the MRI techniques were implemented and tested at a community hospital; 3 patients underwent MARS LDR prostate brachytherapy and were imaged without an ERC. Increasing the in-plane spatial resolution mitigated partial volume artifacts and improved overall seed and seed marker visualization at the expense of reduced signal-to-noise ratio (SNR). The reduced SNR as a result of imaging at higher spatial resolution and without an ERC was partially compensated for by the multi-NEX acquisitions enabled by PICS. Resultant image quality was superior to the current clinical standard. All 3 dosimetrists achieved near-perfect precision and recall for seed identification in the 17 patients. The 3 postimplant MRIs acquired at the community hospital were sufficient to identify 208 out of 211 seeds implanted without reference to computed tomography (CT). Acquiring postimplant prostate brachytherapy MRI without an ERC has several advantages including better patient tolerance, lower costs, higher clinical throughput, and widespread access to precision LDR prostate brachytherapy. This prospective study confirms that the use of an ERC can be circumvented with fully bSSFP and advanced MRI scan techniques in a major academic cancer center and community hospital, potentially enabling postimplant assessment of MARS LDR prostate brachytherapy without CT.

Development of a Surgical Sponge Counting System Using Radiographic Images.

Background. Retention of surgical sponges in patients is a relatively frequent medical malpractice. To prevent it, the surgical sites are scanned using X-ray. However, using radiography in the operation room induces X-ray exposure for both patients and staff. To prevent such issues, a novel sponge counting system was developed. Each surgical sponge used in common hospitals is composed of single radiopaque fibers. Methods. The proposed system scans surgical sponges to estimate their fiber length (EFL) and returns the number of it. In this study, an optimal image acquisition protocol was determined that allows an accurate count of sponges. X-ray doses and multi-angle image procedures were tested. Results. Measurement trials were performed and compared for both dry and blood-soaked sponges. As a result, the X-ray dose of 50 kV and 600 μA and the acquisition of 180 images per sample yielded an accurate EFL. The 180-image protocol achieved good performance in this study and allowed counting of one package of 10 sponges in 226 seconds. For these settings, a significant correlation was found between the actual number of sponges and the estimated fiber lengths. Additionally, the performance of the system was similar for either dry or blood-soaked items. Conclusion. The proposed system could accurately count surgical sponges and is a promising option in preventing the accidental retention of surgical sponges.

Multiparametric Magnetic Resonance Imaging for the Detection of Clinically Significant Prostate Cancer: What Urologists Need to Know. Part 1: Acquisition.

Acquiring multiparametric magnetic resonance images of the prostate is not a simple "push-button" approach. To show how image acquisition of prostate multiparametric Magnetic Resonance Imaging (mpMRI) can be optimized. Image protocols, magnetic field strength choice, and the use of receiver coils are discussed. In addition, patient preparation and the recognition, prevention, and mitigation of artifacts are evaluated. Based on expert prostate MRI technologists (MRI radiographers) opinion, the optimal protocol is reviewed, and potential artifacts are determined. The entire acquisition process is presented from initial patient preparation until the end of the imaging. The choice of the used equipment, pulse sequences, and prevention of patient- and imaging-related artifacts are presented. This will be shown in individual patients. Although the Prostate Imaging Reporting and Data System guidelines (2012 and 2016) describe minimal and optimal acquisition protocols for prostate mpMRI, these standards are not always met in daily practice. A major challenge in mpMRI is to obtain high image quality and reduce its variability for radiologic interpretations. A summary of evidence and guidelines for the acquisition of mpMRI of the prostate can set a basic guideline to reduce these variabilities. This article and an accompanying video can be used as a guide by MRI technologists (MRI radiographers) to improve their image acquisitions by optimizing protocols, magnetic field strength choice, and use of receiver coils. We also discuss patient preparation and the recognition, prevention, and mitigation of artifacts. In this first surgery-in-motion contribution, we will show how optimized image acquisition is performed to detect prostate cancer. Both MRI-dependent and patient related factors are discussed.

Machine Learning and Deep Neural Networks Applications in Computed Tomography for Coronary Artery Disease and Myocardial Perfusion.

During the latest years, artificial intelligence, and especially machine learning (ML), have experienced a growth in popularity due to their versatility and potential in solving complex problems. In fact, ML allows the efficient handling of big volumes of data, allowing to tackle issues that were unfeasible before, especially with deep learning, which utilizes multilayered neural networks. Cardiac computed tomography (CT) is also experiencing a rise in examination numbers, and ML might help handle the increasing derived information. Moreover, cardiac CT presents some fields wherein ML may be pivotal, such as coronary calcium scoring, CT angiography, and perfusion. In particular, the main applications of ML involve image preprocessing and postprocessing, and the development of risk assessment models based on imaging findings. Concerning image preprocessing, ML can help improve image quality by optimizing acquisition protocols or removing artifacts that may hinder image analysis and interpretation. ML in image postprocessing might help perform automatic segmentations and shorten examination processing times, also providing tools for tissue characterization, especially concerning plaques. The development of risk assessment models from ML using data from cardiac CT could aid in the stratification of patients who undergo cardiac CT in different risk classes and better tailor their treatment to individual conditions. While ML is a powerful tool with great potential, applications in the field of cardiac CT are still expanding, and not yet routinely available in clinical practice due to the need for extensive validation. Nevertheless, ML is expected to have a big impact on cardiac CT in the near future.