Optimal Image Quality Research Articles

Evaluation of multiplexed sensitivity encoding diffusion-weighted imaging in detecting uterine lesions: Image quality optimization

PurposeTo compare the image quality of multiplexed sensitivity-encoding diffusion-weighted imaging (MUSE-DWI) and single-shot echo-planar imaging (SS-EPI-DWI) techniques in uterine MRI. MethodsEighty-eight eligible patients underwent MUSE-DWI and SS-EPI-DWI examinations simultaneously using a 3.0 T MRI system. Two radiologists independently performed quantitative and qualitative analysis of the two groups of images using a double-blind method. The weighted Kappa test was used to evaluate the interobserver agreement. Wilcoxon's rank sum test was used for qualitative parameters, and paired t-test was used for quantitative parameters. Spearman rank correlation analysis was used to obtained correlation between pathological results and mean apparent diffusion coefficient (ADC) value. ResultsThe qualitative and quantitative analysis of the images by the two radiologists were in good or excellent agreement, with weighted kappa value ranging from 0.636 to 0.981. The scores of total subjective image quality (15.4 ± 0.99) and signal-to-noise ratio (158.99 ± 60.71) of MUSE-DWI were significantly higher than those of SS-EPI-DWI (12.93 ± 1.62 P < 0.001; 130.23 ± 48.29 P < 0.05). It effectively reduced image distortion and artifact, and had better lesion conspicuity. There was no significant difference in contrast-to-noise ratio score and average ADC values between the two DWI sequences. The average ADC values of the two DWI sequences were highest in the normal uterus group and lowest in the endometrial cancer group, with statistically significant differences among groups (P < 0.01). In addition, the average ADC values of the two DWI sequences were negatively correlated with the type of lesions, decreasing with the malignancy of the lesions (r = −0.805 P < 0.01, r = −0.815 P < 0.01). ConclusionCompared to SS-EPI-DWI, MUSE-DWI can significantly reduce distortion, artifacts, and fuzziness in MRI of uterine lesions, which is more conducive to lesion detection.

Deep Learning Accelerated Brain Diffusion-Weighted MRI with Super Resolution Processing

ObjectivesTo investigate the clinical feasibility and image quality of accelerated brain diffusion-weighted imaging (DL-DWI) with deep learning image reconstruction and super resolution. MethodsEighty-five consecutive patients with clinically indicated MRI at a 3T scanner were prospectively included. Conventional diffusion-weighted data (c-DWI) with four averages were obtained. Reconstructions of one and two averages, as well as DL-DWI, were accomplished. Three experienced readers evaluated the acquired data using a 5-point Likert scale regarding overall image quality, overall contrast, diagnostic confidence, occurrence of artefacts and evaluation of the central region, basal ganglia, brainstem, and cerebellum. To assess interrater agreement, Fleiss’ kappa (ϰ) was determined. Signal intensity (SI) levels for basal ganglia and the central region were estimated via automated segmentation, and SI values of detected pathologies were measured. ResultsIntracranial pathologies were identified in thirty-five patients. DL-DWI was significantly superior for all defined parameters, independently from applied averages (p-value <0.001). Optimum image quality was achieved with DL-DWI by utilizing a single average (p-value <0.001), demonstrating very good (80.9%) to excellent image quality (14.5%) in nearly all cases, compared to 12.5% with very good and 0% with excellent image quality for c-MRI (p-value <0.001). Comparable results could be shown for diagnostic confidence. Inter-rater Fleiss' Kappa demonstrated moderate to substantial agreement for virtually all defined parameters, with good accordance, particularly for the assessment of pathologies (p=0.74). Regarding SI values, no significant difference was found. ConclusionUltra-fast diffusion-weighted imaging with super resolution is feasible, resulting in highly accelerated brain imaging while increasing diagnostic image quality.

Practical Guide to VI-RADS: MRI Protocols, Lesion Characterization, and Pitfalls.

Urothelial carcinoma is the most common type of bladder cancer (BC), accounting for approximately 90% of all cases. Evaluating the depth of tumor invasion in the bladder wall (tumor staging) is essential for determining the treatment and prognosis in patients with BC. Neoadjuvant therapy followed by radical cystectomy is the most common treatment of localized muscle-invasive BC (MIBC). Therefore, it is vital to differentiate non-MIBC from MIBC. Transurethral resection of bladder tumor (TURBT) is the reference standard to determine the extent of tumor invasion into the bladder wall through tissue sampling. However, this diagnostic and therapeutic method may not adequately sample the muscularis propria, leading to a higher risk of residual disease, early recurrence, and tumor understaging in approximately 50% of patients during the initial TURBT. Multiparametric MRI can overcome some of the limitations of TURBT when evaluating BC, particularly regarding tumor staging. In this context, the Vesical Imaging Reporting and Data System (VI-RADS) classification was developed to establish standards for bladder multiparametric MRI and interpretation. It uses a 5-point scale to assess the likelihood of detrusor muscle invasion. T2-weighted MR images are particularly useful as an initial guide, especially for categories 1-3, while the presence of muscular invasion is determined with diffusion-weighted and dynamic contrast-enhanced sequences. Diffusion-weighted imaging takes precedence as the dominant method when optimal image quality is achieved. The presence of a stalk or a thickened inner layer and no evidence of interruption of the signal intensity of the muscular layer are central for predicting a low likelihood of muscle invasion. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material. See the invited commentary by Hoegger in this issue.

NEMA NU 2-2018 evaluation and image quality optimization of a new generation digital 32-cm axial field-of-view Omni Legend PET-CT using a genetic evolutionary algorithm

A performance evaluation was conducted on the new General Electric (GE) digital Omni Legend PET-CT system with 32 cm extended field of view. The first commercially available clinical digital bismuth germanate system. The system does not use time of flight (ToF). Testing was performed in accordance with the NEMA NU2–2018 standard. A comparison was made between two other commercial GE scanners with extended fields of view; the Discovery MI − 6 ring (ToF enabled) and the Discovery IQ (non-ToF). A genetic evolutionary algorithm was developed to optimize image reconstruction parameters from image quality assessments. The Omni demonstrated average spatial resolutions at 1 cm radial offset as 3.9 mm FWHM. The total system sensitivity at the center was 44.36 cps/kBq. The peak NECR was measured as 501 kcps at 17.8 kBq ml−1 with a 35.48% scatter fraction. The maximum count-rate error below NECR peak was 5.5%. Using standard iterative reconstructions, sphere contrast recovery coefficients were from 52.7 ± 3.2% (10 mm) to 92.5 ± 2.4% (37 mm). The PET-CT co-registration accuracy was 2.4 mm. In place of ToF, the Omni employs software corrections through a pre-trained neural network (PDL) (trained on non-ToF to ToF) that takes Bayesian penalized likelihood reconstruction (Q.Clear) images as input. The optimum parameters for image reconstruction, determined using the genetic algorithm were a Q.Clear parameter, β, of 350 and a ‘medium’ PDL setting. Using standard iterative reconstructions, the Omni initially showed increased background variability compared to the Discovery MI. With optimized PDL reconstruction parameters selected using the genetic algorithm the performance of the Omni surpassed that of the Discovery MI on all NEMA tests. The genetic algorithm’s demonstrated ability to enhance image quality in PET-CT imaging underscores the importance of algorithm driven optimization and underscores the requirement to validate its use in the clinical setting.

Design of moderator and collimator based on compact D-T neutron source for neutron imaging

ABSTRACT The Compact thermal neutron imaging systems have become an important development trend. Compact thermal neutron imaging systems can use neutron tubes as neutron sources because of their low cost, small size, and portability. In order to achieve optimal imaging quality, the moderator and collimator in a neutron imaging system based on neutron tubes source are designed and simulated using SuperMC. The entrance position of the collimator is determined by analyzing the performance of different materials with their parameter’s optimization. It is suggested that a cylinder-shaped structure made of carbon, hydrogenous materials, and heavy metals can significantly increase the thermal neutron flux at the sample location. Further dimension optimization is carried out to improve the neutron beam collimation performance. A vertically divergent collimator with a divergence angle of 5° and an air gap is selected, along with the addition of a B4C lining material. According to the modelling results, the sample position can be as far away from the neutron source as 77 cm with a neutron source yield of 1.14 × 109 n/s. The collimation ratio is 29, the thermal neutron flux is 1.08 × 103 n/cm2·s, and n/γ is 1.44 × 1012 n/cm2·Sv, which is suitable for thermal neutron radiography.

Use of a Novel Beyeonics One Three-dimensional Head-mounted Digital Visualization Platform in Vitreoretinal surgeries.

Ophthalmic microscopes have been crucial in visualizing surgical fields, but their limitations in enhancing the surgical view through digital image processing have prompted the development of digital surgical microscopes. The Beyeonics One microscope, a novel digital microscope, offers ophthalmic surgeons a 3D visualization platform and an augmented reality (AR) surgical headset, potentially improving surgical decision-making and outcomes. While its initial use has been described in cataract and corneal surgeries, its application in vitreoretinal surgery remains relatively unexplored. In this interventional case series, we collected data from the medical records of patients who underwent vitreoretinal surgery using the Beyeonics One 3D visualization platform at the Tel Aviv Medical Center. A total of 36 eyes from 36 subjects were included. Surgical techniques included retinal detachment surgeries and macular surgeries, performed by experienced surgeons. The surgical visualization was facilitated by the Beyeonics One 3D head-mounted display (HMD) platform. The procedures were uneventful, and none intra- or postoperative complications were reported, and surgeons did not experience any signal delay in the real-time video. The Beyeonics One microscope offers several potential advantages in vitreoretinal surgery, including digital image processing, enhanced depth perception through the 3D HMD platform, and hands-free image control using head gestures. While this study demonstrates the feasibility and safety of the Beyeonics One microscope, addressing limitations related to hazy views and optimizing image quality are crucial for consistent visualization.

Image Guided Intraoperative Radiation Therapy After Surgical Resection of Brain Metastases: A First In-Human Feasibility Report

PurposeA correct placement of the applicator during intraoperative radiotherapy (IORT) for brain metastasis is of paramount importance, in order to deliver a precise and safe treatment. The applicator-to-surface contact assessment cannot be performed under direct observation, as the applicator itself limits the visual range. No image-guided (IG) verification is currently performed intracranially. We hypothesize that IG-IORT would assure a more precise delivery in the target area. We describe our workflow in a first in-human experience. Methods and MaterialsPhantom-based measurements were performed to reach the best cone-beam computed-tomography (CBCT) imaging quality possible. Once defined, a clinical feasibility study was initiated. An in-room CBCT device is used to acquire intraoperative images after placing the applicator. Repositioning the applicator is thereafter discussed with the surgeon, according to the imaging outcomes, if required. ResultsAn optimal image quality was achieved with 120-kV voltage, 20-mA current and a tube current–time product of 150 mAs. An additional 0.51–mSv patient exposure was calculated for the entire procedure. The wide dynamic range (−600 HU to +600 HU) of CBCT and a 27-HU mean CT values difference between brain tissue and spherical applicator allows distinguishing both structures. In this first in-human experience, the applicator was repositioned after evidencing air gaps, assuring full applicator-to-surface contact. ConclusionThis first in-human procedure confirmed the feasibility of kilovoltage IG-IORT in a neurosurgical setting. A prospective study has been initiated and will provide further dosimetric details.

Optimizing image quality and minimizing radiation dose in pediatric abdominal multiphase contrast-enhanced computed tomography: a study on CARE kV and CARE Dose 4D.

Multiphase contrast-enhanced computed tomography (CECT) is a commonly used modality in pediatric computed tomography (CT) scans. However, the purposes and focus of each phase, such as CT angiography (CTA), and parenchymal phase, are different. In routine practice, the same scanning parameters are used for all phases, resulting in unnecessary radiation exposure for children. Accurately and rapidly adjusting the scanning parameters for each phase of CECT is challenging in clinical settings. This retrospective cross-sectional study was designed to investigate the feasibility of using both CARE kV and CARE Dose 4D to reduce the radiation dose while maintaining diagnostic quality in multiphase CECT scans of children. Overall, 57 children (33 males and 24 females) who underwent multiphase abdominal CECT in Xinjiang Hospital of Beijing Children's Hospital with an average age of 6.52±4.30 years (range, 0.1-15 years), were enrolled. The tube voltage was automatically modulated using CARE kV. The tube current was automatically modulated using CARE Dose 4D. Different dose saving optimization indices (DI) were used for the three phases: a DI value of 3 was used for the unenhanced CT phase, a DI value of 12 was used for the CTA phase, and a DI value of 7 was used for the parenchymal phase. The tube voltage and volume CT dose index (CTDIvol) were recorded for each phase. Two reviewers subjectively evaluated the overall image quality and noise level of the three phases using a 5-point Likert scale (1-2 points: unqualified, 3 points: qualified, 4 points: better, 5 points: best). The CT and noise values of the descending aorta, liver, and back muscle were measured objectively. The voltage distribution and the image quality and CTDIvol in each phase were compared. The most selected tube voltage in the unenhanced CT, CTA, and parenchymal phases was 100 kV (49/57, 85.96%), 70 kV (36/57, 63.16%), and 80 kV (32/57, 56.14%), respectively. The differences between the three phases were statistically significant (P<0.001). The CTDIvol values of the three phases were 3.99±1.99, 2.02±1.71, and 3.18±2.10 mGy, respectively, with a significant difference between the three phases (P<0.001). The CTDIvol decreased linearly as the DI value increased. All images met the diagnostic requirements. The overall quality scores for the three phases were 4.24±0.42, 4.41±0.49, and 4.50±0.45, respectively, with no significant linear relationship with the change in the DI. The combined use of CARE Dose 4D and CARE kV could effectively reduce the radiation dose in children during multiphase abdominal CECT without compromising the diagnostic image quality.

PENGGUNAAN WINDOW WIDTH DAN WINDOW LEVEL PADA PEMERIKSAAN COMPUTED TOMOGRAFY SCANNER THORAX DENGAN KLINIS ANEURISMA AORTA DI RUMAH SAKIT AL ISLAM BANDUNG

Setting the parameters of Window Width and Window Level on CT Scan Thorax examination using contrast media can produce a good image of the lungs and aorta. The purpose of this study is to find out the right window setting so as to produce a good image in the case of Aortic Aneurysm. This type of research is descriptive qualitative with a case study approach. &#x0D; The results showed that the effect of window width and Window Level parameter settings on the lung window and mediastinum window provided optimal image quality results of abnormalities in the lungs and surrounding anatomical structures.

Can we optimise image quality of an inherently high contrast clinical x-ray from a simple measurement using a readily available test object?

Can we optimise image quality of an inherently high contrast clinical x-ray from a simple measurement using a readily available test object?

Reproducibility of 3D pH-weighted chemical exchange saturation transfer contrast in the healthy cervical spinal cord.

Spinal cord ischemia and hypoxia can be caused by compression, injury, and vascular alterations. Measuring ischemia and hypoxia directly in the spinal cord noninvasively remains challenging. Ischemia and hypoxia alter tissue pH, providing a physiologic parameter that may be more directly related to tissue viability. Chemical exchange saturation transfer (CEST) is an MRI contrast mechanism that can be made sensitive to pH. More specifically, amine/amide concentration independent detection (AACID) is a recently developed endogenous CEST contrast that has demonstrated sensitivity to intracellular pH at 9.4 T. The goal of this study was to evaluate the reproducibility of AACID CEST measurements at different levels of the healthy cervical spinal cord at 3.0 T incorporating B1 correction. Using a 3.0 T MRI scanner, two 3D CEST scans (saturation pulse train followed by a 3D snapshot gradient-echo readout) were performed on 12 healthy subjects approximately 10 days apart, with the CEST volume centered at the C4 level for all subjects. Scan-rescan reproducibility was evaluated by examining between and within-subject coefficients of variation (CVs) and absolute AACID value differences. The C4 level of the spinal cord demonstrated the lowest within-subject CVs (4.1%-4.3%), between-subject CVs (5.6%-6.3%), and absolute AACID percent difference (5.8-6.1%). The B1 correction scheme significantly improved reproducibility (adjusted p-value = 0.002) compared with the noncorrected data, suggesting that implementing B1 corrections in the spinal cord is beneficial. It was concluded that pH-weighted AACID measurements, incorporating B1-inhomogeneity correction, were reproducible within subjects along the healthy cervical spinal cord and that optimal image quality was achieved at the center of the 3D CEST volume.

Assessing the effect of scanning parameter on the size and density of pulmonary nodules: a phantom study

BackgroundLung cancer remains a leading cause of death among cancer patients. Computed tomography (CT) plays a key role in lung cancer screening. Previous studies have not adequately quantified the effect of scanning protocols on the detected tumor size. The aim of this study was to assess the effect of various CT scanning parameters on tumor size and densitometry based on a phantom study and to investigate the optimal energy and mA image quality for screening assessment.MethodsWe proposed a new model using the LUNGMAN N1 phantom multipurpose anthropomorphic chest phantom (diameters: 8, 10, and 12 mm; CT values: − 100, − 630, and − 800 HU) to evaluate the influence of changes in tube voltage and tube current on the size and density of pulmonary nodules. In the LUNGMAN N1 model, three types of simulated lung nodules representing solid tumors of different sizes were used. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were used to evaluate the image quality of each scanning combination. The consistency between the calculated results based on segmentation from two physicists was evaluated using the interclass correlation coefficient (ICC).ResultsIn terms of nodule size, the longest diameters of ground-glass nodules (GGNs) were closest to the ground truth on the images measured at 100 kVp tube voltage, and the longest diameters of solid nodules were closest to the ground truth on the images measured at 80 kVp tube voltage. In respect to density, the CT values of GGNs and solid nodules were closest to the ground truth when measured at 80 kVp and 100 kVp tube voltage, respectively. The overall agreement demonstrates that the measurements were consistent between the two physicists.ConclusionsOur proposed model demonstrated that a combination of 80 kVp and 140 mA scans was preferred for measuring the size of the solid nodules, and a combination of 100 kVp and 100 mA scans was preferred for measuring the size of the GGNs when performing lung cancer screening. The CT values at 80 kVp and 100 kVp were preferred for the measurement of GGNs and solid nodules, respectively, which were closest to the true CT values of the nodules. Therefore, the combination of scanning parameters should be selected for different types of nodules to obtain more accurate nodal data.

Bayesian calibration of quasi-static field distortions in HARMONI

ABSTRACT The high angular resolution monolithic optical and near-infrared Integral field spectrograph is the first light visible and near-infrared integral field spectrograph for the Extremely Large Telescope. To reach the diffraction limit of the telescope (≈ 10 mas) and maintain an optimal image quality over long exposures, an accurate measurement of geometrical distortions in the instrument’s guide star field is needed. Geometrical distortions affecting the guide stars map directly to pointing errors of the science field. The systematic contribution to the pointing error can be calibrated and removed by a corrective model. In this work, we propose a formulation of the corrective model that aims to calibrate the geometrical field distortions down to a given target residual, as well as reducing the time spent in calibrations. We also propose a calibration procedure that accounts for the uncertainties of the measurement process. We developed a tool named harmoni-pm to simulate the expected pointing error caused by geometrical distortions and validate the effectiveness of the proposed corrective model. We also relied on pseudo Zernike polynomials to formulate the model, and the Bayesian theoretical framework to study the propagation of uncertainties along the calibration process. Compared with the classical calibration algorithm, the Bayesian calibration algorithm was able to reduce the number of calibration points required to reach the same model residual. Additionally, we were able to optimize the hardware of the Geometrical Calibration Unit and reduce the time required to achieve the calibration goal.

Semantic pixel encoding visual secret sharing technique for balancing quality and security in color images

&lt;p&gt;Color images are widely utilized across various domains, encompassing digital media and extending to critical applications in satellite and military arenas. As the significance of these images has grown, the need to protect their content from unauthorized access and potential threats has been underscored. Visual Secret Sharing (VSS) schemes have been proposed as effective mechanisms, with images being encrypted into multiple shares that, individually, offer no discernible information about the original content. Nevertheless, issues such as pixel expansion have been noted in traditional VSS methods, which result in increased complexity and a potential compromise in image quality. Maintaining impeccable image quality is emphasized, mainly since critical application decisions are often based on the clarity and accuracy of image details. The Semantic Pixel Encoding Visual Secret Sharing (SPEVSS) technique is proposed to address these identified challenges. A robust mechanism has been formulated through the integration of semantic pixel encoding with VSS, effectively countering pixel expansion while preserving the fidelity of the original image. As a result of this research, computational complexity has been significantly reduced, decryption methodologies have been made more efficient, and a more robust security framework for colour images has been established. The performance of the proposed SPEVSS shows the reconstructed images show the PSNR of 42 dB has been recorded in images processed, underscoring the method’s capability to balance security and optimal image quality.&lt;/p&gt;

Optimizing Image Quality: Exploring Preprocessing Filtering Methods for Medical Lung CT-Scan Analysis

Optimizing Image Quality: Exploring Preprocessing Filtering Methods for Medical Lung CT-Scan Analysis

Less qualitative multiparametric magnetic resonance imaging in prostate cancer can underestimate extraprostatic extension in higher grade tumors.

Multiparametric magnetic resonance imaging (mpMRI) is increasingly used for risk stratification and preoperative staging of prostate cancer. It remains unclear how Grade Group (GG) interacts with the ability of mpMRI to determine the presence of extraprostatic extension (EPE) on surgical pathology. A retrospective review of a robotic assisted laparoscopic radical prostatectomy (RALP) database from 2016-2020 was performed. Radiology mpMRI reports by multiple attending radiologists and without clear standardization or quality control were retrospectively assessed for EPE findings and compared with surgical pathology reports. The data were stratified by biopsy-based GG and a multivariable cluster analysis was performed to incorporate additional preoperative variables (age at diagnosis, PSA, etc.). Hazard ratios were calculated to determine how mpMRI findings and radiographic EPE relate to positive surgical margins. 289 patients underwent at least one mpMRI prior to RALP. Preoperative mpMRI demonstrated sensitivity of 39.3% and specificity of 88.8% for pathological EPE and had a negative predictive value (NPV) of 49.5%, and positive predictive value (PPV) of 84.0%. Stratification of NPV by GG yielded the following values: GG 1-5 (49.5%), GG 3-5 (40.8%), GG 4-5 (43.4%), and GG 5 (30.4%). Additionally, positive EPE on preoperative mpMRI was associated with a significantly decreased risk of positive surgical margins (RR: 0.655; 95% CI: 0.557-0.771). NPV of prostate mpMRI for EPE may be decreased for higher grade tumors. A detailed reference reading and image quality optimization may improve performance. However, urologists should exercise caution in nerve sparing approaches in these patients.

Adaptive Structure and Texture Similarity Metric for Image Quality Assessment and Optimization

Adaptive Structure and Texture Similarity Metric for Image Quality Assessment and Optimization

Automating quality control in cardiac magnetic resonance: Artificial intelligence for discriminative assessment of planning and motion artifacts and real-time reacquisition guidance

BackgroundAccurate measurements from cardiovascular magnetic resonance (CMR) images require precise positioning of scan planes and elimination of motion artifacts from arrhythmia or breathing. Unidentified or incorrectly managed artifacts degrade image quality, invalidate clinical measurements, and decrease diagnostic confidence. Currently, radiographers must manually inspect each acquired image to confirm diagnostic quality and decide whether reacquisition or a change in sequences is warranted. We aimed to develop artificial intelligence (AI) to provide continuous quality scores across different quality domains, and from these, determine whether cines are clinically adequate, require replanning, or warrant a change in protocol. MethodsA three-dimensional convolutional neural network was trained to predict cine quality graded on a continuous scale by a level 3 CMR expert, focusing separately on planning and motion artifacts. It incorporated four distinct output heads for the assessment of image quality in terms of (a, b, c) 2-, 3- and 4-chamber misplanning, and (d) long- and short-axis arrhythmia/breathing artifact. Backpropagation was selectively performed across these heads based on the labels present for each cine. Each image in the testing set was reported by four level 3 CMR experts, providing a consensus on clinical adequacy. The AI's assessment of image quality and ability to identify images requiring replanning or sequence changes were evaluated with Spearman’s rho and the area under receiver operating characteristic curve (AUROC), respectively. ResultsA total of 1940 cines across 1387 studies were included. On the test set of 383 cines, AI-judged image quality correlated strongly with expert judgment, with Spearman’s rho of 0.84, 0.84, 0.81, and 0.81 for 2-, 3- and 4-chamber planning quality and the extent of arrhythmia or breathing artifacts, respectively. The AI also showed high efficacy in flagging clinically inadequate cines (AUROC 0.88, 0.93, and 0.93 for identifying misplanning of 2-, 3- and 4-chamber cines, and 0.90 for identifying movement artifacts). ConclusionAI can assess distinct domains of CMR cine quality and provide continuous quality scores that correlate closely with a consensus of experts. These ratings could be used to identify cases where reacquisition is warranted and guide corrective actions to optimize image quality, including replanning, prospective gating, or real-time imaging.

Long Term Visual Outcomes of an Extended Macular Vision IOL in Eyes with Macular Disease and Visually Insignificant Cataract.

To determine long-term efficacy and safety of an extended macular vision intraocular lens (IOL) implanted in patients with dry age-related macular degeneration (AMD) and visually insignificant cataracts. Retrospective observational case series. MicroChirurgia Oculare, Italy. A retrospective case series of patients with dry AMD and visually insignificant cataracts undergoing phacoemulsification and implantation of an extended macular vision IOL designed to optimize image quality up to 10° from the foveal center (EyeMax Mono, Sharpview Ophthalmology, London, UK). Criteria for implantation were visually insignificant cataract (NC1 according to LOCS III classification) with dry age-related macular degeneration. Hypermetropia was targeted in most eyes to provide magnification when corrected with spectacles. Primary outcome measures were changes in corrected distant and secondary outcome measures included near visual acuity (CDVA and CNVA, respectively) between baseline and latest follow-up and safety outcomes. 113 eyes of 86 patients (mean age 70.3±7.9 years) were included (mean follow-up: 48.3±25.1 months). Mean CDVA improved by 0.22 logMAR (11 ETDRS letters), from 0.53±0.4 to 0.31±0.3 (n=113, p<0.001). Similarly, mean CNVA improved by 0.08 logMAR (4 ETDRS letters), from 0.45±0.2 to 0.37±0.2 (n=77, p<0.001). Eleven eyes had AMD with extensive atrophy, and their mean CDVA improved by 0.32 logMAR (16 ETDRS letters). Three eyes (2.7%) experienced loss of more than one line in logMAR CDVA and four eyes (5.2%) experienced loss of more than one line in logMAR CNVA. No complications or instances of IOL exchange were reported. Visual improvement in eyes with visually insignificant cataract and AMD who underwent phacoemulsification and were implanted with EyeMax Mono IOL appears to be influenced by the IOL optical design. Vision enhancement in eyes with visually insignificant cataracts underscores the IOL's ability to optimize use of healthy retinal areas. Prospective studies with control groups are needed to confirm these findings.

Applications, limitations and advancements of ultra-low-field magnetic resonance imaging: A scoping review.

Ultra-low-field magnetic resonance imaging (ULF-MRI) has emerged as an alternative with several portable clinical applications. This review aims to comprehensively explore its applications, potential limitations, technological advancements, and expert recommendations. A review of the literature was conducted across medical databases to identify relevant studies. Articles on clinical usage of ULF-MRI were included, and data regarding applications, limitations, and advancements were extracted. A total of 25 articles were included for qualitative analysis. The review reveals ULF-MRI efficacy in intensive care settings and intraoperatively. Technological strides are evident through innovative reconstruction techniques and integration with machine learning approaches. Additional advantages include features such as portability, cost-effectiveness, reduced power requirements, and improved patient comfort. However, alongside these strengths, certain limitations of ULF-MRI were identified, including low signal-to-noise ratio, limited resolution and length of scanning sequences, as well as variety and absence of regulatory-approved contrast-enhanced imaging. Recommendations from experts emphasize optimizing imaging quality, including addressing signal-to-noise ratio (SNR) and resolution, decreasing the length of scan time, and expanding point-of-care magnetic resonance imaging availability. This review summarizes the potential of ULF-MRI. The technology's adaptability in intensive care unit settings and its diverse clinical and surgical applications, while accounting for SNR and resolution limitations, highlight its significance, especially in resource-limited settings. Technological advancements, alongside expert recommendations, pave the way for refining and expanding ULF-MRI's utility. However, adequate training is crucial for widespread utilization.