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A precise radiotherapy plan is crucial to ensure accurate segmentation of glioblastomas (GBMs) for radiation therapy. However, the traditional manual segmentation process is labor-intensive and heavily reliant on the experience of radiation oncologists. In this retrospective study, a novel auto-segmentation method is proposed to address these problems. To assess the method's applicability across diverse scenarios, we conducted its development and evaluation using a cohort of 148 eligible patients drawn from four multicenter datasets and retrospective data collection including noncontrast CT, multisequence MRI scans, and corresponding medical records. All patients were diagnosed with histologically confirmed high-grade glioma (HGG). A deep learning-based method (PKMI-Net) for automatically segmenting gross tumor volume (GTV) and clinical target volumes (CTV1 and CTV2) of GBMs was proposed by leveraging prior knowledge from multimodal imaging. The proposed PKMI-Net demonstrated high accuracy in segmenting, respectively, GTV, CTV1, and CTV2 in an 11-patient test set, achieving Dice similarity coefficients (DSC) of 0.94, 0.95, and 0.92; 95% Hausdorff distances (HD95) of 2.07, 1.18, and 3.95 mm; average surface distances (ASD) of 0.69, 0.39, and 1.17 mm; and relative volume differences (RVD) of 5.50%, 9.68%, and 3.97%. Moreover, the vast majority of GTV, CTV1, and CTV2 produced by PKMI-Net are clinically acceptable and require no revision for clinical practice. In our multicenter evaluation, the PKMI-Net exhibited consistent and robust generalizability across the various datasets, demonstrating its effectiveness in automatically segmenting GBMs. The proposed method using prior knowledge in multimodal imaging can improve the contouring accuracy of GBMs, which holds the potential to improve the quality and efficiency of GBMs' radiotherapy.
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INTRODUCTION: The interleukin-23p19 subunit inhibitor, guselkumab, has demonstrated improvements in clinical and patient-reported outcome (PRO) measures in patients with moderate-to-severe psoriasis. Understanding the relationship among clinical response, PRO measures and baseline characteristics could help clinicians individualize treatment plans. The objective of this analysis was to examine changes in signs, symptoms and quality-of-life (QoL) PRO measures in patients who maintained complete skin clearance through ≥ 3 years in the phase 3 VOYAGE 1 trial. METHODS: A descriptive post hoc analysis of data from VOYAGE 1 was conducted to compare baseline characteristics of patients who maintained complete skin clearance (Psoriasis Area and Severity Index [PASI] = 0 for ≥ 156 consecutive weeks) versus patients who did not. Mean scores for individual domains of the Dermatology Life Quality Index (DLQI) and Psoriasis Symptom and Sign Diary (PSSD) were evaluated in patients who maintained complete skin clearance, and baseline characteristics of patients who achieved PRO scores of DLQI = 0/1 and PSSD = 0 were compared with those who did not. RESULTS: Of the 329 patients included in this post hoc analysis, 73 (22.2%) maintained PASI = 0 for ≥ 156 weeks. This group had a numerically lower proportion of patients at baseline with obesity, depression or previous biologic treatment and a higher proportion who had never smoked. Patients who maintained PASI = 0 generally achieved positive DLQI and PSSD outcomes, though some impact of residual disease was observed, largely related to the DLQI "Symptoms and feelings" sub-scale and PSSD components "Dryness," "Redness" and "Itch." Patients reporting continued disease impact (despite sustaining PASI = 0) had greater disease severity at baseline versus those achieving DLQI = 0/1 and PSSD = 0. CONCLUSION: Clinical measures alone do not capture the full patient experience. While both QoL and clinical symptoms are responsive to highly effective treatment, a subset of patients with complete clinical response is still impacted by their psoriasis. Further investigation into this population is warranted. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02207231.
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As the direct microenvironment of assisted reproductive technology, the evaluation of culture medium for human assisted reproduction technology is particularly important. This paper discussed the classification management, technical review points, clinical evaluation and review thinking, focusing on the basic requirements, raw material control, biological evaluation, sterilization process of culture medium for human assisted reproduction technology, combined with some material limit, new added material and quality system control to thoroughly assess management risk of the whole life cycle of culture medium for human assisted reproduction technology.
Subject(s)
Culture Media , Reproductive Techniques, Assisted , Humans , Quality Control , SterilizationABSTRACT
BACKGROUND: Activities of daily living (ADL) are essential for independence and personal well-being, reflecting an individual's functional status. Impairment in executing these tasks can limit autonomy and negatively affect quality of life. The assessment of physical function during ADL is crucial for the prevention and rehabilitation of movement limitations. Still, its traditional evaluation based on subjective observation has limitations in precision and objectivity. OBJECTIVE: The primary objective of this study is to use innovative technology, specifically wearable inertial sensors combined with artificial intelligence techniques, to objectively and accurately evaluate human performance in ADL. It is proposed to overcome the limitations of traditional methods by implementing systems that allow dynamic and noninvasive monitoring of movements during daily activities. The approach seeks to provide an effective tool for the early detection of dysfunctions and the personalization of treatment and rehabilitation plans, thus promoting an improvement in the quality of life of individuals. METHODS: To monitor movements, wearable inertial sensors were developed, which include accelerometers and triaxial gyroscopes. The developed sensors were used to create a proprietary database with 6 movements related to the shoulder and 3 related to the back. We registered 53,165 activity records in the database (consisting of accelerometer and gyroscope measurements), which were reduced to 52,600 after processing to remove null or abnormal values. Finally, 4 deep learning (DL) models were created by combining various processing layers to explore different approaches in ADL recognition. RESULTS: The results revealed high performance of the 4 proposed models, with levels of accuracy, precision, recall, and F1-score ranging between 95% and 97% for all classes and an average loss of 0.10. These results indicate the great capacity of the models to accurately identify a variety of activities, with a good balance between precision and recall. Both the convolutional and bidirectional approaches achieved slightly superior results, although the bidirectional model reached convergence in a smaller number of epochs. CONCLUSIONS: The DL models implemented have demonstrated solid performance, indicating an effective ability to identify and classify various daily activities related to the shoulder and lumbar region. These results were achieved with minimal sensorization-being noninvasive and practically imperceptible to the user-which does not affect their daily routine and promotes acceptance and adherence to continuous monitoring, thus improving the reliability of the data collected. This research has the potential to have a significant impact on the clinical evaluation and rehabilitation of patients with movement limitations, by providing an objective and advanced tool to detect key movement patterns and joint dysfunctions.
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Background: Dega osteotomy is becoming more widely used for the treatment of developmental dysplasia of the hip (DDH). Objective: A thorough description of this procedure is needed as many of the technical aspects are not fully defined. Moreover, more follow-up series are also needed to evaluate its outcomes. Methods: In this study, we gave a detailed anatomic description for this procedure and also presented our experience as a retrospective radiographic and case-note study. We examined the clinical and radiographic records of 44 patients (48 hips) with varying degrees of DDH. Results: The average age of the patients was 2 months and 7 months while the average follow up period was 41 months. Clinical and radiographic assessment including CT with 3D reconstruction to examine the anatomic characteristics of the osteotomy were undertaken. We found that concentric reduction was achieved in 93.7% with excellent clinical and radiographic outcomes. Only 3 cases needed revision of the Dega osteotomy. The re-operation rate was 12.5%. CT scan revealed that the arcuate line was crossed by the osteotomy in the majority of cases. In 20.7% of cases, a bone cut that was intended to be a Dega osteotomy was found to have been inadvertently implemented as another osteotomy variant. However, this bore no significant effect on the outcome. Conclusion: We found that a well-implemented Dega osteotomy is a reliable tool to cope with the acetabular changes in DDH.
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PURPOSE: To investigate the potential of virtual contrast-enhanced MRI (VCE-MRI) for gross-tumor-volume (GTV) delineation of nasopharyngeal carcinoma (NPC) using multi-institutional data. METHODS AND MATERIALS: This study retrospectively retrieved T1-weighted (T1w), T2-weighted (T2w) MRI, gadolinium-based contrast-enhanced MRI (CE-MRI) and planning CT of 348 biopsy-proven NPC patients from three oncology centers. A multimodality-guided synergistic neural network (MMgSN-Net) was trained using 288 patients to leverage complementary features in T1w and T2w MRI for VCE-MRI synthesis, which was independently evaluated using 60 patients. Three board-certified radiation oncologists and two medical physicists participated in clinical evaluations in three aspects: image quality assessment of the synthetic VCE-MRI, VCE-MRI in assisting target volume delineation, and effectiveness of VCE-MRI-based contours in treatment planning. The image quality assessment includes distinguishability between VCE-MRI and CE-MRI, clarity of tumor-to-normal tissue interface and veracity of contrast enhancement in tumor invasion risk areas. Primary tumor delineation and treatment planning were manually performed by radiation oncologists and medical physicists, respectively. RESULTS: The mean accuracy to distinguish VCE-MRI from CE-MRI was 31.67%; no significant difference was observed in the clarity of tumor-to-normal tissue interface between VCE-MRI and CE-MRI; for the veracity of contrast enhancement in tumor invasion risk areas, an accuracy of 85.8% was obtained. The image quality assessment results suggest that the image quality of VCE-MRI is highly similar to real CE-MRI. The mean dosimetric difference of planning target volumes were less than 1Gy. CONCLUSIONS: The VCE-MRI is highly promising to replace the use of gadolinium-based CE-MRI in tumor delineation of NPC patients.
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PURPOSE: Isokinetic knee extensor strength is poorly evaluated in geriatric day hospitals (GDHs), despite its potential functional significance compared to grip strength. This study aimed to investigate age-related effects on absolute and relative isokinetic knee extensor peak torque (KEPT) data in community-dwelling older GDH patients. METHODS: A total of 472 French GDH patients (179 men and 293 women, aged 75-94 years) participated in this study. Absolute and relative KEPT were measured at six distinct angular velocities between 0.52 and 3.14 rad/s. In addition, comfortable gait speed and grip strength were assessed. Participants were stratified by sex and age using 5-year intervals. One-way ANOVAs were used to examine age-related effects on KEPT values. Multiple linear regression models were employed to investigate the associations between gait speed and both mean KEPT values and grip strength, with separate models conducted on absolute and relative values. RESULTS: The recruited GDH patients presented lower absolute and relative KEPT values in comparison with established reference values for healthy community-dwelling older individuals, with men being consistently stronger than women. Notably, there was a significant decline in both absolute and relative KEPT values beyond the age of 85 for both sexes. Importantly, the multiple linear regression analyses conducted revealed a significant positive relationship between gait speed and mean KEPT values, surpassing the association with grip strength. CONCLUSIONS: These findings underscore the clinical importance of assessing isokinetic knee extensor strength in community-dwelling older GDH patients, particularly for tailoring personalized physical activity interventions.
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Despite the importance of communication, radiology departments often depend on communication tools that were not created for the unique needs of imaging workflows, leading to frequent radiologist interruptions. The objective of this study was test the hypothesis that a novel asynchronous communication tool for the imaging workflow (RadConnect) reduces the daily average number of synchronous (in-person, telephone) communication requests for radiologists. We conducted a before-after study. Before adoption of RadConnect, technologists used three conventional communication methods to consult radiologists (in-person, telephone, general-purpose enterprise chat (GPEC)). After adoption, participants used RadConnect as a fourth method. Technologists manually recorded every radiologist consult request related to neuro and thorax CT scans in the 40 days before and 40 days after RadConnect adoption. Telephone traffic volume to section beepers was obtained from the hospital telephone system for the same period. The value and usability experiences were collected through an electronic survey and structured interviews. RadConnect adoption resulted in 53% reduction of synchronous (in-person, telephone) consult requests: from 6.1 ± 4.2 per day to 2.9 ± 2.9 (P < 0.001). There was 77% decrease (P < 0.001) in telephone volume to the neuro and thorax beepers, while no significant volume change was noted to the abdomen beeper (control group). Survey responses (46% response rate) and interviews confirmed the positive impact of RadConnect on interruptions. RadConnect significantly reduced radiologists' telephone interruptions. Study participants valued the role-based interaction and prioritized worklist overview in the survey and interviews. Findings from this study will contribute to a more focused work environment.
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BACKGROUND: For a long time, chronic pruritus was considered difficult to treat. Modern therapy options and detailed guidelines have created new opportunities for patients to improve their quality of life. However, due to the complexity of the disease, the need for multimodal treatment remains. OBJECTIVES: This article aims to investigate whether dermatological rehabilitation offers additional benefits to those affected and whether it should therefore be part of the treatment concept for chronic pruritus. METHODS: After introduction of the pruritus program of a rehabilitation clinic, a prospective study is presented that focuses on the patient-relevant benefits of therapy. It used standardized questionnaires to record pruritus intensity, the presence of depression, anxiety, itch-related limitations, and quality of life in patients with chronic pruritus before and after rehabilitation. RESULTS: Of the patients surveyed, 91.7% achieved a patient-relevant benefit through rehabilitation. Pruritus intensity, depression, anxiety, itch-related limitations, and restrictions on quality of life decreased significantly. Almost half of all participating patients had been initially diagnosed more than 10 years ago. CONCLUSIONS: Dermatological rehabilitation with a multimodal concept for the treatment of chronic pruritus can help affected patients and should be part of the therapy concept. This should be done as early as possible before the disease progresses over a long period of time and makes treatment more difficult.
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Pruritus , Quality of Life , Humans , Pruritus/rehabilitation , Pruritus/psychology , Chronic Disease , Female , Male , Middle Aged , Treatment Outcome , Adult , Aged , Anxiety , Combined Modality Therapy , Depression/rehabilitation , Surveys and QuestionnairesABSTRACT
OBJECTIVES: To investigate the best predictor of muscle strength assessed with both Modified Sphygmomanometer Test (MST) methods (bag adaptation and non-adapted) and to provide normative values for these two MST methods for the strength assessment of the trunk, upper, and lower limb muscles. DESIGN: Cross-sectional study. METHODS: The strength of 42 muscle groups were assessed with the MST in the bag adaptation and non-adapted methods in 120 healthy individuals, 50 % males, divided into three age groups (20-39, 40-59, 60-79) with 40 subjects per group. Stepwise multiple regression analysis was performed to investigate which independent variables (sex, age, and limb dominance) is the best predictor of muscle strength (α = 5 %). RESULTS: Sex was the best independent predictor for all muscle groups for both MST methods (8.8 % < R2<57.8 %, p < 0.0001), except for the ankle plantar flexors assed with the non-adapted sphygmomanometer, in which age was the best independent predictor (R2 = 25.6 %; p < 0.0001). The normative values of muscle strength were reported for both MST methods considering the subgroups (sex, age, and limb dominance). Ceiling effect was observed when the MST bag adaptation was used to assess some muscles (8.8 %). CONCLUSION: Sex was the best predictor of muscle strength, as commonly found for muscle strength assessment with the dynamometer. The normative values provided have high clinical utility and can be used to interpret results of muscle strength assessment using both MST methods. For the MST in the bag adaptation method, caution is advised for the assessment of some muscles.
Subject(s)
Muscle Strength , Sphygmomanometers , Humans , Male , Female , Muscle Strength/physiology , Middle Aged , Cross-Sectional Studies , Adult , Sphygmomanometers/standards , Aged , Young Adult , Age Factors , Muscle, Skeletal/physiology , Sex Factors , Reference ValuesABSTRACT
BACKGROUND AND PURPOSE: Idiopathic normal pressure hydrocephalus (iNPH) is a chronic neurological disease resulting in progressive gait and cognitive disorders. We investigated whether the gait phenotype is associated with the severity of cognitive deficits in iNPH. METHODS: This retrospective study recruited 88 patients (mean age = 76.18 ± 7.21 years, 42% female). Patients were initially referred for suspicion of iNPH and underwent a comprehensive analysis, including gait analysis and cognitive evaluation. RESULTS: In this cohort (27% normal gait, 25% frontal gait, 16% parkinsonian gait, 27% other gait abnormalities), patients with parkinsonian and frontal gait had the lowest Mini-Mental State Examination (MMSE) scores and the slowest gait speed. Patients with normal gait had the highest MMSE scores and gait speed. Frontal gait was associated with lower MMSE score, even after adjusting for age, gender, comorbidities, white matter lesions, and education level (ß = -0.221 [95% confidence interval (CI) = -3.718 to -0.150], p = 0.034). Normal gait was associated with the best MMSE scores, even after adjusting for the abovementioned variables (ß = 0.231 [95% CI = 0.124-3.639], p = 0.036). CONCLUSIONS: Gait phenotypes among iNPH patients are linked to global cognition as assessed with MMSE.
Subject(s)
Cognitive Dysfunction , Gait Disorders, Neurologic , Hydrocephalus, Normal Pressure , Phenotype , Humans , Hydrocephalus, Normal Pressure/complications , Hydrocephalus, Normal Pressure/physiopathology , Female , Male , Aged , Cognitive Dysfunction/etiology , Cognitive Dysfunction/physiopathology , Aged, 80 and over , Retrospective Studies , Gait Disorders, Neurologic/physiopathology , Gait Disorders, Neurologic/etiology , Gait/physiologyABSTRACT
BACKGROUND: As artificial intelligence (AI) increasingly integrates into medical education, its specific impact on the development of clinical skills among pediatric trainees needs detailed investigation. Pediatric training presents unique challenges which AI tools like ChatGPT may be well-suited to address. OBJECTIVE: This study evaluates the effectiveness of ChatGPT-assisted instruction versus traditional teaching methods on pediatric trainees' clinical skills performance. METHODS: A cohort of pediatric trainees (n = 77) was randomly assigned to two groups; one underwent ChatGPT-assisted training, while the other received conventional instruction over a period of two weeks. Performance was assessed using theoretical knowledge exams and Mini-Clinical Evaluation Exercises (Mini-CEX), with particular attention to professional conduct, clinical judgment, patient communication, and overall clinical skills. Trainees' acceptance and satisfaction with the AI-assisted method were evaluated through a structured survey. RESULTS: Both groups performed similarly in theoretical exams, indicating no significant difference (p > 0.05). However, the ChatGPT-assisted group showed a statistically significant improvement in Mini-CEX scores (p < 0.05), particularly in patient communication and clinical judgment. The AI-teaching approach received positive feedback from the majority of trainees, highlighting the perceived benefits in interactive learning and skill acquisition. CONCLUSION: ChatGPT-assisted instruction did not affect theoretical knowledge acquisition but did enhance practical clinical skills among pediatric trainees. The positive reception of the AI-based method suggests that it has the potential to complement and augment traditional training approaches in pediatric education. These promising results warrant further exploration into the broader applications of AI in medical education scenarios.
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Clinical Competence , Pediatrics , Humans , Pediatrics/education , Teaching , Educational Measurement , Artificial Intelligence , Male , Female , Internship and ResidencyABSTRACT
Susceptibility source separation, or χ-separation, estimates diamagnetic (χdia) and paramagnetic susceptibility (χpara) signals in the brain using local field and R2' (= R2* - R2) maps. Recently proposed R2*-based χ-separation methods allow for χ-separation using only multi-echo gradient echo (ME-GRE) data, eliminating the need for additional data acquisition for R2 mapping. Although this approach reduces scan time and enhances clinical utility, the impact of missing R2 information remains a subject of exploration. In this study, we evaluate the viability of two previously proposed R2*-based χ-separation methods as alternatives to their R2'-based counterparts: model-based R2*-χ-separation versus χ-separation and deep learning-based χ-sepnet-R2* versus χ-sepnet-R2'. Their performances are assessed in individuals with multiple sclerosis (MS), comparing them with their corresponding R2'-based counterparts (i.e., R2*-χ-separation vs. χ-separation and χ-sepnet-R2* vs. χ-sepnet-R2'). The evaluations encompass qualitative visual assessments by experienced neuroradiologists and quantitative analyses, including region of interest analyses and linear regression analyses. Qualitatively, R2*-χ-separation tends to report higher χpara and χdia values compared with χ-separation, leading to less distinct lesion contrasts, while χ-sepnet-R2* closely aligns with χ-sepnet-R2'. Quantitative analysis reveals a robust correlation between both R2*-based methods and their R2'-based counterparts (r ≥ 0.88). Specifically, in the whole-brain voxels, χ-sepnet-R2* exhibits higher correlation and better linearity than R2*-χ-separation (χdia/χpara from R2*-χ-separation: r = 0.88/0.90, slope = 0.79/0.86; χdia/χpara from χ-sepnet-R2*: r = 0.90/0.92, slope = 0.99/0.97). In MS lesions, both R2*-based methods display comparable correlation and linearity (χdia/χpara from R2*-χ-separation: r = 0.90/0.91, slope = 0.98/0.91; χdia/χpara from χ-sepnet-R2*: r = 0.88/0.88, slope = 0.91/0.95). Notably, χ-sepnet-R2* demonstrates negligible offsets, whereas R2*-χ-separation exhibits relatively large offsets (0.02 ppm in the whole brain and 0.01 ppm in the MS lesions), potentially indicating the false presence of myelin or iron in MS lesions. Overall, both R2*-based χ-separation methods demonstrated their viability as alternatives to their R2'-based counterparts. χ-sepnet-R2* showed better alignment with its R2'-based counterpart with minimal susceptibility offsets, compared with R2*-χ-separation that reported higher χpara and χdia values compared with R2'-based χ-separation.
Subject(s)
Magnetic Resonance Imaging , Multiple Sclerosis , Humans , Multiple Sclerosis/diagnostic imaging , Multiple Sclerosis/pathology , Female , Male , Adult , Middle Aged , Brain/diagnostic imaging , Brain/pathology , Deep LearningABSTRACT
Objective: The applications of personalized abutments and abutment crown bridge products have increased year by year, but there is no clear requirement for clinical evaluation of the same variety of such products. This study mainly introduces the clinical evaluation concerns of personalized abutments and abutment crown bridge products, in order to provide reference for the declaration and registration of such products. Methods: The clinical evaluation of personalized abutments and crown bridge products are summarized, and the research content of clinical evaluation is clarified. Results: The clinical evaluation requirements that need to be considered by enterprises are introduced. Conclusion: Personalized abutment and abutment crown bridge products can refer to this study when they are launched in China, mainly using in vitro performance comparison tests for equivalence verification.
Subject(s)
Denture, Partial , ChinaABSTRACT
OBJECTIVE: This study aimed to introduce, sensitize, and train our postgraduate students and faculty of the department of general surgery with the use of mini-Clinical Evaluation Exercise (miniCEX) and to assess the perception of students and faculty towards it. MATERIAL AND METHODS: A crosssectional observational study was conducted over a period of four months. Ten surgery residents in the department were asked to volunteer to participate and five professors conducted the session. Five sessions of miniCEX (nine points) were conducted for each resident in different settings of the outpatient department (OPD) and inpatient department (IPD). A total of five skills were tested. Feedback from faculty and residents regarding the perception of miniCEX was also taken. RESULTS: A statistically significant difference in mean scores of all domains was observed comparing the first and last assessment (p<0.05). Hundred percent of the residents scored superior category (7-9) in the final assessment in all domains, whereas the maximum was in a satisfactory scoring grade in 1st assessment. The time taken for the assessment significantly reduced from 1st assessment to the last assessment in OPD and IPD settings (p=0.001). The mini-CEX assessment tool got 100% feedback from faculty in terms of skill improvement, method, attitude of residents, and ability to identify gaps in knowledge. However, one assessor thought that "time given for assessment" was inadequate and more effort was required than the usual traditional assessment methods. The most identified problem faced by residents was that the "time given during assessment" was less (50%); however, overall residents also found it valid, effective, and helpful in identifying knowledge gaps and improving clinical and communication skills. CONCLUSION: MiniCEX improves the learning environment in residency and also leads to improvement in medical interviewing skills, physical examination skills, humanistic qualities/professionalism, and counseling skills. So, it can be used for residency training in clinical departments.
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OBJECTIVE: To prospectively evaluate a deep learning-based denoising reconstruction (DLR) for improved resolution and image quality in musculoskeletal (MSK) magnetic resonance imaging (MRI). METHODS: Images from 137 contrast-weighted sequences in 40 MSK patients were evaluated. Each sequence was performed twice, first with the routine parameters and reconstructed with a routine reconstruction filter (REF), then with higher resolution and reconstructed with DLR, and with three conventional reconstruction filters (NL2, GA43, GA53). The five reconstructions (REF, DLR, NL2, GA43, and GA53) were de-identified, randomized, and blindly reviewed by three MSK radiologists using eight scoring criteria and a forced ranking. Quantitative SNR, CNR, and structure's full width at half maximum (FWHM) for resolution assessment were measured and compared. To account for repeated measures, Generalized Estimating Equations (GEE) with Bonferroni adjustment was used to compare the reader's scores, SNR, CNR, and FWHM between DLR vs. NL2, GA43, GA53, and REF. RESULTS: Compared to the routine REF images, the resolution was improved by 47.61% with DLR from 0.39 ± 0.15 mm2 to 0.20 ± 0.06 mm2 (p < 0.001). Per-sequence average scan time was shortened by 7.93% with DLR from 165.58 ± 21.86 s to 152.45 ± 25.65 s (p < 0.001). Based on the average scores, DLR images were rated significantly higher in all image quality criteria and the forced ranking (p < 0.001). CONCLUSION: This prospective clinical evaluation demonstrated that DLR allows approximately two times finer resolution and improved image quality compared to the standard-of-care images.