Emory University

Objective. Magnetic resonance imaging (MRI) is essential in clinical and research contexts, providing exceptional soft-tissue contrast. However, prolonged acquisition times often lead to patient discomfort and motion artifacts. Diffusion-based deep learning super-resolution (SR) techniques reconstruct high-resolution (HR) images from low-resolution (LR) pairs, but they involve extensive sampling steps, limiting real-time application. To overcome these issues, this study introduces a residual error-shifting mechanism markedly reducing sampling steps while maintaining vital anatomical details, thereby accelerating MRI reconstruction. Approach. We developed Res-SRDiff, a novel diffusion-based SR framework incorporating residual error shifting into the forward diffusion process. This integration aligns the degraded HR and LR distributions, enabling efficient HR image reconstruction. We evaluated Res-SRDiff using ultra-high-field brain T1 MP2RAGE maps and T2-weighted prostate images, benchmarking it against Bicubic, Pix2pix, CycleGAN, SPSR, I²SB, and TM-DDPM methods. Quantitative assessments employed peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), gradient magnitude similarity deviation (GMSD), and learned perceptual image patch similarity. Additionally, we qualitatively and quantitatively assessed the proposed framework’s individual components through an ablation study and conducted a Likert-based image quality evaluation. Main results. Res-SRDiff significantly surpassed most comparison methods regarding PSNR, SSIM, and GMSD for both datasets, with statistically significant improvements ( p-values≪0.05). The model achieved high-fidelity image reconstruction using only four sampling steps, drastically reducing computation time to under one second per slice. In contrast, traditional methods like TM-DDPM and I²SB required approximately 20 and 38 s per slice, respectively. Qualitative analysis showed Res-SRDiff effectively preserved fine anatomical details and lesion morphologies. The Likert study indicated that our method received the highest scores, 4.14±0.77(brain) and 4.80±0.40(prostate). Significance. Res-SRDiff demonstrates efficiency and accuracy, markedly improving computational speed and image quality. Incorporating residual error shifting into diffusion-based SR facilitates rapid, robust HR image reconstruction, enhancing clinical MRI workflow and advancing medical imaging research. Code available at https://github.com/mosaf/Res-SRDiff

Objective To examine variations in patterns of care for retroperitoneal sarcoma (RPS) among sarcoma centres globally, including diagnostic work-up, surgical strategies and (neo)adjuvant therapies. Methods Retrospective analysis for primary RPS, from 19 RPS referral centres worldwide, prospectively collected within the RESAR repository (NCT03838718) between Feb 2017 – July 2022. Centres were categorised high volume (HVC) or low volume (LVC). Comprehensive resection (CR) was defined as en-bloc resection of ipsilateral kidney and colon. Results 1718 primary RPS were included. Preoperative biopsy was utilised frequently (median rate 98%) for solid (non-liposarcoma) RPS. In liposarcoma, the median rate of CR was 64%, with wide variation (IQR 37% [43%-80%], range 0-100%). There was greater variation in CR in liposarcoma in LVC (IQR 39.5% [40.5%-80%]) versus HVC (IQR 9.5% [58.3%-67.8%]). Perioperative chemotherapy was seldom used for liposarcoma (median 0%), with higher rates for leiomyosarcoma (median 10%) with high variation (IQR 26% [2%-28%]). Radiotherapy was used consistently infrequently in leiomyosarcoma (IQR 13% [0%-13%]. There was higher use of radiotherapy in HVC than LVC (median HVC 18.5% vs. LVC 5%). There was a significant decrease in radiotherapy use after the STRASS trial (pre 19% vs. post 14%, P =0.045). Conclusions Low variation was found in pre-operative biopsy of non-liposarcomas, use of chemotherapy in liposarcoma and radiotherapy in leiomyosarcoma, suggesting agreement between centres. There was high variation, suggesting equipoise, in the role of chemotherapy in leiomyosarcoma and the value of CR in liposarcoma. The STRASS study results seem to have been accepted, with a reduction in radiotherapy after its publication.

This international multicenter study seeks to determine the frequency and characteristics of meningitis in myelin oligodendrocyte glycoprotein antibody (MOGAD)–associated disease and highlight its pathology.

Background FGFR alterations are known to be driver alterations in several tumor types. We aimed to assess the efficacy of pemigatinib, an oral FGFR1-3 inhibitor, in patients with metastatic or unresectable colorectal cancer whose tumors harbored FGF/FGFR alterations. Patients and Methods The ACCRU-GI-1701 is a single-arm phase II trial which enrolled patients with previously treated FGF/FGFR-altered metastatic colorectal cancer to receive oral pemigatinib daily in 21-day cycles. The primary endpoint is objective response. Secondary endpoints include clinical benefit, progression-free survival, overall survival, quality of life, and adverse events (AEs). This trial was registered with ClinicalTrials.gov (NCT04096417). Results Of the 14 patients included in the interim analysis, the objective response rate as well as clinical benefit rate were 0%. Given these results, the trial closed to enrollment after stage one due to futility. A total of 42.9% of patients had at least one grade 3 or higher AE, the most common being anemia and fatigue. Conclusion Pemigatinib monotherapy did not lead to objective responses in patients with chemorefractory metastatic colorectal cancer harboring FGF/FGFR alterations, although it was overall relatively well tolerated with no new safety signals. Notably, 93% (n = 13) of patients had only FGF/FGFR mutations and amplifications; one patient had an FGFR3-WHSC1 fusion at a low cfDNA percentage (0.02%).

Background Improvements in outcomes among children and adolescents diagnosed with cancer are attributable to many factors—including clinical trials such as those administered through the Children’s Oncology Group (COG), as well as population-based resources like the National Childhood Cancer Registry (NCCR). The objective of this study was to link COG trial data with the NCCR to evaluate overall enrollment patterns. Methods Data were received from the NCCR and COG, which were linked using an array of variables and then compared to evaluate enrollment patterns in COG studies from 2007-2018. Multivariable logistic regression was used to identify characteristics associated with not being enrolled in a COG study. Results Among 134,696 NCCR cancer patients, 51,062 matched with COG study enrollees. There were several differences in demographic and clinical characteristics between those enrolled and not enrolled in COG studies. Enrollment was higher among children aged 0-4 years compared to adolescents aged 15-19 years (53.7% vs 20.1%). Differences by race/ethnicity were also observed; for example, those who identified as non-Hispanic White were more likely to be enrolled than those who identified as non-Hispanic Asian/Pacific Islander (38.8% vs 32.9%). In a multivariable logistic regression model, several characteristics were significantly associated with not being enrolled in a COG study, including age at diagnosis, year of diagnosis, race/ethnicity, and cancer type. Conclusion Our results suggest that several groups are underrepresented in COG clinical trials. This information can help guide the prioritization of population groups for engagement in future studies.

Background Biomechanical asymmetries after anterior cruciate ligament reconstruction (ACLR) may be amplified and perpetuated by progressing athletes to higher-demand tasks despite impairments in lower-demand tasks. Hypotheses (1) Between-limb asymmetries in limb loading and joint kinetics will be greater during the higher-demand drop jump compared with squatting. (2) Asymmetries in limb loading and joint kinetics during squatting will be associated with asymmetries during drop jump. Study Design Descriptive laboratory study. Level of Evidence Level 4. Methods A total of 22 (11 female) participants after primary ACLR (6.4 ± 0.5 months) performed bilateral squat and drop jump tasks. Vertical ground-reaction force (vGRF), knee and hip extensor net joint moments (NJMs), hip/knee mean NJM ratio, and limb symmetry index (LSI) were calculated during the eccentric phase. Comparisons between limbs and across tasks were analyzed using 2-way repeated measures analyses of variance. Pearson’s correlations assessed associations between vGRF and NJM LSIs, and hip/knee NJM ratios across tasks. Results Mean vGRF LSI and knee NJM LSI were significantly more asymmetric during drop jump compared with squatting (79.7 ± 14.9 vs 90.0 ± 11.0%, P < 0.001 and 55.8 ± 17.6 vs 66.4 ± 25.6%, P = 0.02, respectively). Mean vGRF LSI ( r = 0.58; P = 0.004) and knee NJM LSI ( r = 0.61; P = 0.002) were moderately correlated between tasks. The hip/knee ratio for the ACLR limb correlated strongly between tasks ( r = 0.69; P < 0.001); nonsurgical limb: r = 0.39; P = 0.07). Conclusion Underloading and reduced functional use of the ACLR knee were amplified during the drop jump compared with squatting. Limb mechanics during lower-demand squatting are informative of performance during drop jump. Clinical Relevance Criterion-based rehabilitation guidelines may benefit from requiring symmetry in lower-demand tasks before progressing to higher-level activities to optimize recovery and reduce risk of reinjury.

R-loops, RNA:DNA hybrid structures formed during transcription, have emerged as critical regulators of gene expression and genome stability. Initially considered byproducts of transcription, R-loops are now recognized as key players in various cellular processes, including transcription regulation, chromatin remodeling, and DNA repair. However, abnormal accumulation of R-loops can lead to excessive DNA damage and genomic instability, contributing to the pathogenesis of various diseases. This chapter provides a comprehensive overview of recent advances in R-loop biology, emphasizing their formation, genomic distribution, and intricate interactions with epigenetic modifications. We discuss how R-loops influence chromatin architecture and gene expression and the mechanisms through which they contribute to genomic instability. Furthermore, we examine the involvement of R-loops in the pathogenesis of neurological diseases, including repeat expansion disorders and autism spectrum disorder (ASD). Finally, we discuss potential therapeutic strategies targeting pathological R-loops, emphasizing the need for precise compounds to selectively mitigate R-loop accumulation without causing off-target effects. This chapter aims to provide an updated perspective on R-loop biology and its significance in neurological disorder research.

Primary care researchers and clinicians are facing an ever-growing evidence base, more options to access research evidence, and increasingly limited time. Incorporating search filters into primary care systematic reviews can significantly improve the efficiency and confidence of the search process. Search filters, or hedges, are predeveloped search strategies that combine controlled vocabulary and free text terms using Boolean operators (words like “AND,” “OR”). Search filters help to manage the diverse terminology in the literature, such as the various synonyms for primary care, and can be tailored to the specific needs of the review, whether it aims to be exhaustive or more focussed. Resources such as specialized librarians, databases such as PubMed, and repositories such as the InterTASC Information Specialists Sub-Group provide access to these valuable tools. However, as primary care terminology continues to evolve, regular updates to these filters are necessary to maintain their relevance and effectiveness. This method brief presents search filters and highlights their value for finding research literature in primary care.

Recognizing the interconnectedness between social determinants of health (SDOH) and biological factors associated with cancer, the research community is working to identify and refine biological markers of SDOH that can help us better understand this complex interaction. The National Academies of Science, Engineering, and Medicine convened a workshop with the intent of exploring this interaction and how these factors affect cancer onset and cancer-related health outcomes1. Workshop presentations and discussions provided an overview of biological effectors and SDOH; emerging research in these areas, including the development and validation of biomarkers and strategies to improve the evidence base for monitoring, diagnosing, policy, research, and clinical practice opportunities to improve health and address the impact of SDOH on cancer risk, diagnosis and outcomes.