A 3D Conditional Diffusion Model for Image Quality Transfer -- An Application to Low-Field MRI

Low-field (LF) MRI scanners (<1T) are still prevalent in settings with limited resources or unreliable power supply. However, they often yield images with lower spatial resolution and contrast than high-field (HF) scanners. This quality disparity can result in inaccurate clinician interpretations. Image Quality Transfer (IQT) has been developed to enhance the quality of images by learning a mapping function between low and high-quality images. Existing IQT models often fail to restore high-frequency features, leading to blurry output. In this paper, we propose a 3D conditional diffusion model to improve 3D volumetric data, specifically LF MR images. Additionally, we incorporate a cross-batch mechanism into the self-attention and padding of our network, ensuring broader contextual awareness even under small 3D patches. Experiments on the publicly available Human Connectome Project (HCP) dataset for IQT and brain parcellation demonstrate that our model outperforms existing methods both quantitatively and qualitatively. The code is publicly available at \url{https://github.com/edshkim98/DiffusionIQT}

Radiopaque drug-eluting embolisation beads as fiducial markers for stereotactic liver radiotherapy

OBJECTIVE: To determine the feasibility of using radiopaque (RO) beads as direct tumour surrogates for image-guided radiotherapy (IGRT) in patients with liver tumours after transarterial chemoembolisation (TACE). METHODS: A novel vandetanib-eluting RO bead was delivered via TACE as part of a first-in-human clinical trial in patients with either hepatocellular carcinoma or liver metastases from colorectal cancer. Following TACE, patients underwent simulated radiotherapy imaging with 4-dimensional computed tomography (4D-CT) and cone-beam CT (CBCT) imaging. RO beads were contoured using automated thresholding, and feasibility of matching between the simulated radiotherapy planning dataset (AVE-IP image from 4D data) and CBCT scans assessed. Additional kV, MV, helical CT and CBCT images of RO beads were obtained using an in-house phantom. Stability of RO bead position was assessed by comparing 4D-CT imaging to CT scans taken 6-20 days following TACE. RESULTS: Eight patients were treated and 4D-CT and CBCT images acquired. RO beads were visible on 4D-CT and CBCT images in all cases and matching successfully performed. Differences in centre of mass of RO beads between CBCT and simulated radiotherapy planning scans (AVE-IP dataset) were: 2.0 mm mediolaterally, 1.7 mm anteroposteriorally, 3.5 mm craniocaudally. RO beads in the phantom were visible on all imaging modalities assessed. RO bead position remained stable up to 29 days post-TACE. CONCLUSION: RO beads are visible on IGRT imaging modalities, showing minimal artefact. They can be used for on-set matching with CBCT and remain stable over time. ADVANCES IN KNOWLEDGE: The role of RO beads as fiducial markers for stereotactic liver radiotherapy is feasible and warrants further exploration as a combination therapy approach

Accurate Bayesian segmentation of thalamic nuclei using diffusion MRI and an improved histological atlas

The human thalamus is a highly connected brain structure, which is key for the control of numerous functions and is involved in several neurological disorders. Recently, neuroimaging studies have increasingly focused on the volume and connectivity of the specific nuclei comprising this structure, rather than looking at the thalamus as a whole. However, accurate identification of cytoarchitectonically designed histological nuclei on standard in vivo structural MRI is hampered by the lack of image contrast that can be used to distinguish nuclei from each other and from surrounding white matter tracts. While diffusion MRI may offer such contrast, it has lower resolution and lacks some boundaries visible in structural imaging. In this work, we present a Bayesian segmentation algorithm for the thalamus. This algorithm combines prior information from a probabilistic atlas with likelihood models for both structural and diffusion MRI, allowing segmentation of 25 thalamic labels per hemisphere informed by both modalities. We present an improved probabilistic atlas, incorporating thalamic nuclei identified from histology and 45 white matter tracts surrounding the thalamus identified in ultra-high gradient strength diffusion imaging. We present a family of likelihood models for diffusion tensor imaging, ensuring compatibility with the vast majority of neuroimaging datasets that include diffusion MRI data. The use of these diffusion likelihood models greatly improves identification of nuclear groups versus segmentation based solely on structural MRI. Dice comparison of 5 manually identifiable groups of nuclei to ground truth segmentations show improvements of up to 10 percentage points. Additionally, our chosen model shows a high degree of reliability, with median test-retest Dice scores above 0.85 for four out of five nuclei groups, whilst also offering improved detection of differential thalamic involvement in Alzheimer’s disease (AUROC 81.98%). The probabilistic atlas and segmentation tool will be made publicly available as part of the neuroimaging package FreeSurfer

Accurate Bayesian segmentation of thalamic nuclei using diffusion MRI and an improved histological atlas

Data availability: Data will be made available on request.Supplementary materials are available online at: https://www.sciencedirect.com/science/article/pii/S1053811923002744?via%3Dihub#sec0024 .Research data are available online at: https://www.sciencedirect.com/science/article/pii/S1053811923002744?via%3Dihub#ec-research-data .Copyright © 2023 The Author(s). The human thalamus is a highly connected brain structure, which is key for the control of numerous functions and is involved in several neurological disorders. Recently, neuroimaging studies have increasingly focused on the volume and connectivity of the specific nuclei comprising this structure, rather than looking at the thalamus as a whole. However, accurate identification of cytoarchitectonically designed histological nuclei on standard in vivo structural MRI is hampered by the lack of image contrast that can be used to distinguish nuclei from each other and from surrounding white matter tracts. While diffusion MRI may offer such contrast, it has lower resolution and lacks some boundaries visible in structural imaging. In this work, we present a Bayesian segmentation algorithm for the thalamus. This algorithm combines prior information from a probabilistic atlas with likelihood models for both structural and diffusion MRI, allowing segmentation of 25 thalamic labels per hemisphere informed by both modalities. We present an improved probabilistic atlas, incorporating thalamic nuclei identified from histology and 45 white matter tracts surrounding the thalamus identified in ultra-high gradient strength diffusion imaging. We present a family of likelihood models for diffusion tensor imaging, ensuring compatibility with the vast majority of neuroimaging datasets that include diffusion MRI data. The use of these diffusion likelihood models greatly improves identification of nuclear groups versus segmentation based solely on structural MRI. Dice comparison of 5 manually identifiable groups of nuclei to ground truth segmentations show improvements of up to 10 percentage points. Additionally, our chosen model shows a high degree of reliability, with median test-retest Dice scores above 0.85 for four out of five nuclei groups, whilst also offering improved detection of differential thalamic involvement in Alzheimer’s disease (AUROC 81.98%). The probabilistic atlas and segmentation tool will be made publicly available as part of the neuroimaging package FreeSurfer.This work was primarily funded by Alzheimers Research UK (ARUK-IRG2019A003). PGs work in this area was supported by NIH NIBIB NAC P41EB015902 AYs work in this area was supported by NIH grants R01 EB021265 and R56 MH121426. DCAs work in this area was supported by EPSRC grant EP/R006032/1 and Wellcome Trust award 221915/Z/20/Z. The Dementia Research Centre is supported by Alzheimer’s Research UK, Alzheimer’s Society, Brain Research UK, and The Wolfson Foundation. This work was supported by the National Institute for Health Research (NIHR) Queen Square Dementia Biomedical Research Unit and the University College London Hospitals Biomedical Research Centre, the Leonard Wolfson Experimental Neurology Centre (LWENC) Clinical Research Facility, and the UK Dementia Research Institute, which receives its funding from UK DRI Ltd, funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK. This project has received funding from the European Unions Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 765148, as well as from the National Institutes Of Health under project number R01NS112161. MB is supported by a Fellowship award from the Alzheimers Society, UK (AS-JF-19a-004-517). MBs work was also supported by the UK Dementia Research Institute which receives its funding from DRI Ltd, funded by the UK Medical Research Council, Alzheimers Society and Alzheimers Research UK. JDR is supported by the Miriam Marks Brain Research UK Senior Fellowship and has received funding from an MRC Clinician Scientist Fellowship (MR/M008525/1) and the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH). JEI is supported by the European Research Council (Starting Grant 677697, project BUNGEE-TOOLS) and the NIH (1RF1MH123195-01 and 1R01AG070988-01). The collection and sharing of the ADNI data was funded by the Alzheimer’s Disease Neuroimaging Initiative (National Institutes of Health Grant U01 AG024904) and Department of Defence (W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and the following: Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; F. Hoffmann-La Roche Ltd and affiliated company Genentech, Inc.; GE Healthcare; Innogenetics, N.V.; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. The Canadian Institutes of Health Research is providing funds for ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health. The grantee is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Disease Cooperative Study at the University of California, San Diego. ADNI is disseminated by the Laboratory for Neuro Imaging at the University of Southern California

Resonant nonlinear magneto-optical effects in atoms

In this article, we review the history, current status, physical mechanisms, experimental methods, and applications of nonlinear magneto-optical effects in atomic vapors. We begin by describing the pioneering work of Macaluso and Corbino over a century ago on linear magneto-optical effects (in which the properties of the medium do not depend on the light power) in the vicinity of atomic resonances, and contrast these effects with various nonlinear magneto-optical phenomena that have been studied both theoretically and experimentally since the late 1960s. In recent years, the field of nonlinear magneto-optics has experienced a revival of interest that has led to a number of developments, including the observation of ultra-narrow (1-Hz) magneto-optical resonances, applications in sensitive magnetometry, nonlinear magneto-optical tomography, and the possibility of a search for parity- and time-reversal-invariance violation in atoms.Comment: 51 pages, 23 figures, to appear in Rev. Mod. Phys. in Oct. 2002, Figure added, typos corrected, text edited for clarit

Rho GTPase Cdc42 Is a Direct Interacting Partner of Adenomatous Polyposis Coli Protein and Can Alter Its Cellular Localization

Adenomatous Polyposis Coli (APC) is a tumor suppressor gene product involved in colon cancer. APC is a large multidomain molecule of 2843 amino acid residues and connects cell-cell adhesion, the F-actin/microtubule cytoskeleton and the nucleus. Here we show that Cdc42 interacts directly with the first three armadillo repeats of APC by yeast two-hybrid screens. We confirm the Cdc42-APC interaction using pulldown assays in vitro and FRET assays in vivo. Interestingly, Cdc42 interacts with APC at leading edge sites where F-actin is enriched. In contrast, Cdc42 interacts with the truncated mutant APC1–1638 in cellular puncta associated with the golgi-lysozome pathway in transfected CHO cells. In HCT116 and SW480 cells, Cdc42 induces the relocalization of endogenous APC and the mutant APC1–1338 to the plasma membrane and cellular puncta, respectively. Taken together, these data indicate that the Cdc42-APC interaction induces localization of both APC and mutant APC and may thus play a direct role in the functions of these proteins

Author Correction: Nuclear-mitochondrial DNA segments resemble paternally inherited mitochondrial DNA in humans

An amendment to this paper has been published and can be accessed via a link at the top of the paper

DYNC2H1 hypomorphic or retina-predominant variants cause nonsyndromic retinal degeneration

Purpose: Determining the role of DYNC2H1 variants in nonsyndromic inherited retinal disease (IRD). Methods: Genome and exome sequencing were performed for five unrelated cases of IRD with no identified variant. In vitro assays were developed to validate the variants identified (fibroblast assay, induced pluripotent stem cell [iPSC] derived retinal organoids, and a dynein motility assay). Results: Four novel DYNC2H1 variants (V1, g.103327020_103327021dup; V2, g.103055779A>T; V3, g.103112272C>G; V4, g.103070104A>C) and one previously reported variant (V5, g.103339363T>G) were identified. In proband 1 (V1/V2), V1 was predicted to introduce a premature termination codon (PTC), whereas V2 disrupted the exon 41 splice donor site causing incomplete skipping of exon 41. V1 and V2 impaired dynein-2 motility in vitro and perturbed IFT88 distribution within cilia. V3, homozygous in probands 2–4, is predicted to cause a PTC in a retina-predominant transcript. Analysis of retinal organoids showed that this new transcript expression increased with organoid differentiation. V4, a novel missense variant, was in trans with V5, previously associated with Jeune asphyxiating thoracic dystrophy (JATD). Conclusion: The DYNC2H1 variants discussed herein were either hypomorphic or affecting a retina-predominant transcript and caused nonsyndromic IRD. Dynein variants, specifically DYNC2H1 variants are reported as a cause of non syndromic IRD

Changes in the distribution of red foxes (Vulpes vulpes) in urban areas in Great Britain: findings and limitations of a media-driven nationwide survey

Urbanization is one of the major forms of habitat alteration occurring at the present time. Although this is typically deleterious to biodiversity, some species flourish within these human-modified landscapes, potentially leading to negative and/or positive interactions between people and wildlife. Hence, up-to-date assessment of urban wildlife populations is important for developing appropriate management strategies. Surveying urban wildlife is limited by land partition and private ownership, rendering many common survey techniques difficult. Garnering public involvement is one solution, but this method is constrained by the inherent biases of non-standardised survey effort associated with voluntary participation. We used a television-led media approach to solicit national participation in an online sightings survey to investigate changes in the distribution of urban foxes in Great Britain and to explore relationships between urban features and fox occurrence and sightings density. Our results show that media-based approaches can generate a large national database on the current distribution of a recognisable species. Fox distribution in England and Wales has changed markedly within the last 25 years, with sightings submitted from 91% of urban areas previously predicted to support few or no foxes. Data were highly skewed with 90% of urban areas having &lt;30 fox sightings per 1000 people km-2. The extent of total urban area was the only variable with a significant impact on both fox occurrence and sightings density in urban areas; longitude and percentage of public green urban space were respectively, significantly positively and negatively associated with sightings density only. Latitude, and distance to nearest neighbouring conurbation had no impact on either occurrence or sightings density. Given the limitations associated with this method, further investigations are needed to determine the association between sightings density and actual fox density, and variability of fox density within and between urban areas in Britain

On the Front Line of Community-Led Air Quality Monitoring

In this chapter, we explore the potential of community-led air quality monitoring. Community-led air quality monitoring differs from top-down monitoring in many aspects: it is focused on community needs and interests and a local problem and, therefore, has a limited geographical coverage as well as limited temporal coverage. However, localised air quality monitoring can potentially increase the spatial and temporal resolution of air quality information if there is a suitable information-sharing mechanism in place: information from multiple community-led activities can be shared at the city scale and used to augment official information. At the core of the chapter, we provide a detailed experiential description of the process of urban air quality practice, from which we draw our conclusion. We suggest that accessible and reliable community-led air quality monitoring can contribute to the understanding of local environmental issues and improve the dialogue between local authorities and communities about the impacts of air pollution on health and urban and transport planning. Document type: Part of book or chapter of boo