Publications by authors named "Hojgaard L"

Aims: Allogeneic stem cell therapy is more logistically suitable compared with autologous cell therapy for large-scale patient treatment. We aim to investigate the clinical safety and efficacy profile of the allogeneic adipose tissue derived mesenchymal stromal cell product (CSCC_ASC) as an add-on therapy in patients with chronic non-ischaemic heart failure with reduced left ventricular ejection fraction (HFrEF) < 40%.

Methods And Results: This is a single-centre investigator-initiated randomized phase I/II study with direct intra-myocardial injections of 100 million allogeneic CSCC_ASC.

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Meta-[I]iodobenzylguanidine ([I]MIBG) scintigraphy with SPECT/CT is the standard of care for diagnosing and monitoring neuroblastoma. Replacing [I]MIBG with the new PET tracer meta-[F]fluorobenzylguanidine ([F]MFBG) and further improving sensitivity and reducing noise in a new long-axial-field-of-view (LAFOV) PET/CT scanner enable increased image quality and a faster acquisition time, allowing examinations to be performed without sedation or general anesthesia (GA). Focusing on feasibility, we present our first experience with [F]MFBG LAFOV PET/CT and compare it with [I]MIBG scintigraphy plus SPECT/CT for imaging in neuroblastoma in children.

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Incorrect scatter scaling of positron emission tomography (PET) images can lead to halo artifacts, quantitative bias, or reconstruction failure. Tail-fitted scatter scaling (TFSS) possesses performance limitations in multiple cases. This study aims to investigate a novel method for scatter scaling: maximum-likelihood scatter scaling (MLSS) in scenarios where TFSS tends to induce artifacts or are observed to cause reconstruction abortion.

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We performed a systematic evaluation of the diagnostic performance of LAFOV PET/CT with increasing acquisition time. The first 100 oncologic adult patients referred for 3 MBq/kg 2-[18F]fluoro-2-deoxy-D-glucose PET/CT on the Siemens Biograph Vision Quadra were included. A standard imaging protocol of 10 min was used and scans were reconstructed at 30 s, 60 s, 90 s, 180 s, 300 s, and 600 s.

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Introduction: Estimation of brain amyloid accumulation is valuable for evaluation of patients with cognitive impairment in both research and clinical routine. The development of high throughput and accurate strategies for the determination of amyloid status could be an important tool in patient selection for clinical trials and amyloid directed treatment. Here, we propose the use of deep learning to quantify amyloid accumulation using standardized uptake value ratio (SUVR) and classify amyloid status based on their PET images.

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Introduction: Patients with MS are MRI scanned continuously throughout their disease course resulting in a large manual workload for radiologists which includes lesion detection and size estimation. Though many models for automatic lesion segmentation have been published, few are used broadly in clinic today, as there is a lack of testing on clinical datasets. By collecting a large, heterogeneous training dataset directly from our MS clinic we aim to present a model which is robust to different scanner protocols and artefacts and which only uses MRI modalities present in routine clinical examinations.

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Purpose: Conventional magnetic resonance imaging (MRI) can for glioma assessment be supplemented by positron emission tomography (PET) imaging with radiolabeled amino acids such as O-(2-[F]fluoroethyl)-L-tyrosine ([F]FET), which provides additional information on metabolic properties. In neuro-oncology, patients often undergo brain and skull altering treatment, which is known to challenge MRI-based attenuation correction (MR-AC) methods and thereby impact the simplified semi-quantitative measures such as tumor-to-brain ratio (TBR) used in clinical routine. The aim of the present study was to examine the applicability of our deep learning method, DeepDixon, for MR-AC in [F]FET PET/MRI scans of a post-surgery glioma cohort with metal implants.

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Aims: The aim of the SCIENCE trial was to investigate whether a single treatment with direct intramyocardial injections of adipose tissue-derived mesenchymal stromal cells (CSCC_ASCs) was safe and improved cardiac function in patients with chronic ischaemic heart failure with reduced ejection fraction (HFrEF).

Methods And Results: The study was a European multicentre, double-blind, placebo-controlled phase II trial using allogeneic CSCC_ASCs from healthy donors or placebo (2:1 randomization). Main inclusion criteria were New York Heart Association (NYHA) class II-III, left ventricular ejection fraction (LVEF) <45%, and N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels >300 pg/ml.

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Aims: Patients suffering from chronic ischaemic heart failure with reduced left ventricular ejection fraction (HFrEF) have reduced quality-of-life, repetitive hospital admissions, and reduced life expectancy. Allogeneic cell therapy is currently investigated as a potential treatment option after initially encouraging results from clinical autologous and allogeneic trials in patients with HFrEF. We aimed to investigate the allogeneic Cardiology Stem Cell Centre Adipose tissue derived mesenchymal Stromal Cell product (CSCC_ASC) as an add-on therapy in patients with chronic HFrEF.

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Article Synopsis
  • The ongoing war in Ukraine may lead to an increase in tuberculosis (TB) cases in Western Europe, making the choice of diagnostic imaging protocols for children crucial.
  • A research review analyzed studies from 1972 to 2022 that compared various imaging techniques (like chest X-Ray, CT, MRI, and ultrasound) in diagnosing pulmonary TB in children aged 0-18 years.
  • Results indicated that CT scans are more effective than chest X-Rays in detecting TB, with CT confirming the diagnosis in nearly all cases studied, while MRI also showed higher detection rates than CXR.
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The expeditious progress of Mesenchymal Stromal Cells (MSC) for therapeutic intervention calls for means to compare differences in potency of cell products. The differences may be attributed to innumerable sources including tissue origin, production methods, or even between batches. While the immunomodulatory potential of MSC is recognized and well-documented by an expansive body of evidence, the methodologies and findings vary markedly.

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Purpose: Brain 2-Deoxy-2-[F]fluoroglucose ([F]FDG-PET) is widely used in the diagnostic workup of Alzheimer's disease (AD). Current tools for uptake analysis rely on non-personalized templates, which poses a challenge as decreased glucose uptake could reflect neuronal dysfunction, or heterogeneous brain morphology associated with normal aging. Overcoming this, we propose a deep learning method for synthesizing a personalized [F]FDG-PET baseline from the patient's own MRI, and showcase its applicability in detecting AD pathology.

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Introduction: Brain and central nervous system (CNS) tumors are the second most common cancer type in children and adolescents. Positron emission tomography (PET) imaging with radiolabeled amino acids visualizes the amino acid uptake in brain tumor cells compared with the healthy brain tissue, which provides additional information over magnetic resonance imaging (MRI) for differential diagnosis, treatment planning, and the differentiation of tumor relapse from treatment-related changes. However, tumor delineation is a time-consuming task subject to inter-rater variability.

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The emerging field of advanced therapy medicinal products (ATMP) holds promise of treating a variety of diseases. Adipose-derived stromal cells (ASCs) are currently being marketed or tested as cell-based therapies in numerous clinical trials. To ensure safety and efficacy of treatments, high-quality products must be manufactured.

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Purpose: Positron Emission Tomography (PET) can support a diagnosis of neurodegenerative disorder by identifying disease-specific pathologies. Our aim was to investigate the feasibility of using activity reduction in clinical [F]FE-PE2I and [C]PiB PET/CT scans, simulating low injected activity or scanning time reduction, in combination with AI-assisted denoising.

Methods: A total of 162 patients with clinically uncertain Alzheimer's disease underwent amyloid [C]PiB PET/CT and 509 patients referred for clinically uncertain Parkinson's disease underwent dopamine transporter (DAT) [F]FE-PE2I PET/CT.

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Background: Adipose-derived stromal cells (ASCs) possess a multitude of regenerative capabilities, which include immunomodulation, angiogenesis, and stimulation of extracellular matrix (ECM) remodeling. However, the underlying mechanisms leading to ECM remodeling remain largely elusive and highlight the need for functional in vitro models for mode of action studies. Therefore, the purpose of this study was to develop an in vitro co-culture model to investigate the capabilities of ASCs to modulate fibroblasts and ECM.

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Mesenchymal stromal cells have proven capable of improving cardiac pump function in patients with chronic heart failure, yet little is known about their mode of action. The aim of the study was to investigate the short-term effect of cryopreserved allogeneic rat adipose tissue-derived stromal cells (ASC) on cardiac composition, cellular subpopulations, and gene transcription in a rat model of chronic ischemic cardiomyopathy (ICM). Myocardial infarction (MI) was induced by permanent ligation of the left anterior descending coronary artery.

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Purpose: To implement and validate an existing algorithm for automatic delineation of white matter lesions on magnetic resonance imaging (MRI) in patients with multiple sclerosis (MS) on a local single-center dataset.

Methods: We implemented a white matter hyperintensity segmentation model, based on a 2D convolutional neural network, using the conventional T2-weighted fluid attenuated inversion recovery (FLAIR) MRI sequence as input. The model was adapted for delineation of MS lesions by further training on a local dataset of 93 MS patients with a total of 3040 lesions.

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Purpose: To compare prospective motion correction (PMC) and retrospective motion correction (RMC) in Cartesian 3D-encoded MPRAGE scans and to investigate the effects of correction frequency and parallel imaging on the performance of RMC.

Methods: Head motion was estimated using a markerless tracking system and sent to a modified MPRAGE sequence, which can continuously update the imaging FOV to perform PMC. The prospective correction was applied either before each echo train (before-ET) or at every sixth readout within the ET (within-ET).

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Quantitative [O]HO positron emission tomography (PET) is the accepted reference method for regional cerebral blood flow (rCBF) quantification. To perform reliable quantitative [O]HO-PET studies in PET/MRI scanners, MRI-based attenuation-correction (MRAC) is required. Our aim was to compare two MRAC methods (RESOLUTE and DeepUTE) based on ultrashort echo-time with computed tomography-based reference standard AC (CTAC) in dynamic and static [O]HO-PET.

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Purpose: [F]Fluoro-deoxy-glucose positron emission tomography/computed tomography (FDG-PET/CT) is used for response assessment during therapy in Hodgkin lymphoma (HL) and non-Hodgkin lymphoma (NHL). Clinicians report the scans visually using Deauville criteria. Improved performance in modern PET/CT scanners could allow for a reduction in scan time without compromising diagnostic image quality.

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Background: Central nervous system (CNS) tumors cause the highest death rates among childhood cancers, and survivors frequently have severe late effects. Magnetic resonance imaging (MRI) is the imaging modality of choice, but its specificity can be challenged by treatment-induced signal changes. In adults, O-(2-[18F]fluoroethyl)-l-tyrosine ([18F]FET) PET can assist in interpreting MRI findings.

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Introduction: Cardiac [F]FDG-PET is widely used for viability testing in patients with chronic ischemic heart disease. Guidelines recommend injection of 200-350 MBq [F]FDG, however, a reduction of radiation exposure has become increasingly important, but might come at the cost of reduced diagnostic accuracy due to the increased noise in the images. We aimed to explore the use of a common deep learning (DL) network for noise reduction in low-dose PET images, and to validate its accuracy using the clinical quantitative metrics used to determine cardiac viability in patients with ischemic heart disease.

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