Publications by authors named "Leonie Beyer"

Background/objectives: Peptide Receptor Radionuclide Therapy (PRRT) is approved for patients with inoperable, progressive and/or metastatic well-differentiated NETs. Before the approval of Lutathera, locally manufactured Lu-HA-DOTATATE was used on a regular basis in clinical routine. The aim of this study was (1) to compare the hematotoxicity of locally manufactured Lu-HA-DOTATATE with Lutathera in GEP-NET patients and (2) to compare the recommended treatment interval of 8 weeks between each cycle to a prolonged scheme of up to 11 weeks for both Lu-HA-DOTATATE and Lutathera.

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Objectives: Partial volume effects in positron emission tomography occur frequently in neurodegenerative diseases due to increasing cortical atrophy during the disease course, and fronto-temporal dementia is often characterized by severe atrophy. The aim of this study was to challenge partial volume effect correction (PVEC) in patients with nonfluent-agrammatic variant primary progressive aphasia (nfv-PPA) imaged with [F]-THK-5351 PET a marker of reactive neuroinflammatory astrogliosis as well as tau-binding.

Methods: Patients with nfv-PPA (n = 20) were imaged with [F]-THK-5351 PET accompanied by structural magnetic resonance tomography imaging (MRI).

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Tau PET has attracted increasing interest as an imaging biomarker for 4-repeat (4R)-tauopathy progressive supranuclear palsy (PSP). However, the translation of in vitro 4R-tau binding to in vivo tau PET signals is still unclear. Therefore, we performed a translational study using a broad spectrum of advanced methodologies to investigate the sources of [F]PI-2620 tau PET signals in individuals with 4R-tauopathies, including a pilot PET autopsy study in patients.

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Background: Microglial activation is one hallmark of Alzheimer disease (AD) neuropathology but the impact of the regional interplay of microglia cells in the brain is poorly understood. We hypothesized that microglial activation is regionally synchronized in the healthy brain but experiences regional desynchronization with ongoing neurodegenerative disease. We addressed the existence of a microglia connectome and investigated microglial desynchronization as an AD biomarker.

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Aim: β-amyloid (Aβ) small animal PET facilitates quantification of fibrillar amyloidosis in Alzheimer's disease (AD) mouse models. Thus, the methodology is receiving growing interest as a monitoring tool in preclinical drug trials. In this regard, harmonization of data from different scanners at multiple sites would allow the establishment large collaborative cohorts and may facilitate efficacy comparison of different treatments.

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Purpose: We hypothesized that severe tau burden in brain regions involved in direct or indirect pathways of the basal ganglia correlate with more severe striatal dopamine deficiency in four-repeat (4R) tauopathies. Therefore, we correlated [F]PI-2620 tau-positron-emission-tomography (PET) imaging with [I]-Ioflupane single-photon-emission-computed tomography (SPECT) for dopamine transporter (DaT) availability.

Methods: Thirty-eight patients with clinically diagnosed 4R-tauopathies (21 male; 69.

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Among functional imaging methods, metabolic connectivity (MC) is increasingly used for investigation of regional network changes to examine the pathophysiology of neurodegenerative diseases such as Alzheimer's disease (AD) or movement disorders. Hitherto, MC was mostly used in clinical studies, but only a few studies demonstrated the usefulness of MC in the rodent brain. The goal of the current work was to analyze and validate metabolic regional network alterations in three different mouse models of neurodegenerative diseases (β-amyloid and tau) by use of 2-deoxy-2-[F]fluoro-d-glucose positron emission tomography (FDG-PET) imaging.

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Fluorine-18 (F) is undoubtedly one of the most frequently applied radionuclides for the development of new radiotracers for positron emission tomography (PET) in the context of clinical cancer, neurological, and metabolic imaging. Until recently, the available radiochemical methodologies to introduce F into organic molecules ranging from small- to medium- and large-sized compounds were limited to a few applicable protocols. With the advent of late-stage fluorination of small aromatic, nonactivated compounds and various noncanonical labeling strategies geared toward the labeling of peptides and proteins, the molecular toolbox for PET radiotracer development was substantially extended.

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Purpose: Metabolic network analysis of FDG-PET utilizes an index of inter-regional correlation of resting state glucose metabolism and has been proven to provide complementary information regarding the disease process in parkinsonian syndromes. The goals of this study were (i) to evaluate pattern similarities of glucose metabolism and network connectivity in dementia with Lewy bodies (DLB) subjects with subthreshold dopaminergic loss compared to advanced disease stages and to (ii) investigate metabolic network alterations of FDG-PET for discrimination of patients with early DLB from other neurodegenerative disorders (Alzheimer's disease, Parkinson's disease, multiple system atrophy) at individual patient level via principal component analysis (PCA).

Methods: FDG-PETs of subjects with probable or possible DLB (n = 22) without significant dopamine deficiency (z-score < 2 in putamen binding loss on DaT-SPECT compared to healthy controls (HC)) were scaled by global-mean, prior to volume-of-interest-based analyses of relative glucose metabolism.

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Article Synopsis
  • AI is becoming crucial in medical imaging, especially in oncology, by improving lesion detection, therapy monitoring, and recurrence identification.
  • The review highlights current AI research in hybrid imaging, discusses challenges, and examines applications in oncology along with their limitations.
  • Despite the potential for enhancing diagnostic efficiency and quality, there are significant hurdles in developing, benchmarking, and implementing these AI applications in clinical settings.
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β-amyloid (Aβ) and tau aggregation as well as neuronal injury and atrophy (ATN) are the major hallmarks of Alzheimer's disease (AD), and biomarkers for these hallmarks have been linked to neuroinflammation. However, the detailed regional associations of these biomarkers with microglial activation in individual patients remain to be elucidated. We investigated a cohort of 55 patients with AD and primary tauopathies and 10 healthy controls that underwent TSPO-, Aβ-, tau-, and perfusion-surrogate-PET, as well as structural MRI.

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Background: Somatostatin-receptor (SSTR)-targeted PET/CT provides important clinical information in addition to standard imaging in meningioma patients. [F]SiTATE is a novel, F-labeled SSTR-targeting peptide with superior imaging properties according to preliminary data. We provide the first [F]SiTATE PET/CT data of a large cohort of meningioma patients.

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Background: The aim of this retrospective study was to compare the diagnostic accuracy of somatostatin receptor (SSR)-PET/CT to liver MRI as reference standard in the evaluation of hepatic involvement in neuroendocrine tumors (NET).

Methods: An institutional database was screened for "SSR" imaging studies between 2006 and 2021. 1000 NET Patients (grade 1/2) with 2383 SSR-PET/CT studies and matching liver MRI in an interval of +3 months were identified.

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Objectives: The recently proposed standardized reporting and data system for somatostatin receptor (SSTR)-targeted PET/CT SSTR-RADS 1.0 showed promising first results in the assessment of diagnosis and treatment planning with peptide receptor radionuclide therapy (PRRT) in neuroendocrine tumors (NET). This study aimed to determine the intra- and interreader agreement of SSTR-RADS 1.

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Objectives: Reactive gliosis is a common pathological hallmark of CNS pathology resulting from neurodegeneration and neuroinflammation. In this study we investigate the capability of a novel monoamine oxidase B (MAO-B) PET ligand to monitor reactive astrogliosis in a transgenic mouse model of Alzheimer`s disease (AD). Furthermore, we performed a pilot study in patients with a range of neurodegenerative and neuroinflammatory conditions.

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Aim: We aimed to investigate the impact of microglial activity and microglial FDG uptake on metabolic connectivity, since microglial activation states determine FDG-PET alterations. Metabolic connectivity refers to a concept of interacting metabolic brain regions and receives growing interest in approaching complex cerebral metabolic networks in neurodegenerative diseases. However, underlying sources of metabolic connectivity remain to be elucidated.

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Purpose: Somatostatin analogues (SSA) are frequently used in the treatment of neuroendocrine tumours. Recently, [F]SiTATE entered the field of somatostatin receptor (SSR) positron emission tomography (PET)/computed tomography (CT) imaging. The purpose of this study was to compare the SSR-expression of differentiated gastroentero-pancreatic neuroendocrine tumours (GEP-NET) measured by [18F]SiTATE-PET/CT in patients with and without previous treatment with long-acting SSAs to evaluate if SSA treatment needs to be paused prior to [18F]SiTATE-PET/CT.

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Background: Lu-PSMA therapy has been successfully used to prolong the survival of patients with metastatic castration-resistant prostate cancer. Patient-specific dosimetry based on serial quantitative SPECT/CT imaging can support the understanding of dose-effect relationships. However, multiple SPECT/CT measurements can be challenging for patients, which motivates the investigation of efficient sampling schedules and their impact on dosimetry.

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Article Synopsis
  • - Salvage elective nodal radiotherapy (ENRT) is used for prostate cancer patients with lymph node metastases post-prostatectomy, and this study evaluated various treatment templates for their effectiveness in covering affected lymph nodes.
  • - The research examined PSMA PET/CT scans from 105 patients, identifying and categorizing 335 lymph nodes, focusing on comparing the coverage efficacy of three templates: NRG, RTOG, and PIVOTAL.
  • - Results indicated that the NRG template had the lowest average missed lymph nodes compared to RTOG and PIVOTAL, although it still missed about one-third of lymph nodes and provided complete coverage for just under half of the patients, emphasizing the need for advanced imaging in
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Background: Metastatic castration-resistant prostate cancer poses a therapeutic challenge with poor prognosis. The VISION trial showed prolonged progression-free and overall survival in patients treated with lutetium Lu 177 vipivotide tetraxetan (177Lu-PSMA-617) radioligand therapy compared with using the standard of care (SoC) alone. The objective of this study was to determine the cost-effectiveness of 177Lu-PSMA-617 treatment compared with SoC therapy.

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Purpose: Quantitative SPECT for patient-specific dosimetry is a valuable tool in the scope of radionuclide therapy, although its clinical application for Ac-based treatments may be limited due to low therapeutic activities. Therefore, the aim of this study was to demonstrate the feasibility of clinical quantitative low-count SPECT imaging during [Lu]Lu-PSMA-I&T/[Ac]Ac-PSMA-I&T treatment.

Methods: Eight prostate cancer patients (1000 MBq/8 MBq [Lu]Lu-PSMA-I&T/[Ac]Ac-PSMA-I&T) received a single-bed quantitative Lu/Ac SPECT/CT acquisition (1 h) at 24 h post treatment (high-energy collimator, 16 projections p.

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Purpose: Characteristic features of amyloid-PET (A), tau-PET (T), and FDG-PET (N) can serve for the A/T/N classification of neurodegenerative diseases. Recent studies showed that the early, perfusion-weighted phases of amyloid- or tau-PET recordings serve to detect cerebrometabolic deficits equally to FDG-PET, therefore providing a surrogate of neuronal injury. As such, two channels of diagnostic information can be obtained in the setting of a single PET scan.

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Background: Artificial intelligence (AI) applications have become increasingly relevant across a broad spectrum of settings in medical imaging. Due to the large amount of imaging data that is generated in oncological hybrid imaging, AI applications are desirable for lesion detection and characterization in primary staging, therapy monitoring, and recurrence detection. Given the rapid developments in machine learning (ML) and deep learning (DL) methods, the role of AI will have significant impact on the imaging workflow and will eventually improve clinical decision making and outcomes.

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