A prospective study of HER3 expression pre and post neoadjuvant therapy of different breast cancer subtypes: implications for HER3 imaging therapy guidance.

PURPOSE: HER3, a member of the EGFR receptor family, plays a central role in driving oncogenic cell proliferation in breast cancer. Novel HER3 therapeutics are showing promising results while recently developed HER3 PET imaging modalities aid in predicting and assessing early treatment response. However, baseline HER3 expression, as well as changes in expression while on neoadjuvant therapy, have not been well-characterized. We conducted a prospective clinical study, pre- and post-neoadjuvant/systemic therapy, in patients with newly diagnosed breast cancer to determine HER3 expression, and to identify possible resistance mechanisms maintained through the HER3 receptor. EXPERIMENTAL DESIGN: The study was conducted between May 25, 2018 and October 12, 2019. Thirty-four patients with newly diagnosed breast cancer of any subtype (ER ± , PR ± , HER2 ±) were enrolled in the study. Two core biopsy specimens were obtained from each patient at the time of diagnosis. Four patients underwent a second research biopsy following initiation of neoadjuvant/systemic therapy or systemic therapy which we define as neoadjuvant therapy. Molecular characterization of HER3 and downstream signaling nodes of the PI3K/AKT and MAPK pathways pre- and post-initiation of therapy was performed. Transcriptional validation of finings was performed in an external dataset (GSE122630). RESULTS: Variable baseline HER3 expression was found in newly diagnosed breast cancer and correlated positively with pAKT across subtypes (r = 0.45). In patients receiving neoadjuvant/systemic therapy, changes in HER3 expression were variable. In a hormone receptor-positive (ER +/PR +/HER2-) patient, there was a statistically significant increase in HER3 expression post neoadjuvant therapy, while there was no significant change in HER3 expression in a ER +/PR +/HER2+ patient. However, both of these patients showed increased downstream signaling in the PI3K/AKT pathway. One subject with ER +/PR -/HER2- breast cancer and another subject with ER +/PR +/HER2 + breast cancer showed decreased HER3 expression. Transcriptomic findings, revealed an immune suppressive environment in patients with decreased HER3 expression post therapy. CONCLUSION: This study demonstrates variable HER3 expression across breast cancer subtypes. HER3 expression can be assessed early, post-neoadjuvant therapy, providing valuable insight into cancer biology and potentially serving as a prognostic biomarker. Clinical translation of neoadjuvant therapy assessment can be achieved using HER3 PET imaging, offering real-time information on tumor biology and guiding personalized treatment for breast cancer patients.

PSMA-PET follow-up to assess response in patients not receiving PSMA therapy: Is there value beyond localization of disease?

Introduction: Prostate Specific Membrane Antigen Positron Emission Tomography (PSMA-PET) is routinely used for the staging of patients with prostate cancer, but data on response assessment are sparse and primarily stem from metastatic castration-resistant prostate cancer (mCRPC) patients treated with PSMA radioligand therapy. Still, follow-up PSMA-PET is employed in earlier disease stages in case of clinical suspicion of disease persistence, recurrence or progression to decide if localized or systemic treatment is indicated. Therefore, the prognostic value of PSMA-PET derived tumor volumes in earlier disease stages (i.e., hormone-sensitive prostate cancer (HSPC) and non-[177Lu]Lu-PSMA-617 (LuPSMA) therapy castration resistant prostate cancer (CRPC)) are evaluated in this manuscript. Methods: A total number of 73 patients (6 primary staging, 42 HSPC, 25 CRPC) underwent two (i.e., baseline and follow-up, median interval: 379 days) whole-body [68Ga]Ga-PSMA-11 PET/CT scans between Nov 2014 and Dec 2018. Analysis was restricted to non-LuPSMA therapy patients. PSMA-PETs were retrospectively analyzed and primary tumor, lymph node-, visceral-, and bone metastases were segmented. Body weight-adjusted organ-specific and total tumor volumes (PSMAvol: sum of PET volumes of all lesions) were measured for baseline and follow-up. PSMAvol response was calculated as the absolute difference of whole-body tumor volumes. High metastatic burden (>5 metastases), RECIP 1.0 and PSMA-PET Progression Criteria (PPP) were determined. Survival data were sourced from the cancer registry. Results: The average number of tumor lesions per patient on the initial PET examination was 10.3 (SD 28.4). At baseline, PSMAvol was strongly associated with OS (HR 3.92, p <0.001; n = 73). Likewise, response in PSMAvol was significantly associated with OS (HR 10.48, p < 0.005; n = 73). PPP achieved significance as well (HR 2.19, p <0.05, n = 73). Patients with hormone sensitive disease and poor PSMAvol response (upper quartile of PSMAvol change) in follow-up had shorter outcome (p < 0.05; n = 42). PSMAvol in bones was the most relevant parameter for OS prognostication at baseline and for response assessment (HR 31.11 p < 0.001; HR 32.27, p < 0.001; n = 73). Conclusion: PPP and response in PSMAvol were significantly associated with OS in the present heterogeneous cohort. Bone tumor volume was the relevant miTNM region for OS prognostication. Future prospective evaluation of the performance of organ specific PSMAvol in more homogeneous cohorts seems warranted.

Enhancing precision: A predictive model for 177Lu-DOTATATE treatment response in neuroendocrine tumors using quantitative 68Ga-DOTATATE PET and clinicopathological biomarkers.

Purpose: This study aims to elucidate the role of quantitative SSTR-PET metrics and clinicopathological biomarkers in the progression-free survival (PFS) and overall survival (OS) of neuroendocrine tumors (NETs) treated with peptide receptor radionuclide therapy (PRRT). Methods: A retrospective analysis including 91 NET patients (M47/F44; age 66 years, range 34-90 years) who completed four cycles of standard 177Lu-DOTATATE was conducted. SSTR-avid tumors were segmented from pretherapy SSTR-PET images using a semiautomatic workflow with the tumors labeled based on the anatomical regions. Multiple image-based features including total and organ-specific tumor volume and SSTR density along with clinicopathological biomarkers including Ki-67, chromogranin A (CgA) and alkaline phosphatase (ALP) were analyzed with respect to the PRRT response. Results: The median OS was 39.4 months (95% CI: 33.1-NA months), while the median PFS was 23.9 months (95% CI: 19.3-32.4 months). Total SSTR-avid tumor volume (HR = 3.6; P = 0.07) and bone tumor volume (HR = 1.5; P = 0.003) were associated with shorter OS. Also, total tumor volume (HR = 4.3; P = 0.01), liver tumor volume (HR = 1.8; P = 0.05) and bone tumor volume (HR = 1.4; P = 0.01) were associated with shorter PFS. Furthermore, the presence of large lesion volume with low SSTR uptake was correlated with worse OS (HR = 1.4; P = 0.03) and PFS (HR = 1.5; P = 0.003). Among the biomarkers, elevated baseline CgA and ALP showed a negative association with both OS (CgA: HR = 4.9; P = 0.003, ALP: HR = 52.6; P = 0.004) and PFS (CgA: HR = 4.2; P = 0.002, ALP: HR = 9.4; P = 0.06). Similarly, number of prior systemic treatments was associated with shorter OS (HR = 1.4; P = 0.003) and PFS (HR = 1.2; P = 0.05). Additionally, tumors originating from the midgut primary site demonstrated longer PFS, compared to the pancreas (HR = 1.6; P = 0.16), and those categorized as unknown primary (HR = 3.0; P = 0.002). Conclusion: Image-based features such as SSTR-avid tumor volume, bone tumor involvement, and the presence of large tumors with low SSTR expression demonstrated significant predictive value for PFS, suggesting potential clinical utility in NETs management. Moreover, elevated CgA and ALP, along with an increased number of prior systemic treatments, emerged as significant factors associated with worse PRRT outcomes.

Evaluating the immunologically "cold" tumor microenvironment after treatment with immune checkpoint inhibitors utilizing PET imaging of CD4 + and CD8 + T cells in breast cancer mouse models.

BACKGROUND: Immune-positron emission tomography (PET) imaging with tracers that target CD8 and granzyme B has shown promise in predicting the therapeutic response following immune checkpoint blockade (ICB) in immunologically "hot" tumors. However, immune dynamics in the low T-cell infiltrating "cold" tumor immune microenvironment during ICB remain poorly understood. This study uses molecular imaging to evaluate changes in CD4 + T cells and CD8 + T cells during ICB in breast cancer models and examines biomarkers of response. METHODS: [89Zr]Zr-DFO-CD4 and [89Zr]Zr-DFO-CD8 radiotracers were used to quantify changes in intratumoral and splenic CD4 T cells and CD8 T cells in response to ICB treatment in 4T1 and MMTV-HER2 mouse models, which represent immunologically "cold" tumors. A correlation between PET quantification metrics and long-term anti-tumor response was observed. Further biological validation was obtained by autoradiography and immunofluorescence. RESULTS: Following ICB treatment, an increase in the CD8-specific PET signal was observed within 6 days, and an increase in the CD4-specific PET signal was observed within 2 days in tumors that eventually responded to immunotherapy, while no significant differences in CD4 or CD8 were found at the baseline of treatment that differentiated responders from nonresponders. Furthermore, mice whose tumors responded to ICB had a lower CD8 PET signal in the spleen and a higher CD4 PET signal in the spleen compared to non-responders. Intratumoral spatial heterogeneity of the CD8 and CD4-specific PET signals was lower in responders compared to non-responders. Finally, PET imaging, autoradiography, and immunofluorescence signals were correlated when comparing in vivo imaging to ex vivo validations. CONCLUSIONS: CD4- and CD8-specific immuno-PET imaging can be used to characterize the in vivo distribution of CD4 + and CD8 + T cells in response to immune checkpoint blockade. Imaging metrics that describe the overall levels and distribution of CD8 + T cells and CD4 + T cells can provide insight into immunological alterations, predict biomarkers of response to immunotherapy, and guide clinical decision-making in those tumors where the kinetics of the response differ.

Affinity of PET-MRI Tracers for Hypoxic Cells in Breast Cancer: A Systematic Review.

Tumour hypoxia is a known microenvironmental culprit for treatment resistance, tumour recurrence and promotion of metastatic spread. Despite the long-known existence of this factor within the tumour milieu, hypoxia is still one of the greatest challenges in cancer management. The transition from invasive and less reliable detection methods to more accurate and non-invasive ways to identify and quantify hypoxia was a long process that eventually led to the promising results showed by functional imaging techniques. Hybrid imaging, such as PET-CT, has the great advantage of combining the structural or anatomical image (offered by CT) with the functional or metabolic one (offered by PET). However, in the context of hypoxia, it is only the PET image taken after appropriate radiotracer administration that would supply hypoxia-specific information. To overcome this limitation, the development of the latest hybrid imaging systems, such as PET-MRI, enables a synergistic approach towards hypoxia imaging, with both methods having the potential to provide functional information on the tumour microenvironment. This study is designed as a systematic review of the literature on the newest developments of PET-MRI for the imaging of hypoxic cells in breast cancer. The analysis includes the affinity of various PET-MRI tracers for hypoxia in this patient group as well as the correlations between PET-specific and MRI-specific parameters, to offer a broader view on the potential for the widespread clinical implementation of this hybrid imaging technique.

AmyloidPETNet: Classification of Amyloid Positivity in Brain PET Imaging Using End-to-End Deep Learning.

Background Visual assessment of amyloid PET scans relies on the availability of radiologist expertise, whereas quantification of amyloid burden typically involves MRI for processing and analysis, which can be computationally expensive. Purpose To develop a deep learning model to classify minimally processed brain PET scans as amyloid positive or negative, evaluate its performance on independent data sets and different tracers, and compare it with human visual reads. Materials and Methods This retrospective study used 8476 PET scans (6722 patients) obtained from late 2004 to early 2023 that were analyzed across five different data sets. A deep learning model, AmyloidPETNet, was trained on 1538 scans from 766 patients, validated on 205 scans from 95 patients, and internally tested on 184 scans from 95 patients in the Alzheimer's Disease Neuroimaging Initiative (ADNI) fluorine 18 (18F) florbetapir (FBP) data set. It was tested on ADNI scans using different tracers and scans from independent data sets. Scan amyloid positivity was based on mean cortical standardized uptake value ratio cutoffs. To compare with model performance, each scan from both the Centiloid Project and a subset of the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) study were visually interpreted with a confidence level (low, intermediate, high) of amyloid positivity/negativity. The area under the receiver operating characteristic curve (AUC) and other performance metrics were calculated, and Cohen κ was used to measure physician-model agreement. Results The model achieved an AUC of 0.97 (95% CI: 0.95, 0.99) on test ADNI 18F-FBP scans, which generalized well to 18F-FBP scans from the Open Access Series of Imaging Studies (AUC, 0.95; 95% CI: 0.93, 0.97) and the A4 study (AUC, 0.98; 95% CI: 0.98, 0.98). Model performance was high when applied to data sets with different tracers (AUC ≥ 0.97). Other performance metrics provided converging evidence. Physician-model agreement ranged from fair (Cohen κ = 0.39; 95% CI: 0.16, 0.60) on a sample of mostly equivocal cases from the A4 study to almost perfect (Cohen κ = 0.93; 95% CI: 0.86, 1.0) on the Centiloid Project. Conclusion The developed model was capable of automatically and accurately classifying brain PET scans as amyloid positive or negative without relying on experienced readers or requiring structural MRI. Clinical trial registration no. NCT00106899 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Bryan and Forghani in this issue.

Brain delivery enabled by transient blood-brain barrier disruption induced by regadenoson: a PET imaging study.

BACKGROUND: Regadenoson, an agonist of adenosine A2 receptors, enables transient blood-brain barrier (BBB) disruption. The relevance of regadenoson as a pharmacological strategy for brain delivery was investigated using in vivo PET imaging in rats. RESEARCH DESIGN AND METHODS: Kinetic modeling of brain PET data was performed to estimate the impact of regadenoson (0.05 mg.kg-1, i.v.) on BBB permeation compared with control rats (n = 4-6 per group). Three radiolabeled compounds of different sizes, which do not cross the intact BBB, were tested. RESULTS: Regadenoson significantly increased the BBB penetration (+116 ± 13%, p < 0.001) of [18F]2-deoxy-2-fluoro-D-sorbitol ([18F]FDS, MW = 183 Da), a small-molecule marker of BBB permeability. The magnitude of the effect was different across brain regions, with a maximum increase in the striatum. Recovery of BBB integrity was observed 30 min after regadenoson injection. Regadenoson also increased the brain penetration (+72 ± 45%, p < 0.05) of a radiolabeled nanoparticle [89Zr]AGuIX (MW = 9 kDa). However, the brain kinetics of a monoclonal antibody ([89Zr]mAb, MW = 150 kDa) remained unchanged (p > 0.05). CONCLUSIONS: PET imaging showed the features and limitations of BBB disruption induced by regadenoson in terms of extent, regional distribution, and reversibility. Nevertheless, regadenoson enables the brain delivery of small molecules or nanoparticles in rats.

Construction and Application of a PD-L1-Targeted Multimodal Diagnostic and Dual-Functional Theranostics Nanoprobe.

Background: In recent years, PD-L1 has been primarily utilized as an immune checkpoint marker in cancer immunotherapy. However, due to tumor heterogeneity, the response rate to such therapies often falls short of expectations. In addition to its role in immunotherapy, PD-L1 serves as a specific target on the surface of tumor cells for targeted diagnostic and therapeutic interventions. There is an absence of a fully developed PD-L1-targeted diagnostic and therapeutic probe for clinical use, which constrains the exploration and clinical exploitation of this target. Methods and Results: In this study, we engineered a PD-L1-targeted probe with multimodal imaging and dual therapeutic functionalities utilizing organic melanin nanoparticles. Functionalization with the WL12-SH peptide endowed the nanoprobe with specific targeting capabilities. Subsequent radiolabeling with 89Zr (half-life: 100.8 hours) and chelation of Mn2+ ions afforded the probe the capacity for simultaneous PET and MRI imaging modalities. Cellular uptake assays revealed pronounced specificity, with -positive cells exhibiting significantly higher uptake than -negative counterparts (p < 0.05). Dual-modal PET/MRI imaging delineated rapid and sustained accumulation at the neoplastic site, yielding tumor-to-non-tumor (T/NT) signal ratios at 24 hours post-injection of 16.67±3.45 for PET and 6.63±0.64 for MRI, respectively. We conjugated the therapeutic radionuclide 131I (half-life: 8.02 days) to the construct and combined low-dose radiotherapy and photothermal treatment (PTT), culminating in superior antitumor efficacy while preserving a high safety profile. The tumors in the cohort receiving the dual-modality therapy exhibited significantly reduced volume and weight compared to those in the control and monotherapy groups. Conclusion: We developed and applied a novel -targeted multimodal theranostic nanoprobe, characterized by its high specificity and superior imaging capabilities as demonstrated in PET/MRI modalities. Furthermore, this nanoprobe facilitates potent therapeutic efficacy at lower radionuclide doses when used in conjunction with PTT.

Navigating new horizons: Prospects of NET-targeted radiopharmaceuticals in precision medicine.

In the evolving landscape of precision medicine, NET-targeted radiopharmaceuticals are emerging as pivotal tools for the diagnosis and treatment of a range of conditions, from heart failure and neurodegenerative disorders to neuroendocrine cancers. This review evaluates the advancements offered by 18F-labeled PET tracers and 211At alpha-particle therapy, juxtaposed with current 123I-MIBG SPECT and 131I-MIBG therapies. The enhanced spatial resolution and capability for quantitative analysis render 18F-labeled PET tracers potential candidates for improved detection and management of diseases. Alpha-particle therapy with 211At may offer increased specificity and tumoricidal efficacy, pointing towards a shift in therapeutic protocols. While preliminary data is promising, these innovative approaches require thorough validation against current modalities. Ongoing clinical trials are pivotal to confirm the expected clinical benefits and to address safety concerns. This review underscores the need for rigorous research to verify the clinical utility of NET-targeted radiopharmaceuticals, which may redefine precision medicine paradigms and significantly impact patient care.

The Potential of Radiolabeled Bisphosphonates in SPECT and PET for Bone Imaging.

Skeletal-related events due to bone metastases can be prevented by early diagnosis using radiological or nuclear imaging techniques. Nuclear medicine techniques such as Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been used for diagnostic imaging of bone for decades. Although it is widely recognized that conventional diagnostic imaging techniques such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) have high sensitivity, low cost and wide availability, the specificity of both techniques is rather low compared to nuclear medicine techniques. Nuclear medicine techniques, on the other hand, have improved specificity when introduced as a hybrid imaging modality, as they can combine physiological and anatomical information. Two main radiopharmaceuticals are used in nuclear medicine: [99mTc]-methyl diphosphonate ([99mTc]Tc-MDP) from the generator and [18F]sodium fluoride ([18F]NaF) from the cyclotron. The former is used in SPECT imaging, while the latter is used in PET imaging. However, recent studies show that the role of radiolabeled bisphosphonates with gallium-68 (68Ga) and fluorine-18 (18F) may have a potential role in the future. This review, therefore, presents and discusses the brief method for producing current and future potential radiopharmaceuticals for bone metastases.

Ligand-based design of [18F]OXD-2314 for PET imaging in non-Alzheimer's disease tauopathies.

Positron emission tomography (PET) imaging of tau aggregation in Alzheimer's disease (AD) is helping to map and quantify the in vivo progression of AD pathology. To date, no high-affinity tau-PET radiopharmaceutical has been optimized for imaging non-AD tauopathies. Here we show the properties of analogues of a first-in-class 4R-tau lead, [18F]OXD-2115, using ligand-based design. Over 150 analogues of OXD-2115 were synthesized and screened in post-mortem brain tissue for tau affinity against [3H]OXD-2115, and in silico models were used to predict brain uptake. [18F]OXD-2314 was identified as a selective, high-affinity non-AD tau PET radiotracer with favorable brain uptake, dosimetry, and radiometabolite profiles in rats and non-human primate and is being translated for first-in-human PET studies.

Noninvasive assessment of the lung inflammation-fibrosis axis by targeted imaging of CMKLR1.

Precision management of fibrotic lung diseases is challenging due to their diverse clinical trajectories and lack of reliable biomarkers for risk stratification and therapeutic monitoring. Here, we validated the accuracy of CMKLR1 as an imaging biomarker of the lung inflammation-fibrosis axis. By analyzing single-cell RNA sequencing datasets, we demonstrated CMKLR1 expression as a transient signature of monocyte-derived macrophages (MDMφ) enriched in patients with idiopathic pulmonary fibrosis (IPF). Consistently, we identified MDMφ as the major driver of the uptake of CMKLR1-targeting peptides in a murine model of bleomycin-induced lung fibrosis. Furthermore, CMKLR1-targeted positron emission tomography in the murine model enabled quantification and spatial mapping of inflamed lung regions infiltrated by CMKLR1-expressing macrophages and emerged as a robust predictor of subsequent lung fibrosis. Last, high CMKLR1 expression by bronchoalveolar lavage cells identified an inflammatory endotype of IPF with poor survival. Our investigation supports the potential of CMKLR1 as an imaging biomarker for endotyping and risk stratification of fibrotic lung diseases.

Cloud-based serverless computing enables accelerated monte carlo simulations for nuclear medicine imaging.

Objective.This study investigates the potential of cloud-based serverless computing to accelerate Monte Carlo (MC) simulations for nuclear medicine imaging tasks. MC simulations can pose a high computational burden-even when executed on modern multi-core computing servers. Cloud computing allows simulation tasks to be highly parallelized and considerably accelerated.Approach.We investigate the computational performance of a cloud-based serverless MC simulation of radioactive decays for positron emission tomography imaging using Amazon Web Service (AWS) Lambda serverless computing platform for the first time in scientific literature. We provide a comparison of the computational performance of AWS to a modern on-premises multi-thread reconstruction server by measuring the execution times of the processes using between105and2·1010simulated decays. We deployed two popular MC simulation frameworks-SimSET and GATE-within the AWS computing environment. Containerized application images were used as a basis for an AWS Lambda function, and local (non-cloud) scripts were used to orchestrate the deployment of simulations. The task was broken down into smaller parallel runs, and launched on concurrently running AWS Lambda instances, and the results were postprocessed and downloaded via the Simple Storage Service.Main results.Our implementation of cloud-based MC simulations with SimSET outperforms local server-based computations by more than an order of magnitude. However, the GATE implementation creates more and larger output file sizes and reveals that the internet connection speed can become the primary bottleneck for data transfers. Simulating 109decays using SimSET is possible within 5 min and accrues computation costs of about $10 on AWS, whereas GATE would have to run in batches for more than 100 min at considerably higher costs.Significance.Adopting cloud-based serverless computing architecture in medical imaging research facilities can considerably improve processing times and overall workflow efficiency, with future research exploring additional enhancements through optimized configurations and computational methods.

Recent Advancements in Radiopharmaceuticals for Infection Imaging.

COVID-19 pandemic has heightened the interest toward diagnosis and treatment of infectious diseases. Nuclear medicine, with its powerful scintigraphic, single photon emission computer tomography (SPECT), and positron emission tomography (PET) imaging modalities, has always played an important role in diagnosis of infections and distinguishing them from the sterile inflammation. In addition to the clinically available radiopharmaceuticals, there has been a decades-long effort to develop more specific imaging agents with some examples being radiolabeled antibiotics and antimicrobial peptides for bacterial imaging, radiolabeled antifungals for fungal infections imaging, radiolabeled pathogen-specific antibodies, and molecular engineered constructs. In this chapter, we discuss some examples of the work published in the last decade on developing nuclear imaging agents for bacterial, fungal, and viral infections to generate more interest among nuclear medicine community toward conducting clinical trials of these novel probes, as well as toward developing novel radiotracers for imaging infections.

Towards Clinical Development of Scandium Radioisotope Complexes for Use in Nuclear Medicine: Encouraging Prospects with the Chelator 1,4,7,10-Tetraazacyclododecane-1,4,7,10-tetraacetic Acid (DOTA) and Its Analogues.

Scandium (Sc) isotopes have recently attracted significant attention in the search for new radionuclides with potential uses in personalized medicine, especially in the treatment of specific cancer patient categories. In particular, Sc-43 and Sc-44, as positron emitters with a satisfactory half-life (3.9 and 4.0 h, respectively), are ideal for cancer diagnosis via Positron Emission Tomography (PET). On the other hand, Sc-47, as an emitter of beta particles and low gamma radiation, may be used as a therapeutic radionuclide, which also allows Single-Photon Emission Computed Tomography (SPECT) imaging. As these scandium isotopes follow the same biological pathway and chemical reactivity, they appear to fit perfectly into the "theranostic pair" concept. A step-by-step description, initiating from the moment of scandium isotope production and leading up to their preclinical and clinical trial applications, is presented. Recent developments related to the nuclear reactions selected and employed to produce the radionuclides Sc-43, Sc-44, and Sc-47, the chemical processing of these isotopes and the main target recovery methods are also included. Furthermore, the radiolabeling of the leading chelator, 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA), and its structural analogues with scandium is also discussed and the advantages and disadvantages of scandium complexation are evaluated. Finally, a review of the preclinical studies and clinical trials involving scandium, as well as future challenges for its clinical uses and applications, are presented.

Amyloid-PET imaging predicts functional decline in clinically normal individuals.

BACKGROUND: There is good evidence that elevated amyloid-ß (Aß) positron emission tomography (PET) signal is associated with cognitive decline in clinically normal (CN) individuals. However, it is less well established whether there is an association between the Aß burden and decline in daily living activities in this population. Moreover, Aß-PET Centiloids (CL) thresholds that can optimally predict functional decline have not yet been established. METHODS: Cross-sectional and longitudinal analyses over a mean three-year timeframe were performed on the European amyloid-PET imaging AMYPAD-PNHS dataset that phenotypes 1260 individuals, including 1032 CN individuals and 228 participants with questionable functional impairment. Amyloid-PET was assessed continuously on the Centiloid (CL) scale and using Aß groups (CL < 12 = Aß-, 12 ≤ CL ≤ 50 = Aß-intermediate/Aß± , CL > 50 = Aß+). Functional abilities were longitudinally assessed using the Clinical Dementia Rating (Global-CDR, CDR-SOB) and the Amsterdam Instrumental Activities of Daily Living Questionnaire (A-IADL-Q). The Global-CDR was available for the 1260 participants at baseline, while baseline CDR-SOB and A-IADL-Q scores and longitudinal functional data were available for different subsamples that had similar characteristics to those of the entire sample. RESULTS: Participants included 765 Aß- (61%, Mdnage = 66.0, IQRage = 61.0-71.0; 59% women), 301 Aß± (24%; Mdnage = 69.0, IQRage = 64.0-75.0; 53% women) and 194 Aß+ individuals (15%, Mdnage = 73.0, IQRage = 68.0-78.0; 53% women). Cross-sectionally, CL values were associated with CDR outcomes. Longitudinally, baseline CL values predicted prospective changes in the CDR-SOB (bCL*Time = 0.001/CL/year, 95% CI [0.0005,0.0024], p = .003) and A-IADL-Q (bCL*Time = -0.010/CL/year, 95% CI [-0.016,-0.004], p = .002) scores in initially CN participants. Increased clinical progression (Global-CDR > 0) was mainly observed in Aß+ CN individuals (HRAß+ vs Aß- = 2.55, 95% CI [1.16,5.60], p = .020). Optimal thresholds for predicting decline were found at 41 CL using the CDR-SOB (bAß+ vs Aß- = 0.137/year, 95% CI [0.069,0.206], p < .001) and 28 CL using the A-IADL-Q (bAß+ vs Aß- = -0.693/year, 95% CI [-1.179,-0.208], p = .005). CONCLUSIONS: Amyloid-PET quantification supports the identification of CN individuals at risk of functional decline. TRIAL REGISTRATION: The AMYPAD PNHS is registered at www.clinicaltrialsregister.eu with the EudraCT Number: 2018-002277-22.

Clinical Significance of the Plasma Biomarker Panels in Amyloid-Negative and Tau PET-Positive Amnestic Patients: Comparisons with Alzheimer's Disease and Unimpaired Cognitive Controls.

The purpose of this study was to investigate whether plasma biomarkers can help to diagnose, differentiate from Alzheimer disease (AD), and stage cognitive performance in patients with positron emission tomography (PET)-confirmed primary age-related tauopathy, termed tau-first cognitive proteinopathy (TCP) in this study. In this multi-center study, we enrolled 285 subjects with young-onset AD (YOAD; n = 55), late-onset AD (LOAD; n = 96), TCP (n = 44), and cognitively unimpaired controls (CTL; n = 90) and analyzed plasma Aß42/Aß40, pTau181, neurofilament light (NFL), and total-tau using single-molecule assays. Amyloid and tau centiloids reflected pathological burden, and hippocampal volume reflected structural integrity. Receiver operating characteristic curves and areas under the curves (AUCs) were used to determine the diagnostic accuracy of plasma biomarkers compared to hippocampal volume and amyloid and tau centiloids. The Mini-Mental State Examination score (MMSE) served as the major cognitive outcome. Logistic stepwise regression was used to assess the overall diagnostic accuracy, combining fluid and structural biomarkers and a stepwise linear regression model for the significant variables for MMSE. For TCP, tau centiloid reached the highest AUC for diagnosis (0.79), while pTau181 could differentiate TCP from YOAD (accuracy 0.775) and LOAD (accuracy 0.806). NFL reflected the clinical dementia rating in TCP, while pTau181 (rho = 0.3487, p = 0.03) and Aß42/Aß40 (rho = -0.36, p = 0.02) were significantly correlated with tau centiloid. Hippocampal volume (unstandardized ß = 4.99, p = 0.01) outperformed all of the fluid biomarkers in predicting MMSE scores in the TCP group. Our results support the superiority of tau PET to diagnose TCP, pTau181 to differentiate TCP from YOAD or LOAD, and NFL for functional staging.

[18F]FDG PET/CT versus [18F]FDG PET/MRI in the evaluation of liver metastasis in patients with primary cancer: A head-to-head comparative meta-analysis.

PURPOSE: This meta-analysis aimed to compare the diagnostic effectiveness of [18F]FDG PET/CT with that of [18F]FDG PET/MRI in terms of identifying liver metastasis in patients with primary cancer. METHODS: PubMed, Embase, Web of Science, and the Cochrane Library were searched, and studies evaluating the diagnostic efficacy of [18F]FDG PET/CT and [18F]FDG PET/MRI in patients with liver metastasis of primary cancer were included. We used a random effects model to analyze their sensitivity and specificity. Subgroup analyses and corresponding meta-regressions focusing on race, image analysis, study design, and analysis methodologies were conducted. Cochrane Q and I2 statistics were used to assess intra-group and inter-group heterogeneity. RESULTS: Seven articles with 343 patients were included in this meta-analysis. The sensitivity of [18F]FDG PET/CT was 0.82 (95 % CI: 0.63-0.96), and that of [18F]FDG PET/MRI was 0.91 (95 % CI: 0.82-0.98); there was no significant difference between the two methods (P = 0.32). Similarly, both methods showed equal specificity: 1.00 (95 % CI: 0.95-1.00) for [18F]FDG PET/CT and 1.00 (95 % CI: 0.96-1.00) for [18F]FDG PET/MRI, and thus, there was no significant difference between the methods (P = 0.41). Furthermore, the subgroup analyses revealed no differences. Meta-regression analysis revealed that race was a potential source of heterogeneity for [18F]FDG PET/CT (P = 0.01), while image analysis and contrast agent were found to be potential sources of heterogeneity for [18F]FDG PET/MRI (P = 0.02). CONCLUSIONS: [18F]FDG PET/MRI has similar sensitivity and specificity to [18F]FDG PET/CT for detecting liver metastasis of primary cancer in both the general population and in subgroups. [18F]FDG PET/CT may be a more cost-effective option. However, the conclusions of this meta-analysis are tentative due to the limited number of studies included, and further research is necessary for validation.