Seminars in nuclear medicine最新文献

This review aims to provide an up-to-date overview of the utility of artificial intelligence (AI) in evaluating prostate-specific membrane antigen (PSMA) positron emission tomography (PET) scans for prostate cancer (PCa). A literature review was conducted on the Medline, Embase, Web of Science, and IEEE Xplore databases. The search focused on studies that utilizes AI to evaluate PSMA PET scans. Original English language studies published from inception to October 2024 were included, while case reports, series, commentaries, and conference proceedings were excluded. AI applications show promise in automating the detection of metastatic disease and anatomical segmentation in PSMA PET scans. AI was also able to predict response to PSMA-based theragnostic and aids in tumor burden segmentation, improving radiotherapy planning. AI could also differentiate intraprostatic PCa with higher histological grade and predict extra-prostatic extension. AI has potential in evaluating PSMA PET scans for PCa, particularly in detecting metastasis, measuring tumor burden, detecting high grade intraprostatic cancer, and predicting treatment outcomes. Larger multicenter prospective studies are necessary to validate and enhance the generalizability of these AI models.

Gastrin-releasing peptide receptor (GRPR), overexpressed in various cancers, is a promising target for positron emission tomography (PET). This systematic review investigated the diagnostic value of GRPR-targeted PET imaging in oncology. A systematic search was conducted on major medical databases until May 23, 2024. Keywords were modified to include clinical original studies on GRPR-targeted PET in cancer patients. Out of 1624 searched studies initially, 107 were eligible for the full-text review. Overall, data from 38 studies met inclusion criteria, investigating GRPR-targeting radiotracers in breast cancer, prostate cancer, gastrointestinal stromal tumours (GIST) and gliomas (including optic pathway glioma and glioblastoma multiforme). In breast cancer, GRPR-targeted PET effectively detected primary tumours and metastases, particularly in estrogen receptor (ER)-positive patients, and predicted treatment response. In prostate cancer, high sensitivity (up to 88%) and specificity (up to 90%) for detecting primary tumours were observed, providing added value when combined with magnetic resonance imaging (MRI). In biochemical recurrence, sites of prostate cancer were identified even at PSA levels below 0.5ng/dL. Compared with PSMA PET, GRPR-targeted PET showed comparable or superior detection rates. Considering GIST, GRPR-targeted PET imaging proved to be a valuable diagnostic tool, particularly when [¹⁸F] FDG PET results were inconclusive. Regarding gliomas, GRPR-targeted PET achieved a 100% detection rate (MRI reference), aiding localization, preoperative planning, and differentiation between recurrence and malignant transformation. GRPR-targeted PET shows promise in improving cancer diagnostics, particularly in ER-positive breast cancer, prostate cancer, and gliomas, and may enhance clinical decision-making.

Total body (TB) Positron Emission Tomography (PET) / Computed Tomography (CT) scanners have revolutionized nuclear medicine by enabling whole-body imaging in a single bed position.¹ This review assesses the physical and clinical value of TB-PET/CT, with a focus on the advancements in both static and dynamic imaging, as well as the evolving quantification techniques. The significantly enhanced sensitivity of TB scanners can reduce radiation exposure and scan time, offering improved patient comfort and making it particularly useful for pediatric imaging and various other scenarios. Shorter scan times also decrease motion artifacts, leading to higher-quality images and better diagnostic accuracy. Dynamic PET imaging with TB scanners extends these advantages by capturing temporal changes in tracer uptake over time, providing real-time insights into both structural and functional assessment, and promoting the ability to monitor disease progression and treatment response. We also present CT-free attenuation correction methods that utilize the increased sensitivity of TB-PET as a potential improvement for dynamic TB-PET protocols. In static imaging, emerging quantification techniques such as dual-tracer PET using TB scanners allow imaging of two biological pathways, simultaneously, for a more comprehensive assessment of disease. In addition, positronium imaging, a novel technique utilizing positronium lifetime measurements, is introduced as a promising aspect for providing structural information alongside functional quantification. Finally, the potential of expanding clinical applications with the increased sensitivity of TB-PET/CT scanners is discussed.

Recently developed long axial field of view (LAFOV) PET-CT scanners, including total body scanners, are already in use in a few centers worldwide. These systems have some major advantages over standard axial field of view (SAFOV) PET-CT scanners, mainly due to up to 20 times higher sensitivity and therefore improved lesion detectability. Other advantages are the reduction of the PET acquisition time for a static whole-body measurement, the reduction of the administered radiotracer dose, and the ability to perform delayed scans with good image quality, which is important for imaging radionuclides with long half-lives and pharmaceuticals with long biodistribution times, such as ⁸⁹Zr-labeled antibodies. The reduction of the applied tracer dose leads to less radiation exposure and may facilitate longitudinal studies, especially in oncological patients, for the evaluation of therapy. The reduction in acquisition time for a static whole body (WB) study allows a markedly higher patient throughput. Furthermore, LAFOV PET-CT scanners enable for the first-time WB dynamic PET scanning and WB parametric imaging with an improved image quality due to increased sensitivity and time resolution. WB tracer kinetics is of particular interest for the characterization of novel radiopharmaceuticals and for a better biological characterization of cancer diseases, as well as for a more accurate assessment of the response to new targeted therapies. Further technological developments based on artificial intelligence (AI) approaches are underway and may in the future allow CT-less attenuation correction or ultralow dose CT for attenuation correction as well as segmentation algorithms for the evaluation of total metabolic tumor volume. The aim of this review is to present dedicated PET acquisition protocols for oncological studies with LAFOV scanners, including static and dynamic acquisition as well as parametric scans, and to present literature data to date on this topic.

Total-body (TB) positron emission tomography (PET) scanners are classified by their axial field of view (FOV). Long axial field of view (LAFOV) PET scanners can capture images from eyes to thighs in a one-bed position, covering all major organs with an axial FOV of about 100 cm. However, they often miss essential areas like distal lower extremities, limiting their use beyond oncology.TB-PET is reserved for scanners with a FOV of 180 cm or longer, allowing coverage of most of the body. LAFOV PET technology emerged about 40 years ago but gained traction recently due to advancements in data acquisition and cost. Early research highlighted its benefits, leading to the first FDA-cleared TB-PET/CT device in 2019 at UC Davis. Since then, various LAFOV scanners with enhanced capabilities have been developed, improving image quality, reducing acquisition times, and allowing for dynamic imaging. The uEXPLORER, the first LAFOV scanner, has a 194 cm active PET AFOV, far exceeding traditional scanners. The Panorama GS and others have followed suit in optimizing FOVs. Despite slow adoption due to the COVID pandemic and costs, over 50 LAFOV scanners are now in use globally. This review explores the future of LAFOV technology based on recent literature and experiences, covering its clinical applications, implications for radiation oncology, challenges in managing PET data, and expectations for technological advancements.

Nowadays, total body PET has already entered the medical centers and enabled various clinical applications due to its superior imaging capabilities, especially the high sensitivity. However, the potential of the total body PET in the clinical evaluation of radiopharmaceuticals remains underexplored. The development and regulatory processes for radiopharmaceuticals present unique challenges that total body PET could address. In the safety evaluation of radiopharmaceuticals, the internal radiation dosimetry demands images with high quality and quantitative accuracy, which can be achieved using the total body PET. The current clinical pharmacokinetic study for radiopharmaceuticals still relies on invasively sampling of blood and other body fluid, causing discomfort of participant and difficulty in implementation. With the total body PET, the radioactive concentration of the drug in various blood vessels can be assessed noninvasively, facilitating the pharmacokinetic study. The parametric analysis over the total body based on compartment models also sheds light on the pharmacokinetics of the radiopharmaceutical. A special requirement for multi-center clinical research involving PET and SPECT is the harmonization of the quantitative performance among different imaging equipment, and the discrepancy between the total body PET and short axial field of view PET scanners may add to the complexity. To date, there are several successful examples of clinical trials of innovative radiopharmaceuticals using the total body PET, involving different types of tracers ranging from small molecules, peptides, nanobodies, minibodies, and aptamers. In conclusion, total body PET has the potential to revolutionize the clinical evaluation of radiopharmaceuticals and will play a crucial role in future drug development.

This systematic review and network meta-analysis aimed to compare the diagnostic accuracy of 2-[¹⁸F]FDG-PET/CT, ¹⁸F-NaF-PET/CT, MRI, contrast-enhanced CT, and bone scintigraphy for diagnosing bone metastases in patients with breast cancer. Following PRISMA-DTA guidelines, we reviewed studies assessing 2-[¹⁸F]FDG-PET/CT, ¹⁸F-NaF-PET/CT, MRI, contrast-enhanced CT, and bone scintigraphy for diagnosing bone metastases in high-stage primary breast cancer (stage III or IV) or known primary breast cancer with suspicion of recurrence (staging or re-staging). A comprehensive search of MEDLINE/PubMed, Scopus, and Embase was conducted until February 2024. Inclusion criteria were original studies using these imaging methods, excluding those focused on AI/machine learning, primary breast cancer without metastases, mixed cancer types, preclinical studies, and lesion-based accuracy. Preference was given to studies using biopsy or follow-up as the reference standard. Risk of bias was assessed using QUADAS-2. Screening, bias assessment, and data extraction were independently performed by two researchers, with discrepancies resolved by a third. We applied bivariate random-effects models in meta-analysis and network meta-analyzed differences in sensitivity and specificity between the modalities. Forty studies were included, with 29 contributing to the meta-analyses. Of these, 13 studies investigated one single modality only. Both 2-[¹⁸F]FDG-PET/CT (sensitivity: 0.94, 95% CI: 0.89-0.97; specificity: 0.98, 95% CI: 0.96-0.99), MRI (0.94, 0.82-0.98; 0.93, 0.87-0.96), and ¹⁸F-NaF-PET/CT (0.95, 0.85-0.98; 1, 0.93-1) outperformed the less sensitive modalities CE-CT (0.70, 0.62-0.77; 0.98, 0.97-0.99) and bone scintigraphy (0.83, 0.75-0.88; 0.96, 0.87-0.99). The network meta-analysis of multi-modality studies supports the comparable performance of 2-[¹⁸F]FDG-PET/CT and MRI in diagnosing bone metastases (estimated differences in sensitivity and specificity, respectively: 0.01, -0.16 - 0.18; -0.02, -0.15 - 0.12). The results from bivariate random effects modelling and network meta-analysis were consistent for all modalities apart from ¹⁸F-NaF-PET/CT. We concluded that 2-[¹⁸F]FDG-PET/CT and MRI have high and comparable accuracy for diagnosing bone metastases in breast cancer patients. Both outperformed CE-CT and bone scintigraphy regarding sensitivity. Future multimodality studies based on consented thresholds are warranted for further exploration, especially in terms of the potential role of ¹⁸F-NaF-PET/CT in bone metastasis diagnosis in breast cancer.

Long-axial field-of-view (LAFOV) systems have changed the field of molecular imaging. Since their introduction, many PET centers have installed these next-generation digital systems to provide more detailed imaging and acquire PET images in a single bed position. Indeed, vertex to thigh imaging for oncological indications can be obtained in most of the population with the currently available LAFOV systems. Moreover, Total Body (TB) PET, a subtype of LAFOV, enables imaging the entire patient-from vertex through the toes-with one bed-position for most of the population. This review aims to identify possible challenges and opportunities for PET-centers working with TB and LAFOV systems. Emphasis is placed on the strength and weaknesses in clinical routine of currently available and upcoming TB and LAFOV PET systems.

The purpose of this paper is to provide an overview of the cutting-edge applications of artificial intelligence (AI) technology in total-body positron emission tomography/computed tomography (PET/CT) scanning technology and its profound impact on the field of medical imaging. The introduction of total-body PET/CT scanners marked a major breakthrough in medical imaging, as their superior sensitivity and ultralong axial fields of view allowed for high-quality PET images of the entire body to be obtained in a single scan, greatly enhancing the efficiency and accuracy of diagnoses. However, this advancement is accompanied by the challenges of increasing data volumes and data complexity levels, which pose severe challenges for traditional image processing and analysis methods. Given the excellent ability of AI technology to process massive and high-dimensional data, the combination of AI technology and ultrasensitive PET/CT can be considered a complementary match, opening a new path for rapidly improving the efficiency of the PET-based medical diagnosis process. Recently, AI technology has demonstrated extraordinary potential in several key areas related to total-body PET/CT, including radiation dose reductions, dynamic parametric imaging refinements, quantitative analysis accuracy improvements, and significant image quality enhancements. The accelerated adoption of AI in clinical practice is of particular interest and is directly driven by the rapid progress made by AI technologies in terms of interpretability; i.e., the decision-making processes of algorithms and models have become more transparent and understandable. In the future, we believe that AI technology will fundamentally reshape the use of PET/CT, not only playing a more critical role in clinical diagnoses but also facilitating the customization and implementation of personalized healthcare solutions, providing patients with safer, more accurate, and more efficient healthcare experiences.

Positron emission tomography / computed tomography (PET/CT) plays a pivotal role in the assessment of cardiovascular diseases (CVD), particularly in the context of ischemic heart disease. Nevertheless, its application in other forms of CVD, such as infiltrative, infectious, or inflammatory conditions, remains limited. Recently, PET/CT systems with an extended axial field of view (LAFOV) have been developed, offering greater anatomical coverage and significantly enhanced PET sensitivity. These advancements enable head-to-pelvis imaging with a single bed position, and in systems with an axial field of view (FOV) of approximately 2 meters, even total body (TB) imaging is feasible in a single scan session. The application of LAFOV PET/CT in CVD presents a promising opportunity to improve systemic cardiovascular assessments and address the limitations inherent to conventional short axial field of view (SAFOV) devices. However, several technical challenges, including procedural considerations for LAFOV systems in CVD, complexities in data processing, arterial input function extraction, and artefact management, have not been fully explored. This review aims to discuss the technical aspects of LAFOV PET/CT in relation to CVD by highlighting key opportunities and challenges and examining the impact of these factors on the evaluation of most relevant CVD.