Nuclear Medicine

Artificial intelligence for lung cancer: a systematic review of head‑to‑head CT, FDG PET/CT, and multimodal models across screening, staging, and prognosis.

BACKGROUND: Artificial intelligence (AI) has shown increasing potential in lung cancer imaging, particularly in detection, staging, prognosis, and recurrence prediction. However, there is limited synthesis of head-to-head comparative evidence between CT, FDG PET/CT, and multimodal fusion models within the same cohorts. OBJECTIVES: To systematically review and critically appraise studies that direc...

Differential Neural Substrates of Freezing of Gait in Cerebral Small Vessel Disease and Parkinson Disease: A Dual-tracer PET Study.

PURPOSE: Freezing of gait (FOG) occurs in both Parkinson disease (PD) and cerebral small vessel disease (CSVD), but its mechanism in CSVD is unknown. We hypothesize that FOG arises from distinct neural substrates in these 2 disorders. MATERIALS AND METHODS: This cross-sectional study included 7 CSVD patients with FOG, 7 PD patients with FOG, and 20 healthy controls. All underwent clinical assessme...

Enhancing low-dose PET image recovery via edge perception and Mamba-guided network architecture.

Positron emission tomography (PET) is a sensitive molecular imaging technique used extensively in cancer diagnosis, neurology, and cardiovascular dise...

Single-Stage Lesion Identification in $^{68}$Ga-DOTATATE PET Images.

OBJECTIVE: Positron emission tomography (PET) is a commonly used imaging modality for assessment of neuroendocrine tumors (NETs), and lesion identific...

Precision imaging and evolving therapies in paragangliomas and pheochromocytomas: from molecular diagnostics to imaging-guided management.

Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors originating from neural crest-derived chromaffin tissue, marked by clinica...

Deep learning for synthetic PET imaging: a systematic mapping review of techniques, metrics, and clinical relevance.

BACKGROUND: Synthetic positron emission tomography (PET) imaging, enabled by deep learning, represents a promising approach to minimize radiation expo...

Spatial amyloid-informed multimodal brain age as an early marker of Alzheimer's-related vulnerability and risk stratification.

BACKGROUND: Brain age gap (BAG)-the difference between predicted and chronological age-captures neurobiological aging, but MRI-only models insufficien...

Assessment of iodine nutrition status in individual adults using machine learning: a cross-sectional study integrating multidimensional features.

Validation of a Deep-Learning Coregistration Framework for Long-Axial-Field-of-View PET/CT Using Low-Radiation-Exposure Protocols Across Various Tracers.

The advent of long-axial-field-of-view (LAFOV) PET/CT systems has significantly improved whole-body imaging by providing higher sensitivity and extend...

Quantification of PET activation in adipose tissue from non-contrast CT scans.

Brown adipose tissue (BAT) plays a key role in energy metabolism and cardiometabolic health. Its detection typically relies on 18F-FDG PET, which is c...

Beyond CT: Attenuation correction for stand-alone brain PET.

Accurate attenuation correction (AC) is essential for quantitative brain positron emission tomography (PET), but it presents a significant challenge f...

[Innovative imaging techniques for urothelial carcinoma].

BACKGROUND: Imaging guides the staging of urothelial carcinoma and thus plays a central role in treatment decisions. Current guidelines reflect the in...

Enhancing diagnostic safety with low iodine, low radiation CTPA classification using deep learning.

Pulmonary embolism (PE) is a life-threatening condition for which computed tomography pulmonary angiography (CTPA) is the standard diagnostic modality...

DBFANet: a dual-branch feature alignment network for automated detection of breast cancer bone metastasis.

Bone scan imaging for the detection of bone metastasis of breast cancer has been widely adopted; however, noise, anatomy superimposition, and small si...

State-of-the-art 32 cm field-of-view digital PET/CT system: preliminary study for protocols optimization and DRLs update.

The aim of this study was to assess the impact of a state-of-the-art 32 cm axial field-of-view GE Omni Legend PET/CT system on administered activity a...

Parametric imaging of dynamic long-axial-field-of-view PET scans: Technical challenges, statistical insights and clinical applications.

Dynamic long-axial-field-of-view (LAFOV) PET imaging offers unprecedented opportunities for quantitative assessment of tracer kinetics across the enti...

Assignment of the Biological Identity of Breast Masses in Contrast-enhanced Spectral Computed Tomography Examinations of Chest Carried Out in Clinical Routine Diagnostics.

BACKGROUND: Focal breast lesions are observed in up to 5.8% of CT examinations performed in female patients for a wide variety of indications not affe...

Image reconstruction and elongation artifact reduction for a dual-panel dedicated prostate PET scanner.

BACKGROUND: The development of PET scanners dedicated to high temporal and spatial resolution organ-specific imaging is an active research area, motiv...

Scanner-integrated reconstruction versus post-processing deep learning for low-count 18F-FDG PET/CT: a comparative clinical evaluation.

OBJECTIVES: To compare two deep learning (DL) approaches for low-count PET/CT: deep progressive reconstruction (DPR), a scanner-integrated reconstruct...

A comparative review of red, green, and brown seaweed: Bioactive components, health effects, and machine learning approaches.

Edible seaweed subcategorized into Chlorophyta (green algae), Phaeophyceae (brown algae) and Rhodophyta (red algae) are considered sustainable functio...