Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Purpose: Respiratory motion causes uptake in positron emission tomography (PET) images of chest structures to spread out and misregister with the CT images. This misregistration can alter the attenuation correction and thus the quantisation of PET images. In this paper, we present the first clinical results for a respiratory-gated PET (RG-PET) processing method based on a single breath-hold CT (BH-CT) acquisition, which seeks to improve diagnostic accuracy via better PET-to-CT co-registration. We refer to this method as "CT-based" RG-PET processing.

Methods: Thirteen lesions were studied. Patients underwent a standard clinical PET protocol and then the CT-based protocol, which consists of a 10-min List Mode RG-PET acquisition, followed by a shallow end-expiration BH-CT. The respective performances of the CT-based and clinical PET methods were evaluated by comparing the distances between the lesions' centroids on PET and CT images. SUV(MAX) and volume variations were also investigated.

Results: The CT-based method showed significantly lower (p = 0.027) centroid distances (mean change relative to the clinical method = -49%; range = -100% to 0%). This led to higher SUV(MAX) (mean change = +33%; range = -4% to 69%). Lesion volumes were significantly lower (p = 0.022) in CT-based PET volumes (mean change = -39%: range = -74% to -1%) compared with clinical ones.

Conclusions: A CT-based RG-PET processing method can be implemented in clinical practice with a small increase in radiation exposure. It improves PET-CT co-registration of lung lesions and should lead to more accurate attenuation correction and thus SUV measurement.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s00259-008-0858-2DOI Listing

Publication Analysis

Top Keywords

pet images
12
pet
8
respiratory-gated pet
8
attenuation correction
8
rg-pet processing
8
processing method
8
clinical pet
8
ct-based
6
clinical
6
method
5

Similar Publications

Background And Objectives: The relationship between insomnia and cognitive decline is poorly understood. We investigated associations between chronic insomnia, longitudinal cognitive outcomes, and brain health in older adults.

Methods: From the population-based Mayo Clinic Study of Aging, we identified cognitively unimpaired older adults with or without a diagnosis of chronic insomnia who underwent annual neuropsychological assessments (z-scored global cognitive scores and cognitive status) and had quantified serial imaging outcomes (amyloid-PET burden [centiloid] and white matter hyperintensities from MRI [WMH, % of intracranial volume]).

View Article and Find Full Text PDF

FDG PET Findings in Rare Brain Sodium Channelopathy Associated with SCN2A Gene Mutation.

Clin Nucl Med

September 2025

Department of Nuclear Medicine & PET/CT, Mahajan Imaging & Labs.

SCN2A gene mutations, which affect the function of the voltage-gated sodium channel NaV1.2, are associated with a spectrum of neurological disorders, including epileptic encephalopathies and autism spectrum disorders. Advanced imaging modalities such as magnetic resonance imaging (MRI) and positron emission tomography (PET) have been instrumental in elucidating the neuroanatomic and functional alterations associated with these mutations.

View Article and Find Full Text PDF

Objective: This study aims to systematically evaluate the inter- and intra-observer agreement regarding lesions with uncertain malignancy potential in Ga-68 PSMA PET/CT imaging of prostate cancer patients, utilizing the PSMA-RADS 2.0 classification system, and to emphasize the malignancy evidence associated with these lesions.

Methods: We retrospectively reviewed Ga-68 PSMA PET/CT images of patients diagnosed with prostate cancer via histopathology between December 2016 and November 2023.

View Article and Find Full Text PDF

Non-invasive prediction of invasive lung adenocarcinoma and high-risk histopathological characteristics in resectable early-stage adenocarcinoma by [18F]FDG PET/CT radiomics-based machine learning models: a prospective cohort Study.

Int J Surg

September 2025

Department of Respiratory and Critical Care Medicine, Hubei Province Clinical Research Center for Major Respiratory Diseases, Key Laboratory of Pulmonary Diseases of National Health Commission, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China

Background: Precise preoperative discrimination of invasive lung adenocarcinoma (IA) from preinvasive lesions (adenocarcinoma in situ [AIS]/minimally invasive adenocarcinoma [MIA]) and prediction of high-risk histopathological features are critical for optimizing resection strategies in early-stage lung adenocarcinoma (LUAD).

Methods: In this multicenter study, 813 LUAD patients (tumors ≤3 cm) formed the training cohort. A total of 1,709 radiomic features were extracted from the PET/CT images.

View Article and Find Full Text PDF

Introduction: We developed and validated age-related amyloid beta (Aβ) positron emission tomography (PET) trajectories using a statistical model in cognitively unimpaired (CU) individuals.

Methods: We analyzed 849 CU Korean and 521 CU non-Hispanic White (NHW) participants after propensity score matching. Aβ PET trajectories were modeled using the generalized additive model for location, scale, and shape (GAMLSS) based on baseline data and validated with longitudinal data.

View Article and Find Full Text PDF