Purpose: In Y microsphere radioembolization (RE), accurate post-therapy imaging-based dosimetry is important for establishing absorbed dose versus outcome relationships for developing future treatment planning strategies. Additionally, accurately assessing microsphere distributions is important because of concerns for unexpected activity deposition outside the liver. Quantitative Y imaging by either SPECT or PET is challenging. In Y SPECT model based methods are necessary for scatter correction because energy window-based methods are not feasible with the continuous bremsstrahlung energy spectrum. The objective of this work was to implement and evaluate a scatter estimation method for accurate Y bremsstrahlung SPECT/CT imaging.
Methods: Since a fully Monte Carlo (MC) approach to Y SPECT reconstruction is computationally very demanding, in the present study the scatter estimate generated by a MC simulator was combined with an analytical projector in the 3D OS-EM reconstruction model. A single window (105 to 195-keV) was used for both the acquisition and the projector modeling. A liver/lung torso phantom with intrahepatic lesions and low-uptake extrahepatic objects was imaged to evaluate SPECT/CT reconstruction without and with scatter correction. Clinical application was demonstrated by applying the reconstruction approach to five patients treated with RE to determine lesion and normal liver activity concentrations using a (liver) relative calibration.
Results: There was convergence of the scatter estimate after just two updates, greatly reducing computational requirements. In the phantom study, compared with reconstruction without scatter correction, with MC scatter modeling there was substantial improvement in activity recovery in intrahepatic lesions (from > 55% to > 86%), normal liver (from 113% to 104%), and lungs (from 227% to 104%) with only a small degradation in noise (13% vs. 17%). Similarly, with scatter modeling contrast improved substantially both visually and in terms of a detectability index, which was especially relevant for the low uptake extrahepatic objects. The trends observed for the phantom were also seen in the patient studies where lesion activity concentrations and lesion-to-liver concentration ratios were lower for SPECT without scatter correction compared with reconstruction with just two MC scatter updates: in eleven lesions the mean uptake was 4.9 vs. 7.1 MBq/mL (P = 0.0547), the mean normal liver uptake was 1.6 vs. 1.5 MBq/mL (P = 0.056) and the mean lesion-to-liver uptake ratio was 2.7 vs. 4.3 (P = 0.0402) for reconstruction without and with scatter correction respectively.
Conclusions: Quantitative accuracy of Y bremsstrahlung imaging can be substantially improved with MC scatter modeling without significant degradation in image noise or intensive computational requirements.
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http://dx.doi.org/10.1002/mp.12597 | DOI Listing |
Anal Methods
January 2025
Department of Food Science and Postharvest Technology, School of Applied Sciences and Technology, Cape Coast Technical University, Cape Coast, Ghana.
This research examined the distinction between organic and conventional mango fruits, chips, and juice using portable near-infrared (NIR) spectroscopy. A comprehensive analysis was conducted on a sample of 100 mangoes (comprising 50 organic and 50 conventional) utilising a portable NIR spectrometer that spans a wavelength range from 900 to 1700 nm. The mangoes were assessed in their entirety and their juice and chip forms.
View Article and Find Full Text PDFFood Res Int
February 2025
State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, Jiangsu Province, China; School of Food Science and Technology, Jiangnan University University, Wuxi, Jiangsu Province, China; Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, China. Electronic address:
The aim of this study was to explore application of visible and near-infrared (Vis/NIR) spectroscopy combined with machine learning models for SSC and TA prediction of hybrid citrus. The Vis/NIR spectra of samples including navel-region, equator-region and multi-region combination spectra in navel-region and equator-region were collected using a benchtop equipment. The performance of SSC and TA prediction models with different region spectra, including partial least squares (PLS), random forest (RF), k-nearest neighbors (KNN), support vector machine (SVM) and multilayer feedforward neural network (MFNN), was assessed.
View Article and Find Full Text PDFChemosphere
January 2025
TNO Environmental Modelling, Sensing and Analysis, Princetonlaan 6-8, 3584 CB, Utrecht, the Netherlands. Electronic address:
Tyre and road wear particles (TRWPs) are estimated to be the largest source of microplastics in the environment and due to the intrinsic use of tyres in our society this will continue to grow. Understanding their degradation mechanisms and subsequent accumulation over time is important to gain insights into the fate and impact of these particles in the environment. Accelerated UV-ageing was performed on cryomilled tyre tread particles and TRWPs from a road simulator to investigate the abiotic degradation of rubber.
View Article and Find Full Text PDFPhotochem Photobiol
January 2025
Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Photodynamic therapy (PDT) has shown promise as an adjuvant treatment for malignant pleural mesothelioma when combined with surgical resection. Accurate light dosimetry is critical for treatment efficacy. This study presents an improved method for analyzing light fluence distribution in pleural PDT using a standardized anatomical coordinate system and advanced computational modeling.
View Article and Find Full Text PDFAnal Methods
January 2025
College of Pharmaceutical Engineering of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, 301617, China.
The efficacy and safety of drugs are closely related to the geographical origin and quality of the raw materials. This study focuses on using near-infrared hyperspectral imaging (NIR-HSI) combined with machine learning algorithms to construct content prediction models and origin identification models to predict the components and origin of Radix Paeoniae Rubra (RPR). These models are quick, non-destructive, and accurate for assessing both component content and origin.
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