Publications by authors named "B E Mehadji"

Unlabelled: Accurate estimation of the Lung Shunt Fraction (LSF) is a standard of care in yttrium-90 ( Y) radioembolization treatment planning to prevent excessive lung irradiation due to arterio-venous shunting in the liver. LSF is assessed using Tc macroaggregated albumin ( Tc-MAA) imaging, but this approach adds risk, complexity, and expense to the treatment planning. This study investigates the potential of Contrast-Enhanced Computed Tomography (CECT) as a non-invasive alternative for LSF estimation.

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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.

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Contrast-enhanced computed tomography (CECT) is commonly used in the pre-treatment evaluation of liver Y-90 radioembolization feasibility. CECT provides detailed imaging of the liver and surrounding structures, allowing healthcare providers to assess the size, location, and characteristics of liver tumors prior to the treatment. Here we propose a method for translating CECT images to an expected dose distribution for tumor(s) and normal liver tissue.

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In vivo molecular imaging tools are crucially important for elucidating how cells move through complex biological systems; however, achieving single-cell sensitivity over the entire body remains challenging. Here, we report a highly sensitive and multiplexed approach for tracking upward of 20 single cells simultaneously in the same subject using positron emission tomography (PET). The method relies on a statistical tracking algorithm (PEPT-EM) to achieve a sensitivity of 4 becquerel per cell and a streamlined workflow to reliably label single cells with over 50 becquerel per cell of F-fluorodeoxyglucose (FDG).

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molecular imaging tools are crucially important for elucidating how cells move through complex biological systems, however, achieving single-cell sensitivity over the entire body remains challenging. Here, we report a highly sensitive and multiplexed approach for tracking upwards of 20 single cells simultaneously in the same subject using positron emission tomography (PET). The method relies on a new tracking algorithm (PEPT-EM) to push the cellular detection threshold to below 4 Bq/cell, and a streamlined workflow to reliably label single cells with over 50 Bq/cell of F-fluorodeoxyglucose (FDG).

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