Purpose: The aim of the study is to assess the influence of manual adjustment of the Patlak range in computed tomography (CT) perfusion analysis of rectal carcinoma compared with default range of the perfusion software.
Methods: This study was approved by the institutional review board and informed consent was obtained. Twenty-one patients (12 male, 9 female; mean age ± SD, 59 ± 11 years) with rectal cancer were included and underwent perfusion CT before preoperative chemoradiotherapy. Equivalent blood volume (BV) and flow-extraction (FE) were calculated using the Patlak plot model. Two perfusion sets were calculated per patient, a perfusion set using the default setting as provided by the software (dBV, dFE) and an optimized perfusion set after manual adaption of the Patlak range (aBV, aFE), which was limited to the intravascular space clearance of contrast to the extravascular space. Perfusion values calculated with both methods were compared for significance in differences using the Wilcoxon test. A P value of 0.05 or less was defined as statistically significant.
Results: Adjustment of the Patlak range statistically significantly influenced BV and FE calculation. Median dBV was 23.2 mL/100 mL (interquartile range [IQR], 12.1 mL/100 mL), whereas median aBV was 20.3 mL/100 mL (IQR, 10.9 mL/100 mL). The difference in BV was statistically significant ( P = 0.021). Median dFE was 8.3 mL/min/100 mL (IQR, 4.7 mL/min/100 mL), whereas median aFE was 15.4 mL/min/100 mL (IQR, 5.8 mL/min/100 mL). The difference in FE was statistically significant ( P < 0.001).
Conclusions: Our findings indicate that in perfusion CT of rectal carcinoma, adjustment of the Patlak range may significantly influence BV and FE compared with default setting of the software. This may contribute to standardization in the use of this technique for functional imaging of rectal cancer.
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http://dx.doi.org/10.1097/RCT.0000000000001506 | DOI Listing |
Phys Med Biol
December 2024
United Imaging Healthcare Group Co Ltd, 2258 Chengbei Rd., Jiading District, Shanghai, 201807, CHINA.
Objective: The objective is to generate reliable Ki parametric images from 18F-FDG total-body PET with clinically acceptable scan durations using Patlak and shallow machine learning algorithms, under conditions of limited computational and data resources.
Approach: We proposed a robust and fast algorithm named Patlak-KXD to generate Ki images from dynamic PET images with shortened scan durations. In the training phase, K-means is employed to generate a Ki-balanced training dataset.
J Nucl Med
October 2024
Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands; and.
Methods to shorten [F]FDG Patlak PET imaging procedures ranging from 65-90 to 20-30 min after injection, using a population-averaged input function (PIF) scaled to patient-specific image-derived input function (IDIF) values, were recently evaluated. The aim of the present study was to explore the feasibility of ultrashort 10-min [F]FDG Patlak imaging at 55-65 min after injection using a PIF combined with direct Patlak reconstructions to provide reliable quantitative accuracy of lung tumor uptake, compared with a full-duration 65-min acquisition using an IDIF. Patients underwent a 65-min dynamic PET acquisition on a long-axial-field-of-view (LAFOV) Biograph Vision Quadra PET/CT scanner.
View Article and Find Full Text PDFNeuroimage
October 2024
Molecular Imaging Biomarkers Group. Center for Research in Molecular Medicine and Chronic Diseases (CIMUS), University of Santiago de Compostela (USC), Campus Vida, Santiago de Compostela, Galicia, Spain; Nuclear Medicine Department and Molecular Imaging Biomarkers Group, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain; Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain. Electronic address:
Introduction SUV measurements from static brain [F]FDG PET acquisitions are a commonly used tool in preclinical research, providing a simple alternative for kinetic modelling, which requires complex and time-consuming dynamic acquisitions. However, SUV can be severely affected by the animal handling and preconditioning protocols, primarily by those that may induce changes in blood glucose levels (BGL). Here, we aimed at developing and investigating the feasibility of SUV-based approaches for a wide range of BGL far beyond normal values, and consequently, to develop and validate a new model to generate standardized and reproducible SUV measurements for any BGL.
View Article and Find Full Text PDFInt J Geriatr Psychiatry
October 2024
Clinical College of Neurology, Neurosurgery and Neurorehabilitation, Tianjin Medical University, Tianjin, China.
EJNMMI Res
February 2024
Department of Radiology and Nuclear Medicine, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands.
Background: Distribution of mAbs into tumour tissue may occur via different processes contributing differently to the Zr-mAb uptake on PET. Target-specific binding in tumours is of main interest; however, non-specific irreversible uptake may also be present, which influences quantification. The aim was to investigate the presence of non-specific irreversible uptake in tumour tissue using Patlak linearization on Zr-immuno-PET data of biopsy-proven target-negative tumours.
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