Comparative evaluation of scatter correction techniques in 3D positron emission tomography

Much research and development has been concentrated on the scatter compensation required for quantitative 3D PET. Increasingly sophisticated scatter correction procedures are under investigation, particularly those based on accurate scatter models, and iterative reconstruction-based scatter compensation approaches. The main difference among the correction methods is the way in which the scatter component in the selected energy window is estimated. Monte Carlo methods give further insight and might in themselves offer a possible correction procedure. Methods: Five scatter correction methods are compared in this paper where applicable. The dual-energy window (DEW) technique, the convolution-subtraction (CVS) method, two variants of the Monte Carlo-based scatter correction technique (MCBSC1 and MCBSC2) and our newly developed statistical reconstruction-based scatter correction (SRBSC) method. These scatter correction techniques are evaluated using Monte Carlo simulation studies, experimental phantom measurements, and clinical studies. Accurate Monte Carlo modelling is still the gold standard since it allows to separate scattered and unscattered events and compare the estimated and true unscattered component. Results: In this study, our modified version of Monte Carlo-based scatter correction (MCBSC2) seems to provide a good contrast recovery on the simulated Utah phantom, while the DEW method was found to be clearly superior for the experimental phantom studies in terms of quantitative accuracy at the expense of a significant deterioration of the signal-to-noise ratio. On the other hand, the immunity to noise in emission data of statistical reconstruction-based scatter correction methods make them particularly applicable to low-count emission studies. All scatter correction methods give very good activity recovery values for the simulated 3D Hoffman brain phantom which average within 3%. The CVS and MCBSC1 techniques tend to overcorrect while SRBSC undercorrects for scatter in most regions of this phantom. Conclusion: It was concluded that all correction methods significantly improved the image quality and contrast compared to the case where no correction is applied. Generally, it was shown that the differences in the estimated scatter distributions did not have a significant impact on the final quantitative results. The DEW method showed the best compromise between ease of implementation and quantitative accuracy, but significantly deteriorates the signal-noise ratio

Relevance of accurate Monte Carlo modeling in nuclear medical imaging

Monte Carlo techniques have become popular in different areas of medical physics with advantage of powerful computing systems. In particular, they have been extensively applied to simulate processes involving random behavior and to quantify physical parameters that are difficult or even impossible to calculate by experimental measurements. Recent nuclear medical imaging innovations such as single-photon emission computed tomography (SPECT), positron emission tomography (PET), and multiple emission tomography (MET) are ideal for Monte Carlo modeling techniques because of the stochastic nature of radiation emission, transport and detection processes. Factors which have contributed to the wider use include improved models of radiation transport processes, the practicality of application with the development of acceleration schemes and the improved speed of computers. This paper presents derivation and methodological basis for this approach and critically reviews their areas of application in nuclear imaging. An overview of existing simulation programs is provided and illustrated with examples of some useful features of such sophisticated tools in connection with common computing facilities and more powerful multiple-processor parallel processing systems. Current and future trends in the field are also discussed

ASSESSMENT OF NEW INNOVATIONS IN PET/CT FOR RESPIRATORY MOTION CORRECTION

In oncological imaging, Positron Emission Tomography/Computed Tomography (PET/CT) is a vital tool used for stating and treatment response assessment of patients due to its ability to visualize and accurately quantify the bio-distribution of radiolabeled pharmaceuticals. However, due to the long acquisition times, respiratory motion blur is unavoidable in PET images especially in the lower lung and upper abdomen. This leads to reductions in measured radiotracer concentration and lesion detectability all of which can potentially result in incorrect management of patients. Multiple methods exist to correct for respiratory motion but are rarely used in the routine clinical setting because of: 1) increased image noise due to the rejection of motion blurred data; 2) burdensome workflows which require setup and troubleshooting of external hardware needed to track patient breathing; 3) and ineffective respiratory motion correction due to irregular patient breathing potentially caused by the abrupt bed transitions during step and shoot (SS) whole body PET acquisition. Our goal of this Ph.D. dissertation is to address these three issues by evaluating 1) a precommercial version of a vendor designed elastic motion correction (EMC) algorithm which uses all of the acquired PET data resulting in reduced image noise; 2) a pre-commercial version of a vendor designed data driven gating (DDG) algorithm, which determines the respiratory waveform from the PET data alone, thereby removing the need for and challenges of external hardware; 3) the effect of using continuous bed motion (CBM) as compared to SS as a means to minimize the irregularity of patient breathing. vii The results of these evaluations showed that the EMC algorithm performed similarly to conventional respiratory motion correction techniques with respect to radiotracer quantification, however, due to using all of the acquired PET data, the EMC algorithm showed improved performance resulting in the lowest amount of image noise, improved contrast to noise ratio, and had the highest overall image quality scores as assessed by independent observers. Evaluation of the CBM DDG algorithm showed that in comparison to an external device, the measured respiratory waveforms, radiotracer quantification, and assessment of the presence of respiratory motion blur were similar, demonstrating that the CBM DDG algorithm holds promise as a replacement to external hardware devices currently needed to measure respiratory waveforms and hence could potentially simplify the data acquisition workflow. Finally, we found no statistically significant differences between the CBM and SS PET acquisition modes with respect to the regularity of respiratory waveforms, radiotracer quantification, contrast to noise ratio and perceptions of respiratory motion blur. In conclusion, although no reductions of irregular breathing were found between CBM and SS, improvements in image quality through the use of EMC and reductions of workflow complexity through the use of DDG will hopefully facilitate the routine adoption of respiratory motion correction in PET/CT

Image processing software for seizure onset zone localization in refractory epilepsy

Treballs Finals de Grau d'Enginyeria Biomèdica. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona. Curs: 2020-2021. Directora: Aida Niñerola Baizán. Tutors: Aida Niñerola and Raúl TudelaEpilepsy is one of the most common serious neurological disorders in the world and a 30-40% of the affected population is resistant to the pharmacological treatment (refractory epilepsy). A possible treatment for them is the surgical resection of the epileptogenic zone (EZ). The success of the surgical treatment is fundamentally determined by the accuracy of presurgical identification of the EZ based on a variety of diagnostic tests. Among them, PISCOM technique is a multimodal imaging processing algorithm, useful for this purpose, yet not incorporated into clinical routine. This project aims to develop an ergonomic and user-friendly graphical interface that integrates the PISCOM algorithm to make the process become easy and accessible for clinicians. To create the graphical interface, different software environments were studied. The solution chosen was to develop an extension for 3D Slicer, an open-source software package used for medical and biomedical imaging research, and the processing method was therefore adapted to the new platform. The result was assessed with a clinic questionnaire filled out by two nuclear medicine physicians of Hospital Clínic de Barcelona after an introduction session of the developed extension. The extension was considered to be a user-friendly tool for applying the PISCOM technique, that fulfilled their requirements, and with future potential. Some next steps to improve the user experience were suggested..

Simulation of Clinical PET Studies for the Assessment of Quantification Methods

On this PhD thesis we developed a methodology for evaluating the robustness of SUV measurements based on MC simulations and the generation of novel databases of simulated studies based on digital anthropomorphic phantoms. This methodology has been applied to different problems related to quantification that were not previously addressed. Two methods for estimating the extravasated dose were proposed andvalidated in different scenarios using MC simulations. We studied the impact of noise and low counting in the accuracy and repeatability of three commonly used SUV metrics (SUVmax, SUVmean and SUV50). The same model was used to study the effect of physiological muscular uptake variations on the quantification of FDG-PET studies. Finally, our MC models were applied to simulate 18F-fluorocholine (FCH) studies. The aim was to study the effect of spill-in counts from neighbouring regions on the quantification of small regions close to high activity extended sources

MR-based attenuation correction and scatter correction in neurological PET/MR imaging with 18F-FDG

The aim was to investigate the effects of MR-based attenuation correction (MRAC) and scatter correction to positron emission tomography (PET) image quantification in neurological PET/MR with 18F-FDG. A multi-center phantom study was conducted to investigate the effect of MRAC between PET/MR and PET/CT systems (I). An MRAC method to derive bone from T1-weighted MR images was developed (II, III). Finally, scatter correction accuracy with MRAC was investigated (IV). The results show that the quantitative accuracy in PET is well-comparable be-tween PET/MR and PET/CT systems when an attenuation correction method resembling CT-based attenuation correction (CTAC) is implemented. This al-lows achieving of a PET bias within standard uptake value (SUV) quantification repeatability (< 10 % error) and is within the repeatability of PET in most sys-tems and brain regions (< 5 % error). In addition, MRAC considering soft tissue, air and bone can be derived using T1-weighted images alone. The improved version of the MRAC method allows achieving a quantitative accuracy feasible for advanced applications (< 5 % error). MRAC has a minor effect on the scatter correction accuracy (< 3 % error), even when using MRAC without bone. In conclusion, MRAC can be considered the largest contributing factor to PET quantification bias in 18F-FDG neurological PET/MR. This finding is not explicitly limited only to 18F-FDG imaging. Once an MRAC method that performs close to CTAC is implemented, there is no reason why a PET/MR system would perform differently from a PET/CT system. Such an MRAC method has been developed and is freely available (http://bit.ly/2fx6Jjz). Scatter correction can be considered a non-issue in neurological PET/MR imaging when using 18F-FD

Approaches for the optimization of MR protocols in clinical hybrid PET/MRI studies

Magnetic resonance imaging (MRI) is the examination method of choice for the diagnosis of a variety of diseases. MRI allows us to obtain not only anatomical information but also identification of physiological and functional parameters such as networks in the brain and tumor cellularity, which plays an increasing role in oncologic imaging, as well as blood flow and tissue perfusion. However, in many cases such as in epilepsy, degenerative neurological diseases and oncological processes, additional metabolic and molecular information obtained by PET can provide essential complementary information for better diagnosis. The combined information obtained from MRI and PET acquired in a single imaging session allows a more accurate localization of pathological findings and better assessment of the underlying physiopathology, thus providing a more powerful diagnostic tool. Two hundred and twenty-one patients were scanned from April 2011 to January 2012 on a Philips Ingenuity TF PET/MRI system. The purpose of this review article is to provide an overview of the techniques used for the optimization of different protocols performed in our hospital by specialists in the following fields: neuroradiology, head and neck, breast, and prostate imaging. This paper also discusses the different problems encountered, such as the length of studies, motion artifacts, and accuracy of image fusion including physical and technical aspects, and the proposed solution