Iterative Structural and Functional Synergistic Resolution Recovery (iSFS-RR) Applied to PET-MR Images in Epilepsy

Structural Functional Synergistic Resolution Recovery (SFS-RR) is a technique that uses supplementary structural information from MR or CT to improve the spatial resolution of PET or SPECT images. This wavelet-based method may have a potential impact on the clinical decision-making of brain focal disorders such as refractory epilepsy, since it can produce images with better quantitative accuracy and enhanced detectability. In this work, a method for the iterative application of SFS-RR (iSFS-RR) was firstly developed and optimized in terms of convergence and input voxel size, and the corrected images were used for the diagnosis of 18 patients with refractory epilepsy. To this end, PET/MR images were clinically evaluated through visual inspection, atlas-based asymmetry indices (AIs) and SPM (Statistical Parametric Mapping) analysis, using uncorrected images and images corrected with SFS-RR and iSFS-RR. Our results showed that the sensitivity can be increased from 78% for uncorrected images, to 84% for SFS-RR and 94% for the proposed iSFS-RR. Thus, the proposed methodology has demonstrated the potential to improve the management of refractory epilepsy patients in the clinical routine

Epileptogenic Zone Localization With 18FDG PET Using a New Dynamic Parametric Analysis

Introduction: [18F]fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) is part of the regular preoperative work-up in medically refractory epilepsy. As a complement to visual evaluation of PET, statistical parametric maps can help in the detection of the epileptogenic zone (EZ). However, software packages currently available are time-consuming and little intuitive for physicians. We develop a user-friendly software (referred as PET-analysis) for EZ localization in PET studies that allows dynamic real-time statistical parametric analysis. To evaluate its performance, the outcome of PET-analysis was compared with the results obtained by visual assessment and Statistical Parametric Mapping (SPM).Methods: Thirty patients with medically refractory epilepsy who underwent presurgical 18F-FDG PET with good post-operative outcomes were included. The 18F-FDG PET studies were evaluated by visual assessment, with SPM8 and PET-analysis. In SPM, parametric T-maps were thresholded at corrected p < 0.05 and cluster size k = 50 and at uncorrected p < 0.001 and k = 100 (the most used parameters in the literature). Since PET-analysis rapidly processes different threshold combinations, T-maps were thresholded with multiple p-value and different clusters sizes. The presurgical EZ identified by visual assessment, SPM and PET-analysis was compared to the confirmed EZ according to post-surgical follow-up.Results: PET-analysis obtained 66.7% (20/30) of correctly localizing studies, comparable to the 70.0% (21/30) achieved by visual assessment and significantly higher (p < 0.05) than that obtained with the SPM threshold p < 0.001/k = 100, of 36.7% (11/30). Only one study was positive, albeit non-localizing, with the SPM threshold corrected p < 0.05/k = 50. Concordance was substantial for PET-analysis (κ = 0.643) and visual interpretation (κ = 0.622), being fair for SPM (κ = 0.242).Conclusion: Compared to SPM with the fixed standard parameters, PET-analysis may be superior in EZ localization with its easy and rapid processing of different threshold combinations. The results of this initial proof-of-concept study validate the clinical use of PET-analysis as a robust objective complementary tool to visual assessment for EZ localization

Image processing methods for human brain connectivity analysis from in-vivo diffusion MRI

The structural connectivity of the brain is considered to encode species-wise and subject-wise patterns that will unlock large areas of understanding of the human brain. Currently, diffusion MRI of the living brain enables to map the microstructure of tissue, allowing to track the pathways of fiber bundles connecting the cortical regions across the brain. These bundles are summarized in a network representation called connectome that is analyzed using graph theory. The extraction of the connectome from diffusion MRI requires a large processing flow including image enhancement, reconstruction, segmentation, registration, diffusion tracking, etc. Although a concerted effort has been devoted to the definition of standard pipelines for the connectome extraction, it is still crucial to define quality assessment protocols of these workflows. The definition of quality control protocols is hindered by the complexity of the pipelines under test and the absolute lack of gold-standards for diffusion MRI data. Here we characterize the impact on structural connectivity workflows of the geometrical deformation typically shown by diffusion MRI data due to the inhomogeneity of magnetic susceptibility across the imaged object. We propose an evaluation framework to compare the existing methodologies to correct for these artifacts including whole-brain realistic phantoms. Additionally, we design and implement an image segmentation and registration method to avoid performing the correction task and to enable processing in the native space of diffusion data. We release PySDCev, an evaluation framework for the quality control of connectivity pipelines, specialized in the study of susceptibility-derived distortions. In this context, we propose Diffantom, a whole-brain phantom that provides a solution to the lack of gold-standard data. The three correction methodologies under comparison performed reasonably, and it is difficult to determine which method is more advisable. We demonstrate that susceptibility-derived correction is necessary to increase the sensitivity of connectivity pipelines, at the cost of specificity. Finally, with the registration and segmentation tool called regseg we demonstrate how the problem of susceptibility-derived distortion can be overcome allowing data to be used in their original coordinates. This is crucial to increase the sensitivity of the whole pipeline without any loss in specificity

Tomografía por Emisión de Positrones cuantificada en la evaluación prequirúrgica de la epilepsia

[spa] La epilepsia es una enfermedad con una elevada prevalencia e impacto sociosanitario. Aproximadamente un tercio de los pacientes son resistentes al tratamiento farmacológico y en estos casos debe considerarse la cirugía como la única opción potencialmente curativa. El éxito de la cirugía de la epilepsia está directamente relacionado con la precisa localización y resección del córtex epileptógeno, por lo que es crucial realizar una exhaustiva valoración prequirúrgica considerando varias modalidades diagnósticas. Los estudios de neuroimagen funcional como la PET, analizados visual y objetivamente mediante programas informáticos específicos, pueden desempeñar un papel decisivo en este contexto. Este trabajo de investigación se ha basado en la publicación dos estudios. En el primer estudio se incluyeron retrospectivamente 55 pacientes con epilepsia resistente al tratamiento farmacológico a los que se les realizó una PET con 18F-FDG que se interpretó como normal o con hallazgos muy sutiles o dudosos al análisis visual. De entre los pacientes incluidos, 20 habían sido operados con buenos resultados postquirúrgicos (Engel I-II). Se analizaron todos los estudios PET con SPM. Se usaron como dinteles de segmentación un valor de p corregido de p<0,05 con un tamaño mínimo de cluster k=0 (combinación 1 o C1), y tres valores de p no corregidos que eran gradualmente mayores con tamaños mínimos de cluster que también eran progresivamente de mayor tamaño. Estas tres combinaciones fueron p<0,0001 con k=20 (C2), p<0,001 con k=100 (C3) y p=0,005 con k=200 (C4). SPM evidenció áreas hipometabólicas en los estudios PET dudosos o negativos al análisis visual incluídos con los cuatro dinteles. La localización correcta de la ZE aumentó de forma progresiva desde el dintel con valor de p más restrictivo hasta el más liberal (de C1 a C4). En el grupo de pacientes operados, la proporción máxima de estudios correctamente localizadores se obtuvo con el dintel C4, que fue del 55% (11/20), una proporción ligeramente inferior al 65% (13/20) obtenido con la RM. Sin embargo, no se encontraron diferencias estadísticamente significativas entre estas dos proporciones. C3 fue el segundo dintel con la máxima proporción de estudios correctamente localizadores, acertando en la localización de la ZE en el 40% (8/20) de los pacientes operados. En el análisis global de los 55 pacientes, C4 también obtuvo la máxima proporción con un 40% (22/55) de estudios correctamente localizadores, y C3 obtuvo la segunda máxima proporción con un 29.1% (16/55). El aumento progresivo de estudios positivos de C1 a C4 no conllevó un aumento relevante en la proporción de estudios falsamente localizadores. Hubo tres pacientes operados en los que ni la RM ni la PET con SPM detectaron algun área que potencialmente pudiese ser la ZE. La concordancia entre la ZE y el dintel C1 fue justa y moderada con C2, C3 y C4. Cuando se analizó por separado a los pacientes operados las concordancias aumentaron, siendo substancial para C2 (к = 0,696; 95% IC 0,303–1,000) y C4 (к = 0,607; 95% IC 0,258–0,957), valores similares a los obtenidos con la RM (к = 0,783; 95% IC 0,509–1,000). Cuatro pacientes que tuvieron estudios de RM negativos o falsamente localizadores de la ZE tuvieron estudios PET correctamente localizadores tras el análisis con SPM. En el segundo estudio se incluyeron 30 pacientes con epilepsia refractaria al tratamiento farmacológico a los que se realizó una PET con 18F-FDG y que tuvieron unos resultados posoperatorios óptimos. Los estudios PET se evaluaron visualmente, con SPM y con PET-analysis. Para el análisis con SPM, se usaron los dinteles p corregida 50 y p no corregida 100. Como PET-analysis procesa rápidamente varias combinaciones de dinteles de significación, se usaron múltiples dinteles basados en combinaciones de diferentes desviaciones estándar y tamaños de cluster. PET-analysis obtuvo un 66,7% (20/30) de estudios correctamente localizadores de la ZE, comparable con el 70,0% (21/30) obtenido mediante el análisis visual y significativamente superior (p100, que obtuvo 36,7% (11/30). Sólo un estudio fue positivo, aunque no localizador, con el dintel de SPM p50. En cuanto a la RM, un 16/30 (53,3%) de los estudios fueron correctamente localizadores. La concordancia de la ZE posquirúrgica fue sustancial con PET-analysis (к=0,643, IC95% 0,439-0,847) y la interpretación visual (к=0,622, IC95% 0,367-0,877), pero fue débil con SPM (к=0,242, IC95% 0,028-0,455) y moderada con la RM (к=0,520, IC95% 0,268-0,772). En comparación con SPM, PET-analysis podría ser superior para la localización de la ZE con su procesado rápido y sencillo de diferentes combinaciones de dinteles de significación. Los resultados de este estudio validan el uso clínico de PET-analysis como una herramienta robusta complementaria al análisis visual en la localización de la ZE.[eng] FIRST ARTICLE SUMMARY Seizure onset zone localization by Statistical Parametric Mapping in visually normal 18F-FDG PET studies Introduction and objective: Neuroimaging is crucial in the presurgical evaluation of patients with medically refractory epilepsy. To improve the moderate sensitivity of [18F]fluorodeoxyglucose (18F-FDG) positron emission tomograpghy (PET) our aim was to evaluate the usefulness of Statistical Parametric Mapping (SPM) to localize the seizure onset zone (SOZ) in PET studies deemed normal by visual assessment. Methods: Fifty-five patients with medically refractory epilepsy whose 18F-FDG PET was visually evaluated as normal were retrospectively included. Twenty of these patients were surgically-intervened. PET images were analysed by SPM8 using a corrected p value of p0, k>20, k>100 and k>200, respectively. The SPM-identified potential seizure zone (SZ) was compared to the SOZ, which was determined by consensus during patient management meetings in the Epilepsy Unit, taking into account presurgical tests. Studies in which the SPM-identified potential SZ was concordant with the SOZ were considered “correctly localizing”. Results: The SPM threshold combination with the least restrictive p-value and greatest minimum cluster size achieved the highest rate of correctly localizing studies. When p200 was used, 40% (22/55) of studies were correctly localizing, and the concordance obtained in the surgically-intervened subgroup was substantial (к=0.607, CI95% 0.258,0.957), which was comparable to the concordance obtained by MRI (к=0.783, CI95% 0.509,1.000). Conclusion: SPM offers improved SOZ localization in 18F-FDG PET studies that are negative on visual assessment. For this purpose, statistical parametric maps could be thresholded with liberal p-values and restrictive cluster sizes. SECOND ARTICLE SUMMARY Epileptogenic Zone Localization with 18FDG PET Using a New Dynamic Parametric Analysis Introduction and objective: [18F]fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) is part of the regular preoperative work-up in medically refractory epilepsy. As a complement to visual evaluation of PET, statistical parametric maps can help in the detection of the epileptogenic zone (EZ). However, software packages currently available are time-consuming and little intuitive for physicians. We develop a user-friendly software (referred as PET-analysis) for EZ localization in PET studies that allows dynamic real-time statistical parametric analysis. To evaluate its performance, the outcome of PET-analysis was compared with the results obtained by visual assessment and Statistical Parametric Mapping (SPM). Methods: Thirty patients with medically refractory epilepsy who underwent presurgical 18F-FDG PET with good postoperative outcomes were included. The 18F-FDG PET studies were evaluated by visual assessment, with SPM8 and PET-analysis. In SPM, parametric T-maps were thresholded at corrected p<0.05 and cluster size k=50 and at uncorrected p<0.001 and k=100 (the most used parameters in the literature). Since PET-analysis rapidly processes different threshold combinations, T-maps were thresholded with multiple p-value and different clusters sizes. The presurgical EZ identified by visual assessment, SPM and PET-analysis was compared to the confirmed EZ according to postsurgical follow-up. Results: PET-analysis obtained 66.7% (20/30) of correctly localizing studies, comparable to the 70.0% (21/30) achieved by visual assessment and significantly higher (p<0.05) than that obtained with the SPM threshold p<0.001/k=100, of 36.7% (11/30). Only one study was positive, albeit non-localizing, with the SPM threshold corrected p<0.05/k=50. Concordance was substantial for PET-analysis (к=0.643) and visual interpretation (к=0.622), being fair for SPM (к=0.242). Conclusion: Compared to SPM with the fixed standard parameters, PET-analysis may be superior in EZ localization with its easy and rapid processing of different threshold combinations. The results of this initial proof-of-concept study validate the clinical use of PET-analysis as a robust objective complementary tool to visual assessment for EZ localization

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

FocusDET, a new toolbox for SISCOM analysis. Evaluation of the registration accuracy using monte carlo simulation

Subtraction of Ictal SPECT Co-registered to MRI (SISCOM) is an imaging technique used to localize the epileptogenic focus in patients with intractable partial epilepsy. The aim of this study was to determine the accuracy of registration algorithms involved in SISCOM analysis using FocusDET, a new user-friendly application. To this end, Monte Carlo simulation was employed to generate realistic SPECT studies. Simulated sinograms were reconstructed by using the Filtered BackProjection (FBP) algorithm and an Ordered Subsets Expectation Maximization (OSEM) reconstruction method that included compensation for all degradations. Registration errors in SPECT-SPECT and SPECT-MRI registration were evaluated by comparing the theoretical and actual transforms. Patient studies with well-localized epilepsy were also included in the registration assessment. Global registration errors including SPECT-SPECT and SPECT-MRI registration errors were less than 1.2 mm on average, exceeding the voxel size (3.32 mm) of SPECT studies in no case. Although images reconstructed using OSEM led to lower registration errors than images reconstructed with FBP, differences after using OSEM or FBP in reconstruction were less than 0.2 mm on average. This indicates that correction for degradations does not play a major role in the SISCOM process, thereby facilitating the application of the methodology in centers where OSEM is not implemented with correction of all degradations. These findings together with those obtained by clinicians from patients via MRI, interictal and ictal SPECT and video-EEG, show that FocusDET is a robust application for performing SISCOM analysis in clinical practice