Novel spatial analysis method for PET images using 3D moment invariants: Applications to Parkinson's disease

Gonzalez, Marjorie; Dinelle, Katherine; Vafai, Nasim; Heffernan, Nicole; McKenzie, Jessamyn; Appel‐Cresswell, Silke; McKeown, Martin J.; Stoessl, A. Jon

doi:10.1016/j.neuroimage.2012.11.055

Cited by 19 publications

(9 citation statements)

References 55 publications

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“…This obviously depends on the radiotracer used. However, the vast majority of studies to date have been carried out using FDG (and static SUV images), with only a few examples of the use of other radiotracers, such as FET [36], FLT [5, 37], and DBTZ [16]. …”

Section: The Past: Clinical Potential and Underlying Motivationsmentioning

confidence: 99%

“…Several dozen studies investigating the clinical value of PET uptake heterogeneity (using TA or other methods) in various tumour types (including oesophageal, lung, rectal, breast, head and neck, and brain cancer, and lymphoma) as well as more recently in neurodegenerative diseases with PET [16, 43] and DAT SPECT [44] have been published in the last 4 years alone. More recently, a few studies have also focused on extracting features from both the PET and CT components (see the section Promising clinical results below).…”

Section: The Present: An Era Of Rapid Expansionmentioning

confidence: 99%

“…The heterogeneity of image voxel intensities can be quantified by different image processing and analysis methods, including texture analysis (TA) [3], fractal analysis [13], shape models [14–16], intensity histogram analysis [15, 17] and filtering combined with statistical and frequency-based methods [18]. This critical review focuses on the use of TA in PET/CT images, although for completeness a section dedicated to alternative heterogeneity metrics can be found in Supplementary material section 1.…”

Section: Introductionmentioning

confidence: 99%

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Characterization of PET/CT images using texture analysis: the past, the present… any future?

Hatt

Tixier

Pierce

et al. 2016

Eur J Nucl Med Mol Imaging

401

383

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After seminal papers over the period 2009 – 2011, the use of texture analysis of PET/CT images for quantification of intratumour uptake heterogeneity has received increasing attention in the last 4 years. Results are difficult to compare due to the heterogeneity of studies and lack of standardization. There are also numerous challenges to address. In this review we provide critical insights into the recent development of texture analysis for quantifying the heterogeneity in PET/CT images, identify issues and challenges, and offer recommendations for the use of texture analysis in clinical research. Numerous potentially confounding issues have been identified, related to the complex workflow for the calculation of textural features, and the dependency of features on various factors such as acquisition, image reconstruction, preprocessing, functional volume segmentation, and methods of establishing and quantifying correspondences with genomic and clinical metrics of interest. A lack of understanding of what the features may represent in terms of the underlying pathophysiological processes and the variability of technical implementation practices makes comparing results in the literature challenging, if not impossible. Since progress as a field requires pooling results, there is an urgent need for standardization and recommendations/guidelines to enable the field to move forward. We provide a list of correct formulae for usual features and recommendations regarding implementation. Studies on larger cohorts with robust statistical analysis and machine learning approaches are promising directions to evaluate the potential of this approach.

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Section: The Past: Clinical Potential and Underlying Motivationsmentioning

confidence: 99%

Section: The Present: An Era Of Rapid Expansionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Characterization of PET/CT images using texture analysis: the past, the present… any future?

Hatt

Tixier

Pierce

et al. 2016

Eur J Nucl Med Mol Imaging

401

383

View full text Add to dashboard Cite

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“…We have, in the past, investigated advanced texture analysis in the context of quantitative brain PET imaging, in studies of PD (Gonzalez et al, 2013, Klyuzhin et al, 2015, Sossi et al, 2012) and neuroinflammation (Rahmim et al, 2012). These techniques have the advantage of not requiring normalization/registration of ROIs to a common structure.…”

Section: Introductionmentioning

confidence: 99%

Application of texture analysis to DAT SPECT imaging: Relationship to clinical assessments

Rahmim

Salimpour

Jain

et al. 2016

NeuroImage: Clinical

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Dopamine transporter (DAT) SPECT imaging is increasingly utilized for diagnostic purposes in suspected Parkinsonian syndromes. We performed a cross-sectional study to investigate whether assessment of texture in DAT SPECT radiotracer uptake enables enhanced correlations with severity of motor and cognitive symptoms in Parkinson's disease (PD), with the long-term goal of enabling clinical utility of DAT SPECT imaging, beyond standard diagnostic tasks, to tracking of progression in PD. Quantitative analysis in routine DAT SPECT imaging, if performed at all, has been restricted to assessment of mean regional uptake. We applied a framework wherein textural features were extracted from the images. Notably, the framework did not require registration to a common template, and worked in the subject-native space. Image analysis included registration of SPECT images onto corresponding MRI images, automatic region-of-interest (ROI) extraction on the MRI images, followed by computation of Haralick texture features. We analyzed 141 subjects from the Parkinson's Progressive Marker Initiative (PPMI) database, including 85 PD and 56 healthy controls (HC) (baseline scans with accompanying 3 T MRI images). We performed univariate and multivariate regression analyses between the quantitative metrics and different clinical measures, namely (i) the UPDRS (part III - motor) score, disease duration as measured from (ii) time of diagnosis (DD-diag.) and (iii) time of appearance of symptoms (DD-sympt.), as well as (iv) the Montreal Cognitive Assessment (MoCA) score. For conventional mean uptake analysis in the putamen, we showed significant correlations with clinical measures only when both HC and PD were included (Pearson correlation r = − 0.74, p-value < 0.001). However, this was not significant when applied to PD subjects only (r = − 0.19, p-value = 0.084), and no such correlations were observed in the caudate. By contrast, for the PD subjects, significant correlations were observed in the caudate when including texture metrics, with (i) UPDRS (p-values < 0.01), (ii) DD-diag. (p-values < 0.001), (iii) DD-sympt (p-values < 0.05), and (iv) MoCA (p-values < 0.01), while no correlations were observed for conventional analysis (p-values = 0.94, 0.34, 0.88 and 0.96, respectively). Our results demonstrated the ability to capture valuable information using advanced texture metrics from striatal DAT SPECT, enabling significant correlations of striatal DAT binding with clinical, motor and cognitive outcomes, and suggesting that textural features hold potential as biomarkers of PD severity and progression.

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“…MIs are mathematical spatial descriptors designed to be invariant to scaling, translation and rotation, with extensive use in a number of areas including pattern recognition [7], and with recent in an tMRI study to assess spatial characteristics of voxel-based statistics [8]. We have recently demonstrated (i) significant shape differences in striatal ROI PET uptake between healthy controls and patients with Parkinson's disease (PD) imaged using pre-synaptic and post-synaptic radiotracers [9], and (ii) significant correlation of PD disease severity with shape (and change in shape upon administration of stimulant) [9,10]. Here we apply second order J" J], J3, Q and third-order B3 3D-MIs [8,11,12] to quantify ROI PET uptake.…”

Section: A Analysis Using 3d Moment Invariants (3d-mis)mentioning

confidence: 99%

Novel parametric PET image quantification using texture and shape analysis

Rahmim

Coughlin

Gonzalez

et al. 2012

2012 IEEE Nuclear Science Symposium and Medical Imaging Conference Record (NSS/MIC)

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Kinetic parameter estimation at the individual voxel level has the powerful ability to represent both spatial distributions and quantitative physiological parameters of interest. In practice, parametric images are commonly quantified by computing mean values for specified ROIs. Nonetheless, the mean operator vastly oversimplifies the available spatial uptake information. It may be hypothesized that a given tracer will exhibit increasingly differential or heterogeneous uptake due to disease: subsequently, we have implemented and explored a comprehensive texture and shape analysis framework wherein extensive information is generated from parametric PET images, through: (1) 3D moment invariants analysis, (2) intensity histogram analysis, (3) gray-level spatial-dependence (GLSD) analysis, and (4) neighborhood gray tone difference (NGTD) analysis. In the present work, we applied this approach to imaging of llC-DPA-713, a novel PET ligand with high binding to the translocator protein (TSPO), a marker of neuroinflammation. In particular, for tracers such as DPA with relatively wide-spread uptake, where a reliable reference tissue does not exist, quantification of heterogeneity may provide additional valuable information. Our center has been the first to perform DPA PET studies in humans, and is gathering a large collection of PET studies; e.g. subjects with systemic lupus erythematosus (SLE), traumatic brain injury (TBI; former NFL players), along with young and elderly controls. Our preliminary analysis has revealed that, compared to conventional mean ROI analysis, a number of metrics in the proposed framework yield enhanced discrimination (as measured using AVC) between patients vs. controls in a range of ROIs, in TBI as well as SLE vs. controls, consistent with increased heterogeneity of uptake with disease, though in the case of SLE this can be, at least partly, attributed to changes in ROI shapes. Overall, the proposed framework has the potential to bring about a new quantification paradigm in parametric imaging.

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Novel spatial analysis method for PET images using 3D moment invariants: Applications to Parkinson's disease

Cited by 19 publications

References 55 publications

Characterization of PET/CT images using texture analysis: the past, the present… any future?

Characterization of PET/CT images using texture analysis: the past, the present… any future?

Application of texture analysis to DAT SPECT imaging: Relationship to clinical assessments

Novel parametric PET image quantification using texture and shape analysis

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