FDG uptake heterogeneity evaluated by fractal analysis improves the differential diagnosis of pulmonary nodules

Miwa, Koichi; Inubushi, Masayuki; Wagatsuma, Kei; Nagao, Michinobu; Murata, Takahiro; Koyama, Masamichi; Koizumi, Mitsuru; Sasaki, Masayuki

doi:10.1016/j.ejrad.2013.12.020

Cited by 70 publications

(53 citation statements)

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“…On the other hand, more recently the heterogeneity of 18 F-FDG uptake within tumors has been associated with treatment failure (4,(6)(7)(8). Proposed approaches to assessing the heterogeneity of intratumoral activity distribution include visual evaluation (9), SUV coefficient of variation (10), area under the curve of the cumulative histogram (11), and fractal (12) or textural feature analysis (10,13). The last of these can provide several parameters quantifying tumor heterogeneity on a scale of voxels or groups of voxels.…”

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confidence: 99%

¹⁸F-FDG PET Uptake Characterization Through Texture Analysis: Investigating the Complementary Nature of Heterogeneity and Functional Tumor Volume in a Multi–Cancer Site Patient Cohort

et al. 2014

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Intratumoral uptake heterogeneity in 18 F-FDG PET has been associated with patient treatment outcomes in several cancer types. Textural feature analysis is a promising method for its quantification. An open issue associated with textural features for the quantification of intratumoral heterogeneity concerns its added contribution and dependence on the metabolically active tumor volume (MATV), which has already been shown to be a significant predictive and prognostic parameter. Our objective was to address this question using a larger cohort of patients covering different cancer types. Methods: A single database of 555 pretreatment 18 F-FDG PET images (breast, cervix, esophageal, head and neck, and lung cancer tumors) was assembled. Four robust and reproducible textural feature-derived parameters were considered. The issues associated with the calculation of textural features using co-occurrence matrices (such as the quantization and spatial directionality relationships) were also investigated. The relationship between these features and MATV, as well as among the features themselves, was investigated using Spearman rank coefficients for different volume ranges. The complementary prognostic value of MATV and textural features was assessed through multivariate Cox analysis in the esophageal and non-small cell lung cancer (NSCLC) cohorts. Results: A large range of MATVs was included in the population considered (3-415 cm 3 ; mean, 35; median,19; SD, 50). The correlation between MATV and textural features varied greatly depending on the MATVs, with reduced correlation for increasing volumes. These findings were reproducible across the different cancer types. The quantization and calculation methods both had an impact on the correlation. Volume and heterogeneity were independent prognostic factors (P 5 0.0053 and 0.0093, respectively) along with stage (P 5 0.002) in non-small cell lung cancer, but in the esophageal tumors, volume and heterogeneity had less complementary value because of smaller overall volumes. Conclusion: Our results suggest that heterogeneity quantification and volume may provide valuable complementary information for volumes above 10 cm 3 , although the complementary information increases substantially with larger volumes. Fordi agnosis and staging in oncology, 18 F-FDG PET/CT is a powerful tool (1). Its use in therapy assessment (2,3) is increasing. Within this context, more emphasis is being given to image-derived indices (4). On the one hand, features extracted from PET images, including metabolically active tumor volume (MATV), mean standardized uptake value (SUV), and total lesion glycolysis, have provided potentially higher prognostic value than standard maximum SUV in various cancer types (5). On the other hand, more recently the heterogeneity of 18 F-FDG uptake within tumors has been associated with treatment failure (4,6-8). Proposed approaches to assessing the heterogeneity of intratumoral activity distribution include visual evaluation (9), SUV coefficient of variation (10), area under...

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confidence: 99%

¹⁸F-FDG PET Uptake Characterization Through Texture Analysis: Investigating the Complementary Nature of Heterogeneity and Functional Tumor Volume in a Multi–Cancer Site Patient Cohort

et al. 2014

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“…), la forme et l'hétérogénéité, a contrario, peuvent être mesurées, quantifiées et caractérisées à l'aide d'un très grand nombre de paramètres et de méthodes (Section 3). Le faible nombre de travaux de standardisation ou d'études comparatives permettant d'identifier les paramètres les plus fiables, pose alors problème et constitue un facteur limitant pour l'adoption de ces nouveaux indices, malgré leur popularité croissante dans la communauté scientifique et clinique, comme le suggère le nombre étonnant de revues et éditoriaux déjà publiés sur le sujet en quelques années seulement [8,[12][13][14][15][16][17][18][19][20][21].…”

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Nouveaux indices en TEP/TDM : mythe et réalités

et al. 2015

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Reçu le 8 mars 2015 ; accepté le 12 mars 2015Disponible sur Internet le 7 avril 2015 RésuméLe rôle de l'imagerie multimodalité couplant la tomographie par émission de positons (TEP) et la tomodensitométrie (TDM) est devenu de plus en plus important en oncologie. Son utilisation en routine clinique et dans la majorité des travaux de recherche clinique se limite toutefois à des analyses manuelles et visuelles et par l'utilisation de métriques réductrices, comme le SUV max , qui ne représente qu'un seul voxel de la tumeur. D'autres paramètres quantifiant la tumeur de façon plus complète, comme le volume métabolique ou le total lesion glycolysis (TLG, produit du volume et du SUV moyen dans le volume) sont de plus en plus souvent évalués. Depuis quelques années, plusieurs travaux ont étudié la valeur potentielle de nouveaux paramètres caractérisant la forme géométrique ou l'hétérogénéité intratumorale du radiotraceur. Nous faisons le point ici sur quatre aspects du développement de ces nouveaux indices en imagerie TEP : (i) les motivations sous-jacentes à leur utilisation ; (ii) les obstacles à surmonter pour leur mise en oeuvre ; (iii) les problématiques méthodologiques de leur définition ; (iv) leurs potentielles valeurs cliniques et les défis futurs à relever pour les valider. # 2015 Elsevier Masson SAS. Tous droits réservés. AbstractThe role of multimodality imaging based on the use of positron emission tomography (PET) coupled to computerised tomography (CT) is continuously gaining ground in the field of oncology. The use of the technique in routine clinical practice is based on a visual interpretation or the determination of parameters such as the maximum standardised uptake value representing the highest activity voxel within the tumor. Other semiquantitative parameters including the metabolic tumor volume and the total lesion glycolysis are increasingly used in the literature. More recently, alternative image derived parameters characterizing the tumor form and the heterogeneity in the intratumour activity distribution have been proposed. The objective of this article is to cover different aspects on these novel image derived indices, including: (i) the motivation behind their introduction and current use; (ii) obstacles in their utilization; (iii) methodological issues on their definition; (iv) their potential interest for future use in clinical practice. #

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“…The fractal dimension (FD) is a quantitative metric obtained as a slope of the logarithmical function between the number of voxels with a SUV higher than the threshold and a threshold of a percent of the maximum SUV. Although these methods have been reported to be useful for the evaluation of malignant tumors in the clinical setting [6,7], it has been suggested that factors such as partial volume effect (PVE) and image noise may influence the results [7]. In lung cancer, respiratory motion causes the deterioration of image quality and reduces FDG uptake due to image blurring [12,13].…”

Section: Introductionmentioning

confidence: 98%

“…Recently, heterogeneity in the intratumoral uptake of FDG has received focus as a new metric of evaluating malignant tumors [5]. Heterogeneity in the intratumoral uptake of FDG has been reported to be useful for the differential diagnosis between malignant and benign lung tumors and for evaluating the treatment response in lung cancer [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

“…Although many methods for evaluating the heterogeneity of intratumoral FDG uptake have been proposed [6,[9][10][11], cumulative SUV-volume histograms (CSH) and fractal analyses are considered to be simple methods for quantifying the intratumoral heterogeneity of FDG uptake [6,7]. CSH is obtained by plotting the percent area of a tumor with an SUV above a certain threshold against that threshold.…”

Section: Introductionmentioning

confidence: 99%

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The influence of respiratory motion on the cumulative SUV-volume histogram and fractal analyses of intratumoral heterogeneity in PET/CT imaging

et al. 2016

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FDG uptake heterogeneity evaluated by fractal analysis improves the differential diagnosis of pulmonary nodules

Cited by 70 publications

References 19 publications

¹⁸F-FDG PET Uptake Characterization Through Texture Analysis: Investigating the Complementary Nature of Heterogeneity and Functional Tumor Volume in a Multi–Cancer Site Patient Cohort

¹⁸F-FDG PET Uptake Characterization Through Texture Analysis: Investigating the Complementary Nature of Heterogeneity and Functional Tumor Volume in a Multi–Cancer Site Patient Cohort

Nouveaux indices en TEP/TDM : mythe et réalités

The influence of respiratory motion on the cumulative SUV-volume histogram and fractal analyses of intratumoral heterogeneity in PET/CT imaging

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FDG uptake heterogeneity evaluated by fractal analysis improves the differential diagnosis of pulmonary nodules

Cited by 70 publications

References 19 publications

18F-FDG PET Uptake Characterization Through Texture Analysis: Investigating the Complementary Nature of Heterogeneity and Functional Tumor Volume in a Multi–Cancer Site Patient Cohort

18F-FDG PET Uptake Characterization Through Texture Analysis: Investigating the Complementary Nature of Heterogeneity and Functional Tumor Volume in a Multi–Cancer Site Patient Cohort

Nouveaux indices en TEP/TDM : mythe et réalités

The influence of respiratory motion on the cumulative SUV-volume histogram and fractal analyses of intratumoral heterogeneity in PET/CT imaging

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¹⁸F-FDG PET Uptake Characterization Through Texture Analysis: Investigating the Complementary Nature of Heterogeneity and Functional Tumor Volume in a Multi–Cancer Site Patient Cohort

¹⁸F-FDG PET Uptake Characterization Through Texture Analysis: Investigating the Complementary Nature of Heterogeneity and Functional Tumor Volume in a Multi–Cancer Site Patient Cohort