Limits...
The effect of SUV discretization in quantitative FDG-PET Radiomics: the need for standardized methodology in tumor texture analysis.

Leijenaar RT, Nalbantov G, Carvalho S, van Elmpt WJ, Troost EG, Boellaard R, Aerts HJ, Gillies RJ, Lambin P - Sci Rep (2015)

Bottom Line: As part of the process of quantifying heterogeneity, image intensities (SUVs) are typically resampled into a reduced number of discrete bins.Overall, patients ranked differently according to feature values–which was used as a surrogate for textural feature interpretation–between both discretization methods.Our study shows that the manner of SUV discretization has a crucial effect on the resulting textural features and the interpretation thereof, emphasizing the importance of standardized methodology in tumor texture analysis.

View Article: PubMed Central - PubMed

Affiliation: Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre (MUMC+), Maastricht, the Netherlands.

ABSTRACT
FDG-PET-derived textural features describing intra-tumor heterogeneity are increasingly investigated as imaging biomarkers. As part of the process of quantifying heterogeneity, image intensities (SUVs) are typically resampled into a reduced number of discrete bins. We focused on the implications of the manner in which this discretization is implemented. Two methods were evaluated: (1) R(D), dividing the SUV range into D equally spaced bins, where the intensity resolution (i.e. bin size) varies per image; and (2) R(B), maintaining a constant intensity resolution B. Clinical feasibility was assessed on 35 lung cancer patients, imaged before and in the second week of radiotherapy. Forty-four textural features were determined for different D and B for both imaging time points. Feature values depended on the intensity resolution and out of both assessed methods, R(B) was shown to allow for a meaningful inter- and intra-patient comparison of feature values. Overall, patients ranked differently according to feature values–which was used as a surrogate for textural feature interpretation–between both discretization methods. Our study shows that the manner of SUV discretization has a crucial effect on the resulting textural features and the interpretation thereof, emphasizing the importance of standardized methodology in tumor texture analysis.

No MeSH data available.


Related in: MedlinePlus

Left column: Representative images of sequential imaging for one patient, showing pre-treatment imaging (a) and imaging during the second week of radiotherapy (b). The tumor delineation is outlined in green. Both images are displayed with the same window/level settings. Right column: Histograms of the pre-treatment and during treatment images, resampled with a fixed bin size (i.e. intensity resolution) (c) or a predefined number of bins (d). In (d), one can appreciate the difference in resulting intensity resolution when resampling with a fixed number of bins. Pre-treatment and during treatment intensity resolutions were 0.6 and 0.37 [SUV], respectively
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4525145&req=5

f2: Left column: Representative images of sequential imaging for one patient, showing pre-treatment imaging (a) and imaging during the second week of radiotherapy (b). The tumor delineation is outlined in green. Both images are displayed with the same window/level settings. Right column: Histograms of the pre-treatment and during treatment images, resampled with a fixed bin size (i.e. intensity resolution) (c) or a predefined number of bins (d). In (d), one can appreciate the difference in resulting intensity resolution when resampling with a fixed number of bins. Pre-treatment and during treatment intensity resolutions were 0.6 and 0.37 [SUV], respectively

Mentions: This study comprised 35 non-small cell lung cancer (NSCLC) patients who were prospectively included in a clinical trial (NCT00522639) and scheduled for radiotherapy and/or chemotherapy between July and December 200811. 18F-FDG-PET/CT imaging was performed on a Biograph 40 PET/CT scanner (Siemens Medical Solutions) twice: (1) after induction chemotherapy but before radiotherapy and (2) during the second week of radiotherapy (Fig. 2a,b). Patients fasted for at least six hours before imaging. The injected amount of 18F-FDG was (4 × body weight [kg] + 20) MBq. Patients rested 60 minutes before image acquisition. Patients’ blood glucose levels were below 10 mmol/L, so no correction for blood glucose level was applied.


The effect of SUV discretization in quantitative FDG-PET Radiomics: the need for standardized methodology in tumor texture analysis.

Leijenaar RT, Nalbantov G, Carvalho S, van Elmpt WJ, Troost EG, Boellaard R, Aerts HJ, Gillies RJ, Lambin P - Sci Rep (2015)

Left column: Representative images of sequential imaging for one patient, showing pre-treatment imaging (a) and imaging during the second week of radiotherapy (b). The tumor delineation is outlined in green. Both images are displayed with the same window/level settings. Right column: Histograms of the pre-treatment and during treatment images, resampled with a fixed bin size (i.e. intensity resolution) (c) or a predefined number of bins (d). In (d), one can appreciate the difference in resulting intensity resolution when resampling with a fixed number of bins. Pre-treatment and during treatment intensity resolutions were 0.6 and 0.37 [SUV], respectively
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4525145&req=5

f2: Left column: Representative images of sequential imaging for one patient, showing pre-treatment imaging (a) and imaging during the second week of radiotherapy (b). The tumor delineation is outlined in green. Both images are displayed with the same window/level settings. Right column: Histograms of the pre-treatment and during treatment images, resampled with a fixed bin size (i.e. intensity resolution) (c) or a predefined number of bins (d). In (d), one can appreciate the difference in resulting intensity resolution when resampling with a fixed number of bins. Pre-treatment and during treatment intensity resolutions were 0.6 and 0.37 [SUV], respectively
Mentions: This study comprised 35 non-small cell lung cancer (NSCLC) patients who were prospectively included in a clinical trial (NCT00522639) and scheduled for radiotherapy and/or chemotherapy between July and December 200811. 18F-FDG-PET/CT imaging was performed on a Biograph 40 PET/CT scanner (Siemens Medical Solutions) twice: (1) after induction chemotherapy but before radiotherapy and (2) during the second week of radiotherapy (Fig. 2a,b). Patients fasted for at least six hours before imaging. The injected amount of 18F-FDG was (4 × body weight [kg] + 20) MBq. Patients rested 60 minutes before image acquisition. Patients’ blood glucose levels were below 10 mmol/L, so no correction for blood glucose level was applied.

Bottom Line: As part of the process of quantifying heterogeneity, image intensities (SUVs) are typically resampled into a reduced number of discrete bins.Overall, patients ranked differently according to feature values–which was used as a surrogate for textural feature interpretation–between both discretization methods.Our study shows that the manner of SUV discretization has a crucial effect on the resulting textural features and the interpretation thereof, emphasizing the importance of standardized methodology in tumor texture analysis.

View Article: PubMed Central - PubMed

Affiliation: Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre (MUMC+), Maastricht, the Netherlands.

ABSTRACT
FDG-PET-derived textural features describing intra-tumor heterogeneity are increasingly investigated as imaging biomarkers. As part of the process of quantifying heterogeneity, image intensities (SUVs) are typically resampled into a reduced number of discrete bins. We focused on the implications of the manner in which this discretization is implemented. Two methods were evaluated: (1) R(D), dividing the SUV range into D equally spaced bins, where the intensity resolution (i.e. bin size) varies per image; and (2) R(B), maintaining a constant intensity resolution B. Clinical feasibility was assessed on 35 lung cancer patients, imaged before and in the second week of radiotherapy. Forty-four textural features were determined for different D and B for both imaging time points. Feature values depended on the intensity resolution and out of both assessed methods, R(B) was shown to allow for a meaningful inter- and intra-patient comparison of feature values. Overall, patients ranked differently according to feature values–which was used as a surrogate for textural feature interpretation–between both discretization methods. Our study shows that the manner of SUV discretization has a crucial effect on the resulting textural features and the interpretation thereof, emphasizing the importance of standardized methodology in tumor texture analysis.

No MeSH data available.


Related in: MedlinePlus