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Differentiation between primary cerebral lymphoma and glioblastoma using the apparent diffusion coefficient: comparison of three different ROI methods.

Ahn SJ, Shin HJ, Chang JH, Lee SK - PLoS ONE (2014)

Bottom Line: ADCs from ROI1 showed most reproducible results (ICC >0.9).ADCs from the whole tumor volume had the most reproducible results.However, multi-modal imaging approaches are recommended than ADC alone for differentiation.

View Article: PubMed Central - PubMed

Affiliation: From the Department of Radiology, Severance Hospital, Yonsei University College of medicine, Seoul 120-752, Korea.

ABSTRACT

Objective: Apparent diffusion coefficients (ADC) can help differentiate between central nervous system (CNS) lymphoma and Glioblastoma (GBM). However, overlap between ADCs for GBM and lymphoma have been reported because of various region of interest (ROI) methods. Our aim is to explore ROI method to provide the most reproducible results for differentiation.

Materials and methods: We studied 25 CNS lymphomas and 62 GBMs with three ROI methods: (1) ROI1, whole tumor volume; (2) ROI2, multiple ROIs; and (3) ROI3, a single ROI. Interobserver variability of two readers for each method was analyzed by intraclass correlation(ICC). ADCs were compared between GBM and lymphoma, using two-sample t-test. The discriminative ability was determined by ROC analysis.

Results: ADCs from ROI1 showed most reproducible results (ICC >0.9). For ROI1, ADCmean for lymphoma showed significantly lower values than GBM (p = 0.03). The optimal cut-off value was 0.98×10(-3) mm2/s with 85% sensitivity and 90% specificity. For ROI2, ADCmin for lymphoma was significantly lower than GBM (p = 0.02). The cut-off value was 0.69×10(-3) mm2/s with 87% sensitivity and 88% specificity.

Conclusion: ADC values were significantly dependent on ROI method. ADCs from the whole tumor volume had the most reproducible results. ADCmean from the whole tumor volume may aid in differentiating between lymphoma and GBM. However, multi-modal imaging approaches are recommended than ADC alone for differentiation.

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Related in: MedlinePlus

Box-and-whisker plots of representative ADC variables for lymphoma and GBM: mean ADC in ROI1 (A) and minimum ADC in ROI2 (B).The central box represents the value from the lower to upper quartile. The middle line represents the median. The horizontal line extends from the minimum to the maximum value. An outside value are plotted with s square marker.
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pone-0112948-g002: Box-and-whisker plots of representative ADC variables for lymphoma and GBM: mean ADC in ROI1 (A) and minimum ADC in ROI2 (B).The central box represents the value from the lower to upper quartile. The middle line represents the median. The horizontal line extends from the minimum to the maximum value. An outside value are plotted with s square marker.

Mentions: However, our results should be carefully interpreted, because the ranges of ADCs between lymphoma and GBM still substantially overlapped (Fig. 2) and ADC alone might not be sufficient to differentiate lymphoma from GBM. Other advanced imaging techniques such as dynamic contrast-enhanced MRI (DCE), dynamic susceptibility-weighted imaging (DSC), susceptibility-weighted imaging (SWI) and FDG-PET have been reported to improve differential diagnosis of lymphoma and GBM [22]–[25]. Kickingereder et al [26] reported multimodal imaging integrating these advanced sequences allowed reliable differentiation of lymphoma and GBM. Therefore, Multiple advanced imaging techniques in conjunction with ADC should be preferred than ADC alone when differentiating lymphoma from GBM.


Differentiation between primary cerebral lymphoma and glioblastoma using the apparent diffusion coefficient: comparison of three different ROI methods.

Ahn SJ, Shin HJ, Chang JH, Lee SK - PLoS ONE (2014)

Box-and-whisker plots of representative ADC variables for lymphoma and GBM: mean ADC in ROI1 (A) and minimum ADC in ROI2 (B).The central box represents the value from the lower to upper quartile. The middle line represents the median. The horizontal line extends from the minimum to the maximum value. An outside value are plotted with s square marker.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4231099&req=5

pone-0112948-g002: Box-and-whisker plots of representative ADC variables for lymphoma and GBM: mean ADC in ROI1 (A) and minimum ADC in ROI2 (B).The central box represents the value from the lower to upper quartile. The middle line represents the median. The horizontal line extends from the minimum to the maximum value. An outside value are plotted with s square marker.
Mentions: However, our results should be carefully interpreted, because the ranges of ADCs between lymphoma and GBM still substantially overlapped (Fig. 2) and ADC alone might not be sufficient to differentiate lymphoma from GBM. Other advanced imaging techniques such as dynamic contrast-enhanced MRI (DCE), dynamic susceptibility-weighted imaging (DSC), susceptibility-weighted imaging (SWI) and FDG-PET have been reported to improve differential diagnosis of lymphoma and GBM [22]–[25]. Kickingereder et al [26] reported multimodal imaging integrating these advanced sequences allowed reliable differentiation of lymphoma and GBM. Therefore, Multiple advanced imaging techniques in conjunction with ADC should be preferred than ADC alone when differentiating lymphoma from GBM.

Bottom Line: ADCs from ROI1 showed most reproducible results (ICC >0.9).ADCs from the whole tumor volume had the most reproducible results.However, multi-modal imaging approaches are recommended than ADC alone for differentiation.

View Article: PubMed Central - PubMed

Affiliation: From the Department of Radiology, Severance Hospital, Yonsei University College of medicine, Seoul 120-752, Korea.

ABSTRACT

Objective: Apparent diffusion coefficients (ADC) can help differentiate between central nervous system (CNS) lymphoma and Glioblastoma (GBM). However, overlap between ADCs for GBM and lymphoma have been reported because of various region of interest (ROI) methods. Our aim is to explore ROI method to provide the most reproducible results for differentiation.

Materials and methods: We studied 25 CNS lymphomas and 62 GBMs with three ROI methods: (1) ROI1, whole tumor volume; (2) ROI2, multiple ROIs; and (3) ROI3, a single ROI. Interobserver variability of two readers for each method was analyzed by intraclass correlation(ICC). ADCs were compared between GBM and lymphoma, using two-sample t-test. The discriminative ability was determined by ROC analysis.

Results: ADCs from ROI1 showed most reproducible results (ICC >0.9). For ROI1, ADCmean for lymphoma showed significantly lower values than GBM (p = 0.03). The optimal cut-off value was 0.98×10(-3) mm2/s with 85% sensitivity and 90% specificity. For ROI2, ADCmin for lymphoma was significantly lower than GBM (p = 0.02). The cut-off value was 0.69×10(-3) mm2/s with 87% sensitivity and 88% specificity.

Conclusion: ADC values were significantly dependent on ROI method. ADCs from the whole tumor volume had the most reproducible results. ADCmean from the whole tumor volume may aid in differentiating between lymphoma and GBM. However, multi-modal imaging approaches are recommended than ADC alone for differentiation.

Show MeSH
Related in: MedlinePlus