Differences between primary central nervous system lymphoma and glioblastoma: topographic analysis using voxel-based morphometry

K. Yamashita, A. Hiwatashi, O. Togao, K. Kikuchi, D. Momosaka, N. Hata, Y. Akagi, S. O. Suzuki, T. Iwaki, K. Iihara, H. Honda

Research output: Contribution to journalArticle

Abstract

AIM: To evaluate the diagnostic feasibility of probabilistic analysis using voxel-based morphometry (VBM) in differentiating primary central nervous system lymphoma (PCNSL) from glioblastoma (GBM). MATERIALS AND METHODS: In total, 118 patients with GBM (57 males, 61 females; mean [± standard deviation] age, 56.9±19.3 years; median, 61 years) and 52 patients with PCNSL (37 males, 15 females; mean age, 62±13.3 years, median, 66 years) were studied retrospectively. Each patient underwent preoperative contrast-enhanced T1-weighted imaging (CE-T1WI) using a 1.5 or 3 T magnetic resonance imaging (MRI) system. To assess preferential occurrence sites, images from CE-T1WI were co-registered and spatially normalised using the MNI152 T1 template. Subsequently, a region of interest (ROI) was placed in the centre of the enhancing tumour in normalised images with 1-mm isotropic resolution. The same ROI between normalised and T1 template images was set up using an ROI manager function in ImageJ software. A spherical volume of interest (VOI) with a radius of 10 mm was determined. A probability map was created by overlaying each image with the VOI. Each VOI was removed from T1 template images for VBM analysis. VBM analysis was performed using statistical parametric mapping (SPM) 12 software under default settings. RESULTS: VBM analysis showed significantly higher frequency in the splenium of the corpus callosum among PCNSL patients than among GBM patients (p<0.05; family-wise error correction). CONCLUSION: Topographic analysis using VBM provides useful information for differentiating PCNSL from GBM.

Original languageEnglish
Pages (from-to)816.e1-816.e8
JournalClinical Radiology
Volume74
Issue number10
DOIs
Publication statusPublished - Oct 2019

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Glioblastoma
Lymphoma
Central Nervous System
Software
Corpus Callosum
Magnetic Resonance Imaging
Neoplasms

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

Cite this

Differences between primary central nervous system lymphoma and glioblastoma : topographic analysis using voxel-based morphometry. / Yamashita, K.; Hiwatashi, A.; Togao, O.; Kikuchi, K.; Momosaka, D.; Hata, N.; Akagi, Y.; Suzuki, S. O.; Iwaki, T.; Iihara, K.; Honda, H.

In: Clinical Radiology, Vol. 74, No. 10, 10.2019, p. 816.e1-816.e8.

Research output: Contribution to journalArticle

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abstract = "AIM: To evaluate the diagnostic feasibility of probabilistic analysis using voxel-based morphometry (VBM) in differentiating primary central nervous system lymphoma (PCNSL) from glioblastoma (GBM). MATERIALS AND METHODS: In total, 118 patients with GBM (57 males, 61 females; mean [± standard deviation] age, 56.9±19.3 years; median, 61 years) and 52 patients with PCNSL (37 males, 15 females; mean age, 62±13.3 years, median, 66 years) were studied retrospectively. Each patient underwent preoperative contrast-enhanced T1-weighted imaging (CE-T1WI) using a 1.5 or 3 T magnetic resonance imaging (MRI) system. To assess preferential occurrence sites, images from CE-T1WI were co-registered and spatially normalised using the MNI152 T1 template. Subsequently, a region of interest (ROI) was placed in the centre of the enhancing tumour in normalised images with 1-mm isotropic resolution. The same ROI between normalised and T1 template images was set up using an ROI manager function in ImageJ software. A spherical volume of interest (VOI) with a radius of 10 mm was determined. A probability map was created by overlaying each image with the VOI. Each VOI was removed from T1 template images for VBM analysis. VBM analysis was performed using statistical parametric mapping (SPM) 12 software under default settings. RESULTS: VBM analysis showed significantly higher frequency in the splenium of the corpus callosum among PCNSL patients than among GBM patients (p<0.05; family-wise error correction). CONCLUSION: Topographic analysis using VBM provides useful information for differentiating PCNSL from GBM.",
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AU - Yamashita, K.

AU - Hiwatashi, A.

AU - Togao, O.

AU - Kikuchi, K.

AU - Momosaka, D.

AU - Hata, N.

AU - Akagi, Y.

AU - Suzuki, S. O.

AU - Iwaki, T.

AU - Iihara, K.

AU - Honda, H.

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N2 - AIM: To evaluate the diagnostic feasibility of probabilistic analysis using voxel-based morphometry (VBM) in differentiating primary central nervous system lymphoma (PCNSL) from glioblastoma (GBM). MATERIALS AND METHODS: In total, 118 patients with GBM (57 males, 61 females; mean [± standard deviation] age, 56.9±19.3 years; median, 61 years) and 52 patients with PCNSL (37 males, 15 females; mean age, 62±13.3 years, median, 66 years) were studied retrospectively. Each patient underwent preoperative contrast-enhanced T1-weighted imaging (CE-T1WI) using a 1.5 or 3 T magnetic resonance imaging (MRI) system. To assess preferential occurrence sites, images from CE-T1WI were co-registered and spatially normalised using the MNI152 T1 template. Subsequently, a region of interest (ROI) was placed in the centre of the enhancing tumour in normalised images with 1-mm isotropic resolution. The same ROI between normalised and T1 template images was set up using an ROI manager function in ImageJ software. A spherical volume of interest (VOI) with a radius of 10 mm was determined. A probability map was created by overlaying each image with the VOI. Each VOI was removed from T1 template images for VBM analysis. VBM analysis was performed using statistical parametric mapping (SPM) 12 software under default settings. RESULTS: VBM analysis showed significantly higher frequency in the splenium of the corpus callosum among PCNSL patients than among GBM patients (p<0.05; family-wise error correction). CONCLUSION: Topographic analysis using VBM provides useful information for differentiating PCNSL from GBM.

AB - AIM: To evaluate the diagnostic feasibility of probabilistic analysis using voxel-based morphometry (VBM) in differentiating primary central nervous system lymphoma (PCNSL) from glioblastoma (GBM). MATERIALS AND METHODS: In total, 118 patients with GBM (57 males, 61 females; mean [± standard deviation] age, 56.9±19.3 years; median, 61 years) and 52 patients with PCNSL (37 males, 15 females; mean age, 62±13.3 years, median, 66 years) were studied retrospectively. Each patient underwent preoperative contrast-enhanced T1-weighted imaging (CE-T1WI) using a 1.5 or 3 T magnetic resonance imaging (MRI) system. To assess preferential occurrence sites, images from CE-T1WI were co-registered and spatially normalised using the MNI152 T1 template. Subsequently, a region of interest (ROI) was placed in the centre of the enhancing tumour in normalised images with 1-mm isotropic resolution. The same ROI between normalised and T1 template images was set up using an ROI manager function in ImageJ software. A spherical volume of interest (VOI) with a radius of 10 mm was determined. A probability map was created by overlaying each image with the VOI. Each VOI was removed from T1 template images for VBM analysis. VBM analysis was performed using statistical parametric mapping (SPM) 12 software under default settings. RESULTS: VBM analysis showed significantly higher frequency in the splenium of the corpus callosum among PCNSL patients than among GBM patients (p<0.05; family-wise error correction). CONCLUSION: Topographic analysis using VBM provides useful information for differentiating PCNSL from GBM.

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