Differentiating primary central nervous system lymphoma from glioblastoma by time-dependent diffusion using oscillating gradient

• Published in: Cancer imaging Vol. 23; no. 1; pp. 1 - 114
• Main Authors: Kamimura, Kiyohisa, Nakano, Tsubasa, Hasegawa, Tomohito, Nakajo, Masanori, Yamada, Chihiro, Kamimura, Yoshiki, Akune, Kentaro, Ejima, Fumitaka, Ayukawa, Takuro, Nagano, Hiroaki, Takumi, Koji, Nakajo, Masatoyo, Higa, Nayuta, Yonezawa, Hajime, Hanaya, Ryosuke, Kirishima, Mari, Tanimoto, Akihide, Iwanaga, Takashi, Imai, Hiroshi, Feiweier, Thorsten, Yoshiura, Takashi
• Format: Journal Article
• Language: English
• Published: London BioMed Central Ltd 30.11.2023; BioMed Central; BMC
• Subjects: Age; Brain cancer; Central nervous system; Differentiation; Diffusion; Diffusion coefficient; Drunk driving; Glioblastoma; Glioblastoma multiforme; Lymphoma; Magnetic resonance imaging; Medical imaging; Medical research; Medicine, Experimental; Nervous system; Non-Hodgkin's lymphomas; Parameters; Primary central nervous system lymphoma; Time dependence; Time setting
• DOI: 10.1186/s40644-023-00639-7
• ISSN: 1470-7330; 1740-5025

Background This study aimed to elucidate the impact of effective diffusion time setting on apparent diffusion coefficient (ADC)-based differentiation between primary central nervous system lymphomas (PCNSLs) and glioblastomas (GBMs) and to investigate the usage of time-dependent diffusion magnetic resonance imaging (MRI) parameters. Methods A retrospective study was conducted involving 21 patients with PCNSLs and 66 patients with GBMs using diffusion weighted imaging (DWI) sequences with oscillating gradient spin-echo ([DELA].sub.eff = 7.1 ms) and conventional pulsed gradient ([DELA].sub.eff = 44.5 ms). In addition to ADC maps at the two diffusion times (ADC.sub.7.1 ms and ADC.sub.44.5 ms), we generated maps of the ADC changes (cADC) and the relative ADC changes (rcADC) between the two diffusion times. Regions of interest were placed on enhancing regions and non-enhancing peritumoral regions. The mean and the fifth and 95.sup.th percentile values of each parameter were compared between PCNSLs and GBMs. The area under the receiver operating characteristic curve (AUC) values were used to compare the discriminating performances among the indices. Results In enhancing regions, the mean and fifth and 95.sup.th percentile values of ADC.sub.44.5 ms and ADC.sub.7.1 ms in PCNSLs were significantly lower than those in GBMs (p = 0.02 for 95.sup.th percentile of ADC.sub.44.5 ms, p = 0.04 for ADC.sub.7.1 ms, and p < 0.01 for others). Furthermore, the mean and fifth and 95.sup.th percentile values of cADC and rcADC were significantly higher in PCNSLs than in GBMs (each p < 0.01). The AUC of the best-performing index for ADC.sub.7.1 ms was significantly lower than that for ADC.sub.44.5 ms (p < 0.001). The mean rcADC showed the highest discriminating performance (AUC = 0.920) among all indices. In peritumoral regions, no significant difference in any of the three indices of ADC.sub.44.5 ms, ADC.sub.7.1 ms, cADC, and rcADC was observed between PCNSLs and GBMs. Conclusions Effective diffusion time setting can have a crucial impact on the performance of ADC in differentiating between PCNSLs and GBMs. The time-dependent diffusion MRI parameters may be useful in the differentiation of these lesions. Keywords: Diffusion, Glioblastoma, Magnetic resonance imaging, Primary central nervous system lymphoma