Apparent diffusion coefficient in preoperative grading of gliomas: a comparison between ultra-high and conventional mono-b value diffusion-weighted MR imaging
YuChuan Hu1, LinFeng Yan1, ZhiCheng Liu1, YingZhi Sun1, DanDan Zheng2, TianYong Xu2, Wen Wang1, and GuangBin Cui1

1Department of Radiology, Tangdu Hospital, Fourth Military Medical University, Xi’an, China, People's Republic of, 2MR Research China, GE Healthcare China, Beijing, China, People's Republic of

Synopsis

The preoperative grading of gliomas, which is critical for determination of the most appropriate treatment, remains unsatisfactory. As an improved MRI technique, diffusion-weighted imaging (DWI) is considered the most sensitive for early pathological changes and therefore can potentially be useful in evaluating the glioma grades. Recently, apparent diffusion coefficient (ADC) values derived from the high (3000 sec/mm2) b values DWI were reported to improve the diagnostic performance of DWI in differentiating high- from low-grade gliomas5. But a mono-exponential model and relatively lower high-b values were used in this study.We used a tri-component model to calculate ultra-high ADC (ADCuh) in our research, aiming to retrospectively compare the efficacy of ultra-high and conventional mono-b value DWI in the glioma grading.

purpose

The preoperative grading of gliomas, which is critical for determination of the most appropriate treatment, remains unsatisfactory[1]. As an improved MRI technique, diffusion-weighted imaging (DWI) is considered the most sensitive for early pathological changes and therefore can potentially be useful in evaluating the glioma grades[2-4]. Recently, apparent diffusion coefficient (ADC) values derived from the high (3000 sec/mm2) b values DWI were reported to improve the diagnostic performance of DWI in differentiating high- from low-grade gliomas[5]. But a mono-exponential model and relatively lower high-b values were used in this study[5].

We used a tri-component model to calculate ultra-high ADC (ADCuh) in our research, aiming to retrospectively compare the efficacy of ultra-high and conventional mono-b value DWI in the glioma grading.

Methods

This retrospective study was approved by the Ethics Committee and informed consents were obtained from all participants. Between July 2014 and September 2015, seventy-four consecutive glioma patients (mean age, 47 years; range, 2-87 years) confirmed by postoperative histopathology and immunohistochemistry were enrolled in the study. Each subject underwent routine MRI, eighteen b-value DWI (b-value:0,50,100,150,200,300,500,800,1000,1300,1500,1700,2000,2500,3000,3500,4000,4500 sec/mm2), as well as contrast-enhanced MRI sequence of the brain on a 3.0-T MRI system (MR750, GE Healthcare, Milwaukee, USA) before any treatments. All data were analyzed and processed on a GE ADW4.6 workstation. The multi-b-value data were analyzed using a AQP program. A freehand ROI was placed on the solid tumor parts with the highest signal intensity on DW image (b=1000-4000 sec/mm2) and the corresponding region of relatively low ADC values on the ADC map to avoid hemorrhagic, calcified, cystic and necrotic areas (as shown in Figure 1A or D). Tri-exponential curve (Figure 1B or E), ADCuh maps (Figure 1C or F) were generated. The ADC values at standard (1000 sec/mm2) and ultrahigh (0-4500 sec/mm2) b values were calculated according to the mono-exponential (ADCst) and tri-component model (ADCuh), respectively[6]. Parameters ADCuh, ADCst, ADCuh_edema (edema area) and ADCuh_wm (contralateral healthy white matter area) were compared for the differences between the low-grade (WHO I and II) and high-grade gliomas (WHO III and IV) by using independent sample t test. Receiver operating characteristic (ROC) analyses were performed to determine optimal thresholds for differentiating the low-grade from the high-grade gliomas by ADCuh and ADCst value respectively. Also the sensitivity, specificity, and area under curve (AUC) for differentiating the low-grade gliomas were calculated.

Results

Among the 74 studied patients, 18 were low-grade and 56 were high-grade gliomas. ADCuh and ADCst tended to be higher in the low-grade glioma (P=0.000, Table 1 and Fig 2), while no significant differences were found in tumor edema area (ADCuh_edema) and contralateral healthy white matter area (ADCuh_wm). According to the ROC analyses, with AUC of 0.922, ADCuh parameter had 94.4 % sensitivity and 78.6 % specificity for differentiating the low-grade gliomas at the cutoff value of 0.362×10−3 mm2/sec. With regards to ADCst, AUC of 0.886, and 83.3% sensitivity and 82.1% specificity at the cutoff value of 1.105×10−3 mm2/sec were achieved(Table 2).

Discussion

This study suggested that the ADCuh based on tri-exponential model DWI could be used to grade gliomas preoperatively. We detected significant differences in parameters ADCuh and ADCst between low- and high-grade gliomas. We also determined the most appropriate cutoff values for both parameter, which could potentially be used in clinical practice regarding preoperatively grading gliomas.

Conclusions

Both tri- and mono-exponential models provide accurate preoperative glioma gradings. The ADCuh parameter demonstrate higher efficacy over the conventional ADC value.

Keywords words

Glioma; Grading; Diffusion-weighted imaging; MRI; Apparent diffusion coefficient

Acknowledgements

We would like to thank Dandan Zheng of GE Healthcare China for her helpful comments during the revision of this manuscript.

References

1.Hu YC, Yan LF, Wu L, et al. Intravoxel incoherent motion diffusion-weighted MR imaging of gliomas: efficacy in preoperative grading. Sci Rep. 2014;4:7208.

2.Kono K, Inoue Y, Nakayama K, et al. The role of diffusion-weighted imaging in patients with brain tumors. AJNR. American journal of neuroradiology. 2001;22(6):1081-1088.

3.Yamasaki F, Kurisu K, Satoh K, et al. Apparent diffusion coefficient of human brain tumors at MR imaging. Radiology. 2005;235(3):985-991.

4.Maier SE, Sun Y, Mulkern RV. Diffusion imaging of brain tumors. NMR Biomed. 2010;23(7):849-864.

5.Kang Y, Choi SH, Kim YJ, et al. Gliomas: Histogram analysis of apparent diffusion coefficient maps with standard- or high-b-value diffusion-weighted MR imaging--correlation with tumor grade. Radiology. 2011;261(3):882-890.

6.Xueying L, Zhongping Z, Zhoushe Z, et al. Investigation of Apparent Diffusion Coefficient from Ultra-high b-Values in Parkinson's Disease. Eur Radiol. 2015;25(9):2593-2600.

Figures

Figure 1.(A) and (D), Axial diffusion-weighted trace image (b=4000 sec/mm2) shows ROIs in placed in the solid tumor parts, edema and contralateral healthy white matter area, respectively. (B) and (E), The tri-exponential fitting of the diffusion signal decay over a wide-range of b values (up to 4,500). (B) and (E), Axial ADCuh map. (A-C, a case of high- grade glioma. D-E, a case of low- grade glioma)

Figure 2. Box plots for values of ADCuh and ADCst in high- and low-grade gliomas(A and C), among low-, grade 2 and 3 gliomas(B and D).

Figure 3. ROC curve for differentiating the performances of the ADCuh and ADCst value for low- and high-grade gliomas.

Table 1. ADC values comparison between tri-component model and conventional mono-b value DWI in low- and high-grade gliomas

Table 2. ROC curve



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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