Mean Of Apparent Diffusion Coefficient Values Research Articles

Value of quantitative apparent diffusion coefficients in differentiating low-grade gliomas from mixed neuronal-glial tumors

PurposeTo retrospectively assess if diffusion-weighted MR imaging (DWI) and quantitative apparent–diffusion coefficient (ADC) maps could be used to differentiate between low-grade gliomas (LGGs) and mixed neuronal–glial tumors (MNGTs including Dysembryoplastic Neuroepithelial Tumor and Ganglioglioma). Materials and methodsWe retrospectively searched the clinical, pathological, and radiological databases for a span of 9 years and identified 24 patients with biopsy proven LGG. This included WHO (fourth edition) grade I and II tumors including astrocytoma, oligoastrocytoma and oligodendrogliomas. We also identified 22 patients with MNGTs (WHO grade I) including 13 patients with DNET and 9 patients with Ganglioglioma. All patients with pathologically confirmed tumors who had MRI including DWI sequence were included in the study. Regions of interest (ROIs) of 0.1–0.15 cm2 were manually positioned on the ADC maps and multiple values (10−6 mm2/s) were obtained including the ADCmean. Optimal thresholds of ADC values and ADC ratios for distinguishing low-grade gliomas from mixed neuronal–glial tumors were determined by receiver operating characteristic (ROC) curve analysis. ResultsAll the four ADC measurement variables, including the minimum (ADC min), the (ADC max) maximum, the mean of ADC values (ADC mean) and the ADC ratios (ADC mean/ADCnormal) showed significant difference between the MNGTs and LGGs. The most significant difference was seen with the maximum ADC value (ADC max) of the tumor where the values for LGGs were 1317 ± 314 whereas the values for MNGTs were 2134 ± 438. In both subsets of patients with MNGTs (DNET and Ganglioglioma), this difference was statistically significant (P = .015 and P = .0066, respectively). However, there was no significant difference between the ADC values of these subtypes of MNGTs. ConclusionThe ADC values of MNGTs are significantly higher compared to LGGs and can be helpful in radiological demarcation of these two conditions. The high ADC of MNGTs may be attributable to the presence of large extracellular spaces and their cellularity, which is much lower than that of pure glial neoplasms.

Correlation of Peri-Tumoral Edema Determined in T2 Weighted Imaging with Apparent Diffusion Coefficient of Peritumoral Area in Patients with Breast Carcinoma

Background: Breast cancer may result in remodeling of adjacent normal appearing breast tissues. Magnetic resonance imaging (MRI) is increasingly used in the diagnosis and follow-up of breast cancer by means of diffusion weighted imaging, which is based on thermal motion of water molecules in the extracellular fluid. Objectives: We investigated the correlation of visual assessment of peri-tumoral edema with peri-tumoral and tumoral apparent diffusion coefficient (ADC) values. Patients and Methods: In this cross-sectional study, from 2016 to 2018, 78 patients with 89 malignant breast lesions (mean age, 47 years) were examined by 1.5-T breast MRI. The lesions were categorized based on the visual assessment of peri-tumoral edema on T2 weighted imaging (T2WI) into two groups: (A) with edema (36 lesions) and (B) without edema (53 lesions). Measuring ADC values in the contralateral normal breast tissue, peri-tumoral tissue and peri-tumoral-normal tissue ADC ratio were compared between the two groups for all lesions. Results: The number of in situ lesions was higher in group B (7.5% vs 2.7%) with the p value of 0.01. The mean of ADC values in the normal breast tissue was 1.76 × 10-3mm2/s. Tumor ADCs were significantly lower in group A compared to group B (0.95 × 10-3mm2/s vs. 1.11 × 10-3mm2/s) with the P value of 0.003. However, peri-tumoral ADCs were significantly higher in group A (1.82 × 10-3mm2/s vs. 1.53 × 10-3mm2/s) with the p value of 0.005. The peri-tumoral-normal tissue ADC ratio was 0.87 in group B and about 1 in group A. However, the difference between normal tissue ADCs and peri-tumoral ADCs was only significant (P value of 0.005) in group B. The cut-off point value for differentiating normal tissue ADCs and peri-tumoral ADCs was 1.61 × 10-3mm2/s with the sensitivity of 65% and specificity of 70%. Conclusion: Breast cancer with peri-tumoral edema has lower tumoral ADC values, higher peri-tumoral ADC values and lower prevalence of in situ lesions. Visual assessment of peri-tumoral edema on T2WI could predict the tumoral characteristic on diffusion-weighted imaging.