scholarly journals Normalized Apparent Diffusion Coefficient in the Prognostication of Patients with Glioblastoma Multiforme

2016 ◽  
Vol 43 (1) ◽  
pp. 127-133 ◽  
Author(s):  
Jai Jai Shiva Shankar ◽  
Adil Bata ◽  
Krista Ritchie ◽  
Andrea Hebb ◽  
Simon Walling
Keyword(s):  
Diffusion Coefficient ◽  
Glioblastoma Multiforme ◽  
Apparent Diffusion Coefficient ◽  
Survival Function ◽  
Correlation Coefficients ◽  
Diffusion Weighted Images ◽  
Institutional Ethics ◽  
Normal Appearing White Matter ◽  
Kaplan Meier ◽  
Apparent Diffusion

AbstractBackground: Glioblastoma multiforme (GBM) is known to have poor prognosis, with no available imaging marker that can predict survival at the time of diagnosis. Diffusion weighted images are used in characterisation of cellularity and necrosis of GBM. The purpose of this study was to assess whether pattern or degree of diffusion restriction could help in the prognostication of patients with GBM. Material and Methods: We retrospectively analyzed 84 consecutive patients with confirmed GBM on biopsy or resection. The study was approved by the institutional ethics committee. The total volume of the tumor and total volume of tumor showing restricted diffusion were calculated. The lowest Apparent Diffusion Coefficient (ADC) in the region of the tumor and in the contralateral Normal Appearing White Matter were calculated in order to calculate the nADC. Treatment and follow-up data in these patients were recorded. Multivariate analsysis was completed to determine significant correlations between different variables and the survival of these patients. Results: Patient survival was significantly related to the age of the patient (p<0.0001; 95% CI-1.022-1.043) and the nADC value (p=0.014; 95% CI-0.269-0.860) in the tumor. The correlation coefficients of age and nADC with survival were −0.335 (p=0.002) and 0.390 (p<0.001), respectively. Kaplan Meier survival function, grouped by normalized Apparent Diffusion Coefficient cut off value of 0.75, was significant (p=0.007). Conclusion: The survival of patients with GBM had small, but significant, correlations with the patient’s age and nADC within the tumor.

scholarly journals Semi-Automated Segmentation of Bone Metastases from Whole-Body MRI: Reproducibility of Apparent Diffusion Coefficient Measurements

Diagnostics ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 499
Author(s):  
Alberto Colombo ◽  
Giulia Saia ◽  
Alcide A. Azzena ◽  
Alice Rossi ◽  
Fabio Zugni ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Bone Metastases ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Whole Body ◽  
Whole Body Mri ◽  
Diffusion Weighted Images ◽  
Diffusion Weighted ◽  
Apparent Diffusion

Using semi-automated software simplifies quantitative analysis of the visible burden of disease on whole-body MRI diffusion-weighted images. To establish the intra- and inter-observer reproducibility of apparent diffusion coefficient (ADC) measures, we retrospectively analyzed data from 20 patients with bone metastases from breast (BCa; n = 10; aged 62.3 ± 14.8) or prostate cancer (PCa; n = 10; aged 67.4 ± 9.0) who had undergone examinations at two timepoints, before and after hormone-therapy. Four independent observers processed all images twice, first segmenting the entire skeleton on diffusion-weighted images, and then isolating bone metastases via ADC histogram thresholding (ADC: 650–1400 µm2/s). Dice Similarity, Bland-Altman method, and Intraclass Correlation Coefficient were used to assess reproducibility. Inter-observer Dice similarity was moderate (0.71) for women with BCa and poor (0.40) for men with PCa. Nonetheless, the limits of agreement of the mean ADC were just ±6% for women with BCa and ±10% for men with PCa (mean ADCs: 941 and 999 µm2/s, respectively). Inter-observer Intraclass Correlation Coefficients of the ADC histogram parameters were consistently greater in women with BCa than in men with PCa. While scope remains for improving consistency of the volume segmented, the observer-dependent variability measured in this study was appropriate to distinguish the clinically meaningful changes of ADC observed in patients responding to therapy, as changes of at least 25% are of interest.

scholarly journals Differentiating glioblastoma multiforme from cerebral lymphoma: application of advanced texture analysis of quantitative apparent diffusion coefficients

2020 ◽  
Vol 33 (5) ◽  
pp. 428-436
Author(s):  
Mehrsad Mehrnahad ◽  
Sara Rostami ◽  
Farnaz Kimia ◽  
Reza Kord ◽  
Morteza Sanei Taheri ◽  
...  
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Diffusion Coefficient ◽  
Glioblastoma Multiforme ◽  
Apparent Diffusion Coefficient ◽  
Central Nervous System Lymphoma ◽  
Second Order ◽  
Regions Of Interest ◽  
Apparent Diffusion ◽  
Histogram Feature

Purpose The purpose of this study was to differentiate glioblastoma multiforme from primary central nervous system lymphoma using the customised first and second-order histogram features derived from apparent diffusion coefficients. Methods and materials: A total of 82 patients (57 with glioblastoma multiforme and 25 with primary central nervous system lymphoma) were included in this study. The axial T1 post-contrast and fluid-attenuated inversion recovery magnetic resonance images were used to delineate regions of interest for the tumour and peritumoral oedema. The regions of interest were then co-registered with the apparent diffusion coefficient maps, and the first and second-order histogram features were extracted and compared between glioblastoma multiforme and primary central nervous system lymphoma groups. Receiver operating characteristic curve analysis was performed to calculate a cut-off value and its sensitivity and specificity to differentiate glioblastoma multiforme from primary central nervous system lymphoma. Results Based on the tumour regions of interest, apparent diffusion coefficient mean, maximum, median, uniformity and entropy were higher in the glioblastoma multiforme group than the primary central nervous system lymphoma group ( P ≤ 0.001). The most sensitive first and second-order histogram feature to differentiate glioblastoma multiforme from primary central nervous system lymphoma was the maximum of 2.026 or less (95% confidence interval (CI) 75.1–99.9%), and the most specific first and second-order histogram feature was smoothness of 1.28 or greater (84.0% CI 70.9–92.8%). Based on the oedema regions of interest, most of the first and second-order histogram features were higher in the glioblastoma multiforme group compared to the primary central nervous system lymphoma group ( P ≤ 0.015). The most sensitive first and second-order histogram feature to differentiate glioblastoma multiforme from primary central nervous system lymphoma was the 25th percentile of 0.675 or less (100% CI 83.2–100%) and the most specific first and second-order histogram feature was the median of 1.28 or less (85.9% CI 66.3–95.8%). Conclusions Texture analysis using first and second-order histogram features derived from apparent diffusion coefficient maps may be helpful in differentiating glioblastoma multiforme from primary central nervous system lymphoma.

Prognostic significance of early changes in the apparent diffusion coefficient that occurs after treatment of patients with glioblastoma multiforme with bevacizumab

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 2058-2058
Author(s):  
M. Paldino ◽  
A. Desjardins ◽  
H. S. Friedman ◽  
J. J. Vredenburgh ◽  
D. P. Barboriak
Keyword(s):  
Diffusion Coefficient ◽  
Glioblastoma Multiforme ◽  
Mr Imaging ◽  
Apparent Diffusion Coefficient ◽  
Diffusion Tensor ◽  
Prognostic Significance ◽  
Single Shot ◽  
Signal Abnormality ◽  
Contrast Enhanced ◽  
Apparent Diffusion

2058 Background: To determine the prognostic significance of changes in parameters derived from diffusion tensor imaging (DTI) that occur in response to combination chemotherapy with the antiangiogenesis agent bevacizumab (BEV) in patients with recurrent glioblastoma multiforme (GBM). Methods: 16 patients (10 men, 6 women; age range 38–62 years) with recurrent GBM underwent serial 1.5T MR imaging. Axial single-shot echo planar DTI (TR/TE 6000/100; flip angle 90 degrees; voxel: 1.72 x 1.72 x 5mm; b value of 1000 sec/mm2; 12 directions) was obtained on scans performed 3 days and 1 day prior to and 1 day after initiation of therapy with BEV and irinotecan (CPT-11). Clinical follow-up and survival status was documented up to 20 months after the date of initial MR imaging. Apparent diffusion coefficient (ADC) and fractional anisotropy (FA) maps were aligned to whole brain contrast-enhanced 3D FLASH and 3D FLAIR image volumes (1 mm isotropic voxels) using a rigid body normalized mutual information algorithm. Based on two pre-treatment scans, the 95% confidence limits for change (95%CL) in ADC and FA were calculated in volumes of tumor-related contrast-enhancement (TRE) and FLAIR signal abnormality (FSA). A patient was considered to have a change in FA or ADC after therapy if the difference between the pre- and post-treatment values was greater than the 95% CL for that parameter. Progression was defined on contrast-enhanced MRI using MacDonald criteria by neuro-oncologists blinded to the DTI findings. Survival was compared using the log rank test. Results: DTI detected a change in ADC within FSA after therapy in three patients (2 increased, 1 decreased). Patients with a change in ADC within FSA had significantly shorter overall (p < 0.0012) and progression free (p < 0.015) survival than those with no change. Median survival in the patient group with a change in ADC was 24.7 (95% CI [17.3, 39.4]) weeks and 56.4 (95% CI [41.7, 96]) weeks in those patients with no change. Conclusions: In patients with GBM treated with BEV and CPT-11, a change in ADC after therapy in areas of FSA is associated with decreased survival. Parameters derived from DTI may, therefore, potentially serve as early markers of treatment failure in patients with GBM. [Table: see text]

Histogram analysis of volume-based apparent diffusion coefficient in breast cancer

2017 ◽  
Vol 58 (11) ◽  
pp. 1294-1302 ◽  
Author(s):  
Ga Eun Park ◽  
Sung Hun Kim ◽  
Eun Jeong Kim ◽  
Bong Joo Kang ◽  
Mi Sun Park
Keyword(s):  
Breast Cancer ◽  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Ductal Carcinoma ◽  
Histogram Analysis ◽  
Invasive Ductal Cancer ◽  
Diffusion Weighted Images ◽  
Apparent Diffusion ◽  
Adc Values ◽  
Magnetic Resonance Imaging Mri

Background Breast cancer is a heterogeneous disease. Recent studies showed that apparent diffusion coefficient (ADC) values have various association with tumor aggressiveness and prognosis. Purpose To evaluate the value of histogram analysis of ADC values obtained from the whole tumor volume in invasive ductal cancer (IDC) and ductal carcinoma in situ (DCIS). Material and Methods This retrospective study included 201 patients with confirmed DCIS (n = 37) and IDC (n = 164). The IDC group was divided into two groups based on the presence of a DCIS component: IDC–DCIS (n = 76) and pure IDC (n = 88). All patients underwent preoperative breast magnetic resonance imaging (MRI) with diffusion-weighted images at 3.0 T. Histogram parameters of cumulative ADC values, skewness, and kurtosis were calculated and statistically analyzed. Results The differences between DCIS, IDC–DCIS, and pure IDC were significant in all percentiles of ADC values, in descending order of DCIS, IDC–DCIS, and pure IDC. IDC showed significantly lower ADC values than DCIS, and ADC50 was the best indicator for discriminating IDC from DCIS, with a threshold of 1.185 × 10–3 mm2/s (sensitivity of 82.9%, specificity of 75.7%). However, multivariate analysis of obtained ADC values showed no significant differences between DCIS, IDC–DCIS, and pure IDC ( P > 0.05). Conclusion Volume-based ADC values showed association with heterogeneity of breast cancer. However, there was no additional diagnostic performance in histogram analysis for differentiating between DCIS, IDC–DCIS, and pure IDC.

Sign in / Sign up

Export Citation Format

Share Document