Magnetic Resonance Diffusion-Weighted Imaging: Sensitivity and Apparent Diffusion Constant in Stroke

1994 ◽  
pp. 207-210 ◽  
Author(s):  
Stephen C. Jones ◽  
A. D. Perez-Trepichio ◽  
M. Xue ◽  
A. J. Furlan ◽  
I. A. Awad
Keyword(s):  
Magnetic Resonance ◽  
Diffusion Weighted Imaging ◽  
Diffusion Constant ◽  
Diffusion Weighted ◽  
Apparent Diffusion

scholarly journals Magnetic resonance texture analysis utility in differentiating intraparenchymal neurosarcoidosis from primary central nervous system lymphoma: a preliminary analysis

2019 ◽  
Vol 32 (3) ◽  
pp. 203-209 ◽  
Author(s):  
Girish Bathla ◽  
Neetu Soni ◽  
Raymondo Endozo ◽  
Balaji Ganeshan
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Diffusion Coefficient ◽  
Magnetic Resonance ◽  
Spatial Scale ◽  
Texture Analysis ◽  
Diffusion Weighted Imaging ◽  
Post Contrast ◽  
Diffusion Weighted ◽  
Apparent Diffusion

Purpose Neurosarcoidosis and primary central nervous system lymphomas, although distinct disease entities, can both have overlapping neuroimaging findings. The purpose of our preliminary study was to assess if magnetic resonance texture analysis can differentiate parenchymal mass-like neurosarcoidosis granulomas from primary central nervous system lymphomas. Methods A total of nine patients was evaluated, four with parenchymal neurosarcoidosis granulomas and five with primary central nervous system lymphomas. Magnetic resonance texture analysis was performed with commercial software using a filtration histogram technique. Texture features of different sizes and variations in signal intensity were extracted at six different spatial scale filters, followed by feature quantification using statistical and histogram parameters and 36 features were analysed for each sequence (T1-weighted, T2-weighted, fluid-attenuated inversion recovery, diffusion-weighted, apparent diffusion coefficient, T1-post contrast). The non-parametric Mann–Whitney test was used to evaluate the differences between different texture parameters. Results The differences in distribution of entropy on T2-weighted imaging, apparent diffusion coefficient and T1-weighted post-contrast images were statistically significant on all spatial scale filters. Magnetic resonance texture analysis using medium and coarse spatial scale filters was especially useful in discriminating neurosarcoidosis from primary central nervous system lymphomas for mean, mean positive pixels, kurtosis, and skewness on diffusion-weighted imaging ( P < 0.004–0.030). At spatial scale filter 5, entropy on T2-weighted imaging ( P = 0.001) was the most useful discriminator with a cut-off value of 6.12 ( P = 0.001, area under the curve (AUC)-1, sensitivity (Sn)-100%, specificity (Sp)-100%), followed by kurtosis and skewness on diffusion-weighted imaging with a cut-off value of −0.565 ( P = 0.011, AUC-0.97, Sn-100%, Sp-83%) and–0.365 ( P = 0.008, AUC-0.98, Sn-100%, Sp-100%) respectively. Conclusion Filtration histogram-based magnetic resonance texture analysis appears to be a promising modality to distinguish parenchymal neurosarcoidosis granulomas from primary central nervous system lymphomas.

scholarly journals Accuracy of diffusion-weighted imaging-magnetic resonance in differentiating functional from non-functional pituitary macro-adenoma and classification of tumor consistency

2018 ◽  
Vol 32 (2) ◽  
pp. 74-85 ◽  
Author(s):  
Morteza Sanei Taheri ◽  
Farnaz Kimia ◽  
Mersad Mehrnahad ◽  
Hamidreza Saligheh Rad ◽  
Hamidreza Haghighatkhah ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Confidence Interval ◽  
Diffusion Weighted Imaging ◽  
Area Under The Curve ◽  
Second Order ◽  
Diffusion Weighted ◽  
Functional Types ◽  
Apparent Diffusion ◽  
Tumor Consistency

Purpose The purpose of this study was to determine the accuracy of selected first or second-order histogram features in differentiation of functional types of pituitary macro-adenomas. Materials and methods Diffusion-weighted imaging magnetic resonance imaging was performed on 32 patients (age mean±standard deviation = 43.09 ± 11.02 years; min = 22 and max = 65 years) with pituitary macro-adenoma (10 with functional and 22 with non-functional tumors). Histograms of apparent diffusion coefficient were generated from regions of interest and selected first or second-order histogram features were extracted. Collagen contents of the surgically resected tumors were examined histochemically using Masson trichromatic staining and graded as containing <1%, 1–3%, and >3% of collagen. Results Among selected first or second-order histogram features, uniformity ( p = 0.02), 75th percentile ( p = 0.03), and tumor smoothness ( p = 0.02) were significantly different between functional and non-functional tumors. Tumor smoothness > 5.7 × 10−9 (area under the curve = 0.75; 0.56–0.89) had 70% (95% confidence interval = 34.8–93.3%) sensitivity and 33.33% (95% confidence interval = 14.6–57.0%) specificity for diagnosis of functional tumors. Uniformity ≤179.271 had a sensitivity of 60% (95% confidence interval = 26.2–87.8%) and specificity of 90.48% (95% confidence interval = 69.6–98.8%) with area under the curve = 0.76; 0.57–0.89. The 75th percentile >0.7 had a sensitivity of 80% (95% confidence interval = 44.4–97.5%) and specificity of 66.67% (95% confidence interval = 43.0–85.4%) for categorizing tumors to functional and non-functional types (area under the curve = 0.74; 0.55–0.88). Using these cut-offs, smoothness and uniformity are suggested as negative predictive indices (non-functional tumors) whereas 75th percentile is more applicable for diagnosis of functional tumors. Conclusion First or second-order histogram features could be helpful in differentiating functional vs non-functional pituitary macro-adenoma tumors.

A History of Sarcoidosis and a New Brain Lesion

2021 ◽  
pp. 187-188
Author(s):  
Andrew McKeon ◽  
Julie E. Hammack
Keyword(s):  
Diffusion Coefficient ◽  
Magnetic Resonance ◽  
Apparent Diffusion Coefficient ◽  
Symptom Onset ◽  
Magnetic Resonance Image ◽  
Diffusion Weighted Imaging ◽  
Lymph Node Biopsy ◽  
Active Pulmonary Tuberculosis ◽  
Diffusion Weighted ◽  
Apparent Diffusion

A 59-year-old man with long-standing hypertension sought a second opinion for a left-sided posterior headache and aphasia of approximately 1 week’s duration. Eight months before neurologic symptom presentation, he was febrile with night sweats, weight loss, arthralgias, dyspnea, and wheezing. Bronchoscopy and hilar lymph node biopsy showed noncaseating granulomatous inflammation consistent with pulmonary sarcoidosis. Remotely, as a teenager, given exposure to a family member with active pulmonary tuberculosis infection, he had a purified protein derivative skin test, which was positive; he received 6 months of isoniazid treatment. On examination, he was aphasic but had an otherwise normal neurologic examination. Brain magnetic resonance image performed at hospital admission (1 week after symptom onset) showed extensive T2 signal abnormality in the left temporal neocortex, with vasogenic edema, and abnormal gyriform gadolinium enhancement. There was no restricted diffusion in the left temporal lobe on diffusion-weighted imaging, but an apparent diffusion coefficient map showed a gyriform hypointense pattern. Prior outside magnetic resonance image obtained 1 day into the patient’s symptoms showed similar findings on T2/fluid-attenuated inversion recovery and T1 postgadolinium images but also gyriform hyperintensity on diffusion-weighted imaging, with hypointensity on apparent diffusion coefficient map in the same region. The patient was diagnosed with subacute cerebral infarction in the context of cardioembolic disease secondary to hereditary hypertrophic cardiomyopathy. As a result of the findings and diagnosis, the patient received an implantable cardioverter-defibrillator and was treated with warfarin, aiming for an international normalized ratio of 2.0 to 3.0 to reduce the risk of recurrent cardioembolic disease. The patient had a subacute ischemic stroke mimicking a brain mass radiologically. The acuity of symptom onset could have been a key clinical clue in this case but was absent from the patient history. Patients with stroke typically have hyperacute symptom onset (over seconds to minutes). Autoimmune and inflammatory central nervous system disease symptoms tend to have subacute evolution (over days to weeks) or might be chronic (over months).

scholarly journals Comparison of magnetic resonance diffusion-weighted imaging characteristics between cystic lesions and normal pancreatic parenchyma

2016 ◽  
Vol 6 (3) ◽  
pp. 149-153
Author(s):  
Fuad Julardžija ◽  
Adnan Šehić ◽  
Melika Bukvić ◽  
Fahrudin Smajlović
Keyword(s):  
Diffusion Coefficient ◽  
Magnetic Resonance ◽  
Signal Intensity ◽  
Diffusion Weighted Imaging ◽  
Pancreatic Head ◽  
Cystic Lesions ◽  
Adc Value ◽  
Pancreatic Parenchyma ◽  
Diffusion Weighted ◽  
Apparent Diffusion

Introduction: Diffusion weighted imaging (DWI) is a form of magnetic resonance imaging (MRI) based on measuring the random Brownian motion of water molecules within a tissue. The aim of this study was to show the significance of diffusion-weighted imaging (DWI) in differentiating pancreatic cystic formations from normal pancreatic parenchyma using MRI 1.5 T.Methods: A total of 52 patients were included in the study (25 with pancreatic cystic formations and 27 with normal MRI findings of the pancreas). DWI technique was used with b values of 0.500 and 1 000 mm2/s at 1.5 T. The signal intensity was measured, as well as apparent diffusion coefficient (ADC). Visual estimation of the signal intensity of detected cystic lesions was performed and compared to the normal appearance of pancreas.Results: The highest signal intensity of the cystic lesions with hyper-signal was observed with DWI b0 value in the pancreatic head (M 185.1 ± 47.205, p < 0.05). Similarly, the highest apparent diffusion coefficient (ADC) value of the cystic formations with hyper-signal was observed in the pancreatic head (2.09 x 10-3 mm2/s, p < 0.05). In the group with healthy pancreas, the highest signal intensity was observed with DWI b0 value (M 76.40 ± 18.28, p < 0.05). The observed ADC value in this group was 1.21 x 10-3 mm2/s in the head, 1.24 x 10-3mm2/s in the neck, 1.21 x 10-3mm2/s in the body, and 1.06 x 10-3mm2/s in the tail; p > 0.05.Conclusions: Differences in signal intensity and ADC values have an important diagnostic value in differentiating the cystic formations from normal pancreatic parenchyma in MRI examination.

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