scholarly journals Diffusion-weighted imaging characteristics of methotrexate-induced acute encephalopathy

2018 ◽  
Vol 6 (3) ◽  
pp. 469-472 ◽  
Author(s):  
Mayumi Yoshimi ◽  
Shoko Abe
Keyword(s):  
Diffusion Weighted Imaging ◽  
Acute Encephalopathy ◽  
Diffusion Weighted ◽  
Imaging Characteristics

scholarly journals Diffusion-weighted Imaging Reversibility In Stroke After Successful Mechanical Recanalization. Case report

2020 ◽  
Vol 29 (2) ◽  
Author(s):  
Matías Negrotto ◽  
Alejandro M. Spiotta ◽  
Aquilla S. Turk ◽  
Raymond D. Turner ◽  
Jonathan Lena ◽  
...  
Keyword(s):  
Case Report ◽  
Clinical Outcome ◽  
Thrombolytic Therapy ◽  
Tissue Damage ◽  
Diffusion Weighted Imaging ◽  
Lesion Size ◽  
Infarct Core ◽  
Mechanical Recanalization ◽  
Diffusion Weighted ◽  
Imaging Characteristics

Increased use of Diffusion-weighted imaging (DWI) in acute stroke has led to observations of early diffusion normalization in lesions thatinitially show diffusion slowing. The “renormalization” of DWI may be spontaneous or the result of thrombolytic therapy, thus, acuteslowing of diffusion is not necessarily an indicator of irreversible tissue damage. The perfusion-diffusion mismatch concept is attractiveas it assumes that DWI lesion size reflects the infarct core whilst the mismatch area reflects the penumbra. However, this concept maybe an oversimplification. This paper shows a case with Diffusion Lesion Reversal after successful neuroendovascular treatment andexcellent clinical outcome, and discuss the imaging characteristics associated with this phenomenon.

Diffusion-Weighted Imaging Characteristics of Primary Central Nervous System Germinoma with Histopathologic Correlation

2009 ◽  
Vol 16 (11) ◽  
pp. 1356-1365 ◽  
Author(s):  
Annette C. Douglas-Akinwande ◽  
Jun Ying ◽  
Zahirabbas Momin ◽  
Amr Mourad ◽  
Eyas M. Hattab
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Diffusion Weighted Imaging ◽  
Diffusion Weighted ◽  
Imaging Characteristics

scholarly journals A Case of Mass-Forming Splenic Tuberculosis: MRI Findings with Emphasis of Diffusion-Weighted Imaging Characteristics

2011 ◽  
Vol 26 (3) ◽  
pp. 457 ◽  
Author(s):  
Jihe Lim ◽  
Jeong-Sik Yu ◽  
Soon Won Hong ◽  
Jae-Joon Chung ◽  
Joo Hee Kim ◽  
...  
Keyword(s):  
Diffusion Weighted Imaging ◽  
Mri Findings ◽  
Diffusion Weighted ◽  
Imaging Characteristics ◽  
Splenic Tuberculosis

scholarly journals Analysis of Multiple B-Value Diffusion-Weighted Imaging in Pediatric Acute Encephalopathy

PLoS ONE ◽  
2013 ◽  
Vol 8 (6) ◽  
pp. e63869 ◽  
Author(s):  
Yasuhiko Tachibana ◽  
Noriko Aida ◽  
Tetsu Niwa ◽  
Kumiko Nozawa ◽  
Kouki Kusagiri ◽  
...  
Keyword(s):  
Diffusion Weighted Imaging ◽  
B Value ◽  
Acute Encephalopathy ◽  
Diffusion Weighted

scholarly journals Diffusion-weighted imaging characteristics of biopsy-proven demyelinating brain lesions

Neurology ◽  
2012 ◽  
Vol 78 (21) ◽  
pp. 1655-1662 ◽  
Author(s):  
N. Abou Zeid ◽  
I. Pirko ◽  
B. Erickson ◽  
S. D. Weigand ◽  
K. M. Thomsen ◽  
...  
Keyword(s):  
Diffusion Weighted Imaging ◽  
Brain Lesions ◽  
Diffusion Weighted ◽  
Imaging Characteristics

scholarly journals Lymphoepithelial cysts in the pancreas: MRI of two cases with emphasis of diffusion-weighted imaging characteristics

2010 ◽  
Vol 32 (3) ◽  
pp. 692-696 ◽  
Author(s):  
Se Jin Nam ◽  
Ho Kyoung Hwang ◽  
Hyunki Kim ◽  
Jeong-Sik Yu ◽  
Dong-Sup Yoon ◽  
...  
Keyword(s):  
Diffusion Weighted Imaging ◽  
Diffusion Weighted ◽  
Imaging Characteristics ◽  
Lymphoepithelial Cysts

Differentiation of cystic lesions in the jaw by conventional magnetic resonance imaging and diffusion-weighted imaging

2021 ◽  
pp. 20210212
Author(s):  
Natnicha Wamasing ◽  
Hiroshi Watanabe ◽  
Junichiro Sakamoto ◽  
Hiroshi Tomisato ◽  
Tohru Kurabayashi
Keyword(s):  
Decision Tree ◽  
Diffusion Weighted Imaging ◽  
Cystic Lesions ◽  
Characteristic Analysis ◽  
Discrimination Power ◽  
Adc Value ◽  
Diffusion Weighted ◽  
Imaging Characteristics ◽  
Dentigerous Cysts ◽  
Adc Values

Objectives: This study aimed to determine the discrimination power of apparent diffusion coefficient (ADC) for cystic lesions in the jaw using MRI. Methods: We selected 127 cystic lesions, comprising dentigerous cysts (DCs), odontogenic keratocysts (OKCs), and unicystic ameloblastomas (UABs), from our MRI database examined by 3T MRI, including diffusion-weighted imaging sequences, and we reviewed their imaging characteristics. We attempted to discriminate the three types of lesions by ADC values with receiver operator characteristic analysis; however, satisfactory results were not obtained for differentiation between DC and OKC. Therefore, we performed a decision tree analysis. Results: The imaging characteristics of the lesions were significantly different according to Fisher’s exact test, except for differences in sex. The ADC values statistically discriminated the lesions of DC and UAB, OKC and UAB, but not DC and OKC. Thus, differentiation was performed by a decision tree for DC and OKC by evaluating the following points: the attached tooth condition, signal intensity on the T1 weighted image (T1SI), ADC value, and the cyst site. However, cases showing hypo- or isointense T1SI with an ADC value under 1.168 × 10–3 mm2/s were difficult to differentiate. Conclusion: The ADC value helped distinguish UAB from both DC and OKC, but not DC from OKC. However, the decision tree based on ADC value, tooth contact status, and T1SI helped differentiate DC and OKC to some extent.

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