Chrome Extension
WeChat Mini Program
Use on ChatGLM

Atypical and malignant canine intracranial meningiomas may have lower apparent diffusion coefficient values than benign tumors

VETERINARY RADIOLOGY & ULTRASOUND(2020)

Cited 3|Views5
No score
Abstract
Canine intracranial meningiomas can be graded based on histological classification as benign (grade I), atypical (grade II), and anaplastic or malignant (grade III). In people, grade II/III meningiomas behave more aggressively, have a higher potential for recurrence after surgical resection, and have lower apparent diffusion coefficient (ADC) values with diffusion weighted imaging (DWI). In this retrospective analytical cross-sectional study, 42 dogs had ADC values quantified in an attempt to differentiate tumor histologic grade. Our hypothesis was that ADC values would be significantly lower in grade II and III versus grade I meningiomas in dogs. On each ADC image, a polygonal region of interest (ROI) was hand-drawn along the lesion's periphery, excluding fluid-filled and hemorrhagic regions. Mean ADC value (ADC(mean)) and minimum ADC value (ADC(min)) were calculated. Additionally, two smaller, ovoid ROI were drawn within the lesion with mean ADC calculated (ADC(mean sR) and ADC(min sR)). Normalized ADC values using white matter were also calculated (ADC(n) and ADC(n sR)). Grades of each tumor were assigned based on histopathology review. Association between ADC parameters and histological grade was tested by means of two-sample t-tests. There were 14 grade I (33.3%), 25 grade II (59.5%), and three grade III (7.2%) meningiomas. ADC(mean sR) and ADC(min sR) were significantly lower when comparing grade II/III to grade I (P < .05). Grade II tumors had significantly lower ADC(mean), ADC(mean sR), ADC(min sR), ADC(n), and ADC(n sR) than grade I meningiomas. This preliminary study supports the potential of ADC values to help predict the histological grade of intracranial meningiomas in dogs.
More
Translated text
Key words
brain,DWI,MRI,neoplasia
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined