Published August 2019 | Version v1
Journal article Metadata-only

Grading meningiomas using mono-exponential, bi-exponential and stretched exponential model-based diffusion-weighted MR imaging

Creators

  • 1. Department of Radiology, Huashan Hospital, Fudan University, No.12 Wulumuqi Road (Middle), Jingan District, Shanghai (China)
  • 2. Department of Radiology, Fujian Medical University Union Hospital, 29 Xinquan Road, Gulou District, Fuzhou, Fujian (China)
  • 3. Department of Radiology, Fujian Cancer Hospital & Fujian Medical University Cancer Hospital, 240 Fuma Road, Jinan District, Fuzhou, Fujian (China)
  • 4. Department of Pathology, Fujian Medical University Union Hospital, 29 Xinquan Road, Gulou District, Fuzhou, Fujian (China)
  • 5. Department of Management Science, University of Miami, Coral Gables, FL (United States)

Description

Highlights: • DWI-derived parameters from different models can help to grade meningiomas. • D and DDC are superior to f in distinguishing low-grade from high-grade meningiomas. • D derived from BEM is the strongest independent factor for predicting the grade of meningiomas. -- Abstract: To prospectively evaluate and compare the potential of various diffusion metrics obtained from mono-exponential model (MEM), bi-exponential model (BEM), and stretched exponential model (SEM)-based diffusion-weighted imaging (DWI) in the grading of meningiomas.

Additional details

Identifiers

DOI
10.1016/j.crad.2019.04.007;
PII
S0009926019301941;

Publishing Information

Journal Title
Clinical Radiology
Journal Volume
74
Journal Issue
8
Journal Page Range
p. 651.e15-651.e23
ISSN
0009-9260
CODEN
CLRAAG

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
55056858
Subject category
S62: RADIOLOGY AND NUCLEAR MEDICINE;
Descriptors DEI
METRICS; NMR IMAGING; SCANNING ELECTRON MICROSCOPY; WEIGHT
Descriptors DEC
DIAGNOSTIC TECHNIQUES; ELECTRON MICROSCOPY; MICROSCOPY

Optional Information

Copyright
Copyright (c) 2019 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.