Value of opposed-phase gradient-echo technique in distinguishing between benign and malignant vertebral lesions

2001 ◽  
Vol 12 (7) ◽  
pp. 1811-1818 ◽  
Author(s):  
Virna Zampa ◽  
Mirco Cosottini ◽  
Maria Michelassi ◽  
Simona Ortori ◽  
Luca Bruschini ◽  
...  
Keyword(s):  
Gradient Echo ◽  
Phase Gradient

Characterization of Adrenal Lesions With 1.5-T MRI: Preliminary Observations on Comparison of Three In-Phase and Out-of-Phase Gradient-Echo Techniques

2011 ◽  
Vol 197 (2) ◽  
pp. 415-423 ◽  
Author(s):  
Miguel Ramalho ◽  
Rafael O. P. de Campos ◽  
Vasco Heredia ◽  
Brian M. Dale ◽  
Penampai Tannaphai ◽  
...  
Keyword(s):  
Gradient Echo ◽  
Phase Gradient

Focal Sparing in Fatty Liver: Mimicking Hypervascular Tumor on Gadolinium-Enhanced Opposed-Phase Gradient-Echo Images

2001 ◽  
Vol 45 (6) ◽  
pp. 611
Author(s):  
Dal Mo Yang ◽  
Hak Soo Kim ◽  
Hyung Sik Kim ◽  
Wook Jin ◽  
Seung Whi Cho
Keyword(s):  
Fatty Liver ◽  
Gradient Echo ◽  
Phase Gradient ◽  
Hypervascular Tumor

MR Imaging of Bone Metastases and Choice of Sequence: Spin Echo, In-Phase Gradient Echo, Diffusion, and Contrast Medium

2009 ◽  
Vol 13 (02) ◽  
pp. 097-103 ◽  
Author(s):  
Daniel Vanel ◽  
Roberto Casadei ◽  
Marco Alberghini ◽  
Manel Razgallah ◽  
Maurizio Busacca ◽  
...  
Keyword(s):  
Mr Imaging ◽  
Bone Metastases ◽  
Contrast Medium ◽  
Spin Echo ◽  
Gradient Echo ◽  
Phase Gradient

Lipid in renal clear cell carcinoma: detection on opposed-phase gradient-echo MR images.

Radiology ◽  
1997 ◽  
Vol 205 (1) ◽  
pp. 103-107 ◽  
Author(s):  
E K Outwater ◽  
M Bhatia ◽  
E S Siegelman ◽  
M A Burke ◽  
D G Mitchell
Keyword(s):  
Cell Carcinoma ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Renal Clear Cell Carcinoma ◽  
Gradient Echo ◽  
Mr Images ◽  
Phase Gradient

Peritumoral spared area in fatty liver: correlation between opposed-phase gradient-echo MR imaging and CT arteriography

2001 ◽  
Vol 26 (4) ◽  
pp. 384-389 ◽  
Author(s):  
T. Gabata ◽  
M. Kadoya ◽  
O. Matsui ◽  
K. Ueda ◽  
Y. Kawamori ◽  
...  
Keyword(s):  
Mr Imaging ◽  
Fatty Liver ◽  
Gradient Echo ◽  
Phase Gradient

scholarly journals Diagnostic accuracy of signal loss in in-phase gradient-echo images for differentiation between small renal cell carcinoma and lipid-poor angiomyolipomas

2020 ◽  
Vol 93 (1108) ◽  
pp. 20190975
Author(s):  
Francisco V.A. Lima ◽  
Jorge Elias ◽  
Fernando Chahud ◽  
Rodolfo B. Reis ◽  
Valdair F. Muglia
Keyword(s):  
Diagnostic Accuracy ◽  
Predictive Value ◽  
Renal Cell ◽  
Signal Loss ◽  
Gradient Echo ◽  
Renal Masses ◽  
Phase Gradient ◽  
Subjective Analysis ◽  
Intensity Index ◽  
Low Sensitivity

Objectives: To assess the diagnostic accuracy of signal loss on in-phase (IP) gradient-echo (GRE) images for differentiation between renal cell carcinomas (RCCs) and lipid-poor angiomyolipomas (lpAMLs). Methods: We retrospectively searched our institutional database for histologically proven small RCCs (<5.0 cm) and AMLs without visible macroscopic fat (lpAMLs). Two experienced radiologists assessed MRIs qualitatively, to depict signal loss foci on IP GRE images. A third radiologist drew regions of interest (ROIs) on the same lesions, on IP and out-of-phase (OP) images to calculate the ratio of signal loss. Diagnostic accuracy parameters were calculated for both techniques and the inter-reader agreement for the qualitative analysis was evaluated using the κ test. Results: 15 (38.4%) RCCs lost their signal on IP images, with a sensitivity of 38.5% (95% CI = 23.4–55.4), a specificity of 100% (71.1–100), a positive predictive value (PPV) of 100% (73.4–100), a negative predictive value (NPV) of 31.4% (26.3–37.0), and an overall accuracy of 52% (37.4–66.3%). In terms of the quantitative analysis, the signal intensity index (SII= [(SIIP – SIOP) / SIOP] x 100) for RCCs was −0.132 ± 0.05, while for AMLs it was −0.031 ± 0.02, p = 0.26. The AUC was 0.414 ± −0.09 (0.237–0.592). Using 19% of signal loss as the threshold, sensitivity was 16% and specificity was 100%. The κappa value for subjective analysis was 0.63. Conclusion: Signal loss in “IP” images, assessed subjectively, was highly specific for distinction between RCCs and lpAMLs, although with low sensitivity. The findings can be used to improve the preoperative diagnostic accuracy of MRI for renal masses. Advances in knowledge: Signal loss on “IP” GRE images is a reliable sign for differentiation between RCC and lpAMLs.

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