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MR conventional sagittal-axial plane and coronal iterative decomposition of water and fat with echo asymmetry and least-squares estimation technique in diagnosis of extraforaminal lumbar disc herniation / 中国医学影像技术
Chinese Journal of Medical Imaging Technology ; (12): 288-292, 2018.
Article in Chinese | WPRIM | ID: wpr-706226
ABSTRACT
Objective To compare the diagnostic value of MR conventional sagittal-axial plane and coronal iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) technique in diagnosis of extraforaminal lumbar disc herniation (ELDH).Methods Totally 32 patients with ELDH confirmed by surgery underwent preoperative MR sagittal-axial plane and coronal IDEAL scanning.Disc herniation,nerve involvement,nerve angle,nerve deep impression,nerve thinning or truncation,nerve adhesion unsmooth and nerve swelling were analyzed between the two methods.Results Disc herniation,nerve involvement and number of reduction or disappearance of surrounding fat had no statistically significant differences between the two methods (all P>0.05),while nerve angle,nerve deep impression,nerve thinning or truncation,nerve adhesion unsmooth and nerve swelling were significantly different between the two methods (all P<0.05).Surgical operation confirmed that 32 patients with nerve compression were consistent with findings by IDEAL.Conclusion MR sagittal-axial plane and coronal IDEAL both can be used to diagnose ELDH,but their display ability of nerve compression is different.Coronal IDEAL is superior to conventional sagittal-axial plane and is an effective imaging method,being able to display nerve compression more intuitively,clearly and comprehensively.

Full text: Available Index: WPRIM (Western Pacific) Type of study: Diagnostic study Language: Chinese Journal: Chinese Journal of Medical Imaging Technology Year: 2018 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Type of study: Diagnostic study Language: Chinese Journal: Chinese Journal of Medical Imaging Technology Year: 2018 Type: Article