Does Quantification of Diffusion (ADC value) Aid In Identifying Malignant Vertebral Lesions? A Cross Sectional Observational Study.
International journal of scientific research(2021)
摘要
Background: Characterization of vertebral pathologies as benign or malignant is a frequent dilemma that often requires invasive procedures for diagnosis. Today, imaging is sufcient for diagnosis of most benign vertebral pathologies with further conrmation on response to therapy. With better understanding of diffusion characteristics of tissues, attempt is being made to assess various imaging characteristics to make a denite diagnosis of malignant lesions as well. In this study we quantied apparent diffusion coefcient (ADC) of lesions in an effort to determine whether ADC values are different for benign or malignant vertebral body lesions. Consecutive patients that reported to the department of Radiodiagnosis, during 1st November 2017 to 31st March 2019, were included in the study. In this cross sectional observational study, for 32, that is, 22 benign and ten malignant vertebral lesions, diffusion weighted (DW) MRI sequence was done and ADC values were recorded. Conrmation was done with post treatment follow up or wherever feasible, tissue diagnosis. All malignant cases had histopathology conrmation from the site of primary lesion. Quantitative variables using independent t-test were used for comparison of ADC values between two groups. Results: The difference in mean ADC values of benign and malignant lesions were statistically signicant (P<0.0001). The optimal cutoff of ADC -3 2 value for differentiating benign from malignant vertebral body lesion was 0.950 x 10 mm /s with sensitivity of 80% and specicity of 95.45%. Conclusion:In all cases, DWI/ ADC, along with routine MR sequences, were able to characterize the lesion either as benign or malignant except in two cases of tubercular infection of spine and one each of spindle cell sarcoma & metastasis from cancer lung where there was overlap of ADC values.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要