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Combination of MR-T2 BLADE and Diffusion Weighted Imaging in Differentiating Focal Organizing Pneumonia from Peripheral Lung Carcinoma / 中国医学影像学杂志
Chinese Journal of Medical Imaging ; (12): 1282-1287, 2023.
Article in Zh | WPRIM | ID: wpr-1026331
Responsible library: WPRO
ABSTRACT
Purpose To evaluate the efficacy of T2-weighted imaging combined with diffusion weighted imaging in differential diagnosis of peripheral lung cancer(PLC)and focal organizational pneumonia(FOP).Materials and Methods A total of 36 patients with FOP and PLC diagnosed pathologically in the Affiliated Hospital of Shaanxi University of Chinese Medicine from November 2016 to December 2021 were retrospectively included.Two experienced radiologists independently read MR Images,and measured T2 contrast ratio(T2CR)and apparent diffusion coefficient(ADC)respectively.The T2CR and ADC values of the two groups were compared,and the diagnostic efficacy of MR-T2WI and diffusion weighted imaging was evaluated using the receiver operating characteristic curve.Results Two radiologists demonstrated good inter-observer agreement for T2CR and ADC values(ICC values of 0.951 and 0.955,respectively).The FOP group exhibited significantly higher T2CR and ADC values compared to the PLC group(t=3.920 and 5.819,both P<0.001),with threshold values of 2.29 for T2CR and 1 048×10-6 mm2/s for ADC being identified.ADC values accurately diagnosed FOP in 33 cases and PLC in 28 cases,while T2CR correctly diagnosed FOP in 20 cases and PLC in 33 cases.Combining both T2CR and ADC values resulted in accurate diagnoses of FOP in 29 cases and PLC in 33 cases.The diagnostic accuracy and area under the curve were improved by combining ADC and T2CR values compared with using them alone(accuracy:86.1%vs.84.7%,73.6%;AUC:0.924 vs.0.879,0.740;Z=2.208,P<0.05).Conclusion The combination of T2CR and ADC values aids in distinguishing FOP from PLC,exhibiting a higher diagnostic efficiency compared to their individual use.
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Full text: 1 Index: WPRIM Language: Zh Journal: Chinese Journal of Medical Imaging Year: 2023 Type: Article
Full text: 1 Index: WPRIM Language: Zh Journal: Chinese Journal of Medical Imaging Year: 2023 Type: Article