Ex-vivo human pancreatic specimen evaluation by 7 Tesla MRI: a prospective radiological-pathological correlation study

La radiologia medica(2022)

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摘要
Purpose To compare the characteristics detected by 7Tesla (7 T) MR and the histological composition of ex-vivo specimens from lesions diagnosed at preoperative CT scan as Pancreatic Ductal Adenocarcinoma (PDAC). Materials and methods Ten pancreatic specimens were examined. The 7 T imaging protocol included both morphologic and quantitative sequences; the latter was acquired by conventional methods and a novel multiparametric method, the magnetic resonance fingerprinting (MRF) sequence. Two radiologists reviewed the images to: (1) evaluate the quality of the morphological and quantitative sequences by assigning an “ image consistency score” on a 4-point scale; (2) identify the lesion, recording its characteristics; (3) perform the quantitative analysis on “target lesion” and “non target tissue”. Finally, the specimen was analysed by two pathologists. Results Seven out of 10 lesions were PDAC, 2/10 were biliary carcinomas, whereas one lesion was an ampullary adenocarcinoma. The quality of the morphological sequences was judged “excellent”. The “ image consistency score” for the conventional quantitative sequences and MRF were 2.8 ± 0.42 and 2.9 ± 0.57; the “overall MR examination score” was 3.5 ± 0.53. A statistical correlation was found between the relaxation time values of conventional and MRF T1-weighted sequences ( p < 0.0001), as well as between conventional and MRF fat- and water-fraction maps ( p < 0.05). The “target lesion” and “non target tissue” relaxation time values were statistically different according to conventional T1-, T2-weighted, and MRF T1-weighted sequences. Conclusions Conventional T1-, T2-weighted sequences and MRF derived relaxometries may be useful in differentiating between tumour and non-target pancreatic tissue. Moreover, the MRF sequence can be used to obtain reliable relaxation time data.
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关键词
Pancreatic ductal carcinoma,Ultra-high field MRI,Multiparametric magnetic resonance imaging,MR fingerprinting,Correlation of data
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