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

Radiol Med. 2022 Aug 19. doi: 10.1007/s11547-022-01533-1. Online ahead of print.


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.

PMID:35984559 | DOI:10.1007/s11547-022-01533-1

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