OBJECTIVE: The purpose of this study was to determine the value of three MR pulse sequences for the detection of tumors and abnormal lymph nodes in the head and neck. This was accomplished by quantifying differences in contrast between tumor, lymph node, and respective adjacent tissue on contrast-enhanced fat-suppressed T1-weighted MR images, conventional spin-echo T2-weighted images, and fast spin-echo fat-suppressed T2-weighted images in a group of patients with head and neck tumors. SUBJECTS AND METHODS: Two groups of patients with head and neck tumors were studied. In the first group (16 patients), contrast-enhanced fat-suppressed T1-weighted images were compared with conventional spin-echo T2-weighted images. In the second group (21 patients), contrast-enhanced fat-suppressed T1-weighted images were compared with fast spin-echo fat-suppressed T2-weighted images. The detectability of tumor and abnormal lymph nodes was measured by calculating the contrast-to-noise ratio. RESULTS: The fat-suppressed T1-weighted images had significantly higher (p < or = .02) contrast-to-noise ratios for both the primary tumor and lymph nodes than either conventional or fast spin-echo T2-weighted images did. However, subjective evaluation of the contrast-to-noise ratios proved satisfactory for tumor detection with all three imaging sequences (contrast-enhanced fat-suppressed T1-weighted, fast spin-echo fat-suppressed T2-weighted, and conventional T2-weighted). CONCLUSION: Our results show that fat-suppressed contrast-enhanced T1-weighted images provide the highest contrast-to-noise ratio for head and neck tumors and abnormal lymph nodes. However, head and neck tumors encompass a broad range of neoplasms that are distributed in a complicated anatomic area. Therefore, in some patients, a combination of contrast-enhanced fat-suppressed T1- and T2-weighted images, preferably fast spin-echo fat-suppressed images, is useful for detection of these tumors and nodal metastases.
OBJECTIVE: The purpose of this study was to determine the value of three MR pulse sequences for the detection of tumors and abnormal lymph nodes in the head and neck. This was accomplished by quantifying differences in contrast between tumor, lymph node, and respective adjacent tissue on contrast-enhanced fat-suppressed T1-weighted MR images, conventional spin-echo T2-weighted images, and fast spin-echo fat-suppressed T2-weighted images in a group of patients with head and neck tumors. SUBJECTS AND METHODS: Two groups of patients with head and neck tumors were studied. In the first group (16 patients), contrast-enhanced fat-suppressed T1-weighted images were compared with conventional spin-echo T2-weighted images. In the second group (21 patients), contrast-enhanced fat-suppressed T1-weighted images were compared with fast spin-echo fat-suppressed T2-weighted images. The detectability of tumor and abnormal lymph nodes was measured by calculating the contrast-to-noise ratio. RESULTS: The fat-suppressed T1-weighted images had significantly higher (p < or = .02) contrast-to-noise ratios for both the primary tumor and lymph nodes than either conventional or fast spin-echo T2-weighted images did. However, subjective evaluation of the contrast-to-noise ratios proved satisfactory for tumor detection with all three imaging sequences (contrast-enhanced fat-suppressed T1-weighted, fast spin-echo fat-suppressed T2-weighted, and conventional T2-weighted). CONCLUSION: Our results show that fat-suppressed contrast-enhanced T1-weighted images provide the highest contrast-to-noise ratio for head and neck tumors and abnormal lymph nodes. However, head and neck tumors encompass a broad range of neoplasms that are distributed in a complicated anatomic area. Therefore, in some patients, a combination of contrast-enhanced fat-suppressed T1- and T2-weighted images, preferably fast spin-echo fat-suppressed images, is useful for detection of these tumors and nodal metastases.
Authors: S F Nemec; C R Krestan; I M Noebauer-Huhmann; M Formanek; J Frühwald; P Peloschek; F Kainberger; C Czerny Journal: Radiologe Date: 2009-01 Impact factor: 0.635
Authors: René van den Berg; Berit M Verbist; Bart J A Mertens; Andel G L van der Mey; Mark A van Buchem Journal: AJNR Am J Neuroradiol Date: 2004-05 Impact factor: 3.825
Authors: Gregorio Chazenbalk; Prapti Singh; Dana Irge; Amy Shah; David H Abbott; Daniel A Dumesic Journal: Steroids Date: 2013-05-23 Impact factor: 2.668
Authors: F Neves; L Huwart; G Jourdan; D Reizine; P Herman; E Vicaut; J P Guichard Journal: AJNR Am J Neuroradiol Date: 2008-03-13 Impact factor: 3.825
Authors: N Pyatigorskaya; R De Laroche; G Bera; A Giron; C Bertolus; G Herve; E Chambenois; S Bergeret; D Dormont; M Amor-Sahli; A Kas Journal: AJNR Am J Neuroradiol Date: 2020-09-24 Impact factor: 4.966