In vivo detection of choline in ovarian tumors using 3D magnetic resonance spectroscopy.

OBJECTIVES: To assess the clinical feasibility of 3-dimensional (3D) proton magnetic resonance spectroscopy (MRS) of ovarian masses at 1.5 T. MATERIALS AND METHODS: We prospectively evaluated 16 patients with 23 ovarian masses using contrast-enhanced magnetic resonance imaging and 3D chemical shift imaging MRS (time of reception/time of echo = 700/135 ms, number of excitations = 6, interpolated voxel = 5 × 5 × 5 mm(3), water and fat suppression). Spectral editing consisted of water reference, filtering, zero-filling, Fourier transformation, frequency shift, automatic baseline and phase correction, and curve fitting. The volume of interest was placed to encompass both solid and cystic tumor components as well as apparently healthy pelvic tissues. The presence of a choline peak at 3.14 to 3.34 ppm was considered as a marker of malignancy. All patients underwent surgery and histopathological evaluation. RESULTS: Of 23 masses, 19 were malignant and the remaining 4 benign lesions were a fibrothecoma, an endometriosis, a cyst, and a cystadenofibroma. A choline peak was detected in 17/19 malignant tumors (sensitivity 89%), absent in 2 G1 tumors. It was visible in 16 solid components of 19 malignant tumors (in one of them, a choline peak was detected only in the cystic component, in 6 in both solid and cystic components). The choline peak was absent in 20/21 apparently healthy pelvic tissues, with a very low choline peak being detected in one intraperitoneal fluid collection with malignant cells at cytologic analysis; 3/4 benign tumors showed a choline peak (overall specificity 21/25 = 84%). A significant difference between the mean choline peak integral detected within the solid component and that within the cystic component was observed (P = 0.002). No correlation between the choline peak integral and the tumor size was found (r = 0.120, P = 0.615). CONCLUSIONS: 3D MRS of ovarian masses is clinically feasible at 1.5 T. This opens new research strategies for early diagnosis of ovarian cancer.