ABSTRACT
PURPOSE: To evaluate sensitivity and specificity of proton magnetic resonance (MR) spectroscopy of the prostate with external surface coil elements at 3 T for differentiation of cancer from healthy tissue within an acceptable measurement time, by using histopathologic findings as the reference standard. MATERIALS AND METHODS: The study was approved by the institutional review board; informed consent was obtained. Forty-five men (age range, 51-70 years) underwent 3-T MR imaging with external radiofrequency surface coils for signal reception. MR spectroscopy was performed with acquisition-weighted three-dimensional water- and lipid-suppressed point-resolved spectroscopy pulse sequence. Voxels were classified into healthy peripheral zone, central gland, and periurethral zone and cancer tissue. Cancer voxels were classified according to cancer size and certainty in matching histopathologic findings with MR images. After visual inspection of automated fitting of classified voxels, the choline plus creatine-to-citrate (Cho + Cr/Cit) ratio was calculated for all tissues. Area under the receiver operating characteristic curves (A(z)) values were used to assess accuracy of discrimination of cancer from healthy tissues. P < .05 indicated a significant difference. RESULTS: After exclusion of four patients with no voxels that passed visual inspection of the automated fit, a median of 82% of the classified voxels per patient was used in the analysis. Mean Cho + Cr/Cit ratios for healthy tissues were 0.22 +/- 0.12 (standard deviation) for peripheral zone, 0.34 +/- 0.14 for central gland, and 0.36 +/- 0.20 for periurethral area; all were significantly different from that of cancer (P < .001). A(z) for discrimination of probable and definite cancer tissue from healthy tissue for the peripheral zone (0.84) was significantly higher than that for the central gland (0.69) (P < .05). CONCLUSION: Three-dimensional proton MR spectroscopy of the prostate, with a combination of only external radiofrequency surface coils at 3 T, can be used to discriminate cancer from healthy tissue.
