OBJECTIVE: The purpose of this study was to determine whether histogram analysis of apparent diffusion coefficient (ADC) values from diffusion-weighted MRI can be used to differentiate cervical tumors according to their histologic characteristics. SUBJECTS AND METHODS: Sixty patients with International Federation of Gynecology stage I cervical cancer underwent MRI at 1.5 T with a 37-mm-diameter endovaginal coil. T2-weighted images (TR/TE, 2000-2368/90) followed by diffusion-weighted images (TR/TE, 2500/69; b values, 0, 100, 300, 500, and 800 s/mm(2)) were acquired. An expert observer drew regions of interest around a histologically confirmed tumor on ADC maps by referring to the T2-weighted images. Pixel-by-pixel ADCs were calculated with a monoexponential fit of data from b values of 100-800 s/mm(2), and ADC histograms were obtained from the entire tumor volume. An independent samples Student t test was used to compare differences in ADC percentile values, skew, and kurtosis between squamous cell carcinoma and adenocarcinoma, well or moderately differentiated and poorly differentiated tumors, and absence and presence of lymphovascular space invasion. RESULTS: There was no statistically significant difference in ADC percentiles between squamous cell carcinoma and adenocarcinoma, but the median was significantly higher in well or moderately differentiated tumors (50th percentile, 1113 ± 177 × 10(-6) mm(2)/s) compared with poorly differentiated tumors (50th percentile, 996 ± 184 × 10(-6) mm(2)/s) (p = 0.049). Histogram skew was significantly less positive for adenocarcinoma compared with squamous cell carcinoma (p = 0.016) but did not differ between tumor grades. There was no significant difference between any parameter with regard to lymphovascular space invasion. CONCLUSION: Median ADC is lower in poorly compared with well or moderately differentiated tumors, while lower histogram-positive skew in adenocarcinoma compared with squamous cell carcinoma is likely to reflect the glandular content of adenocarcinoma.
OBJECTIVE: The purpose of this study was to determine whether histogram analysis of apparent diffusion coefficient (ADC) values from diffusion-weighted MRI can be used to differentiate cervical tumors according to their histologic characteristics. SUBJECTS AND METHODS: Sixty patients with International Federation of Gynecology stage I cervical cancer underwent MRI at 1.5 T with a 37-mm-diameter endovaginal coil. T2-weighted images (TR/TE, 2000-2368/90) followed by diffusion-weighted images (TR/TE, 2500/69; b values, 0, 100, 300, 500, and 800 s/mm(2)) were acquired. An expert observer drew regions of interest around a histologically confirmed tumor on ADC maps by referring to the T2-weighted images. Pixel-by-pixel ADCs were calculated with a monoexponential fit of data from b values of 100-800 s/mm(2), and ADC histograms were obtained from the entire tumor volume. An independent samples Student t test was used to compare differences in ADC percentile values, skew, and kurtosis between squamous cell carcinoma and adenocarcinoma, well or moderately differentiated and poorly differentiated tumors, and absence and presence of lymphovascular space invasion. RESULTS: There was no statistically significant difference in ADC percentiles between squamous cell carcinoma and adenocarcinoma, but the median was significantly higher in well or moderately differentiated tumors (50th percentile, 1113 ± 177 × 10(-6) mm(2)/s) compared with poorly differentiated tumors (50th percentile, 996 ± 184 × 10(-6) mm(2)/s) (p = 0.049). Histogram skew was significantly less positive for adenocarcinoma compared with squamous cell carcinoma (p = 0.016) but did not differ between tumor grades. There was no significant difference between any parameter with regard to lymphovascular space invasion. CONCLUSION: Median ADC is lower in poorly compared with well or moderately differentiated tumors, while lower histogram-positive skew in adenocarcinoma compared with squamous cell carcinoma is likely to reflect the glandular content of adenocarcinoma.
Authors: Andrew B Rosenkrantz; Michael J Triolo; Jonathan Melamed; Henry Rusinek; Samir S Taneja; Fang-Ming Deng Journal: J Magn Reson Imaging Date: 2014-02-25 Impact factor: 4.813
Authors: Stephanie Nougaret; Caroline Reinhold; Shaza S Alsharif; Helen Addley; Jocelyne Arceneau; Nicolas Molinari; Boris Guiu; Evis Sala Journal: Radiology Date: 2015-04-30 Impact factor: 11.105